People with diabetic foot frequently exhibit poor gait and balance. However, there is no review to inform digital biomarkers of poor gait and balance related to diabetic foot, measurable by wearables outside traditional gait laboratories. Such information could assist in designing remote patient monitoring platform to track changes in gait and balance dysfunction among people with diabetic foot for timely referral and intervention. Accordingly, we conducted a web-based review using PubMed. Our search was limited to human subjects and English-written papers published in peer-reviewed journals. We identified 20 papers in this review. We found preliminary evidence of digital biomarkers of gait and balance dysfunction in people with diabetic foot, measured by wearables, such as slow gait speed, large gait variability, unstable gait initiation, and large body sway. However, due to heterogeneities in included papers in terms of study design, movement tasks, and small sample size, more studies are recommended to confirm this preliminary evidence. Additionally, based on our review, we recommend establishing appropriate strategies to successfully implement wearable-based assessment into clinical practice for diabetic foot care.

Abstract: The objective of Peter Chew Triangle Diagram is to clearly illustrate the topic solution of triangle and provide a complete design for the knowledge of AI age. Peter Chew's triangle diagram will suggest a better single rule that allows us to solve any problem of topic solution of triangle simple , directly and more accurately. There are two important rules for solving the topic solution of triangle today [1,2], namely the sine rule and the cosine rule. The sine rule is used to find a non-included angle when are given two sides and a non-included angle or the opposite side angle given when are given two angles and one side. The cosine rule normally is used to find the included angle when are given three sides or the third side when are given two sides and the included angle. Peter Chew Method[3] allow us to find the third side simple and directly when given two sides and a non-included angle. Peter Chew rule [4] allow us to find a non included angle simple, directly and more accurately when given 2 sides and an included angle. Aply Peter Chew Triangle Diagram to Education 4.0 Calculator , Peter Chew Triangle Diagram Calculator allows the Calculator to solve any problems in the topic solution of triangle simple, directly and more accurate. This can be effective in increasing students' interest in using technology while learning mathematics and will help in the learning of mathematics, especially when similar covid-19 issues arise in the future.

In this paper is discussed sediment transport as a mechanical process that characterises a natural stream or channel flow regime. The objective of experimental work presented in this paper is to recall and to give another prospect of well-known Meyer-Peter and Müller approach for estimation of Shield’s number (θ_c,θ) in laboratory conditions, and calibration of dimensionless MPM number (A). For this purpose two different experiments are conducted, during the first experiment water amount flushed on the flume and bed slope was changed simultaneously until equilibrium state is achieved, meanwhile is estimated the critical Shield’s number (θ_c). While, during the second experiment, water amount was kept constant, only bed slope of flume was continuously tilted, meanwhile sediment, discharge and Shield’s number (θ) was determined for given hydraulic conditions. In addition calibration of dimensionless MPM number (A) was performed, where several iteration were considered until for (A=3.42), sediment discharge measured become almost equal with sediment discharge computed by using MPM formula. After these experiments, is concluded that MPM formula can be used also for other certain initial condition and similar procedure may be adopted to calibrate the dimensionless MPM number (A) .

Creating intelligent systems capable of recognizing emotions is a difficult task, especially when looking at emotions in animals. This paper describes the process of designing a “proof of concept” system to recognize emotions in horses. This system is formed by two elements, a detector and a model. The detector is a fast region-based convolutional neural network that detects horses in an image. The model is a convolutional neural network that predicts the emotions of those horses. These two elements were trained with multiple images of horses until they achieved high accuracy in their tasks. 400 images of horses were collected and labeled to train both the detector and the model while 80 were used to validate the system. Once the two components were validated, they were combined into a testable system that would detect equine emotions based on established behavioral ethograms indicating emotional affect through head, neck, ear, muzzle and eye position. The system showed an accuracy of between 69% and 74% on the validation set, demonstrating that it is possible to predict emotions in animals using autonomous intelligent systems. Such a system has multiple applications including further studies in the growing field of animal emotions as well as in the veterinary field to determine the physical welfare of horses or other livestock.

Forensic hospitals throughout the country house individuals with severe mental illness and history of criminal violations. Insomnia affects 67.4% of hospitalized patients with chronic neuropsychiatric disorders, indicating that these conditions may hijack human somnogenic pathways. Conversely, somnolence is a common adverse effect of many antipsychotic drugs, further highlighting a common etiopathogenesis. The role of dysfunctional mitochondria in psychopathology is well-established, however, the association of these organelles with sleep physiology is novel. Indeed, reducing neuronal oxidative stress by importing mitochondria from astrocytes, may be the purpose of human slumber. This model may explain mitochondrial dysfunction during anesthesia as well as in the rare genetic disease, fatal familial insomnia. In this narrative review, we focus on the salience network of the brain, a common denominator for insomnia, neuropsychiatric and neurodegenerative disorders. We also discuss mitochondria-protecting strategies, including membrane lipid replacement, natural and synthetic phenazine and phenothiazine derivatives.

This study provides a comprehensive comparison of the Peter Chew Sum method and Newton's Sum in Quadratic Root Function Computations. Both methods offer significant advancements by alleviating the need for memorization of multiple formulas. However, when confronted with higher-order quadratic root functions such as the calculation of power 33. Newton's Sum method proves cumbersome due to its requirement of all previous answers for final computation, leading to increased steps and error risks. In contrast, the Peter Chew Sum method simplifies the computational process by requiring only a few previous answers, resulting in a more straightforward series of operations. We contextualize our analysis within the historical progression of mathematical techniques, highlighting the transformative leap represented by the Peter Chew Sum method in quadratic root function computations. Peter Chew Sum addressing the limitations of Newton's Sum , especially concerning higher-order functions such as the calculation of power 256. Furthermore, study demonstrates that the innovative approach of the Peter Chew Sum method not only simplifies complex computations but also fosters enhanced conceptual understanding among students. In conclusion, study findings underscore the profound impact of the Peter Chew Sum method on quadratic root function computations.

As the coronavirus disease 2019 (COVID-19) continues to rage worldwide, the United States has become the most affected country with more than 34.1 million total confirmed cases up to June 1, 2021. In this work, we investigate correlations between online social media and Internet search for the COVID-19 pandemic among 50 U.S. states. By collecting the state-level daily trends through both Twitter and Google Trends, we observe a high but state-different lag correlation with the number of daily confirmed cases. We further find that the predictive accuracy measured by the correlation coefficient is positively correlated to a state’s demographic, air traffic volume and GDP development. Most importantly, we show that a state’s early infection rate is negatively correlated with the lag to the previous peak in Internet search and tweeting about COVID-19, indicating that earlier collective awareness on Twitter/Google correlates with lower infection rate. Lastly, we demonstrate that correlations between online social media and search trends are sensitive to time, mainly due to the attention shifting of the public.

Background: Sexual dysfunction is the most common side effect encountered by cervical cancer patients during and after treatment, and rehabilitation strategies are needed to improve their quality of life. A variety of rehabilitation strategies have been reported in previous studies, varying by country, race and even continent. However, the common rehabilitation strategies used by cervical cancer survivors in Tanzania and their outcomes are unknown. The study aimed to unfold sexual rehabilitation strategies and outcome practiced by cervical cancer survivors who experienced sexual dysfunction during and after treatment in North-western Tanzania. Methods: Descriptive qualitative study were employed. Phenomenology study design used with a sample of 7 participants and data corrected via in-depth interview guided by 11 questions. Audiotaped and transcribed to get main themes and sub themes through deductive analysis. Results: Most participants reported inability to achieve an orgasm and low libido and dyspareunia after treatment. Most participants were eagerly to have their sexual activity recovered. However, they were not familiar with any rehabilitation strategy after the experience of sexual dysfunction. Even though, some of the participants attempted various interventions, but all were unsatisfactory leading to a significant decline in sexual interest and activity. Conclusion: Cervical cancer survivors are not familiar with any sexual rehabilitation strategies. Health education concerning various sexual rehabilitation strategies should be provided to survivors during and even after treatment.

Metabolic flexibility is the ability of an organism to adapt its energy source based on nutrient availability and energy requirements. In humans, this ability has been linked to cardio-metabolic health and healthy aging. Genome-scale metabolic models have been employed to simulate metabolic flexibility by computing the Respiratory Quotient (RQ), which is defined as the ratio of carbon dioxide produced to oxygen consumed, and varies between values of 0.7 for pure fat metabolism and 1.0 for pure carbohydrate metabolism. While the nutritional determinants of metabolic flexibility are known, the role of low energy expenditure and sedentary behavior in the development of metabolic inflexibility is less studied. In this study we present a new description of metabolic flexibility in genome-scale metabolic models which accounts for energy expenditure, and we study the interactions between physical activity and nutrition in a set of patient-derived models of skeletal muscle metabolism in older adults. The simulations show that fuel choice is sensitive to ATP consumption rate in all models tested. The ability to adapt fuel utilization to energy demands is an intrinsic property of the metabolic network

Successful fertilization treatments targeted to improve stand productivity while reducing operational complexities and cost depend on a clear understanding of soil nutrient availability under varying environmental conditions. Soil nutrient data collected from 154 forest sites throughout the Inland Northwest, USA were analyzed to examine soil nutrient characteristics on different geologic soil parent materials and to rank soil fertility. Results show that soil parent material explains significant differences in soil nutrient availability. Soils developed from volcanic rocks have the highest CEC and are relatively high in P, K, S, Mg, Cu, Ca, and B, but generally poor in N. Forest soils developed from plutonic rocks exhibit the lowest CEC and are low in N, S, K, Mg, Cu, and Ca, but higher in P. Some soils located on mixed glacial till are low only in K, Cu, Mg, and Ca, but many glacial soils are relatively rich in other nutrients, albeit the second lowest CEC. Soils developed from metasedimentary and sedimentary rocks are among those with lowest soil nutrient availability for P and B. Sulfur was found to have the highest concentrations in metasedimentary influenced soils and the least in sedimentary derived soils. Our results should be useful in designing site-specific fertilizer and nutrient management prescriptions for forest stands growing on soils developed from these major geologies within the Inland Northwest region of the United States.

We present a case of a 47-year-old male who died unexpectedly from acute pulmonary hemorrhage 555 days after completing the BNT162b2 (Pfizer) COVID-19 vaccination primary series. Before death, he exhibited symptoms of a mild respiratory infection. Despite a healthy medical history and no medication use, the patient’s condition rapidly deteriorated and he experienced severe respiratory distress, followed by cardiopulmonary arrest with evidence of profuse pulmonary bleeding. Autopsy findings revealed massive lung congestion without embolism, normal heart size, moderate coronary atherosclerosis without myocardial infarction, and no evidence of other hemorrhagic events. The patient tested negative for COVID-19 and other respiratory pathogens at autopsy. Despite these findings, the medical examiner determined the cause of death was attributed to atherosclerotic and hypertensive cardiovascular disease, without considering the recent pulmonary hemorrhage and unremarkable medical history. Investigation into the vaccine batch indicated a higher-than-average number of serious adverse events, including fatalities. The patient's BNT162b2 batch was among the top 2.8% for reported deaths. Moreover, the autopsy failed to investigate potential contributions from the vaccine, such as the presence of the Spike protein or related antibodies. The evidence suggests that the pulmonary hemorrhage, exacerbated by a viral infection, was the immediate cause of death, with the COVID-19 vaccine potentially playing a role in the development of cardiopulmonary pathology and hemorrhage. We propose autopsy protocols for COVID-19 vaccine recipients to better investigate vaccine-related pathologies among those with one or more prior injections.

Spray penetration into citrus canopies is critical for adequate coverage and deposition to ensure effective pest control. However, mismatch of air assistance to target canopy characteristics can lead to unintended spray loss through over penetration. To evaluate the effect of air assistance on on-target deposition, two sprayers (surrogates for airflow rates) were used to apply a fluorescent tracer dye solution @ target concentration of 300 ppm to 16 medium foliage density tree blocks in a commercial mandarin orchard. The complete factorial experiment in three replications comprised two ground speeds (1.6 and 4.8 km/h), two disc-core nozzles (TeeJet® D3-25 and D6-45), and either one or two nozzle rows to obtain a wide range of application rates (496 to 9,719 L/ha). Dye deposition significantly decreased with canopy depth (p=<0.001) by nearly 7 times across the 3.4-m-wide canopies but was not significant over 1.2 to 2.2 m sampling height (p=0.867). Deposition obtained with the low airflow rate sprayer was significantly greater (p=<0.001) than that obtained with the high airflow rate sprayer over the dose range likely due to too much air pushing out spray droplets. This study underscores the importance of matching the air assistance of orchard sprayers to the target canopy.

Wheeled mobile robot dynamics and suitable controller design are challenging but rewarding fields of study. By understanding the dynamics of wheeled mobile robots, it could be possible to design suitable hybrid control schemes for wheeled mobile robots. Since hybrid control schemes involve combining individual control methods to create a more effective overall control strategy. This can be done in a variety of ways, such as using fuzzy linear quadratic Gaussian control. We were therefore inspired to create dynamic models and their controller designs for the wheeled mobile robot by examining the dynamics of the wheeled mobile robot. The novelty of the current paper is to hybridize the different control schemes for wheeled mobile robots in order to get better performance. Entire systems models were simulated in a MATLAB/SIMULINK environment. The results obtained for the settling time response by FLQG were 87.1% over LQG; this study compared the effectiveness of current and previous FLQG controllers in external disturbances and found peak amplitude improvements of 71.25%. Therefore, the proposed controller is suitable for use with the wheeled mobile robot.

This work examines dairy and sheep farmer attitudes toward antimicrobial use (AMU) in New Zealand. There is increasing public demand on livestock producers to reduce AMU in livestock. The demand stems from concerns about potential antimicrobial resistance (AMR) that could originate from food animals. There is limited practical data on farmer knowledge of AMU. An electronic survey was sent to dairy (n= 378) and sheep farmers (n= 551). Seventy-six dairy farmers (20%, n=76/378) returned the survey. Dairy farmers (69%) showed low levels of concern about antimicrobial resistance and awareness of the need to reduce AMU. Additionally, 76% of dairy farmers didn’t think it was possible to reduce AMU. Thirty-nine sheep farmers (7%, 39/551) returned the survey. 76% of sheep farmers were supportive of restricted use of AMU. The dairy and sheep farmers sourced most of the advice from veterinarians (>90%), the livestock industry (>80%) and their colleagues (>70%). This study shows that farmers showed varied concerns about AMR and AMU. Moreover, sheep farmers were more amenable to increased restriction on AMU than dairy farmers. This study suggests that knowledge gaps in farmers may best be filled by veterinarian input.

Temperature-index modeling is used to determine the magnitude of temperature depression on the Blanca Massif, Colorado, required to maintain steady-state mass balances of nine reconstructed glaciers at their extent during the Last Glacial Maximum (LGM). The mean temperature depression thus determined is ~8.6 +0.7/–0.9 °C where the uncertainties account for those inherent in the glacier reconstructions, in model parameters (e.g. melt factors), and possible modest changes in LGM precipitation. Associated equilibrium-line altitudes (ELAs) exhibit a statistically significant directional dependency being lower toward the north and east. Under the assumption that regional temperature change was uniform, required changes in precipitation vary systematically – also exhibiting a directional dependency coinciding with that in ELAs – and indicate increases (over modern) occurred on the eastern side of the massif while decreases occurred on the western side. This disparity represents a strengthening of a precipitation asymmetry, particularly winter precipitation, that exists today. The modern precipitation asymmetry may be a consequence of snow being blown over to the eastern side of the massif (advective transport) by southwesterly flow. Intensification of this flow during the LGM would have enhanced advection, and augmented snow accumulation on glaciers, thus explaining the lower ELAs and increased precipitation on that side of the massif.

Background: Since the onset of widespread COVID-19 vaccination campaigns, there have been concerns about serious cardiovascular adverse events, including myocarditis, myocardial infarction, and venous thromboembolisms, all of which can lead to cardiopulmonary arrest. This study aimed to estimate excess cardiopulmonary arrest mortality in King County, WA, and investigate any association with COVID-19 vaccination rates. Methods: Data was obtained from the annual King County, WA, EMS reports, the U.S. Census Bureau, and The Tennessean COVID-19 Vaccine Tracker. An exploratory data analysis was performed. Excess deaths were calculated using the 2015-2020 cardiopulmonary arrest mortality trend line. The relationship between excess cardiopulmonary arrest mortality and vaccination rates was analyzed using polynomial regression analysis. A quadratic regression model was used to generate expected population growth trends. The excess mortality model for King County was used to calculate yearly estimates for excess cardiopulmonary arrest fatalities in the USA. Results: Approximately 98% of the King County population received at least one dose of a COVID-19 vaccine by 2023. Our analysis revealed a 25.7% increase in total cardiopulmonary arrests and a 25.4% increase in cardiopulmonary arrest mortality from 2020 to 2023 in King County, WA. Excess cardiopulmonary arrest deaths were estimated to have increased by 1,236% from 2020 to 2023, rising from 11 excess deaths (95% CI: -12, 34) in 2020 to 147 excess deaths (95% CI: 123, 170) in 2023. A quadratic increase in excess cardiopulmonary arrest mortality was observed with higher COVID-19 vaccination rates. The general population of King County sharply declined by 0.94% (21,300) in 2021, deviating from the expected population size. Applying our model from these data to the entire United States yielded 49,240 excess fatal cardiopulmonary arrests from 2021-2023. Conclusions: We identified a very strong ecological and temporal association between excess cardiopulmonary arrest mortality and the COVID-19 vaccination campaign, which resulted in high vaccination rates. The biological plausibility of death from acute cardiac and pulmonary causes after COVID-19 vaccination has been previously demonstrated and is concerning given these real-world observations. Urgent further research is needed to determine if similar trends are observed in other regions with attention to risk mitigation for incident events and improved survival with resuscitation.

The wound management sector has attracted considerable attention due to the increasing challenge posed by antimicrobial resistance (AMR) and the specialized care required for chronic wounds. Effective wound care involves selecting appropriate dressings tailored with antimicrobial agents to prevent bacterial infection. Among various types of wound dressings, fibers and electrospun fibers, with their unique characteristics, have emerged as innovative new materials. However, the rise of AMR necessitates the exploration of new antimicrobial agents for wound dressings, particularly for addressing bacterial pathogens like methicillin-resistant Staphylococcus aureus (MRSA). Endophytic fungi, known for producing diverse bioactive compounds, including novel antibacterial agents, represent a promising source of such new agents. This study tested thirty-two endophytic fungi from thirteen distinct Australian native plants for their antibacterial activity against S. aureus, the most common wound-associated bacteria. Ethyl acetate (EtOAc) extracts from fungal culture filtrates exhibited inhibitory effects against both methicillin-sensitive S. aureus ATCC 25923 and MRSA strains M173525 and M180920. DNA sequence analysis was employed for fungal identification, with EtOAc extracts from the most active sample, EL 19 (Chaetomium globosum), selected for further bactericidal and antibiofilm testing against the chosen bacteria. Biofilm of S. aureus ATCC 25923 was reduced by 55% by EtOAc extracts of EL 19 at 1/2 × MIC. To demonstrate the potential application in wound dressing materials, three different concentrations of the extract were incorporated into Polycaprolactone fiber mats through electrospinning, with resultant inhibition of S. aureus ATCC 25923 being observed. This research underscores the potential of endophytic fungi from Australian plants as sources of substances effective against common wound pathogens. Further exploration of the responsible compounds and their mechanisms could facilitate the development of wound dressings effective against MRSA and innovative biofilm-resistant electrospun fibers, contributing to the global efforts to combat AMR.

Molnupiravir, a prodrug known for its broad antiviral activity, demonstrated efficacy in animal models of Covid-19, prompting clinical trials where initial results indicated a significant effect against the disease. However, subsequent clinical studies did not confirm these findings, leading to the rejection of molnupiravir for permanent market authorization in many countries. This report critically assessed 19 studies published in 17 reports that investigated the efficacy of molnupiravir in animal models of Covid-19 with the purpose of determining how well the design of these models informed human studies. We found that the administered doses of molnupiravir in most studies involving animal Covid-19 models were disproportionately higher than the dose rec-ommended for human use. Specifically, when adjusted for body surface area, half of the doses of molnupiravir used in the animal studies were more than twice as high as the human dose. Addi-tionally, the drug was frequently given prophylactically or shortly after SARS-CoV-2 inoculation in these models, in contrast to clinical trials where such timing is not consistently achieved. Furthermore, the recommended five-day treatment duration for humans was exceeded in several animal studies. Collectively, we suggest that these design elements in the reported animal studies contributed to a bias favoring molnupiravir, and thus inflated expectations for its efficacy against Covid-19. Addressing these elements may offer avenues to enhance the clinical efficacy of mol-nupiravir for treatment of Covid-19 that include dose increment, early treatment, and admin-istration by inhalation along with use of molnupiravir in antiviral combination therapy.

In this article, we present solutions for one of the oldest mathematical problems, the Collatz Conjecture, and provide a proof for the Riemann Hypothesis, utilizing a new number theory based on newly discovered number properties, which will also be presented in this paper. This is made possible through the Sophy-Peter mathematical framework, built upon this new number theory. The Collatz Conjecture will be disproven, but as an alternative, the Oscillating Theorem will be introduced, with its correctness proven within this article. Furthermore, we present the general version of the Riemann zeta function, developed based on the new number theory. The correctness of this function is verified by comparing it with existing results of the zeta function. Using this approach and the Sophy-Peter framework, we have successfully proven the Riemann Hypothesis, long considered a millennium problem. Moreover, since the general zeta function is proven, this implies the correctness of the new number theory and the Sophy-Peter framework.

Lutein, a plant-derived xanthophyl-carotenoid, is an exceptional antioxidant and anti-inflammatory constituent found in food. Elevated concentrations of lutein found in human blood and plasma, due to high dietary intake, are beneficial against eye disease and improve cardiometabolic health. Lutein plays an important protective role against the development of neurological disorders, including Alzheimer’s disease (AD), multiple sclerosis (MS) and Parkinson’s disease (PD). It has also been shown to be beneficial for liver, kidney and respiratory health. Lutein, acting as a very strong antioxidant, can alleviate oxidative stress and downgrade reactive oxygen species (ROS). Oxidative stress is one of the key pathogenic mechanisms in post-COVID and mRNA vaccine injury syndromes. Recent in silico studies suggest that lutein and other naturally derived antioxidants, by docking at the site where the SARS-CoV-2 spike protein (SP) binds to the angiotensin enzyme type 2 (ACE2) receptor, may neutralize the SP-ACE2 interactions. Lutein can be added to a detoxification regimen to aid in clearing Spike protein and relieving symptoms. In agreement with Hippocrates’ dictum to “Let food be thy medicine,” this review establishes dietary lutein as a valuable therapy in the treatment of post-COVID syndrome, mRNA vaccine injury syndromes, and a wide range of other chronic illnesses.

Buruli ulcer is a chronic ulcerative disease of skin and subcutaneous tissues caused by infection with Mycobacterium ulcerans. Although Australian possums are known to be susceptible to Buruli ulcer, many aspects of the disease in possums, including welfare impacts, remain largely unreported. Severe clinical Buruli ulcer was identified in four common ringtail possums (Pseudocheirus peregrinus) from Melbourne, Victoria. All four possums were euthanised due to welfare concerns and poor prognosis, based on the presence of deep ulcerative lesions to paws, some of which exposed carpal or tarsal bones. These lesions were considered likely to cause partial or complete loss of limb function, which would severely affect the welfare and survival of these wild arboreal animals. Histologically, there was severe ulcerative necrotising pyogranulomatous dermatitis, panniculitis, and myositis, with intralesional acid-fast bacteria. M. ulcerans was detected by real-time PCR in all swabs and biological tissues collected from all four cases. Buruli ulcer may be an important and under-recognised cause of poor possum welfare in endemic areas. In addition to severe cutaneous lesions, infection extends to underlying bones and joints, and the systemic distribution of M. ulcerans throughout all major tissues and internal organs, as observed in these four cases, may further impact the health and fitness of infected possums. Further research is needed to investigate the epidemiology, pathogenesis and impacts of Buruli ulcer in possums, and to inform the design of interventions that may protect the health and welfare of possums and other affected animal species.

Emerging autologous cellular therapies that utilize platelet-rich plasma (PRP) applications have the potential to play adjunctive roles in a variety of regenerative medicine treatment plans. There is a global unmet need for tissue repair strategies to treat musculoskeletal (MSK) and spinal disorders, osteoarthritis (OA), and patients with chronic complex and recalcitrant wounds. PRP therapy is based on the fact that platelet growth factors (PGFs) support the three phases of wound healing and repair cascade (inflammation, proliferation, remodeling). Many different PRP formulations have been evaluated, originating from human, in vitro, and animal studies. However, recommendations from in vitro and animal research often lead to different clinical outcomes because it is difficult to translate non-clinical study outcomes and methodology recommendations to human clinical treatment protocols. In recent years, progress has been made in understanding PRP technology and the concepts for bioformulation, and new research directives and new indications have been suggested. In this review, we will discuss recent developments regarding PRP preparation and composition regarding platelet dosing, leukocyte activities concerning innate and adaptive immunomodulation, serotonin (5-HT) effects and pain killing. Furthermore, we discuss PRP mechanisms related to inflammation and angiogenesis in tissue repair and regenerative processes. Lastly, we will review the effect of certain drugs on PRP activity, and the combination of PRP and rehabilitation protocols.

Aeromagnetic data coupled with Landsat ETM+ data and SRTM DEM have been processed in order to map regional hydrogeological structures in the basement complex region of Paiko, north-central Nigeria. Lineaments were extracted from derivative maps from aeromagnetic, Landsat ETM+ and SRTM DEM datasets. Ground geophysical investigation utilizing Radial Vertical Electrical Sounding (RVES) was established in nine transects comprising of four sounding stations which are oriented in three azimuths. Source Parameter Imaging (SPI) was employed to map the average depths structures from aeromagnetic dataset. Selected thematic layers which included lineaments density, lithologic, slope, drainage density and geomorphologic maps were integrated and modelled using ArcGIS to generate groundwater potential map of the area. Groundwater zones were classified into four categories: very good, good, moderate and poor according to their potential to yield sustainable water to drilled wells. Results from RVES survey reveal a close correlation to lineaments delineated from surface structural mapping and remotely sensed datasets. Hydrogeological significance of these orientations suggest that aeromagnetic data can be used to map relatively deep-seated fractures which are likely to be open groundwater conduits while remotely sensed lineaments and orientations delineated from the RVES survey may indicate areas of recharge. Regions with high lineament density have relatively better groundwater potential. This is attributable to areas having deep weathering profiles associated with intrusive bodies that have resulted in intense fracturing in the area. Drill depths in this area should target a minimum of 80 m to ensure sufficient and sustainable supplies to drilled wells. The outcome of this study should act as information framework that would guide the siting of productive water wells and while providing needed information for relevant agencies in need of data for the development of groundwater resources.

Exercising surds to represent figures is a common practice in scientific and Engineering fields, especially in scripts where calculators are banned or unapproachable. Peter Chew Theorem make result becomes simple when dealing with converting Quadratic Surds. The substance of the Peter Chew Theorem lies in enabling the forthcoming generation to simple break problems related to Quadratic Surds more effectively, easing a direct comparison with contemporary results. By employing the Peter Chew Theorem, one can streamline the tutoring and literacy of math, particularly concerning second- order direct equations with constant portions. This theorem's objective aligns with Albert Einstein's famed quotation Everything should be made as simple as possible, but not simpler.

Inteins, often referred to as protein introns, are highly mobile genetic elements that invade conserved genes throughout the tree of life. Inteins have been found to invade a wide variety of key genes within actinophages. While in the process of conducting a survey of these inteins in actinophages we discovered that one protein family of methylases contained a putative intein, and two other unique insertion elements. These methylases are known to occur commonly in phages as orphan methylases (possibly as a form of resistance to restriction-modification systems). We found that the methylase family is not conserved within phage clusters and has a disparate distribution across divergent phage groups. We determined that two of the three insertion elements have a patchy distribution within the methylase protein family. We also found that the third insertion element is likely a second homing endonuclease, and that all three elements (the intein, the homing endonuclease, and what we refer to as the ShiLan domain) all have different insertion sites that are conserved in the methylase gene family. Furthermore, we find strong evidence that both the intein and ShiLan domain are partaking in long distance horizontal gene transfer events between divergent methylases in disparate phage hosts within the already dispersed methylase distribution. The reticulate evolutionary history of methylases and their insertion elements reveals high rates of gene transfer and within-gene recombination in actinophages.

A number of Unidentified Aerial Phenomena (UAP) encountered by military, commercial, and civilian aircraft have been reported to be structured craft that exhibit 'impossible' flight characteristics. We consider a handful of well-documented encounters, including the 2004 encounters with the Nimitz Carrier Group off the coast of California, and estimate lower bounds on the accelerations exhibited by the craft during the observed maneuvers. Estimated accelerations range from almost 100g to 1000s of g's with no observed air disturbance, no sonic booms, and no evidence of excessive heat commensurate with even the minimal estimated energies. In accordance with observations, the estimated parameters describing the behavior of these craft are both anomalous and surprising. The extreme estimated flight characteristics reveal that these observations are either fabricated or seriously in error, or that these craft exhibit technology far more advanced than any known craft on Earth. In many cases, the number and quality of witnesses, the variety of roles they played in the encounters, and the equipment used to track and record the craft favor the latter hypothesis that these are indeed technologically advanced craft. The observed flight characteristics of these craft are consistent with the flight characteristics required for interstellar travel. That is, if these observed accelerations were sustainable in space, then these craft could easily reach relativistic speeds within a matter of minutes to hours and cover interstellar distances in a matter of days to weeks, proper time.

Analytical channel design tools have not advanced appreciably in the last decades, and continue to produce designs based upon a single representative discharge that may not lead to overall sediment continuity. It is beneficial for designers to know when a simplified design may be problematic and to efficiently produce alternative designs that approximate sediment balance over the entire flow regime. The Capacity/Supply Ratio (CSR) approach, an extension of the Copeland method of analytical channel design for sand channels, balances the sediment transport capacity of a design reach with the sediment supply of a stable upstream reach over the entire flow duration curve (FDC) rather than just a single discharge. Although CSR has a stronger physical basis than previous analytical channel design approaches, it has not been adopted in practice because it can be a cumbersome and time-consuming iterative analysis without the use of software. We investigate eighteen sand-bed rivers in a comparison of designs based on the CSR approach and five single-discharge metrics: the effective discharge (Qeff), the 1.5-year recurrence interval discharge (Q1.5), the bankfull discharge (Qbf), and the discharges associated with 50th (Qs50) and 75th (Qs75) percentiles of the cumulative sediment yield curve. To facilitate this analysis we developed a novel design tool using the Visual Basic for Applications (VBA) programming language in Excel® to produce stable channel slope-width combinations based on the CSR methodology for both sand- and gravel-bed streams. The CSR Stable Channel Design Tool’s (CSR Tool) code structure was based on Copeland’s method in SAM and HEC-RAS (Hydrologic Engineering Center’s River Analysis System) and was tested with a single discharge to verify outputs. The Qs50 and Qs75 single-discharge designs match the CSR output most closely, followed by the Qbf, Qeff, and Q1.5. The Qeff proved to be the most inconsistent design metric because it can be highly dependent on the binning procedure used in the effectiveness analysis. Furthermore, we found that the more rigorous physical basis of the CSR analysis is potentially most important in designing ‘labile’ channels with highly erodible substrate, high perennial flow ‘flashiness,’ low width-to-depth ratio, and high incoming sediment load. The CSR Tool provides a resource for river restoration practitioners to efficiently utilize in-depth design techniques that can promote sediment balance in dynamic fluvial systems.

Let Vn(d) denote the least number such that every collection of nd-cubes with total volume 1 in d-dimensional (Euclidean) space can be packed parallelly into some d-box of volume Vn(d). We show that V3(d)=r1−dd if d≥11 and V3(d)=1r+1rd+1r−rd+1 if 2≤d≤10, where r is the only solution of the equation 2(d−1)kd+dkd−1=1 on 22,1 and (k+1)d(1−k)d−1dk2+d+k−1=kddkd+1+dkd+kd+1 on 22,1, respectively. The maximum volume is achieved by hypercubes with edges x, y, z such that x=2rd+1−1/d, y=z=rx if d≥11, and x=rd+(1r−r)d+1−1/d, y=rx, z=(1r−r)x if 2≤d≤10. We also proved that only for dimensions less than 11 there are two different maximum packings, and for all dimensions greater than 10 the maximum packing has the two smallest cubes the same.

A time integration scheme based on semi-Lagrangian advection and Laplace transform adjustment has been implemented in a baroclinic primitive equation model. The semi-Lagrangian scheme makes it possible to use large time steps. However, errors arising from the semi-implicit scheme increase with the time step size. In contrast, the errors using the Laplace transform adjustment remain relatively small for typical time steps used with semi-Lagrangian advection. Numerical experiments confirm the superior performance of the Laplace transform scheme relative to the semi-implicit reference model. The algorithmic complexity of the scheme is comparable to the reference model, making it computationally competitive, and indicating its potential for integrating weather and climate prediction models.

Tree pruning is a management tool in agroforestry systems for reducing shade, enhancing nutrient cycling or providing fodder. However, little information is available on the effect of pruning management on plant growth, non-structural carbohydrate (NSC) levels in the roots and N2 fixation of Sesbania sesban. A glasshouse experiment was conducted to assess the effect of pruning frequency on biomass production, NSC levels and N2 fixation of Sesbania sesban. Treatments included pruning at (i) 3 months only, (ii) 3 and 6 months, and (iii) 3, 6 and 9 months, with each pruning removing shoot biomass above 50% of the initial height. Increased pruning frequency decreased above- and belowground dry matter (DM), and root NSC levels. The decrease in aboveground DM correlated with reduced levels of starch, sugar and total non-structural carbohydrates. Pruning more frequently significantly decreased nodulation, the percentage N derived from the atmosphere and N2 fixed. It could be concluded that more frequent prunings decreases biomass and NSC levels which could reduce the regeneration capacity of trees since they rely on NSCs to regrow. The suppressive effects of increased pruning frequency on N2 fixation could decrease the desirable benefits of legume trees on soil N fertility improvement.

This paper describes preliminary results of measuring the impact of human body movements on plants. In particular, we analyze the influence of eurythmic gestures of human actors on lettuce and beans. In an eight week experiment, we exposed rows of lettuce and beans to weekly eurythmic movements (similar to Qi Gong) of a eurythmist, while at the same time measuring changes in voltage between the roots and leaves of lettuce and beans using the plant spikerbox (https://backyardbrains.com/products/plantspikerbox). We compared this experimental group of vegetables with a control group of vegetables whose voltage differential was also measured while never being exposed to eurythmy. Using t-tests, we found a clear difference between the experimental and the control group which was also verified with a machine learning model. In other words, the vegetables showed a noticeably different pattern in electric potentials in response to eurythmic gestures.

The plant-microbe-soil nexus is critical in maintaining biogeochemical balance of the biosphere. However, soil loss and land degradation are occurring at alarmingly high rates, with soil loss exceeding soil formation rates. This necessitates evaluating marginal soils for their capacity to support and sustain plant growth. In a greenhouse study, we evaluated the capacity of marginal incipient basaltic parent material to support native plant growth, and the associated variation in soil microbial community dynamics. Three plant species, native to the Southwestern Arizona-Sonora region were tested with three soil treatments including basaltic parent material, parent material amended with 20% compost, and potting soil. The parent material with and without compost supported germination and growth of all the plant species, though germination was lower than the potting soil. A 16S rRNA amplicon sequencing approach showed Proteobacteria to be the most abundant phyla in both parent material and potting soil, followed by Actinobacteria. Microbial community composition had strong correlations with soil characteristics but not plant attributes within a given soil material. Predictive functional potential capacity of the communities revealed chemoheterotrophy as the most abundant metabolism within the parent material, while photoheterotrophy and anoxygenic photoautotrophy were prevalent in the potting soil. These results show that marginal incipient basaltic soil has the ability to support native plant species growth, and non-linear associations may exist between plant-marginal soil-microbial interactions.

Sustainable continuous cover forestry is defined and analyzed in several ways. The differential equation representing growth of the basal areas of individual trees, motivated by fundamental biological production theory by Lohmander (2017a), is analyzed and extended in different directions. From the solution of the differential equation, the basal area and the tree diameter are obtained as explicit functions of time. The diameter is a strictly increasing function of time. In the absence of competitors, the diameter increment is shown to be a strictly decreasing function of time. Hence, the diameter increment can also be interpreted as a strictly decreasing function of the diameter. Alternative forms of adjustment of the differential equation, with consideration of competition, are defined. If the competition is strong, with large trees in the vicinity of a particular tree, then the basal area increment, and the diameter increment, are reduced. The growth of a large tree is less sensitive than the growth of a small tree, to competition from other trees. Under strong competition, the basal area increment, and the diameter increment, are strictly concave functions of the size of the tree. The unique maximum of the diameter increment occurs at a higher diameter, if the competition increases. In dynamic equilibrium, the tree size frequency distribution is stationary. If natural tree mortality can be avoided via the harvest strategy, the tree size frequency distribution is a function of the size and competition dependent growth function, and the harvest strategy. Empirical tree size frequency data are used to simultaneously estimate parameters of a size and competition dependent growth function and the applied harvest strategy, via nonlinear optimization. The properties of the estimated growth function are consistent with the corresponding properties of the production theoretically motivated hypothetical function, and the properties of the estimated harvest strategy confirm the corresponding hypotheses. The R2 of the nonlinear regression exceeds 0.97. With access to an empirically estimated equilibrium tree size distribution, it is possible to: 1. Estimate size frequency relevant parameters of tree size and competition dependent growth functions for individual trees. 2. Estimate the applied harvest strategy. 3. Explain and reproduce the empirically estimated tree size equilibrium distribution.

Religious and spiritual struggles are typically assessed by self-report scales using closed-ended items, yet nascent research suggests that using open-ended items may complement and advance assessment. In the current study, undergraduate participants (N = 976) completed open-ended descriptions of their religious and spiritual struggles, the Religious and Spiritual Struggles Scale (RSS), and a standardized measures of religious belief salience. Qualitative coding showed that the themes emerging from open-ended descriptions generally fell within the broad domains of the RSS though some descriptions reflected more contextualized struggles. Scores derived from the open-ended responses to assess RSS domains achieved evidence of reliability as well as convergent and discriminant validity with the RSS . Correlations revealed a mix of similar and divergent associations between methods of assessing religious and spiritual struggles and religious belief salience. Open-ended descriptions of religious and spiritual struggles may yield reliable and valid information that is related to but distinct from assessments relying on closed-ended items.

This paper discusses the tectonics of the St. Peter and St. Paul Archipelago (SPSPA) in the Equato-rial Atlantic Ocean, based on the joint-system geometry which show a North-South shorten-ing/transpressional uplift tectonism, is active leading to exhumation of the sub-oceanic mantle. These islets are the summits of a sigmoidal submarine ridge formed by mantle ultramafic rocks. The ridge is crossed by the principal transform deformation zone of the northern transform fault of the St. Paul Multifault System. The South flank ridge exposes serpentinized mantle perido-tites, while the North flank exposes strongly deformed/fractured ultramylonites, recording duc-tile and brittle deformation at lithospheric conditions. The SPSPA show multiple joint systems cutting mylonitic foliation of the exposed rocks, forming three main families: high-angle paral-lel joints of tectonic origin, serpentinization-related joints with random direction and load-release low-angle parallel joints. The tectonic joints show an average direction of N31°E and N28°W, forming a conjugate system with a N1ºW compression axes, coherent with a trans-pressive stress field. Accordingly, the earthquakes focal mechanism close to the islets also shows N-S compression. The previously reported active uplift with an average rate of 1.5 mm/year and the directions of the joint system here reported agreeing with a present-day active N-S compres-sive field at a high angle with the direction of the transform fault.

Objectives Assess rates of adverse events (AE) after COVID-19 vaccines experienced by women of reproductive age, focusing on pregnancy and menstruation, using data collected by the US Centers for Disease Control and Prevention (CDC) Vaccine Adverse Events Reporting System (VAERS) database. Design Population-based retrospective cohort study. Setting US and global entries in US Centers for Disease Control and Prevention (CDC) Vaccine Adverse Events Reporting System (VAERS). Participants CDC VAERS entries from January 1, 1998 to June 30, 2022. Interventions None. Main Outcome Measures A proportional reporting ratio analysis is performed using data in the VAERS system comparing adverse events (AE) reported post-COVID-19 vaccines with that of post-Influenza vaccines. Results COVID-19 vaccines, when compared to the Influenza vaccines, are associated with a significant increase in AE with all proportional reporting ratios of > 2.0: menstrual abnormalities, miscarriage, fetal chromosomal abnormalities, fetal malformation, fetal cystic hygroma, fetal cardiac disorders, fetal arrhythmias, fetal cardiac arrest, fetal vascular malperfusion, fetal growth abnormalities, fetal abnormal surveillance, fetal placental thrombosis, low amniotic fluid, preeclampsia, premature delivery, preterm premature rupture of membrane, fetal death/stillbirth, and premature baby death (all p values were much smaller than 0.05). When normalized by time-available, doses-given, or persons-received, all COVID-19 vaccine AE far exceed the safety signal on all recognized thresholds. Conclusions Pregnancy complications and menstrual abnormalities are significantly more frequent following COVID-19 vaccinations than Influenza vaccinations. A worldwide moratorium on the use of COVID-19 vaccines in pregnancy is advised until randomized prospective trials document safety in pregnancy and long-term follow-up in offspring.

Differential RNA editing by adenosine deaminases that act on RNA (ADARs) has been implicat-ed in several neurological disorders, including Parkinson’s disease (PD). Here, we report results of an RNAi screen of genes differentially regulated in adr-2 mutants, normally encoding the only catalytically active ADAR in Caenorhabditis elegans, ADR-2. Subsequent analysis of candidate genes that alter the misfolding of human α-synuclein (α-syn) and dopaminergic neurodegenera-tion, two PD pathologies, reveal that reduced expression of xdh-1, the ortholog of human xanthine dehydrogenase (XDH), is protective against α-synuclein-induced dopaminergic neurodegenera-tion. Further RNAi experiments show that WHT-2, the worm ortholog of the human ABCG2 transporter and a predicted interactor of XDH-1, is the rate-limiting factor in the ADR-2, XDH-1, WHT-2 system for dopaminergic neuroprotection. Proteomic analysis indicates that the editing of one nucleotide in wht-2 RNA leads to the substitution of threonine with alanine at residue 124 in the WHT-2 protein, changing its structure. Thus, we propose a model where wht-2, is edited by ADR-2 which promotes optimal export of uric acid, a known substrate of WHT-2 and a product of XDH-1 activity. In the absence of editing, uric acid export is limited provoking a reduction in xdh-1 transcription to limit uric acid production and maintain cellular homeostasis. In turn, ele-vation of uric acid is protective against dopaminergic neuronal cell death. These data indicate that modifying specific targets of RNA editing may represent a promising therapeutic strategy for PD.

Recent advances in artificial intelligence combined with behavioral sciences have led to the development of cutting-edge tools for recognizing human emotions based on text, video, audio, and physiological data. However, these data sources are expensive, intrusive, and regulated, unlike plants which have been shown to be sensitive to human steps and sounds. A methodology is proposed to use plants as human emotion detectors. Electrical signals from plants are tracked and labeled based on video data. Labeled data are then used for classification. MLP, biLSTM, MFCC-CNN, MFCC-ResNet, and additionally, Random Forests, 1-Dimensional CNN, and biLSTM without windowing models are set using a grid search algorithm with cross-validation. Finally, best-parameterized models are trained and used with the test set for classification. The performance of this methodology is measured with a case study with 54 participants, who were watching an emotionally charged video, as ground truth their facial emotions were simultaneously measured using face emotion analysis. The Random Forest model shows the best performance, particularly in recognizing high-arousal emotions, achieving an overall weighted accuracy of 55.2% and demonstrating high weighted recall in emotions such as fear 61.0% and happiness 60.4%. The MFCC-ResNet model offers decently balanced results, with Accuracy(MFCC-ResNet)=0.318 and Recall (MFCC-ResNet)=0.324. With the MFCC-ResNet model fear and anger are recognized with 75% and 50% recall respectively. Thus, using plants as an emotion recognition tool seems worth investigating, addressing both cost and privacy concerns.

Introduction: This population-based retrospective cohort study assesses rates of adverse events (AEs) involving cerebral thromboembolism (CTE) after COVID-19 vaccines. Methods: Data were collected from the U.S. Centers for Disease Control and Prevention (CDC) and Food and Drug Administration (FDA) Vaccine Adverse Event Reporting System (VAERS) database from January 1, 1990 to December 31, 2023. CTE AEs after COVID-19 vaccines were compared to those after influenza vaccines and after all other vaccines using proportional reporting ratio (PRR) analysis by time. Results: There are 5137 cerebral thromboembolism AEs reported in the 3 years (36 months) after COVID-19 vaccines compared to 52 AEs for the influenza vaccines over the past 34 years (408 months) and 282 AEs for all other vaccines (excluding COVID-19) over the past 34 years (408 months). The PRR’s are significant when comparing AEs by time from COVID-19 vaccines to that of the influenza vaccines (p < 0.0001) or to that of all other vaccines (p < 0.0001). The CTE AEs PRR by time (95% confidence intervals) for the COVID-19 vaccine AEs vs influenza AEs is 1120 (95% confidence interval (723-1730), p < 0.0001) and for COVID-19 vaccines vs all others is 207 (95% confidence interval (144-296), p < 0.0001). Cerebral venous thromboembolism AEs are female predominant with a female/male odds ratio of 1.63 (95% confidence interval (1.52-1.74), p < 0.0001). Conversely, cerebral arterial thromboembolism has a nonsignificant male preponderance. Cerebral venous thromboembolism is far more common than cerebral arterial thromboembolism over 36 months with an odds ratio (OR) of 14.8 (95% confidence interval 14.0-15.5, p < 0.0001). Atrial fibrillation, the most common identifiable cause of cerebral arterial thromboembolism, occurs far more commonly after the COVID-19 as compared to all other vaccines with a PRR of 123 (95% CI 88.3-172, p < 0.0001) Conclusions: There is an alarming breach in the safety signal threshold concerning cerebral thrombosis AEs after COVID-19 vaccines compared to that of the influenza vaccines and even when compared to that of all other vaccines. An immediate global moratorium on the use of COVID-19 vaccines is necessary with an absolute contraindication in women of reproductive age.

A multitude of factors influence our well-being and health in everyday life. Some of which we are totally aware like a delayed train, car exhausts, or continuous work stress. Other factors influence us on a subconscious level, making them, however, not less important to address. One of these factors is the built environment surrounding us almost every second of our lives. The idea of biophilic design states the importance of natural elements implemented in architectural structures to improve the occupants’ health and well-being. Adding to this field of research, this article targets the impact of biophilic design on positive emotions and productivity by using novel approaches like Facial Emotion Recognition (FER) with Residual Masking Networks, and sentiment detection using Large Language Models. Two separate but related studies were conducted and their results reported here. The first study measured emotions of people when confronted with images of different kinds of architecture, via FER (Facial Emotion Recognition) and also via a user survey. We distinguish between self-stated emotions entered through a survey by study participants, and emotions detected from studying the participants’ faces through AI from our FER (Facial Emotion Recognition) system. We found clear trends for most detected emotions, and significant evidence for self-stated emotions, that architecture implementing biophilic design evokes more positive emotions than one that does not. The second study measures the influence of natural elements on productivity and team-engagement. We found that natural elements do influence productivity and sentiment positively; however, only the change in sentiment was shown to be significant. As our sample size, especially for the second study, was relatively small, future research will apply these ideas in a larger setup to acquire further evidence for the importance of biophilic design for human well-being and health.

Radio astronomical observations at millimeter and submillimeter wavelengths are a very important tool of astrophysical research. However, there is a huge area in the northern Eurasia, including the whole Russian territory, which lacks sufficiently large radio telescopes effectively operating at these wavelengths. In this review we describe our long-term efforts to find suitable sites for such radio telescopes in this area, that is, sites with good atmospheric transparency at millimeter and submillimeter waves. We describe methods and instruments used for measurements and evaluations of the atmospheric opacity. They include special radiometric systems, which are used for estimations of the atmospheric opacity from the sky brightness measurements. Evaluation of the precipitable water vapor from such measurements by the artificial neural network is discussed. Alternative approaches use global atmospheric models and signals of the Global Navigation Satellite Systems. To date, a long-term radiometric monitoring has been performed at several candidate sites and atmospheric conditions for many sites have been evaluated using global atmospheric models. Several sites with the best atmospheric transparency at millimeter and submillimeter wavelengths have been selected. They can be effectively used for astronomical observations at least in the major atmospheric transparency windows at 1.3 mm and 0.85 mm. These results can be also used for space communications and radar systems.

The removal of non-climatic biases, so-called inhomogeneities, from long climatic records needs sophistically developed statistical methods. One principle is that usually the differences between a candidate series and its neighbour series are analysed instead of directly the candidate series, in order to neutralize the possible impacts of regionally common natural climate variation on the detection of inhomogeneities. In most homogenization methods, two main kinds of time series comparisons are applied, i.e. composite reference series or pairwise comparisons. In composite reference series the inhomogeneities of neighbour series are attenuated by averaging the individual series, and the accuracy of homogenization can be improved by the iterative improvement of composite reference series. By contrast, pairwise comparisons have the advantage that coincidental inhomogeneities affecting several station series in a similar way can be identified with higher certainty than with composite reference series. In addition, homogenization with pairwise comparisons tends to facilitate the most accurate regional trend estimations. A new time series comparison method is presented here, which combines the use of pairwise comparisons and composite reference series in a way that their advantages are unified. This time series comparison method is embedded into the ACMANT homogenization method, and tested in large, commonly available monthly temperature test datasets.

Introduction Livestock abortigenic agents, which are microorganisms that lead to premature foetal death and expulsion before completion of the gestation period, are common in Africa and Asia. Abortion events cause economic losses by lowering reproduction (and hence herd/flock sizes) and effects on milk production. Despite the importance of livestock production for food security and livelihoods of millions of the world’s poorest communities, very little is known about the scale, magnitude or causes of livestock abortion in Africa. The aim of this review was to determine the current status of the burden of livestock abortion and surveillance measures adopted for livestock abortigenic pathogens in Africa and Asia, and to explore feasible surveillance technologies. Methodology A systematic literature search was conducted using Preferred Reporting of Systematic Reviews and Meta-analyses (PRISMA) guidelines in four databases for studies published between 1 Jan 1990 and 31 July 2021 that reported epidemiological surveys of livestock abortigenic pathogens in cattle, goats and sheep in Africa and Asia including; Brucella spp., Neospora caninum, Toxoplasma gondii, Rift valley fever virus, Coxiella burnetii, Chlamydia, Leptospira and Bovine viral Diarrhoea Virus. A meta-analysis was used to estimate the species-specific prevalence of the abortigenic diseases and the region where they were detected. Results In the systematic literature search, 48 full papers were included which in total included 50 species-specific surveillance reports from Africa and 19 from Asia. Adjusted median seroprevalence calculations estimated Brucella at 6.85% (range 1.2-11.6) of 9071 sheep, 3.35% (range 0.90-5.40) of 17,007 goats, 8.95% (range 0.50-63.60) of 171,733 cattle, Neospora at 6.80% (range 6.80 -6.80) of 555 sheep, 10.80 (range 10.80-10.80) of 185 goats, 12.65% (range 3.40- 25.60) of 3775 cattle, Toxoplasma at 27.50% (range 1.40 – 75.90) of 2284 sheep, 32.0% (range 20.00- 64.80) of 1226 goats, 7.50% (range 7.50 - 7.50) of 174 cattle, Coxiella at 9.20 (range 9.20 – 9.20) of 184 sheep, 24.20% (range 24.20-24.20) of 91 goats, 13.80% (range 13.80-13.80) of 217 cattle, Rift valley fever virus at 7.70 (2.40-40.00) of 874 sheep, 20.95 (range 2.50-40.00) of 547 goats, 7.45% (range 3.60-11.30) of 309 cattle, Bovine viral diarrhea virus at 78.90 (range 78.90 – 78.90) of 398 cattle, Leptospira at 70.50 (range 70.50 – 70.50) of 373 cattle and Chlamydia at 6.60 (6.60-6.60) of 803 sheep. We found that most studies, 45 (89%) used serological surveys, 1 (2%) used molecular and 1 (2%) reported to have used Mobile-phone based surveillance approach. Three studies (6.25%) of the 48 included were embedded in the national surveillance programs of the respective countries they were conducted, majority 89% were stand-alone cross-sectional studies. Conclusion In conclusion, livestock abortigenic pathogens are still a burden in many African and Asian countries.

Silicatein-α (Silα), a hydrolytic enzyme derived from siliceous marine sponges, is one of the few enzymes in nature capable of catalysing the metathesis of silicon-oxygen bonds. It is therefore of interest as a possible biocatalyst for the synthesis of organosiloxanes. To further investigate the substrate scope of this enzyme, a series of condensation reactions with a variety of phenols and aliphatic alcohols were carried out. In general, it was observed that Silα demonstrated a preference for phenols, though the conversions were relatively modest in most cases. In the two pairs of chiral alcohols that were investigated, it was found that the enzyme displayed a preference for the silylation of the S-enantiomers. Additionally, the enzyme’s tolerance to a range of solvents was tested. Silα had the highest level of substrate conversion in the non-polar solvents n-octane and toluene, although the inclusion of up to 20% of 1,4-dioxane was tolerated. These results suggest that Silα is a potential candidate for directed evolution towards future application as a robust and selective bi-ocatalyst for organosiloxane chemistry.

We summarise contributions made to the computational phase-field modelling of alloy solidification from the University of Leeds spoke of the LiME project. We begin with a general introduction to phase-field, and then reference the numerical issues that arise from solution of the model, before detailing each contribution to the modelling itself. These latter contributions range from controlling and developing interface-width independent modelling; controlling morphology in both single and multiphase settings; generalising from single to multi-phase models; and creating a thermodynamic consistent framework for modelling entropy flow and thereby postulate a temperature field consistent with the concepts of, and applicable in, multiphase and density-dependent settings.

The research presents a novel synthetic photosensitizer for photodynamic therapy (PDT) of malignant tumors - meso-tetra(3-pyridyl) bacteriochlorin, which absorbs at 747 nm (in the long-wavelength region of the spectrum) and is stable when stored in the dark. H2Py4BC demonstrates pronounced photoinduced activity in vitro against tumor cells of various genesis (IC50 varies from 21 to 68 nM for НЕр2, EJ, S37, CТ26, and LLC cultured cells) and provides in vivo pronounced antitumor efficacy in the treatment of mice bearing small or large S37, Colo26, and LLC metastatic tumors, as well as in the treatment of rats bearing RS-1 liver cholangioma. As a result, total regress of primary tumor nodules and cure of 40 to 100% of the animals were proved by the experiment criteria, MRI, and histological analysis. Meso-tetra(3-pyridyl) bacteriochlorin quickly penetrates and accumulates in the tumor tissue and internal organs of mice, and after 24 hours 80% of the dye is excreted from skin as well as 87% - 92% from liver, kidneys, and spleen.

In recent years, technical processes for the sequestration of CO2 through industrial waste mineral carbonation have been explored and developed. There is a large portfolio of Carbon Capture, Uti-lisation and Storage (CCUS) techniques that have been employed on a laboratory and at pilot scale. These include geological storage, ocean storage and mineralisation by carbonate ores. In view of this, the main purpose of this research was to investigate and explore chemical variables, particularly ammonium salts as lixiviants for calcium mineral extraction from iron making slag. The slag in use was acquired from a Steel Mill in the Vaal Triangle Region in Gauteng, South Af-rica. The experimental test work was conducted using different ammonium lixiviants, namely, NH4NO3, NH4Cl and CH3COONH4 to understand the influence of anion type as well as possible differences in mechanisms of interactions. Lixiviant concentration as well as the reaction time were varied in this research study. The three selected ammonium based lixiviants showed different extents of calcium extraction owing to differences in the anion groups. NH4NO3, NH4Cl and CH3COONH4 were found capable of dissolving 50% to 80% of calcium from the selected slag for different molar concentrations. Anion type and leaching time also had significant influences on the leaching of calcium from the slag. Rapid pH degradation resulted in better calcium extraction ca-pabilities. This work has shown that the selected ammonium salts have a potential as lixiviants for calcium dissolution from iron making blast furnace slags. These lixiviants would therefore be important to consider during calcium mineral carbonation for CO2 sequestration.

White adipose tissue (WAT) represents an endocrinologically and immunologically active tissue that’s primary role is energy storage and homeostasis. Breast WAT is involved in the secretion of hormones and proinflammatory molecules that are associated with breast cancer development and progression. The role of adiposity and systemic inflammation in immune responses and resistance to anti-cancer treatment in breast cancer (BC) patients is still not clear. This review aims to evaluate the emerging evidence on the crosstalk between adiposity and the immune-tumour microenvironment in BC, its progression and treatment resistance. Adiposity, and by extension subclinical inflammation, are associated with metabolic dysfunction and changes in the immune-tumour microenvironment in BC. In oestrogen receptor positive (ER+) breast tumours, it is proposed that these changes are mediated via a paracrine interaction between macrophages and preadipocytes leading to elevated aromatase expression and secretion of pro-inflammatory cytokines and adipokines in the breast tissue in patients who are obese or overweight. In HER2+ breast tumours, WAT inflammation has been shown to be associated with resistance to trastuzumab mediated via MAPK or PI3K pathways. Furthermore, adipose tissue in patients with obesity is associated with upregulation of immune checkpoints on T-cells that is partially mediated via immunomodulatory effects of leptin and has been paradoxically associated with improved responses to immunotherapy in several cancers. In conclusion, evidence suggests that body composition and metabolic status are associated with patient outcomes. To optimise patient stratification and personalisation of treatment, prospective studies are required to evaluate the role of body composition and metabolic parameters in metabolic immune reprogramming with and without immunotherapy in patients with BC.

The integration of diverse distributed generation (DG) units, encompassing both Renewable Energy Sources (RES) and non-RES technologies delves into voltage levels, current distributions, and power flows, aiming to optimize and effectively manage the distribution network. An RES-based DGs such as photovoltaic systems and wind turbines, alongside non-RES units like fuel cells and micro turbines. This study proposes a hybrid approach the Multi-Objective Genetic Algorithm - Grey Wolf Optimizer (MOGA-GWO). By merging the strengths of multi-objective genetic algorithms with the efficiency of the Grey Wolf Optimizer, this advanced algorithm seeks semi-optimal solutions for multi-objective optimization problems. The algorithm aims to improve convergence speed without compromising solution quality, offering a promising solution for optimizing the characteristics of DG and RES integration in distribution networks compared to Cuckoo Search and Simulation Annealing Techniques. Key algorithmic operations include individual representation, initialization, fitness function computation, selection, crossover, mutation, and ending conditions. The DG optimal power flow problem is explored with a focus on minimizing generation costs, improving voltage profiles, minimizing losses, enhancing reliability, integrating renewable energy, reducing environmental impact, managing congestion, and ensuring compliance with operational constraints. Beyond traditional considerations, the study emphasizes neglected objectives and constraints, such as cyber-security concerns, real-time operation, regulatory frameworks, social acceptance, lifecycle environmental impact, grid resilience, data privacy, aging infrastructure compatibility, and economic viability.

The estuarine exchange flow increases longitudinal dispersion of passive tracers and traps sinking particles, potentially creating an estuarine turbidity maximum (ETM): a localized maximum of suspended particulate matter concentration in an estuary. The ETM can have many implications - dead zones due to increased turbidity or hypoxia from organic matter decomposition, naval navigation challenges, and other water quality problems. Using timescales, we investigate how the interaction between exchange flow and particle sinking leads to ETMs by modeling a sinking tracer in an idealized box model of the Total Exchange Flow (TEF) first developed by Parker MacCready. Results indicate that the balance of particle sinking and vertical mixing is critical to determining ETM size and location. We then focus on the role of ecology in ETM formation through the use of The Peter-Parker Model: a new biophysical model which combines the TEF box model with a Nutrient-Phytoplankton-Zooplankton-Detritus (NPZD) model, the likes of which were first developed by Peter J.S. Franks. Detritus sinking rates similarly influence detritus peak concentration and location (an ETM), but detritus ETMs occur in a different location than the sinking tracer due to the influence of the biological factors which create a time lag of about 1 day. Lastly, we characterize the flow of the models with a dimensionless parameter that compares timescales and summarizes the dynamics of the sinking tracer in ETM formation and can be used across systems.

This article uses a contemporary and revelatory case study to explore the relationship between three conversations in the innovation literature: design thinking, creativity in strategy and, the emerging area of art-thinking. Businesses are increasingly operating in a VUCA environment where they need to design better experiences for their customers and better outcomes for their firm and the Arts are no exception. Innovation, or more correctly growth through innovation, is a top priority for business and although there is no single, unifying blueprint for success at innovation, design thinking is the process that is receiving most attention and getting most traction. Design thinking teaches businesses to think with the creativity and intuition of a designer; to show a deep understanding of; and have empathy with the user. But design thinking has limitations. By placing the consumer at the very heart of the innovation process, design thinking can often lead to more incremental than radical ideas. Now there is a new perspective emerging, art-thinking, in which the objective is not to design a journey from current scenario; A to improved position: B. Art thinking requires the creation of B and spends more time in the open ended, problem space, staking out possibilities and looking for uncontested space. In Dublin, we examine a case of the oldest, largest and most prestigious fine art gallery and studio where most of the country’s best-known and successful visual artists both make, exhibit and sell their art. Graphic Studio Dublin is primarily a printmaking studio, established by artists over 60 years ago. It has facilities for woodblock, lino-print, silkscreen, intaglio and carborundum etching spread over four floors of a centrally located studio where the artists have access 24/7. But two years ago it found itself on the brink of collapse having borrowed heavily to invest in new facilities during the period of Ireland’s economic collapse. Its loans were sold to a vulture-fund who were about to foreclose in a move that would have seen a generation of Irish Artists displaced. A new board of directors was empaneled and they introduced some art thinking principles to bring the organisation back from the brink. They used an art-thinking mindset and design thinking tools to restore the fortunes of this venerable, artist-led institution and it worked.

We examine here the conductance changes associated with the change in spin state in a variety of different structures, using the example of the spin crossover complex [Fe(H2B(pz)2)2(bipy)] (pz= (pyrazol-1-yl)-borate and bipy = 2,2’-bipyridine) and [Fe(Htrz)2(trz)](BF4)] (Htrz = 1H-1,2,4-triazole) thin films . This conductance change is highly variable depending on the mechanism driving the change in spin state, the substrate and the device geometry. Simply stated, the choice of spin crossover complex used to build a device is not the only factor in determining the change in conductance with the change in spin state.

Spin crossover (SCO) complexes are in the forefront of image, memory and sensing devices, with applications already established since for thirty years. In order to reach magnetic multistability conditions, the high-spin (HS) and low-spin (LS) states have to be carefully balanced by ligand field stabilization and spin pairing energies. Both of these effects could be effectively modelled by electronic structure theory, if the description would be accurate enough to describe these concurrent influences to within a few kJ/mol. Such a milestone would allow for the in silico-driven development of SCO complexes. However, so far, the ab initio simulation of such systems has been dominated by general gradient approximation density functional calculations. The latter can only provide the right answer for the wrong reasons, given that the LS states are grossly stabilized. In this contribution, we explore different venues for the parameterisation of hybrid functionals. A fitting set is provided on the basis of explicitly correlated coupled cluster calculations, with single- and multi-dimensional fitting approaches being tested to selected classes of hybrid functionals (hybrid, range separated and local hybrid). Promising agreement to benchmark data is found for a rescaled PBE0 hybrid functional and a local version thereof, with a discussion of different atomic exchange factors.

Peatlands in Indonesia are one of the world's largest carbon sinks, helping to regulate greenhouse gas emissions and global climate change. Lophostemon suaveolens is a plant found in Papua's endemic peat ecosystem that grows well in wet areas with low fertility. It is geographically dispersed and has the potential for peatland re-habilitation. We present an efficient and reproducible protocol for in vitro multiplication of plantlets using nodal segments and shoot apices collected from plantlets. The Murashige and Skoog (MS) medium was sup-plemented with single and double kinds of PGRs (BAP and NAA). The concentration used in this study is based on the best findings of earlier preliminary research on single PGR treatment (0.5 ml/l BAP and 0.1 ml/l NAA) for the initiation stage. After 3 months of in vitro axillary shoot initiation, elongated shoots from plant-lets were separated from the clumps and multiplied. Until 6 months incubation, the potential multiplication of axillary shoots was determined by counting the number of nodule multiplication coefficients (NMC), shoot length, root length, and number of leaves (6 successive subculture). The highest average per plantlet of NMC (8.4 0.13) was observed in MS medium with a combination of 0.5 ml/l BAP and 0.1 ml/l NAA (double PGRs), with the longest shoots (5.91 0.17 cm), the longest root length (8.83 0.69 cm), and the most leaves (32 0.69). They were cultured in a pH 5 environment with a light photoperiod (40 mol/m2/s intensity) for 16 hours. When BAP and NAA were used together after acclimatization, seedling survival was highest. This is the first report of L. suaveolens in vitro multiplication, and the protocol could be used to propagate this peatland species on a large scale.

Hypertensive disorders of pregnancy (HDP), including preeclampsia (PE) and gestational hypertension (GH), are major causes of maternal and fetal morbidity and mortality. This review elucidates the role of regulatory T cells (Tregs) in the immunological aspects of HDP and explores their therapeutic potential. Tregs, known for maintaining immune tolerance, are crucial in pregnancy to prevent immune-mediated rejection of the fetus. In HDP, Treg numbers and function imbalance are observed, correlating with disease severity. The review highlights that Tregs contribute to immunological adaptation in normal pregnancy, ensuring fetal acceptance and placental development. In contrast, HDP is associated with Treg dysfunction, marked by decreased numbers and impaired regulatory capacity, leading to inadequate immune tolerance and abnormal placental development. This dysfunction is particularly evident in PE, where Tregs fail to adequately modulate the maternal immune response against fetal antigens, contributing to the pathophysiology of the disorder. Therapeutic interventions aiming to modulate Treg activity represent a promising avenue for HDP management. Studies in animal models and limited clinical trials suggest that enhancing Treg functionality could mitigate HDP symptoms and improve pregnancy outcomes. However, the review acknowledges the complexity of translating these findings into effective clinical therapies, given the multifactorial nature of HDP and the intricate regulatory mechanisms of Tregs. In conclusion, while the precise role of Tregs in HDP is still being unravelled, their central role in immune regulation during pregnancy is indisputable. Further research is needed to fully understand the mechanisms by which Tregs contribute to HDP and to develop targeted therapies that can safely and effectively harness their regulatory potential for treating hypertensive diseases of pregnancy.

Knowledge of the interaction between inorganic and organic phosphates with soil minerals is vital for improving the soil P fertility. To achieve an in-depth understanding we combined adsorption experiments and hybrid ab initio molecular dynamics simulations to analyze the adsorption of common phosphates, i.e. orthophosphate (OP), glycerolphosphate (GP) and inositolhexaphosphate (IHP), onto the 100 surface plane of goethite. Experimental adsorption data per mol P-molecule basis fitted to the Freundlich model show the adsorption strength increases in the order GP &lt; OP &lt; IHP, and IHP adsorption being saturated faster followed by GP and OP. Modeling results show that OP and GP form stable monodentate (M) and binuclear bidentate (B) motifs with B being more stable than M, whereas IHP forms stable M and 3M motifs. Interfacial water plays an important role through hydrogen bonds and proton transfers with OP/GP/IHP and goethite. It also controls the binding motifs of phosphates with goethite. Combining both experimental and modeling results, we propose that the B motif dominates for OP, whereas GP forms M and IHP forms a combination of M and 3M motifs. The joint approach plausibly explains why IHP is the predominant organically bound P form in soil. This study could be considered as a preliminary step for further studies for understanding the mechanisms of how microbes and plants overcome the strong IHP–mineral binding to implement the phosphate groups into their metabolism.

This paper presents preliminary research that investigates the relationship between the flow of a group of jazz musicians, quantified through multi-person pose synchronization, and their collective emotions. Building upon previous studies that measured the physical synchronicity of team members by tracking their body movements and measuring the difference in arm, leg, and head movements, we introduce a novel metric termed "team entanglement". We employ facial expression recognition to evaluate the musicians’ collective emotions. Through correlation and regression analysis, we establish that higher levels of synchronized body and head movements correspond to lower levels of disgust, anger, sadness and higher levels of joy among the musicians. Furthermore, we utilize a Convolutional Neural Network (CNN) based deep learning model to predict the collective emotions of the musicians. This model leverages 17 body synchrony keypoint vectors as features, resulting in a training accuracy of 61.47% and a test accuracy of 66.17%.

The self-organisation of a fertilised egg to form a blastocyst structure, which consists of three distinct cell lineages (trophoblast, epiblast and hypoblast) arranged around an off-centre cavity, is unique to mammals. While the starting point (the zygote) and endpoint (the blastocyst) are similar in all mammals, the intervening events have diverged. This review examines and compares the descriptive and functional data surrounding embryonic gene activation, symmetry-breaking, first and second lineage establishment, and fate commitment in a wide range of mammalian orders. The exquisite detail known from mouse embryogenesis, embryonic stem cell studies and the wealth of recent single cell transcriptomic experiments are used to highlight the building principles underlying early mammalian embryonic development.

Regeneration is a fundamental process much attributed to functions of adult stem cells. In last decades delivery of suspended adult stem cells is widely adopted in regenerative medicine as a leading mean of cell therapy. However, adult stem cells can not complete the task of human body regeneration effectively by themselves as far as they need a receptive microenvironment (the niche) to engraft and perform properly. Understanding of mechanisms underlying mammalian regeneration lead us to an assumption that improved outcomes of cell therapy requires a specific microenvironment generated in damaged area prior to stem cell delivery. To certain extent it may be achieved by delivery of mesenchymal stromal cells (MSC), not in dispersed form, but rather self-organized in cell sheets (CS) – tissue-like structures comprising of viable cells and microenvironment components: extracellular matrix and soluble factors deposited in the matrix. In this communication we highlight a potential role of mesenchymal stromal cells (MSC) as regeneration organizers and speculate that this function emerges in CS. This concept shifts our understanding of therapeutic mechanism underlying a widely known CS-based delivery method for regenerative medicine.

The functioning of forest ecosystems depends on the taxonomic and ecological diversity of soil fungi. Urbanization is increasing worldwide and is regarded a major driver of environmental change altering local species assemblages in urban forest. We investigated whether the degree of urbanization and local forest characteristics affect the soil fungal community in 20 beech forests located along a rural–urban gradient in the city of Basel and its suburbs (Switzerland). We analyzed their soil fungal communities by DNA metabarcoding of the rDNA ITS2 region and related these data to local forest vegetation characteristics and soil properties. The number of fungal OTUs in the 20 forests examined ranged from 170 to 303. Richness, diversity and evenness of fungal OTUs were all significantly affected by the degree of urbanization, but in different ways. OTU richness was highest in forests in areas with a low degree of urbanization and lowest in forests in rural areas. In contrast, the diversity of OTUs increased with increasing degree of urbanization. Different fungal phyla and fungal guilds showed distinct patterns in their relative abundance along the rural-urban gradient. The degree of urbanization reduced the relative abundance of symbiotrophic fungi, but increased that of saprotrophic and pathotrophic fungi. Our results show that urbanization alters soil fungal community, which in turn can lead to changes in forest ecosystems.

There is an urgent need to advance safe and affordable COVID-19 vaccines for low- and middle-income countries of Asia, Africa and Latin America. Such vaccines rely on proven technologies such as recombinant protein-based vaccines to facilitate its transfer for emerging market vaccine manufacturers. Our group is developing a two-pronged approach to advance recombinant protein-based vaccines to prevent COVID-19 caused by SARS CoV2 and other coronavirus infections. One vaccine is based on a yeast-derived (Pichia pastoris) recombinant protein comprised of the receptor binding domain (RBD) of the SARS-CoV formulated on alum and referred to as the CoV RBD219-N1 Vaccine. Potentially this vaccine could be used as a heterologous vaccine against COVID-19. A second vaccine specific for COVID-19 is also being advanced using the corresponding RBD of SARS-CoV-2. The first antigen has already undergone cGMP manufacture and is therefore “shovel ready” for advancing into clinical trials, following vialing and required GLP toxicology testing. Evidence for its potential efficacy to cross-protect against SARS-CoV-2 includes cross-neutralization and binding studies using polyclonal and monoclonal antibodies. Evidence in support of its safety profile include our internal assessments in a mouse challenge model using a lethal mouse adapted SARS strain, which show that SARS-CoV RBD 291N1 (when adsorbed to Alhydrogel®) does not elicit eosinophilic lung pathology. Together these findings suggest that recombinant protein-based vaccines based on the RBD warrant further development to prevent SARS, COVID-19 or other coronaviruses of pandemic potential.

Fructose in beverages has adverse effects on lipids, glucose and insulin sensitivity after acute and chronic ingestion. There is limited data showing that chronic consumption of fructose in solid foods has harmful effects. We hypothesized that a moderate amount of fructose compared with sucrose in solid food consumed for a month would not adversely influence fasting or postprandial lipids and glucose after an acute fat and carbohydrate load. Twenty-five men and women with prediabetes and/or obesity and overweight consumed in random order two acute test meals of muffins sweetened with either fructose or sucrose, followed by 4-week chronic consumption of 42g/day of either fructose or sucrose in low fat muffins after which the 2 meal tests were repeated. Subjects were randomised to sugar type in the chronic feeding period. Sugar type had no effect on the incremental area under the curve for triglyceride or uric acid at either time point (P=0.4 and P=0.9). There was no overall difference between meal tests at baseline and after 1 month and no effect of consuming sucrose or fructose muffins for 1 month. Fasting triglyceride increased after chronic consumption of fructose by 0.31±0.37 mmol/L compared with sucrose in people with IFG/IGT only (P=0.004). Fructose at a moderate intake of <10% of energy in solid food has no different effects on postprandial triglyceride and uric acid compared with sucrose although fasting triglyceride was increased in people with IFG/IGT after 1 month of fructose muffins suggesting the need for caution.

Autologous platelet-rich plasma (PRP) preparations are prepared at point of care. Centrifugation cellular density separation sequesters a fresh unit of blood into three main fractions: a platelet-poor plasma (PPP) fraction, a stratum rich in platelets (platelet concentrate) and, bioformulation dependent, also leukocyte and erythrocyte fractions. The employment of autologous platelet concentrates facilitates the biological potential to accelerate and support in numerous cellular activities that can lead to tissue repair, tissue regeneration, wound healing, and ultimately functional structural repair. Normally, after PRP preparation the PPP fraction is discarded. One of the less well known, but equally important features of PPP is that particular growth factors (GFs) are not abundantly present in PRP, as they reside outside the platelet alpha granules. Precisely, insulin-like growth factor-1 (IGF-1) and hepatocyte growth factor (HGF) are mainly present in the PPP fraction. In addition to their roles as angiogenesis activators, these plasma-based GFs are also known to inhibit inflammation, fibrosis, and they promote keratinocyte migration and support in tissue repair and wound healing. Additionally, PPP is known for the presence of exosomes and other macrovesicles, exerting cell-cell communication and cell signaling. Newly developed ultrafiltration technologies incorporate PPP processing methods by eliminating in a fast and efficient manner plasma water, cytokines, molecules, and plasma proteins with a molecular mass (weight) less than the pore size of the fibers. Consequently, a viable and viscous protein concentrate of functional, total proteins, like fibrinogen, albumin, and alpha-2-macroglobulin is created. Consolidating a small volume of high platelet concentrate with a small volume of highly concentrated protein-rich PPP creates a protein rich platelet concentrate (PRPC) biological preparation. After the activation of proteins, mainly fibrinogen, the PRPC matrix retains and facilitates interactions between invading resident cells, like macrophages, fibroblast, and mesenchymal stem cells (MSCs), and the embedded concentrated PRP cells and molecules. The administered PRPC biologic will ultimately undergo fibrinolysis, leading to a sustained release of concentrated cells and molecules that have been retained in the PRPC matrix until the matrix is dissolved. We will discuss the unique biological and tissue reparative and regenerative properties of PRPC matrix.

The impetus for the development of coaching as a professional managerial activity is based on the needs and requirements of a modern sustainable society. The paper aims to explore the awareness of academic students about the coaching approach and to formu-late recommendations for its application in the academic environment. The article focuses on the views of experts in the field of coaching approach as a means of improving com-munication in the academic/educational setting, characterizes communication and coaching approach, coaching models and its benefits and barriers. The survey presents a survey of awareness of the coaching approach among college and university students of in Slovakia and the possibilities/options of its application in the academic environment. The research was carried out by the questionnaire method. The evaluation of the questionnaire and the statistical evaluation of established hypotheses and assumptions concerning the coaching approach. The proposion of students was the introduction of the subject "Basics of coaching" which could be taught for all students at University of Zilina, Slovakia. Acording to the survey, 468 students, representing 68%, have knowledge about coaching. Furthermore, 68% of students had or have doubts about achieving their goals during their studies. According to the results of the survey, only 24% of students had ex-perience with coaching. The cooperation with a coach was regarded as beneficial for 71% of participants of the survey, which had already experience the coaching lectures. The students of managerial fields would benefit in enhancing leadership skills and providing support of their working teams.Finally, suggest organizing an introductory full-day workshops for students of man-agement -future managers, followed by organizing individual thematic workshops for specific areas of coaching.Moreover, the usage of coaching skills is possible yet while they are students with applications in communication in their relationships, student jobs, searching the profes-sional job opportunities and accomplishing the final thesis.To raise awareness of coaching approach in the University of Zilina in a cooperation with The Counseling and Career Center and its activities.

Recently, a paper was written to establish semi-structured complex numbers ℍ (a new number set invented to enable division by zero) as a useful mathematical tool providing novel results from its application in engineering and science. Whilst the paper was a milestone, the application of this number set to quantum and classical physics had not been fully explored. Consequently, the aim of this research was to use semi-structured complex numbers to develop a new mathematical model for the mass of an object and in course unite classical and quantum physics in a simple yet effective manner. As its major contributions this paper: (1) develops a new mathematical model for the mass of an object called the wave-mass function using De Broglie’s mass and frequency relation and semi-structured complex numbers; (2) uses the new wave-mass function to determine what happens to an object traveling at the speed of light; (3) derives a relation between Schrödinger’s wave function and the new wave-mass function; (4) derives a relation between Einstein’s Field Equation and the new wave-mass function; (5) uses the wave-mass function to combine Einstein’s Field Equation with Schrödinger’s wave function to form a new quantum gravity equation. These results and their applications provide a firm foundation to advance the number set ℍ as a useful mathematical tool.

The quiet-time solar wind electrons feature non-thermal characteristics when viewed from the perspective of their velocity distribution functions. They typically have an appearance of being composed of a denser thermal “core” population plus a tenuous energetic “halo” population. At first, such a feature was empirically fitted with the Kappa velocity space distribution function, but ever since the ground-breaking work by Tsallis, the space physics community has embraced the potential implication of the Kappa distribution as reflecting the non-extensive nature of the space plasma. From the viewpoint of microscopic plasma theory, the formation of non-thermal electron velocity distribution function can be interpreted in terms of the plasma being in a state of turbulent quasi equilibrium. Such a finding brings forth the possible existence of a profound inter-relationship between the non-extensive statistical state and the turbulent quasi-equilibrium state. The present paper further develops the idea of solar wind electrons being in the turbulent equilibrium, but unlike the previous model, which involves the electrostatic turbulence near the plasma oscillation frequency (i.e., Langmuir turbulence), the present paper considers the impact of transverse electromagnetic turbulence, particularly, the turbulence in the whistler-mode frequency range. It is found that the coupling of spontaneously-emitted thermal fluctuations and the background turbulence leads to the formation of non-thermal electron velocity distribution function of the type observed in the solar wind during quiet times. This demonstrates that the whistler-range turbulence represents an alternative mechanism for producing the Kappa-like non-thermal distribution, especially close to the Sun and in the near-Earth space environment.

This paper describes the state of the art and future opportunities for process design and sustainable development. In the Introduction the main global megatrends and European Union's response to two of them, the European Green Deal, are presented. The organization of professionals in the field, their conferences and publications support the two topics. A brief analysis of the published documents in the two most popular databases shows that the environmental dimension predominates, followed by an economic one, while the social pillar of sustainable development is undervalued. The main design tools for sustainability are described. As an important practical case, the European chemical and process industries are analyzed and their achievements in sustainable development are highlighted; in particular, their strategies are presented in more detail. The conclusions cover the most urgent future development areas of the process industries, carbon capture with utilization or storage, process analysis, simulation, synthesis and optimization tools; zero waste, circular economy and resource efficiency already play an important role. However, more profound changes are needed in the coming decades, including a shift away from growth with changes in habits, lifestyles and business models. Lifelong education for sustainable development will play a very important role in the growth of democracy and happiness instead of consumerism and neoliberalism.

Since certain Mycobacterium tuberculosis complex (MTBC) members, like M. bovis, are endemic in specific South African wildlife reserves and zoos, cases of clinically important nontuberculous mycobacteria (NTM) in wildlife may be neglected. Additionally, due to the inability of tests to differentiate between host responses to MTBC and NTM, the diagnosis of MTBC may be confounded by the presence of NTMs. This may hinder control efforts. These constraints highlight the need for enhanced rapid detection and differentiation methods for MTBC and NTM, especially in high MTBC burden areas. We evaluated the use of the GeneXpert MTB/RIF Ultra, the Hain CMdirect V1.0, and novel amplicon sequencing PCRs targeting the mycobacterial rpoB and ku gene targets, directly on antemortem respiratory samples from known MTBC-infected and NTM culture-positive African elephants (n=26 animals) and rhinoceros (n=23 animals). Our findings suggest that the Ultra is the most sensitive diagnostic test for MTBC DNA detection directly in raw antemortem respiratory specimens and that the rpoB PCR is ideal for Mycobacterium genus DNA detection and species identification through amplicon sequencing.

Human and animal waste, including waste products originating from human or animal digestive systems such as urine, feces, and animal manure, have constituted a nuisance to the environment. Inappropriate disposal and poor sanitation of human and animal waste often cause negative impacts on human health through contamination of the terrestrial environment, soil, and water bodies. Therefore, it is necessary to convert these wastes into useful resources to mitigate their adverse environmental effect. The present study provides an overview and research progress of different thermochemical and biological conversion pathways for the transformation of human- and animal-derived waste into valuable resources. The physicochemical properties of human and animal waste are meticulously discussed as well as nutrient recovery strategies. In addition, a bibliometric analysis is provided to identify the trends in research and knowledge gaps. The results reveal that the U.S.A, China and England are the dominant countries in the research areas related to resource recovery from human or animal waste. In addition, researchers from the University of Illinois, the University of California Davis, the Chinese Academy of Science and Zhejiang University are front runners in research related to these areas. Future research should be centred on developing technologies for the on-site recovery of resources, exploring integrated resource recovery pathways, and exploring different safe waste processing methods.

This paper explores if plants are capable of responding to human movement by changes in their electrical signals. Towards that goal we conducted a series of experiments, where humans over a period of 6 months were performing different types of eurythmic gestures in proximity of garden plants, namely salad, basil, and tomatoes. To measure plant perception, we used the plant spikerbox, a device that measures changes in voltage differentials of plants between roots and leaves. Using machine learning, we find that the voltage differentials over time of the plant predict if (a) eurythmy has been performed, and (b) which kind of eurythmy gestures has been performed. We also find that the signals are different based on the species of the plant. In other words, the perception of a salad, tomato, or basil might differ just as perception of different species of animals differ. This opens new ways of studying plant ecosystems, while also paving the way to use plants as biosensors for analyzing human movement.

Introduction: In Part II of this three-part series, we expose techniques that can be used by the U.S. Centers for Disease Control and prevention (CDC) and Food and Drug Administration (FDA) to manipulate and throttle the Vaccine Adverse Event Reporting System (VAERS), a vaccine safety monitoring system open to the public. The U.S. government’s recommendation of COVID-19 vaccines during pregnancy was more a product of propaganda than of science and plagued with conflicts of interest. The extreme breach of COVID-19 vaccine pregnancy complication safety signals documented in VAERS cannot be disregarded or concealed. As a result, CDC/FDA are moving to closed, government captured platforms, including V-safe, Vaccine Safety Datalink (VSD) system, and the Biologics Effectiveness and Safety (BEST) system. Public transparency of adverse events following COVID-19 vaccination in pregnancy should be increased, not thwarted. Methods: In Part I the CDC/FDA Vaccine Adverse Event Reporting System (VAERS) database was queried from January 1, 1990, to April 26, 2024 for adverse events (AEs) involving pregnancy complications following vaccination. In Part II we investigate tactics discovered in VAERS that concealed vaccine injuries and deaths. Conflicts of interest, as well as specific communications and publications from the CDC/FDA and the New England Journal of Medicine (NEJM) are analyzed. Results: Of all VAERS AE reports, 8.47% (138,983) of COVID-19 reports had no vaccination date and thus were missing from the data presented in Part I of this series. We unconcealed data presented in Part I of this series to include VAERS case reports that were excluded when using standard queries because of an “unknown vaccination date”. The unconcealed data in the 37 AE cases reported in this study (Part II) ranged from 0 - 38% with a mean of 8.2% (standard deviation 9.7%) and the significant breaches of VAERS safety signals in Part I of this series were largely underestimated. Another method of concealing vaccine associated AEs is to exclude the specific vaccine type rendering it as an “unknown vaccine type”. “Unknown vaccine type” has logarithmically increased since the rollout of the COVID-19 vaccines in 2021, ranging from 1 to 400 cases between 1990 to 2018 to 11,461 cases in 2021. CDC/FDA granted $67 million via a Cooperative Agreement grant to Massachusetts Department of Public Health (MDPH) between July 1, 2019, to June 30, 2025. MDPH then made subawards under this grant to 21 influential public and private health and civic organizations, including NEJM’s owner, Massachusetts Medical Society (MMS). As one of the subawardees under the grant, MMS as owner of NEJM received over $426,000 in federal HHS/CDC grant money from 2019 to 2020 for “public health and medical emergency preparedness projects”. Conclusions: CDC/FDA has failed to capture and account for a significant number of AE case reports following COVID-19 in VAERS by a variety of techniques in an apparent attempt to sanitize the data. CDC’s Rochelle Walensky and NEJM’s Editor-in-Chief Eric Rubin pushed novel untested COVID-19 vaccines in pregnant women despite clear evidence from multiple sources that safety signals had been breached.

Angiogenesis is a critical physiological response to ischemia but becomes pathological when dysregulated and driven excessively by inflammation. We recently identified a novel angiogenic role for tripartite-motif-containing protein 2 (TRIM2) whereby lentiviral shRNA-mediated TRIM2 knockdown impaired endothelial angiogenic functions in vitro. This study sought to determine whether these effects could be translated in vivo and to determine the molecular mechanisms involved. CRISPR/Cas9-generated Trim2–/– mice that underwent a periarterial collar model of inflammation-induced angiogenesis exhibited significantly less adventitial macrophage infiltration relative to wildtype (WT) littermates, concomitant with decreased mRNA expression of macrophage marker Cd68 and reduced adventitial proliferating neovessels. Mechanistically, TRIM2 knockdown in endothelial cells in vitro attenuated inflammation-driven induction of critical angiogenic mediators, including nuclear HIF-1α, and curbed the phosphorylation of downstream effector eNOS. Conversely, in a hindlimb ischemia model of hypoxia-mediated angiogenesis, there were no differences in blood flow reperfusion to the ischemic hindlimbs of Trim2–/– and WT mice despite a decrease in proliferating neovessels and arterioles. TRIM2 knockdown in vitro attenuated hypoxia-driven induction of nuclear HIF-1α but had no further downstream effects on other angiogenic proteins. Our study has implications for understanding the role of TRIM2 in the regulation of angiogenesis in both pathophysiological contexts.

Literature pertaining to youth development has identified the importance of understanding the physical, intellectual and emotional needs of adolescent youth. The purpose of this study was to compare the use of a ‘traditional’ and ‘progressive’ coaching style to train a general male youth population to improve sprint and jump performances, whilst assessing enjoyment to comment on long term application. Maximal sprint times, sprint kinematics, unilateral jump distances and repetitive tuck jump scores were measured alongside anthropometric variables to characterise performance. Results revealed significant (p>0.05) pre/post differences in anthropometric variables across all maturation groups, and each of the maturational levels displayed a tendency to favour a particular coaching or control condition. Pre-PHV groups responded most effectively to the progressive style of coaching, displaying improvements in horizontal jump performances, and -0.7 to -2.7% improvements in all sprint times, despite also showing the largest increase in tuck jump scores (25.8%). The circa-PHV group produced their greatest improvements in the traditional intervention, as displayed through significant improvements (p<0.05) in 20m sprint times and dominant-leg horizontal jump performance, whilst also revealing the greatest deterioration in tuck jump scores (14.2%). Post-PHV displayed the greatest improvements in the control setting, suggesting the natural benefits gained through adolescent development were greater than the influence of the training interventions. In conclusion, it is suggested that matching coaching strategies and delivery techniques to the period of biological maturation may have implications for both performance and athlete safety.

A model for the simulation of ion beam extraction from an electron cyclotron resonance ion source is proposed. It is based on the simple fact that charged particles follow magnetic field lines. Therefore magnetic field lines are used to generate initial conditions for ray-tracing. This model reproduces in simulation experimentally obtained results. The importance of correlations in phase-space caused by the magnetic field is shown in simulation. This model also describes the physics of space-charge and its compensation in the extracted (fast) ion beam by low energy electrons. Simulation provides the possibility to test theoretical assumptions, as well as to optimize technical designs.

Understanding the detailed timing of crop phenology and their variability enhances grain yield and quality by providing precise scheduling of irrigation, fertilization, and crop protection mechanisms. Advances in information and communication technology (ICT) provide a unique opportunity to develop agriculture-related tools that enhance wall-to-wall upscaling of data outputs from point-location data to wide-area spatial scales. Because of the heterogeneity of the worldwide agro-ecological zones where crops are cultivated, it is unproductive to perform plant phenology research without providing means to upscale results to landscape-level while safeguarding field-scale relevance. This paper presents an advanced, reproducible, and open-source software for plant phenology prediction and mapping (PPMaP) that inputs data obtained from multi-location field experiments to derive models for any crop variety. This information can then be applied consecutively at a localized grid within a spatial framework to produce plant phenology predictions at the landscape level. This software supports the development of process-oriented and temperature-driven plant phenology models by intuitively and interactively leading the user through a step-by-step progression to the production of spatial maps for any region of interest. Maize (Zea mays L.) was used to demonstrate the robustness, versatility, and high computing efficiency of the resulting modeling outputs of the PPMaP. The framework is implemented in R, providing a flexible and easy‐to‐use GUI interface. Since this allows appropriate scaling to the larger spatial domain, the software can effectively be used to determine the spatially explicit length of growing period (LGP) of any variety.

This paper addresses the evolving landscape of electricity markets in Europe, with a focus on the integration of Renewable Energy Communities as introduced by the Renewable Energy Directive 2018/2001. Residents within a postal code area are highly incentivized to join a community, which enables them to exchange energy among themselves at lower procurement costs. Thereby, energy management systems optimize the operation of respective energy systems, with electrical load forecasting playing a key role. Given that prosumers may switch between communities on a daily basis, electricity demands within these groups will vary, leading to data that is non-stationary, discontinuous as well as non-identical and independently distributed. To encounter this issue, we propose a sophisticated forecasting model that applies federated learning, using informations from various distributed communities to learn domain-invariant features. To achieve this, we initially utilize synthetic electrical load time series at district level and aggregate them to profiles of Renewable Energy Communities with dynamic portfolios. Subsequently, we develop a forecasting model that accounts for the composition of residents of a Renewable Energy Community, adapt data pre-processing in accordance with the time series process, and detail a federated learning algorithm that incorporates weight averaging and data sharing. Following the training of various experimental setups, we ultimately evaluate their effectiveness. The findings suggest that our proposed framework is capable of effectively forecast non-stationary and discontinuous time series and that it can be applied to new, unseen data through the integration of knowledge from multiple sources.

In this study, the Bohler K 190 steel was used. The steel was manufactured by the powder metallurgy (PM) process. The boronizing process was carried out in the range of 1173 to 1323 K, for 1-10 h. The samples were boronized in solid medium, called the Durborid powder mixture. For the microstructural observations, the scanning electron microscopy was utilized for determining the morphology of interfaces and measuring the layers’ thicknesses. The phase composition of boride layers was also determined with X-ray diffraction analysis. To investigate the redistribution of chemical elements redistribution during the boronizing process, the EDS mapping and EDS point analysis were used. The boride layers were constituted by FeB and Fe2B phases except for 1173 K for 1 h. The values of Vickers microhardness of Fe2B, FeB and transition zone were estimated. Finally, to assess the boron activation energies in FeB and Fe2B, the so-called integral method was applied and the results in terms of activation energies were confronted with the literature data.

This study focuses on the optimal deployment problem, and determines the optimal size of a military force to send to the battle field. The decision is optimized, based on an objective function, that considers the cost of deployment, the cost of the time it takes to win the battle, and the costs of killed and wounded soldiers with equipment. The cost of deployment is modeled as an explicit function of the number of deployed troops and the value of a victory with access to a free territory, is modeled as a function of the length of the time it takes to win the battle. The cost of lost troops and equipment, is a function of the size of the reduction of these lives and resources. An objective function, based on these values and costs, is optimized, under different parameter assumptions. The battle dynamics is modeled via the Lanchester differential equation system based on the principles of directed fire. First, the deterministic problem is solved analytically, via derivations and comparative statics analysis. General mathematical results are reported, including the directions of changes of the optimal deployment decisions, under the influence of alternative types of parameter changes. Then, the first order optimum condition from the analytical model, in combination with numerically specified parameter values, is used to determine optimal values of the levels of deployment in different situations. A concrete numerical case, based on documented facts from the Battle of Iwo Jima, during WW II, is analyzed, and the optimal US deployment decisions are determined under different assumptions. The known attrition coefficients of both armies, from USA and Japan, and the initial size of the Japanese force, are parameters. The analysis is also based on some parameters without empirical documentation, that are necessary to include to make optimization possible. These parameter values are motivated in the text. The optimal solutions are found via Newton- Raphson iteration. Finally, a stochastic version of the optimal deployment problem is defined. The attrition parameters are considered as stochastic, before the deployment decisions have been made. The attrition parameters of the two armies have the same expected values as in the deterministic analysis, are independent of each other, have correlation zero, and have relative standard deviations of 20%. All possible deployment decisions, with 5000 units intervals, from 0 to 150000 troops, are investigated, and the optimal decisions are selected. The analytical, and the two numerical, methods, all show that the optimal deployment level is a decreasing function of the marginal deployment cost, an increasing function of the marginal cost of the time to win the battle, an increasing function of the marginal cost of killed and wounded soldiers and lost equipment, an increasing function of the initial size of the opposing army, an increasing function of the efficiency of the soldiers in the opposing army and a decreasing function of the efficiency of the soldiers in the deployed army. With stochastic attrition parameters, the stochastic model also shows that the probability to win the battle is an increasing function of the size of the deployed army. When the optimal deployment level is selected, the probability of a victory is usually less than 100%, since it would be too expensive to guarantee a victory with 100% probability. Some of many results of relevance to the Battle of Iwo Jima, are the following: In the deterministic Case 0 analysis, the optimal US deployment level is 66200, the time to win the battle is 30 days and 14000 US soldiers are killed or wounded. If the marginal cost of the time it takes to win a victory doubles, the optimal deployment increases to 75400, the time to win a victory is reduced to 26 days, and less than 12000 soldiers are killed or wounded. In the stochastic Case 0 analysis, the optimal US deployment level is 65000, the expected time to win the battle is 46 days and almost 25000 US soldiers are expected to be killed or wounded. If the cost per killed or wounded soldier increases from 0 to 5 M $US, the optimal deployment level increases to 75000. Then, the victory is expected to appear after 35 days and 19900 US soldiers are expected to be killed or wounded.

Rare Earth Elements (REE), also known as Lanthanides (Ln3+), are a group of 17 elements showing peculiar physical and chemical properties. Unlike technological applications, very little is known about the physiological role and toxicity of Ln3+ on biological systems, in particular on microorganisms (e.g., bacteria), which represent the most abundant domains on our planet. Up to now, very limited studies have been conducted due to Ln3+ precipitation with some anions commonly present in the culture media. Therefore, the development of a minimal medium is essential to allow the study of Ln3+-microbial interactions, limiting considerably the precipitation as insoluble salts. In this regard, a new minimal culture medium capable of solubilizing large amounts of Ln3+, and allowing the growth of different microbial taxa, was successfully developed. Assays have shown that the medium is capable of solubilizing Ln3+ up to 100 times more than other common culture media and allowed the growth of 63 bacteria and 5 fungi. The kinetic growth of one yeast and one gram-positive bacterium has been defined, proving to support superior growth and biomass compared to other commonly used minimal media. Moreover, the sensitivity and uptake/absorption of a Bacillus stratosphericus strain was tested, highlighting its capability to tolerate concentrations up to 10 mM of either Cerium, Gadolinium or Lanthanum and accumulate different quantities of the three.

This paper directly addresses a long-standing issue that affects the development of many complex distributed software systems: how to establish quickly, cheaply, and reliably whether they can deliver their intended performance before expending significant time, effort and money on detailed design and implementation. We describe ∆QSD, a novel metrics-based and quality-centric paradigm that uses formalised outcome diagrams to explore the performance consequences of design decisions, as a performance blueprint of the system. The distinctive feature of outcome diagrams is that they capture the essential observational properties of the system, independent of the details of system structure and behaviour. The ∆QSD paradigm derives bounds on performance expressed as probability distributions encompassing all possible executions of the system. The ∆QSD paradigm is both effective and generic: it allows values from various sources to be combined in a rigorous way, so that approximate results can be obtained quickly and subsequently refined. ∆QSD has been successfully used by Predictable Network Solutions for consultancy on large-scale applications in a number of industries, including telecommunications, avionics, and space and defence, resulting in cumulative savings worth billions of US dollars. The paper outlines the ∆QSD paradigm, describes its formal underpinnings, and illustrates its use via a topical real-world example taken from the blockchain/cryptocurrency domain. ∆QSD has enabled challenging throughput targets to be met for a globally distributed blockchain operating on the public internet.

A proxy war, between a coalition of countries, BLUE and a country, RED, is considered. RED wants to increase the size of the RED territory. BLUE wants to involve more regions in trade and other types of cooperation. GREEN is a small and independent nation that wants to become a member of BLUE. RED attacks GREEN and tries to invade. BLUE decides to give optimal arms support to GREEN. This support can help GREEN in the war against RED and simultaneously reduce the military power of RED, which is valuable to BLUE, also outside this proxy war, since RED may confront BLUE also in other regions. The optimal control problem of dynamic arms support, from the BLUE perspective, is defined in general form. The objective function is a weighted sum of the present value of the free GREEN territory and the present value to BLUE of the net loss of military resources in the RED army. The net loss of RED at a particular point in time is a function of the location of the front line and the size of the mobile GREEN forces behind the RED line. First, it is assumed that the expected net loss is proportional to the force ratio behind the red front line. It is proved that the net loss function is a strictly concave quadratic function of x, the location of the front line. It is also proved that the unique maximum of the net loss function occurs at the same front location, also if the net loss function is proportional to the strength ratio behind the RED lines, raised to any strictly positive exponent. From the BLUE perspective, there is an optimal position of the front. This position is a function of the weights in the objective function and all other parameters. Optimal control theory is used to determine the optimal dynamic BLUE strategy, conditional on a RED strategy, which is observed by BLUE military intelligence. The optimal arms support strategy for BLUE is to initially send a large volume of arms support to GREEN, to rapidly move the front to the optimal position. Then, the support should be almost constant during most of the war, keeping the war front location stationary. In the final part of the conflict, when RED will have almost no military resources left and tries to retire from the GREEN territory, BLUE should strongly increase the arms support and make sure that GREEN rapidly can regain the complete territory and end the war

Current methods for assessing individual well-being in team collaboration at the workplace rely often on manually collected surveys. This limits continuous real-world data collection and proactive measures to improve team member workplace satisfaction. We propose a method to automatically derive social signals related to individual well-being in team collaboration from raw audio and video data collected in teamwork contexts. The goal is to develop computational methods and measurements to facilitate the mirroring of individuals’ well-being to themselves. We are focusing on how speech behavior is perceived by team members to improve their well-being. Our main contribution is the assembly of an integrated toolchain to perform multi-modal extraction of robust speech features in noisy field settings and to find which features are predictors of self-reported satisfaction scores. We apply the toolchain to a case study where we collected videos of 22 teams with 56 participants collaborating over a four-day period in a team project. Our audiovisual speaker diarization extracts individual speech features in a noisy environment. As the dependent variable team members filled out a daily PERMA (positive emotion, engagement, relationships, meaning, and accomplishment) survey. These well-being scores have been predicted with speech features extracted from the videos using machine learning. The results suggest that the proposed toolchain is able to automatically predict individual well-being in teams, leading to better teamwork and happier team members.

A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article's main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

How does the world around us work and what is real? This question has preoccupied humanity since its beginnings. From the 16th century onwards, it has been periodically necessary to revise the prevailing worldview. But things became very strange at the beginning of the 20th century with the advent of relativity theory and quantum physics. The current focus is on the role of information, there being a debate about whether this is ontological or epistemological. A theory has recently been formulated in which spacetime and gravity emerges from microscopic quantum information, more specifically from quantum entanglement via entanglement entropy. A latest theory describes the emergence of reality itself through first-person perspective experiences and algorithmic information theory. In quantum physics, perception and observation play a central role. Perception, interaction with the environment, requires an exchange of information. Via biochemical projection, information is given an interpretation that is necessary to make life and consciousness possible. The world around us is not at all what it seems.

When discussing the concepts of risk, safety, and security, people have an intuitive understanding of what these concepts mean, and, to a certain level, this understanding is universal. However, when delving into the real meaning of these concepts, one is likely to fall into semantic debates and ontological discussions. In industrial parks, it is important that (risk) managers from dierent companies, belonging to one and the same park, have the same understanding of the concepts of risk, safety, and security. It is even important that all companies in all industrial parks share a common understanding regarding these issues. As such, this paper explores the similarities and dierences behind the perceptions of these concepts, to come to a fundamental understanding of risk, safety, and security, proposing a semantic and ontological ground for safety and security science, based on an etymological and etiological study of the concepts of risk and safety. The foundation has been induced by the semantics used in the ISO 31000 risk management guidance standard. Hence, this article proposes a coherent, standardized set of concepts and definitions with a focus on the notion “objectives” that can be used as an ontological foundation for safety and security science, linking “objectives” with the concepts of safety, security, risk, performance and also failure and success, theoretically allowing for an increasingly more precise understanding and measurement of (un)safety across the whole range of individuals, sectors and organizations, or even society as a whole.

Rice bran arabinoxylan compound (RBAC) is a polysaccharide modified by Lentinus edodes mycelial enzyme widely used as a nutraceutical. To explore translational research on RBAC, a scoping review was conducted to synthesise research evidence from English, Japanese, Korean, and Chinese sources while combining bibliometrics and network analyses for data visualisation. Ninety-eight articles on RBAC and the biological activities related to human health or disease were included. Research progressed with linear growth (median=3/year) from 1998 to 2022, predominantly on Biobran MGN-3 (86.73%) and contributed by 289 authors from 100 institutions across 18 countries. Clinical studies constitute 61.1% of recent articles (2018 to 2022). A shifting focus from immuno-cellular activities to human translations over the years was shown via keyword visualisation. Beneficial effects of RBAC include immunomodulation, synergistic anticancer properties, hepatoprotection, antiinflammation, and antioxidation. Cancer patients reported reduced side effects from chemoradiotherapy and improved quality of life in human studies, indicating RBAC’s impact on the psycho-neuro-immune axis. RBAC has been studied in 17 conditions, including cancer, liver diseases, HIV, allergy, chronic fatigue, gastroenteritis, cold/flu, diabetes, and in healthy participants. Further translational research on the impact on patient and community health is required for the evidence-informed use of RBAC in health and disease.

Rising antimicrobial resistance (AMR) in Salmonella serotypes host-adapted to cattle is of increasing concern to the beef and dairy industry. The bulk of the existing literature focuses on AMR post-slaughter. In comparison, the understanding of AMR in Salmonella among pre-harvest cattle is still limited, particularly in Texas, which ranks top five in beef and dairy exports in the United States; inherently, the health of Texas cattle has nationwide implications for the health of the United States beef and dairy industry. In this study, long-read whole genome sequencing and bioinformatic methods were utilized to analyze antimicrobial resistance genes (ARGs) in 98 isolates from beef and dairy cattle in the Texas Panhandle. Fisher exact tests and elastic net models accounting for population structure were used to infer associations between ARGs and antimicrobial phenotypic profiles and metadata. Gene mapping was also performed to assess the role of mobile genetic elements in harboring ARGs. ARG were found to be statistically different between the type of cattle operation and Salmonella serotypes. Beef operations were statistically significantly associated with more resistance genes compared to dairy operations. Salmonella Heidelberg, followed by Salmonella Dublin isolates, were associated with the most ARGs. Additionally, specific classes of ARGs were only present within mobile genetic elements.

Designing the future energy supply in accordance with ambitious climate change mitigation goals is a challenging issue. Common tools for planning and calculating future investments in renewable and sustainable technologies are often linear energy system models based on cost optimisation. However, input data and the underlying assumptions of future developments are subject to uncertainties that negatively affect the robustness of results. This paper introduces a quadratic programming approach to modifying linear, bottom-up energy system optimisation models in order to take cost uncertainties into account. This is accomplished by implementing specific investment costs as a function of the installed capacity of each technology. In contrast to established approaches like stochastic programming or Monte Carlo Simulation, the computation time of the quadratic programming approach is only slightly higher than that of linear programming. The model’s outcomes were found to show a wider range as well as a more robust allocation of the considered technologies than the linear model equivalent.

Current antibiograms cannot discern the particular effect of a specific antibiotic when the bacteria are incubated with a mixture of antibiotics. To prove that this task is achievable, Escherichia coli strains were treated with ciprofloxacin for 45 min, immobilized on a slide and stained with SYBR Gold. In susceptible strains, the nucleoid relative surface started to decrease near the MIC, being progressively condensed as dose increased. The shrinkage level correlated with the DNA fragmentation degree. Ciprofloxacin-resistant bacilli showed no change. Additionally, E. coli strains were incubated with ampicillin for 45 min and processed similarly. The ampicillin-susceptible strain revealed intercellular DNA fragments that increased with dose, unlike the resistant strain. Co-incubation with both antibiotics revealed that ampicillin did not modify the nucleoid condensation effect of ciprofloxacin, whereas the quinolone partially decreased the background of DNA fragments induced by ampicillin. Sixty clinical isolates, with different combinations of susceptibility-resistance to each antibiotic, were co-incubated with the EUCAST breakpoints of susceptibility of ciprofloxacin and ampicillin. The morphological assay correctly categorized all the strains for each antibiotic in 60 min, demonstrating the feasible independent evaluation of a mixture of quinolone and beta-lactam. The rapid phenotypic assay may shorten the incubation times and necessary microbial mass currently required for evaluation.

Gas chromatography-coupled mass spectrometry (GC-MS) has been used in biomedical research to analyze volatile, non-polar, and polar metabolites in a wide array of sample types. Despite advances in technology, missing values are still common in metabolomics datasets and must be properly handled. We evaluated the performance of ten commonly used missing value imputation methods with metabolites analyzed on an HR GC-MS instrument. By introducing missing values into the complete (i.e., data without any missing values) NIST plasma dataset we demonstrate that Random Forest (RF), Glmnet Ridge Regression (GRR), and Bayesian Principal Component Analysis (BPCA) shared the lowest Root Mean Squared Error (RMSE) in technical replicate data. Further examination of these three methods in data from baboon plasma and liver samples demonstrated they all maintained high accuracy. Overall, our analysis suggests that any of the three imputation methods can be applied effectively to untargeted metabolomics datasets with high accuracy. However, it is important to note that imputation will alter the correlation structure of the dataset, and bias downstream regression coefficients and p-values.

While the angiotensin converting enzyme 2 (ACE2) protein is defined as the primary severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) receptor, the viral serine molecule might be mobilized by the host's transmembrane protease serine subtype 2 (TMPRSS2) enzyme from the viral spike (S) protein and hijack the host’s N-acetyl-D-galactosamine (GalNAc) metabolism. The resulting hybrid, serologically A-like/Tn (T-nouvelle) structure potentially acts as a host–pathogen functional molecular bridge. In humans, this intermediate structure will hypothetically be replaced by ABO(H) blood group-specific, mucin-type structures, in the case of infection hybrid epitopes, implicating the phenotypically glycosidic accommodation of plasma proteins. The virus may, by mimicking the synthetic pathways of the ABO(H) blood groups, bind to the cell surfaces of the blood group O(H) by formation of a hybrid H-type antigen as the potential precursor of hybrid non-O blood groups, which does not affect the highly anti-glycan aggressive anti-A and anti-B isoagglutinin activities, exerted by the germline-encoded nonimmune immunoglobulin M (IgM). In the non-O blood groups, which have developed from the H-type antigen, these IgM activities are downregulated by phenotypic glycosylation, while adaptive immunoglobulins might arise in response to the hybrid A and B blood group structures, bonds between autologous carbohydrates and foreign peptides, suggesting the exertion of autoreactivity. The non-O blood groups thus become a preferred target for the virus, whereas blood group O(H) individuals, lacking the A/B phenotype-determining enzymes and binding the virus alone by hybrid H-type antigen formation, have the least molecular contact with the virus and maintain the critical anti-A and anti-B isoagglutinin activities, exerted by the ancestral IgM, which is considered the humoral spearhead of innate immunity.

When participants in a statistical learning paradigm are asked to learn from two incompatible or competing inputs, they often fail to learn from one or both inputs. This study presents the results of two experiments that were both completed by one group of typically developing four-year-old children. One experiment targeted word-medial consonant patterns (phonotactics), whereas the other targeted strong-weak and weak-strong stress patterns (prosody). The order of the experiments was critical for learning outcomes in the phonotactics experiment: When children learned phonotactics first, their production accuracy increased following exposure to a high frequency input. When children learned phonotactics second, however, their production accuracy dropped when they were exposed to the high frequency input. Results from the prosody experiment were inconclusive, with limited evidence of any learning effect. Overall, the results suggest that children may conflate learning experiences, and patterns learned from an initial experimental input compete with patterns in a subsequent experiment. When considering natural language acquisition, the results suggest that an isolated episode of learning may lead to generalizations that are incompatible with later input, and possibly, with larger patterns in the language.

Cutaneous wound healing is a complex multi-stage process involving direct and indirect cell communication events with the aim of efficiently restoring the barrier function of the skin. One key aspect in cutaneous wound healing is associated with cell movement and migration into the physically, chemically and biologically injured area resulting in wound closure. Understanding the conditions under which cell migration is impaired and elucidating the cellular and molecular mechanisms that improve healing dynamics is therefore crucial in devising novel therapeutic strategies to elevate patient suffering, reduce scaring and eliminate chronic wounds. Following the global trend towards automation, miniaturization and integration of cell-based assays into microphysiological systems, conventional wound healing assays such as the scratch assay or cell exclusion assay have recently been translated and improved using microfluidics and lab-on-a-chip technologies. These miniaturized cell analysis systems allow precise spatial and temporal control over a range of dynamic microenvironmental factors including shear stress, biochemical and oxygen gradients to create more reliable in vitro models that resemble the in vivo microenvironment of a wound more closely on a molecular, cellular, and tissue level. The current review provides (a) an overview on the main molecular and cellular processes that take place during wound healing, (b) a brief introduction into conventional in vitro wound healing assays, and (c) a perspective on future cutaneous and vascular wound healing research using microfluidic technology.

The rising global incidence of acute and chronic kidney diseases has increased the demand for renal replacement therapy. This issue, compounded with the limited availability of viable kidneys for transplantation, has propelled the search for alternative strategies to address the growing health and economic burdens associated with these conditions. In the search for such alternatives, significant efforts have been devised to augment the current and primarily supportive management of renal injury with novel regenerative strategies. For example, gene- and cell-based approaches that utilize recombinant peptides/proteins, gene, cell, organoid, and RNAi technologies have shown promising outcomes primarily in experimental models. Supporting research has also been conducted to improve our understanding of the critical aspects that facilitate the development of efficient gene- and cell-based techniques that the complex structure of the kidney has traditionally limited. This manuscript is intended to communicate efforts that have driven the development of such therapies by identifying the vectors and delivery routes needed to drive exogenous transgene incorporation that may support the treatment of acute and chronic kidney diseases.

The Industrial Internet of things (IIoT) enabled smart system has entered into a golden era of rapid technology growth. IIoT is a concept to make every system interrelated such that they are able to collect and transfer data over a wireless network without human intervention. In this paper, we discuss the development of an IoT enabled system to monitor the vibration signature of equipment as part of prognosis and availability management system (P&AM) that serves to prevent unplanned operation downtime and catastrophic failure of a whole system. In order to simply the complexity of processing video content and performing inference, the Intel OpenVINO platform was selected because of it’s simplicity, portability across Intel AI processors, performance and comprehensiveness of it’s analytical and diagnostics capabilities that can be tested in Intel’s DevCloud. The IIoT system consists of a High Performance Computing (HPC) platform based on Intel’s Xeon processors and Movidius AI accelerator, Intel’s OpenVINO toolkit for AI, a Regul high performance programmable controller capturing vibration data through sensors and a low-latency network connection. Notifications of anomalies are sent to a smartphone. This paper reveals an approach for the features extraction and selection, known as feature engineering, of the equipment component we want to protect. Feature engineering is the first step for the P&AM of these components and extends to the whole system. The broader aim of this paper is to help technical leaders at the exploring or experimenting stages of their AI framework to learn the concepts of implementing algorithms using datasets that have real value to their companies. Datasets generated and referred to in this paper were generated by simulation under various material failure scenarios.

We propose two methods for obtaining estimations on the minimum distance and covering radius of orthogonal arrays. Both methods are based on knowledge about the (feasible) sets of distance distributions of orthogonal arrays with given length, cardinality, factors and strength. New bounds are presented either in analytic form and as products of an ongoing project for computation and investigation of the possible distance distributions of orthogonal arrays with parameters in doable ranges.

We present a case of adult-onset systemic chronic active EBV disease (CAEBV) in a 40-year-old woman with chronic HBV hepatitis. Initial symptoms resembled a viral illness, progressing to recurrent fever, transaminitis, and anasarca. Investigations revealed high-level EBV viremia and an abnormal T-cell population in liver and bone marrow, indicative of CAEBV. Liver biopsy showed CD3+ T-cells lacking TCRbeta and displaying dim/negative CD5, with elevated EBV-infected T-cells. Next-generation sequencing identified rare variants in CREBBP, SPEN, TP73, and PLCG2, suggesting potential contributions to disease pathogenesis. This case underscores diagnostic challenges and management complexities of adult-onset CAEBV, particularly with underlying chronic HBV infection. Genomic profiling offers crucial insights into the molecular landscape of rare lymphoid malignancies, highlighting the importance of personalized treatment strategies. The distinct immunophenotypic features underscore the heterogeneity in EBV-associated T-cell LPDs, urging further research for optimized clinical management

The use of pain relief during castration and dehorning of calves on commercial beef operations can be limited by constraints associated with the delivery of analgesic agents. As topical anaesthetic (TA) and buccal meloxicam (MEL) are now available in Australia, offering practical analgesic treatments for concurrent castration and dehorning of beef calves, a study was conducted to determine their efficacy in providing pain relief when applied alone or in combination. Weaner calves were randomly allocated to; (1) no castration and dehorning / positive control (CONP); (2) castration and dehorning / negative control (CONN); (3) castration and dehorning with buccal meloxicam (BM); (4) castration and dehorning with topical anaesthetic (TA); and (5) castration and dehorning with buccal meloxicam and topical anaesthetic (BMTA). Weight gain, paddock utilisation, lying activity and behaviour following treatment were measured. CONP and BMTA calves had significantly greater weight gain than CONN calves (P < 0.001). CONN calves spent less time lying compared to BMTA calves on all days (P < 0.001). All dehorned and castrated calves spent more time walking (P = 0.024) and less time eating (P < 0.001) compared to CONP calves. There was a trend for CONP calves to spend the most time standing and CONN calves to spend the least time standing (P = 0.059). There were also trends for the frequency of head turns to be lowest in CONP and BMTA calves (P = 0.098) and tail flicks to be highest in CONN and BM calves (P = 0.061). The findings of this study suggest that TA and MEL can improve welfare and production of calves following surgical castration and amputation dehorning.

Urban transit planning is going through a transition to greater private investment in many parts of the world and is now on the agenda in Australia. After showing examples of private investment in transit globally the paper focuses on historical case studies of private rail investment in Western Australia. These case studies mirror the historical experience in rapidly growing railway cities in Europe, North America and Asia (particularly Japan), and also the land grant railways that facilitated settlement in North America. The Western Australian experience is noteworthy for the small but rapidly growing populations of the settlements involved, suggesting that growth, rather than size, is the key to successfully raising funding for railways through land development. The paper shows through the history of transport, with particular reference to Perth, that the practice of private infrastructure provision can provide lessons for how to enable this again. It suggests that new partnerships with private transport investment as set out in the Federal Government City Deal process, should create many more opportunities to improve the future of cities through once again integrating transit, land development and private finance.

Pharmaceuticals contain biologically active components that can pollute water courses as a result of the excretions from individuals and/or uncontrolled release of residues from chemical plants, and they can pose a hazard to health. Pharmaceutical residues can persist at low concentrations in the environment, and thus may be potentially harmful to aquatic animals and to humans. Controlling and monitoring such residues are therefore a prime interest, for example, a solid-phase extraction uses solid sorbents to purify and preconcentrate the residues prior to their chemical analysis. In the present study, poly (acrylonitrile-co-divinylbenzene-80) sorbents are synthesised by varying the comonomer feed ratios under precipitation polymerisation conditions to deliver a family of porous polymer microspheres. Acrylonitrile confers polar characters onto the sorbents, and the acrylonitrile-derived nitrile groups can be chemically transformed via polymer-analogous reactions into thioamide and sulfonated residues which make the sorbents even more suitable for the capture of polar analytes, including selected pharmaceuticals. The utility of the porous thioamide-sulfonated containing sorbents is demonstrated via the dispersion-solid phase extraction of mefenamic acid from aqueous media; mefenamic acid is an anthranilic acid derivative which is a potent, non-steroidal anti-inflammatory drug which is found in environmental waters at low concentrations.