The paper analyses the national DK-model Hydrological Information and Prediction (HIP) system and HIP portal viewed as a ‘Digital Twin’ and how the introduction of real-time dynamic updating of the DK-model HIP simulations can give room for plug-in sub-models with real-time boundary conditions made available from a HIP portal. The possible feedback to a national real-time risk knowledge base during extreme events (flooding and drought) is also discussed. Under climate change conditions, Denmark is likely to experience more rain in winter, more evapotranspiration in summer, intensified cloudbursts, drought, and sea level rise. These challenges have been addressed as part of the Joint Governmental Digitalization Strategy 2016-2020 for better use and sharing of public data about the terrain, water, and climate to support climate adaptation, water management, and disaster risk reduction. This initiative included the development of a new web-based data portal (HIP portal) developed by the Danish Agency for Data Supply and Infrastructure (SDFI). GEUS delivered 5 terra-byte of hydrological model data to the portal with robust calibration methods and hybrid Machine Learning (ML) being key parts of the deliverables. The paper discusses the challenges and potentials of further developing the HIP Digital Twin with ‘plug-in Digital Twins’ for local river basins including feedback to the national level.

Among the various types of gas sensors, the chemoresistive gas sensors based on metal oxides are considered the most attractive ones due to their simple operation, low costs and miniaturization. Thin films of V2O5 undoped and doped with TiO2 were studied as nitrogen dioxide, methane and hydrogen sensors. The experimental kinetics of the electrical conductivity changes due to introduction and removal of gas on metal oxide gas sensors were successfully explained in terms of the Langmuir adsorption theory.

Higher concentrations of greenhouse gases resulting from anthropogenic actions associated with energy generation are one of the causes of climate change. In view of this, several efforts have been undertaken in the search for more sustainable alternatives, and photovoltaic (PV) technology has stood out among the different possibilities. However, PV generation is highly sensitive to future climate variability, which is a source of uncertainty that can complicate energy planning and compromise the viability of systems. This theme has received attention from the academic community, but some challenges to map and identify relevant literature have been encountered. Therefore, this study was conducted to analyze and identify relevant aspects of international scientific production on the impacts of climate change on the potential of photovoltaic production, CC-PVP, through bibliometric techniques. For this, 3900 articles from the Web of Science and Scopus databases, published between 1960 and 2021, were retrieved and analyzed through a bibliometric approach, using the SciMAT tool. Among the results obtained, it is worth pointing out that the CC-PVP research field (i) has moderate maturity, (ii) is concentrated in the areas of energy, fuels and technology, as well as environmental sciences and meteorology, (iii) has the most studied themes currently related to energy and the forecasting of photovoltaic energy production and electric energy consumption in the world, especially when considering climate change, and (iv) is more researched by Chinese, North Americans and Australians.

The advancement of autonomous capabilities in maritime navigation has gained significant attention, with a trajectory moving from decision support systems to full autonomy. This push towards autonomy has led to extensive research focusing on collision avoidance, a critical aspect of safe navigation. Among the various possible approaches, Dynamic Programming is a promising tool for optimizing collision avoidance maneuvers. This paper presents a DP formulation for collision avoidance of autonomous vessels. We set up the problem framework, formulate it as a multi-stage decision process, define cost functions and constraints focusing on the actual requirements a marine maneuver must comply with, and propose a solution algorithm leveraging parallel computing. Additionally, we present a greedy approximation to reduce algorithm complexity. Through case studies, we demonstrate the effectiveness of the proposed approach in navigating complex scenarios, contributing to the future of autonomous maritime navigation. Through case studies, we show the efficacy of our approach in navigating complex scenarios.

Disulfiram (DSF), an anti-alcoholism medicine, exerts treatment effects in patients suffering from persistent Borreliosis and also exhibits anti-cancer effects by its copper chelating derivatives. Since chronic/persistent borreliosis is characterized by increased amounts of proinflammatory macrophages, this study investigated opsonin-independent phagocytosis, migration and surface marker expression of in vivo activated human monocyte-derived macrophages and dendritic cells with and without DSF treatment. Phagocytosis of non-opsonized Dynabeads® M-450 and migration of macrophages and dendritic cells were monitored using live cell analyzer Juli™ Br for 24h by imaging every 3.5 min. Results were analyzed by a newly developed software based on the differential phase contrast images of cells before and after ingestion of Dynabeads bearing an electron dense iron core. As a control, phagocytosis was also monitored by visual counting of ingested beads. DSF decreased the phagocytic capacities exhibited by global macrophages and dendritic cells. DSF also impaired the migration of human monocyte-derived macrophages and dendritic cells (hMDMD) and significantly reduced the expression densities of surface antigens CD45 and CD14. In cells consisting of anti-inflammatory M2 macrophages, DSF led to a remarkable cell death and also increased oxidative stress as determined by MitoSox staining. Mitochondrial oxidative stress was a prominent feature in M2 macrophages which were more sensitive to DSF-induced cytotoxicity.

Visualization of volumetric data holds great importance, particularly in medical and biomedical applications. Various imaging techniques, such as FMRI and 3D microscopy, are employed to generate volumetric data, used in medical practice, research, and teaching. Commonly utilized tools like 3D Slicer, Fiji, and MATLAB ® aid in rendering and analyzing 3D images. However, these tools may lack comprehensive rendering functionality and face challenges in handling computational demands as data sizes grow. To address these limitations, this work introduces a GPU-supported renderer with a MATLAB ® interface. This solution gives the user flexible control over rendering parameters and optimizes data transfer through a memory management system. By leveraging the computational power of NVIDIA GPUs, the renderer enables complex and high-quality renderings, enhancing speed and efficiency. It therefore facilitates the analysis and visualization of volumetric data within an integrated environment, namely MATLAB ®, streamlining their workflows. This advancement provides valuable opportunities for researchers and medical professionals to explore and comprehend volumetric data effectively.

Predicting human trajectories poses a significant challenge due to the complex interplay of pedestrian behavior, which is influenced by environmental layout and interpersonal dynamics. This complexity is further compounded by variations in scene density. To address this, we introduce a novel dataset from the Festival of Lights in Lyon 2022, characterized by a wide range of densities (0.2-2.2 ped/m2). Our analysis demonstrates that density-based classification of data can significantly enhance the accuracy of predictive algorithms. We propose an innovative two-stage processing approach, surpassing current state-of-the-art methods in performance. Additionally, we utilize a collision-based error metric to better account for collisions in trajectory predictions. Our findings indicate that the effectiveness of this error metric is density-dependent, offering prediction insights. This study not only advances our understanding of human trajectory prediction in dense environments but also presents a methodological framework for integrating density considerations into predictive modeling, thereby improving algorithmic performance and collision avoidance.

This research paper contributes to the literature of deterrence theory in general, and in particular with respect to white-collar crime, offering valuable inside by using a unique data set of fraud and violation of trust incidents for Paraguay. Descriptive evidence show a clear and continuous misallocation of funds and human capital, and therefore providing less efficient services for the public. Regression analysis suggests that clearance rate exerts a highly significant effect in deterring fraud but results are not clear for violation of trust incidents. Despite the limitations of available data, results confirm deterrence theory in Paraguay. However, to more than two-thirds of victims, not even the attempt was made to seek justice. As a side-result, it seems that a soft on crime strategy, induced from the former German penal code, has led to an increasing share of pre-trial diversion and therefore enhancing white-collar crimes like fraud and violation of trust due to impunity.

Background: Inappropriate use of antibiotics has been reported to contribute to the emergence and increase of antimicrobial resistance (AMR) in the world. Antibiotics are prescription-only medicines to be dispensed to a person with a legal prescription inscribed by a qualified medical practitioner. Enforcing the dispensing of antibiotics with prescription is a way to promote the rational use of antibiotics and preventing the development and spread of AMR. It is, therefore, the responsibility of a pharmacist to dispense or supervise the dispensing of antibiotics in pharmacies and ensure its rational use. This study aimed to assess pharmacists’ knowledge, attitude and practice regarding the dispensing of antibiotics without prescription in Tanzania. Methods: An online semi-structured questionnaire was designed, tested and shared with licensed pharmacists in Tanzania through an invitation link sent in their official WhatsApp groups. A list of names, contacts and emails of licensed pharmacists obtained from the Pharmacy Council was used to directly contact and request pharmacist to fill the questionnaire, in case the pharmacist contact was not on WhatsApp, a text SMS invitation was sent. Study data were collected and managed using REDCap electronic data capture tools hosted at Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania. Data were then downloaded and exported into Statistical Package for Social Sciences (SPSS) version 20 for data analysis; Chi-square test was used to test association for categorical data, where a p-value of less than 0.05 was considered statistically significant. Results: More than 75% of pharmacists had excellent knowledge about the legal requirements for dispensing antibiotics and of the AMR challenge. Of the interviewed pharmacists, seventy-four percent admitted to dispensing antibiotics without prescription in their daily practice. The main reasons for administering antibiotics without prescription were the profitability nature of pharmacy business, a failure of the patient to get a prescription and lack of stringent regulatory authorities. Penicillins, macrolides and floroquinolones were the classes of antibiotics mostly dispensed without a prescription. Conclusion: The study shows that the dispensing of antibiotics without prescription is a common practice in Tanzania. The regulatory authorities should make regular inspections in pharmacies to detect this malpractice. The community should be trained on the importance of taking laboratory tests before getting medications for their sickness by a qualified medical practitioner.

Technology then has become a mixed bag for the tourism industry. It creates a great deal of conveniences while at the same time has been used as a way to increase revenues and to lessen customer service, especially for the education of adults in the area of digital competence for the use for advertising the tourist offer of your own units. Modern Education Programs can be a great help in overcoming digital literacy and thus helping to choose a variety of offers that offer free internet advertising. The survey was conducted on the example of Okrug municipality on the Čiovo peninsula in the period from February 2017 to April 2017. 278 private renters participated. The aim of the research was to show that the Program for the Education of Foreign Languages, a specific English language that was organized by the Municipality, contributed to the advertising of its tourist units, thereby contributing to the revenue, ie the occupancy in the number of reservations. The paper used a quantization method, a questionnaire survey. point to the fact that it is necessary to invest in the Education Program so that the older population, in particular, acquires the general level of digital literacy and foreign language learning, for the purpose of finding an adequate media for advertising and strengthening the tourist capital of a municipality.

Electromagnetic interference (EMI) generated by switching operations within high voltage DC (HVDC) converter stations is an issue that has been addressed by CIGRE and methods to manage EMI should be considered in the design phase using electromagnetic modeling techniques. It is shown that method of moments-based techniques that have been used in many previous studies may not be sufficient. Here, the finite-difference time-domain method is used to study the properties of single switching events using a realistic model of an HVDC converter station with special emphasis on determining the impact of the valve hall on shielding EMI. It is shown that the valve hall does not confine high frequency electromagnetic fields to the valve hall; rather it delays them from exiting through bushings in the wall. Further, it is shown that incorporating electromagnetic absorbing material into the valve hall design can significantly reduce EMI outside the converter station.

This study aimed to investigate the effects of forearm postures and elbow joint angles on muscle torque and mechanomyography (MMG) signals. The torque about the elbow and MMG of the biceps brachii (BB) muscle were measured in 36 healthy subjects using an in-house elbow flexion testbed and Neuromuscular electrical stimulation (NMES) of the BB muscle. The BB muscle received stimulation intensity while the forearm was positioned in the neutral, pronation or supination. The elbow was flexed at angles 10°, 30°, 60° and 90°. (0° = full elbow extension). The study analyzed the impact of forearm posture(s) and elbow joint angle(s) on the root mean square value of torque (TQ_RMS). Subsequently, MMG parameters such as the root mean square value (MMG_RMS), the mean power frequency (MMG_MPF), and the median frequency (MMG_MDF), were analyzed in the longitudinal, lateral, and transverse axes of the BB muscle fibers. Forearm posture and elbow flexion angle were found to significantly influence TQ_RMS (P < 0.05). Similarly, MMG_RMS, MMG_MPF and MMG_MDF exhibited a significant difference for all postures and angles (P < 0.05). However, the combined main effect of forearm postures and elbow joint angles was insignificant in the longitudinal axis (P > 0.05). The study also found that MMG_RMS and TQ_RMS increased with the joint angle to 60° and decreased to the other angle(s). However, during this investigation,MMG_MPF and MMG_MDF exhibited a consistent decrease in response to joint angles. This finding suggests that the muscle contraction evoked by NMES may be influenced by the interplay between actin and myosin filaments, which are responsible for muscle contraction and are in turn influenced by muscle length. As restoring the function of limbs is a common goal in rehabilitation services, it becomes imperative to develop methods that may enable the real-time tracking of exact muscle dimensional changes and activation levels.

The rising of an oil drop in a non-Newtonian viscous solution is studied experimentally. In this case, the shape of the ascending drop is strongly affected by the non-Newtonian properties of the surrounding liquid. We found that the so-called velocity discontinuity phenomena is observed for drops larger than a certain critical size. Beyond the critical velocity, the formation of a long tail is observed, from which small droplets are continuously emitted. We determined that the fragmentation of the tail results mainly from the effect of capillary effects. We explore the idea of using this configuration as a new encapsulation technique, where the size and frequency of droplets can be well predicted.

(1) Background: Sensing of critical events or flow signatures in nature often presents itself as a coupled interaction between a fluid and arrays of slender flexible beams, such a wind-hairs or whiskers. It is hypothesized that important information is gained in highly noisy environments by the inter-correlation within the array. (2) Methods: The present study uses a model sea lion head with artificial whiskers in the form of slender beams (optical fibres), which are subjected to a mean flow with overlaid turbulent structures generated in the wake of a cylinder. Motion tracking of the array of fibres is used to analyse the correlation of the bending deformations of pairs of fibres. (3) Results: Cross-correlation of the bending signal from tandem pairs of whiskers proves that the detection of vortices and their passage along the animals head is possible even in noisy environments. The underlying pattern, during passage of a vortex core, is a jerk-like response of the whiskers, which can be found at later arrival-times in similar form in the downstream whisker's response. (4) Conclusion: Coherent vortical structures can be detected from cross-correlation of pairs of cantilever-beam like sensors even in highly turbulent flows. Such vortices carry important information within the environment, e.g. the underlying convection velocity. More importantly in nature, these vortices are characteristic elementary signals left by prey and predators. The present work can help to further develop flow, or critical event, sensory systems which can overcome high noise levels due to the proposed correlation principle.

Multiple studies have shown that hospital settings are poorly cleaned during terminal cleaning. The adequacy of these cleaning methods has been undermined by presence of multi drug resistant bacteria on hospital surfaces. This case is even more serious in developing countries leading to health care- associated infections that pose a great threat to patients, visitors and health care providers in hospital settings.This study used various microbiological techniques to test for antibiotic susceptibility profiles of bacteria present at Thika Level 5 Hospital surfaces, Kenya. A simple random cross sectional study was performed, with a total of 85 samples being collected from five different sites. The sites included male and female wards, health care personnel offices, latrine, and kitchen surfaces. Samples were collected using sterile swabs, dipped in normal saline, and transported to the laboratory within 2Hours for processing.Of the 85 plates cultured, 47 plates showed bacterial growth (55%) on selective media with a significant P value of 0.0357. Seven different species of bacteria were identified biochemically from all sites, Escherichia coli was the most abundant species (28%), and the least was Salmonella typhii (5%). Multiple drug resistance was common in the different bacteria identified. All isolates were resistant to chloramphenical and susceptible to gentamycin. The most resistant microorganism was Staphylococcus aureus (50%), and the least resistant microorganism was Klebsiella pneumoniae (12.5%). The antimicrobial resistant bacterial species identified in this study have been documented to cause serious health care associated infections. These results present a significant public health concern because there is a possibility of patients, staff and visitors contacting nosocomial infections when they come into contact with surfaces at Thika Level 5 Hospital surfaces, Kenya.

An SIRS (Susceptible–Infected–Removed-Susceptible) mathematical model for the transmission dynamics of the Transfusion–Transmitted Malaria (TTM) model with optimal control pair u₁(t) and u₂(t) was developed and studied in this research work. The model Transfusion–Transmitted Malaria disease–free equilibrium and endemic equilibriums points were determined. The model exhibited two equilibriums; disease-free and endemic equilibrium. It is shown that the disease–free equilibrium was locally asymptotically stable if the associated basic reproduction numbers R₀ is less than unity while the disease persists if R₀ is greater than unity. The global stability of the Transfusion–Transmitted Malaria model at the disease-free equilibrium was established using the comparison method. The optimality system was derived and an optimal control model of blood screening and drug treatment for the Transfusion–Transmitted Malaria model was investigated. Conditions for the optimal control were considered using Pontryagin’s Maximum Principle and solved numerically using the Forward and Backward Finite Difference Method (FBDM). Numerical results obtained are in perfect agreement with our analytical results.

Abstract: The broad clinical use of synthetic vascular grafts for vascular diseases is limited by their thrombogenicity and low patency rate, especially for vessels with a diameter inferior to 6 mm. Alternatives such as tissue-engineered blood grafts (TEBGs) have gained increasing interest. Among the different manufacturing approaches, 3D bioprinting presents numerous advantages and enables the fabrication of multi-scale, multi-material, and multicellular tissues with heterogeneous and functional intrinsic structures. Extrusion-, inkjet- and light-based 3D printing techniques have been used for the fabrication of TEBG out of hydrogels, cells, and/or solid polymers. This review discusses the state-of-the-art research on the use of 3D printing for TEBG with a focus on the biomaterials and deposition methods.

Introduction: Frostbite is a condition that mostly affects skin, but also the underlying tissues, resulting from prolonged exposure to temperatures below freezing point (-0.55°C). Although frostbite has been a known phenomenon for several millennia, the exact incidence of frostbite is not known. This is partly due to variable internal and external etiological factors. One of the many consequences of climate change are extreme cold events, which increase the risk of frostbite in the general population, particularly among individuals who are involuntarily exposed to cold for prolonged periods of time. Severe cold injury can lead to deep frostbite with irreversible sequalae such as amputations. Objectives: The reviews objective is to compare data collection and incidence rates of frostbite in different studies and populations. Methods: Out of a total of 61 studies using the keywords "frostbite" and "incidence", 7 were selected that dealt with frostbite causes and incidence over 20 years. The studies results were briefly summarized and their conditions were compared. Results: Frostbite can damage tissue superficially or deeply, depending on its degree. The results of the seven studies show a great variation of frostbite incidence depending on population, its size, and method of data collection. Studies that include the entirety of the civilian population show significantly lower frostbite incidence rates than studies focusing individuals who are exposed to temperatures below -0.55°C for long periods of time, such as mountaineers, military personnel, or homeless people. Although cold injuries are rare, they are becoming increasingly problematic for individuals who are exposed to a cold environment for prolonged periods of time due to climate change. This includes homeless individuals, outdoor workers in cold regions, alpinists and persons with inadequate equipment. The results underline different incidence rates for different populations and show that retrospectively collected data are insufficiently comparable. Enhanced frostbite susceptibility in some individuals should also be considered in the future in order to estimate the frostbite incidence more accurately. Moreover, defining frostbite susceptibility in advance could prevent frostbite incidence in the future to some degree, especially in military operations in the cold and certain leisure activities (e.g. mountaineering). Conclusions: Frostbite poses a significant risk in cold regions and can lead to severe complications without adequate protection. To enhance our ability to predict frostbite occurrences within the general population, it is crucial to understand its incidence in relation to climatic factors. Establishing an international or national frostbite registry in high-risk countries could effectively guide preventive measures and safeguard individuals. This registry should encompass frostbite occurrences alongside contextual elements, such as freezing temperatures and cold exposure duration. Moreover, comprehensive weather conditions like wind chill, precipitation, humidity, and cloud cover must also be considered. When similar external conditions result in frostbite, investigating protective measures becomes pivotal. Furthermore, researching individual susceptibility to cold is essential to discern variations in frostbite vulnerability, especially for activities in cold environments.

We developed a temporal population receptive field model to differentiate the functional and hemodynamic responses in the human LGN. The hemodynamic response of the human LGN is dominated by the richly vascularized hilum, a structure that serves as a point of entry for blood vessels entering the LGN and supplying the substrates of central vision. The location of the hilum along the ventral surface of the LGN and the resulting gradient in the amplitude of the hemodynamic response across the extent of the LGN has made it difficult to segment the human LGN into its more interesting magnocellular and parvocellular regions that represent two distinct visual processing streams. Here, we show that an intrinsic clustering of the LGN responses to a variety of visual input reveals the hilum, and further that this clustering is dominated by the amplitude of the hemodynamic response. We introduce a temporal population receptive field model that includes both a sustained and transient temporal impulse response. When we account for the hemodynamic amplitude, we demonstrate that this temporal response model is able to functionally segregate the residual responses according to their temporal properties.

Background: The 2021 “Universal Definition of Heart Failure (HF)” Proposed the following left ventricle ejection (LVEF) phenotype classification: ≤40%; HF with intermediate LVEF: between 41-49% and HF with preserved LVEF: ≥50%. LVEF represents the percentage of left ventricular ejected volume in each cardiac cycle and Cut-points considered statistically normal are: ≥52% in men and ≥54% in women. The prevalence HFpEF is of 35-60% among the HF phenotypes, with a facing to increase rates in relation to HFrEF and is associated with mortality rates similar to those of HFrEF. The pathophysiology of HFpEF is based on vascular and metabolic dysfunction, therefore, there is less neurohumoral stimulation compared to HFrEF. Methodology: A systematic review was performed to report of information related to Sacubitril-valsartan and the treatment of HFrEF. Terms related to “treatment” and “brazil” were used in the databases PubMed (MEDLINE) and Scientific Electronic Library Online (SCIELO). Results: Clinical trials testing drugs that modulate the neurohumoral system in patients with HFpEF failed to demonstrate benefit in the combined endpoint of reduced mortality/hospitalization due to HF compared to placebo to date. Sacubitril-valsartan is a drug with a mechanism of action surrogate the pathophysiological concept of HFpEF, it is safe and decreased endpoints of natriuretic peptides and left atrial structure in a phase II clinical study. Conclusions: The PARAGON-HF trial demonstrated that sacubitril-valsartan reduced the primary endpoint of the study when assessed the pre-specified subgroup of LVEF≤57% and improved the secondary endpoints of performance status and renal function in the population.

In searching for compounds with antioxidant and antifungal activity, our study focused on the subshrub species Empetrum rubrum Vahl ex Willd. (Ericaceae), commonly known as Brecillo or Murtilla de Magallanes. We measured the antioxidant activity of its methanolic extract (MEE) obtained from the aerial parts (leaves and stems). The antioxidant activity of MEE was evaluated in vitro by 2,2-Diphenyl-1-picrylhydrazyl (DPPH) free radical and 2,2′-Azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) cationic radical. Results were expressed in gallic acid and Trolox equivalents for DPPH and ABTS assays, respectively. The antioxidant activities, for the DPPH and ABTS assays, were also calculated as an inhibitory concentration of extract needed to inhibit 50% of the absorbance (IC50 value). The results of IC50 values measured by the DPPH and ABTS methods were 0.4145 mg mL-1 and 0.1081 mg mL-1, respectively. In relation to the antioxidant activity, the total phenolic content (TPC) in MEE was determined by the Folin-Ciocalteu method, and the presence of secondary metabolites groups, including phenolic compounds, was determined by using different standardized test procedures. Phenolic compounds contained in leaves, stems, and fruits of E. rubrum were determined qualitatively by means of high-performance liquid chromatography coupled with mass spectrometry (HPLC-MS) analysis. The antifungal activity of MEE obtained from aerial parts of E. rubrum was tested against Rhizoctonia solani. In vitro, mycelial growth of this fungus was reduced from 90% to 100% in the presence of MEE.

Ancient reliefs in temple can provide information of past ecosystem along with biodiversity including Makara relief representing crocodile figure. In here, this study aims to identify and model the population of freshwater Crocodylus siamensis as portrayed in reliefs in 6 temples. The result shows that the crocodile reliefs in temples were having similar pattern to the freshwater Crocodylus siamensis fossils in term of locality. The temples and the fossils were located in the inland and near the rivers. While the temple locality patterns were in contrast to the locations where extant saltwater Crocodylus porosus has occurred. These contradictions strengthen the possibility that the crocodile portrayed in reliefs was made based on the C. siamensis occurrences. Based on the analysis, it is estimated that the C. siamensis once has occupied river and wetland in Java and its presence has been recorded in the reliefs. This occurrence at least happened from 1280 to 700 BC. From assessments of habitats near the temples using ᴪ AIC, most surrounding habitats have high detection probability and occupancy for C. siamensis from ᴪ 0.500 (95%CI:0.058-0.941). to ᴪ 1.000 (95%CI:0.000-1.000).

The global predicament of solid waste generation looms as a mounting crisis, profoundly impacting the world, particularly in developing nations. Each day, the world's population contributes millions of tonnes of municipal solid waste, with projections pointing toward further escalation in the coming years. This surge in waste, predominantly composed of cellulose-rich materials, correlates directly with heightened pollution, a threat that transcends borders and imperils humanity as a whole.To confront this ever-growing issue, cellulase, a potent hydrolytic enzyme capable of digesting cellulose, a chief component of solid waste, is explored as a potential solution. In this study, we harness cellulase enzymes derived from the digestive tracts of both Archachatina marginata and Oryctes rhinoceros larvae, employing them as biodegradation agents for cellulose-based waste materials.The cellulase enzymes are methodically isolated and partially purified via ammonium sulfate precipitation at 65% saturation. Their efficacy in breaking down a variety of waste categories, encompassing kitchen waste, leaves, paper, wood, and industrial waste, is meticulously assessed and benchmarked against carboxymethyl cellulose (CMC), a well-established laboratory substrate. The study also ascertains the specific activity of these enzymes.Spectrophotometric analyses of the cellulase enzymes' actions on the diverse waste materials unveil intriguing results. Archachatina marginata and Oryctes rhinoceros larvae exhibit distinct performance metrics, registering percentage ranges of (11.04% - 28.31%) and (33.69% - 189.11%) on wood waste, (76.52% - 196%) and (108.56% - 567.01%) on paper waste, (78.57% - 148.14%) and (163.33% - 436.76%) on leaf waste, (57.16% - 179.95%) and (63.38% - 457.05%) on kitchen waste, and (59.95% - 77.51%) and (117.26% - 155.23%) on industrial waste, respectively. This study underscores the substantial biodegradation potential inherent in cellulase enzymes from both Oryctes rhinoceros larvae and Archachatina marginata when applied to diverse waste materials. While the rates and impacts of waste degradation vary between these sources, their promising contributions to waste management come into focus, offering sustainable and innovative approaches to tackle the pressing global challenge of solid waste proliferation.

Trichomonas vaginalis is an extracellular parasite protozoan that causes human trichomoniasis, a sexually transmitted infection (STI) that affects approximately 200 million people worldwide. The presence of T. vaginalis adhesion to inert substrates has been described in several reports. Still, very few studies on cluster formation and more detailed analyses of the contact regions between the membranes of the parasites in these aggregate formations have not been carried out. We analyzed the formation of parasite monolayers and clusters using high-resolution scanning electron microscopy, transmission electron microscopy, cytochemistry, TEM tomography, and dye injection. Here, we show the formation of a monolayer of tightly adherent cells, epithelium-like, when the parasites are in contact with an inert material. Based on this observation, we analyzed whether this monolayer behaves as an epithelium, analyzing cell junctions, cell communication, and ultrastructural aspects. We also analyzed the cluster formation and the morphological characteristics of parasite aggregation observed in the culture supernatant. We report that monolayer formation differs from cluster formation in many aspects. The monolayers form strong adhesion, whereas the clusters have fragile attachments. There is no fusion or passage of molecules between neighbor-attached cells; there is no need for different strains to form filopodia, cytonemes, and extracellular vesicles during cluster formation.

Abstract: Fertility tracking of menstrual cycles during perimenopause with a quantitative hormone monitor is a novel undertaking. Women in regular menstrual cycles have been tracking their fertility using different biomarkers since the 1960’s [1]. Presently, there are newer electronic hormonal devices used to track fertility that provide more exact and objective data to help delineate the fertile time frame of a woman’s cycle. These devices measure quantitative levels of estrogen, luteinizing hormone, progesterone, and follicle stimulating hormone, all of which occur at varying levels during the menstrual cycle. As women advance toward menopause, their cycles vary in length and their hormones fluctuate [2]. In this retrospective analysis, forty-two women aged 40 to 50 tracked their cycles over time and eight of the forty-two women used the quantitative hormonal device. With the use of this device, the perimenopausal period has revealed distinct hormonal cycle characteristics unique to this group of women. It is the purpose of this paper to discuss those cycle characteristics during perimenopause that were found with the use of the quantitative hormonal device.

Since its initial development in the 1970’s by Phil Burke and his collaborators, the R-matrix theory and associated computer codes have become the de facto approach for the calculation of accurate data for general electron-atom/ion/molecule collision and photoionization processes. The use of a non-orthonormal set of orbitals based on B-splines, now called the B-spline R-matrix (BSR) approach, was pioneered by Zatsarinny. It has considerably extended the flexibility of the approach and improved particularly the treatment of complex many-electron atomic and ionic targets, for which accurate data are needed in many modelling applications for processes involving low-temperature plasmas. Both the original R-matrix approach and the BSR method have been extended to the interaction of short, intense electromagnetic (EM) radiation with atoms and molecules. Here we provide an overview of the theoretical tools that were required to facilitate the extension of the theory to the time domain. As an example of a practical application, we show results for two-photon ionization of argon by intense short-pulse extreme ultraviolet radiation

Research conducted on individuals with depression reveals that major depressive disorders (MDDs) coincide with diminished levels of the inhibitory neurotransmitter γ-aminobutyric acid (GABA) in the brain, as well as modifications in the subunit composition of the primary receptors (GABAA receptors) responsible for mediating GABAergic inhibition. Furthermore, there is substantial evidence supporting the significant role of GABA in regulating stress within the brain, which is a pivotal vulnerability factor in mood disorders. Although there is substantial evidence indicating that GABA may be affecting GABA receptors in peripheral tissues, there is comparatively less evidence supporting its direct action within the brain. Emerging evidence highlights that GABA may exert beneficial effects on the brain and psyche through the gut-brain axis. GABA is readily available and approved as a food supplement in many countries. While GABA enjoys wide consumer acceptance in Eastern Asian markets, with many consumers reporting favorable effects on stress regulation, mood, and sleep, rigorous independent research is still largely lacking. Basic research, coupled with initial clinical findings, makes GABA an intriguing neuro-nutritional compound deserving of clinical studies in individuals with depression and other psychological problems.

As semi-airborne mineral exploration has limited budgets, it is critical to design experimental procedures that generate data maximizing the desired information We investigate the effects of transmitter-receiver geometries for a variety of anomalies and semi-airborne layouts. Our simulations indicate that 200 m flight line spacing and 100 m point distance are the optimal trade-off between coverage and survey progress for various targets. Based on the target size and distance between the transmitter and the target, the transmitter length should be at least equal to the length of the target and for more than 1 km, at least two or three times the target size. Likewise important are the location and direction of the transmitter cables, which can have great impact on the result of inversion and should be parallel to the target strike. By using more than one transmitter, better results are obtained. If the strike of the target is known, transmitters should be parallel to each other and if not, it is better to use perpendicular transmitters. Results showed that the optimal distance between transmitters is 3 km. Our simulations show that it is even possible to recover targets just below the transmitter in corresponding areas of masked data.

The coordination polymer [Fe(NH₂trz)₃](2ns)₂ exhibits the rare phenomenon of spin crossover in an attractive temperature range, i.e., somewhat above room temperature. Spin crossover in [Fe(NH₂trz)₃](2ns)₂ is manifest by thermochromism, which is accompanied by a magnetic transition from diamagnetism to paramagnetism. However, [Fe(NH₂trz)₃](2ns)₂ is brittle and difficult to process, which limits its use. In this study, we show that [Fe(NH₂trz)₃](2ns)₂ can be co-processed with ultrahigh molecular weight polyethylene (UHMWPE), which possesses outstanding mechanical properties, particularly when tensile drawn. Therefore, [Fe(NH₂trz)₃](2ns)₂–UHMWPE blends were gel-processed by extrusion, employing a relatively poor solvent, which has recently been shown to offer advantages compared to good solvents. Uniform and flexible films, ribbons and fibers with [Fe(NH₂trz)₃](2ns)₂ fractions as high as 33.3% m/m were obtained that could be readily drawn. Spin crossover in the coordination polymer is retained in these materials, as evident from their thermochromism. The tensile strength and Young’s modulus of the blends exceed those of typical commodity polymers. Thus, the films, ribbons and fibers constitute a special class of multifunctional materials that combine the flexibility and excellent mechanical properties of drawn UHMWPE with the spin crossover behavior of [Fe(NH₂trz)₃](2ns)₂.

In recent years, weeds is responsible for most of the agricultural yield losses. To deal with this threat, farmers resort to spraying pesticides throughout the field. Such method not only requires huge quantities of herbicides but impact environment and humans health. One way to reduce the cost and environmental impact is to allocate the right doses of herbicide at the right place and at the right time (Precision Agriculture). Nowadays, Unmanned Aerial Vehicle (UAV) is becoming an interesting acquisition system for weeds localization and management due to its ability to obtain the images of the entire agricultural field with a very high spatial resolution and at low cost. Despite the important advances in UAV acquisition systems, automatic weeds detection remains a challenging problem because of its strong similarity with the crops. Recently Deep Learning approach has shown impressive results in different complex classification problem. However, this approach needs a certain amount of training data but, creating large agricultural datasets with pixel-level annotations by expert is an extremely time consuming task. In this paper, we propose a novel fully automatic learning method using Convolutional Neuronal Networks (CNNs) with unsupervised training dataset collection for weeds detection from UAV images. The proposed method consists in three main phases. First we automatically detect the crop lines and using them to identify the interline weeds. In the second phase, interline weeds are used to constitute the training dataset. Finally, we performed CNNs on this dataset to build a model able to detect the crop and weeds in the images. The results obtained are comparable to the traditional supervised training data labeling. The accuracy gaps are 1.5% in the spinach field and 6% in the bean field.

The sensitivity of macroscopic mechanical and thermal properties of grey cast iron is computationally investigated for a variety of graphite microstructures over a wide temperature range. In order to represent common graphite microstructures according to DIN EN ISO 945-1, a synthetic approach is used to algorithmically generate simulation domains. The developed mechanical and thermal model is applied in a large simulation study. The study includes statistical volume elements of the graphite microstructures classes GG-15 and IA2 to IA5, with 10 v.-%, 11 v.-% and 12 v.-% graphite, respectively, for a temperature range from 20 °C to 750 °C. Homogenized macroscopic quantities such as the Young's moduli, Poisson's ratios, yield strengths and thermal conductivities are predicted for the different microstructure classes by applying simulation and data analysis tools of the research data infrastructure Kadi4Mat.

There is a lack of knowledge concerning the effects of ambient heat exposure on morbidity in Northern Europe. Therefore, this study aimed to evaluate the relationships of daily summer-time temperature and heatwaves with cardiorespiratory hospital admissions in the Helsinki metropolitan area, Finland. Methods: Time-series models adjusted for potential confounders such as air pollution were used to investigate the associations of daily temperature and heatwaves with cause-specific cardiorespiratory hospital admissions, during summer months of 2001-2017. Daily number of hospitalizations was obtained from the national hospital discharge register, weather information from the Finnish Meteorological Institute. Results: Increased daily temperature was associated with decreased risk of total respiratory hospital admissions and asthma. Heatwave days were associated with 20.5% (95% CI: 6.9, 35.9) increased risk of pneumonia admissions and during long or intense heatwaves also with total respiratory admissions in the oldest age group (≥ 75 years). There were also suggestive positive associations between heatwave days and admissions due to myocardial infarction and cerebrovascular diseases. In contrast, risk of arrhythmia admissions was decreased 20.8% (95% CI: 8.0, 31.8) during heatwaves. Conclusions: Heatwaves, rather than single hot days, are a health threat affecting the morbidity even in a Northern climate.

In the recent years, Cannabis and hemp-based products have become increasingly popular for various applications ranging from recreational use, edibles, beverages to health care products and medicines. The rapid detection and differentiation of phytocannabinoids is, therefore, essential to assess the potency, therapeutic and nutritional values of cannabis cultivars. Here, we implemented the SpiderMass technology for the in vivo detection of cannabidiol acid (CBDA) and tetrahydrocannabinol acid (THCA) and other endogenous organic plant compounds to access distribution gradients within the plants and differentiate cultivars. The SpiderMass system is composed of an IR- laser handheld microsampling probe connected to the mass spectrometer through a transfer tube. The analysis was performed in situ on different plant organs from freshly cultivated Cannabis plants in only a few seconds. SpiderMass analysis easily discriminated the two acid phytocannabinoid isomers by MS/MS and the built statistical models differentiated between four Cannabis cultivars. Different abundancies of acid phytocannabinoids were also found along the plant as well as between different cultivars. All together, these results introduce the direct analysis by SpiderMass as a compelling analytical alternative for forensic and hemp industrial analysis.

In this work, a small-strain phase-field model is presented, which is able to predict crack propagation in systems with anisotropic brittle and ductile constituents. To model the anisotropic brittle crack propagation, an anisotropic critical energy release rate is used. The brittle constituents behave linear-elastically, in a transversely isotropic manner. Ductile crack growth is realised by a special crack degradation function, depending on the accumulated plastic strain, which is calculated by following the J2-plasticity theory. The mechanical jump conditions are applied in solid-solid phase transition regions. The influence of the relevant model parameters on a crack, propagating through a planar brittle-ductile interface, and furthermore a crack developing in a domain with a single anisotropic brittle ellipsoid, embedded in a ductile matrix, is investigated. We demonstrate that important properties, concerning the mechanical behaviour of grey cast iron, such as the favoured growth of cracks along the graphite lamellae and the tension-compression load asymmetry of the stress-strain response, are covered by the model. The behaviour is analysed on basis of a simulation domain consisting of three differently oriented elliptical inclusions, embedded in a ductile matrix, which is subjected to tensile and compressive load. The used material parameters correspond to graphite lamellae and pearlite.

Ankle sprains are exceedingly common injuries in both athletes and general population. They account for 10 to 30% of all sports injuries. Although the vast majority of lateral ankle ligamentous injuries respond successfully to conservative management, the absolute number of those that progress to chronic lateral ankle instability (CLAI) remains considerably important. This condition is characterized by persistent symptoms and may be associated with short-term and long-term complications and functional deficits. There is still a lack of ideal postoperative management of CLAI patients. Furthermore, an evidence-based rehabilitation phasing does not exist and most of the published studies regarding this subject suggest some protocols based on a wide variety of functional assessment scores and other modalities which are not accurate enough. Moreover, the literature that assesses the ability to return to work (RTW) and return to sport (RTS) in general population and athletes operated for CLAI shows most commonly aggregated results with global rates of RTW or RTS without describing a detailed timeline based on the readiness of patients to return to each level of activity. Although stress radiographs and MRI have been assessed as potential tools to improve postoperative management of CLAI patients, the first modality is limited by its low sensitivity to detect laxity and the second one by its static character and its inability to predict the healing process phase nor the mechanical properties of the repaired/reconstructed ligaments. Bioelectrical impedance, mechanical impedance and near-infrared spectroscopy are non-invasive methods of measurement that could be potential assessment tools to help surgeons improve the postoperative management of patients after CLAI surgery.

The hydrochemical composition of the Upper Jurassic groundwaters in the South German Mo-lasse Basin (SGMB) indicates a heterogeneous and varying hydrogeochemical evolution, which contradicts previous flow model concepts. For this study, the data of 88 Tertiary, Cretaceous and Upper Jurassic groundwater samples were investigated for hydrochemical elements, 2H/18O-H2O isotopes, 87Sr/86Sr ratios as well as δ11B values. In addition, the geochemical composition, 87Sr/86Sr and δ11B values were analysed from depth-oriented Upper Jurassic rock samples to delineate water-rock interactions in the aquifer systems. Slightly elevated 87Sr/86Sr ratios of the carbonates compared to the typical signatures of marine Upper Jurassic carbonates indicate a synsedimentary radiogenic influence due to the erosion of the adjacent Bohemian Massif. However, these values cannot explain the significant higher Sr-isotope fingerprint of the groundwaters in the central SGMB. Different water types occur in the Upper Jurassic aquifer, primarily distinguished by the dominant cations, calcium or sodium with subclasses of the major anions. The calcium-dominated groundwaters occur mainly at the western and northern margins of the SGMB. The sodi-um-dominated ion exchange groundwaters instead dominate in the central and eastern SGMB. With increasing strontium content, the 87Sr/86Sr ratios of the Upper Jurassic groundwater samples either indicate a strontium uptake by carbonate of the host rocks, or a prevailing radiogenic sig-nature. This implies a basic interaction with terrestrial or marine Tertiary sediments. The results illustrate a downward transformational fluid flow systematic via the thick Tertiary sediment cover into the Upper Jurassic carbonate formation in the SGMB, highlighting a new understanding on the evolution of the Upper Jurassic groundwaters and a basin-wide recharge mechanism.

Responding to changing value creation processes in the sheet metal working sec-tor, where the complexity and interchangeability of products challenge traditional dif-ferentiation strategies, this empirical analysis explores integrating service-oriented and data-driven business models as new paths to ensure competitiveness, especially for small and medium-sized enterprises (SMEs). This study aims to capture the current state and challenges associated with the implementation of these business models in this sector. The research was conducted through semi-structured interviews with SMEs in the industry. The findings indicate that service-oriented and data-driven business models are not yet widely adopted and that manufacturing companies re-quire support in their implementation. Fields of action were identified for the industry. These are "Creating awareness and understanding", "Recognizing added value", "In-creasing company maturity" and "Understanding the change process". Cooperation between science and industry is essential in tackling these fields of action to ensure the successful integration of such business models in manufacturing companies. This pa-per identifies challenges in the fields of action that companies must address through a structured approach promoting awareness, recognizing value, improving organiza-tional maturity, and understanding the change process to successfully implement ser-vice-oriented and data-driven business models.

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.

This paper presents the goals and components of a quantitative energy balance assessment framework to define PEDs flexibly in three important contexts: the context of the district's density and RES potential, the context of a district's location, induced mobility and the context of the dis-trict's future environment and its decarbonized energy demand or supply. It starts by introducing the practical goals of this definition approach: achievable, yet sufficiently ambitious to be inline with Paris 2050 for most urban and rural Austrian district typologies. It goes on to identify the main design parts of the definition: system boundaries, balancing weights and balance targets and argue how they can be linked to the definition goals in detail. In particular we specify three levels of system boundaries and argue their individual necessity: operation, including everyday mobili-ty, including embodied energy and emissions. It argues that all three pillars of PEDs, energy effi-ciency, onsite renewables and energy flexibility can be assessed with the single metric of a prima-ry energy balance when using carefully designed, time-dependent conversion factors. Finally, it is discussed how balance targets can be interpreted as information and requirements from the sur-rounding energy system, which we identify as a "context factor". Three examples of such context factors, each corresponding to the balance target of one of the previously defined system bounda-ries operation, mobility and embodied emissions are presented: Density (as a context of opera-tion), sectoral energy balances and location (as a context for mobility) and an outlook of a person-al emission budgets (as a context for embodied emissions). Finally, the proposed definition framework is applied to seven distinct district typologies in Austria and discussed in terms of its design goals.

The research investigates the role the environmental manager plays to ensure a successful (or not) implementation of environmental performance within an organization. It is based on interviews of 5-7 actors per company within a sample of 7 companies (42 interviews). We build upon bias of perception of the various actors interviewed within each company to define 4 paradoxes related to the roles and mission of the environmental manager that hinder proper efficiency of environmental management at company level. Paradox 1 is that no one takes ownership of environmental performance within the organization. Paradox 2 is that the environmental manager is in an awkward situation vis-à-vis his boss. Paradox 3 is that the role of the environmental manager is ambiguous vis-à-vis employees. Paradox 4 is that corporate and product approaches are decoupled. We suggest that these paradoxes interact and form a vicious cycle that may in part be responsible for the environmental decoupling phenomenon – the fact that companies often adopt a sustainability policy symbolically without implementing it substantively. Our research suggests that, by leveraging the leadership of the environmental manager through organizational and motivational measures, the vicious cycle can be transformed into a virtuous cycle and the human motivation can become a driver for green change within corporations. We proposed the SEA (Shaping Environmental Action) model based of 4 pillars: information, motivation, organization and strategy.

With metal oxide semiconductors being a promising candidate for accurate indoor air quality assessments, multiple drawbacks of the gas sensors prevent their widespread use. Examples include poor selectivity, instability over time, and sensor poisoning. Complex calibration methods and advanced operation modes can solve some of those drawbacks. However, this leads to long calibration times, which are unsuitable for mass production. In recent years, multiple attempts to solve calibration transfer have been made with the help of direct standardization, orthogonal signal correction, and many more methods. Besides those, a new promising approach is transfer learning from deep learning. This article will compare different calibration transfer methods, including direct standardization, piecewise direct standardization, transfer learning for deep learning models, and global model building. The machine learning methods to calibrate the initial models for calibration transfer are feature extraction, selection, and regression (established methods) and a custom convolutional neural network TCOCNN. It is shown that transfer learning can outperform the other calibration transfer methods regarding the root mean squared error, especially if the initial model is built with multiple sensors. It was possible to reduce the number of calibration samples by up to 99.3 % (from 10 days to approximately 2 hours) and still achieve an RMSE for acetone of around 18 ppb (15 ppb with extended individual calibration) if six different sensors were used for building the initial model. Furthermore, it was shown that the other calibration transfer methods (direct standardization and piecewise direct standardization) also work reasonably well for both machine learning approaches, primarily when multiple sensors are used for the initial model.

BACKGROUND: Current research recorded hearing loss in 8.5million Nigerians. Hearing loss can be prevented and treated. Most individuals in the communities are unaware. Available hearing screening instruments are not readily accessible in communities. Regular screening is the key. Hence, the introduction of the HearWHO App in the communities, a mobile hearing screener. AIM: - To detect hearing loss and otological disorders - To validate the HearWHO App in the communities - To launch the HearWHO App in the communities MATERIALS AND METHODS: Commenced after obtaining due ethical clearance, informed consent and permissions. A 3 year duration study (March 2020 to March 2022). Study centres were 4 motor parks in Benin City Edo State (Muyi line, Faith motors, Iyare motors and Magorawa terminal) and 2 hospitals in Ondo City, Ondo state (General Hospital and Trauma Centre of the UNIMEDTH complexes). Ambient noise was recorded. Total population sampling technique was used. Health education was given. Using the HearWHO App in mobile smartphone connected to ear piece, each participant’s ears were tested. Each ear was regarded as a separate entity. Otoscopy was done. Findings of hearWHO App were compared with Otoscopic findings. Data realized were documented and analyzed with SPSS -23. P value < 0.05 was regarded statistically significant. RESULTS: 175 individuals participated, giving 350 ears examined. There were abnormal HearWHO findings in 77.4% ears compared to abnormal Otological findings in 65.0% ears. Predominant otological disorder was Eustachian Tube Dysfunction. Association of HearWHO finding with location was statistically significant (P=0.014). CONCLUSION AND RECOMMENDATION: Hearing loss and otological disorders were detected. There was agreement between HearWHO normal findings and normal otological findings. Based on challenges encountered, there is need to develop additional Apps or modify the HearWHO App to ensure Sustainable Developmental Goal -3 (SDG -3). Thus, creating a better future today making impact with mobile technology.

Increased traffic in combination with growing environmental impacts, have led to accelerated degradation of the built infrastructure. In reinforced concrete structures, the corrosion of steel reinforcement is the predominant cause of deterioration. Thus, over the last years the use of glass fiber reinforced polymer (GFRP) composites as internal reinforcement bars (rebars) for concrete structures was evaluated, and has been proved to be a viable alternative to traditional steel reinforcement mainly due to its tensile strength and non-corrosive nature. However, thus far, the GFRP rebar market is diverse and manufacturers around the world produce GFRP rebar types with different surface enhancement to improve the bond to concrete characteristics. In this study, the bond performance of three dissimilar GFRP rebar types (sand coated, helically grooved and with surface lugs) was evaluated over time in seawater environments, with a focus on the bond strength. Accordingly, specimens were expose to seawater in circulating chambers, at three different temperatures (23 °C, 40 °C and 60 °C) for multiple time periods (60 and 120 days). To evaluate the bond performance, pullout tests were conducted according to ASTM D7913 [1]. The results showed that the bond strength varies with surface enhancement features. However, the bond strength didn’t vary significantly with exposure time and temperature for all three evaluated rebar types.

Nowadays, the Internet of Things (IoT) concept plays a pivotal role in society and brings new capabilities to different industries. The number IoT solutions in areas such as transportation and healthcare is increasing and new services are under development. In the last decade, society has experienced a drastic increase in IoT connections. In fact, IoT connections will increase in the next few years across different areas. Conversely, despite these benefits, several challenges still need to be faced to enable efficient and secure operations (e.g., interoperability, security, standards, and server technologies). Furthermore, although efforts have been made to produce datasets composed of attacks against IoT devices, several possible attacks are not considered. Most existing efforts do not consider an extensive network topology with real IoT devices. The main goal of this research is to propose a novel and extensive IoT attack dataset to foster the development of security analytics applications in real IoT operations. To accomplish this, 33 attacks are executed in an IoT topology composed of 105 devices. These attacks are classified into seven categories, namely DDoS, DoS, Recon, Web-based, Brute Force, Spoofing, and Mirai. Finally, all attacks are executed by malicious IoT devices targeting other IoT devices.

This article presents the implementation of a model to estimate the future price of commodities in the Brazilian market from time series of short-term technical evaluation. For this, data from two databases were used, one referring to the foreign market (opening values, maximum, minimum, closing, closing adjustment and volume) and the other, from the Brazilian market (the price of the day), considering commodities, sugar, cotton, corn, soybean and wheat. Subsequently, the technical indicators were calculated from the TA-Lib technical analysis library. Pearson’s correlation coefficient was applied, records with low correlation were removed, and then the database was consolidated. From the pre-processed data, Long Short-Term Memory (LSTM) recurrent neural networks were used to perform data prediction at the one and three day interval. These models were evaluated using the mean square error (MSE), obtaining results between 0.00010 and 0.00037 on test data one day ahead, and from 0.00017 to 0.00042 three days ahead. However, based on the results obtained, it was observed that the developed model obtained a promising forecasting performance for all the commodities evaluated. As a main contribution, there is the consolidation of databases that can be used in future scientific research. Furthermore, based on its interpretation, it can assist in decision making regarding the buying and selling of commodities to increase financial gains.

This paper presents the development and implementation of a machine learning model to estimate the future price of commodities in the Brazilian market from technical analysis indicators. For this, two databases were obtained regarding the commodities sugar, cotton, corn, soybean and wheat, which were submitted to the steps of data cleaning, pre-processing and subdivision. From the pre-processed data, recurrent neural networks of the long short-term memory type were used to perform the prediction of data in the interval of 1 and 3 days ahead. These models were evaluated using mean squared error, obtaining an accuracy between 0.00010 and 0.00037 on the test data for 1 day ahead and 0.00015 to 0.00041 for 3 days ahead. However, based on the results obtained, it can be stated that the developed model obtained a good prediction performance for all commodities evaluated.

Millions of people use public transportation daily worldwide and frequently touch surfaces, thereby producing a reservoir of microorganisms on surfaces increasing the risk of transmission. Constant occupation makes sufficient cleaning difficult to achieve. Thus, an autonomous, perma-nent antimicrobial coating (AMC) could keep down the microbial burden on such surfaces. A photodynamic AMC was applied to frequently touched surfaces in buses. The microbial burden (colony forming units, cfu) was determined weekly and compared to equivalent surfaces in buses without AMC (references). The microbial burden ranged from 0 – 209 cfu/cm² on references and from 0 – 54 cfu/cm² on AMC. The means were 13.4 ± 29.6 cfu/cm² on references and 4.5 ± 8.4 cfu/cm² on AMC (p<0.001). The difference of microbial burden on AMC and references was al-most constant throughout the study. Considering a hygiene benchmark of 5 cfu/cm², the data yield an absolute risk reduction of 22.6 % and a relative risk reduction of 50.7 %. In conclusion, photo-dynamic AMC kept down the microbial burden, reducing the risk of transmission of microor-ganisms. AMC permanently and autonomously contributes to hygienic conditions on surfaces in public transportation. Photodynamic AMC therefore are suitable for reducing the microbial load and closing hygiene gaps in public transportation.

Quinacridone (QA) and 2,9-dimethylquinacridone (DQA) are synthetic substances suitable as a hard, abrasion-resistant, self-organizing gliding layer on ice, snow, and water. For sustainable use, a large number of parameters must be considered to demonstrate that these non-biogenic substances and their by-products and degradation products are harmless to humans and the environment in the quantities released. For this task, available experimental data are used and supplemented for all tautomers by numerous relevant physical, chemical, toxicological and ecotoxicological estimated values based on various Quantitative Structure Activity Relationship (QSAR) methods. On the one hand, the low solubility of QA and DQA leads to stable gliding layers and thus low abrasion and uptake by plants, animals, and humans. On the other hand, the four hydrogen bond forming functional groups per molecule allow nanoparticle decomposition and enzymatic degradation in natural environments. All available data justify a sustainable use of QA and DQA as a gliding layer. The assessment of the toxicological properties is complemented with an investigation of the size and morphology of DQA particles as well as field tests indicating an excellent performance as a gliding layer on snow.

Campylobacter jejuni is a zoonotic bacterium, causing intestinal infection in humans. One characteristic feature of the pathogenicity process is the ability of this bacterium invading the epithelial cells. Several factors have been identified to contribute to this process and some recent analyses revealed changes in the bacterium cell on molecular level. However, our knowledge is still limited about responses of the host that accompany the bacterial internalisation and survival process. This study focused on molecular events on transcriptomic level detected between the 1st and the 3rd hour of internalisation in INT407 epithelial cells. From the 41.769 human genes tested, altogether 19,060 genes and 22,734 pseudogenes and introns were shown by whole transcriptome analysis to be affected in different extent. Most affected functions regulate transcription (28%), signal transduction (21%), apoptosis (15%), immune responses (9%), transmembrane transport (6%), cell-cell signaling (3%), cell-cell adhesions (3%) and carbohydrate metabolism (3%) and to a lesser extent other functions. Our results provide insight into a scenario where, the invaded cell focuses on survival, but, at the same time, flashing the possibility of pushing the process toward the death of the invaded and metabolically disrupted cell.

TThe following three objectives were tested in this study: (1) investigate the utility of low-altitude remote sensing using UAS technology to compare the effects of different N application systems in rice production; (2) use spatial extrapolation to scale up plot-level generated to farmer field rice yield data based on crop spectral signatures, and (3) predict and map out rice productivity as a function of N placement systems. Images were captured on a UAV platform at midseason of the rice crop. Orthomosaics were developed for selected fields in rice-producing zones. Grain yields were assessed from low, medium, and high crop health plots delineated based on NDVI values. On the plot scale, UDP outyielded non-UDP by 0.84%. Individual plot yield data were scaled up to the farmer field level through Jenks natural breaks classification and es-tablishing an empirical relationship between OSAVI and plot yields. Assessment of the scaled-up field levelfield-level data also confirmed the superiority of UDP N man-agement over the non-UDP systems in promoting rice yields. Scaling up plot scale da-ta to whole field levels also facilitated generating and mapping expected yield maps for individual farmer fields in the three zones studied. This study has established a tangible simple but tangible protocol protocol for predicting and mapping rice yields in small-scale farmer fields using UAS data.

We investigate the extent to which a two-level quantum system subjected to an external time-dependent drive can be characterized by supervised learning. We apply this approach to the case of bang-bang control and the estimation of the offset and the final distance to a given target state. The estimate is global in the sense that no a priori knowledge is required on the parameters to be determined. Different neural network algorithms are tested on a series of data sets. We point out the limits of the estimation procedure with respect to the properties of the mapping to be interpolated. We discuss the physical relevance of the different results.

Optimal breastfeeding practices among mothers have been proven to have health and economic benefits, but evidence on breastfeeding practices among adolescent mothers in Bangladesh is limited. Hence, this study aims to estimate breastfeeding indicators and factors associated with selected feeding practices. The sample included 2554 children aged 0-23 months of adolescent mothers aged 12-19 years from four Bangladesh Demographic and Health Surveys collected between 2004 and 2014. Breastfeeding indicators were estimated using World Health Organization indicators. Selected feeding indicators were examined against potential confounding factors using univariate and multivariate analyses. Only 42.2% of adolescent mothers initiated breastfeeding within the first hour of birth, 53% exclusively breastfed their infants, predominant breastfeeding was 17.3%, and 15.7% bottle-fed their children. Parity (2-3 children), older infants and adolescent mothers who made postnatal check-up after two days were associated with increased exclusive breastfeeding (EBF) rates. Adolescent mothers aged 12-18 years and who watched television were less likely to delay breastfeeding initiation within the first hour of birth. Adolescent mothers who delivered at home (adjusted OR=2.63, 95% CI:1.86, 3.74) and made postnatal check-up after two days (adjusted OR=1.67, 95% CI: 1.21, 2.30) were significantly more likely to delay initiation breastfeeding within the first hour of birth. Younger infants, adolescent mothers living in Barisal region and who listened to radio reported increased odds of predominant breastfeeding and increased odds for bottle-feeding included male infants, an infant aged 0-5 months, Adolescent mothers who had eight or more antenatal clinic visits and richest wealth quintiles. In order for Bangladesh to meet the Sustainable Development Goals (SDGs) 2 and 3 by 2030, breastfeeding promotion programmes should discourage bottle-feeding among adolescent mothers from richest households and promote early initiation of breastfeeding especially among adolescent mothers who delivered at home and had late postnatal check-up after delivery

The blood-brain barrier (BBB), built by brain endothelial cells (BECs), is impermeable to biologics. Liposomes and other nanoparticles are good candidates for delivery of biologics across the BECs, as they can encapsulate numerous molecules of interest in an omnipotent manner. The liposomes need attachment of a targeting molecule, as BECs unfortunately are virtually incapable of uptake of non-targeted liposomes from the circulation. Experiments of independent research groups have qualified antibodies targeting the transferrin receptor as superior for targeted delivery of nanoparticles to BECs. Functionalization of nanoparticles via conjugation with anti-transferrin receptor antibodies leads to nanoparticle uptake by endothelial cells of both brain capillaries and post-capillary venules. Reducing the density of transferrin receptor-targeted antibodies conjugated to liposomes limits uptake in BECs. Opposing the transport of nanoparticles conjugated to high-affine anti-transferrin receptor antibodies, lowering the affinity of the targeting antibodies or implementing monovalent antibodies increase uptake by BECs and allows for further transport across the BBB. The novel demonstration of transport of targeted liposomes in post-capillary venules from blood to the brain is interesting and clearly warrants further mechanistic pursuit. The recent evidence for passing targeted nanoparticles through the BBB shows great promise for future drug delivery of biologics to the brain.

Mapping drought from space using, e.g., surface soil moisture (SSM), has become viable in the last decade. However, state of the art SSM retrieval products suffer from very poor coverage over northern latitudes. In this study, we propose an innovative drought indicator with a wider spatial and temporal coverage than that obtained from satellite SSM retrievals. We evaluate passive microwave brightness temperature observations from the Soil Moisture and Ocean Salinity (SMOS) satellite as a surrogate drought metric, and introduce a Standardized Brightness Temperature Index (STBI). The STBI is validated against drought indices from a land surface data assimilation system (LDAS-Monde), two satellite dervied SSM indices and a standardized precipitation index. Finally, we evaluate the STBI against the before mentioned drought indices in a case study of the 2018 Nordic drought. The STBI is found to be superior to the drought index created from satellite derived SSM in both spatial and temporal coverage over the Nordic region. Our results indicate that when compared to drought indices from precipitation data and a land data assimilation system, the STBI is able to capture the 2018 drought onset, severity and extent. Thus, the STBI index could provide additional information for drought monitoring in regions where the SSM retrieval problem is difficult.

Type 2 diabetes (T2D) has a complex pathophysiology which makes modeling the disease difficult. We aimed to develop a novel model for simulating T2D in vitro, including hyperglycemia, hyperlipidemia, and variably elevated insulin levels targeting muscle cells. We investigated insulin resistance (IR), cellular respiration, mitochondrial morphometry and the associated function in different T2D -mimicking conditions in rodent skeletal (C2C12) and cardiac (H9C2) myotubes. Physiological controls included 5mM glucose with 20mM mannitol as osmotic controls. To mimic hyperglycemia, cells were exposed to 25mM glucose. Further treatments included insulin, palmitate, or both. After short-term (24h) or long-term (96h) exposure, we performed radioactive glucose uptake and mitochondrial function assays. Mitochondrial size and relative frequencies were assessed by morphometric analyses using electron micrographs. C2C12 and H9C2 cells treated short- or long-term with insulin and/or palmitate and HG showed IR. C2C12 myotubes exposed to T2D -mimicking conditions showed significantly decreased ATP-linked respiration and spare respiratory capacity, and less cytoplasmic area occupied by mitochondria, implying mitochondrial dysfunction. In contrast, H9C2 myotubes showed elevated ATP-linked and maximal respiration and increased cytoplasmic area occupied by mitochondria, indicating better adaptation to stress and compensatory lipid oxidation in a T2D environment. Both cell lines displayed elevated fractions of swollen/vacuolated mitochondria after T2D -mimicking treatments.Our stable and reproducible in vitro model of T2D rapidly induced IR, changes in ATP-linked respiration, shifts in energetic phenotypes, and mitochondrial morphology, which are comparable to the muscles of patients suffering from T2D. Thus, our model should allow studying disease mechanisms, potential new targets, and screen candidate therapeutic compounds.

The demand for explainable and transparent models increases with the continued success of reinforcement learning. In this article, we explore the potential of generating shallow decision trees (DT) as simple and transparent surrogate models for opaque deep reinforcement learning (DRL) agents. We investigate three algorithms for generating training data for axis-parallel and oblique DTs with the help of DRL agents ("oracles") and evaluate these methods on classic control problems from OpenAI Gym. The results show that one of our newly developed algorithms, the iterative training, outperforms traditional sampling algorithms, resulting in well-performing DTs that often even surpass the oracle from which they were trained. Even higher dimensional problems can be solved with surprisingly shallow DTs. We discuss the advantages and disadvantages of different sampling methods and insights into the decision-making process made possible by the transparent nature of DTs. Our work contributes to the development of not only powerful but also explainable RL agents and highlights the potential of DTs as a simple and effective alternative to complex DRL models.

Background. Transferrin receptor 1 (TfR1), glucose transporter 1 (GLUT1), and CD98hc are candidates for targeted therapy at the blood-brain barrier (BBB). Our objective was to challenge the expression of TfR1, GLUT1, and CD98hc in brain capillaries by the histone deacetylase inhibitor (HDACi) valproic acid (VPA). Methods. Primary mouse brain capillary endothelial cells (BCECs) and brain capillaries isolated from mice injected intraperitoneally with VPA were examined using RT-qPCR and ELISA. Targeting to the BBB was performed by injecting monoclonal anti-TfR1 (Ri7217)-conjugated gold nanoparticles measured using ICP-MS. Results. In BCECs co-cultured with glial cells, Tfrc mRNA expression was significantly higher after 6 h VPA returning to baseline after 24 h. In vivo Glut1 mRNA expression was significantly higher in males, but not females', receiving VPA, whereas Cd98hc mRNA expression was unaffected by VPA. TfR1 increased significantly in vivo after VPA, whereas GLUT1 and CD98hc were unchanged. Uptake of anti-TfR1-conjugated nanoparticles was unaltered by VPA in spite upregulated TfR expression. Conclusions. VPA upregulates TfR1 in brain endothelium in vivo and in vitro. VPA does not increase GLUT1 and CD98hc proteins. The increase in TfR1 does not result in higher anti-TfR1 antibody targetability, suggesting targeting sufficiently occurs with available transferrin receptors without further contribution from accessory VPA-induced TfR1.

Background: Seizures in the early postoperative period may impair patient recovery and increase risk of complication. The aim of this study is to determine whether there is any advantage in postoperative seizure prophylaxis following meningioma resection. Methods: This systematic review was conducted in accordance with PRISMA guidelines. PUBMED, Web of Science, Embase, Science Direct, and Cochrane were searched for papers until April 2023. Results: Among 9 studies, a total of 3,249 were evaluated patients, of which 984 patients received antiepileptic drugs (AEDs). A comparison between patients who received AEDs and those who did not showed a non-significant differences between both groups (RR 1.22, 95% CI 0.66 to 2.40; I² = 57%). Postoperative seizures occurred in 5% (95% CI: 1% to 9%) within the early time period (<7 days), and 9% (95% CI: 1% to 17%) in the late time period (>7 days), with significant heterogeneity (I² = 91% and 97% respectively). In seizure-naive patients, the rate of postoperative seizures was 2% (95% CI: 0% to 6%) in the early period and increased to 6% (95% CI: 0% to 15%) in the late period. High heterogeneity led to the use of random-effects models in all analyses. Conclusion: The current evidence does not provide sufficient support for the effectiveness of prophylactic AED medications in preventing postoperative seizures in patients undergoing meningioma resection. This underscores the importance of considering diagnostic criteria and conducting individual patient analysis to guide clinical decision-making in this context.

Vertical Indoor Farming (VIF) with hydroponics offers a promising perspective for sustainable food production. Intelligent control of VIF system components plays a key role in reducing operating costs and increasing crop yields. Modern machine vision (MV) systems use Deep Learning (DL) in combination with camera systems for various tasks in agriculture, such as disease and nutrient deficiency detection, and flower and fruit identification and classification for pollination and harvesting. This study presents the applicability of MV technology with DL modelling to detect the growth stages of chilli plants using YOLOv8 networks. The influence of different bird’s eye and side view datasets and different YOLOv8 architectures was analysed. To generate the image data for training and testing the YOLO models, chilli plants were grown in a hydroponic environment and imaged throughout their life cycle using four camera systems. The growth stages were divided into growing, flowering and fruiting classes. All trained YOLOv8 models showed reliable identification of growth stages with high accuracy. The results indicate that models trained with data from both views show better generalisation. YOLO’s middle architecture achieved the best performance.

Digital federated platforms and data cooperatives for secure, trusted and sovereign data exchange will play a central role in the construction industry of the future. With the help of platforms, cooperatives and their novel value creation, the digital transformation and the degree of organization of the construction value chain can be taken to a new level of collaboration. The goal of this research project was to develop an experimental prototype for a federated innovation data platform along with a suitable exemplary use case. The prototype is to serve the construction industry as a demonstrator for further developments and form the basis for an innovation platform. It exemplifies how an overall concept is concretely implemented along one or more use cases that address high-priority industry pain points. This concept will create a blueprint and a framework for further developments, which will then be further established in the market. The research project illuminates the perspective of various governance innovations to increase industry collaboration, productivity and capital project performance and transparency as well as the overall potential of possible platform business models. However, a comprehensive expert survey revealed that there are considerable obstacles to trust-based data exchange between the key stakeholders in the industry value network. The obstacles to cooperation are predominantly not of a technical nature, but of a competitive, predominantly trust-related nature. To overcome these obstacles and create a pre-competitive space of trust, the authors therefore propose the governance structure of a data cooperative model, which is discussed in detail in this paper.

Seasonal snow cover is a fundamental component of both the global energy budget and the water cycle. Its properties such as fractional snow cover or albedo are particularly affected by climate change. Several methods based on satellite data products are available to estimate these properties, each one with its pros and cons. This work presents a novel methodology that integrates three indexes applied to MODIS satellite data (Spectral Mixture Analysis (SMA), Normalized Difference Snow Index (NDSI) and Melt Area Detection Index (MADI)), to perform a spatio-temporal reconstruction of the fractional snow cover and albedo at 250 m spatial resolution in the Brunswick Peninsula, southwest Patagonia during the cold season (April-October) for the period 2000-2020. Three main steps are included: (1) the increase of the spatial resolution of MODIS (MOD09) data to 250 m using a spectral fusion technique; (2) the snow-cloud discrimination; (3) the daily spatio-temporal reconstruction of snow extent and its albedo signature with subpixel detection using the endmembers extraction and spectral mixture analysis. The results show a 98% agreement between MODIS snow detection and ground-based snow measurement at the automatic weather station Tres Morros (53.3174 °S, 71.2790 °W), with fractional snow cover values between 20% and 50%, showing a close relationship between snow and vegetation type. The number of snow days compiled from the MODIS data indicates a good performance (Pearson correlation of 0.9) compared with the number of skiing days at Cerro Mirador ski centre near Punta Arenas. Although the number of seasonal snow days show a significant increase trend of 0.54 days/year in Brunswick Peninsula during the 2000-2020 period a significant decreasing trend of -4.64 days/year was detected during 2010-2020, and also below the 400 m a.s.l. elevation, which is the most affected area. A reconstruction of the monthly mean temperature using the ERA5 Land reanalysis product shows a significant warming trend in May (0.068 ºC/year) and October (0.098 ºC/year) in the 2000-2020 period. Under the future emission scenario RCP8.5, the regional climate model RegCM4 predicts further warming during 2020-2050 of 0.059 ºC/year in July, 0.088 ºC/year in August, and 0.019 ºC/year in October, which will further reduce snow cover.

The broad and rapid application of new genomic techniques (NGTs) such as CRISPR-Cas has led to a fast increase in the number of genetically modified crops. With the recently published EU Commission’s (EC) regulatory proposal on plants generated with NGTs (July 5, 2023) the process of admission of such genetically modified plants is aimed to get accelerated and simplified. NGT plant applications shall be categorized based on their molecular characteristics into category 1 NGT (NGT1) and category 2 NGT (NGT2), which is in divergence from the current legislation centered around Directive 2001/18/EC. In the regulatory proposal NGT2 plants are envisioned to undergo a reduced risk assessment while for NGT1 plants no risk assessment is foreseen at all. To demonstrate were the path of the proposal leads to in practice, we applied the proposed criteria for categorization to a list of NGT plant applications that are currently in the commercialization pipeline. A key finding is that out of those plant applications affected by the EC proposal, 94% would be classified as NGT1 and thus would receive a market approval without risk assessment, monitoring and sufficient labeling provisions. The remaining 6% of applications would be classified as NGT2 plants for which, in deviation from the current regulation, an adapted risk assessment is proposed. A screening of intended traits in the pipeline highlights that certain NGT1 plants can pose similar environmental risks (e.g. invasiveness) compared to other genetically modified organisms (GMOs), as defined in Directive 2001/18/EC. For example, NGT1 applications based on RNAi technology can exhibit insecticidal effects with potential side effects on non-target organisms (i.e. other insects). Our quantitative and case-specific elaboration on how the current EC regulatory proposal would affect the environment, health or consumer protection will be informative for decision makers and politicians.

This paper presents a novel approach to financial network analysis by leveraging PolyModel theory. Traditional financial networks often rely on correlation matrices to represent relationships between assets, but these fail to capture the complex, non-linear interactions prevalent in financial markets. In response, we propose a method that quantifies the relationship between financial time series by comparing their reactions to a broad set of environmental risk factors. This method constructs a network based on the inherent similarities in how assets respond to external risks, offering a more robust representation of financial markets. We introduce several network topological properties, such as eigenvalues, degree, and clustering coefficients, to measure market stability and detect financial instabilities. These metrics are applied to a real-world dataset, including the DOW 30, to predict market drawdowns. Our results indicate that this PolyModel-based network framework is effective in capturing downside risks and can predict significant market drawdowns with high accuracy. Furthermore, we enhance sensitivity to smaller market changes by introducing new time-series indicators, which further improve the predictive power of the model.

Type-2 diabetes mellitus is recognized as a serious public health concern with a considerable impact on human life, long-term health expenditures, and substantial health losses. In this context, the use of dietary polyphenols to prevent and manage Type 2 diabetes mellitus is widely documented. These dietary compounds exert their beneficial effects by several actions, including the protection of pancreatic islet β-cell, the antioxidant capacities of these molecules, their effects on insulin secretion and actions, the regulation of intestinal microbiota, and their contribution to ameliorating diabetic complications, particularly those of vascular origin. In the present review, we intend to highlight these multifaceted actions and the molecular mechanisms by which these plant-derived secondary metabolites exert their beneficial effects on type-2 diabetes patients.

This study investigates the impact of real-time emotional feedback on the quality of teamwork conducted over videoconferencing. We developed a framework that provides real-time feedback through a virtual mirror based on facial and voice emotion recognition. In an experiment with 28 teams (84 participants), teams collaborated over Zoom to set up a virtual Mars station using custom simulation software. Participants were divided into 14 experimental teams which were shown the virtual mirror, and 14 control teams without it. Team performance was measured by the improvement in the Mars simulation output quality. Our analysis using correlation, multilevel regression, and machine learning revealed that fewer interruptions but an increasing number over time correlated with higher performance. Higher vocal arousal and happiness also enhanced performance. We confirmed that female presence in teams boosts performance. SHAP values indicated that high variability in happiness, head movement, and positive facial valence—an “emotional rollercoaster”—positively predicted team performance. The experimental group outperformed the control group, suggesting that virtual mirroring improves virtual teamwork and that interrupting each other more, while speaking less, leads to better results.

The artificial intelligence chatbot ChatGPT can answer questions and solve tasks posed by the user within seconds. Using an exemplary task, this study investigates the reliability and con-sistency of the answers given by ChatGPT. For this purpose, it was analyzed whether the an-swers differ when a question is asked repeatedly and whether selected content categories and associated word combinations coincide with those from scientific literature. ChatGPT was asked 400 times, how the connectedness between humans and nature can be increased. The responses were classified into a categorization system and the most frequently occurring word combina-tions for each category were extracted. These word combinations were used for a search of re-lated scientific literature. In addition, the Normalized Mutual Information (NMI) between the 400 individual responses was calculated. The results show that the phrases used by ChatGPT within the categories are also found in the scientific literature, however, the number of mentions between scientific literature and ChatGPT differs. In addition, the NMI suggested that there are large differences between the categories mentioned in the individual answers. These results in-dicate that ChatGPT currently still has difficulties in answering complex questions and cannot yet replace scientific literature research or academic writing.

Zoonotic abortive diseases represent a significant health and economic risk for national public health. This cross-sectional survey was conducted from April to October 2021 among 200 selected small ruminant farmers in the three northern regions of Cameroon. Data collection was done through questionnaires administered by exchange with the herder and responses were coded and recorded on an Excel spreadsheet. The data were then analyzed with R software, version 2.13.0. An ANOVA test was used to assess significant differences in mean of Knowledge, Attitudes, Practices and Perception of zoonotic risks (KAPP) scores between regions. Pearson correlations were used to calculate the association between KAPP scores within regions. Small ruminant farmers surveyed had low mean scores for knowledge of abortive Toxoplasmosis and Chla-mydophilosis (0.1 ± 0.2), desirable attitude (0.32 ± 0.07), appropriate practice (0.36 ± 0.13) in managing abortion, and positive perception of zoonotic risks of Toxoplasmosis and Chlamydo-philosis in small ruminants (0.12 ± 0.33), respectively. KAPP was significantly (p<0.01) and posi-tively associated with knowledge (r=0.98) and risk perception (r=0.99). However, attitudes (r=0.06), practices (r=0.05) and risk perception of toxoplasmosis (r=0.07) and Chlamydophilosis (r=0.08) were not associated with farmers' knowledge. This study revealed significant knowledge gaps, low levels of desired attitudes, and high-risk behavioral practices. These results therefore call for capacity building of health professionals and farmers to better integrate the One Health concept in the management of neglected zoonotic diseases.

The aim of this study was to evaluate soil properties and Eragrostis tef (teff) growth on Technosols produced from coarse and fine coal wastes from Moatize Mine, Mozambique. The experiment was performed in triplicate in 30 L containers filled with different substrate conditions, composed of fine coal waste, coarse coal waste, agricultural soil, and sewage sludge as an organic matter source. The soil analyses included bulk density, available water capacity, permeability, and fertility. Plant growth was monitored for biomass production and plant tissue composition. All the substrates presented a good available water capacity and a proper drainage condition. Regarding the soil fertility, there were shortages of potassium and boron in the substrates composed exclusively of coal wastes, which was reflected in the composition of the plant tissue. Even so, plant growth was statistically equivalent to the control in all conditions, except for the substrate produced exclusively with fine coal waste and sewage sludge, which presented a better performance. Technosols are an alternative for reducing the final mine waste volume, and Eragrostis tef used as a means for land use after the mining process, with social gains, and as a tool in an ecological process for restoring coal mining sites.

Chikungunya virus (CHIKV), a mosquito-borne alphavirus of the family Togaviridae, has recently emerged in the Americas from lineages from two continents, Asia and Africa. Historically, CHIKV circulated as at least four lineages worldwide with both enzootic and epidemic transmission cycles. To understand the recent patterns of emergence and the current status of the CHIKV spread, updated analyses of the viral genetic data and metadata are needed. Here, we performed phylogenetic and comparative genomics screens of CHIKV genomes, taking advantage of the public availability of many recently sequenced isolates. Based on these new data and analyses, we derive a revised phylogeny from nucleotide sequences in coding regions. Using this phylogeny, we uncover the presence of several distinct lineages in Africa that were previously considered a single one. In parallel, we performed thermodynamic modeling of CHIKV untranslated regions (UTRs), which revealed evolutionarily conserved structured and unstructured RNA elements in the 3'UTR. We provide evidence for duplication events in recently emerged American isolates of the Asian CHIKV lineage and propose the existence of a flexible 3'UTR architecture among different CHIKV lineages.

The traditional manual recording of vaccination records in Germany faced challenges during the COVID-19 pandemic, prompting the introduction of a Covid smartphone app with QR codes. However, this solution brought new challenges, emphasizing the need for a centrally managed European digital vaccination record for efficiency and validity. Thus, this study assesses the feasibility of using the HL7 FHIR standard in the healthcare industry for implementing a digital vaccination pass management and monitoring system. The system aims to offer convenience and improved efficiency for both patients and healthcare providers while promoting interoperability with other healthcare systems. We developed a prototype using modern technologies, such as React, Quarkus, and Keycloak, evaluating the applicability of FHIR in promoting interoperability within the healthcare industry. Results indicate potential benefits for patients and healthcare providers, offering secure access to immunization records, personalized recommendations, and streamlined management. However, challenges in integrating nuanced vaccination processes into the standardized FHIR system, necessitating custom extensions, and issues with manual data entry and identity provider integration, pose obstacles. Despite these challenges, the study suggests that implementing HL7 FHIR can enhance efficiency, data accessibility, and accuracy in the vaccination process, supporting broader digitization efforts in the German healthcare system and beyond.

Lightning discharges in electric power networks generate voltage and current surges that are propagated through the electrical network causing damage and shutdowns in the electrical system. To protect the system against these phenomena, surge arresters are very effective and widely used by electrical utilities in their electric grids. This paper presents a methodology for optimized surge arrester allocation based on genetic algorithm (GA), creating a simulation environment in the software ATP (Alternative Transients Program) to implement the proposed methodology. The optimized allocation procedure is based on a fitness function that minimizes the cost of surge arresters and maximizes the number of protected equipment. To carry out this optimized arrester allocation procedure using ATP may demand too much processing time when running large distribution grids. To overcome this difficulty a procedure is proposed to obtain an overvoltage severity description of the grid and select the most critical electric nodes for the incidence of lightning discharges, in the GA allocation procedure. The case study is applied to the IEEE 123-bus electrical feeder to demonstrate the effectiveness of the proposed methodology.

Structure quality of LuFeO3 epitaxial layers grown by pulsed-laser deposition on sapphire substrates with and without platinum interlayers has been investigated by in-situ high-resolution x-ray diffraction (reciprocal-space mapping). The parameters of the structure such as size and misorientation of mosaic blocks have been determined as functions of the thickness of LuFeO3 during the PLD growth and for different platinum interlayers thicknesses up to 40 nm. The x-ray diffraction results combined with ex-situ scanning electron microscopy and high-resolution transmission electron microscopy demonstrate that the Pt interlayer significantly improves the structure of LuFeO3 by reducing the misfit of the LuFeO3 lattice with respect to the material underneath.

Ceftiofur (CEF) sodium is a third-generation broad-spectrum cephalosporin commonly used in an extra-label manner in dogs for the treatment of respiratory and urinary system infections. To contribute to the literature supporting CEF use in companion animals, we have developed a compartmental, nonlinear mixed-effects (NLME) model of CEF pharmacokinetics in dogs (PK). We then used the mathematical model to predict (via Monte Carlo simulation) the duration of time for which plasma concentrations of CEF and its pharmacologically active metabolites remained above minimum inhibitory concentrations (respiratory tractEscherichia coli spp). Twelve healthy beagle dogs were administered either 2.2 mg/kg ceftiofur-sodium (CEF-Na) intravenously (I.V) or 2.2 mg/kg CEF-Na subcutaneously (S.C). Plasma samples were collected over a period of 72 hours post-administration. To produce a measurement of total CEF, both CEF and CEF metabolites were derivatized into desfuroylceftiofur acetamide (DCA) before analysis by UPLC-MS/MS. No adverse effects were reported after I.V or S.C dosing. The NLME PK models were parameterized using the stochastic approximation expectation maximization algorithm as implemented in Monolix 2018R2. A two-compartment mamillary model with first-order elimination and first-order S.C absorption best described the available kinetic data. Final parameter estimates indicate that CEF has a low systemic clearance (0.25 L/h/kg) associated with a low global extraction ratio E = 0.02) and a moderate volume of distribution (2.97 L/kg) in dogs. The absolute bioavailability after S.C administration was high (93.7%). Gender was determined to be a significant covariate in explaining the variability of S.C absorption. Our simulations predicted that a dose of 2.2 mg/kg CEF-Na S.C would produce median plasma concentrations of CEF of at least 0.5 µg/mL (MIC₅₀) for approximately 30 hours.

The current work investigates the auxetic tensile deformation behavior of the inversehoneycomb structure with 5 × 5 cells made of biodegradable poly(butylene adipate-coterephthalate) (PBAT). Fused deposition modeling, an additive manufacturing method, produced such specimens. Residual stress (RS) and warpage, more or less, always exist in such specimens due to layer-by-layer fabrication, i.e., repeated heating and cooling. The RS influences the auxetic deformation behavior, but its measurement is challenging due to the very fine structure. Instead, the finite-element(FE)-based process simulation realized by an ABAQUS plug-in numerically predicts the RS and warpage. The predicted warpage shows a negligible slight deviation compared to the design topology. This process simulation also delivers the temperature evolution of a small volume material, revealing the local cyclic heating and cooling. The achieved RS serves as the initial condition for the FE model used to investigate the auxetic tensile behavior. With the outcomes from FE calculation without considering RS at hand, the effect of the RS on the deformation behavior is discussed for the global force-displacement curve, the structural Poisson’s ratio evolution, the deformed structural status, the stress distribution, and evolution, where the first three and the warpage are also compared with experimental results. Furthermore, the FE simulation can easily provide the global stress-strain flow curve with the total stress calculated from the elemental ones.

In an attempt to improve free-range beef cattle herds and explore the economic viability of utilizing Opuntia ficus-indica (spineless cactus) cladodes as supplementary feed, we investigated the impact of cactus diets on animal growth performance and carcass characteristics of Nguni cattle heifers. Four dietary treatments were randomly assigned to 32 heifers aged 24-months, weighing on average 172.2±27.1 kg, with each dietary treatment replicated to 8 individually penned heifers for 90 days. The dietary treatments were control diet (pasture-based energy + protein sources), 10% cactus diet, 20% cactus diet and commercial diet (crop-based energy and commercial protein source). The heifers fed commercial and control diets attained significantly (P < 0.05) higher dry matter intake, average daily gains, fat thickness, carcass conformation scores and lower feed conversion ratio than those fed cactus diets. However, the final body weight gains, slaughter and carcass weights, rib-eye muscle area and meat pH45 min and 24h were comparable (P > 0.05) between heifers fed cactus diets and those fed commercial and control diets. The 10 and 20% cactus diets had greater gross margins (P < 0.05) of R278.6 and R296.9, respectively than the other diets, due largely to reduced total variable costs. The comparability of carcass traits of heifers fed cactus diets and those fed non-cactus diets as well as higher economic returns from cactus inclusion warrants the use of cactus diets, particularly during drought when commercial feed prices rise.

In Germany, the phloem sucking planthopper Pentastiridius leporinus (Hemiptera: Cixiidae) currently represents the epidemiological driver for the spread of the syndrome “Basses Richesses” in sugar beet, which results in a reduced sugar content and an economic loss for the farmers. This disease is associated with the γ-proteobacterium ‘Candidatus Arsenophonus phytopathogenicus’ and the Stolbur phytoplasma ‘Candidatus Phytoplasma solani’. Recently, P. leporinus was found in potato fields in Germany associated with Stolbur-like symptoms in this crop. In this study, we confirmed that the vector completes its lifecycle on sugar beet as well as on potato when reared under controlled conditions. Transmission experiments with adults of this vector combined with molecular analyses showed for the first time that both pathogens are transmitted by this vector to potato. For an accurate assessment of the Ca. P. solani and Ca. A. phytopathogenicus titers in the vector and host plants, gBlocks derived from the hsp20- and 16S rRNA gene were employed, respectively. For Ca. P. solani the limit of detection was determined in potato and sugar beet material. The results of this study will further research on the epidemiology of the syndrome “Basses Richesses” and “Stolbur” diseases and the response of host plants and vector insects to both pathogens.

From the perspective of manufacturing companies, the political, media and economic discourse on decarbonisation of the recent years manifests itself as an increasing social expectation of action. In Germany in particular, this discourse is also being driven forward by powerful companies, respectively sectors, most notably the automotive industry. Against this background, it was examined how German manufacturing companies react to rising societal pressure and emerging policies. It is examined which measures the companies have taken or plan to take to reduce their footprint, which aspirations are associated with this and by which structural characteristics (company size, energy intensity, sector) these are influenced. A mix methods approach was applied, utilising data gathered from approx. 900 companies in context of the Energy Efficiency Index of German Industry (EEI), along with media research focusing on decarbonisation plans and initiatives announced. We demonstrate that one-size-serves-all approaches are not suitable to decarbonise industry as the situation and ambitions differ considerably depending on size, energy intensity and sector. Even though the level of ambition and urgency is high, particularly micro and energy intensive companies are challenged. The research uncovers a series of questions that call for attention to materialise the ambitions and address the challenges outlined.

Introduction: Lyme disease is a tickborne illness that generates controversy among medical providers and researchers. One of the key topics of debate is the existence of persistent infection with the Lyme spirochete, Borrelia burgdorferi, in patients who have been treated with recommended doses of antibiotics yet remain symptomatic. Persistent spirochetal infection despite antibiotic therapy has recently been demonstrated in non-human primates. We present evidence of persistent Borrelia infection despite antibiotic therapy in patients with ongoing Lyme disease symptoms. Materials & Methods: In this pilot study, culture of body fluids and tissues was performed in a randomly selected group of 12 patients with persistent Lyme disease symptoms who had been treated or who were being treated with antibiotics. Cultures were also performed on a group of 10 control subjects without Lyme disease. The cultures were subjected to corroborative microscopic, histopathological and molecular testing for Borrelia organisms in four independent laboratories in a blinded manner. Results: Motile spirochetes identified histopathologically as Borrelia were detected in culture specimens, and these spirochetes were genetically identified as Borrelia burgdorferi by three distinct polymerase chain reaction (PCR) methods. Spirochetes identified as Borrelia burgdorferi were cultured from the blood of seven subjects, from the genital secretions of ten subjects, and from a skin lesion of one subject. Cultures from control subjects without Lyme disease were negative for Borrelia using these methods. Conclusions: Using multiple corroborative detection methods, we showed that patients with persistent Lyme disease symptoms may have ongoing spirochetal infection despite antibiotic treatment, similar to findings in non-human primates. The optimal treatment for persistent Borrelia infection remains to be determined.

Localized jawbone invasion is a milestone in the progression of oral squamous cell carcinoma (OSCC). The factors that promote this process are not well understood. Sclerostin is known to be involved in bone metabolism and there are preliminary reports of its involvement in bone tumors and metastasis. To identify a possible involvement of sclerostin in the bone invasion process of OSCC, sclerostin expression was analyzed in vitro in two different human OSCC tumor cell lines by qRT-PCR, and the effect of recombinant human (rh)-sclerostin treatment on tumor cell capabil-ities was evaluated using proliferation, migration, and invasion assays. Undifferentiated human mesenchymal stem cells (hMSCs) were osteogenically differentiated and co-cultured with OSCC tumor cells to demonstrate potential interactions on migration characteristics. Sclerostin expres-sion was evaluated in clinical cases by immunohistochemistry at the OSCC jawbone interface in a cohort of 15 patients. Sclerostin expression was detected in both OSCC tumor cell lines in vitro and was also detected at the OSCC jawbone interface in clinical cases. Tumor cell proliferation rate, migration and invasion ability were increased by rh-sclerostin treatment. The migration rate of tumor cells co-cultured with osteogenically differentiated hMSCs was increased. The re-sults presented are the first data suggesting a possible involvement of sclerostin in the bone inva-sion process of OSCC, which needs to be further investigated

The aim of this study was to investigate succinic acid production from lactose concentrate, a by-product of cheese-making, using Actinobacillus succinogenes and Basfia succiniciproducens. Although the capability of these strains to metabolize different sugars is already known, their application in the conversion of lactose bears high potential for optimization. With regard to B. succiniciproducens this approach is completely novel. In particular the influence of the mediums sugar concentration and its supplementation with yeast extract to prevent a lack of proteins and vitamins were examined. Lactose based media containing sugar concentrations between 20 and 65 g L-1 and 5 g L-1 yeast extract were fermented, whereby both strains showed comparable performances. The best results in succinic acid yield and acid concentration, 0.57 g g-1 initial sugar and 23 g L1, were achieved at an initial sugar concentration of 43 g L-1. The necessity of yeast extract was demonstrated using the sugar optimized medium without supplementation. As a result, yield and concentration of succinic acid dropped to 0.34 g g-1 and 13 g L-1, the sugar consumption decreased from more than 99 to less than 55 %. Therefore the supplementation amount of 5 g L-1 yeast extract can be regarded as well-balanced.

Hematological and biochemical reference values in sickle cell disease (SCD) are crucial for patient management and evaluation of interventions. This study was conducted at Muhimbili National Hospital (MNH) in Dar es Salaam, to establish laboratory reference ranges in SCD at steady-state. Patients were grouped into five age groups with respects to their sex. Aggregate functions were used to handle repeated measures within the indi-vidual level in each age group. A nonparametric approach was used to smooth the curves and a parametric approach was used to determine SCD normal ranges. Comparison between males and females and against the general population was documented. Data from 4,422 patients collected from 2004-2015 were analyzed. The majority of the patients (35.41%) were children aged between 5-11 years. There were no significant differences (p≥0.05) in mean corpuscular hemoglobin concentration (MCHC), lymphocytes, basophils and bilirubin direct observed between males and females. Significant differences (p<0.05) were observed in all selected parameters across age groups except neutrophils and MCHC in adults, as well as platelets and alkaline phosphatase in infants when SCD estimates were compared to the general population. Laboratory reference ranges in SCD at steady-state were different from those of the general population and varied with sex and age. The established reference ranges for SCD at steady-state will be a helpful in the management and monitoring of the progress of SCD.

Age-related macular degeneration (AMD) is a leading cause of blindness worldwide. In late-stage AMD, geographic atrophy (GA) of dry AMD or choroidal neovascularization (CNV) of neovascular AMD results in macular atrophy (MA), leading to significant visual loss. Despite the development of innovative therapies, there are currently no established effective treatments for MA. As a result, early detection of MA is critical in identifying later central macular involvement throughout time. Accurate and early diagnosis is achieved through a combination of clinical examination and imaging techniques. Our review of the literature depicted advances in retinal imaging to identify biomarkers of progression and risk factors for late AMD. Imaging methods like fundus autofluorescence (FAF), near-infrared reflectance (NIR), widefield imaging, optical coherence tomography (OCT), multicolor confocal scanning laser ophthalmoscopy (cSLO), and optical coherence tomography angiography (OCTA) can be used to detect and monitor the progression of retinal atrophy. Multifocal electroretinogram (ERG) and microperimetry are methods for quantifying visual function to map disease progression. The evolving diverse imaging modalities optimize detection of pathology anatomy and measurement of visual function; they may also contribute to the understanding of the underlying mechanistic pathways, particularly the underlying MA changes in late AMD.

Regenerative endodontic procedures (REPs) aim at recreating dental pulp tissue using biomaterials such as hydrogels. Their bioactivity is mostly linked to the nature of biomolecules or chemical compounds that will compose the endodontic hydrogel. However, many other parameters, such as hydrogel concentration, type, bioactive molecules solubility, of apex size were reported to influence the hydrogel behavior, leading to the inability to predict the clinical outcome. This lack of knowledge and the various parameters that should be considered, suggest that biological activity of endodontic hydrogel is impossible to anticipate and could hinder the bench to bedside transition. We formulated in this article our opinion that most of these parameters could be identified, described, and studied. A second part of the document lists some challenges and perspectives, including development of future mathematical models able to explain and predict the bioactivity of these endodontic hydrogel in clinic.

Selecting drought-tolerant and more water-efficient wheat genotypes is a research priority, spe-cifically in regions with irregular rainfall or areas where climate change is expected to result in reduced water availability. The objective of this work was to use high-throughput measurements with morphophysiological traits to characterize wheat genotypes in relation to water stress. Field experiments were conducted from May to September 2018 and 2019, using a sprinkler bar irriga-tion system to control water availability to eighteen wheat genotypes: BRS 254; BRS 264; CPAC 01019; CPAC 01047; CPAC 07258; CPAC 08318; CPAC 9110; BRS 394 (irrigated biotypes) and Aliança; BR 18_Terena; BRS 404; MGS Brilhante; PF 020037; PF 020062; PF 120337; PF 100368; PF 080492; TBIO Sintonia (rainfed biotypes). The water regimes varied from 22 to 100% of the crop evapotranspiration replacement. Water stress negatively affected gas exchange, vegetation indices and grain yield. High throughput variables TCARI, NDVI, OSAVI, SAVI, PRI, NDRE and GNDVI had higher correlation with yield and morphophysiological measurements. The drought re-sistance index indicated that genotypes Aliança BRS 254, BRS 404, CPAC 01019, PF 020062, and PF 080492 were more drought tolerant.

Sickle cell disease (SCD) is a blood disorder caused by a point mutation on the beta globin gene resulting in the synthesis of abnormal hemoglobin. Fetal hemoglobin (HbF) reduces disease severity, but the levels vary from one individual to another. Most research has focused on common variants which differ across populations and hence do not fully account for HbF variation. To investigate rare and common variants influencing HbF levels in SCD, we performed targeted next generation sequencing covering exonic and other significant fetal hemoglobin-associated loci, including BCL11A, MYB, HOXA9, HBB, HBG1, HBG2, CHD4, KLF1, MBD3, ZBTB7A and PGLYRP1. Results revealed a range of functionally relevant genetic variants. Notably, there were significantly more deletions in individuals with high HbF levels (11% vs 0.9%). We identified frameshift deletion in individuals with high HbF levels and frameshift insertions in individuals with low HbF. CHD4 and MBD3 genes, interacting in the same sub-network, were identified to have a significant number of pathogenic or non-synonymous mutations in individuals with low HbF levels, suggesting an important role of epigenetic pathways in the regulation of HbF synthesis. This study provides new insights in selecting essential variants associated with extreme HbF levels in SCD.

Solvent-free, single-ion conducting electrolytes are sought after for use in electrochemical energy storage devices. Here, we investigate the ionic conductivity and how this property is influenced by segmental mobility and conducting ion number in crosslinked single-ion conducting polyether-based electrolytes with varying tethered anion and counter-cation types. Crosslinked electrolytes are prepared by the polymerization of poly(ethylene glycol) diacrylate (PEGDA), poly(ethylene glycol) methyl ether acrylate, and ionic monomers. The ionic conductivity of the electrolytes is measured and interpreted in the context of differential scanning calorimetry and Raman spectroscopy measurements. A lithiated crosslinked electrolyte prepared with PEG₃₁DA and STFSI monomers is found to have a lithium ion conductivity of 3.2 × 10^-6 and 1.8 × 10⁻⁵ S/cm at 55 and 100 °C, respectively. The percentage of unpaired anions for this electrolyte was estimated at about 23% via Raman spectroscopy. Despite the large variances in metal cation – STFSI binding energies as predicted via DFT and large variations in ionic conductivity, STFSI-based crosslinked electrolytes with the same charge density and varying cations (Li, Na, K, Mg, and Ca) were estimated to all have unpaired anion populations in the range of 19 to 29%.

The objective was to estimate the correlation between VIs and grain yield and identify the optimal timing and VIs for precise corn grain yield estimation. Furthermore, the study aims to employ photographic quantification to measure corn ear traits and establish their correlation with corn grain yield. Ten corn hybrids were evaluated in CRB with three rep-lications at three locations. Vegetation indices and green leaf area were estimated throughout the cycle using an unmanned aerial vehicle (UAV) and subsequently corre-lated with grain productivity. In addition, photographs were taken of the corn ear to esti-mate their length, width and total number of kernels and compare these values with manual measurements. The experiments consistently demonstrated significant experi-mental quality across sites, with accuracy ranging from 79.07% to 95.94%. UAV flights carried out at the beginning of the crop cycle revealed a positive correlation between grain productivity and the evaluated indices (NGRDI, VARI, GLI). Regarding the phenotyping of corn ears, the regression coefficients for width, length and TNG were 0.92, 0.88 and 0.62, respectively, indicating an association with manual measurements. However, stage V5 in the localities of Lavras and Ijaci and stage V8 in the locality of Nazareno showed a posi-tive correlation with productivity. The use of images for ear phenotyping is promising as a method for measuring corn components.

Background: MRI-guided prostate biopsies from visible tumor-specific lesions (TBx) can be used to diagnose clinically significant carcinomas (csPCa) requiring treatment more selectively than conventional systematic biopsies (SBx). Ex vivo fluorescence confocal microscopy (FCM) is a novel technique that can be used to examine TBx prior to conventional histologic workup. Methods: TBx from 150 patients were examined with FCM on the day of collection. Preliminary findings were reported within 2 hours of collection. The results were statistically compared with the final histology. Results: 27/40 (68%) of the csPCa were already recognized in the intraday FCM in accordance with the results of conventional histology. Even non-significant carcinomas (cisPCa) of the intermediate and high-risk groups (PSA &gt; 10 or 20 ng/ml) according to conventional risk stratifications were reliably detectable. In contrast, small foci of cisPCa were often not detected or were difficult to distinguish from reactive changes. Conclusion: The rapid reporting of preliminary FCM findings helps reduce the psychological stress on patients an can improve the clinical management of csPCa. Additional SBx can be avoided in individual cases, leading to lower rates of complications and scaring in the future surgical area. Additional staging examinations can be arranged without losing time. FCM represents a promising basis for future AI-based diagnostic algorithms.

The transnational spread of coronavirus (2019-nCoV) first detected in Wuhan is causing global panic; thus, accelerated research into clinical intervention is of high necessity. The spike glycoprotein structure has been resolved, and its affinity to human angiotensin-converting enzyme 2 (ACE-2) has been experimentally validated. Here, using computational methods, a metastable conformation of 2019-nCoV-RBD/ACE-2 complex has been revealed and FDA-database of approved drugs have been docked into the interface. Darunavir has been discovered as high ligand affinity candidate capable of disrupting communication between 2019-nCoV-RBD and ACE-2. Darunavir, in addition to its previously known anti-HIV protease inhibitor is now repurposeable for the treatment 2019-nCoV disease acting via disruption of cellular recognition, binding and invasion.

Using straightforward and cost-effective methods, persimmon leaves were converted into a high-quality powder. This powder was applied as an adsorbent for the removal of Cu(II) and Cd(II) from aqueous solutions. Scanning electron microscopy (SEM) indicated the presence of particles with non-homogeneous sizes and rough texture. Elemental analysis and the EDX technique confirmed the presence of elements such as sulfur, phosphorus, nitrogen, and oxygen. The results of ¹³C nuclear magnetic resonance (¹³C-NMR), obtained through the cross-polarization technique, suggest the presence of groups containing sulfur and oxygen. Infrared spectroscopy (FTIR) indicated the existence of amine and hydroxyl groups. The material was used in solid-phase extraction of Cu(II) and Cd(II) in batch experiments, and its adsorption capacity was evaluated as a function of time, pH, and analyte concentration. Kinetic equilibrium was reached within 5 minutes, and the experimental data were fitted to the pseudo-second-order kinetic model. The optimum pH for adsorption of both metal species was observed to be around 5.0. The adsorption isotherms were adjusted using the modified Langmuir equation, and the maximum amount of metal species extracted from the solution was determined to be 0.213 mmol g^-1 for Cu(II) and 0.215 mmol g^-1 for Cd(II), with high linear correlation coefficients for both metals. The persimmon leaves are typically abundant during the growing season, and since they are seasonal, the Diospyros kaki L.f. tree undergoes the natural process of leaf abscission, ensuring the availability of leaves for application.

In light of the globally increasing prevalence of diet-related non-communicable diseases (NCDs), new scalable and non-invasive dietary monitoring techniques are urgently needed. Automatically collected digital receipts from loyalty cards have the potential to serve as an objective and automatically traceable digital biomarker for individual food choice behavior and do not require patients to manually log each individual meal item. Until recently, such electronic purchase records were hard to collect for researchers and were only validated in national empirical studies. Multiple quantitative indicators for purchase quality have been suggested, but so far no comparison has validated the potential of these alternative indicators to discriminate between health-beneficial and -detrimental food choices. With the introduction of the General Data Privacy Regulation in the European Union, millions of consumers gained the right to access their purchase data in a machine-readable form, representing a historic chance to leverage purchase data for scalable monitoring of food choices. This study hence is the first study comparing the calibration capacity and validating the discrimination potential of previously suggested purchase indicators for the nutritional quality of purchased groceries, incl. HEI-2015, HETI, GPQI, and FSA-NPS DI. To assess the indicators' potential, 464 study participants were asked to complete a validated food frequency questionnaire (FFQ) and to donate their digital receipts from the loyalty card programs of the two leading Swiss grocery retailers, representing 69\% of the national grocery market. 89 participants fulfilled the eligibility criteria, i.e. completed the FFQ and were frequent users of the loyalty card systems. Compared to absolute food and nutrient intake, correlations between density-based relative food and nutrient intake and food purchase data are stronger. Counterintuitively, although the frameworks of the HETI and the GPQI are centered around food groups, both indicators do not capture food group intake such as vegetables or sweets very well. The FSA-NPS DI has the best calibration and discrimination performance in classifying participants' consumption of nutrients and food groups, and seems to be a superior indicator to estimate nutritional quality of a user's diet based on digital receipts from grocery purchases in Switzerland.

This survey reports on the DNA identification and occurrence of Culex torrentium and Cx. pipiens s.s. in Belgium. These native disease vector mosquito species are morphologically difficult to separate and the biotypes of Cx. pipiens s.s. are morphologically indistinguishable. Culex torrentium and Cx. pipiens s.s. were identified using the COI and ACE2 loci. We recorded 1,248 Cx. pipiens s.s. and 401 Cx. torrentium specimens from 24 locations in Belgium (collected between 2017 and 2019). Culex pipiens biotypes pipiens and molestus, and their hybrids, were differentiated by fragment size analysis of the CQ11 locus (956 pipiens and 227 molestus biotype specimens, 29 hybrids). Hybrids were observed at 13 out of 16 sympatric sites. These results confirm that both species are widespread in Belgium, but while Cx. torrentium revealed many COI haplotypes, Cx. pipiens s.s. showed only one abundant haplotype. This latter observation may either reflect a recent population-wide demographic or range expansion, or a recent bottleneck, possibly linked to a Wolbachia infection. Finally, new evidence is provided for the asymmetric but limited introgression of the molestus biotype into the pipiens biotype.

Antimicrobial use (AMU) is one of the major drivers of emerging antimicrobial resistance (AMR). Surveillance of AMU, a pillar of AMR stewardship (AMS), helps devise strategies to mitigate AMR. This descriptive, longitudinal retrospective study quantified the trends in human antibiotic utilization between 2010 and 2016 using data on all antibiotics imported for systemic human use into Tanzania's mainland. Regression and time series analyses were used to establish trends in antibiotics use. A total of 12,073 records for antibiotics were retrieved, totaling 154.51Daily Defined Doses per 1,000 inhabitants per day (DID) with a mean (± standard deviation) of 22.07 (±48.85) DID. The private sector contributed 93.76%% of utilized antibiotics. The top-ranking antibiotics were amoxicillin, metronidazole, tetracycline, ciprofloxacin and cefalexin. The DDIs and percentage contribution of these antibiotics were 53.78 (34.81%), 23.86 (15.44), 20.53 (13.29), 9.27 (6.0) and 6.94 (4.49), respectively. The time series model predicted significant increase in utilization(p-value =0.002). The model forecasted that by 2022, the total antibiotics consumed would reach 89.6 DIDs, corresponding to a 13-fold increase compared to 2010. Government intervention to curb inappropriate antibiotic utilization to mitigate the rising threat of antibiotic resistance should focus on implementing AMS programs in pharmacies and hospitals in Tanzania.

Carbapenemase resistance in Enterobacterales is a global public health problem and rapid and effective methods to detect resistance mechanisms are needed urgently. Our aim was to evaluate the performance of a MALDI-TOF MS based KPC detection protocol from patients’ positive blood cultures, short-term cultures and colonies at health care settings. Bacterial identification and KPC detection were achieved after protein extraction with organic solvents and target spot loading with suitable organic matrices. Confirmation of KPC production was performed by susceptibility tests, blaKPC amplification by PCR and sequencing. KPC direct detection (KPC-peak at approximately 28.681 Da) from patients’ positive blood cultures, short-term cultures and colonies, once bacterial identification was achieved, showed an overall sensibility and specificity of 100% (CI95: [95%,100%] and CI95: [99%, 100%], respectively). Concordance between hospital routine bacterial identification protocol and identification with this new methodology from the same extract used for KPC detection was ≥92%. This study represents the pioneering effort to directly detect KPC using MALD-TOF MS technology, conducted on patient-derived samples obtained at the hospitals for validation purposes, in a multi-resistance global context that requires concrete actions to preserve available therapeutic options and reduce the spread of antibiotic resistance markers.

Ternary ZnS/ZnO/graphitic carbon nitride (gCN) photocatalysts were prepared by coupling gCN sheets with ZnO nanorods under solvothermal conditions followed by sulfurization using Na2S. SEM and TEM analyses show that small-sized ZnS particles (ca. 7.2 nm) deposit homo-geneously on the surface of ZnO/gCN nanohybrids. Photoluminescence and electrochemical impedance spectroscopy show that ZnS allows an enhanced charge separation efficiency as well as prolonged lifetime of photogenerated charge carriers, leading to improved hydrogen photo-production under UV light irradiation compared to ZnO/gCN. Moreover, the deposition of ZnS nanoparticles improves the photostability of the ZnS/ZnO/gCN catalyst for hydrogen produc-tion. A double Z-scheme mechanism is proposed for hydrogen photoproduction using the ZnS/ZnO/gCN heterojunction.

This study aimed at evaluating changes in the clinical and echocardiographic parameters of pregnant sheep, as well as the HRV indexes due to the physiological alterations that happen at this stage implicating in high maternal metabolic demands. For this purpose, the study evaluated 10 Dorper sheep through their pregnancy, starting from the second month until the day before birth, conducting clinical, echocardiographic and electrocardiographic examinations focused on the HRV. The echocardiogram was conducted in a doppler ultrasound device with a multifrequency sectorial transducer in bidimensional mode. The HRV indexes were obtained through the Televet 100® system. There were increases in the thickness of the interventricular septum during diastole starting from the third month, and in the internal diameter of the left ventricle during systole and diastole at the second and third months, while the ejection fraction increased as the pregnancy progressed. The size of the left atrium increased starting at the second month. The SDNN, RMSSD and PNN50 HRV indexes were higher at the fifth month of pregnancy and after delivery. There were no significant differences in the frequency-domain HRV indexes during pregnancy. The gestation leads to alterations in the clinical parameters and the activity of the autonomic nervous system.

Global warming caused by climate change is a challenge for dairy farming, especially in sub-Saharan countries. Under high temperature and relative humidity dairy cows suffer from heat stress. The objective of this study was to investigate the effects and relationship of heat stress (HS) measured by temperature-humidity index (THI) on physiological parameters and milk yield and composition of lactating Holstein Friesian crosses reared in the humid coastal region of Tanzania. A total of 29 lactating Holstein Friesian x Zebu crossbred dairy cattle with 50% (HF50) and 75% (HF75) Holstein Friesian blood levels in their second and third month of lactation were used. Breed composition of Holstein Friesian was determined based on animal recording system used at the Tanzania Livestock Research Institute (TALIRI), Tanga. Data collected included daily temperature, relative humidity, daily milk yield, and physiological parameters (core-body temperature, rectal temperature, respiration rate, and panting score). The THI was calculated using the equation of National Research Council [39]. The THI values were categorized into three classes i.e. low THI (76-78), moderate THI (79-81) and high THI (82-84). The effects of THI on physiological parameters and milk yield and composition were assessed. Also, the effects of genotype, parity, lactation month, and interaction of these parameters with THI i on milk yield, milk composition, and physiological parameters were investigated. The results indicate that THI and its interaction with genotypes, parity, and lactation month had highly significant effect on all the parameters. THI affected (P ˂ 0.05) average daily milk yield and milk fat %, protein %, lactose %, and solids – not – fat %. When THI increased from moderate to high values, average daily milk yield declined from 3.49 ± 0.04 to 3.43 ± 0.05 liters/day while fat % increased from 2.66 ± 0.05% to 3.04 ± 0.06% and protein decreased from 3.15 ± 0.02% to 3.13 ± 0.03%. No decline was observed on lactose % whilst solids – not – fat % declined from 8.56 ± 0.08% to 8.55 ± 0.10%, when the THI values increased from moderate to high. Also, THI affected (P˂0.05) physiological parameters. Core-body temperature (CBT), rectal temperature (RT), respiration rate (RR) and panting score (PS) increased from 35.60 ± 0.01 to 36.00 ± 0.01oC, 38.03 ± 0.02 to 38.3.30 ± 0.02oC, 62.53 ± 0.29 to 72.35 ± 0.28 breaths/min and 1.35 ± 0.01 to 1.47 ± 0.09, respectively, when THI increased from low to high. THI showed a low positive correlation with average daily milk yield and fat percentage whilst protein, lactose, and solids – not - fat percentages showed negative relationships with THI (P ≤ 0.05). The CBT, RT, RR, and PS showed positive relationships (P ≤ 0.05) with THI. These negative relationships indicate that there is an antagonistic correlation between sensitivity to HS and degree of production. It is concluded that the THI, genotype, parity, and lactation month, and their interactions with THI significantly affected milk yield, milk composition, and physiological parameters of lactating Holstein Friesian dairy crosses at THI thresholds ranging from 77 to 84.

As a conceptual model of disease mechanisms, a disease map integrates available knowledge and is applied for data interpretation, predictions and hypothesis generation. It is possible to model disease mechanisms on different levels of granularity and adjust the approach to the goals of a particular project. This rich environment together with requirements for high-quality network reconstruction makes it challenging for new curators and groups to be quickly introduced to the development methods. In this review, we offer a step-by-step guide for developing a disease map within its mainstream pipeline that involves using the CellDesigner tool for creating and editing diagrams and the MINERVA Platform for online visualisation and exploration. We also describe how the Neo4j graph database environment can be used for managing and querying efficiently such a resource. For assessing the interoperability and reproducibility we apply FAIR principles.

Patients with low back pain often have deficits in trunk stability. For this reason, many patients receive physiotherapy treatment, which represents an enormous socio-economic burden. Training at home could reduce these costs. The prob-lem here is the lack of correction of the exercise execution. This feasibility study therefore investigates the applicability of a vibrotactile-controlled feedback system for trunk stabilization exercises. A sample of 13 healthy adults performed three trunk stabilization exercises. Exercise performance was corrected by physiotherapists using vibrotactile feedback. The NASA TLX questionnaire was used to assess the practicability of the vibrotactile feedback. The Nasa TLX questionnaire show a very low global workload M = 37.96 (SD =11.63). The quality of feedback perception was perceived as good by the subjects, varying between 76.9 % and 92.3 % depending on the body part. 80.8 % rated the feedback as helpful for their training. On the expert side, the results show a high rating of movement quality. The positive evaluations of the physiotherapists and the participants on the use of the vibrotactile feedback system indi-cate that such a system can reduce the trainees fear of independent training and support the users in their training. This could increase training adherence and long-term success.

Spectral unmixing represents both an application per se and a pre-processing step for several applications involving data acquired by imaging spectrometers. However, there is still a lack of publicly available reference data sets suitable for the validation and comparison of different spectral unmixing methods. In this paper we introduce the DLR HyperSpectral Unmixing (DLR HySU) benchmark dataset, acquired over German Aerospace Center (DLR) premises in Oberpfaffenhofen. The dataset includes airborne hyperspectral and RGB imagery of targets of different materials and sizes, complemented by simultaneous ground-based reflectance measurements. The DLR HySU benchmark allows a separate assessment of all spectral unmixing main steps: dimensionality estimation, endmember extraction (with and without pure pixe assumption), and abundance estimation. Results obtained with traditional algorithms for each of these steps are reported. To the best of our knowledge, this is the first time that real imaging spectrometer data with accurately measured targets are made available for hyperspectral unmixing experiments. The DLR HySU benchmark dataset is openly available online and the community is welcome to use it for spectral unmixing and other applications.