Patient group engagement is increasingly used to inform the design, conduct, and dissemination of clinical trials and other medical research activities. However, the priorities of industry sponsors and patient groups differ, and there is currently no framework to help these groups identify mutually beneficial engagement activities. Methods: We conducted 28 qualitative, semi-structured interviews with representatives from research sponsor organizations (n=14) and patient groups (n=14) to determine: 1) how representatives define benefits and investments of patient group engagement in medical product development and, 2) to refine a list of 31 predefined patient group engagement activities. Results: Patient group and sponsor representatives described similar benefits: engagement activities can enhance the quality and efficiency of clinical trials by improving patient recruitment and retention, reduce costs, and help trials meet expectations of regulators and payers. All representatives indicated that investments include both dedicated staff time and expertise, and financial resources. Factors to consider when evaluating benefits and investments were also identified as were suggestions for clarifying the list of engagement activities. Discussion: Using these findings, we refined the 31 engagement activities to 24 unique activities across the medical product development lifecycle. We also developed a web-based prioritization tool (https://prioritizationtool.ctti-clinicaltrials.org/) to help clinical research sponsors and patient groups identify high priority engagement activities. Use of this tools can help sponsors and patient groups identify the engagement activities that they believe will provide the most benefit for the least investment and may lead to more meaningful and mutually beneficial partnerships in medical product development.

Background: Good clinical practice (GCP) training is the industry standard for ensuring the quality conduct of registrational clinical trials. However, concerns have been raised about whether the current structure and delivery of GCP training sufficiently prepares clinical investigators and their delegates to conduct clinical trials. Methods: We conducted qualitative semi-structured interviews with 13 clinical investigators and 10 research sponsors to 1) examine characteristics of the quality conduct of sponsored clinical trials, including critical tasks and concerns perceived as essential for trial quality, 2) identify key knowledge and skills required to perform critical tasks, and 3) identify gaps and redundancies in GCP training and areas of improvement to ensure the quality conduct of clinical trials. We used applied thematic analysis to analyze the data. Results: The top three tasks identified as critical for the quality conduct of clinical trials were obtaining informed consent, ensuring protocol compliance, and protecting participants’ health and safety. Respondents acknowledged that GCP principles address each of these critical tasks; however, they described many challenges and burdens of GCP training, including high training frequency and repetitive content. Respondents suggested moving beyond GCP training as a mere check-box activity by making it more effective, engaging, and interactive. They also emphasized that applying GCP principles in a real-world, skills-based environment would increase the relevance of GCP training to investigators and their delegates. Conclusion: Our findings indicate that although investigators and sponsors recognize that GCP training addresses critical tasks necessary to the quality conduct of clinical trials, they articulated the need for significant improvement in the design, content, and presentation of GCP training.

This study reports on empirical findings of participatory design workshops for the development of a supportive user experience design system in the automotive. Identifying and addressing this area with traditional research methods is problematic due to the different UX design perspectives that might be conflicting and the related automotive domain limitations. To help resolve this problem, we conducted research with 12 User Experience (UX) designers through individual participatory prototyping activities to gain insights on their explicit, observable, tacit and latent needs. These activities allowed us to explore their motivation to use different technologies; the system's architecture; detailed features of interactivity and describe user needs including Efficiency, Effectiveness, Engagement, Naturalness, Ease of Use, Information retrieval, Self-Image awareness, Politeness, and Flexibility. Our analysis led us to design implications that translate participants' needs into UX design goals, informing practitioners on how to develop relevant systems further.

Protected areas, such as natural World Heritage sites, RAMSAR wetlands, and Biosphere reserves are ecosystems within landscapes. Each site meets certain criteria that allow it to qualify as heritage or protected. Both climate change and human influence (e.g., incursion, increased tourist visitation) are altering biophysical conditions at many such sites. As a result, conditions at many sites are falling outside the criteria for their original designation. The alternatives are to change the criteria, remove protection from the site, change site boundaries such that the larger or smaller landscape meets the criteria, or manage the existing landscape in some way that reduces the threat. This paper argues for adaptive heritage, an approach that explicitly recognizes changing conditions. We discuss the need to view heritage areas as parts of a larger landscape, and to take an adaptive approach to management of that landscape. We offer five themes of adaptive heritage: 1) treat sites as living heritage, 2) employ innovative governance, 3) embrace transparency and accountability, 4) invest in monitoring and evaluation, and 5) manage adaptively. We offer the Australian Wet Tropics as an example where aspects of adaptive heritage currently are practiced, highlighting the tools being used. This paper offers guidance supporting decisions about natural heritage in the face of climate change and non-climatic pressures. Rather than delisting or lowering standards, we argue for adaptive approaches.

Rationale:First discovered in 1990, the endocannabinoid system (ECS) was initially shown to have an intimate relationship with central areas of the nervous system associated with pain, reward, and motivation. Recently, however, the ECS has been extensively implicated in the cardiovascular system with contractility, heart rate, blood pressure, and vasodilation. Emerging data demonstrates modulation of the ECS plays an essential role in cardio metabolic risk, atherosclerosis, and can even limit damage to cardiomyocytes during ischemic events.Patient Concerns:This case describes a 63-year-old male who presented to a primary care physician for a medical cannabis (MC) consult due to unstable angina (UA) not relieved by morphine or cardiac medications; having failed all first- and second-line poly-pharmaceutical therapies. The patient reported frequent, unprovoked, angina and exertional dyspnea.Diagnosis:Having a complex cardiac history, the patient first presented 22 years ago after a suspected myocardial infarction (MI). He re-presented in 2010 and underwent stent placement at that time for inoperable triple-vessel coronary artery disease (CAD) which was identified via percutaneous transluminal coronary angioplasty. UA developed on follow up and, despite medical management over the past 6 years, his UA became progressively debilitating.Interventions and Outcomes:In conjunction with his standard cardiac care, patient had a gradual lessening of UA related pain, including frequency and character, after using an edible form of medical cannabis (MC) (1:1 CBD:THC). Following continued treatment, he ceased long term morphine treatment and describes the pain as no longer crippling. As demonstrated by his exercise tolerance tests, the patient experienced an improved functional capacity and reported an increase in his daily functioning, and overall activity.Lessons:This case uniquely highlights MC in possibly reducing the character, quality, and frequency of UA; while concordantly improving functional cardiac capacity in a patient with CAD. Additional case reports are necessary to verify this.

This paper discusses the preliminary results of archaeological surveys conducted in the Juuku Region of north-central Kyrgyzstan on the south side of Lake Issyk kul. Our goal was to document ancient and contemporary agropastoral systems over a four millenia time period. During the surveys about 350 loci were identified as settlements, burial mounds, graves, single artifact finds, and artifact scatters (ceramic). The areas of Juuku Valley survey included two discrete polygons: Polygon 1, Lower Juuku at 1750 to 1950 m asl in elevation and Polygon 2, Chak Juuku or Upper Eastern Branch Juuku Valley at 2060 to 2100 m asl in elevation. Three radiometric dates and preliminary archaeobotanical studies were conducted at three exposed profile cuts. The methods included here are: (1) pedestrian surveys; (2) use of digital maps (Google Earth, Encarta); (3) placing archaeological loci within known chronological time periods; (4) AMS dating of charcoal samples collected from profile deposits; and (5) preliminary identification of plant remains found from archaeobotanical samples. The results of our research represent the first step toward inventorying and interpreting archaeological data in the Juuku Valley derived from field studies.

Gelatinization of starch content in pet foods can be impacted by several factors including moisture, retention time, and ingredients used. Starch gelatinization has been associated with digestibility but isn’t well studied using ingredients common in non-traditional canine diets. The objective of this research was to examine the impacts of dietary ingredient profile (traditional vs non-traditional) and assess impacts to total starch content and starch gelatinization. Traditional diets (n = 10) utilizing meat-based ingredients including chicken, chicken by-product meal, meat and bone meal and plant-based ingredients including rice, barley, oats, and corn were examined in comparison with non-traditional diets (n = 10) utilizing meat-based ingredients including alligator, buffalo, venison, kangaroo, squid, quail, rabbit, rabbit and salmon along with plant-based ingredients including tapioca, peas, chickpeas, lentils, potato, and pumpkin. Representative samples were collected via grab sample technique (5 samples/diet) and were assessed for total starch content as well as percent starch gelatinization. Difference between ingredient type was assessed using a Students t-test in SAS 9.4. Significance was set at P < 0.05. Distribution of total starch content based on ingredient type (traditional vs non-traditional) revealed that mean total starch content was higher in traditional diets as compared to non-traditional diets (P <0.0001). Conversely, starch gelatinization was found to be higher in non-traditional diets (P < 0.0001). Total starch content and total gelatinized starch had a strong negative correlation (P < 0.01) in traditional diets, though no correlation was observed in non-traditional diets. This negative correlation indicates a decrease in total gelatinized starch associated with increased total starch content. These novel data reveal important differences between starch content and gelatinization and could impact manufacturing processes for ingredient types as well as feeding recommendations. Unpredicted variation between ingredient formulations could potentially lead to decreased digestibility and absorption and may result in nutrient deficiencies.

Duchenne muscular dystrophy (DMD) is caused by genetic mutations in the cytoskeletal-sarcolemmal anchor protein dystrophin. Repeated cycles of sarcolemmal tearing and repair lead to a variety of secondary cellular and physiological stressors that are thought to contribute to weakness, atrophy, and fibrosis. Collectively, these stressors can contribute to a pro-inflammatory milieu in locomotor, cardiac, and respiratory muscles. Given the many unwanted side effects that accompany current anti-inflammatory steroid-based approaches for treating DMD (e.g., glucocorticoids), there is a need to develop new therapies that address inflammation and other cellular dysfunctions. Adiponectin receptor (AdipoR) agonists, which stimulate AdipoR1 and R2 isoforms on various cell types, have emerged as therapeutic candidates for DMD due to their anti-inflammatory, anti-fibrotic, and pro-myogenic properties in pre-clinical human and rodent DMD models. Although these molecules represent a new direction for therapeutic intervention, the mechanisms through which they elicit their beneficial effects are not yet fully understood, and DMD-specific data is limited. The overarching goal of this review is to investigate how adiponectin signaling may ameliorate pathology associated with dystrophin deficiency through inflammatory-dependent and -independent mechanisms, and to determine if current data supports their future progression to clinical trials.

Malawi has developed an excellent, nation-wide system for monitoring people infected with HIV and keeping track of key epidemic markers. Their success lies in two things: the focus on simplicity and the use of data collection not only to track the epidemic and identify problems but also to give regular feedback and support to every clinic in the country. This achievement is the more remarkable given that Malawi is one of the poorest countries in the world, ranking 190 out of 194 countries by GDP, but has one of the most severe epidemics of HIV in the world, ranking 9th out of 168 countries by HIV prevalence. We first discuss the current state and likely future epidemic trends in Malawi: unless we know where we are and where we are going we cannot decide what to do or how to do it to in order to achieve a better outcome. We then discuss the history and development of Malawi’s patient monitoring system, as reported in their Integrated HIV Program Reports,ix which have been published quarterly since the beginning of 2004. We consider the current state of patient monitoring and support as reflected in the most recent report for the third quarter (Q3) of 2016 and comment on some of the questions that this raises. Finally, we consider ways in which the current system could be improved by strengthening Malawi’s analytical capacity and making better use of this unique data set. The focus here is on HIV in adultsv because if ART is initiated early in all adults living with HIV this should include testing all pregnant women for HIV and starting them on treatment immediately. However, PMTCT is especially important and care must be given to reducing MTCT and identifying the long-term child survivors of mother-to-child transmission and this demands a complementary assessment. There is an ongoing debate about the relative merits of treatment and prevention in reducing transmission and it should be made clear that the primary reason for starting people on treatment early is that it is in the best interest of the individual patient to start treatment as soon as possible after becoming infected. Allowing a person’s immune system to deteriorate to any degree is not consistent with the clinician’s commitment to ‘first do no harm’ and even those with the highest CD4⁺ cell count are at a substantially increased risk of death. What matters, therefore, is to get as many people as possible onto ART, ensure that they remain virally suppressed, and consider prevention in this context.

In contrast to animals, adult organs in plants are not determined during embryogenesis but gen-erated from meristematic cells as plants advance through development. Plant development in-volves a succession of different phenotypic stages and the transition between these stages is termed phase transition. Phase transitions need to be tightly regulated and coordinated to ensure they occur under optimal seasonal, environmental conditions. Polycarpic perennials transition through vegetative stages and the mature, reproductive stage many times during their lifecycles and, in both perennial and annual species, environmental factors and culturing methods can re-verse the otherwise unidirectional vector of plant development. Epigenetic factors regulating gene expression in response to internal cues and external (environmental) stimuli influencing the plant’s phenotype and development have been shown to control phase transitions. How develop-mental and environmental cues interact to epigenetically alter gene expression and influence these transitions are not well understood and understanding this interaction is important considering the current climate change scenarios, since epigenetic maladaptation could have catastrophic con-sequences for perennial plants in natural and agricultural ecosystems. Here we review studies focussing on the epigenetic regulators of the vegetative phase change and highlight how these mechanisms might act in exogenously induced plant rejuvenation and regrowth following stress.

1) Background: Climate change may subject forests to climate conditions to which they are not adapted. Elevated temperatures reduce net photosynthesis by increasing respiration rates and increasingly long droughts dramatically increase morbidity. CO₂ enrichment enhances productivity, but it is not clear to what extent CO₂ enrichment can offset the negative effects of elevated temperatures and longer droughts. 2) Methods: We used a mechanistic landscape model to conduct controlled simulation experiments manipulating CO₂ concentration, temperature, drought length and soil water capacity. 3) Results: We found that elevated CO₂ stimulates productivity such that it dwarfs the negative effect caused by elevated temperature. Energy reserves were not as strongly mitigated by elevated CO₂, and mortality of less competitive cohorts increased. Drought length had a surprisingly small effect on productivity measures, but had a marked negative effect on mortality risk. 4) Conclusions: Elevated CO₂ compensated for the negative effect of longer droughts in terms of productivity measures, but not survival measures.

Staphylococcus aureus can develop resistance by mutation, tranfection or biofilm formation. Resistance was induced in S. aureus by growth in sub-inhibitory concentrations of ciprofloxacin for 30 days. The ability of the antimicrobials to disrupt biofilms was determined using crystal violet and live/dead staining. Effects on the cell membranes of biofilm cells was evaluated by measuring release of dyes and ATP and nucleic acids. S. aureus did not develop resistance to the AMPs but resistance increased to ciprofloxacin by 128 times after 30 passages. Only peptides reduced biofilms of ciprofloxacin resistant cells. The antibiofilm effect of melimine with ciprofloxacin was more (27%) than with melimine alone at 1X MIC (p < 0.001). Similarly, at 1X MIC the combination of Mel4 and ciprofloxacin produced more (48%) biofilm disruption than Mel4 alone (p < 0.001). Combinations of either of the peptides with ciprofloxacin at 2X MIC released  66 nM ATP, more than either peptide alone (p  0.005). At 2X MIC, only melimine in combination with ciprofloxacin released DNA/RNA which was 3 times more than released by melimine alone (p = 0.043). These results suggest the potential use of melimine and Mel4 with conventional antibiotics for the treatments of S. aureus biofilms.

South Africa is afflicted with the worst epidemic of HIV in the world a legacy of the system of oscillating migrant labour in the region and the consequent social disruption that was the legacy of Apartheid. The initial response from the national government was slow and ineffective but once the magnitude of the epidemic became apparent the government began to respond. The investment in HIV- and TB-related activities in 2013 was R22 Bn or (US$2.5; 2013 exchange rate) of which the South Africa government contributed 80% and the Presidents Emergency Plan for AIDS Relief (PEPFAR) 17%. South Africa now has the more people on anti-retroviral therapy than any other country and treatment is being started much sooner after infection. Much of the best biomedical, virological, immunological, mathematical and social science around the treatment and prevention of HIV and AIDS and the associated epidemic of TB has been done by South African’s and their international collaborators. If the efforts to control the epidemic are maintained South Africa is on track to meet the UNAIDS 90-90-90target by 2020 and to End AIDS by 2030 in spite of the magnitude of the problem. While individual, patient level data are increasingly available, especially in the Western Cape, much greater efforts need to be made to ensure that the information collected in this way is used to give feedback and support to clinic staff, to ensure that health clinics are providing the best possible service, and to individual patients and people living with HIV to ensure that they are receiving the best possible care and support. South Africa needs to make better use of the rich and detailed data that are being collected from individual clinics and their patients to identify problems or difficulties at the clinic level and to ensure that individual patients are retained on treatment, are virally suppressed and receive the best possible care and support.

(1) Background: The purpose of this study is to evaluate the full arch scan accuracy (precision and trueness) of nine digital intra-oral scanners and four lab scanners. Previous studies have compared the accuracy of some intra-oral scanners, but as this is a field of quickly developing technologies, a more up-to-date study was needed to assess the capabilities of currently available models.; (2) Methods: The present in vitro study compared nine different intraoral scanners (Omnicam 4.6; Omnicam 5.1; Primescan; CS 3600; Trios 3; Trios 4; Runyes; i500 and DL206) as well as four lab light scanners (Einscan SE; 300e; E2 and Ineos X5) to investigate the accuracy of each scanner by examining the overall trueness and precision. Ten aligned and cut scans from each of the intra-oral and lab scanners in the in vitro study were brought into CloudCompare. A comparison was made with the master STL using the CloudCompare 3D analysis best-fit algorithm. The results were recorded along with individual standard deviation and a colorimetric map of the deviation across the surface of the STL mesh; a comparison was made to the master STL, quantified at specific points. ; (3) Results: In the present study, the Primescan had the best overall trueness (17.3 ± 4.9). Followed by (in order of increasing deviation) the Trios 4 (20.8 ± 6.2), i500 (25.2 ± 7.3), CS3600 (26.9 ± 15.9), Trios 3 (27.7 ± 6.8), Runyes (47.2 ± 5.4), Omnicam 5.1 (55.1 ± 9.5), Omnicam 4.6 (57.5 ± 3.2) and Launca DL206 (58.5 ± 22.0). Regarding the lab light scanners, the Ineos X5 had the best overall trueness with (0.0 ± 1.9). Followed by (in order of increasing deviation) the 3Shape E2 (3.6 ± 2.2), Up3D 300E (12.8 ± 2.7), and Einscan SE (14.9 ± 9.5); (4) Conclusions: This study confirms that all current generations of intra-oral digital scanners can capture a reliable, reproducible full arch scan in dentate patients. Out of the intra-oral scanners tested, no scanner produced results significantly similar in trueness to the Ineos X5. However, the Primescan was the only one to be statistically of a similar level of trueness to the 3Shape E2 lab scanner. All scanners in the study had mean trueness of under 60-micron deviation. While this study can compare the scanning accuracy of this sample in a dentate arch, the scanning of a fully edentulous arch is more challenging. The accuracy of these scanners in edentulous cases should be examined in further studies.

Dust inhalation is a huge concern in the mining environment and within all its operations. In fact, dust to be one of the most serious occupational hazards in the mining industry. Coal and crystalline silica dust are the causes of serious, sometimes fatal lung diseases such as pneumoconiosis, which affects coal miners, as well as silicosis, tuberculosis, chronic bronchitis, emphysema, chronic obstructive pulmonary disease, and chronic renal disease, which affect coal and other types of miners. The resulting effects both affect workers and nearby communities. The mining industry has in the past, employed several approaches to reduce effects of dust. But these strategies have often been ineffective because the grass withers during the dry season and sprayed water is rapidly absorbed or evaporates. This paper endeavors to review information on dust in the mining environment and how it is a nuisance to workers and communities and establish what strategies exist for this.

Introduction: The term 3D printing is commonly used to depict an assembling method whereby the final form of an object is the result of the addition of different layers to build the frame of an object. This procedure is more accurately portrayed as additive manufacturing and is likewise alluded to as fast prototyping. The term 3D printing, in any case, is generally new and has been an active part of current developments in Dentistry. Much publicity encompasses the evolution of 3D printing, which is hailed as an innovation that will perpetually change CAM manufacturing, including in the dental sector. This review is the first part in a 3D Printing series that looks at the history of 3D Printing, the technologies available and reviews the literature relating to the accuracy of these technologies. Conclusions: The recent advancement in digital dentistry to incorporate these tools has modernised dental practices by paving the way for computer-aided design (CAD) technology and rapid prototyping. The use of 3D printing has led to 3D digital models produced with intraoral scanners (IOS), which can be manipulated easily for diagnosis, treatment planning, mockups, and a multitude of other uses. Combining 3D Printing with a 3D intraoral scan eliminates the need for physical storage but makes it to retrieve a 3D models for use within all dental modalities.

Capacitive contact imaging has shown potential in measuring skin properties including hydration, micro relief analysis, as well as solvent penetration measurements. Through calibration we can also measure the absolute permittivity of the skin, and from absolute permittivity we then work out the absolute solvent content in skin. In this paper, we present our latest study of capacitive contact imaging for skin characterizations and vivo skin solvent penetration. We will show how to use capacitive occlusion measurements to characterize skin damages, and how to calculate the absolute water content and solvent content in skin.

The ability to replicate scientific experiments is a cornerstone of the scientific method. Sharing ideas, workflows, data, and protocols facilitates testing the generalizability of results, increases the speed that science progresses, and enhances quality control of published work. Fields of science such as medicine, the social sciences, and the physical sciences have embraced practices designed to increase replicability. Granting agencies, for example, may require data management plans and journals may require data and code availability statements along with the deposition of data and code in publicly available repositories. While many tools commonly used in replicable workflows such as distributed version control systems (e.g. “git”) or scripted programming languages for data cleaning and analysis may have a steep learning curve, their adoption can increase individual efficiency and facilitate collaborations both within entomology and across disciplines. The open science movement is developing within the discipline of entomology, but practitioners of these concepts or those desiring to work more collaboratively across disciplines may be unsure where or how to embrace these initiatives. This article is meant to introduce some of the tools entomologists can incorporate into their workflows to increase the replicability and openness of their work. We describe these tools and others, recommend additional resources for learning more about these tools, and discuss the benefits to both individuals and the scientific community and potential drawbacks associated with implementing a replicable workflow.

Heat-stressed lactating dairy cattle exhibit unique metabolic symptoms; many of which are undoubtedly involved in heat-induced subfertility. Because of its known systemic effects, we hypothesized that γ-aminobutyric acid (GABA) participates in the regulation of insulin and progesterone during heat stress. Multiparous lactating Holstein cows (n=6) were studied during four experimental periods: 1) thermoneutral (TN; d 1-5), 2) TN + hyperinsulinemic-hypoglycemic clamp (d 6-10), 3) heat stress (HS; d 16-20), and 4) HS + euglycemic clamp (d 21-25). Blood samples were collected once daily via coccygeal venipuncture into heparinized evacuated tubes. Analysis of GABA concentrations from all four treatment periods yielded no differences. In direct comparison to TN concentrations, plasma GABA tended to be decreased during HS (16.57±2.64 vs 13.87±2.28 ng/ml, respectively, P = 0.06). Both milk production and plasma insulin were moderately correlated with plasma GABA (r=0.35, P<0.01; r = -0.32, P<0.01). Plasma progesterone was correlated with plasma GABA concentrations during TN but not HS. These results are the first to indicate that peripheral GABA could be involved in regulating aspects of production and reproduction during heat stress. More research is needed to determine its precise role(s).

Evidence-based canine decontamination protocols are underrepresented in the veterinary literature. Aerosolized microbiological and chemical contaminants can pose a risk in deployment environments highlighting the need for improved canine field decontamination strategies. Prior work has established the efficacy of traditional, water-intensive methods on contaminant removal from the coat of the working canine; however, it is not known if similar reductions can be achieved with simple field expedient methods when resources are limited. The objective of this study was to measure the reduction of aerosolized contamination via a practical “wipe-down” procedure performed on working canine coats contaminated with a fluorescent, non-toxic, water-based aerosol. Disposable, lint-free towels were saturated with one of three treatments: water, 2% chlorhexidine gluconate scrub (CHX), or 7.5% povidone-iodine scrub (PVD). Both CHX and PVD were diluted at a 1:4 ratio. Treatments were randomly assigned to one of three quadrants established across the shoulders and back of commonly utilized working dog breeds (Labrador retrievers, n = 16; German shepherds, n = 16). The fourth quadrant remained unwiped, serving as a control. Reduction in fluorescent marker contamination was measured and compared across all quadrants. PVD demonstrated greater marker reduction compared to CHX or water in both breeds (P < 0.0001). Reduction was similar between CHX or water in Labradors (P = 0.86) and shepherds (P = 0.06). Effective wipe-down strategies using common veterinary cleansers should be further investigated and incorporated into decontamination practices to safeguard working canine health and prevent cross-contamination of human personnel working with these animals.

The horizontal storm structure surrounding lightning ignited wildfires is examined using Vaisala’s National Lightning Detection Network (NLDN), NCEP’s Stage IV gauge corrected radar precipitation mosaic, and the US Forest Service’s Fire Occurrence Database. Though lightning flash density peaks strongly around fire ignitions on the instantaneous 1 km scale, on the hourly 10 km scale both the lightning and precipitation peaks are typically offset from fire ignitions. Lightning density is higher and precipitation lower around ignition points compared to non-ignition points. Both regression and horizontal distributions are consistent with the claim that positive flashes have a stronger association with ignition than negative flashes, but the statistical significance remains ambiguous

1) Background: The influence of estrogen on cognitive and perceptual functions is debated. Some research suggests that estrogen increases arousal, improving cognitive function, while others propose that increased arousal might reduce performance on certain tasks. This study investigates the effects of menstrual cycle phase and estrogen levels on lightness perception in cycling women and hormonal contraceptive (HC) users. (2) Methods: Estrogen levels were determined from saliva samples collected at three sessions aligned with different menstrual phases in 16 women (9 with natural cycles, 7 HC users). The effects of wavelength and menstrual cycle phase on lightness perception were analyzed, followed by post-hoc comparisons and correlations between lightness perception and estrogen levels for both cycling women and HC users. (3) Results: Lightness varied by menstrual phase (MCP) in cycling women and was slightly higher during the low estrogen menstrual phase compared to peri-ovulation or luteal phases. In HC users, lightness measures were equivalent across phases. For cycling women, lightness was negatively correlated with estrogen for the green and green-yellow stimuli. There were no such associations among HC users. (4) Conclusions: This report challenges the concept that high estrogen phases of the menstrual cycle always positively influence perception. Conversely, the present results revealed that—at least in cycling, non-hormonal contraceptive users—lightness perception was both at a maximum during the low estrogen menstrual phase and negatively associated with estrogen levels across all tested wavelengths.

There is high confidence that climate change has increased the probability of concurrent temperature-precipitation extremes, changed their spatial-temporal variations, and affected the relationships between drivers of such natural hazards. However, the extent of such changes has been less investigated in Australia. Daily weather data (131 years, 1889-2019) at 700 grid cells (1◦ × 1◦) across Australia was obtained to calculate annual and seasonal mean daily maximum temperature (MMT) and total precipitation (TPR). A nonparametric multivariate copula framework was adopted to estimate the return period of compound hot-dry (CHD) events based on an ‘And’ hazard scenario (hotter than a threshold ‘And’ drier than a threshold). CHD extremes were defined as years with joint return periods of larger than 25 years. Mann-Kendall nonparametric tests was used to analyse trends in MMT and TPR as well as in the frequency of univariate and CHD extremes. A general cooling-wetting trend was observed over 1889-1989. Significant increasing trends were detected over 1990-2019 in the frequency and severity of hot extremes across the country while trends in dry extremes were mostly insignificant (and decreasing). Results showed a significant increase in the association between temperature and precipitation at various temporal scales. The frequency of CHD extremes was mostly stable over 1889-1989, but significantly increased between 1990 and 2019 at 44% of studied grid cells, mostly located in the north, south-east and south-west. Spatial homogeneity (i.e. connectedness) and propagation of extreme events from one grid cell to its neighbouring cells was investigated across Australia. It can be concluded that this connectedness has not significantly changed since 1889.

To account for the very low mass density associated with Dark Energy and the Cosmological Constant, a new approach to the ground state of empty space is presented. The resulting model for the vacuum state associated with empty space proposes a crystalline-like texture for the chromatic structure of empty space. This vacuum state has the appropriate mass density and predicts acceleration for the Universe expansion. Furthermore, the model predicts that this texture is anisotropic and may lead to measurable changes in the production of electron and positron pairs by gamma rays incident on a solid crystal of low mass density such as graphite.

The market for shark fin soup, a fashionable, high-end Chinese dish, has resulted in intensive shark fishing across all oceans. At the same time, 90% of teleost fish stocks are over-exploited, making sharks the most lucrative target: fisheries that have not previously hunted them are now. As top and middle predators, sharks have high ecological value and poor capacity to withstand fishing mortality, but though their numbers are plummeting, the secretive nature of the fin trade, along with the difficulties of obtaining relevant data, obscure their true status. In consumer countries, shark fin is a luxury item and rich consumers are willing to pay high prices. There is little interest in sustainability or legal trade. Thus market demand will continue to fuel the search for sharks and those accessible to fishing fleets are increasingly endangered. Current legal protections are not working, as is clearly seen in the case of the shortfin mako. Claims that sharks can withstand such targeted, industrial hunting and be sustainably fished under these circumstances are shown to be misguided. In the interests of averting a catastrophic collapse across the planet’s aquatic ecosystems, sharks must be given effective protection. We recommend that all sharks, chimaeras, manta rays, devil rays, and rhino rays be protected from international trade through an immediate CITES Appendix I listing. However, a binding international agreement for protection, not only of sharks, but of the loss of biodiversity in general, is what is most needed to allow marine and fresh water ecosystems to recover.

The African continent has the highest prevalence of hypertension globally, with South Africa reporting the highest prevalence in Southern Africa. While the influence of genetic variability in the pathogenesis of hypertension is well described internationally, limited reports are available for African populations. This study aimed to assess the association of genetic variants and essential hypertension in a cohort of two ethnic South African population groups. Two hundred and seventy-seven hypertensive and one hundred and seventy-six normotensive individuals were genotyped for 79 variants. Genotyping was performed using the Illumina GoldenGate Assay and allele-specific polymerase chain reaction. The association of variants was assessed using the Fisher Exact test under the additive and allelic genetic models, while multivariate logistic regression was used to predict the development of hypertension. Five variants (CYP11B2 rs179998, AGT rs5051 and rs699, AGTR1 rs5186 and ACE rs4646994) were significantly associated with essential hypertension in the cohort under study. Furthermore, AGTR1 rs5186 and AGT rs699 were identified as risk factors for the development of hypertension in both ethnic groups. In two ethnic South African populations an association was observed between Renin-Angiotensin-Aldosterone System (RAAS) related genes and the development of hypertension.

Phylogenies depict shared evolutionary patterns and structures on a tree topology, enabling the identification of hierarchical and historical relationships. Recent analyses indicate that phylogenetic signals extend beyond the primary structure of protein or DNA, and various aspects of codon usage biases are phylogenetically conserved. Several functional biases exist within genes, including the number of codons that are used, the position of the codons, and the overall nucleotide composition of the genome. Codon usage biases can significantly affect transcription and translational efficiencies, leading to differential gene expression. Although systematic codon usage biases originate from the overall GC content of a species, ramp sequences, codon aversion, codon pairing, and tRNA competition also significantly affect gene expression and are phylogenetically conserved. We review recent advances in analyzing codon usage biases and their implications in phylogenomics. We first outline common phylogenomic techniques. Next, we identify several codon usage biases and their effects on secondary structure, gene expression, and implications in phylogenetics. Finally, we suggest how codon usage biases can be included in phylogenomics. By incorporating various codon usage biases in common phylogenomic algorithms, we propose that we can significantly improve tree inference. Since codon usage biases have significant biological implications, they should be considered in conjunction with other phylogenetic algorithms.

Saturated lights appear brighter than white lights of the same luminance. This phenomenon is known as the Helmholtz-Kohlrausch (H-K) effect and can be estimated by modeling achromatic luminance and saturation to total brightness. These models have been shown to differ between women and men and are more variable in women. The variation in brightness models among women may be due to hormonal changes across the menstrual cycle. To test this, total brightness and achromatic luminance were measured across blue, green, yellow-green, yellow, and red hues. These data were measured along with salivary hormone levels for nine cycling women at points representing the menstrual, peri-ovulation, and luteal phases. These data were also collected for seven oral contraceptive (OC) users. There were no main effects of OC use nor menstrual cycle phase on B/L ratios, but ratios were higher for the red stimulus in cycling women than OC users. Red B/L ratios were also higher for cycling women than OC users during the luteal phase. Estrogen, progesterone, and their interaction predicted 18% of the variation in brightness for cycling women. These models could not be fit for OC users, and estrogen only accounted for 5% of brightness variance with progesterone terms omitted. These findings and potential mechanisms are discussed in the context of previous results.

Introduction: The current generation of 3D printers are lighter, cheaper, and smaller, making them more accessible to the chairside digital dentist than ever before. 3D printers in general in the industrial and chairside setting can work with various types of materials including, metals, ceramics, and polymers. Evidence presented in many studies show that an ideal material used for dental restorations is characterised by several properties related to durability, cost-effectiveness, and high performance. This review is the second part in a 3D Printing series that looks at the literature on material science and applications for these materials in 3D printing as well as a discussion on the potential further development and future evolution in 3D printing materials. Conclusions: Current materials in 3D printing provide a wide range of possibilities for providing more predictable workflows as well as improving efficiency through less wasteful additive manufacturing in CAD/CAM procedures. Incorporating a 3D printer and a digital workflow into a dental practice is challenging but the wide range of manufacturing options and materials available mean that the dentist should be well prepared to treat patients with a more predictable and cost effective treatment pathway. As 3D printing continues to become a commonplace addition to chair side dental clinics, the evolution of these materials, in particular reinforced PMMA, resin incorporating zirconia and glass reinforced polymers offer increased speed and improved aesthetics that will likely replace subtractive manufacturing milling machines for most procedures.

In the pursuit of better treatments, the concept of a chemically-active material, responding to local conditions by causing reactions, or reacting to produce substances that are deemed beneficial, seems laudable. Ultimately, the goal appears to be to recruit natural biological processes such that a natural ‘repair’ is effected. This goal seems to be the reason for prefixing “bio-“ to many terms with a view to advertising the desire, yet without presenting evidence that it has occurred, or indeed that it is capable of occurring, relying instead on non-biological processes to justify the claims. The dogma is such that all work where local ‘responsive’ chemistry is involved must receive the label “bioactive” to legitimize and promote. Nevertheless, the primary evidence adduced is flawed, and the claim must fail. A rethink to restore scientific sense and confidence in the endeavour is essential if real progress is to be made.

Glioblastoma multiforme (GBM) is a glioma and the most aggressive type of brain tumor with a dismal average survival time, despite the standard of care. One promising alternative therapy is boron neutron capture therapy (BNCT), which is a noninvasive therapy for treating locally invasive malignant tumors, including glioma. BNCT involves boron-10-released radiation directly into tumor cells with minimal damage to healthy tissues. This therapy lacks clinically approved targeted blood-brain-barrier-permeating delivery vehicles for therapeutic drug/ boron-10. Nanoparticles, particularly gold nanoparticles (GNPs), are selective and effective drug-delivery vehicles because of their desirable properties, facile synthesis, and biocompatibility. This review discusses historical and current GNP therapeutic applications as a drug delivery vehicle for treating glioma. Furthermore, GNPs loaded with therapeutic drugs, imaging agents, and GBM-targeting antibodies/ peptides to treat GBM will be discussed. Additionally, the importance of upper and lower limits on therapeutic efficacy will be described and explored followed by highlighting their advantages, limitations, and possible toxicity. Recent research and selected important findings for GNP-mediated pharmaceutics in GBM will also be considered.

Western Iran barb species are scientifically, environmentally, and economically important. Some of them are the largest riverine freshwater species, which will grow in size and weight to 170 cm, and 120 kg respectively. Although these species are vulnerable, there is little information on taxonomy or environmental status of the species Luciobarbus barbulus is one of the important large species. In order to find the new record on the present status of large barb species sampling program carried out in western Iran, during the resent year since 2013 to now. This species overlaps in distinction with L. mystaceus, L scheich, and other similar species. In this study re-description of L.barbulus is given. This species differs from L. mystaceus in having thick and very wide fleshy lip, inferior mouth and slightly shorter head. In Luciobarbus barbulus head is more inferior. The details of differences between these species are given. This species is one of stable growing fish without dimorphism, retain its shape from a fingerling species to a giant fish.

We construct a Bayesian estimator for the dilution of a wastewater sample. When wastewater is diluted by rainwater an estimate of the level of dilution is required if we are to normalise sample measurements of disease markers such as SARS-CoV-2 RNA. We consider the situation where flow measurements are available, but will regularly be unreliable because of the action of combined sewer outflows (CSOs) and wastewater storage tanks, which divert wastewater away from treatment plants when the flow is excessive. However, we also have proxies for the flow from various chemical markers (e.g.\ phosphate, ammonium, electrical conductivity), whose level per unit of population is fixed. The new flow estimator has multiple advantages compared to existing procedures: credible intervals for the estimates; optimal weighting of the chemical markers; systematic handling of missing and censored values; and model based smoothing without lags.

Colon cancer (CRC) is a prevalent malignancy that exhibits distinct differences in incidence, prognosis, and treatment responses between males and females. These disparities have long been attributed to hormonal differences, particularly the influence of estrogen signaling. This review aims to provide a comprehensive analysis of recent advances in our understanding of the molecular mechanisms underlying sex differences in colon cancer and the protective role of membrane and nuclear estrogen signaling in CRC development, progression, and therapeutic interventions. We discuss the epidemiological and molecular evidence supporting sex differences in colon cancer, followed by an exploration of the impact of estrogen in CRC through various genomic and non-genomic signaling pathways involving membrane and nuclear estrogen receptors. Furthermore, we examine the interplay between estrogen receptors and other signaling pathways, in particular the Wnt/-catenin proliferative pathway and hypoxia in shaping biological sex differences and estrogen protective actions in colon cancer. Lastly, we highlight the potential therapeutic implications of targeting estrogen signaling in the management of colon cancer and propose future research directions to address the current gaps in our understanding of this complex phenomenon.

Western Iran barb species are scientifically, environmentally, and economically important. Some of them are the largest riverine freshwater species, which will grow in size and weight to 170 cm, and 120 kg respectively. There is little information on taxonomy or environmental status of these species Luciobarbus barbulus is one of the important large species. During the resent year since 2013, in order to find the new record of large barb species, sampling program carried out in western Iran,. Luciobarbus barbulus briefly described by Heckel (1849) but during the time, have been synonymized with other related species or vice versa, other similar species miss-identically have been known as this species. Also the synonymy of Luciobarbus barbulus with L. pectoralis remains uncertain. The possible syntypes of L. barbulus in Vienna Museum (NMW 53957 and NMW 6596) are in too poor condition to be of any value, being mostly bones, and are dried, and. The fleshy lip of NMW 6596, (measures 119.3 mm standard length) fold of the original description could not be discerned, teeth are missing and the dorsal fin is broken off short. In 1997 this was the only syntype recognized. The catalog in Vienna lists only 1 fish, while Heckel's description refers to several fishes!. So designing of Lecotype and re-description of L. barbulus is essential. In this paper the details of description and differences between these species are given.

We evaluated the potential of using fish species and functional traits as indicators of land use impacts to fish assemblages. We used environmental data collected at multiple spatial scales (local, reach, and upstream catchment) for 19 tributary and main stem sites in the Nolichucky River watershed in Tennessee. Canonical correspondence analyses showed that temperature, elevation, specific conductivity, sediment yield, impervious surfaces, and row crop cover at the catchment scale were strongly associated with fish assemblage structure, as well as forest cover from all three spatial scales. Blocked indicator species analysis, with stream size as the block, showed that significantly strong indicators of the least-impacted riparian land use condition (≥60% forest cover) were Saffron Shiner (Notropis rubricroceus), Rainbow Trout (Oncorhyncus mykiss), Longnose Dace (Rhynichthys cataractae), Creek Chub (Semotilus atromaculatus), and Mottled Sculpin (Cottus bairdi). Traits indicative of the least-impacted sites were the herbivorous trophic guild, mean female age-at-maturity, longevity, rock-gravel spawners, montane geology and pelagic swimmers. Specific conductivity was strongly related to multiple catchment-scale land use variables, and was a strong local-scale influence on fish assemblage structure. Our results show promise for using a relatively common but endemic southern Appalachian fish species, the Saffron Shiner, as an indicator for land-use related impacts to these streams.

Maxillomandibular advancement (MMA) is a surgical intervention that reduces the symptoms of obstructive sleep apnea via anterior repositioning of the upper and lower jaws. Pre-operative orthodontic alignment is often a critical component in aiding MMA. Orthodontia are important in intraoperative anchorage for intermaxillary fixation, healthy post-operative occlusion, and post-operative skeletal stability. Sequential clear aligners (SCA) refer to removable orthodontic appliances that are replaced at regular intervals to stimulate dental migration without the use of bonded hardware. These aligners have demonstrated efficacy in aiding orthognathic surgery for dentofacial deformities, which share some technical similarities with MMA for OSA. Here, we explore the treatment protocol for MMA followed by post-operative SCA treatment. Our experiences show that post-operative orthodontic treatment with SCAs results in similarly successful post-operative surgical outcomes given that the patient’s pre-operative occlusion is stable.

The main goal of this paper is to present results of preliminary archaeological research on the south side of Lake Issyk-Kul in Kyrgyzstan. We test the hypothesis that agropastoral land use changed over four millennia from the Bronze Age through the ethnographic Kirghiz period due to economic, socio-political, and religious changes in the prehistoric and historic societies of this region. Our research objectives are to: (1) describe and analyze survey results from Lower Kizil Suu Valley; (2) discuss the results of radiometric and archaeobotanical samples taken from three stratigraphic profiles from three settlements from the Juuku Valley, including these chronological periods: the Wusun period (200 to 400 CE), the Qarakhanid period (1100 to 1200 CE), and the ethnographic Kirghiz period (1700 to 1900 CE); and (3) conduct preliminary GIS spatial analyses on the Iron Age mortuary remains (Saka and Wusun period). This research emerges out of the first archaeological surveys conducted in 2019 - 2021 and includes the Lower Kizil Suu alluvial fan; it is an initial step toward developing a model for agropastoral land use for upland valleys of the Inner Tian Shan Mountains.

Multi-task Gaussian processes (MTGPs) are a powerful approach for modeling structured dependencies among multiple tasks. Researchers on MTGPs have contributed to enhance this approach in various ways. Current MTGP methods, however, cannot model nonlinear task correlations in a general way. In this paper we address this problem. We focus on spectral mixture (SM) based kernels and propose an enhancement of this type of kernels, called multi-task generalized convolution spectral mixture (MT-GCSM) kernel. The MT-GCSM kernel can model nonlinear task correlations and mixtures dependency, including time and phase delay, not only between different tasks but also within a task at the spectral mixture level. Each task in MT-GCSM has its own generalized convolution spectral mixture kernel (GCSM) with a different number of convolution structures and all spectral mixtures from different tasks are dependent. Furthermore, the proposed kernel uses inner and outer full cross convolution between base spectral mixtures, so that the base spectral mixtures in the tasks are not necessarily aligned. Extensive experiments on synthetic and real-life datasets illustrate the difference between MT-GCSM and other kernels as well as the practical effectiveness of MT-GCSM.

Conservation of natural habitats in human-dominated landscapes is critical for halting biodiversity loss. Maintaining habitat quantity and connectivity requires landscape-level collective action, which results from environmental decisions made by individual land owners. We investigate how individual decision making in a rural collective translates into quantitative differences in landscape-level environmental outcomes. Behavioral science has become a critical domain of knowledge in conservation, but little attention has been paid to how multiple behavioral drivers determine the success of collective environmental action. We developed a social-ecological model for landscape-level conservation using a detailed data set of 600 land owners in New Zealand. With the model, we tested whether the effect of social influence networks on collective conservation action was altered by their interplay with land owners’ personal characteristics, connections to cross-scale actors and local environmental contexts. Interactions between multiple behavioral drivers determined the environmental outcomes of collective action in unexpected ways by modifying, muting or amplifying the effects of single drivers. Importantly, we detected a social-ecological mechanism for rapid change in the extent of protected habitats, which can explain highly successful or failed environmental outcomes of collective conservation. Further, when environmentally desirable and undesirable behaviors spread simultaneously through the social network, homophily and network cohesion hinder desirable environmental outcomes. This effect can be modified by other drivers such as social responses to local environmental change. Thus, understanding how the antagonistic and synergistic effects of behavioral drivers can be best utilized in conservation will benefit biodiversity and ensure benefits that humans obtain from biodiversity.

Duchenne muscular dystrophy (DMD) is a progressive neuromuscular disease caused by mutations to the dystrophin gene - resulting in deficiency of dystrophin protein, loss of myofiber integrity in skeletal and cardiac muscle, and eventual cell death and replacement with fibrotic tissue. Pathologic cardiac manifestations occur in nearly every DMD patient, with development of cardiomyopathy - the leading cause of death - inevitable by adulthood. As early cardiac abnormalities are difficult to detect, timely diagnosis and appropriate treatment modalities remain a challenge. There is no cure for DMD – treatment is aimed at delaying disorder progression and alleviating symptoms. A comprehensive understanding of the pathophysiological mechanisms is crucial to development of targeted treatments. While established hypotheses of underlying mechanisms include sarcolemmal weakening, upregulation of pro-inflammatory cytokines, and perturbed ion homeostasis, mitochondrial stress has recently come into focus as a potential key contributor. Several experimental compounds targeting the skeletal muscle pathology of DMD are in development, but effects of such agents on cardiac function remain unclear. Synergistic integration of small molecule- and gene-target-based drugs with metabolic, immune, or ion balance-enhancing compounds into a combinatorial therapy offers potential for treating dystrophin deficiency-induced cardiomyopathy, making it crucial to understand the underlying mechanisms driving the disorder.

Microfluidic devices which integrate both rapid mixing and liquid jetting for sample delivery are an emerging solution for studying molecular dynamics via X-ray diffraction. Here we use finite element modelling to investigate the efficiency and time-resolution achievable using microfluidic mixers within the parameter range required for producing stable liquid jets. Three-dimensional simulations, validated by experimental data, are used to determine the velocity and concentration distribution within these devices. The results show that by adopting a serpentine geometry, it is possible to induce chaotic mixing, which effectively reduces the time required to achieve a homogeneous mixture for sample delivery. Further, we investigate the effect of flow rate and the mixer microchannel size on the mixing efficiency and minimum time required for complete mixing of the two solutions whilst maintaining a stable jet. In general, we find that the smaller the cross-sectional area of the mixer microchannel, the shorter the time needed to achieve homogeneous mixing for a given flow rate. The results of these simulations will form the basis for optimised designs enabling the study of molecular dynamics occurring on millisecond timescales using integrated mix-and-inject microfluidic devices.

With the increasing use of genome sequencing as a surveillance tool for molecular epidemiology of antimicrobial resistance (AMR), databases and clear nomenclature for AMR gene families are critical. Due to the convoluted nomenclatural history of the integron-associated trimethoprim-resistant dihydrofolatereductase (dfr) gene family, we decided to conduct a literature review, comparative sequence analysis, and phylogenetic investigation of the dfr family, the results of which are presented here and available at the Comprehensive Antibiotic Resistance Database (CARD). Overall, literature review and phylogenetic analysis resolved gene name synonyms based on sequence. We recommend adoption of phylogenetic methods to help guide AMR gene naming efforts and relegation of misleading names to synonyms.

Electric energy is one of the driving forces in every country. The supply of electrical energy continues to present various challenges, such as high costs associated with procuring raw materials for generation, sparsely populated areas that are not connected to the main grid, and the need for infrastructure to support generation and network delivery. These challenges have contributed to the growing adoption of renewable energy sources, particularly solar photovoltaics (PV).In this study, we have developed a practical method to assess the spatial PV potential in a selected urban area. The methodology combines data collected from an unmanned aerial vehicle (UAV) photogrammetry, Geographic Information System (GIS), and the energy output from three remote photovoltaic systems installed at different locations. The results obtained from this approach not only provide the energy generated per square meter, per year (kWh m-2 yr-1), but also provides a base to calculate the potential distance that electric cars could travel based on the energy generated. To illustrate the application of this method, two practical cases were selected: Senglea, Malta, and Munxar, Gozo. These examples highlight the versatility and effectiveness of our approach for evaluating and harnessing solar energy through photovoltaic panels in different contexts.

This paper uses preliminary studies of archaeological sites (burial mounds and settlements) from the Iron Age through Medieval periods (ca. 800 BCE to 1200 CE) in the Juuku Valley on the South side of Lake Issyk-Kul to model land-use across vertical mountain zones. To do so, we have established a radiometric chronology, conducted test excavations of an Iron Age settlement and a Turkic period burial, undertaken preliminary archaeobotanical research, and pedestrian surveys. Seed remains of wheat (Triticum aestivum), barley (Hordeum vulgare), broomcorn millet (Panicum milaceum) and foxtail millet (Setaria italica) and legumes were recovered in very small quantities from an Iron Age upland settlement at 2100 m asl and a Turkic period burial mound at 1934 m asl. These preliminary archaeobotanical results are compared to the Talgar Iron Age settlements on the north side of the Tian Shan Mountain range in Kazakhstan studied earlier by Robert Spengler. Small samples of faunal remains found at the Turkic period kurgan and from a profile at the upland Iron Age settlement indicate livestock herding of sheep/goats, cattle, and horses in Juuku Valley. The goal of this paper is to test the hypothesis that pastoral transhumance and agropastoralism were economic strategies used by ancient societies during the Iron Age through Medieval periods in mountain-river valley areas between 750 m to 2500 m asl. These economic strategies that combined the pasturing of sheep, goats, cattle and horses with the cultivation of cereals were adapted to the use of different vegetational zones along a vertical gradient. This paper based on preliminary research of upland sites of the Juuku Valley in Kyrgyzstan, initiates a long-term research study of four millennia of settlements that ranged from pastoral transhumance, pastoral nomadism, and combined mountain agriculture using survey data and test excavations.

We provide quantitative results from GIS-based modelling of urban emission functions for a range of representative low- and mid-rise locations, ranging from individual streets to residential communities within cities as well as entire towns and city regions with the aim of whether lantern photometry or built environment has the dominant effect on light pollution. We demonstrate the scalability of our work by providing results for the largest urban area modelled to date, comprising the central 117 km2 area of Dublin City and containing nearly 42,000 public lights. Our results show a general similarity in the shape of the azimuthally-averaged emission function for all areas examined, with differences in total light output distribution depending primarily on the nature of the lighting and, to a smaller extent, on the obscuring environment including seasonal foliage effects. A comparison with global satellite observations shows that they are consistent with the deduced angular emission function for other low-rise areas worldwide. We further validate our approach by comparing results for a range of urban locations by the close agreement observed in a detailed comparison of with calibrated imagery from the International Space Station. To our knowledge, this is the first such detailed quantitative verification of light loss calculations.

Motivation is essential in education, with highly motivated learners engaging more deeply with content and more ably transferring knowledge to new contexts. However, the validity of scales to measure motivation has been underexplored in pre-clerkship medical education. This study evaluates the validity of the Situational Motivation Scale (SIMS) for measuring motivation among pre-clerkship medical students in post-situational and short-term contexts. Using a sample of n = 156 students from the Frank H. Netter MD School of Medicine at Quinnipiac University, SIMS was tested for construct validity with attention paid to content, response process, internal structure, relationships to other variables, and consequences of use evidence. Small modifications from present to past tense in English were made for clarity following focus group feedback, and content validity was ensured via expert consultation. SIMS demonstrated strong internal consistency with a satisfactory Cronbach’s alpha for all subscales and anticipated patterns of correlations. Factor analysis confirmed appropriate factor loadings, with a stronger model fit for the short-term context, and no observed adverse effects on student engagement. These findings support the robustness of SIMS in capturing intrinsic, extrinsic, and amotivation in pre-clerkship medical students, highlighting its applicability for short-term and situational motivational assessment.

This paper explores the tuning and results of two-part models on rich datasets provided through the Casualty Actuarial Society (CAS). These data sets include BI (bodily injury), PD (property damage) and COLL (collision) coverage, each documenting policy characteristics and claims across a four year period. The datasets are explored, including summaries of all variables, then the methods for modeling are set forth. Models are tuned and the tuning results are displayed, after which we train the final models and seek to explain select predictions. All of the code will be made available on GitHub. Data was provided by a private insurance carrier to the CAS after anonymizing the data set. This data is available to actuarial researchers for well-defined research projects that have universal benefit to the insurance industry and the public. Our hope is that the methods demonstrated here can be a good foundation for future ratemaking models to be developed and tested more efficiently.

Buprenorphine, an analogue of thebaine, is a Schedule III opioid in the United States used for opioid-use disorder and as an analgesic. Research has shown drugs like buprenorphine have a complicated pharmacology with characteristics that challenge traditional definitions of terms like agonist, antagonist, and efficacy. Buprenorphine has a high affinity for the mu (MOR), delta (DOR), kappa (KOR), and intermediate for the nociceptin opioid receptors (NOR). Buprenorphine is generally described as a partial MOR agonist with limited activity and decreased response at the mu-receptor relative to full agonists. In opioid naïve patients, the drug’s analgesic efficacy is equivalent to a full MOR agonist, despite decreased receptor occupancy and the “ceiling effect” produced from larger doses. Some argue buprenorphine’s effects depend on the endpoint measured, as it functions as a partial agonist for respiratory depression, but a full-agonist for pain. Buprenorphine’s active metabolite, norbuprenorphine, attenuates buprenorphine's analgesic effects due to NOR binding and respiratory depressant effects. The method of administration impacts efficacy and tolerance when administered for analgesia. There have been eleven-thousand reports involving buprenorphine and minors (age < 19) to US poison control centers, the preponderance (89.2%) with children. The consequences of prenatal buprenorphine exposure in experimental animals and humans should continue to be carefully evaluated. In conclusion, buprenorphine’s characterization as only a partial mu-agonist is an oversimplification. Contemporary research shows the traditional explanation of the pharmacology of buprenorphine does not take into account changes to receptor theory, pharmacological terminology, route of administration, and biologically active major metabolites.

Body temperature responses were recorded during phases of work (waiting to work in close proximity to search site, active work in a search site, and post-work recovery crated in vehicle) in human remains detection dogs during search training. State or federally certified human remains detection dogs (n = 8) completed eight iterations of searching, rotating through six different types of search environments to detect numerous scent sources including partial and complete, buried, hidden, or fully visible human remains. Internal temperature (Tgi) of the body was measured continuously using an ingestible thermistor in the gastrointestinal tract. Mean total phase times were: waiting to work: 9.17 minutes (± 2.27); active work: 8:58 minutes (± 2:49); and post work recovery: 24:04 minutes (± 10.59). Tgi was impacted by phase of work (P < 0.001) with a small increase during active work, with mean peak temperature 39.4 °C (± 0.34 ºC) during that period. Tgi continued to increase for a mean of 7:37 (± 6:04) minutes into the post-work recovery phase in the handler’s vehicle with a mean peak Tgi of 39.66 °C (± 0.41 ºC). No significant increase in temperature was measured during the waiting to work phase, suggesting anticipation of work did not appear to contribute to overall body temperature increase during the waiting to work recovery cycle. Continued increase of gastrointestinal body temperature several minutes after cessation of exercise indicates that risk of heat injury does not immediately stop when the dog stops exercising, although none of the dogs in this study reached clinically concerning body temperatures or displayed any behavioral signs suggestive of pending heat injury. More work is needed to better understand the impact of vehicle crating on post-work recovery temperatures in dogs.

Fatty acids play a major role in determining membrane biophysical properties. Staphylococcus aureus produces branched-chain fatty acids (BCFAs) and straight-chain fatty acids (SCFAs), and can incorporate exogenous SCFAs and straight-chain unsaturated fatty acids (SCUFAs). Many S. aureus strains produce the triterpenoid pigment staphyloxanthin, and the balance of BCFAs, SCFAs and staphyloxanthin determines membrane fluidity. Here, we investigated the relationship of fatty acid and carotenoid production in S. aureus using a pigmented strain (Pig1), its carotenoid-deficient mutant (Pig1ΔcrtM) and the naturally non-pigmented Staphylococcus argenteus that lacks carotenoid biosynthesis genes and is closely related to S. aureus. Fatty acid compositions in all strains were similar under a given condition indicating that staphyloxanthin does not influence fatty acid composition. Strain Pig1 had decreased membrane fluidity as measured by fluorescence anisotropy than the other strains under all conditions indicating that staphyloxanthin helps maintain membrane rigidity. We could find no evidence for correlation of expression of crtM and fatty acid biosynthesis genes. Supplementation of medium with glucose increased SCFA production and decreased BCFA and staphyloxanthin production, whereas acetate-supplementation also decreased BCFAs but increased staphyloxanthin production. We believe that staphyloxanthin levels are influenced more through metabolic regulation than responding to fatty acids incorporated into the membrane.

The lack of reliable rainfall projection records remains a major challenge to Uganda. In the advent of extreme wetness or drought events, reliable rainfall estimates for local planning and adaptation are essential. The present study used two main datasets to conduct a historical analysis from 1981 to 2019, coupled with future projections under representative concentration pathway (RCP 8.5) for the period 2020-2050. Historical analysis revealed bimodal annual rainfall pattern for March-May (MAM) and September-November (SON) gradients representing heavier to lighter rainfall events respectively over the study area. Investigation of recent trends in rainfall patterns revealed an upward trend from 2010 onwards in annual and seasonal rainfall. Moreover, results for future projections show wet conditions are projected to occur over the study area between the months of April/May and October. Contrarily, March is likely to experience a reduction in wet conditions. Mann-Kendall test employed to make future projections of rainfall depicted decreasing patterns during MAM season whilst increasing tendencies with strong shift was highlighted for SON season over the study region. Meanwhile, annual projections indicate huge variations with linear trends showing a marginal increase as compared to historical trends. Findings would serve as baseline print to propel further studies that could delve into impact analysis of drought extreme events which pose significant threats to the agricultural sector which is heavily reliant on rainfall.

Mycobacterium tuberculosis (Mtb) is the etiological agent of tuberculosis (TB), a disease that alt-hough preventable and curable, remains a global epidemic due to the emergence of resistance and a latent form responsible for a long period of treatment. Drug discovery in TB is a challenging task due to the heterogeneity of the disease, the emergence of resistance and an uncomplete knowledge of the pathophysiology of the disease. The limited permeability of the cell wall and the presence of multiple efflux pumps remain a major barrier to achieve effective intracellular drug accumulation. While the complete genome sequence of Mtb has been determined and several potential protein targets have been validated, the lack of adequate models for in vitro and in vivo studies is a limit-ing factor in TB drug discovery programs. In current therapeutic regimens, less than 0.5% of bac-terial proteins are targeted being the biosynthesis of the cell wall and the energetic metabolism two of the most important processes exploited for TB chemotherapeutics. This review provides an overview on the current challenges in TB drug discovery and emerging Mtb druggable proteins, and how chemical probes for protein profiling enabled the identification of new targets and bi-omarkers, paving the way to disruptive therapeutic regimens and diagnostic tools.

Noise in requirements has been known to be a defect in software requirements specifications (SRS). Detecting defects at an early stage is crucial in the process of software development. Noise can be in the form of irrelevant requirements that are included within a SRS. A previous study had attempted to detect noise in SRS, in which noise was considered as an outlier. However, the resulting method only demonstrated a moderate reliability due to the overshadowing of unique actor words by unique action words in the topic-word distribution. In this study, we propose a framework to identify irrelevant requirements based on the MultiPhiLDA method. The proposed framework distinguishes the topic-word distribution of actor words and action words as two separate topic-word distributions with two multinomial probability functions. Weights are used to maintain a proportional contribution of actor and action words. We also explore the use of two outlier detection methods, namely Percentile-based Outlier Detection (PBOD) and Angle-based Outlier Detection (ABOD), to distinguish irrelevant requirements from relevant requirements. The experimental results show that the proposed framework was able to exhibit better performance than previous methods. Furthermore, the use of the combination of ABOD as the outlier detection method and topic coherence as the estimation approach to determine the optimal number of topics and iterations in the proposed framework outperformed the other combinations and obtained sensitivity, specificity, F1-score, and G-mean values of 0.59, 0.65, 0.62, and 0.62, respectively.

Gas sensor arrays, also known as electronic noses, leverage a diverse set of materials to identify the components of complex gas mixtures. Metal-organic frameworks (MOFs) have emerged as promising materials for electronic noses due to their high-surface areas and chemical as well as structural tunability. Using our recently reported genetic algorithm design approach, we examined a set of 50 MOFs and searched through the over 1.125x1015 unique array combinations to identify optimal arrays for the detection of CO₂ in air. We found that despite individual MOFs having lower selectivity for O2 or N2 relative to CO₂, intelligently selecting the right combinations of MOFs enabled accurate prediction of the concentrations of all components in the mixture (i.e. CO₂, O₂, N₂). We also analyzed the physical properties of the elements in the arrays to develop an intuition for improving array design. Notably, we find that diversity among the surface areas in the MOFs leads to improved sensing. Consistent with the observation, we found that, as one might expect, the best arrays consistently had more structural diversity than the worst arrays.

Alginate-gelatin hydrogels are extensively used in bioengineering. However, despite different formulations being utilized for growing different cell types in vitro, their pH and its effect, together with the crosslinking ions, of those formulations are still infrequently assessed. In this work we studied how these elements can affect hydrogel stability and printability and influence U2OS and NIH/3T3 cell viability and metabolism on the resulting 3D prints. In this context, 6% alginate + 2% gelatin hydrogels were prepared with 0.1 M MES buffer with pH 5.5, 6.5, 7.0 or 8.0, printed by extrusion-based 3D printing, and crosslinked immediately after printing with either CaCl2 or BaCl2. Our results showed that both the buffer pH and the crosslinking ion (Ca2+ or Ba2+) influence the swelling and degradation rates of the prints. Moreover, the buffer pH influenced the printability of the hydrogel in air, but when printed directly in a fluid-phase CaCl2 or BaCl2 crosslinking bath. In addition, both U2OS and NIH/3T3 cells showed greater cell metabolic activity on one-layer prints crosslinked with Ca2+. Besides, Ba2+ increased cell death of NIH/3T3 cells while had no effect on the U2OS cell viability. The pH of the buffer also caused an important impact on the cell behaviour. U2OS cells showed a 2.25-fold cell metabolism increase on one-layer prints prepared at pH 8.0 in comparison to those prepared at pH 5.5. Whereas, NIH/3T3 cells showed greater metabolism on one-layer prints with pH 7.0. Finally, we observed a difference on cell arrangement of the U2OS cells growing on prints prepared from hydrogels with acidic buffer in comparison to cells growing on those prepared using neutral or basic buffer. These results show that both pH and crosslinking ion influence hydrogel strength and cell behaviour.

Authentic learning opportunities that simulate full scale design and construction experiences using real materials offer ideal experiential learning environments for construction and civil engineering students by challenging students to apply building concepts in practical settings. However, the excessive cost of real building materials required for this mode of education limits access to the vast majority of students. As a result, educational researchers have explored potential alternatives to provide cost-effective experiential learning through activities using mock-up materials (e.g., plastic straws, popsicle sticks) and simulation of experiences using immersive technologies (e.g., virtual reality or augmented reality). While some of these alternatives approximate the environment and others provide physical interaction with mock-up materials, the lack of authenticity in the building materials used introduces some apparent differences between the “authentic” learning environments and their cost-effective approximations. Therefore, this research aims to identify the learning processes reported by students and faculty who participated in authentic learning experiences to understand the ways in which this mode of education offers unique value to construction education. Their interview responses illustrated characteristics of authentic learning experiences that were believed to be critical to the learning process, some of which included: working in groups; interdisciplinary participants; and use of real construction materials. Although some of these characteristics are intrinsically linked to the use of real materials, others do not explicitly refer to interaction with real materials. This may indicate to aspects of the authentic learning processes that educational researchers can strategically target through more cost-effective learning environments like virtual and augmented reality. The contribution of this paper is in identifying the characteristics of authentic learning experiences that may guide educational investment and research innovations that aim to replicate some of these learning experiences through more accessible learning environments.

Viscoelastic testing (VET) by both TEG and ROTEM has demonstrated hypercoagulability early in Covid Associated Coagulopathy (CAC). Additional VET studies demonstrated fibrinolytic shutdown late in a majority of severely ill Covid-19 patients with associated elevation of D-dimer. Elevated d-dimer confirms that coagulation, followed by fibrinolysis, has occurred. These findings imply that, during CAC, three enzymes—thrombin, Factor XIIIa and plasmin—must have acted in sequence. However, limitations in standard VET analyses preclude exploration of the earliest phases of clot induction, as well as clot formation and clot dissolution in flowing blood. Herein we describe a novel method illuminating aspects of this unexplored area. In addition, we created an ex vivo blood flow model in which the interactions of thrombin, Factor XIII and plasmin with fibrinogen can be studied, allowing determination of Soluble Fibrin (SF), the highly unstable form of fibrin that precedes the appearance of a visible clot. This model allows determination of the SF level at which fibrin microclots begin to form and the length of time the resulting microclots persist under normal fibrinolytic attack. In addition, the flow model allows exploration of the late fibrinolytic shutdown that VET has previously demonstrated in CAC through standard methodology.

A significant portion of the harvested land base in western Canada is becoming old enough or entering a phase where thinning is a legitimate option. A comprehensive review of the existing knowledge of commercial thinning (CT) treatments applied to pine and spruce-dominated stands in Alberta was conducted, with particular regard to the intensity, the timing of interventions, method and impacts on crop tree growth responses. Although the geographical focus of this review is Alberta, information on this topic is more complete in other areas of North America, and Europe, where there is a long history of density management. In areas of eastern North America, our review revealed that CT from below, with tree removal levels from 27 to 43% of the basal area could increase the merchantable wood volume from 11 to 60 m3 ha-1, depending on stand age and intensity of thinning. For Alberta conditions, and considering the risks, we conclude that commercial thinning basal area removal should be in the range of 25 to 40%, depending on a variety of factors such as species, wind firmness and insect or disease incidence and risk. Thinning too aggressively and/or too late will increase the blowdown risk but the literature is fairly consistent in suggesting that live crown ratios should be >40% to maximize the chance of growth response and minimize the blowdown risk. In cases where stands are also threatened by stressors such as drought, wind, and insect or disease outbreaks, CT treatments likely offer the potential at limiting the overall risk, but localized knowledge and experience are critical. It is intended that the information presented may support ongoing and future research trials and growth and yield (G&Y) model development with regard to potential CT treatments to apply and the likely results of practical application to commercial forestry.

Fungal keratitis (FK) is an invasive infection of the cornea primarily associated with Aspergillus and Fusarium species. FK is treated empirically with a limited selection of topical antifungals with varying levels of success. Though clinical infections are typically characterized by a dense network of mature mycelium, traditional models used to test antifungal susceptibility of FK isolates exclusively evaluate susceptibility in fungal cultures derived from asexual spores known as conidia. The purpose of this study was to characterize differences in fungal response when topical antifungal treatment is initiated at progressive phases of fungal development. We compared efficacy of voriconazole and luliconazole against in vitro cultures of A. flavus and F. keratoplasticum at 0, 24, and 48 h of fungal development. A porcine cadaver corneal model was used to compare antifungal efficacy of voriconazole and luliconazole in ex vivo tissue cultures of A. flavus and F. keratoplasticum at 0, 24, and 48 h of fungal development. Our results demonstrate phase-dependent susceptibility of both A. flavus and F. keratoplasticum to both azoles in vitro as well as ex vivo. We conclude that traditional antifungal susceptibility testing with conidial suspensions does not correlate with fungal susceptibility in cultures of a more advanced developmental phase. A revised method of antifungal susceptibility testing that evaluates hyphal susceptibility may better predict fungal response in the clinical setting where treatment is often delayed until days after the initial insult.

One characteristic of mammalian species is their capacity to produce and secrete milk from their mammary glands to feed and provide vital nutrients for the growth of their offspring. Even though mammary glands provide the same function in different species, their development, shape, and structure can vary according to their reproductive and ecological adaptations. Reproduction studies are important for cetacean conservation because they provide essential information to assess the dynamics of populations and species, particularly in relation to the management of animals under human care. A vast majority of literature on the female cetacean reproductive anatomy and physiology has focused on the ovaries, which can be used to infer life history characteristics, or genital diseases and anomalies. However, literature regarding the morphology, physiology, and developmental pattern of their mammary glands is scarce, with few anatomical and histological descriptions in species such as baleen whales; and more recently it has been assessed with the use of ultrasound in finless porpoises (Neophocaena asiaeorientalis). The aim of this review is to describe the current diagnostic tools applied in human and veterinary medicine to assess the mammary glands and how marine mammal medicine could benefit from these tools to evaluate the mammary glands in free-ranging and captive cetaceans. With the use of imaging techniques such as B-mode ultrasound, non-invasive studies could be performed to assess the mammary tissues, as what has been done to characterize the morphology of other organs in cetaceans, such as the reproductive tract of Indo-Pacific bottlenose dolphins under human care. By understanding and revising the current diagnostic tools to assess the mammary gland of humans and domestic animals, such as ultrasonography, it might be possible to determine which techniques could be applied by marine mammal veterinarians to enhance the evaluation of the cetacean mammary gland morphology and physiology.

Aim: To determine whether an AI model and single sensor measuring acceleration and ECG could model cognitive and physical fatigue for a self-paced trail run. Methods: A field-based protocol of continuous fatigue repeated hourly induced physical (~45 minutes) and cognitive (~10 minutes) fatigue on one healthy participant. Physical load was a 3.8 km, 200 m vertical gain, trail run with acceleration and electrocardiogram (ECG) data collected using a single sensor. Cognitive load was a Multi Attribute Test Battery (MATB) and separate assessment battery including the Finger Tap Test (FTT), Stroop, Trail Making A and B, Spatial Memory, Paced Visual Serial Addition Test (PVSAT), and a vertical jump. A fatigue prediction model was implemented using a Convolutional Neural Network (CNN). Results: When the fatigue test battery results were compared for sensitivity to the protocol load, FTT right hand (R2 0.71) and Jump Height (R2 0.78) were the most sensitive while the other tests were less sensitive (R2 values Stroop 0.49, Trail Making A 0.29, Trail Making B 0.05, PVSAT 0.03, spatial memory 0.003). Best prediction results were achieved with a rolling average of 200 predictions (102.4 s), during set activity types, mean absolute error for ‘walk up’ (MAE200 12.5%) and range of absolute error for ‘run down‘ (RAE200 16.7%). Conclusion: We were able to measure cognitive and physical fatigue using a single wearable sensor during a practical field protocol including contextual factors in conjunction with a neural network model. This research has practical application to fatigue research in the field.

Passive microwave measurements have been available on satellites dating back to the 1970s on research satellites flown by the National Aeronautics and Space Administration (NASA). Since then, several other sensors have been flown to retrieve hydrological products for both operational weather applications (e.g., the Special Sensor Microwave/Imager–SSM/I; the Advanced Microwave Sounding Unit–AMSU) and climate applications (e.g., the Advanced Microwave Scanning Radiometer–AMSR; the Tropical Rainfall Measurement Mission Microwave Imager–TMI; the Global Precipitation Mission Microwave Imager–GMI). Here the focus is on measurements from the AMSU-A, AMSU-B and Microwave Humidity Sounder (MHS). These sensors have been in operation since 1998 with the launch of NOAA-15, and are also on board NOAA-16, -17, -18, -19 and the MetOp-A and -B satellites. A data set called the “Hydrological Bundle” is a Climate Data Record (CDR) that utilizes brightness temperatures from Fundamental CDRs to generate Thematic CDRs (TCDR). The TCDR’s include: Total Precipitable Water (TPW), Cloud Liquid Water (CLW), Sea-Ice concentration (SIC), Land surface temperature (LST), Land surface emissivity (LSE) for 23, 31, 50 GHz, rain rate (RR), snow cover (SC), ice water path (IWP), and snow water equivalent (SWE). The TCDR’s are shown to be in general good agreement with similar products from other sources such as the Global Precipitation Climatology Project (GPCP) and the Modern-Era Retrospective Analysis for Research and Applications (MERRA-2). Because of the careful intercalibration of the FCDR’s, little bias is found among the different TCDR’s produced from individual NOAA and MetOp satellites, except for normal diurnal cycle differences.

In the United States, several land use and land cover (LULC) data sets are available based on Landsat. These data sets often fail to accurately represent the features on the ground despite having several advantages over other data. Detailed mapping of complex heterogeneous landscapes for informed decision-making is possible using high spatial resolution orthoimagery from the National Agricultural Imagery Program (NAIP). However, large-area mapping at this resolution remains challenging due to radiometric differences between scenes, low spectral depth of imagery, landscape heterogeneity, and computational limitations. Machine learning (ML) techniques have shown promise in improving LULC maps. The primary purposes of this study are to examine and evaluate bagging (Random Forest; RF), Boosting (Gradient Boosting Machines [GBM] and Extreme Gradient Boosting [XGB]), and stacking ensemble models on sentinel 2A fusion data on NAIP imagery. We also compared the accuracy based on random cross-validation (80% / 20% split) without accounting for spatial autocorrelation and target-oriented validation (10 clusters) accounting for spatial structures of the training data set. To make the LULC map of a portion of Tom Green and Irion counties in central Texas, we used a time series of sentinel data and NAIP orthoimagery. We created several spectral indices, structural variables, and geometry-based variables, reducing the dimensionality of features generated on Sentinel and NAIP data. The random and target-oriented validation results show that autocorrelation in the training data offers over-optimistic results. In our case, the overestimation ranged from 2 % to 3.5 %. The XGB-boosted stacking ensemble on-base learners (RF, XGB, and GBM) improved model performance over individual base-learner. The main contribution of this research is that meta-learners are just as sensitive to overfitting as base models, as these algorithms are not designed to account for spatial information. Finally, we show that the fusion of Sentinel 2A data with NAIP data improves land use land cover classification using Geographic Object-Based Image Analysis (GEOBIA).

Early detection of neurological conditions is critical for timely diagnosis and treatment. Identifying cellular-level changes is essential for implementing therapeutic interventions prior to symptomatic disease onset. However, monitoring brain tissue directly through biopsies is invasive and high-risk. Bodily fluids such as blood or cerebrospinal fluid contain information in many forms, including proteins and nucleic acids. Particularly, cell-free DNA (cfDNA) has potential as a versatile neurological biomarker. Yet, our knowledge of cfDNA released by brain tissue and how cfDNA changes in response to deleterious events within the brain is incomplete. Mapping changes in cfDNA to specific cellular events is difficult in vivo, where many tissues contribute to circulating cfDNA. Organoids are tractable systems for examining specific changes consistently in a human background. However, few studies have investigated cfDNA released from organoids. Here, we examined cfDNA isolated from cerebral organoids. We found that cerebral organoids release quantities of cfDNA sufficient for downstream analysis with droplet-digital PCR and whole-genome sequencing. Further, gene ontology analysis of genes aligning with sequenced cfDNA fragments revealed association with terms related to neurodevelopment and autism spectrum disorder. We conclude that cerebral organoids hold promise as tools for the discovery of cfDNA biomarkers related to neurodevelopmental and neurological disorders.

Accurate estimation of livestock carrying capacity (LCC) and implementing an appropriate actual stocking rate (ASR) is key to sustainable management of grazing adapted alpine grassland ecosystems. Reliable determination of aboveground biomass is fundamental to these determinations. Peak aboveground biomass (AGBP) captured from satellite data at the peak of the growing season (POS) is widely used as a proxy for annual aboveground biomass (AGBA) to estimate LCC of grasslands. Here we demonstrate limitations of this approach and highlight the ability of POS in the estimation of ASR. We develop and trail new approaches that incorporate remote sensing phenology timings of grassland response to grazing activity, considering relations between biomass growth and consumption dynamics, in efforts to support more accurate and reliable estimation of LCC and ASR. Results show that based on averaged values from large-scale studies of alpine grassland on the Qinghai-Tibet Plateau (QTP), differences between AGBP and AGBA underestimate LCC by about 31%. Findings from a smaller-scale study that incorporate phenology timings into estimation of annual aboveground biomass reveal that Haibei alpine meadows were overgrazed by 11.5% during the study period from 2000-2005. The methods proposed can be extended to map grassland grazing pressure by predicting LCC and tracking ASR, thereby improving sustainable resource use in alpine grasslands.

Commercial crocodilian farms face significant economic and livestock losses attributed to stress, which may be linked to their adopted husbandry practices. The development of appropriate and modernized husbandry guidelines, particularly those focused on stress mitigation, is impeded by the limited understanding of the crocodilian stress response. Fifteen grower Nile crocodiles were subjected to simulated acute transport stress, with blood samples collected at various intervals post-stress. Plasma levels of corticosterone, dehydroepiandrosterone (DHEA), adrenaline, and noradrenaline were determined using high-performance liquid chromatography. Glucose and lactate were measured using portable meters, and the heterophil-to-lymphocyte ratio (HLR) was determined via differential leucocyte counts. Significant differences were elicited after the stressor, with acute fluctuations observed in the fast-acting catecholamines (adrenaline and noradrenaline) when compared to baseline. Downstream effects of these catecholamines and corticosterone appear to be associated with a persistent increase in plasma glucose and HLR. Lactate also showed acute fluctuations over time but returned to baseline by the final measurement. DHEA, used as a ratio with corticosterone, showed fluctuations over time with an inverted release pattern to the catecholamines. The study highlights the temporal dynamics of physiological markers under acute stress, contributing to understanding crocodilian stress and potentially informing improved farming practices for conservation and sustainable management.

In many of the current software applications, numerous vulnerabilities may be present.1 Attackers attempt to exploit existing vulnerabilities that lead to security breaches, unauthorized entry,2 data theft, or incapacitation of a computer system. Rather than addressing software or hardware3 vulnerabilities at a later stage, it is better to address them immediately. DevSecOps, when utilized4 in application development, tackles these vulnerabilities at an early stage. AIBughunter is a tool5 that addresses this problem in software and was developed by the ASWM research group to predict,6 classify, and repair software vulnerabilities. AIBughunter integrates LineVul to find vulnerable7 code lines and returns information about the type of vulnerability and its severity to developers.8 It also includes a tool, VulRepair, which detects and repairs vulnerabilities. VulRepair currently9 predicts patches for vulnerable functions at 44%. In order to become truly effective, this number 10 needs to be increased. This study examines VulRepair to see whether the 44% Perfect Prediction 11 can be increased. VulRepair is a T5 based model that uses Natural Language and Programming 12 Languages for pre-training along with Byte Pair Encoding. It outperforms other existing models, 13 such as VRepair and CodeBERT. However, the hyperparameters may not be optimized due to the 14 development of new optimizers. We review a Deep Neural Network (DNN) optimizer developed by 15 Google in 2023. This optimizer called Evolved Sign Momentum (LION) is available in PyTorch. We 16 applied this optimizer to VulRepair and tested its influence on hyperparameters. After adjusting the 17 hyperparameters, we obtained a 56% Perfect Prediction, which exceeds the value of the VulRepair 18 report of 44%. This means that VulRepair can repair more vulnerabilities and avoid more attacks. As 19 far as we know, our approach of utilizing an alternative to AdamW, the standard optimizer, has not 20 been previously applied to enhance VulRepair and similar models. 21

Current instrumental technology in evaluating performance of skin care creams is still rather limited and there are no industrial standard testing equipment, method and performance specifications for it. In this paper, we report our attempt in using an instrument called PhabrOmeter for this purpose. PhabrOmeter is a commercialized instrument for sensory performance evaluation of textiles, leather, paper and nonwoven and has been designated by American Association of Textile Chemists and Colorists (AATCC) as a standard test method for textiles, AATCC TM 202 in 2013. By adopting artificial skin samples treated with skin care creams, we have developed a procedure to apply this instrument for evaluation of skin care creams from sample preparation, measurement to data analysis and interpretation. The results using commercial skin care creams to demonstrate the feasibility and advantages of this instrument are provided.

The use of flexible sensors has tripled over the last decade due to the increased demand in various fields including health monitoring, food packaging, electronic skins and soft robotics. Flexible sensors have the ability to be bent and stretched during use and can still maintain their electrical and mechanical properties. This gives them an advantage over rigid sensors that lose their sensitivity when subject to bending. Advancements in 3D printing have enabled the development of tailored flexible sensors. Various additive manufacturing methods are being used to develop these sensors including inkjet printing, aerosol jet printing, fused deposition modelling, direct ink writing, selective laser melting and others. Hydrogels have gained much attention in the literature due to their self-healing and shape transforming. Self-healing enables the sensor to recover from damages such as cracks and cuts incurred during use and this enables the sensor to have a longer operating life and stability. Various polymers are used as substrates on which the sensing conductive material is placed. Polymers including polydimethylsiloxane (PDMS), polyvinyl acetate (PVA), and Kapton are extensively used in flexible sensors. The most widely used nanomaterials in flexible sensors are carbon and silver, however, other nanomaterials such as iron, copper, manganese dioxide and gold are also used to provide controlled levels of conductivity or other functional properties.

Chronic lymphocytic leukemia (CLL) is characterized by dysfunctional B cells. Immune checkpoint molecules such as cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), and programmed death-1 (PD-1) are upregulated in patients with CLL and may correlate with prognostic markers such as beta-2 microglobulin (B2M). The aim of this study was to evaluate the levels of immune checkpoints on B-cell subsets and to further correlate them with B2M levels in patients with CLL. We recruited 21 patients with CLL and 12 controls. B cell subsets and the levels of immune checkpoint expression were determined using conventional multi-color flowcytometry. Basal levels of B2M in patients with CLL were measured using an Enzyme-linked immunosorbent assay. Patients with CLL had increased levels of activated B cells when compared to the control group, p< 0.001. The expression of PD-1 and CTLA-4 were increased on activated B cells and memory B cells, p< 0.05. There were no associations between B2M levels and the measured immune checkpoints on B cell subsets, after adjusting for sex and age. African patients with CLL express elevated levels of PD-1 and CTLA-4 immune checkpoints on activated and memory B cell subsets. However, there is no correlation between these immune checkpoint expressions and B2M levels.

Membrane filtration is a popular choice in the treatment of wastewater for reuse. However, when used to produce clean water, these devices are subject to concentration polarization and fouling, which inhibit their ability to operate efficiently and provide high-quality permeate streams. Patterned membrane surfaces offer a hydrodynamic approach to mitigating concentration polarization and the surface fouling that follows. However, when subject to a steady feed flow rate, surface patterns generally produce stagnant zones in cavity-like spaces where particulate from the bulk flow recirculates in stationary vortices. To prevent aggregation in these recirculation zones, and therefore the onset of surface fouling, we study a rapidly pulsed feed flow. When combined with cavity-like geometries, such as the valleys present in membrane surface patterns, a rapidly pulsed flow generates mixing mechanisms (i.e., the deep sweep and the vortex ejection) that disrupt otherwise stagnant regions. First, we confirm the existence of these mechanisms, which are typically induced in impermeable cavities at relatively low Reynolds numbers, for near transitional feed Reynolds numbers in permeable cavity spaces via numerical simulation of the flow field. Following this confirmation, we demonstrate the ability of these mechanisms to remove particles trapped in recirculation zones via massless particle tracking studies. The results of this work suggest that when combined with a rapidly pulsed inlet flow, patterned membrane surfaces can not only alleviate concentration polarization and the surface fouling that follows but also reduce the need for traditional cleaning methods, which require operational downtime and often involve the use of abrasive chemical agents.

The Internet of Medical Things (IoMT) represents a specialized domain within the Internet of Things, focusing on medical devices that require regulatory approval to ensure patient safety. Trusted composition of IoMT systems aims to ensure high assurance of the entire composed system, despite potential variability in the assurance levels of individual components. Achieving this trustworthiness in IoMT systems, especially when using less-assured, commercial, off-the-shelf networks like Ethernet and WiFi, presents a significant challenge. To address this challenge, this paper advocates a systematic approach that leverages the Architecture Analysis & Design Language (AADL) along with Behavior Language for Embedded Systems with Software (BLESS) specification and behavior. This approach aims to provide high assurance on critical components through formal verification, while using less-assured components in a manner that maintains overall system determinism and reliability. A clinical case study involving an automated opioid infusion monitoring IoMT system is presented to illustrate the application of the proposed approach. Through this case study, the effectiveness of the systemic approach in achieving trusted composition of heterogeneous medical devices over less-assured networks is demonstrated.

A two-year study was conducted in Maine wild blueberry fields (Vaccinium angustifolium Aiton) on the health of migratory honey bee colonies in 2014 and 2015. In each year 3-5 colonies were monitored at each of 9 wild blueberry field locations during bloom (mid-May until mid-June). Colony health was measured by assessing percent worker and sealed brood rate of change from the beginning of bloom until the end of bloom. Potential factors that might affect colony health were queen failure or supersedure; pes-ticide residues on trapped pollen, wax comb, and bee bread; and parasites and pathogens. We found that Varroa mite and pesti-cide residues on trapped pollen were significant predictors of colony health as measured by the percent rate of change of sealed brood during bloom. These two factors explained 71% of the variance in colony health over the two years. Pesticide exposure was different in each year as were pathogen prevalence and incidence. We detected high prevalence and abundance of two recently discovered pathogens and one recently discovered parasite, the trypanosome Lotmaria passim Schwartz, the Sinai virus, and the phorid fly, Apocephalus borealis Brues.

Imaging systems mounted to ground vehicles are used to image fruit tree canopies for estimation of fruit load, but frequently need correction for fruit occluded by branches, foliage or other fruits. This can be achieved using an orchard ‘occlusion factor’, estimated from a manual count of fruit load on a sample of trees (referred to as the reference method). It was hypothesised that canopy images could hold information related to the number of occluded fruit. Five approaches to correct for occluded fruit based on canopy images were compared using data of three mango orchards in two seasons. However, no attribute correlates to the number of hidden fruit were identified. Several image features obtained through segmentation of fruit and canopy areas, such as the proportion of fruit that were partly occluded, were used in training Random forest and multi-layered perceptron (MLP) models for estimation of a correction factor per tree. In another approach, deep learning convolutional neural networks (CNNs) were directly trained against harvest fruit count on trees. The supervised machine learning methods for direct estimation of fruit load per tree delivered an improved prediction outcome over the reference method for data of the season/orchard from which training data was acquired. For a set of 2017 season tree images (n=98 trees), a R2 of 0.98 was achieved for the correlation of the number of fruits predicted by a Random forest model and the ground truth fruit count on the trees, compared to a R2 of 0.68 for the reference method. The best prediction of whole orchard (n = 880 trees) fruit load, in the season of the training data, was achieved by the MLP model, with an error to packhouse count of 1.6% compared to the reference method error of 13.6%. However, the performance of these models on new season data (test set images) was at best equivalent and generally poorer than the reference method. This result indicates that training on one season of data was insufficient for the development of a robust model. This outcome was attributed to variability in tree architecture and foliage density between seasons and between orchards, such that the characters of the canopy visible from the interrow that relate to the proportion of hidden fruit are not consistent. Training of these models across several seasons and orchards is recommended.

The propeller jet from a ship has a significant component directed upwards towards the free surface of the water, which can be used for ice management. This paper describes a comprehensive laboratory experiment where the influences of operational factors affecting a propeller wake velocity field were investigated. The experiment was done on a steady wake field to investigate the characteristics of the axial velocity of the fluid in the wake and the corresponding variability downstream of the propeller. The axial velocities and the variability recorded were time-averaged. Propeller rotational speed was found to be the most significant factor, followed by propeller inclination. The experimental results also provide some idea about the change of the patterns of the mean axial velocity distribution against the factors considered for the test throughout the effective wake field, as well as the relationships to predict the axial velocity for known factors.

Background: Grades in clinical courses matter. They are often used to determine clinical academic awards, scholarships, and—most importantly—interns’ suitability for graduate medical education opportunities. Aware of these stakes, clinic preceptors may feel pressure to grade too leniently or uniformly. A fair method of adjusting for differences in preceptor bias is then needed. Approach: The authors propose a technique that employs the advantages of both criterion- and normative-based grading to adjust for differences in both grader leniency and uniformity. Evaluation: The technique produces fair adjustments to any raw assign grades, and the authors demonstrate how easily this process can be administered in any clinical setting where multiple preceptors are evaluating interns. Implications: This work provides a grading framework that is transparent to all stakeholders but places responsibilities at the appropriate level. That is, clinic performance evaluations are left to clinic preceptors but grading to clinic academic managers.

The Rosetta software suite for macromolecular modeling, docking, and design is widely used in pharmaceutical, industrial, academic, non-profit, and government laboratories. Considering its broad modeling capabilities, Rosetta consistently ranks highly when compared to other leading methods created for highly specialized protein modeling and design tasks. Developed for over two decades by a global community of scientists at more than 60 institutions, Rosetta has undergone multiple refactorings, and now comprises over three million lines of code. Here we discuss the methods developed in the last five years, involving the latest protocols for structure prediction, protein–protein and protein–small molecule docking, protein structure and interface design, loop modeling, the incorporation of various types of experimental data, and modeling of peptides, antibodies and other proteins in the immune system, nucleic acids, non-standard amino acids, carbohydrates, and membrane proteins. We briefly discuss improvements to the energy function, user interfaces, and usability of the ­­software. Rosetta is available at www.rosettacommons.org.

Solar power innately has issues with weather, grid demand and time of day, which for the case of concentrating solar power (CSP) can be mitigated through use of thermal energy storage. Nuclear reactors, including lead-cooled fast reactors (LFRs), can load follow, but have high fixed and low operating costs which can make this economically unattractive. We investigate potential synergies through coupling CSP and LFR together in a single supercritical CO$_2$ Brayton cycle and/or using the same thermal energy storage. Combining these cycles allows for the LFR to thermally charge the salt storage in the CSP cycle during low demand periods to be dispatched when grid demand increases. The LFR/CSP coupling into one cycle is modeled to find the preferred location of the LFR heat exchanger, CSP heat exchanger, sCO$_2$-to-salt heat exchanger (C2S), turbines, and recuperators within the supercritical CO$_2$ Brayton cycle. Three cycle configurations have been studied: two-cycle configuration, which uses CSP and LFR heat for dedicated turbocompressors, has the highest efficiencies but with less component synergies; a combined cycle with CSP and LFR heat sources in parallel is the simplest with the lowest efficiencies; and a combined cycle with separate high temperature recuperators for both the CSP and LFR is a compromise between efficiency and component synergies. Additionally, four thermal energy storage charging techniques are studied: the turbine positioned before C2S, requiring a high LFR outlet temperature for viability; the turbine after the C2S, reducing turbine inlet temperature and therefore power; the turbine parallel to the C2S producing moderate efficiency; and a dedicated circulator loop. While all configurations have pros and cons, use of a single cycle offers component synergies with limited efficiency penalty. Using a turbine in parallel with the C2S heat exchanger is feasible but results in a low charging efficiency, while a dedicated circulator loop offers flexibility and near perfect heat storage efficiency but increasing cost with additional cycle components.

An area has been designated for demonstrating the utility of marine hydrokinetic turbines in Minas Passage, Bay of Fundy. Marine renewable energy may be useful for the transition from carbon-based energy sources but there is concern for the safety of fish that might encounter turbines. Acoustic receivers that detect signals from acoustically tagged fish that pass through the tidal demonstration area and detection efficiency of tag signals might be used to estimate the likelihood of fish encountering marine hydrokinetic turbines. The method requires that tagged fish passing through the development area will be reliably detected by a receiver array. The present research tests the reliability with which passing tags are detected by suspending tags beneath GPS-tracked drifters. Drifters carrying high residency Innovasea tags that transmitted every 2 seconds were usually detected by the receiver array even in fast currents during spring tides but pulse position modulation tags were inadequate. Sometimes very few high residency tag signals were detected when fast tidal currents swept a drifter through the receiver array, so increasing the transmission interval degrades performance at the tidal energy development area. High residency tags suspended close to the sea surface were slightly less likely to be detected if they passed by during calm conditions. Previously measured detection efficiencies were found to slightly overestimate the chances of a high residency tag carried by a drifter being detected as it passed by a receiver. This works elucidates the effectiveness with which acoustically tagged fish are detected in fast, highly turbulent tidal currents and informs the application of detection efficiency measurements to calculate the probability that fish encounter a marine hydrokinetic turbine.

We aimed to investigate whether the sequence length of HIV-1 increases over time. A longitudinal analysis of full-length coding region sequences (FLs) during an HIV-1 outbreak among pa-tients with hemophilia and local controls infected with the Korean subclade B of HIV-1 (KSB) was performed. Genes were amplified by overlapping RT-PCR or nested PCR and subjected to direct sequencing. Overall, 141 FLs were sequentially determined over 30 years in 62 KSB-infected patients. Phylogenetic analysis indicated that within KSB, two FLs from plasma donors O and P comprised two clusters together with 8 and 12 patients with hemophilia, respectively. Signature pattern analysis for the KSB of HIV-1 revealed 91 signature nucleotide residues (1.05%). In total, 48 and 43 signature nucleotides originated from clusters O and P, respectively. Only six positions contained 100% specific nucleotide(s) in clusters O and P. Additionally, in-depth FL analysis over 30 years indicates that the KSB FL significantly increased over time before combined antiretroviral therapy (cART) and decreased with cART. The increase occurred due to a significant increase in env and nef genes, originating in the variable regions of both genes. The increase in the sequence length of HIV-1 over time suggests that it has an evolutionary direction.

The objective of this study is to investigate whether the sequence length of HIV-1 increases over time. A longitudinal analysis of full-length coding region sequences (FLs) in an outbreak of HIV-1 infection among patients with hemophilia and local controls identified as infected with the Korean subclade B of HIV-1 (KSB). Genes amplified by overlapping RT-PCR or nested PCR were subjected to direct sequencing. In total, 141 FLs were sequentially determined over 30 years in 62 KSB-infected patients. Non-KSB sequences were retrieved from the Los Alamos National Laboratory HIV Database. Phylogenetic analysis indicated that within KSB, 2 FLs from plasma donors O and P comprised two clusters together with 8 and 12 patients with hemophilia, respectively. Signature pattern analysis for the KSB of HIV-1 revealed signature nucleotide residues at 1.05%, compared with local controls. Additionally, in-depth FLs sequence analysis over 30 years in KSB indicates that the KSB FL significantly increases over time before combined antiretroviral therapy (cART) and decreases on cART. Furthermore, the increase in FLs over time significantly occurred in the subtypes B, C and G, but, there was no increase in the subtypes D, A, and F1. Consequently, subtypes F1 and D had the shortest sequence length. Our analysis was extended to compare HIV-1 with HIV-2 and SIVs. Essentially, the longer the sequence length (SIVsm > HIV-2 > SIVcpz > HIV-1), the longer the survival period. The increase in the length of the HIV-1 sequence over time suggests that it might be an evolutionary direction toward attenuated pathogenicity.

The aims of the review were to elucidate the spatial variation in sea ice algae primary production rates and biomasses (Chl a) in the Canadian Arctic – Greenland region, characterized by comparable physical settings. A database was compiled from 30 studies of sea ice algae primary production rates, biomasses (Chl a), snow and ice thicknesses, ice types, nutrient (Si(OH)4, PO4, (NO3+NO2), and (NH4) concentrations in ice and below ice from the region. Production rates were significantly high (463 mg C m-2 d-1) in Resolute Bay and in Northern Baffin Bay (317 mg C m-2 d-1) both in Canadian Arctic, as compared to a rate of 0.2 mg C m-2 d-1 in northeast Greenland. The biomasses reached 340 mg Chl a m-2 in Resolute Bay in comparison to a 0.02 mg Chl a m-2 in southwest Greenland. Primary production at other Canadian and Greenland sites were comparable but sea ice Chl a was higher (15.0 ± 13.4 mg Chl a m-2) at Canadian sites as compared to Greenland (0.8 ± 0.5 mg Chl a m-2). Resolute and Northern Baffin Bays production rates were significantly higher when compared to other Arctic Ocean sites outside the studied region. The review concludes that high production rates and biomasses in Resolute and Northern Baffin Bay’s were related to inflow and mixing of nutrient rich waters of Pacific origin. A conceptual model with drivers and inhibitors of sea ice algae primary production is projected, and the database compiles a dataset of published data for further studies.

The accommodative response of the human eye is predominantly driven by foveal vision but reacts also to off-foveal stimuli. Here, we report on monocular accommodation measurements using parafoveal and perifoveal annular stimuli centered around the fovea and extending up to 8 degree radial eccentricity for young emmetropic and myopic subjects. The stimuli were presented through a sequence of random defocus step changes induced by a pupil-conjugated tunable lens. A Hartmann-Shack wavefront sensor with an infrared beacon was used to measure real-time changes of ocular aberrations up to and including the 4th radial order across a 3 mm pupil at 20 Hz. Our findings show a significant reduction in accommodative response with increased radial eccentricity.

The purpose of this study is to determine the availability of "more healthful" (MH) versus "less healthful" (LH) entrée items in the campus dining and if students' purchases are reflective of what is offered. This is an observational study in which students' purchases of the available entrée items in the campus dining at a Midwestern university in one academic year were collected and categorized as either MH or LH according to the American Heart Association guidelines. Chi-square tests were used to determine the differences between the proportion of purchased MH and LH versus those available. Odds ratio estimates with 95% confidence limits were used to determine the associations between the demographics and MH and LH purchases. Of the total entrée items available, 15.0% were MH and 85.0% were LH. In the fall, 8.0% of purchases were MH and 92.0% purchases were LH as compared to 8.9% MH and 91.1% LH in the spring. Whites were less likely than non-whites to purchase a MH entrée. Females were two times more likely to choose MH entrées than males. The campus dining offerings and students' purchases of entrees were primarily LH. Work with campus dining providers to create profitable, yet healthful, dining entrees is needed to improve the healthfulness of entrée offerings.

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

In an era of unparalleled technical advancement, the pharmaceutical industry is struggling to transform data into increased research and development efficiency, and as a corollary, new drugs for patients. Here, we briefly review some of the commonly discussed issues around this counterintuitive innovation crisis. Looking at both industry and science related factors, we posit that traditional preclinical research is front-loading the development pipeline with data and drug candidates that are unlikely to succeed in patients. Applying a first principles analysis, we highlight the critical culprits and provide suggestions as to how these issues can be rectified through pursuit of a Human Data-driven Discovery (HD3) paradigm. Consistent with other examples of disruptive innovation, we propose that new levels of success are not dependent on new inventions, but rather the strategic integration of existing data and technology assets. In support of these suggestions, we highlight the power of HD3, through recently published proof-of-concept applications in the areas of drug safety analysis and prediction, drug repositioning, rational design of combination therapies and the global response to the Covid19 pandemic. We conclude that innovators must play a key role in expediting the path to a largely human focused, systems-based approach to drug discovery and research.

Diffuse intrinsic pontine glioma (DIPG) is recognized as a pediatric brainstem cancer with a 0% survival rate. On a molecular basis, DIPG commonly results from mutations in histone H3, specifically a mutation in the H3K27M gene, that promotes tumorigenesis and results in presentation of this fatal brainstem tumor. DIPG is challenging to treat, as surgical intervention is inefficacious due to the location where the glioma resides. To date, traditional treatments such as radiation, chemotherapy, and immunotherapy have not increased survival rates and have only been successful at relieving symptoms. Future therapeutic approaches such as proton beam radiation, Chimeric Antigen Receptor T Cell (CAR-T) immunotherapy, and alternative epigenetic pharmaceuticals are under investigation for potential benefits. Various clinical trials have also explored these treatment procedures to discover potential increases in survival rates in both animal and human studies. In this review, we will evaluate the pathology and molecular characteristics of DIPG, the current and future approaches to DIPG treatment; and, lastly, we will discuss clinical trials that have been completed to develop successful treatment options.

Understanding the dynamics of humoral immune responses throughout the COVID-19 pandemic is crucial for optimizing vaccine strategies. This study aimed to investigate the impact of infection and vaccine-induced immunity on the Albanian population from August 2021 to August 2022. Two independent samples from the Albanian general population were analyzed using an ELISA method to assess IgG class anti-Spike (S1) and anti-Nucleocapsid (N) SARS-CoV-2 antibodies. The results revealed a robust immune response among vaccinated individuals with prior COVID-19 infection who received only one vaccine dose. In the 2022 cohort, most individuals who received one vaccine dose achieved comparable seropositivity and antibody levels to those who received two doses. However, individuals aged 61 and over required two or three vaccine doses to reach the same level of immune response as the younger population. Notably, the time elapsed since infection or vaccination did not significantly impact the immune response. These findings highlight the importance of hybrid immunity and suggest that one vaccine dose may be sufficient for most individuals with prior COVID-19 infection. However, additional doses are necessary for optimal protection in older individuals. This study provides unique insights into humoral immune response dynamics that can be used to refine ongoing COVID-19 population vaccination strategies for middle-income countries with low vaccination coverage.

The extent of single and multi-cropping systems in any region, and potential changes to it, have consequences on food and resource use raising important policy questions. However, addressing these questions is limited by a lack of reliable data on multi-cropping practices at a high spatial resolution, especially in areas with high crop diversity. In this paper, we describe a relatively low-cost and scalable method to identify double cropping at the field-scale using satellite (Landsat) imagery. The process combines machine learning methods with expert labeling. We demonstrate the process by measuring double cropping extent in a portion of Washington State in the Pacific Northwest United States--- a region with significant production of more than 60 distinct types of crops including hay, fruits, vegetables, and grains in irrigated settings. Our results indicate that the current state-of-the-art methods for identifying cropping intensity---that apply rule-based thresholds on vegetation indices---do not work well in regions with high-crop-diversity. Our deep learning model was able to capture the diverse nuances and achieve a high accuracy (99\% overall accuracy and 0.92 Kappa coefficient). Our expert labeling process worked well and has potential as a relatively low-cost, scalable approach for remote sensing applications. The product developed here is valuable to inform several policy questions related to food production and resource use.

Soybean maturity is a trait of critical importance for the development of new soybean cultivars, nevertheless, its characterization based on visual ratings has many challenges. Unmanned aerial vehicles (UAVs) imagery-based high-throughput phenotyping methodologies have been proposed as an alternative to the traditional visual ratings of pod senescence. However, the lack of scalable and accurate methods to extract the desired information from the images remains a significant bottleneck in breeding programs. The objective of this study was to develop an image-based high-throughput phenotyping system for evaluating soybean maturity in breeding programs. Images were acquired twice a week, starting when the earlier lines began maturation until the latest ones were mature. Two complementary convolutional neural networks (CNN) were developed to predict the maturity date. The first using a single date and the second using the five best image dates identified by the first model. The proposed CNN architecture was validated using more than 15,000 ground truth observations from five trials, including data from three growing seasons and two countries. The trained model showed good generalization capability with a root mean squared error lower than two days in four out of five trials. Four methods of estimating prediction uncertainty showed potential at identifying different sources of errors in the maturity date predictions. The architecture used solves limitations of previous research and can be used at scale in commercial breeding programs.

Fusarium head blight (FHB) disease is extensively distributed worldwide. This disease damages grain quality and reduces yield. The detection of this disease in a high throughput way is crucial to planters and breeders. Our study focused on developing a method for processing wheat color images and accurately detecting disease areas using deep learning and image processing techniques. The color images of wheat at the milky stage were collected and processed to construct datasets, which were used to retrain a deep convolutional neural network model using transfer learning. Testing results showed that the model can detect spikes, and the coefficient of determination of the number of spikes between the manual count and the detection was 0.80. The model was assessed, and the mean average precision for the testing dataset was 0.9201. On the basis of the results of spike detection, a new color feature was applied to obtain the gray image of each spike. Then, a modified region growing algorithm was implemented to segment and detect the diseased areas of each spike. Results show that the region growing algorithm performs better than K-means and Otsu’s method in segmenting the FHB disease. Overall, this study demonstrates that deep learning techniques enable the accurate detection of FHB in wheat using color images, and the proposed method can effectively detect spikes and diseased areas, thereby improving the efficiency of FHB detection.

Running on a non-motorized, curved-deck treadmill is thought to improve gait mechanics. It is not known, though, if the change in gait carries over to running on a motorized treadmill or level ground. To determine the effect of running on a curved non-motorized treadmill (CNT) on gait characteristics measured during a subsequent bout of running on a traditional motorized treadmill (TMT). Sixteen healthy college-aged participants, age (mean±SD) 20.4±1.6 years volunteered to have their gait analyzed while running on a TMT and CNT. After familiarization and warm-up on both treadmills, each subject completed five, 4-minute bouts of running alternating between traditional motorized and curved non-motorized treadmills: TMT-1, CNT-1, TMT-2, CNT-2, and TMT-3. Variables of interest included step length (m), stride length (m), imbalance score (%), and step angle (°) and were measured using Optogait gait analysis equipment. Differences in gait char acteristics among TMT-1, TMT-2, and TMT-3 can be attributed to running on the CNT. The results show that running on a CNT resulted in significant changes in gait characteristics. These findings suggest that running on a CNT can significantly alter gait characteristics may result in improvements in running gait that persist to subsequent running on a TMT.

Magnesium nanoparticles of various mean diameters (53 – 239 nm) were synthesized herein via Pulsed Laser Ablation in Liquid (PLAL) from millimeter sized magnesium powders within iso-propyl alcohol. It was observed via a 3x3 full factorial DOE that the processing parameters can control the nanoparticle distribution to produce three size-distribution types (bimodal, skewed and normal). Ablation times of 2, 5, and 25 minutes where investigated. An ablation time of 2 minutes produced a bimodal distribution with the other types seen at higher periods of processing. Mg nanoparticle UV-Vis absorbance at 204 nm increased linearly with increasing ablation time, indicating an increase in nanoparticle count. The colloidal density (mg/ml) generally increased with increasing nanoparticle mean diameter as noted via increasing UV-vis absorbance. High la-ser scan speeds (within the studied range of 3000 - 3500 mm/s) tend to increase the nanoparticle count/yield. For the first time, the effect of scan speed on colloidal density, UV-vis absorbance and nanoparticle diameter from metallic powder ablation was investigated and is reported herein. The nanoparticles formed dendritic structures after being drop cast on aluminum foil as observed via FESEM analysis. Dynamic light scattering was used to measure the size of the nanoparticles. Magnesium nanoparticles have promising use in the fabrication of wearables, such as in conductive tracks or battery electrodes, owing to their low heat capacity, high melting point and bio-compatibility.

Primary central nervous system and brain tumors are one of the global burdens that are continuously increasing in cases and requiring more treatment options. Surgery has been the leading treatment option for tumors, however, the localization of the tumor and its infiltrating nature make this option challenging. DNA microarray expression profiles of different CNS tumors provide insight into potential biomarkers for identifying different tumor types and subtypes. Here, we utilized the differentially expressed genes common in four expression profiles, GSE66354, GSE68848, GSE74195, and GSE43290 to reconstruct the gene co-expression network. In this study, we were able to identify preserved cluster genes, hub genes, co-regulating transcription factors, miRNA families, and candidate repurposed drugs. Fourteen identified hub genes, which were, CACNA1A, DNM1, GABRA1, GRIA2, MAPT, SLC17A7, SNAP25, SNAP91, STXBP1, SYT1, COL1A1, COL6A2, FBN2, and FN1 appeared to play a role in tumor progression and may serve as drug targets. We also reported the DEGs in each tumor type, which were ATRT, EPN, PA, MED, PNET, MEN, ACM, ODG, and GBM. Five identified miRNA families, which were, let-7 family, mir-124 family, mir-1 family, mir-103 family, and mir-27 family described in the literature to have tumor-suppressing characteristics. Drug-gene and drug-transcription factor network revealed 32 candidate repurposed drugs and 13 were validated through connectivity map analysis. Here, two main repurposed drugs fit the regulatory requirement for gene interaction, these were, quercetin and vorinostat. Future validation in experimental studies may utilize the future use of the candidate repurposed drugs. Our study provides insights into drug repurposing prospects and understanding tumor expressions.

Pregnancy is a dynamic state with multiple metabolic changes occurring including insulin resistance. Gestational diabetes mellitus (GDM), a form of diabetes that appears during pregnancy, develops if metabolic aberrations occur, in particular, in normal pregnancy-induced insulin resistance. Multi-omics is a powerful approach for uncovering the mechanisms driving metabolic change in different physiologic and pathologic states. A recent study demonstrated that the gestational gut microbiome mediates pregnancy metabolic adaptations through effects on gut indoleamine-2,3 dioxygenase 1 activity and the production of kynurenine. Using the dataset generated from this highly controlled study, we performed a comprehensive analysis of the pregnancy-specific physiological and metabolic profiles, 16S rRNA microbiome, and plasma untargeted LC-MS metabolome data. To facilitate the utilization of these analysis results by other researchers, we developed MOMMI-MP, a database that provides an easy-to-use platform to browse and search differential abundant microbial taxa and metabolites, and to examine metabolic pathways. The datasets consist of data collected from 3 genetically diverse strains of mice (C57BL/6J, CD1, and NIH-Swiss) over 6 time points during the gestational (days 0, 10, 15, and 19 during gestation) and postpartum (days 3 and 20 after delivery) states, totaling 180 samples for each strain. The computational results are presented in various tables and plots, and organized in MOMMI-MP to empower exploratory analyses by other researchers. In conclusion, MOMMI-MP is a resource to facilitate the investigation of novel mechanisms governing metabolic changes during pregnancy.

This paper aims to provoke fundamental thinking and action around the value and importance of socially-equitable development to the economic advancement, resilience, and prosperity of communities, as we contend with the 21^st Century grand challenge of the changing climate and disasters. As local communities and the global community have experienced an increased frequency, intensity and duration of natural and man-made disasters over the past several decades, opportunities have also grown to identify and reap the benefits of socially-equitable economic development. Reflecting on the COVID-19 pandemic, we discuss the critical importance of socially-equitable economic development to the resilience and sustainability of communities and the infrastructure that supports them. To this end, we: (1) examine what constitutes socially-equitable economic development at different spatial scales of community; (2) explore whether socially-equitable development can occur at different scales of community; (3) explicate the importance of formally considering the inputs, processes, outputs and outcomes for socially-equitable development; (4) explain why the pursuit of equal distribution of the benefits and burdens of development is a necessary but not sufficient endeavor for socially-equitable economic development; (5) analyze the relationships between socially-equitable development, and resilient and sustainable infrastructure and communities; (6) explain why socially-equitable development should be a key component of infrastructure and community resilience strategies in the 21^st Century; and, (7) explain why socially-equitable development can ultimately be viewed as a long-term strategy for prosperity.

Although jojoba (Simmondsia chinensis) has been cultivated for years, information on its N re-quirements is limited. A 6-year study of mature jojoba plants grown under field conditions with an intensive management regime evaluated the effect of N-application rate on plant nutrient status, growth and productivity, and nitrate accumulation in the soil. Five levels of N application were tested: 50, 150, 250, 370 and 500 kg N ha-1. The fertilizers were provided all along the growing season via subsurface drip irrigation system. Leaf N concentration, in both spring and summer, reflected the level of N applied. Diagnostic leaf (youngest leaf that has reached full size) concentration of 1.3% N was identified as the threshold for N deficiency. Increasing rates of N application resulted in higher P levels in young leaves. Plant K status, as reflected by leaf analysis, was not affected by N treatment but was strongly affected by fruit load. Vegetative growth was inhibited when only 50 kg N ha-1 was applied. Soil analysis at the end of the fertilization season showed substantial accumulation of nitrate for the two highest application rates. Considering productivity, N costs, and environmental risk, 150 kg N ha-1 is the recommended dosage for in-tensively grown jojoba. N deficiencies can be identified using leaf analysis and excess N can be detected by soil sampling toward the end of the growing season. These results and tools will fa-cilitate precise N fertilization in intensive jojoba plantations.

Humanity’s social and economic development has been challenged by a range of adversities over the millennia that have caused widespread and unimaginable suffering. At the same time, these challenges have forced humans to evolve more wisely, overcoming adversity through creativity and leading to advancements in science and technology, medicine, ethics and legal systems, and socio-political systems. The dynamics of risks and opportunities caused by COVID-19, in the built, cyber, social and economic environments, present opportunities for deepening our understanding of resilient and sustainable development and infrastructure. This article reflects on five lessons that COVID-19 is teaching us about what it means to develop sustainably through the lens of transportation: (1) sustainable development planning and analytical frameworks must be comprehensive, for long-term sustainability; (2) multi-modal transportation is a superior vision for sustainable development than any one particular mode; (3) tele-activities are part of an effective infrastructure sustainability strategy; (4) economic capital is critically important to sustainable development even when it is not a critical existential threat, and, (5) effective social capital is essential in global disaster resistance and recovery, and can and must be leveraged between fast-moving and slow-moving disasters. Resilient and sustainable infrastructure will continue to be critical to addressing evolving natural and man-made hazards in the 21^st Century.

Studies investigating the acute effect of postprandial exercise (PPE) on glucose responses exhibit significant heterogeneity in terms of participant demographic, exercise protocol, and exercise timing post-meal. As such, this study aimed to further analyze the existing literature on the impact of PPE on glycemic control in individuals with overweight, obesity, and type 2 diabetes (T2D). Literature search was conducted through databases including PubMed, CINAHL, and Google Scholar. Thirty-one original research studies that met the inclusion criteria were selected. The random-effect meta-analysis was performed to compare postprandial glucose area under the curve (AUC) and 24-h mean glucose levels between PPE and the time-matched no-exercise control (CON). Subgroup analysis was conducted to explore whether the glucose-lowering effect of PPE could be influenced by exercise duration, exercise timing post-meal, and disease status of participants. This study revealed significantly reduced glucose AUC (Hedges’ g = -0.317; SE = 0.057; p < 0.05) and 24-hour mean glucose levels (Hedges’ g = -0.328; SE = 0.062; p < 0.05) following PPE than CON. The reduction in glucose AUC was greater (p < 0.05) following PPE lasting >30 min than ≤30 min. The reduction in 24-hour mean glucose levels was also greater (p < 0.05) following PPE initiated ≥60 min than <60 min post-meal and in those with T2D than those without T2D. PPE offers a viable approach for glucose management and can be performed in various forms so long as exercise duration is sufficient. The glucose-lowering effect of PPE may be further enhanced by initiating it after the first hour post-meal. PPE represents a promising strategy, particularly for patients with T2D.