The number of obese people worldwide is rising dramatically, with 51% of the global population expected to be obese or overweight by 2035. And it is usually involved in a variety of chronic diseases, including diabetes, hypertension, cardiovascular and cerebrovascular diseases. In the process of obesity, adipose tissue expands indefinitely, which induces metabolic dysfunction. Here, we confirm the role of succinate in the intervention of obesity. Through adding succinate to drinking water, high-fat diet induced obese mice were associated with the lower fat mass, and improved glucose tolerance and energy expenditure. These metabolic changes are accompanied by increased expression of lipolysis genes and decreased lipogenesis genes, especially in subcutaneous adipose tissue. In summary, supplement of succinate improves lipid deposition and metabolic health in obese mice.

The paper describes a new formula for calculating the mutual inductance between a thin conical sheet inductor and a filamentary circular loop, which are coaxial. The presented formula is derived semi-analytically using the complete elliptic integrals of the first, second, and the third kind, along with the integral term which will be solved numerically. The results are validated using double and single integration methods, as well as the semi-analytical formula. The mutual inductance between a thin wall solenoid and a filamentary circular loop can be obtained using the new formula for the conical coil and circular loop. Presented formulas can be useful in various applications, such as broadband RF and wireless power transfer systems that utilize conical inductors. Overall, the paper presents a valuable contribution to the field of inductor design and can be useful in various applications involving conical inductors.

Although, central venous pressure (CVP) is among the most frequent estimated hemodynamic parameters in the critically ill setting, extremely little is known on how intensive care unit (ICU) nurses use this index in their decision-making process. The purpose of the study was to develop a new questionnaire for accessing how ICU nurses use CVP measurements to address patients’ he-modynamics investigating its validity and reliability. A cross-sectional study was conducted among 120 ICU nurses from four ICUs of Greece. Based on a comprehensive literature review and the evaluation of a five-experts panel a new questionnaire, named “CVP-Score”, was created having 8 items. The construct validity and the reliability of the questionnaire were examined. The half of the study participants’ (51.7%) was working at a specialized ICU, and they had a mean [±Standard Deviation (SD)] ICU experience of 13(±7.1) years. The estimated construct validity of the new-developed tool was acceptable, while the internal consistency reliability as measured by Cronbach alpha was excellent (0.901). CVP Score had acceptable test-retest reliability (r=0.996, p<0.001) and split-half reliability (0.855). CVP Score is a valid and reliable instrument for measuring how critical care nurses use CVP measurements in their decision-making process.

The Asian weaver ant Oecophylla smaragdina is a natural enemy (predator) used as a biological control agent in Australia and several Southeast Asian nations against the most destructive and economically important oriental fruit fly Bactrocera dorsalis. For biological control of the invasive bagworm species Metisa plana in oil palm plantations, the composition of the colony's social structure was investigated to ensure its efficacy. On two colonies, all castes were examined stereo microscopically after nest collection and dissection. The head's width, head, thorax, abdomen, and body lengths of workers were evaluated during the morphology analysis. All colonies with more than a thousand eggs comprise of a founding egg-laying queen, reproductive winged green and newly emerged yellow queens, as well as adult drone males and workers. Future queens, males, and workers' pupae and larvae comprised immature individuals. It is the first study to characterise one caste of minor workers, two previously unidentified castes of intermediate workers, and two castes of major workers. The lengths of the body and abdomen are proposed as differentiating factors for workers. The discovery of a polymorphic size frequency distribution model contrasts with the consistently reported existence of archetypical bimodal systems in ants. Intermediate workers foraging outside the nest revealed reconnaissance and aggressive behaviours that aided major workers in their daily tasks. Due to their short lifespan and segregated nests, it is difficult to successfully sample adult males in wide plantations. An entire year's worth of reproductive individuals are produced by stable, three-year-old colonies, with a decrease in population size correlated with a significant decline in rainfall interception.

Macrophages are the key effector cells of innate immunity which show two polarized states: M1, classically activated and M2, alternatively activated. Tumor-associated macrophages (TAMs) which usually show M2 polarization, are immunosuppressive cells that enhance tumor metastasis and invasion. Also, enrichment of TAMs is known to be closely associated with poor prognosis of cancer patients. Therefore, TAMs are considered to be promising targets for immunotherapy. Importantly, tumor-derived exosomes emerged as a crucial player in immune regulation which can remodel the tumor microenvironment towards immunosuppressive state. Of note, few studies have shown that exosomes could induce polarization of macrophages towards M2 type in tumor condition, while others showed activation of M1 or mixed phenotype. Considering the role of TAMs in cancer, there is an urgent need to decipher the exosome-mediated cross-talk between tumor cells and macrophages.For this, we used murine model of Dalton’s lymphoma (DL), wherein, firstly, we evaluated increased exosome burden by assessing exosome level in serum as well as in various tissues of tumor-bearing host. Next, proteomic profiling of lymphoma-derived exosomes was done which revealed the presence of immunomodulatory proteins. Of note, these proteins were known to alter the macrophage polarization. In order to assess the effect of these exosomes on macrophages, we performed in vitro study using RAW264.7 cells. In vitro study revealed that frequent uptake of exosomes mediated a morphological change in macrophages which reduced their phagocytic activity. In parallel, exosomes increased reactive oxygen species (ROS) level and inhibited LPS-induced nitric oxide (NO) level in macrophages. Also, exosomes upregulated the expression of arginase-1 (an M2 marker) in macrophages but decreased the LPS-induced nitric oxide synthase 2 (NOS2) (an M1 marker) expression. Moreover, we observed a pro-tumoral cytokine profile in macrophages incubated with exosomes. Our study suggests that exosome load increases in lymphoma-bearing hosts systemically. Importantly, lymphoma-derived exosomes mediate the activation of macrophages towards pro-tumoral M2 type. Our results give an insight into the exosome-mediated tumor and immune cell cross-talk which could serve as an important prospect for targeting in cancer immunotherapy.

: Polymer single screw extrusion is a major industrial processing technique used to obtain plastics products. To assure high outputs, tight dimensional tolerances, and excellent product performance, extruder screws may show different design characteristics. Barrier screws, which contain a second flight in the compression zone, have become quite popular as they promote and stabilize polymer melting. Therefore, it is important to design efficiently extruder screws and decide whether a conventional screw will do the job efficiently, or a barrier-screw should be considered instead. This work uses multi-objective evolutionary algorithms to design conventional and barrier screws (Maillefer screws will be studied) with optimized geometry. Processing of two polymers, Low Density Polyethylene and Polypropylene, is analyzed. A methodology based on the use of Artificial Intelligence (AI) techniques, namely data mining, decision making and evolutionary algorithms, is presented and utilized to obtain results with practical significance, based on relevant performance measures (objectives) used in the optimization. For the various case studies selected, Maillefer screws were generally advantageous for processing LDPE, while for PP the use of both types of screws would be feasible.

The global population is currently experiencing the impact of the SARS-CoV-2 coronavirus, which has caused the Coronavirus Disease 2019 (COVID-19) pandemic. By our profound comprehension of COVID-19, encompassing the involvement sequence of the respiratory tract, gastrointestinal system, and cardiovascular apparatus, the multiorgan symptoms of this infectious disease have been discerned. Metabolic-associated fatty liver disease (MAFLD) is a pervasive public health concern, intricately linked with metabolic dysregulation and estimated to afflict one-fourth of the global adult population. The burgeoning focus on the association between COVID-19 and metabolic dysfunction-associated fatty liver disease (MAFLD) is justified by the potential role of the latter as a risk factor for both SARS-CoV-2 infection and the subsequent emergence of severe COVID-19 symptoms. Investigations have suggested that changes in both innate and adaptive immune responses among metabolic dysfunction-associated fatty liver disease (MAFLD) patients may play a role in determining the severity of COVID-19. The remarkable similarities observed in the cytokine pathways implicated in both diseases imply the existence of shared mechanisms governing the chronic inflammatory responses characterizing these conditions. The effect of metabolic dysfunction-associated fatty liver disease (MAFLD) on the severity of COVID-19 illness remains uncertain, as indicated by conflicting results in cohort investigations.

Computer extended Descriptive Geometry (CeDG) is a new approach to solve and build computer models of three dimensional (3D) geometrical systems through descriptive geometry procedures that have demonstrated reliability and accuracy. CeDG may calculate a parametric algebraic exact form for the spatial curves generated in the intersection of two surfaces, as well as of the flattened pattern of any developable surface involved in those encounters. This study presents first the theoretical foundations and methodology to calculate those parametric algebraic curves. Secondly, a compound hopper is defined and modelled through CeDG (implemented in GeoGebra) and CAD (Solid Edge 2023) approaches to evaluate the advantages of CeDG against CAD. The results demonstrate the robustness and accuracy of the CeDG technique for surfaces intersection and flattening and the advantages of CeDG against Solid Edge 2023 in solving the hopper case study.

Postural deficits such as hyperlordosis (hollow back) or hyperkyphosis (hunchback) are relevant health issues. Diagnoses depend on the experience of the examiner and are therefore often subjective and prone to errors. Machine learning (ML) methods in combination with explainable ar-tificial intelligence (XAI) tools have proven useful for providing an objective, data-based orien-tation. However, only a few works have considered posture parameters, leaving the potential of more human-friendly XAI interpretations still untouched. Therefore, the present work proposes an objective, data-driven ML system for medical decision support that enables especially human-friendly interpretations using counterfactual explanations (CFs). Posture data for 1151 subjects were recorded by means of stereophotogrammetry. An expert-based classification of the subjects regarding the presence of hyperlordosis or hyperkyphosis was initially performed. Using a Gaussian progress classifier, the models were trained and interpreted using CFs. Label errors were flagged and re-evaluated using confident learning. Very good classification performances for both hyperlordosis and hyperkyphosis were found, whereby the re-evaluation and correction of the test labels led to a significant improvement (MPRAUC = 0.97). A statistical evaluation showed that the CFs seemed to be plausible in general. In the context of personalized medicine, the present study’s approach could be of importance for reducing diagnostic errors and thereby improving the individual adaptation of therapeutic measures. Likewise, it could be a basis for the development of apps for preventive posture assessment.

The concerning rise in emergence and prevalence of resistant strains to drugs of M. tuberculosis has ,the prompted researchers to look for new and effective treatments. With this motive, biscoumarins were identified as the lead molecules on a whole-cell-based screening of several less explored low molecular weight bioactive compounds against M. tuberculosis strains. Among the screened biscoumarins, the highest dock score derivatives were synthesized (a-h) using a programmable microwave synthesizer for better yields and reaction control. The synthesized derivatives were evaluated against H37Rv, H37Ra, M. smegmatis, an MDR surrogate model, and other bacterial strains for the structure-activity response. Assessment of the synthesized library against mycobacterial strains led to the identification of compounds (f and d) as lead anti-tuberculosis agents. Compounds (f and d) exhibited less toxicity against human cell lines. At the same time, it displayed enjoyable activity wherein MIC concentrations were observed to be 16- and 32 µg/mL against the susceptible H37Rv, and H37Ra strains of M. tuberculosis and MIC value of 128 µg/mL for M. smegmatis, respectively. For mechanistic insights and identification of drug binding targets, molecular docking and dynamic simulations were employed for a panel of 16 mycobacterial enzymes essential for mycobacterial growth and survival. These in silico studies revealed the DprE1 enzyme as a druggable target for the anti-tuberculosis activity of the selected biscoumarins derivatives. Further investigation is underway in our laboratory, leading to its development as an anti-tuberculosis drug (animal model studies).

We propose a new statistical analysis of the Acoustic Emissions (AE) produced in a series of triaxial deformation experiments leading to fractures and failure of two different rocks, namely, Darley Dale Sandstone (DDS) and AG Granite (AG). By means of q-statistical formalism, we are able to characterize the pre-failure processes in both types of rocks. In particular, we study AE inter-event time and AE inter-event distance distributions. Both of them can be reproduced with q-exponential curves, showing universal features which are observed here for the first time and could be important in order to understand more in detail rock fractures dynamics.

ChatGPT, a groundbreaking natural language processing technology released just three months ago, has attracted significant attention due to its remarkable capabilities. This AI milestone has urged researchers, industry, decision-makers, and governments to examine this technology, including its implications, threats, and benefits. Despite the short period since its release, several researchers have examined ChatGPT from different perspectives. This paper presents a comprehensive review of ChatGPT, highlighting its technical novelties compared to previous models and analyzing existing research from various perspectives. We followed a rigorous methodology to conduct a critical review of existing research on ChatGPT and developed a taxonomy for the different areas of study. Additionally, we identify future challenges and research trends associated with ChatGPT. Our paper is the first critical review of ChatGPT literature, providing valuable insights for practitioners and policymakers. This paper serves as a reference for researchers seeking to advance research on ChatGPT, including its applications and development.

Urban water management rules have long been oriented towards the rapid disposal of rainwater and wastewater through combined or separate drainage networks. This type of urban water management has shown its limits in both developed and undeveloped countries, notably because of its inexorable degradation over time and the cost of its rehabilitation and adaptation to the increase in demand due to urban growth. Sanitation data from the Office Nationale de l’Assainissement du Sénégal. Rainfall data are processed and analyzed to describe the current situation and how variable and high rainfall affects the neighborhood. Approximately 70-92% of the Dakar region's inhabitants have on-site sanitation facilities and sufficient income makes it difficult to manage their wastewater without exposing the environment or the health of citizens. The volumes of domestic wastewater flowed into the environment, in addition to poorly evacuated rainwater, show that the current sanitation system in the Dakar region is largely outdated, and insufficient for an effective drainage of rainwater and wastewater. Increasingly, frequent flash floods of polluted storm water from large amounts of domestic sewage are occurring, resulting in damage to human health. Exceptionally high rainfall is in correlation with high daily rainfall, therefore in recent years daily rainfall higher than 100 mm have been recorded in connection with above-average annual rainfall. That increase in rainfall disrupts the drainage of wastewater in the region of Dakar. A pragmatic and voluntary policy based on the principles of ecohydrology to recreate natural areas will be the only way for Dakar to efficiently manage storm water and wastewater. It can bring Dakar in 2030 into the international group of sustainable green cities.

In the recent years, biochar has emerged as a remarkable biosourced material for addressing global environmental, agricultural, biomedical, and energy challenges. However, the performances of biochar rest in part on finely tuning its surface chemical properties, intended to obtain specific functionalities. In this review, we tackle surface treatment of biochar with silane and other coupling agents such as diazonium salts, titatantes, ionic/non-ionic surfactants, as well as nitrogen-containing (macro)molecules. We summarize the recent progress achieved mostly in the last five years, and correlate the nature and extent of functionalization to eye catchy end applications of the surface engineered biochar.

Traditional dry fermented meat products are obtained artisanally in many countries, where they represent a gastronomic heritage well distinguished from industrial counterparts. This food category is most often obtained from red meat, a food commodity that is under attack because of evidences of increased risk of cancer and degenerative diseases with high consumption. However, traditional fermented meat products are intended for moderate consumption and gastronomic experience and, as such, their production must be continued also to safeguard culture and economy of the geographical areas of origin. In this review, the main risks attributed to these products are considered and how these risks are minimized by following precise production norms, respectful of the ancient manufacturing processes is described. Moreover, results obtained in studies reporting use of autochthonous microbial cultures of lactic acid bacteria (LAB), coagulase negative staphylococci (CNS), Debaryomyces hansenii and Penicillium nalgiovense to improve safety and quality of traditional fermented meats are summarized. The role of these products as a source of microorganisms that can be beneficial to the host are also considered. From the results of the studies reviewed here it appears that the development of autochthonous cultures for these foods ensure safety and stabilize sensory characteristics with possibility to be extended to the large variety of traditional productions.

The winged bean is an underutilized legume that has the potential to contribute to nutrition and food security globally, especially in sub-Saharan Africa (SSA). However, very little research attention is paid to exploiting its full potential due to a lack of adequate knowledge of the existing genetic diversity in the available winged bean germplasm. To bridge this gap, seed morphometric and selected agro-morphological traits which are crucial for yield and seed quality determination in crop plants were used to assess the genetic diversity of thirty accessions of winged bean sourced from the Gene bank of the International Institute of Tropical Agriculture (IITA), Ibadan. The thirty winged accessions were evaluated under field trials at three agro-ecological zones in Nigeria. The agro-morphological data as well as the seed morphometric dataset obtained from a Multi-Spectral Imaging (MSI) system were subjected to Analysis of Variance (ANOVA), Principal Component (PC) analysis, cluster analysis, and correlation analysis. Significant differences (p &lt; 0.05) were observed among the accessions for all measured traits. The first three PCs accounted for 93% of the variation observed among the accessions for all measured traits. Accessions were grouped into three clusters based on the agro- morphological traits and three clusters under the MSI system. Seed yield per plant had the highest estimates of significant positive correlation with hundred seed weight, pod weight per plant, etc. at both phenotypic and genotypic levels. TPt-31 had the highest seed yield per plant, pod weight per plant, and early maturity while TPt-7 had an extended flowering and maturity period, the highest number of pods per peduncle and pods per plant as well as the lowest seed yield. These accessions could serve as a good resource for future winged bean improvement programs. The result also confirmed that the MSI system is an invaluable tool for discriminating among accessions of the same crop species.

From the merge of arts and crafts towards a practice for mass production of desirability, consumption and product development in a capitalist economy of scale, design has lost its natural ability of problem comprehension and tension alleviation. The modern world needs the creativity, flexibility, and responsiveness embedded into design practices, mostly when a behavioural change, either individual or organizational, is intended. Still, the informality nature of the field is creating a gap between the study, research, and industrial design practice. Here it is presented the Biology of Creativity Model (BoC) which is a design-by-analogy method that promotes an empowered design practice through analysis of mostly biology reference texts for enhanced creativity and innovation performance in a diverse array of contexts.

This paper explores how Artificial Intelligence (AI) can help reduce the communication gap and streamline the distribution of resources. It uses an exploratory case study to examine the current state of the communication gap and the potential opportunities AI can bring to close it. The paper will discuss the current state of the communication gap, the current methods of resource distribution, and the potential opportunities AI can bring to reduce the communication gap. It will also explore the potential implications of AI on resource distribution and the communication gap. The paper will review the existing literature on the communication gap, resource distribution, and AI. It will then focus on the opportunities AI can bring to the communication gap. It will analyze the use of machine learning, natural language processing, and other AI-based technologies to reduce the communication gap. It will also examine the potential implications of AI on resource distribution, such as developing more efficient distribution channels, increasing transparency, and reducing costs. Finally, the paper will analyze the impact of AI on the communication gap and resource distribution. It will discuss the potential challenges and benefits of using AI, such as the need for data security, the potential for bias, and the limitations of AI technology. The paper will also explore the potential for AI to improve the distribution of resources and reduce the communication gap. Overall, this paper provides an exploratory case study on the opportunities of how AI can contribute to reducing the communication gap and streamlining the distribution of resources. It discusses the potential implications of AI on the communication gap and resource distribution, and it reviews the potential challenges and benefits of using AI. The paper provides an in-depth analysis of the potential opportunities of using AI to reduce the communication gap and streamline the distribution of resources.

The celebrated geodesic congruence equation of Raychaudhuri, together with the resulting singularity theorems of Penrose and Hawking that it enabled, yield a highly general set of conditions under which a spacetime (or, more generically, a pseudo-Riemannian manifold) is expected to become geodesically incomplete. However, the proofs of these theorems traditionally depend upon a collection of assumptions about the continuum spacetime (and, in the physical case, the stress-energy distribution defined over it), including its global structure, its energy conditions, the existence of trapped null surfaces and the various volume/intersection properties of geodesic congruences, that are inherently difficult to translate to the case of discrete spacetime formalisms, such as causal set theory or the Wolfram model. Some, such as the discrete analog of Raychaudhuri's equation for the volumes of geodesic congruences, are subtle to formulate due to intrinsic differences in the behavior of discrete vs. continuous geodesics; for others, such as the definition of a trapped null surface, no appropriate translation is known for the general discrete case due to a lack of a priori coordinate information. It is therefore a non-trivial question to ask whether (and to what extent) there exist equivalently general conditions under which one expects discrete spacetimes to become geodesically incomplete, and how these conditions might differ from those in the continuum. This article builds upon previous work, in which the conformal and covariant Z4 (CCZ4) formulation of the Cauchy problem for the Einstein field equations, with constraint-violation damping, was defined in terms of Wolfram model evolution over discrete (spatial) hypergraphs for the case of vacuum spacetimes, and proceeds to consider a minimal extension to the non-vacuum case by introducing a massive scalar field distribution, defined in either spherical or axial symmetry. Under appropriate assumptions, this scalar field distribution admits a physical interpretation as a collapsing (and, in the axially-symmetric case, uniformly rotating) dust, and we are able to show, through a combination of rigorous mathematical analysis and explicit numerical simulation, that the resulting discrete spacetimes converge asymptotically to either non-rotating Schwarzschild black hole solutions or maximally-rotating (extremal) Kerr black hole solutions, respectively. Although the assumptions used in obtaining these preliminary results are very strong, they nevertheless offer hope that a more general, perhaps ultimately ``Penrose-like'', singularity theorem may be provable in the discrete spacetime case too.

University course scheduling (UCS) is one of the most important and time-consuming issues that all educational institutions face yearly. Most of the existing techniques to model and solve UCS problems have applied approximate methods, which are different in terms of efficiency, performance, and optimization speed. Accordingly, this research aims to apply an exact optimization method to provide an optimal solution to the course scheduling problem. In other words, in this research, an integer programming model is presented to solve the USC problem. In this model, hard and soft constraints include the facilities of classrooms, courses of different levels and compression of students' curriculum, courses outside the faculty and planning for them, and the limited time allocated to the professors. The objective is to maximize the weighted sum of allocating available times to professors based on their preferences in all periods. To evaluate the presented model's feasibility, it is implemented using the GAMS software. Finally, the presented model is solved in a larger dimension using a real data set from a college in China and compared with the current program in the same college. The obtained results show that considering the mathematical model's constraints and objective function, the faculty courses' timetable is reduced from 4 days a week to 3 working days. Moreover, master courses are planned in two days, and the courses in the educational groups do not interfere with each other. Furthermore, by implementing the proposed model for the real case study, the maximum teaching hours of the professors are significantly reduced. The results demonstrate the efficiency of the proposed model and solution method in terms of optimization speed and solution accuracy.

A total internal reflection photonic crystal fiber (PCF) based on hexagonal core is proposed for gas sensing in a specific wavelength range. The higher sensitivity and lower confinement loss were realized by the structure of the proposed PCF consists of two layers with circular holes rotated hexagonally around a core region and six slotted air-hole in the cladding based on numerical analysis. The simulation results show that the enhancement of the relative sensitivity has been done by enhancing the diameter of the hexagonal shape air-hole cladding (d1) and the hexagonal arranged holes around the central solid core (d0) in this design. Also, the confinement loss has been reduced by enhancing the ratio of length to width of slotted holes (l/w) and decreasing the cladding air-hole diameters (d1). As the refractive index increases, the wavelength shifts toward the long wavelength. And in a certain temperature range, the transmission characteristics of the device does not change with the temperature. The results are helpful for designing high performance PCF for gas sensing applications.

Employing data supplied by the Oxford-based UK Childhood Cancer Research Group in 2003 it is shown that after the Chernobyl accident, childhood leukemia by single age and year of birth in the 0-4y cohort increased significantly in Wales and Scotland combined in the period 1986-1990 compared with controls born 1970-1985 and 1991-1994. Relative risk RR = 1.41; 95% CI 1.20<RR<1.65; p = 0.00004. These exposure periods were chosen because whole body Caesium-137 monitoring had demonstrated that internal exposures persisted for more than 4 years. The dose-response exhibits saturation and reversal, interpreted as biological censoring effects in the developing individual.

In the East, it has already become a tradition to prepare dry powdered seasonings from the fruits of the sumac plant (Rhus coriaria L.). In this work, we tested their processing by extraction. Sumac was collected in mid-September in a mountain forest near the village of Gezik (Guba, Azerbaijan). Before extraction, it was first dehydrated in a drying cabinet SH-DO-149 FG (Southern Bark) to an air-dry state; then crushed in a Tube Mill control mill (Germany) into pieces of 1-3 mm in size. One- and two-stage maceration extraction was tested together with water or acidified water at temperatures from 20 to 80 °C. Evaporation of primary extracts was carried out in a rotary evaporator Lab Rot 2 L (China). The concentration of coloring substances in the extract (in units of optical density) was used as an output parameter. It was found that the use of two-stage extraction and acidified water with a concentration of citric acid 0.3 g/cm³ contributes to the extraction of the maximum amount of coloring substances and increases the transparency of the resulting extracts, which allows the extracted extracts to be concentrated directly to obtain a new type of natural food dye. The involvement of sumac fruits in industrial processing will increase the need for these medicinal fruits, and this, in turn, will serve as an incentive for the introduction of this medicinal plant into culture.

Background: Free-living amoebas (FLA), also amebas, are eukaryotic and mitochondrial microorganisms that are capable of growing in any environment, aquatic or terrestrial. These free-living amoebas are mostly non-pathogenic to humans. However, there exist some highly pathogenic species, such as Acanthamoeba — mainly T-4 genotype —, Naegleria fowleri (known as brain-eating amoeba), and Balamuthia mandrillaris. They can be called "brain-eating amoebas” because of their ability to cause substantial destruction of brain tissue. There is no standard treatment; immunological processes which predispose humans to acquire and infection and, then, a disease are unknown. In addition, there are other species of free-living amoebas such as, Sappinea pedata, Vermamoeba vermiformes, Vanellas sp,Vahlkampfia sp., and, more recently, Paravahlkampfia francinae, which is less virulent and aggressive than the first three mentioned above. Methods: All CSF samples were evaluated in our laboratory under the microscope. Monoxenic and axenic cultures were negative as well as the presence of cysts or exponential growth. PCR was negative using the FLA primers. Results: Under close observation of sterile CSF, we can see mobile forms of non-human cells. None of the observed forms has the morphotype of Acanthamoeba, Naegleria sp. or Balamuthia mandrillaris. Conclusions: Due to these findings, we know these structures can be observed in the CSF and many of them do not form cysts as others do. In addition, these microorganisms are uncultivable in conventional medium culture to FLA and impossible to detect even when using molecular tools such as PCR, using the primers for EUK A/B or 18s RNAr gene as a target.

Wound healing is a process through which skin maintains itself. Once a wound occurs, the inflammatory and proliferative stages are instigated in reaction to injury. It is established that wound restorative comprises four stages including haemostasis, inflammation, proliferation, and remodeling. The amelioration of wound healing is very challenging as tumors can develop at the site of chronic injury. There are numerous plants, plant extracts and plant based natural products were widely used by tribal communities from ancient times for the treatment of cuts, burns, scars, burns and wounds. The therapeutic potential of these plants is recognized due to the presence of phytomolecules such as phenolic compounds, flavonoids, triterpenoids, saponins, tannins, alkaloids and glycosides. The plant used for the treatments of wound healing includes Achillea millefolium, Andrographis paniculata, Boswellia sacra, Calendula officinalis, Crocus sativus, Curcuma longa, Ehretia laevis, Ehretia microphylla, Glycyrrhiza glabra, Malva sylvestris, Rosmarinus officinalis and Salvia officinalis. This assemblage comprises the structures of phytomolecules isolated from the different extracts of these plants, mechanistic insights and important key findings responsible for wound healing. The mechanistic insights involved in wound healing are similar to cytotoxic, anti-inflammatory and antioxidant agents such as ROS generation, DNA fragmentation and western blotting. This review article is an effort to bridge the gaps in the prevailing literature and thus offers gigantic scope for researchers and academicians betrothed in validation of the customary claims and development of safer and efficient and worldwide recognized natural potential candidates as drugs for healing of wounds, burns and cuts.

In recent decades, the Variational AutoEncoder (VAE) model has shown good potential and capabilities in image generation and dimensionality reduction. The combination of VAE and various machine learning frameworks has also worked effectively in different daily life applications, however its possibility and effectiveness in modern game design has seldom been explored nor assessed. The use of its feature extractor for data clustering was minimally discussed in literature neither. This paper first attempts to explore different mathematical properties of the VAE model, in particular, the theoretical framework of the encoding and decoding processes, the possible achievable lower bound and loss functions of different applications; then applies the established VAE model into generating new game levels within two well-known game settings; as well as validating the effectiveness of its data clustering mechanism with the aid of the Modified National Institute of Standards and Technology (MNIST) database. Respective statistical metrics and assessments were also utilized for evaluating the performance of the proposed VAE model in aforementioned case studies. Based on the statistical and spatial results, several potential drawbacks and future enhancement of the established model were outlined, with the aim of maximizing the strengths and advantages of VAE for future game design tasks and relevant industrial missions.

The frequency of non-alcoholic fatty liver disease (NAFLD) has exacerbated setting diagnostic challenges, which increases the need for reliable non-invasive diagnostic tools. Due to the importance of gut-liver axis in the progression of NAFLD, studies try to reveal microbial signatures in NAFLD, evaluate them as diagnostic biomarkers and to predict the disease progression. The gut microbiome affects human physiology by processing the ingested food to bioactive metabolites. These molecules can penetrate the portal vein and the liver to promote or prevent hepatic fat accumulation. Here findings of human fecal metagenomic and metabolomic studies in relation to NAFLD are reviewed. The studies present mostly distinct and even contradictory findings on microbial metabolites and functional genes in NAFLD. The most reproducing microbial biomarkers are increased lipopolysaccharides and peptidoglycan biosynthesis, enhanced degradation of lysine, increased levels of branched chain amino acids as well as altered lipid and carbohydrate metabolism. Among other causes, the discrepancies between the studies may be related to the obesity status of the patients and severity of NAFLD. In none of the studies except one, diet was considered, though it is an important factor driving the gut microbiota metabolism. The future studies should consider diet in the analyses.

Background and Purpose: Open-source Artificial intelligence (AI) applications are fast transforming access to information and allow students to prepare assignments and offer quite accurate responses to a wide range of exam questions which are routinely used in assessments of students across the board including undergraduate dental students. This study aims to evaluate the performance ChatGPT, an AI-based application, on a wide range of dental assessments and discusses the implications for undergraduate dental education. Methods: This was an exploratory study investigating the accuracy of ChatGPT to attempt a range of recognized assessments in undergraduate dental curricula. ChatGPT was used to attempt ten items based on each of the five commonly used question formats including single-best answer (SBA) multiple-choice questions (MCQs); short answer questions (SAQs); short essay questions (SEQs); True/False questions and fill in the blanks items. In addition, ChatGPT was used to generate reflective reports based on multisource feedback (MSF); research methodology; critical appraisal of the literature. Results: ChatGPT application provided accurate responses to majority of knowledge-based assessments based on MCQs, SAQs, SEQs, Tue/False and fill in the blanks items. However, it was only able to answer text-based questions and did not allow processing of questions based on images. Responses generated to written assignments were also of good quality apart from those for critical appraisal of literature. Word count was the key limitation observed in outputs by ChatGPT as it was only able to produce reports limited to approximately 650 words. Conclusion: Notwithstanding their current limitations, AI-based applications have the potential to revolutionize virtual learning. Instead of treating it as a threat, dental educators need to adapt teaching and assessments in dental education to the benefits of the learners whilst mitigating against dishonest use of AI-based applications.

Passive dynamics is an aspect of locomotion which is entirely dependent on the mechanical configuration and linkages of adjacent body segments. Tension distribution along mechanical linkages enables execution of movement patterns with reduced need for complex neurological pathways and may play a role in reestablishing postural stability following external disturbances. Here we demonstrate a uni-directional mechanical relationship between the equine forelimb, head and neck, which may have implications for balance and forelimb loading in the horse. These observations suggest that forelimb, head and neck movement coordination (observed in the horse during unrestrained locomotion) is largely controlled by the mechanical linkages between body segments, rather than being entirely dependent on neurological input as previously thought. This highlights the potential significance of research directed at investigating passively induced movements in understanding common locomotory patterns. Additionally, it suggests a mode of postural control which may provide instantaneous adjustments to postural disturbances, thus promoting rapid and efficient locomotion.

Background: Pregnancy can be a period of increased psychological susceptibility for women living with HIV. This study aimed to determine the prevalence and factors associated with depression and psychological stress among women living with HIV during their perinatal period in Ibadan, Nigeria. Methods: This study was a facility-based cross-sectional survey conducted in three HIV treatment centers. The study population consisted of women living with HIV 18 years and above who were pregnant or had given birth within the last two years. Data obtained were analyzed using Statistical Package for Social Science version 25. Results: A total of 402 participants were eligible for this study. About 69.0% and 78.0% of the participants were depressed and had perceived stress respectively. Women who had positive partners (OR=0.60, 95% CI=0.20-1.30) were found to be significantly associated with perceived depression. Women who reported having a gestational age between 29-40 weeks (OR=0.054 95% CI = 0.006, 0.500) were found to be significantly associated with perceived stress. Factors associated with the co-occurrence of symptoms of depression and perceived stress were partner status, income level, family support, gestational age, and years on ART. Conclusions: Given the high prevalence of major depression, perceived stress, and the co-occurrence of depression and perceived stress among women living with HIV, mental health care should be incorporated into the routine maternal healthcare for all women, especially those living with HIV.

The Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) first emerged in 2019 in China and has resulted in millions of human morbidities and mortalities across the globe. It has been shown that this novel virus originated in animals, mutated, and made the cross-species jump to humans. At the time of this communication, the Coronavirus disease (COVID-19) may be on way to an endemic form, however the threat of the virus is more for susceptible (older people and immunocompromised) people. The human body has more bacterial cells than its own, thus making us more bacterial than humans. As a consequence, the bacteriomes in the human body heavily influence human health and disease. The bacteriomes in the body and the immune system seem to be in constant association during bacterial and viral infections. In this review, we identify various bacterial spp. in major bacteriomes (oral, nasal, lung, and gut) of the body in healthy humans and compare them with dysbiotic bacteriomes of COVID-19 patients. We try to identify key bacterial spp. that have a positive effect on the functionality of the immune system and human health. These select bacterial spp. could be used as potential probiotics to counter or prevent COVID-19 infections. In addition, we try to identify key metabolites produced by probiotic bacterial spp. that could have potential anti-viral effects against SARS-CoV-2. These metabolites could be subject to future therapeutic trials to determine their anti-viral efficacy.

This study was performed to synthesize multimodal radiopharmaceutical designed for the diagnosis and treatment of prostate cancer. To achieve this goal, Super Paramagnetic Iron Oxide (SPIO) nanoparticles were used as a platform for targeting molecule (PSMA-617) and for complexation of two scandium radionuclides, 44Sc for PET imaging and 47Sc for radionuclide therapy. TEM and XPS images showed that the Fe3O4 NPs have a uniform cubic shape and a diameter from 38 to 50 nm. The Fe3O4 core are surrounded by SiO2 and an organic layer. The saturation magnetization of the SPION core was 60 emu/g. However, coating the SPIONs with silica and polyglycerol reduces the magnetization significantly. The obtained bioconjugates were labeled with 44Sc and 47Sc, with a yield higher than 97%. The radiobioconjugate exhibited high affinity and cytotoxicity towards the human prostate cancer LNCaP (PSMA+) cell line, much higher than for PC-3 (PSMA-) cells. High cytotoxicity of the radiobioconjugate was confirmed by radiotoxicity studies on LNCaP 3D-spheroids. In addition, the magnetic properties of the radiobioconjugate should allow for its use in guide drug delivery driven by magnetic field gradient.

This paper aims to list the current challenges in the study of Sports Medicine in Brazil based on a review of the literature and the author's experience as a member of a transdisciplinary team in this field, as well as to discuss methods for establishing an appropriate and organized course of health activities in this context. The authors identified four significant contemporary difficulties in the field of sports medicine in Brazil that, while minor, are complicated. There is a need to publish a greater number of national studies, generate integrated knowledge through transdisciplinary research, propose sports and movement as a tool for the prevention of degenerative conditions, and research and develop better therapeutic options through transdisciplinary research. It is expected that a transdisciplinary approach will reduce divergences between the real world and science, putting an end to dogmatism, prejudice, and theoretical thinking, increasing the scientificity of sports, bringing competitive advantages, improving training, performance, and athlete health management, and contributing to the advancement of sports medicine.

The 3x+1 problem asks the following: Suppose we start with a positive integer, and if it is odd then multiply it by 3 and add 1, and if it is even, divide it by 2. Then repeat this process as long as you can. Do you eventually reach the integer 1, no matter what you started with? Collatz conjecture (or 3n+1 problem) has been explored for about 85 years. In this paper, we convert an integer number from decimal to binary number, and convert the Collatz function to binary function, which is multiplication and division of two binary numbers. Finally the iternation of the Collatz function, eventually reach the integer 1, thus we solve the 3x+1 problem completely.

The uniqueness of each system stems from the fact that the risks of disasters are specific and that their presence and manifestation are not universal and the same for every country. Just as no country is the same in all other segments, their disaster risk management systems are unequal. The paper describes the systems in four different countries, through observation and comparison of four areas of activity that are implemented in dealing with disasters. First of all, in the paper, the legal basis and institutional frameworks on which these systems rest in each of the countries were considered – starting from the international level and guidelines given at international conferences, to all by-laws and local disaster activity plans. It was considered how each of the states implements risk mitigation activities and how it increases preparedness for them. When the system recognizes risks, their probability and the frequency of their occurrence, activities are planned to prepare the country and every individual in it for a potentially unwanted event. Differences in the ways of mitigating risks and preparing all elements of the system and protected values for disasters are presented. The third element of action in the event of disasters concerns the response. In this segment, questions are raised regarding institutional solutions in the system, division of responsibilities, the priority of response and mobilization of resources at all levels. The last phase, the one that occurs after the disaster, and that is the recovery from it, depends on the reaction. In the paper, it was discussed how in the end, when a disaster occurs and when damage to the population, environment, material and other goods occurred, how each of the states implements reconstruction, i.e. how it recovers - whether that recovery was previously well planned or whether ad hoc solutions are applied.

With the rapid development of the Internet industry, the problem of information overload has arisen due to the abundance of information available online. Recommendation algorithms, as the core of recommendation systems, have been attracting much attention and are a hot topic of research for many experts and scholars. The classical recommendation algorithms are mainly divided into three major categories: collaborative filtering recommendation algorithms, content-based recommendation algorithms, and hybrid-based recommendation algorithms. Although these algorithms are widely used in various fields, with the proliferation of information, these traditional recommendation algorithms are no longer able to meet the needs of the times. To address this issue, recommendation systems have been developed to provide users with personalized and relevant information or products. Despite the wide use of recommendation algorithms, such as collaborative filtering, content-based filtering, and hybrid approaches, traditional recommendation algorithms have limitations and are no longer suitable for meeting the demands of the times. This paper proposes a new recommendation algorithm, SFRRG, that fuses structure and feature information in graph neural networks to improve the performance of the recommendation system in rating prediction. The effectiveness of the proposed algorithm is demonstrated through experiments on various data sets and compared with existing recommendation algorithms.

This article proposes the use of intranasal rifampin as a means to improve protein homeostasis and disaggregate misfolded proteins in the age-related neurodegenerative proteinopathies. Alzheimer’s disease, Parkinson’s disease, multi-system atrophy, Lewy body dementia, frontotemporal dementia, amyotrophic lateral sclerosis and Huntington’s disease are all, at the core, proteinopathies. Although these diseases varying greatly in the specific disease-associated proteins, anatomic sites of the abnormal protein deposition and clinical presentations, what they have in common is disruption of normal “housekeeping” functions related to protein homeostasis, proteostasis. The prospect of pharmacologically augmenting autophagic capacity with a known drug repurposed to improve proteostasis is attractive; to accomplish these ends with an inexpensive drug with relative ease of delivery adds to the attractiveness. Rifampin can be delivered to the brain via the intranasal route. Rifampin has been used for decades primarily against mycobacterial infection; it has been given with intravenous, oral, intrathecal and topical routes including as eyedrops and nasal spray. Rifampin disaggregates toxic oligomers in vitro; given intranasally, rifampin improves memory and clears pathologic proteins in animal models of the proteinopathies. Rifampin acts as both a gatekeeper and a housekeeper against the abnormal proteins of these diseases. This article suggests the merit of a clinical trial with intranasal rifampin to boost protein homeostasis in the most common age-related neurodegenerative proteinopathy, Alzheimer’s disease. The primary outcome of such a trial is change in risk of Alzheimer’s pathology as measured by plasma-based amyloid peptide 42/40 testing pretreatment and follow-up testing after 6 months of intranasal rifampin.

Purpose: Physical activity (PA) is likely the most important modifiable element for the growth of skeletal muscle. However, a detailed investigation of PA’s impact on preschoolers’ of skeletal muscle development is lacking. This study aimed to determine whether PA level is related to skeletal muscle thickness among preschool children. Methods: 275 healthy preschoolers between the ages 4–6 were instructed to wear an accelerometer for 4 consecutive days. The daily steps and minutes spent in moderate-to-vigorous PA (MVPA) and total PA (TPA) were examined. Muscle thickness (MT) was measured by B-mode ultrasonography. The MT was measured at the anterior (AT) and posterior thigh (PT) and the anterior (AL) and posterior lower leg (PL). Results: Boys were more physically active and engaged in significantly more TPA and MVPA on weekdays compared with girls. Compared with that on the weekends, more physical activity, and significantly greater number of daily steps and higher TPA and MVPA were recorded for both boys and girls on the weekdays. Multivariable regression analyses, after adjusting for daylight duration, indicated that a daily increase in the TPA and MVPA would lead to higher muscle size in AT (β=1.11 and β=1.37, p<0.05), and PL (β=1.18 and β=0.94, p<0.05) among preschool children. Conclusions: The time spent involved in most of the different categories of MVPA was significantly higher for boys than for girls on the weekdays and weekends. MVPA was positively correlated with greater skeletal muscle development in the lower body.

Accurate and efficient determination of excited-state polarizabilities (α) is an open problem both experimentally and computationally. Following our previous work, [Phys. Chem. Chem. Phys. 2023, 25, 2131−2141], where one can employ simple ground-state density-based functions from the information-theoretic approach (ITA) to accurately and efficiently predict the macromolecular polarizabilities, we aim to predict the lowest excited-state polarizabilities in this work. The philosophy is to use density-based functions to depict the excited-state polarizabilities. As a proof-of-principle application, employing 2-(2′-hydroxyphenyl)benzimidazole and its derivatives as model systems, we have verified that either with the ground-state (S0) or excited-state (S1) densities as input, ITA quantities can be strongly correlated with the excited-state polarizabilities. When the transition densities are considered, both S0 and S1 polarizabilities are in good relationships with some ITA quantities. Furthermore, excitation and emission energies can be predicted based on multivariant linear regression equations of ITA quantities.

Vision loss can be avoided if diabetic retinopathy (DR) is diagnosed and treated promptly. Following are the main 5 DR stages: none, moderate, mild, proliferate, and severe. In this study, a deep learning (DL) model is presented that diagnoses all 5 stages of DR with more accuracy than previous methods. The suggested method presents two scenarios: case 1 with image enhancement using contrast limited adaptive histogram equalization (CLAHE) filtering algorithm in conjunction with an Enhanced Super-resolution generative adversarial network (ESRGAN), and case 2 without image enhancement; augmentation techniques are then performed to generate a balanced dataset utilizing the same parameters for both cases. Using Inception-V3 applied to the Asia Pacific Tele-Ophthalmology Society (APTOS) datasets, the developed model achieved an accuracy of 98.7% for case 1 and 80.87% for case 2, which is greater than existing methods for detecting the five stages of DR. It was demonstrated that using CLAHE and ESRGAN improves a model's performance and learning ability.

The sudden outbreak of the COVID-19 pandemic challenged education systems worldwide to quickly pivot their teaching-learning processes from in-person to virtual modes in order to control the spread of the virus. In a short period of time, teachers were forced to adopt new remote teaching methods to ensure the continuation of education. This paper examines how teachers in Pakistan leveraged mobile technology as an alternative teaching strategy to provide access to education during these unprecedented times. Through in-depth individual interviews with selected teachers, the study explores the potential of mobile technology to transform traditional teaching methods into interactive learning environments. The findings highlight the importance of embracing new pedagogical possibilities offered by mobile technology and the need for effective teacher professional development in the post-pandemic era. The study offers valuable insights into how mobile technology can be effectively utilized in education, even in the most challenging circumstances.

Free-living terrestrial mites (Acari) have persisted through numerous glacial cycles in Antarctica. Very little is known, however, of their genetic diversity and distribution, particularly within the Ross Sea region. To redress this gap, we sampled for mites throughout the Ross Sea region, East Antarctica, including Victoria Land and the Queen Maud Mountains (QMM), covering a latitudinal range of 72-85oS, as well as from Lauft Island near Mt Siple (73oS) in West Antarctica and Macquarie Island (54oS) in the sub-Antarctic. We assessed genetic diversity using mitochondrial cytochrome c oxidase subunit I gene sequences (COI-5P DNA barcode region), and also morphologically identified voucher specimens. We obtained 130 sequences representing four genera: Nanorchestes (n = 30 sequences), Stereotydeus (n = 46), Coccorhagidia (n = 18) and Eupodes (n = 36). Tree-based analyses (maximum likelihood) revealed 13 genetic clusters, representing as many as 23 putative species indicated by Barcode Index Numbers (BINs) from the Barcode of Life Datasystems (BOLD) database. We found evidence for geographically-isolated cryptic species, e.g. within Stereotydeus belli and S. punctatus, as well as unique genetic groups occurring in sympatry (e.g. Nanorchestes spp. in QMM). Collectively, these data confirm high genetic divergence as a consequence of geographic isolation over evolutionary timescales. From a conservation perspective, additional targeted sampling of understudied areas in the Ross Sea region should be prioritised, as further diversity is likely to be found for these short-range endemic mites.

Background: Chronic Back Pain due to Facet Joint Syndrome is a common and debilitating con-dition. Advances in regenerative medicine have shown that Autologous Unmodified Adipose Tissue-Derived Regenerative Cells (ADRC) provide several beneficial effects [1,2]. These regen-erative cells can differentiate into various tissues [3] and exhibit a strong anti-inflammatory po-tential. ADRCs can be obtained from a small amount of fatty tissue derived from the patient´s abdominal fat. Methods: We report long-term results of 37 patients (age 31-78 years, mean 62.5) suffering from “Facet Joint Syndrome” The pathology was confirmed by clinical, radiological examinations and fluoroscopically guided test injections. Then liposuction was performed. 50-100 cc of fat were harvested. To recover stem cells from adipose tissue, we use the CE-certified Transpose RT™ system from InGeneron GmbH. The cells were then injected under fluoroscopic control in the periarticular fat. Follow-up examinations were performed at one week 1 and 5 years. Results: Every patient reported improved VAS pain at any follow-up (1 week, 1, and 5 years) with ADRCs compared to the baseline. Conclusion: Our observational data indicate that facet joint syndrome patients treated with unmodified adipose tissue-derived regenerative cells experience improved quality of life in the long term.

The cattle sector is strategic sector for both the economic development and food security of Africa. However, the low availability and quality of forage puts the most vulnerable population in the field at risk. Hybrid forages have proven to be a real alternative for enhancing both the food security and sustainability of the sector. They are the product of genetic improvements and combine the superior traits of different materials. In 1987, the International Center for Tropical Agriculture (CIAT) began this line of research and together with the private sector various ma-terials have been released until today. Despite their beforementioned potential, forage hybrid adoption levels are still low in Africa, which is related to various factors among which the availability of seeds and planting material stands out. This document analyzes the potential markets for new forage hybrids adapted to the environmental conditions of eastern Africa and partially western Africa. Likewise, an estimation of the commercial value of these markets is provided. The results show a potential market of 414,388 ha for new interspecific hybrids of Urochloa and 528,409 ha for potential hybrids of Megathyrsus maximus, with approximate values of 73.5 and 101.1 million dollars, respectively. Ethiopia, Tanzania, and Kenya have a 70% market share for Urochloa, while South Sudan, Ethiopia, and Tanzania have a 67% share for Megathyrsus maximus. The results will help different actors in decision-making, i.e., regarding private sector investments in forage seed commercialization or public sector incentives supporting adoption processes, and thus contribute to increasing food security and sustainability in the region.

Phytoseiidae inhabit a wide range of herbs, shrubs and trees. Aesculus hippocastanum is an important ornamental tree in Europe and is likely reservoir of these mites. We therefore assessed the species composition and the spatial and seasonal variability in the abundance of Phytoseiidae in city parks in South Bohemia, Czech Republic. Leaf samples were randomly collected from horse chestnut tree branches at eight sites, five times during the vegetation season in 2013. The mites were collected by washing technique and mounted on slides for identification. In total, 13,903 specimens of phytoseiid mites were found, and eight species were identified: Amblyseius andersoni, Euseius finlandicus, Kampimodromus aberrans, Neoseiulella tiliarum, Phytoseilus macropilis, Paraseiulus talbii, Paraseiulus triporus and Typhlodromus (Typhlodromus) pyri. Paraseiulus talbii and P. macropilis were recorded on the leaves of horse chestnut trees for the first time in the Czech Republic in this study. The predominant species was E. finlandicus (96.25%). The number of mites per compound leaf was, on average, 2.53, 10.40, 23.54, 11.59 and 9.27 on the sampling dates in each month between May and September, respectively. The mite density was significantly affected by the sampling site and date.

Legume seed protein is an important source of nutrition, but it is less digestible than animal protein. Poor protein digestibility in legume seeds and seedlings may partly reflect defences against herbivores. Protein changes during germination typically increase proteolysis and digestibility, by lowering the levels of anti-nutrient protease inhibitors, activating proteases, and breaking down storage proteins (including allergens). Germinating legume sprouts also show striking increases in free amino acids (especially asparagine), but their roles in host defence or other processes are not known. While the net effect of germination is generally to increase the digestibility of legume seed proteins, the extent of improvement in digestibility is species and strain dependent. Further research is needed to highlight which changes contribute the most to improved digestibility of sprouted seeds. Such knowledge could guide the selection of varieties that are more digestible, and also guide the development of food preparations that are more digestible, potentially combining germination with other factors altering digestibility, such as heating and fermentation. Techniques to characterize the shifts in protein make-up, activity and degradation during germination need to draw on traditional analytical approaches, complemented by proteomic and peptidomic analysis of mass spectrometry identified peptide breakdown products.

In this paper, we introduce the application of Type-I fuzzy inference systems (FIS) as an alternative to improve the prioritization in the FMECA analysis applied in cyber-power grids. Classical FMECA assesses the risk level through the Risk Priority Number (RPN). The multiplication between three integer numbers computes this, called risk factors, representing the severity, occurrence, and detectability of each failure mode and are defined by a team of experts. The RPN does not consider any relative importance between the risk factors and may not necessarily represent the real risk perception of the FMECA team members, usually expressed by natural language; this is the main FMECA shortcoming criticized in the literature. Our approach considers fuzzy variables defined by FMECA experts to represent the uncertainty associated with the human language and a rule base consisting of 125 fuzzy rules to represent the risk perception of the experts. To test our approach, we select a cyber-power grid previously analyzed by the authors using the classical FMECA. The results reveal our proposed fuzzy approach as promissory to represent the uncertainty associated with expert knowledge and to perform an accurate prioritization of failure modes in the context of electrical power systems.

SMEs constitute the backbone of the Syrian economy which have suffered manifold challenges due to the continuous Syrian war. Covid-19 added further pressures on Syrian SMEs and force them to take certain adaptation strategies to survive. This paper aims to investigate the main challenges that face Syrian SMEs during the pandemic and illustrate how they respond to adversities emerged from governmental intervention to control the spread of the virus. It also discusses the measures initiated by the government to support SMEs during the pandemic. Through interviewing persons from the Syrian SMEs ecosystem, we find that high interest rates on SMEs loans, decline on demand as well as high inflation represent the main challenges. SMEs respond to these challenges by marketing products online, stock procurement, and strengthen connections with stakeholders. We recommend the Syrian authorities reduce lending rates and increase loan size available to SMEs to help them overcome the pandemic adversities. Moreover, SMEs will immensely benefit from training on digital tools to enhance their expansion and survival opportunities. Furthermore, bazars should be organized around the year to give SMEs the opportunity to gain continuous access to markets. In addition, incubation services should be revised, particularly, to SMEs with great potential to grow to create the suitable environment for them to scale and flourish.

Many papers in recent years have been devoted to estimating the per pixel proportions of three broad classes of materials (e.g. photosynthetic vegetation, non-photosynthetic vegetation and bare soil) using data from multispectral sensors. Many of these papers use estimation methods based on the linear mixture model. Very few of these papers assess the accuracy of their estimators. I show how to produce confidence intervals (CIs) and joint confidence regions (JCRs) for the proportions associated with various linear mixture models. There are two main models, both of which assume that the coefficients in the model are non-negative. The first model assumes that the coefficients sum to 1. The second does not, but uses rescaling of the estimated coefficients to produce estimated proportions. Three variants of these two models are also analysed. JCRs are shown to be particularly informative, because they are typically better at localising the information than CIs are. The methodology is illustrated using examples from Landsat Thematic Mapper data at 1169 locations across Australia, each of which has associated field observations. There is also discussion about the extent to which the methodology can be extended to hyperspectral data.

In this review, we present several extracellular proteases, enzymes, membrane permeases, and transporters as essential accessories proteins for nutrient assimilation, conservation, and transportation as determined by nutrient repletion or depletion. As an obligate aerobic pathogen, it is crucial for invading Cryptococcus (C.) neoformans to negotiate its adaptation to human internal organs like the brain and spinal cord, where the oxygen level is low compared to peripheral organs. Besides, essential metals like copper and iron are important cofactors to functional proteins; however, these metals are not usually freely available to invading human pathogens. Again, the phagolysosome low pH with glucose paucity, internal temperature, immune response, and complex extracellular matrixes are challenging environments that must be circumvented by C. neoformans in the systemic tissues for survival, adaptation, and infection in humans. We review extensive works on several extracellular proteases, enzymes, membrane permeases and transporters orchestrated by different transcription factors and present these proteins as weapons needed to outwit systemic resistance to invading pathogens. Lastly, we examine the extracellular secretory vesicles of C. neoformans as “an exosomal virulence bag” that harbours urease, laccase, phosphatase, and capsular components as additional secretory weapons for tissue invasion and persistence.

As AI models become more and more common in business and even in our daily lives, it is important to understand what the carbon impact of these models is. Recent papers have shown that this impact can be quite great, i.e., the training of a single high-end model can result in emissions of more than 500t of CO2eq. In this paper we discuss the factors that influence the carbon footprint of AI models, explore what impact different decisions have, and show how the footprint can be reduced. We also examine the footprint of different models to give a guideline on how urgent action is for different organizations.

Antibiotic resistance is a major public health issue that requires a multifaceted approach. One potential source of antibiotic-resistant bacteria is wastewater in developing countries, which often lacks proper treatment infrastructure and can release high levels of antibiotics and antibiotic-resistant bacteria into the environment. This review article summarizes current knowledge on strategies to combat antibiotic resistance in wastewater in developing countries. Our review highlights the importance of improving wastewater treatment infrastructure to effectively remove antibiotics and antibiotic-resistant bacteria, implementing measures to reduce the release of antibiotics into the environment, and monitoring and surveillance to track the presence and spread of antibiotic-resistant bacteria in wastewater. We also discuss the potential challenges and barriers to implementing these strategies and the need for further research to determine their effectiveness in real-world settings. Overall, this review highlights the need for a comprehensive approach to address antibiotic resistance in wastewater in developing countries and underscores the importance of addressing this issue to protect public health.

SARS-CoV-2 resembles the ancient mythical creature Hydra. Just like with the Hydra, when one head is cut, it is followed by appearance of two more heads, suppression of one SARS-CoV-2 variant causes appearance of newer variants. Unlike Hydra that grows identical heads, newer SARS-CoV-2 variants are usually more infective, which can be observed as time evolution of the virus at hand, which occurs through acquisition of mutations during time. The appearance of new variants is followed by appearance of new COVID-19 pandemic waves. With the appearance of new pandemic waves and determining of sequences, in the scientific community and general public the question is always raised of whether the new variant will be more virulent and more pathogenic. The two variants characterized in this paper, BA.5.2 and BF.7, have caused a pandemic wave during the late 2022. This paper gives full chemical and thermodynamic characterization of the BA.5.2 and BF.7 variants of SARS-CoV-2. Having in mind that Gibbs energy of binding and biosynthesis represent the driving forces for the viral life cycle, based on the calculated thermodynamic properties we can conclude that the newer variants are more infective than earlier ones, but that their pathogenicity has not changed.

Oral health surveys are essential to assess the dental caries experience and to influence national policies. This retrospective cross-sectional study aims to analysis dental caries experience who sought dental treatment in a reference university dental hospital at the Lisbon Metropolitan Area between January 2016 and March 2020. Full-mouth examination, sociodemographic, behaviors and medical information were included. Descriptive analyses and logistic regression analysis were applied to ascertain risk indicators associated with dental caries experience. A final sample of 9,349 participants (5,592 females/3,757 males) were included, aged 18 to 99 years old. In this population, caries experience was 91.1%, higher in female participants. Age (OR= 1.01, 95% CI [1.00-1.02], occupation (OR= 2.94, 95% CI [2.37-3.65], OR= 3.35, 95% CI [2.40-4.67], OR= 2.55, 95% CI [1.66-3.91], for employed, unemployed and retired, respectively), overweight (OR= 1.52, 95% CI [1.18-1.96]), reporting to never visited a dentist (OR= 0.38, 95% CI [0.23-0.64] and self-reported week teeth status (OR= 2.14, 95% CI [1.40-3.28]) were identified as risk indicators for the presence of dental caries, according to adjusted multivariable logistic analyses. These results highlight a substantial rate of dental experience in a Portuguese cohort and will pave the way for future tailored oral public health programs in Portugal.

Chrysoeriol (CHE) is a flavonoid substance that exists in many plants and has various physiological and pharmacological effects, including anti-inflammatory, antioxidant, anti-tumor, and protective activity, especially for the cardiovascular system and liver. This study aimed to analyze the results and possible mechanisms of CHE on early porcine embryo development. Adding CHE to the culture media can improve the development quality of early porcine embryos. CHE significantly increased the blastocyst rate and total cell number of embryos in vitro. The apoptosis of blastocyst in CHE-treated culture also decreased significantly compared with untreated culture. Furthermore, CHE downregulated intracellular reactive oxygen species (ROS) and increased glutathione (GSH) in embryos. CHE was also shown to improve the activity of mitochondria and inhibit the occurrence of autophagy. In addition, antioxidant-related genes (SOD1, SOD2, and CAT) and cell pluripotency-related genes (SOX2, OCT4, and NANOG) were upregulated, while those related to apoptosis (Caspase 3) and autophagy (LC3B) showed a downward trend after supplementation with CHE. These results indicated that CHE improved the development of porcine embryos in vitro by reducing oxidative stress and autophagy levels.

Among the impacts of climate change in West Africa, coastal erosion is the most threatening disaster apart from floods and the increase in temperature. The southern coast of the Dakar region, as part of the most threatened coastal zones in West Africa, records the most current coastal damages in Dakar due to its coastline dynamics and low-lying area. This study was conducted in three littoral cells (Mbao, Bargny and Toubab Dialaw) and aims to investigate if there is a relationship between the coastline dynamic, topographic and slope and the contribution of the geomorphology along the southern coast of Dakar. It helps to understand better the role which plays the topography, Slope and geomorphology in coastal dynamics using remote sensing, cartographic tools and statistical methods. The Modified Normalized Different Water index (MNDWI) was employed to delineate the coastlines before computing the dynamic rate of the coastline using the Digital Shoreline Analysis System (DSAS) software. After that, Topography and Slope were determined using Digital Elevation Model (DEM). Then, the correlation between the coastline dynamic, topography and slope was analyzed through the coefficient of correlation and multiple linear regression model. High dynamic rates were noted in the littoral cells, where the topography and slope are low. In Mbao, there is a significant relationship between the coastline dynamic, topography and slope with a coefficient of correlation of about 0.63. In Bargny, the relationship is also significant, with a coefficient of 0.87. The relationship is not significant in Toubab Dialaw, where topography and Slope are high, with a coefficient of 0.15. We conclude that topography, slope and soil properties play an important role in the study area.

Antimicrobial peptides (AMPs) are essential components of innate immunity across all species. AMPs have become the focus of attention in recent years as scientists are addressing antibiotic resistance, a public health crisis that has reached epidemic proportions. This family of peptides are a promising alternative to current antibiotics due to their broad-spectrum antimicrobial activity and tendency to avoid resistance development. A subfamily of AMPs interact with metal ions to potentiate their antimicrobial effectiveness, as such they have been termed metalloAMPs. In this work, we review the scientific literature of metalloAMPs that enhance their antimicrobial efficacy when combined with the essential metal ion, zinc (II). Beyond the role played by Zn(II) as a cofactor in different systems, it is well-known that this metal ion plays an important role in innate immunity. Here, we classify the different types of synergistic interactions between AMPs and Zn(II) into three distinct classes. By better understanding how each class of metalloAMPs uses Zn(II) to potentiate their activity, researchers can begin to exploit these interactions in the development of new antimicrobial agents and accelerate their use as therapeutics.

Background: Diffuse glioma is a malignant human brain cancer that is hard to overcome. This represents a high risk of mortality. The current challenge is limited to the control of tumor progression and survival improvement. Immunotherapy consists of stimulating the immune system in order to eliminate the non-self-elements that damage the human body, including cancer cells. However, in human glioma, the current immunotherapeutic targets did not show significant benefit. In this study, we aimed at evaluating the expression and potential role of a new immunosuppressive molecule, TIGIT in glioma patients. Methods: A cohort of 667 patients from the TCGA database along with a cohort of 53 Moroccan patients, were analyzed in order to assess the role of TIGIT in human glioma progression and to estimate whether blocking this immune checkpoint molecule would be of a potential therapeutic benefit. Real time RT-PCR from fresh human biopsies and RNAseq data analysis were performed in this study. Results: Our results showed that high expression of TIGIT had prognostic value with some known clinical glioma risk factors such as sex, age and IDH mutation status. High expression of TIGIT was positively associated with advanced grades of glioma. Interestingly, elevated rates of TIGIT were significantly associated to elevated levels of other inhibitory immune checkpoint molecules (PD-1, VISTA and Tim-3) in human glioma patients, also TIGIT showed strong association with Treg cell-secreted cytokines (TGF-beta and IL-10), indicating the high potential involvement of TIGIT in immunosuppression in human glioma. Moreover, we reported that high TIGIT expressing CD8 T-cells displayed more surface inhibitory molecules and, elevated levels of Treg cells and FoxP3 were linked to higher rates of TIGIT, supporting the likely involvement of TIGIT in the suppression of the intra-tumoral immune cells. Finally, high expression of TIGIT was significantly linked to advanced histological subtypes of glioma and was associated with poor overall survival in human glioma. Conclusion: TIGIT blockade might be of valuable therapeutic benefit in patients with advanced glioma.

Although initially conceived for high-risk patients who are ineligible for surgical aortic valve replacement (SAVR), transcatheter aortic valve replacement (TAVR) is now recommended in a wider spectrum of indications including young patients. However, as for SAVR, TAVR is also associated with a risk of infectious complications, namely prosthetic valve endocarditis (PVE). As the number of performed TAVR procedure increases, and despite the low incidence of PVE post TAVR, clinicians should be familiar with the associated risk factors and the clinical presentation. Whereas the diagnosis of native valve endocarditis can be straightforward applying the modified Duke criteria, the diagnosis of PVE is more challenging given its atypical symptoms, lower sensitivity of the criteria, and low diagnostic yield of conventional echocardiography. Delay in proper management can be associated with increased morbidity and mortality. Therefore, clinicians should have a high index of suspicion and initiate proper work-up according to the severity of illness, the underlying host, and the local epidemiology of the causative organisms. The most common causative pathogens are Gram-positive bacteria such as S. aureus, coagulase negative staphylococci, Enterococcus spp. and Streptococcus spp. (particularly the viridans group) and, less likely Gram-negative and fungal pathogens. The high prevalence of antimicrobial resistance complicates the choice of therapy. There remain controversies regarding the optimal management strategies including indications for surgical interventions. Surgical assessment is recommended early in the course of illness and surgical intervention should be considered in selected patients. As in other PVE, duration of therapy depends on the isolated pathogen, the host, and the clinical response. Since TAVR is a relatively new procedure, the outcome of TAVR-PVE is yet to be fully understood.

Cenospheres are hollow particles in fly-ash, a by-product of coal burning, and are widely used as reinforcement for developing low density composites called syntactic foams. This study investigates the physical, chemical, and thermal properties of cenospheres obtained from 3 different sources, CS1, CS2, and CS3, for the development of syntactic foams. Description of floatation method to separate broken particles is given, and it was seen that up to 11 % of the particles were damaged. Post heat treatment samples show development of SiO2 phase in the cenosphere, which is not present in the as received product. CS3 had the highest quantity of Si element, compared to the other two, showing the difference in the source quality. The particle size distribution for CS2 is very narrow while for the others is much broader. All censopheres have porous walls but the morphology of CS2 is the most uniform and smooth. For the application of metallic layer and subsequent consolidation via spark plasma sintering, CS2 was deemed the most physically, thermally, and chemically suitable.

The novel coronavirus disease 19 (COVID-19) has resulted in an estimated 20 million excess deaths and the recent resurgence of COVID-19 in China is predicted to result in up to 1 million deaths over the next few months. With vaccines unable to halt transmission it is important to continue our quest for safe, effective, affordable drugs that will be available to all countries. Drug repurposing is one of the strategies being explored in this context. Recently, out of 7,817 approved drugs, 214 candidates were systematically down-selected using a combination of 11 filters including approval status, assay data against SARS-CoV-2, pharmacokinetic, pharmacodynamic and toxicity profiles. These drugs were subjected in this study to virtual screening against various targets of SARS-CoV-2 followed by molecular dynamic studies of the best scoring ligands against each target. The chosen molecular targets were Spike receptor binding domain, Nucleocapsid protein RNA binding domain, and key non-structural proteins 3, 5, 12, 13 and 14. Four drugs approved for other indications — alendronate, cromolyn, natamycin and treprostinil — look sufficiently promising from our in silicostudies to warrant further in vitro and in vivo investigations as appropriate to ascertain their extent of anti-viral activities.

This paper presents the experimental and numerical studies of the vertical stress distribution beneath the centerline of circular footings resting on the sand. Vertical stress values due to circular load in medium-dense sand were measured using soil stress transducers. Reduced-scale laboratory model tests were carried out in a square-shaped test box and vertical stresses were measured at the centerline of the circular footing at different depths of the sand. In order to determine the effect of footing width on vertical stress distribution, laboratory experiments were performed on circular footings of different diameters. In addition, a series of finite element analyses was carried out on the test model to validate the findings of the experimental study. In the numerical analysis, the sand was modeled as a non-linear elastoplastic material. The analyses were performed using the finite element method with two-dimensional axisymmetric and three-dimensional conditions. The results obtained from laboratory model tests and numerical analysis were compared with the vertical stress values obtained from the theoretical solution in the literature. Vertical stress distribution in horizontal planes at any depth from the footing base shows the same characteristic form in all methods. However, some differences were observed between experimental, numerical, and theoretical results and discussed.

Colonoscopy is used for colorectal cancer (CRC) screening. Extracting details of the colonoscopy findings from free text in electronic health records (EHRs) can be used to determine patient risk for CRC and colorectal screening strategies. In this study, we developed and evaluated the accuracy of a deep learning model framework to extract information for the clinical decision support system to analyze relevant free-text colonoscopy reports, including indications, pathology, and findings notes. The Bio-Bi-LSTM-CRF framework was developed using Bidirectional Long Short-term Memory (Bi-LSTM) and Conditional Random Fields (CRF) to extract several clinical features from these free-text reports, including indications for the colonoscopy, findings during the colonoscopy, and pathology of the resected material. We then trained the Bio-Bi-LSTM-CRF and existing Bi-LSTM-CRF models on 80% of 4,000 manually annotated notes obtained from the colonoscopy reports of 3,867 patients. The clinical notes were from a group of patients aged over 40 years old enrolled in four Veterans Affairs Medical Centers. A total of 10% of the remaining annotated notes were used to train hyperparameter, while the remaining 10% were used to evaluate the accuracy of our model (Bio-Bi-LSTM-CRF) and to compare the results with the outcomes obtained using Bi-LSTM-CRF. The results of our experiments showed that the bidirectional encoder representations by integrating dictionary function vector from Bio-Bi-LSTM-CRF and strategies character sequence embedding approach is an effective way to identify colonoscopy features from EHR-extracted clinical notes. Therefore, the Bio-Bi-LSTM-CRF model is concluded to be capable of creating new opportunities to identify patients at risk for colon cancer and to study their health outcomes.

Child sexual abuse inflicts lifelong devastating consequences for victims and is an ongoing social concern. In most countries, child sexual abuse material (CSAM) distribution is illegal. As a result, there are many research papers in the literature which proposed technologies to detect and investigate CSAM. In this survey, a comprehensive search of the peer-reviewed journal and conference paper databases (including preprints) is conducted to identify high-quality literature. We use the PRISMA methodology to refine our search space to 2,761 papers published by Springer, Elsevier, IEEE and ACM. After iterative reviews of title, abstract and full text for relevance to our topics, 43 papers are included for full review. Our paper provides a comprehensive synthesis of the tasks of the current research and how the papers use techniques and datasets to solve their tasks and evaluate their models. To the best of our knowledge, we are the first to focus exclusively on online CSAM detection and prevention with no geographic boundaries, and the first survey to review papers published after 2018. It can be used by researchers to identify gaps in knowledge and relevant publicly available datasets that may be useful for their research.

Magnetoelectric (ME) sensor is a new type magnetic sensor with ultrahigh sensitivity, low power consumption, and suitable for the measurement of low frequency weak magnetic field. In this study, metglas/PZT-5B ME sensor with a mechanical resonance frequency f_res of 60.041 kHz was prepared. It is interesting to note that its magnetic field resolution reaches 0.20 nT at f_res and 0.34 nT for DC field, respectively. In order to measure the ultralow frequency AC magnetic fields, a frequency upconversion technique was employed. Under this technique, a limit of detection (LOD) of AC magnetic field lower than 1 nT at 8 Hz is obtained, and the minimum LOD of 0.51 nT is achieved at 20 Hz. The high resolution ME sensor with sub-pT level is promising in the field of low frequency weak magnetic field measurement technology.

Since the beginning of 2020, tetracycline (TC), such as minocycline (MINO), has been used to inhibit coronavirus disease 2019 (COVID-19). Traditional Japanese Kampo medicine, such as Saiko-keishi-to (SKT), has recently received a lot of attention for its anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) effects. We describe a COVID-19 patient treated with MINO and SKT in anticipation of their anti-SARS-CoV-2 properties. A 90-year-old male patient with Alzheimer’s disease was referred to a medical clinic due to fever, appetite loss, and general malaise. Based on positive SARS-CoV-2 rapid antigen tests, he was diagnosed with COVID-19. He did not have COVID-19 pneumonia, but he had difficulty in eating on his own. As a result, he was referred to a hospital for admission. After admission, he was treated with molnupiravir to avoid aggravation. Seven days after his admission, he was discharged. After his discharge, he was referred to our hospital as an outpatient due to a prolonged mild fever and general malaise. As a precaution, a real-time reverse transcription-polymerase chain reaction (RT-PCR) test was performed, which yielded a positive result. Therefore, the aforementioned symptoms were thought to be caused by prolonged COVID-19. He was treated with MINO and SKT due to the anti-viral properties of these two drugs. The RT-PCR test became negative 7 days after receiving this treatment, and the fever and general malaise subsided.

As the globe becomes more urban, the question how much natural biodiversity can subsist in cities becomes increasingly urgent to answer, and also how is urban diversity structured? To contribute to an answer, we studied the metacommunity of bees in a North European metropolitan area. The system consisted of 13 sites in the city of Aarhus, Denmark, censused from April to September during one year. Bees were sampled monthly in pan traps and a set of traits was related to their presence. In total, 40 species were collected–29 solitary species (40% of all sampled individuals), ten Bombus species (28%), and Apis mellifera (32%). Most sampled bees were soil-nesting, pollen generalists, and relatively common. Habitat diversity within a set of concentric circles with trap as centre and radius from 50 m to 1000 m was related to bee a diversity per site (total bee spp. with and without honeybee, solitary bees, and bumblebees). The relationship was only significant within the 1,000 m circle, and solitary bee diversity did not even correlate with habitat diversity at this large spatial scale level. The bee-site (space) and bee-month (time) networks were analyzed with respect to nestedness, modularity, and spatio-temporal b diversity. The two networks were weakly nested and strongly modular, being composed of five and six modules of tightly linked bees. Total b diversity, b_TOTAL, is the sum of species turnover, b_TURN, and species loss/gain or nestedness, b_NEST; and for both space and time, b_TURN was more important than b_NEST. Furthermore, b_TOTAL was higher than season b_TOTAL. Thus, the urban bee metacommunity was well-structured in both space and time and the high b_TURN indicated, that the network was strongly modular. We suggest the main reason is the high spatio-temporal patchiness of habitats, sustaining many unique species.

Science evolves over a gentle arc spanning centuries, with scientists building upon and extending the hypotheses and discoveries of their forebears when nurturing their own work from ideation to crystallization and finally implementation. However, evidence suggests several limitations of our modern academic pursuits including major inertia and epistemological biases to implement even major advancements. For instance, the transformative uncertainty principles of quantum mechanics are yet to be satisfactorily integrated in modern analyses and publications, even almost a century after Heisenberg received the Nobel prize for these. Another example is ever expanding reliance on mathematics to validate the hypotheses of Physics, and undermine the opinions to the contrary. In addition, modern science limits itself to the era post fifteenth century and hastily rejects premodern achievements despite glaring examples. This reluctance and inertia to capitalize on existing knowledge is a challenge that imperils our intellectual pursuits. A salient facet of science is "the willingness to admit ignorance". Only on this foundational principle can science meaningfully evolve. It is time we take a step back to evaluate widely accepted and foundational premises of modern science and institute structured processes to implement the treasure trove of knowledge amassed by our predecessors. This essay highlights some of the opportunities that can and should be availed capitalizing upon the recent developments of computational and analytical capabilities along with artificial intelligence.

We examine here characteristics of electromagnetic waves that propagate through an unbounded space filled with a homogeneous isotropic chiral medium. Resulting characters are compared to those of the electromagnetic waves propagating through an achiral free space. To this goal, we form energy conservation laws for key bilinear parameters in a chiral case. Due to a nonzero medium chirality, conservation laws turn out to contain extra terms that are linked to the spin-orbit coupling, which is absent for an achiral case. As an example, we take a plane wave for achiral case to evaluate those bilinear parameters. Resultantly, the conservation laws for a chiral case are found to reveal inconsistencies among several bilinear parameters that constitute the con-servation laws , thereby prompting us to establish partial remedies for formulating proper wave-propagation problems.

Metchnikovellids (Microsporidia: Metchnikovellida) are poorly studied hyperparasitic micro-sporidia that live in gregarines inhabiting the intestines of marine invertebrates, mostly poly-chaetes. Our recent studies showed that the diversity of the metchnikovellids might be signifi-cantly higher than previously thought, even within a single host. Four species of metchnikovellids were found in the gregarines inhabiting the gut of the polychaete Pygospio elegans from littoral populations of the White and Barents Seas: the eugregarine Polyrhabdina pygospionis is the host for Metchnikovella incurvata and M. spiralis, while the archigregarine Selenidium pygospionis is the host for M. dogieli and M. dobrovolskiji. The most common species in the White Sea is M. in-curvata, while M. dobrovolskiji prevails in the Barents Sea. The gregarines within a single worm could be infected with different metchnikovellid species. However, co-infection of one and the same gregarine with several species of metchnikovellids has never been observed. The difference in prevalence and intensity of metchnikovellid invasion apparently depends on the features of the life cycle and on the development strategies of individual species.

The emergence of unmanned aerial vehicles (UAVs) raised multiple concerns, given their potential for malicious misuse in unlawful acts Vision-based counter-UAV applications offer a reliable solution compared to acoustic and radio frequency-based solutions because of their high detection accuracy in diverse weather conditions. The existing solutions work well on trained datasets, but their accuracy is relatively low for real-time detection. In this paper, we model deep learning-empowered solutions to improve the multi-class UAV's classification performance using single-shot object detection algorithms YOLOv5 and YOLOv7. The transfer learning is employed for performance improvement and rapid training with improved results. We customized a multi-class dataset containing multi-rotor, fixed-wing, and single-rotor UAVs in challenging weather conditions. Experiments show that the integration of transfer learning has achieved good results, with an overall best average-classification precision of 94\%, an average recall of 93.1\%, a mAP$@$0.5 average of 95.3\%, and an average F1 score of 92.33\%. The dataset and code are available as an open source: https://github.com/ZeeshanKaleem/YOLOV5-Large-vs-YOLOV7.git

To evaluate the nutrient load due to the grazing of laying hens in outdoor runs, soil characteristics were monitored in three Italian organic farms. For each farm, soil samples were taken from three increasing distances from the hen house and two depths and different chemical parameters were evaluated. The comparison among the results from the different distances shows that N-NO3 and Olsen P are the most affected parameters by hen faeces: both present high values with a statistically significant difference in the area close to the poultry house and for the most superficial layer. Even TKN and TOC show significant differences between the concentrations of the first layer (more concentrated) and those of the second layer (less concentrated). In general, the surface soil layer closest to the chicken house is the portion of the outdoor run most affected by chicken droppings and represents the most critical point in terms of potential environmental impact. Therefore, it is necessary to intensify the management of the outdoor run with tools that can facilitate the grazing of animals and with vegetation that can absorb nutrients by limiting leaching and run-off.

1) Background: There are few studies of burnout syndrome (BS) in occupational therapists (OTs), and protective factors of BS has received little attention in the scientific literature. This research aimed to estimate the prevalence of BS, characterize the associated psychosocial factors, and analyze their relationship with health in a sample of Spanish OTs. (2) Methods A total of 127 therapists completed the Maslach Burnout Inventory (MBI) and other standardized questionnaires measuring: personality traits (reduced five-factor personality inventory, NEO-FFI), coping styles (Coping Strategies Questionnaire, CAE), work-family conflict (Survey Work-Home Interaction Nijmegen, SWING), professional factors (role ambiguity/clarity and modified role conflict questionnaires), and the perception of health (Goldberg’s General Health Questionnaire). Several correlational and multiple regression analyses were performed to study the psychosocial predictors of burnout and its relationship with health perception. (3) Results showed that 15.8% of the professionals presented BS, with emotional exhaustion (EE; 38.7%) being the most compromised dimension. Neuroticism, role conflict, negative work-family interaction, and open emotional expression (OE) significantly predicted a higher EE. The main predictors of cynicism (CY) were being male, role conflict, and OE. Finally, role conflict and role ambiguity and social support-seeking were significant predictors of reduced professional efficiency (PE). (4) Conclusion: A high percentage of OTs with BS advocates becoming aware of the importance of this syndrome in the health community, it would be critical to consider the protective factors (i.e., emotional management, social support) that help promote OTs’ well-being and health.

Skin detection, the process of distinguishing between skin and non-skin regions in a digital image, is widely used in a variety of applications ranging from hand gesture analysis to body part tracking to facial recognition. Skin detection is a challenging problem that has received a lot of attention from experts and proposals from the research community in the context of intelligent systems, but the lack of common benchmarks and unified testing protocols has hampered fairness among approaches. Comparisons are very difficult. Recently, the success of deep neural networks has had a major impact on the field of image segmentation detection, resulting in various successful models to date. In this work, we survey the most recent research in this field and propose fair comparisons between approaches using several different datasets. The main contributions of this work are: (i) a comprehensive literature review of approaches to skin color detection and a comparison of approaches that may help researchers and practitioners choose the best method for their application; (ii) a comprehensive list of datasets that report ground truth for skin detection; (iii) a framework for evaluating and combining different skin detection approaches. Moreover, we proposed an ensemble of convolutional neural networks and transformers that obtains state of the art performance. All the code is made publicly available at https://github.com/LorisNanni

Low-dimensional carbon-based (LDC) materials have attracted extensive research attentions in electrocatalysis because of their unique advantages such as structural diversity, low cost, and chemical tolerance. They have been widely used in a broad range of electrochemical reactions to relief environmental pollution and energy crisis. Typical examples include hydrogen evolution reaction (HER), oxygen evolution reaction (OER), oxygen reduction reaction (ORR), carbon dioxide reduction reaction (CO₂RR), and nitrogen reduction reaction (NRR). Traditional “trial and error” strategies seriously slowed down the rational design of electrocatalysts for these important applications. Recent studies show that the combination of density functional theory (DFT) calculations and experimental research is capable of accurately predicting the structures of electrocatalysts, thus could reveal the catalytic mechanisms. Herein, current well-recognized collaboration methods of theory and practice are reviewed. The history of modern DFT, commonly used calculation methods, and basic functionals are briefly summarized. Special attention is paid to descriptors that are widely accepted as a bridge links the structure and activity, and the breakthroughs for high-volume accurate prediction of electrocatalysts. Importantly, correlating multiple descriptors are used to systematically describe the complicated interfacial electrocatalytic processes of LDC catalysts. In addition, machine learning and high-throughput simulations are crucial in assisting the discovery of new multiple descriptors and reaction mechanisms. This review will guide the further development of LDC electrocatalysts for extended applications from the aspect of DFT computations.

Introduction: A dual malignancy with both Ewing Sarcoma and Prostate Adenocarcinoma has not been reported in the English literature. We report a case of simultaneous diagnosis of Ewing sarcoma and prostate adenocarcinoma with profound clinical manifestation. Case presentation: A 53-year-old male with advanced metastatic prostate cancer (Gleason-9) admitted with classical presentation of cauda equina syndrome including incontinence, back pain, and paresis following bilateral nephrostomy insertion for the treatment of bilateral renal hy-dronephrosis. The patient was diagnosed with an epidural abscess at the level of L5-S1 and an emergency surgical spine decompression was performed. No abscess was found, and pathology results showed a concomitant primary Ewing sarcoma in the spine. Conclusions: Very rare occurrences of a dual primary malignancy, in this case, Ewing sarcoma and prostate adenocarcinoma, should be kept in mind in patients suffering from complex clinical course of malignancies.

Floodplains are critically important ecosystems that provide a whole suite of ecosystem services including nutrient and carbon sequestration, flood mitigation, water storage, and critical wildlife habitat to name a few. However, human modification of rivers and floodplains through channelization, artificial levee construction, reduction in active floodplain area, and water management can significantly reduce the ecosystem function of river-floodplain systems. In this study, we evaluated the changes in nutrient loading of the Kissimmee River floodplain during the restoration of the river-floodplain system. In addition to time-series loading analysis, we also evaluated soil nutrient concentrations across the lower portion of the Kissimmee River floodplain. During the 44-year nutrient loading time-series, the floodplain remained a nutrient exporter with changes in nutrient loading generally corresponding to both water quality (i.e. point source reductions) and hydrologic restoration activities in the watershed and Kissimmee River floodplain. During the study period, inputs of total phosphorus and total nitrogen loads from upstream either significantly increased or remained the same. In addition to external sources of nutrients, internal sources of nutrients from floodplain soils can also contribute to the total nutrient export from the system. These internal sources could be organic via the decomposition of organic matter or geologic from the original excavation of the canal and/or restoration backfilling. Soil nutrient concentrations vary between vegetative communities and landscape position and could be a significant source of phosphorus to the downstream system which is plagued by eutrophic conditions. Therefore, as floodplain function in the Kissimmee River continues to be restored and managed, additional effort may be needed to address nutrient inputs and internal legacy nutrients.

Fiber aggregation in nanocomposites has an important effect on the macroscopic electrical performance. To quantitatively evaluate its effect, an index to characterize the degree of aggregation is imperative, and ideally it should have three features simultaneously, i.e., single-parametric, dimensionless and physically meaningful, applicable to different aggregation topologies, and one-to-one corresponding to material electrical properties. To this end, a new aggregation degree is proposed, which is defined as the average increased number of fibers that connect with each one when fibers aggregate from a uniformly distributed state. This index is applicable to different aggregation topologies from lump-like aggregating clusters to network-like aggregating clusters. This index is proven to only depend on the local features of aggregating clusters, and can be concisely expressed by the characteristic parameters of local structure, via geometric probability analysis and numerical validations. Further, a one-to-one linear relation between the aggregation degree and percolation threshold is established by Monte Carlo simulations, which is independent of the distribution law of the fibers. This work provides a guide to the property characterization, performance prediction and material design of nanocomposites, and also gives a physical insight into the understanding of systems with similar non-uniform distributions.

Orientia tsutsugamushi is an obligately intracellular bacterium and the etiological agent of scrub typhus. Human studies and animal models of scrub typhus have shown robust type 1-skewed proinflammatory responses during severe infection. Macrophages (Mφ) play a critical role in initiating such responses, yet mechanisms of innate recognition for O. tsutsugamushi remain unclear. In this study, we investigated whether Syk-dependent C-type lectin receptors (CLRs) contribute to innate immune recognition and the generation of proinflammatory responses. To validate a role of CLRs in scrub typhus, we infected murine bone marrow-derived (Mφ) with O. tsutsugamushi in the presence of selective Syk inhibitors and analysed a panel of CLRs and proinflammatory markers via qRT-PCR. We found that Mincle/Clec4a and Clec5a transcription was significantly abrogated upon Syk inhibition at 6 hours of infection. The effect of Syk inhibition on Mincle protein expression was validated via western blot. Syk-inhibited Mφ had diminished expression of type 1 cytokines/chemokines (Il12p40, Tnf, Il27p28, Cxcl1) during infection. Additionally, expression of innate immune cytosolic sensors (Mx1 and Oas1-3) was highly induced in the brain of lethally infected mice. We established that Mx1 and Oas1 expression was reduced in Syk-inhibited M, while Oas2, Oas3, and MerTK were not sensitive to Syk inhibition. This study reveals that Syk-dependent CLRs contribute to inflammatory responses to O. tsutsugamushi. It also provides the first evidence for Syk-dependent activation of intracellular defenses during infection, suggesting a role of pattern recognition receptor crosstalk in orchestrating macrophage-mediated responses to this poorly studied bacterium.

It is now widely accepted the climate change is having a profound impact on the weather systems around the world. These, in turn, have a considerable effect on two important elements of the Tuscan economy: wine producing and tourism. This case study sought to explore the relationship between the perception of Tuscan wine-producing agritourism owners of the potentially abstract notion of climate change and their concrete experiences as entrepreneurs. Semi-structured interviews were conducted with eight wine-producing agritourism owners or managers in Val d’Orcia, a small area of Siena, Tuscany and analyzed thematically. The impact of climate change on the area’s viticulture is undeniable but the responses to the challenges are more nuanced. Political leadership on the climate crisis appears absent and perhaps as a consequence, these small-scale operators lack knowledge and funds to enable them to plan ahead: they react often day-to-day to the immediate weather conditions rather than planning long term. While recognizing the difficulties they face from climate change as viticulturists, as agrotourism owners they welcome the longer seasons which enable them to open in the formally barren shoulder seasons but struggle with last-minute cancellations due to unpredictable weather in the area.

The factors influencing hepatitis E virus (HEV) circulation remain largely unexplored. We investigated HEV seroprevalence in humans and the prevalence of infection in farm pigs and rabbits in different regions of the Russian Federation, as well as the genetic diversity and population dynamics of HEV. Anti-HEV IgG antibody detection rates in the general population increase significantly with age, from 1.5% in children and adolescents under 20 years old to 4.8% in adults aged between 20 and 59 years old, to 16.7% in people aged 60 years and older. HEV seroprevalence varies between regions, with the highest rate observed in Belgorod Region (16.4% compared with the national average of 4.6%), which also has the country’s highest pig population. When compared with the archival data, both increases and declines in HEV seroprevalence have been observed within the last 10 years, depending on the study region. Virus shedding has been detected in 19 out of the 21 pig farms surveyed. On one farm, circulation of the same viral strain for five years was documented. All human and animal strains belonged to the HEV-3 genotype, with its clade 2 sequences being predominant in pigs. Sequences from patients, pigs, and sewage from pig farms clustered together, suggesting a zoonotic infection in humans and possible environmental contamination. The HEV-3 population size predicted using SkyGrid reconstruction demonstrated exponential growth in the 1970s–1990s, with a subsequent decline followed by a short rise around the year 2010, the pattern being similar to the dynamics of the pig population in the country. The HEV-3 reproduction number (Re) predicted using Birth-Death Skyline analysis has fluctuated around 1 over the past 20 years in Russia, but is 10 times higher in Belgorod Region. In conclusion, HEV-3 circulation varies both geographically and temporally, even within a single country. The possible factors contributing to this variability are largely related to the circulation of the virus among farm pigs.

A significant number of research studies have focused on determining whether BMI influences various types of cancer. The findings of these studies showed that people have to manage their BMIs to decrease their risk of developing various types of cancer, one of which is ovarian cancer. A PRISMA guideline for systematic review and meta-analysis was used to identify 20 research studies related to the topic to establish the truth or falsity of the findings. Later, their findings were synthesized. The synthesis of the findings of such research articles suggests that overweight and obesity increase an individual’s risk of developing ovarian cancer and experiencing severe symptoms of the disease. In such a manner, the current research study can conclude that effective management of BMI is necessary for decreasing the prevalence and mortality rates associated with ovarian cancer.

Widespread patterns of poor dietary behavior are a key factor causing the increasing prevalence of chronic diseases around the world. Research provides initial insights into the potential of food literacy (FL) to empower individuals to improve their dietary behavior. Yet, studies on FL interventions in working adults are scarce. This study aimed to investigate the short- and long-term effects of a comprehensive 3-week workplace health promotion program (WHPP) on FL and dietary intake (DI) and to examine the association between FL and DI in a sample of 144 German office workers (30.0% female). Using two random intercept mixed linear regression models, we found significant strong improvements for both FL (β = 0.52, p &lt; .0001) and DI (β = 0.63, p &lt; .0001) after the WHPP when compared to baseline. Significant long-term improvements at 18 months where strong for FL (β = 0.55, p &lt; .0001) and small for DI (β = 0.10, p &lt; .0001). FL showed a significant moderate effect on DI across all measurement time points (β = 0.24, p &lt; .0001). Our study fills a gap of long-term findings in the literature on FL interventions, offers insights into underlying mechanisms, and provides recommendations for effective WHPPs.

The reported study was devoted to the investigation of viscoelastic behavior for solid and porous ultra-high-molecular-weight polyethylene (UHMWPE) under compression. The obtained experimental stress curves were interpreted using a two-term Prony series to represent the superposition of two coexisting activation processes corresponding to long molecular (~160 s) and short structural (~20 s) time scales, respectively, leading to good statistical correlation with the observations. In the case of porous polymer, the internal strain redistribution during relaxation was quantified using Digital Image Correlation (DIC) analysis. The strongly inhomogeneous deformation of the porous polymer was found not to affect the relaxation times. In order to generalize the results to three dimensions, X-ray tomography was used to examine the porous structure at the macro- and micro-scale levels. DIC analysis revealed positive correlation between the applied force and relative density. The apparent stiffness variation for UHMWPE foams with mixed open and closed cells was described using a newly proposed three-term expression. Furthermore, the in situ tensile loading and X-ray scattering study was applied for isotropic solid UHMWPE specimens to investigate their parameters of internal structure during orientation and stress relaxation process at another mode.

The article is devoted to the problem of autoimmune diseases provocation by coronavirus infection and the role of molecular mimicry in this phenomenon. SARS-CoV-2 can disguise its proteins as human ones in order to avoid immune attack. A bioinformatics analysis of the probable pentapeptide sharing between human autoantigens of endocrinocytes and SARS-CoV-2 spike protein, membrane protein and nucleocapsid protein was performed. Antigen mimicry between S-proteins of all other known human Coronaviruses and typical target autoantigens of endocrinocytes was also explored. Six human-identical regions were found in the SARS-CoV-2 membrane and nucleocapsid proteins, all of them in their immunodominant epitopes. All shared epitopes belong to antigens of endocrine cells commonly targeted during autoimmune endocrinopathies. Moreover, samples of the pituitary, adrenal and thyroid from patients who died from coronovirus infection (COVID-19) were studied morphologically using histochemical methods. A high frequency of SARS-CoV-2 caused inflammation of the studied endocrine organs was found in patients who died from severe COVID-19. At the same time, the abundant expression of virus antigens by the cells of the adenohypophysis was combined with the complete absence of its expression by the cells of the neurohypophysis. SARS-CoV-2 infected cells apparently perished by non-apoptotic pathway. The foci of lesions in endocrine organs contained abundant lymphocytic infiltrates which may witness for the impact of autoimmune processes. The facts revealed emphasize the need of endocrinological diagnostic alertness of a physician while observing patients with post-vaccination and post-COVID-19 health disorders. [3 figures, 6 tables, bibliography: 45 references].

Aim: Exposure to polycyclic aromatic hydrocarbons (PAHs) has been in the past associated with adverse effects on human health among which belong also respiratory diseases. Our study is focused on the evaluation of PAH exposure by measuring the concentrations of their monohydroxylated metabolites (OH-PAHs) in urine and comparing their concentrations with the incidence of respiratory diseases in 2-year-old children from two locations of the Czech Republic – a control locality Ceske Budejovice and a previously highly contaminated mining district Most. Methods: The total number of 248 participants were sampled for urine samples that were analysed for the presence of 11 OH-PAHs using liquid-liquid extraction with ethyl acetate and clean-up employing dispersive solid phase extraction with a sorbent Z-Sep. Separation, identification and quantification of the target compounds was achieved by ultra-high performance liquid chromatography coupled to tandem mass spectrometry. The incidence of respiratory diseases was evaluated according to the questionnaires provided by the paediatricians. Results and discussion: The concentrations of measured OH-PAHs were higher in the urine samples collected from 2-year-old children living in Most compared to 2-year-old children from Ceske Budejovice. The same trend was observed also when the urine samples were analysed when these children were studied as newborns in our previous study. From all of the monitored respiratory diseases, only influenza due to unidentified influenza virus showed a difference between tested locations where the 2-year-old children living in Most were more frequently diagnosed with this disease. Conclusion: Even though the air pollution and lifestyle in both cities is very similar, we have observed higher incidence of respiratory diseases as well as higher concentration of OH-PAHs in urine of the 2-year-old children from Most. Therefore, we hypothesize that the population living in this previously highly contaminated location (in 1970s and 1980s) can carry some long-term health burden.

Blockchain technology has gotten much interest recently from academics, industry, and governments worldwide. It is regarded as a technical innovation that can disrupt various application fields affecting many aspects of our lives. Cryptocurrencies are a public blockchain application's success story that sparked extensive research and development. Scalability, energy consumption, and security, on the other hand, remain significant challenges. With low throughput, high transaction delay, and high energy consumption, most cryptocurrencies are experiencing low-efficiency difficulties. The scalability issue with public Blockchains is preventing organizations and sectors from receiving effective solutions. As a result, it is critical to bridge the gap and develop new frameworks that connect Blockchain with those goals. This paper examines the evolution of blockchain architecture and consensus protocols, provides a retrospective analysis, discusses the rationale for the various architectures and protocols' change, and captures the assumptions supporting their development and contributions to collaborative application development. However, existing research on consensus algorithms is insufficient. The features of the algorithms are discussed insufficiently in those papers, and some prominent blockchain consensus methods are not examined in terms of their scopes. The study’s findings are delivered in tabular formats, allowing for a clear representation of these algorithms. We discovered in our investigation that scalability is a result of many parameters such; transaction throughput, number of nodes, storage, block size, high communication, latency, cost. Furthermore, Due to its off-chain data storage and smaller block size, PoF is much more scalable than PoS and PoW, and Because PoA is a hybrid of PoW and PoC, it does not necessitate a large number of computational resources. As a result, it has a higher throughput than PoW. PoPF entails ranking all participating nodes and appointing n accountants to compete for adding new blocks. This article addresses the need by analyzing a wide range of consensus algorithms using a complete taxonomy of attributes and delving into the consequences of several still-present flaws in consensus algorithms.

One of the most frequent brain diseases, Alzheimer's is defined by poor cognitive function brought on by the build-up of Beta Amyloid plaques and the gradual death of neurons. Glucose metabolism and the development of amyloid plaques are being studied together. Under physiologically normal circumstances, glucose is the primary substrate for the adult human brain. The prodromal phases of AD are significantly influenced by glucose hypometabolism. Hypometabolism of glucose in the brain is a clear sign of mitochondrial dysfunction and bioenergetic system impairment. By regulating energy synthesis and cell death, mitochondria play a crucial role in the functioning of cells. Increased formation of reactive oxygen species (ROS) and oxidative stress are a result of mitochondrial dysfunction, which also accelerates the development of Alzheimer's disease. For the maintenance of balance, autophagy is crucial because it selectively destroys damaged mitochondria. AD affects this route for mitochondrial breakdown. Targeting specific mitochondrial ligands by interventions along this pathway might be a useful therapeutic approach. Due to a number of biological obstacles, this method has significant limitations. As a result, many nanocarriers have been created to improve drug delivery effectiveness. All potential nanotechnology-based treatments for AD have been examined in this study, with a particular emphasis on medication delivery to the mitochondria

With increasing constraints on energy and resource markets and the non-decreasing trend in energy demand, the need for relevant clean energy generation and storage solutions is growing and is gradually reaching the individual home. But small-scale energy storage is still an expensive investment in 2022 and the risk/reward ratio is not yet attractive enough for individual homeowners. One solution is for homeowners not to store excess clean energy individually but to produce hydrogen for mutual use. In this paper a collective production of hydrogen for a daily filling of a bus is considered. Following our previous work on the subject, the investigation consists of finding an optimal buy/sell rule to the grid, and the use of the energy with an additional objective: mobility. The dominant technique in the energy community is reinforcement learning, which is however difficult to use when the learning data is limited as in our study. We chose a less data-intensive and yet technically well-documented approach. Our results show that rulebooks, different but more interesting than the usual robust rule, exist and can be cost-effective. But they require fine-tuning as to not deteriorate system performance. In some cases, it is worth missing the H2 production requirement in exchange for higher economic performance.

This paper documents the development of a special case of multilingual Automatic Speech Recognition model, specifically tailored to attend two languages spoken by the majority of Latin America, Portuguese and Spanish. The bilingual model combines Language Identification and Speech Recognition developed with the Wav2Vec2.0 architecture and trained on several open and private speech datasets. In this model, the feature encoder is trained jointly for all tasks and different context encoders are trained for each task. The model is evaluated separately on two tasks: language identification and speech recognition. The results indicate that this model achieves good performance on speech recognition and average performance on language identification, training on a low quantity of speech material. The average accuracy of the language identification module on the MLS dataset is 66.75%. The average Word Error Rate in the same scenario is 13.89%, which is better than average 22.58% achieved by the commercial speech recognizer developed by Google.

The COVID-19 pandemic creates anxiety among hospitalised SARS-CoV-2 patients. Therefore, this study aims to determine the prevalence of anxiety and its associated factors among stable inpatient COVID-19 patients in Malaysia. A cross-sectional study was conducted using a web-based online survey involving 401 patients from Malaysia's leading COVID-19 hospitals from 15th April until 30th June 2020 who were chosen using quota sampling. General Anxiety Disorders 7 items (GAD-7), Coping Orientation to Problems Experienced Inventory (Brief-COPE) and Socio-demographic profile questionnaire were used. Descriptive analysis and multiple logistic regression were performed using SPSS v23 to determine the prevalence of anxiety and its associated factors. The results showed that prevalence of anxiety was 7.0%. Multiple logistic regression analysis revealed that female (p < 0.05), fear of infection (p < 0.05), lack of information (p < 0.05), maladaptive coping mechanism of behavioural disengagement (p < 0.001) and self-blame (p < 0.001) were significantly associated with anxiety. Whereas adaptive coping mechanisms via instrumental support (p < 0.001) was a significant protective predictor of anxiety. COVID-19 infection has had a significant influence on the mental health of patients. Findings in our study provides baseline findings on prevalence of anxiety among stabilized COVID-19 inpatient in Malaysia. Despite the relative low prevalence, the data has the potential to improve the present mental health monitoring system and the deployment of suitable treatments in dealing with similar circumstances

The pandemic has accentuated the power that influencers have to influence their followers. Various scientific approaches highlight the lack of moral and ethical responsibility of these creators when disseminating content under highly sensitive tags such as health. This article presents a correlational statistical study of 443 Instagram accounts with more than one million followers belonging to health-related categories. This study aims to describe the content of these profiles and their authors and to determine whether they promote health as accounts that disseminate health-related content, identifying predictive factors of their content topics. In addition, it aims to portray their followers and establish correlations between the gender of the self-described health influencers, the characteristics of their audience and the messages that these prescribers share. Health promotion is not the predominant narrative among these influencers, who tend to promote beauty and normative bodies over health matters. A correlation is observed between posting health content, the gender of the influencers and the average age of their audiences. The study concludes with a discussion on the role of public media education and the improvement of ethical protocols on social networks to limit the impact of misleading and false content on sensitive topics, increasing the influence of real health prescribers.

Calculus, as a starting point to everyone's study of mathematics, was developed along with classical mechanics. Though not rigorously formulated, the intuition for differential form and infinitesimal motion makes calculus not hard to understand. And hence it does not require great effort to grasp the principles of classical mechanics. However, the situation becomes quite different when it comes to the quantum world. Given a particle system, what of interest is always the physical quantity of this system, such as energy, position, momentum, entropy, etc. But it is no longer straightforward.

After the great success of Mobile wallet, the Internet of Things (IoT) leaves the door wide open for consumers to use their connected devices to access their bank accounts and perform routine banking activities from anywhere, anytime and with any device. However, consumers need to feel safe when interacting with IoT-based payment systems, and their personal information should be protected as much as possible. Unlike as usually done in the literature, in this paper, we introduce two lightweight and secure IoT-based payment protocols based on an identity-based signature scheme. We adopt a server-aided verification technique to construct the first scheme. This technique allows to outsource the heavy computation overhead on the sensor node to a cloud server while maintaining the user's privacy. The second scheme is built upon a pairing-free ECC-based security protocol to avoid the heavy computational complexity of bilinear pairing operations. The security reduction results of both schemes are held in the Random Oracle Model (ROM) under the discrete logarithm and computational Diffie-Hellman assumptions. Finally, we experimentally compare the proposed schemes against each other and against the original scheme on the most commonly used IoT devices: a smartphone, a smartwatch and the embedded device Raspberry Pi. Compared with existing schemes, our proposed schemes achieve significant efficiency in the term of communication and computational overheads

RNA interference (RNAi) is one of the main mechanisms for disease resistance and small RNA production in plants. The main proteins involved in RNAi include Dicer-like (DCL), RNA-dependent RNA polymerase (RDR), double-stranded RNA-binding (DRB), and Argonaute (AGO). Juglandaceae contains a variety of important woody plants, and walnuts are one of the four major woody plant groups and one of the four major dried fruits in the world. To clarify the evolution and functional differentiation of RNAi-related proteins in the walnut (Juglans regia) genome, this study integrated various web resources from gene family acquisition to structural analysis and transcriptome data to correlate walnuts and their congeners. The walnut genome has 5 DCL, 13 RDR, 15 DRB and 15 AGO genes, similar genes encoding conserved protein structural domains and conserved motifs with similar subcellular localization. Walnut AGO proteins are classified into three classes and seven subclasses. The DCL is divided into four categories, while RDR is mainly divided into four categories, and DRB can be divided into six categories. The exception is that the copy number of walnut RDR1 is 9, in which seven RDR1 are distributed in clusters on chromosome 16. Purifying selection drove the formation of walnut genes, but protein classes were subjected to varying degrees of purifying selection. Additionally, these results showed some similarity in other plants of the walnut family. Moreover, different RNAi-related genes of walnut produced abundant selective expression in response to different tissues and stresses. In this study, DCL, RDR, DRB and AGO gene families were identified and analysed in the genome of the walnut family for the first time and preliminarily examined the evolution, structure and expression characteristics of these families to provide a preliminary basis for the evolution of the walnut RNAi pathway and breeding research.

Alternative fuels have the potential to reduce exhaust emissions in the transportation sector. In this study, the effects of oxygenated fuels on the performance and emissions of a gasoline single-cylinder spark-ignition engine have been investigated experimentally. Experiments were conducted using a DIDACTA-T85 testbed under full load conditions and variable engine speed. Performance tests were performed by measuring the brake torque, brake power, brake mean effective pressure (BMEP), brake specific fuel consumption (BSFC), and brake thermal efficiency (BTE). The tested fuel blends were G0, E10, A10, and M10. G0 represented the base fuel and pure gasoline. E10, A10, and M10 were represented by a 10% volume of ethanol, acetone, and methanol in gasoline respectively. Results showed that M10 produced better engine performance in terms of brake torque, brake power, and BMEP, while E10 performed better results in terms of BSFC and BTE. A10 gave the lowest value in NOx emission at all engine speeds. On the other hand, it increased the NOX emission for E10 and M10 blends. This study showed that oxygenated fuel blends significantly reduced carbon monoxide emission at all engine speeds whereas carbon dioxide emission was higher at the highest engine speed.

Fiber distributed optical fiber acoustic sensor (DAS) is generally used in distributed long-distance acoustic/vibration measurement. We found that DAS with excellent performance of low self-noise and anti-fading in combination with the plastic structure in daily life as an acoustic transducer can achieve high-sensitivity acoustic measurement at a single point rather than designing a state-of-the-art acoustic transducer or using special enhanced scattering fiber. The simple acoustic transducer we proposed for DAS can reach the sensitivity level of -106.5dB re. 1rad/μPa at a sensing range of 5.1 km, which can meet many demands on the industrial site.

Mass transfer is often the rate determining step for solid-liquid chemical reactions. Decrease of the concentration boundary layer thickness is essential to intensify the chemical reaction. Because the concentration boundary layer exists in the velocity boundary layer, force imposition in the concentration boundary layer by superimposing an electrical current and a magnetic field was proposed. Through, flow can be directly excited in the concentration boundary layer. The previous result indicates that by superimposing a DC current and a gradient magnetic field, the development of the concentration boundary layer was suppressed, because of a macro-scale flow excitation in the whole vessel. And by superimposing the gradient magnetic field with a modulate current, the development of the concentration boundary layer was further suppressed. This is because of the macro-scale flow enhancement and the excitation of a micro-scale flow near the solid-liquid interface. However, the mechanism for the micro-scale flow excitation has not been clarified. To clarify this, a uniform magnetic field was superimposed with the DC current or the modulate current. By this means, only the micro-scale flow was excited near the anode surface. The results found that the non-unform electromagnetic force distribution is the main reason for the micro-scale flow excitation.

Background: When homeostasis is disturbed it can occur a pathological event named inflammation. The main drugs used in the treatment consist of the non-steroidal and steroidal anti-inflammatory drugs. However, the side effects remain an obstacle during the treatments. In this work we aimed to evaluate three new regioisomers analogues of naphthyl-N-acylhydrazone derivatives. Methods: Acute models of inflammation in vivo (formalin-induced licking and carrageenan-induced inflammation) as well as in vitro were used to evaluate the effects of LASSBio-2039, LASSBio-2040, and LASSBio-2041. Results: All three substances (at 1, 10 or 30 µmol/kg) presented significant effect in the in vivo model reducing leukocyte migration, nitric oxide (NO) and interleukin-1β production. It was observed that only LASSBio-2039 significantly reduced cell migration in vitro. None of the LASSBios did affect inducible nitric oxide synthase activity nor presented NO scavenger effect. It was not observed any toxic effect neither in vivo nor in vitro. The new regioisomers analogues of naphthyl-N-acylhydrazone derivatives presented a significant anti-inflammatory activity suggesting LASSBio-2039 with a direct effect in leukocytes migratory capacity. Conclusions: Taken together the data indicate that these substances present promising effect for de development a prototype for new drugs.

(1) Background: Metabolic syndrome is associated with cardiovascular complications. Therefore, this study aims to establish cut points for the conicity index based on the components of the metabolic syndrome and to associate it with characteristics sociodemographic, food consumption and occupational factors in Brazilian rural workers; (2) Methods: Cross-sectional study carried out with farmers. The receiver operating characteristic curve was calculated and the cutoff points for the conicity index were identified by the area under the curve, sensitivity and specificity. The variables included in the binary logistic regression analysis were selected by considering p &lt; 0.20 in the bivariate test; (3) Results: The cut points were similar in females according to both criteria, resulting in a single cut-off of 1.269. In males, the cut points showed differences, resulting in 1.272 according to the NCEP-ATP III and 1.252 according to the IDF. We have shown that younger people, those who work more than 40 hours a week and the lowest contribution of culinary ingredients are associated with increased odds of abdominal obesity. While the consumption of the products they sell or produce decreases these chances; (4) Conclusions: The conicity index showed high discriminatory power for the identification of abdominal obesity in rural workers.