The aims of this research were to know the physicochemical parameters, texture properties and sensory profile of vegetarian sausages through the flash profile, overall liking and purchase intention. Additionally, protein, fat and carbohydrate contents, pH, water activity, color, instrumental texture and descriptive profile were quantified with the overall liking and purchase intention of four sausages: ovo-vegetarian (SO), classic vegan (SC), fine herb vegan (SH) and vegan quinoa (SQ). Regarding the physicochemical properties, significant differences (p < 0.05) were obtained. Using the flash profile, consumers described SO with attributes of elasticity, tamale smell, strange smell, characteristic flavor, pastiness, softness, pastel color. SC described as soft, pale color, characteristic odor, characteristic flavor, porous and flexible; SH and SQ characterized by the presence of ingredients, stew flavor, spices, pale and soft color. The SO sample presented greater overall liking and purchase intention compared to the other samples, and had a better texture and higher protein content. Through the HMFA analysis, a positive correlation was obtained between the texture and descriptive sensory of the flash profile, and on the other hand, a correlation between the physicochemical characteristics pH, aw, color, overall liking and purchase intention.

Alzheimer's disease (AD) is the most common form of dementia and neurogenerative diseases (NDDs), which is one of the leading causes of death worldwide. The number of AD patients is over 55 million according to 2020 Alzheimer's Disease International (ADI) and the number is increasing drastically without any effective cure. In this review, we discuss and analyze the potential role of anthocyanins (ACNs) against AD with understanding the molecular mechanisms. ACNs have been reported as having neuroprotective effects by mitigating cognitive impairments, apoptotic markers, neuroinflammation, aberrant amyloidogenesis, and tauopathy. Taken together, ACNs could be the therapeutic agent for combating or delaying the onset of AD.

Novel far-red-sensitive symmetric squaraine (SQ) dyes with terminal alkyl-chain modifications were designed, synthesized and characterized aiming towards imparting multifunctionalities such as photosensitization, dye aggregation prevention and source of electrolyte components. The dye sensitizers SQ-77 and SQ-80 with the alkyl chain terminal modifications consisting of iodine and 1-methylimidazolium iodide, respectively, were designed and synthesized as new dye sensitizers for DSSCs based on the symmetric SQ-5 without any terminal modification used as reference. Upon adsorption on the mesoporous TiO2 surface, The SQ-77 depicted an enhanced dye loading and dye aggregation. On the other hand, SQ-80 demonstrated reduced dye aggregation and stronger binding on the TiO2 surface leading to enhanced durability of DSSCs. Apart from the most common photosensitization behaviour, the newly designed dye demonstrated multifunctionality such as aggregation prevention and electrolyte functionality utilizing iodine-based redox electrolyte in the presence and absence of I2 and LiI additives. In the absence of LiI and I2, a mixture of SQ-77 and SQ-80 demonstrated a photoconversion efficiency of 1.54 % under simulated solar irradiation, which was about 6 times higher as compared to reference dye SQ-5 (0.24 %) having no alkyl chai terminal modification.

With the rapid development of society and the deteriorating natural environment, there has been an increase in public events. This study aimed to explore how sadness and fear in the context of public emergency influence moral judgments. This research first induced feelings of sadness and fear by videos about public events and music, and then used moral scenarios from the CNI model to assess participants’ moral thinking. In Study 1, participants were divided into sadness group and neutral group, while in Study 2, participants were divided into fear group and neutral group. During the experiment, participants were exposed to different videos related to public events to induce the corresponding emotions, and emotional music was continuously played throughout the entire experiment. Participants were then asked to answer questions regarding moral judgments. The results showed that based on CNI model, sadness induced in the context of public events significantly increased C parameter, without affecting N or I parameter. Fear increased I parameter, without affecting C or I parameter. That is, sadness and fear induced in the context of public events can influence moral judgments. Specifically, sadness increases individuals’ sensitivity to consequence, and fear increases the general preference for inaction in moral judgments.

This paper introduces a novel architecture—bidirectional optical neural network (BONN)—for providing backward connections alongside forward connections in artificial neural networks (ANNs). BONN incorporates laser diodes and photodiodes and exploits the properties of Köhler illumination to establish optical channels for backward directions. Thus, it has bidirectional functionality that is crucial for algorithms such as the backpropagation algorithm. BONN has a scaling limit of 96 × 96 for input and output arrays, and a throughput of 8.5 × 1015 MAC/s. While BONN's throughput may rise with additional layers for continuous input, limitations emerge in the backpropagation algorithm as its throughput doesn't scale with layer count. Successful BONN-based implementation of the backpropagation algorithm requires the development of fast spatial light modulator to accommodate frequent data flow changes. A two-mirror-like BONN and its cascaded extension are alternatives for multilayer emulation, and they help save hardware space and increase the parallel throughput for inference. An investigation into the application of the clustering technique to BONN revealed its potential to help overcome scaling limits and to provide full interconnections for backward directions between doubled input and output ports. BONN's bidirectional nature holds promise for enhancing supervised learning in ANNs and increasing hardware compactness.

Spinal muscular atrophy is a neuromuscular genetic condition associated with progressive muscle weakness and atrophy. Nusinersen is an antisense oligonucleotide therapy approved for the treatment of 5q spinal muscular atrophy in pediatric and adult patients. The objective of this clinical case series is to describe the efficacy and safety of nusinersen in treating spinal muscular atrophy in 20 pediatric and 18 adult patients across six treatment centers in Kuwait. Functional motor assessments (Children’s Hospital of Philadelphia Infant Test of Neuromuscular Disorders, Hammersmith Functional Motor Scale Expanded, and Revised Upper Limb Module) were used to assess changes in motor function following nusinersen treatment. Safety assessment involved clinical monitoring of adverse events. The results demonstrate clinically meaningful or considerable improvement in motor performance for nearly all patients, lasting over 4 years in some cases. 70% of patients in the pediatric cohort and 72% of patients in the adult cohort achieved clinically meaningful improvement in motor function following nusinersen treatment. Additionally, nusinersen was well-tolerated in both cohorts. These findings add to the growing body of evidence relating to the clinical efficacy and safety of nusinersen.

The beta-galactoside-binding mammalian lectin galectin-1 can bind, via its carbohydrate recognition domain (CRD), various cell surface glycoproteins and has been implicated in a range of cancers. As a consequence of binding to sugar residues on cell surface receptors it has been shown to have a pleiotropic effect across many cell types and mechanisms resulting in immune system modulation and cancer progression. As a result, it has started to become a therapeutic target for both small and large molecules. In previous studies, we have used fluorescence polarisation (FP) assays to determine KD values to screen and triage small molecule glycomimetics that bind to the galectin-1 CRD. In this study surface plasmon resonance (SPR) was used to compare human and mouse galectin-1 affinity measures with FP as SPR has not been applied for compound screening against this galectin. Binding affinities for a selection of mono- and di-saccharides covering a 1,000-fold range correlated well between FP and SPR assay formats for both human and mouse galectin-1. It was shown that slower dissociation drove the increased affinity at human galectin-1 whilst faster association was responsible for the effects at mouse galectin-1. This study demonstrates that SPR is a sound alternative to FP for early drug discovery screening and determining affinity estimates. Consequently, it also allows association and dissociation constants to be measured in a high throughput manner for small molecule galectin-1 inhibitors.

Accurate cloud quantification is essential in climate change research. In this work, we construct an automated computer vision framework by synergistically incorporating deep neural networks and finite sector clustering to achieve robust whole sky image-based cloud classification, adaptive segmentation, and recognition under intricate illumination dynamics. A bespoke YOLOv8 architecture attains over 95% categorical precision across four archetypal cloud varieties curated from extensive annual observations (2020) at a Tibetan highland station. Tailor-made segmentation strategies adapted to distinct cloud configurations, allied with illumination-invariant image enhancement algorithms, effectively eliminate solar interference and substantially boost quantitative performance even in illumination-adverse analysis scenarios. Compared with the traditional threshold analysis method, the cloud quantification accuracy calculated within the framework of this paper is significantly improved. Collectively, the methodological innovations provide an advanced solution to markedly escalate cloud quantification precision levels imperative for climate change research, while offering a paradigm for cloud analytics transferable to various meteorological stations.

This paper presents the design of a new neuro-generator of pseudorandom number type PRNG Pseudorandom Number Generator, which produces complex sequences with an adequate bit distri-bution. The circuit is connected to a neuronal module with six impulse neurons with different be-haviors: spike frequency adaptation, phasic spiking, mixed mode, phasic bursting, tonic bursting and tonic spiking. This module aims to generate a non-periodic signal that becomes the clock sig-nal for one of the LFSRs Linear Feedback Shift Register that the neuro-generator has. To verify its correct operation, the neuro-generator was subjected to a series of tests where the frequencies of the impulse neurons were modified. This modification allows generating a greater number of pulses at the output of the neuronal module, to obtain sequences with different characteristics that pass different NIST statistical tests National Institute of Standards and Technology of U.S. The results show that the new neuro-generator maintains pseudo-randomness in the sequences obtained with different frequencies and it can be implemented on reconfigurable FPGA Field Programmable Gate Array Virtex 7 xc7vx85t-2ffg1761 device. Therefore, it can be used for applications such as biologi-cal systems.

Landslides, resulting from disturbances in slope equilibrium, pose a significant threat to landscapes, infrastructure, and human life. Triggered by factors such as intense precipitation, seismic activities, or volcanic eruptions, these events can cause extensive damage and endanger nearby communities. A comprehensive understanding of landslide characteristics, including spatio-temporal patterns, dimensions, and morphology, is vital for effective landslide-disaster management. Existing Remote Sensing approaches mostly use either optical or Synthetic Aperture Radar (SAR) sensors. Integrating information from both these types of sensors promises greater accuracy for identifying and locating landslides. This study proposes a novel approach, the ML-LaDeCORsat (Machine Learning-based coseismic Landslide Detection using Combined Optical and Radar Satellite Imagery), that integrates freely available Sentinel-1, Palsar-2, and Sentinel-2 imagery data, along with relevant spectral indices and suitable bands using machine-learning-based classification for coseismic landslide detection implemented in Google Earth Engine (GEE). The approach includes a robust and reproducible training and validation strategy. Using landslides from four different earthquake case studies, we demonstrate the superiority of our approach over existing solutions in coseismic landslide iden-tification and localization, providing a detection accuracy of 87-92%. ML-LaDeCORsat can be adapted to other landslide events (GEE script is provided). Transfer learning experiments proofed that our model can be applied to other coseismic landslide events without the need for additional training data. Our novel approach therefore facilitates quick and reliable identification of co-seismic landslides, highlighting its potential to contribute towards more effective disaster management.

Sample size using prevalence has been one of the most important medical research methodologies and has been used in original articles more often than any other statistical tool available. The simple formula consists of variables interdependent and it is as important to understand how they influence each other as it is to learn to use the formula to calculate the sample size. With the choice of different amounts of precision and levels of confidence available to a medical researcher, it should be of paramount importance to understand what a slight change in choosing the parameter would mean at the end of the research. Understanding of different Z values, Levels of precision, and ranging Prevalence is required to understand the effect on the sample size and subsequently on the research. Topological representation using parameter ranges can be used to demonstrate this relationship.

Astaxanthin (ATX) is a carotenoid nutraceutical with a poor bioavailability due to its high lipophilicity. We tested a new tailored nano-droplet capable of solubilizing ATX in an oil-in-water micro-environment (LDS-ATX, manufactured by Lyotropic Delivery Systems (LDS)), for its capacity to improve ATX pharmacokinetic profile and anti-oxidant efficacy. We used liquid chromatography tandem mass spectrometry (LC-MS/MS) to compare the pharmacokinetic profile of ATX and LDS-ATX and protein carbonylation and lipid peroxidation assays to compare their basal and lipopolysaccharide (LPS)-induced oxidative damage. Our results show that only LPS-induced oxidative damage was corrected by ATX and LDS-ATX. While in the liver and muscle LDS-ATX was more efficacious than ATX in attenuating oxidative damage to both proteins and lipids, only oxidative damage to lipids was preferably corrected by LDS-ATX in the brain. These results strongly suggest improvement of ATX bioavailability and efficacy by the LDS-ATX nano-formulation.

Rheumatoid arthritis (RA) is a complex illness with both hereditary and environmental compo-nents. Globally, in 2019, 18 million people had RA. RA is characterised by persistent inflammation of the synovial membrane that lines the joints, cartilage loss, and bone erosion. Phenolic molecules are the most prevalent secondary metabolites in plants, with a diverse spectrum of biological ac-tions that benefit functional meals and nutraceuticals. These compounds have received a lot of at-tention recently because they have antioxidant, anti-inflammatory, immunomodulatory, and anti-rheumatoid activity by modulating tumour necrosis factor, mitogen-activated protein kinase, nu-clear factor kappa-light-chain-enhancer of activated B cells, and c-Jun N-terminal kinases, as well as other preventative properties. This article discusses dietary polyphenols, their pharmacological properties, and innovative delivery technologies for the treatment of RA, with a focus on their possible biological activities. Nonetheless, commercialization of polyphenols may be achievable only after confirming their safety profile and completing successful clinical trials.

When asked to estimate the carbon footprint of a bundle of relatively low carbon footprint items and relatively high carbon footprint items, people typically report a lower value compared to estimating the high carbon footprint items alone. This finding is called the negative footprint illusion and suggests people report the average rather than sum of the combined items’ carbon footprint. In a recent paper by Gorissen et al. (2024), the authors claimed that people are immune to this illusion if the question is framed differently. Specifically, they found that estimates of the environmental friendliness of a set comprising a burger (high carbon footprint) and an organic apple (low carbon footprint) was higher than for a set comprising the burger alone, whereas no difference was found between the two sets when participants were asked to estimate how environmentally damaging they were. Using larger item categories wherein the degree of the items’ environmental impact is clearly communicated, here we show it does not matter whether participants are required to estimate how friendly or damaging the items are. The roles of attribute substitution, dependent variables, and independent variables (stimulus characteristics) in modulating the negative footprint illusion is discussed.

The purpose of this study was to identify candidate novel species performing beneficial ecological functions from soil. The hypothesis was that novel culturable species with antibiotic production potential could be readily found from soil in the Nature Canyon at Los Angeles Pierce College. 137 bacterial isolates from soil were grown on nutrient agar, ISP-6 medium, or LB agar and partial 16S was ascertained using the Sanger platform for regions V1-V4. One of the potentially novel isolates, Pseudomonas sp. 21-C3-ER, was isolated on nutrient agar from fallow soil in an agricultural nature preserve in Los Angeles. The soil conditions were 3.7% moisture, clay texture by touch, 13.37% organic matter, pH=6.63, TDS=638, 150 ppm nitrogen, 114 ppm phosphate, and 42 ppm potash. Whole genome sequencing was performed on the DNBseq platform and species identification was performed with TRUEBacID; the closest relative was Pseudomonas brassicacearum subsp. neoaurantiaca which was 92.05% similar by genomic evidence. 197 virulence factors were identified including flagellar biosynthesis, motor proteins, Beta-lactamase, Fosfomycin, copper, and sulfur drug resistance. Gram stain of strain 21-C3-ER revealed gram negative rods. Rods were visualized with scanning electron microscopy, revealing individuals approximately 1 µm in length. Secondary metabolite analysis using antiSMASH showed a variety of post-translationally modified proteins and a promysalin analog. The qualitative test for pyoverdine siderophore production using UV light was positive. Metabolic analysis using RAST indicated genes were present for pyoverdine production, antimicrobial resistance, and ammonification. The nitrate reduction test was positive. Denitrifying bacteria may prevent leaching of nitrates from soil, since ammonia has a higher affinity to soil and organic matter than nitrate. We propose Pseudomonas fernandeno as a novel species. The type stain is 21-C3-ER.

The tambaqui Colossoma macropomum is the main species of edible fish originating from fish farming in the Amazon region. This study aimed to determine and compare the hematological and biochemical parameters of tambaqui from fish farms in municipalities in the Metropolitan Region of Manaus, Amazonas, Brazil. Two fish farms were sampled in a semi-excavated pond-type breeding system in each of the five towns investigated (Presidente Figueiredo, Manaus, Iranduba, Manacapuru and Novo Airão), totaling ten breeders. On each farm, ten specimens were captured, totaling 100 animals. Blood was collected by caudal puncture, and hematological and biochemical parameters were determined using the methodology described for teleosts fish. For the erythrogram in the variables of hematocrit, hemoglobin concentration and erythrocytes, significant differences were observed in Iranduba and Novo Airão, demonstrating indications of anemic processes and dehydration. For plasma biochemistry, low levels were observed in fish from Iranduba and Novo Airão. High values in lipid compounds were found in tambaqui from Manacapuru. High intraspecific variation was found in the leukogram and thrombogram, which determined similarities between tambaqui from different farms and municipalities. On the other hand, fish from Manacapuru have an inappropriate diet, indicated by the high levels of cholesterol and triglycerides found in the blood.

Background: Both of cognitive decline and unhealthy lifestyle have been associated with an increased risk of mortality in older people. We aimed to investigate whether lifestyle behaviors might modify the association between cognitive function and the risk of all-cause mortality in Chinese older populations. Methods: The study included 5,124 individuals free of dementia in the Chinese Longitudinal Healthy Longevity Survey from 2011 to 2018. Cognitive function was measured using the Mini-Mental State Examination in 2011. A lifestyle score was calculated on the basis of five lifestyle factors including smoking, alcohol consumption, physical activity, diet and body mass index. Cox proportional hazards models were performed to examine the association between baseline cognitive function and all-cause mortality, with an interaction term of cognitive function and lifestyle score being added to the models Results: During a median follow-up of 6.4 years, we documented 1,461 deaths. Both higher cognitive function (HR: 0.96; 95% CI: 0.96–0.97) and healthier lifestyle (HR: 0.92; 95% CI: 0.87–0.97) were significantly associated with a lower risk of mortality. We found that lifestyle significantly modified the association of cognitive function with mortality (P for interaction = 0.004). The inverse association between high cognitive function and mortality was more prominent among participants with healthier lifestyle. Of note, among the lifestyle scores component, diet showed a significant interaction with mortality (P for interaction = 0.003), with the protective HR of the all-cause mortality associated with higher MMSE scores was stronger among participants with healthy diets compared with unhealthy diets. Conclusion: Our study indicates that cognitive decline is associated with an increased risk of mortality, and such relations are modified by overall lifestyle, with healthy diet being the major contributor.

This paper investigates a numerical code coupling technique to tackle multi-physics and multi-scale simulations using state-of-the-art software packages that typically address some specific modeling domain. The coupling considers the in-house FEM code, FEMuS, and the FVM code OpenFOAM, by exploiting the MED library from the SALOME platform. The present approach is tested on a buoyancy-driven fluid flow within a square cavity, where the buoyancy force constitutes the coupling term. In uncoupled scenarios, momentum and temperature equations are solved both in FEM and FVM codes without data exchange. In the coupled setting, only the OpenFOAM velocity and the FEMuS temperature fields are solved separately and shared at each time step (or vice versa). The MED library handles the coupling with the addition of suitable ad-hoc data structures that perform the field transfer between codes. Different Rayleigh numbers are investigated, comparing the outcomes of coupled and uncoupled cases with reference literature results. Additionally, a boundary data transfer application is presented to extend the capabilities of the coupling algorithm to coupled applications with separate domains. In this problem, the two domains share interfaces and boundary values on specific fields as fluxes are exchanged between the two numerical codes.

The continuing mutability of the SARS-CoV-2 virus can result in failures of diagnostic assays. To address this, we describe a generalizable bioinformatics-to-biology pipeline developed for calibration and quality assurance of inactivated SARS-COV-2 variant panels provided to Radical Acceleration of Diagnostics programs (RADx)-radical program awardees. Heuristic genetic analysis based on variant-defining mutations demonstrated the lowest genetic variance in the Nucleocapsid protein (Np)- C-terminal domain (CTD) across all SARS-COV-2 variants. We then employed the Shannon entropy method on (Np) sequences collected from the major variants, verifying the CTD with lower entropy (less prone to mutations) than other Np regions. Polyclonal and monoclonal antibodies were raised against this target CTD antigen and used to develop an Enzyme-linked immunoassay (ELISA) test for SARS-CoV-2. Blinded Viral Quality Assurance (VQA) panels comprising of UV-inactivated SARS CoV-2 variants (XBB.1.5, BF.7, BA.1, B.1.617.2, and WA1) and distractor respiratory viruses (CoV 229E, CoV OC43, RSV A2, RSV B, IAV H1N1, and IBV) were assembled by the RADx-rad Diagnostics core and tested using the ELISA described here. The assay tested positive for all variants with high sensitivity (Limit of Detection: 1.72-8.78 ng/mL) and negative for the distractor virus panel. Epitope mapping for the monoclonal antibodies identified a twenty amino acid antigenic peptide on the Np-CTD that an in-silico program also predicted for the highest antigenicity. This work provides a template for a bioinformatics pipeline to select genetic regions with a low propensity for mutation (low Shannon entropy) to develop robust ‘pan-variant’ antigen-based assays for viruses prone to high mutational rates.

Soccer is the leading cause of all sports-related ocular injuries in Europe and Israel and leads to blindness at a disproportionately high rate, especially among children (Thompson et al., 2019). With soccer being the most popular sport in the world, it is surprising the only solution to ocular injuries are sports glasses which can cause direct damage to the eye and impair peripheral vision by 15%, calling for an alternative (Smith & Jones, 2020). This work, based on an imported facial model, focuses on both the qualitative and quantitative aspects of building a personalized, low-cost (through optimizing material needed), superior apparatus to conventional sports glasses. The quantitative side examines a modified and model-validated (through a SRS of thirty unique extrapolated points) multivariate linear regression equation, based on horizontal and vertical rotation angles (n=60) trained with residual and computer simulation data, that can accurately extrapolate and quantify ocular impact from all horizontal and vertical rotation angles and a modified Hertzian Contact Stress Equation to determine the thickness of the apparatus using the elasticity modulus, impact force, and geometrical facial and soccer-ball features. The qualitative side examines where firstly, ocular impact is most prevalent, and secondly, where most impact is seen from rotating the ball horizontally and vertically through analysis of Pearson’s Correlation Coefficient at the supraorbital, medial canthus, infraorbital, and lateral canthus regions from both regression equations as well as a cost-benefit analysis for comparison with conventional sports glasses. The findings discovered in this work lay the groundwork for future research to build a customized low-cost ocular injury prevention device which can simultaneously ensure complete ocular safety while enhancing athletic performance for over 250,000,000 players (Johnson & Garcia, 2022).

This review focuses on an extensive synopsis of the recent improvements in the field of CO2 hydrogenation over structured zeolites including their properties, synthesis methods, and characterization approaches. The role of bimodal mesoporous structures surface oxygen vacancies, and the Si/Al ratio in improving catalytic activity is highlighted. The porosity, thermal stability, and structural integrity are also discussed in the review along with how structured zeolites are affected by electrical and plasma interactions. The synthesis methods are analyzed in detail by comparing the benefits and drawbacks of the bottom-up techniques, such as hard templating, soft templating, and non-templating on the one side; and the top-down approaches, e.g. dealumination, desilication, and recrystallization on the other. This review also draws attention to the necessity of overcoming the difficulties arising from these synthesis techniques, for example, micropore-induced diffusion restrictions and morphological constraints, employing innovative approaches and optimization strategies. Conventional and advanced characterization techniques are pointed out in this respect as crucial for understanding the catalytic mechanism and the dynamic behavior, hence, beneficial in the advancements of research on structured zeolites with higher efficiency and activity. The review ends with a perspective that highlights the necessity of further research in the improvement of synthesis approaches and characterization procedures of the structured zeolites to increase their catalytic activity in CO2 hydrogenation, a critical process of paramount importance in the global effort to reduce excessive carbon emissions and combat climate change..

Drugs are known to cause substantial liver injury, with hepatotoxicity ranging from asymptomatic increase of liver enzymes to hepatic failure. HIV/AIDS patients, with compromised immune systems, are especially vulnerable to opportunistic infections such as tuberculosis (TB). Patients with co-infection frequently get combined antiretroviral (ART) and antitubercular (ATD) regimens, which can cause hepatotoxicity. Hepatotoxicity has been linked to commonly administered antiretroviral drug regimens as well as first-line antitubercular agents such isoniazid, rifampin, and pyrazinamide, which are required for the treatment of both drug-sensitive and drug-resistant tuberculosis. As a result, there is an urgent need to investigate treatments based from traditional herbs known for their hepatoprotective abilities against ART and ATD-induced liver injury. Many researchers have investigated the effectiveness of medicinal plants in treating chemically caused hepatotoxicity. Medicinal plants are high in phytochemicals and secondary metabolites, both of which have a variety of medicinal benefits. Currently, there is a lack of specific therapeutic regimens to address this adverse effect, and management often relies on symptomatic treatment or therapy withdrawal. Traditional medicinal plants may have the potential to restore normal liver function, enzyme activity, and cellular structure in response to ART and ATD-induced hepatotoxicity. This review aims to examine the scientific evidence supporting the use of medicinal plants as hepatoprotective agents against liver damage induced by ART and ATDs.

Certain micronutrients exhibit immunomodulatory effects. However, no intervention has yet investigated the effect of an individualized supplementation on the severity of upper respiratory tract infections (URI). Therefore, we investigated whether a personalized supplementation moderates the incidence and severity of URI. Selenium, zinc, and vitamin D was measured from 59 healthy participants ) in dried blood spots. Accordingly, a personalized supplement was provided with or without the respective micronutrients. We used WURSS-21 questionnaires to assess the disease status. The blood values converged during the intervention and micronutrients no longer differed at the end of the intervention period between treated and untreated volunteers. The incidence and severity of the illness did not significantly differ between the groups. However, when analyzing the WURSS-21 score by the intention to treat, the initially randomized treatment arm revealed a significantly higher score than the placebo arm. Upon acute administration, individualized combination of selenium, zinc and vitamin D does not reduce the number or contribute to a milder course of URIs. Therefore, supplementation in acute infectious situations seems questionable. Further studies must address the habitual diet in more detail to better understand the impact of individual micronutrient status on the prevention of URI.

The vast majority of antibodies generated against a virus will be non-neutralising1. However, this does not denote an absence of protective capacity. Yet, within the field there is typically a large focus on antibodies capable of directly blocking infection (neutralising antibodies, nAbs) of either specific viral strains or multiple viral strains (broadly-neutralising antibodies, bnAbs). More recently, a focus on non-neutralising antibodies (nnAbs), or neutralisation-independent effects of nAbs, has emerged. These can have additive effects on protection or in some cases, be a major correlate of protection. As their name suggests, nnAbs do not directly neutralise infection but instead, through their Fc domains, may mediate interaction with other immune effectors to induce clearance of viral particles or virally infected cells. nnAbs may also interrupt viral replication within infected cells. Developing technologies of antibody modification and functionalisation may lead to innovative biologics that harness the activities of nnAbs for antiviral prophylaxis and therapeutics. In this review, we discuss specific examples of nnAb actions in viral infections where they have known importance. We also discuss the potential detrimental effects of such responses. Finally, we explore new technologies for nnAb functionalisation to increase efficacy or introduce favourable characteristics for their therapeutic applications.

This study aimed to introduce a novel machine learning (ML) model designed to predict the need of interventions during endoscopy in patients with upper gastrointestinal bleeding (UGIB). The risk stratification tools in current use, such as the Glasgow Blatchford Score (GBS) and pre-endoscopic Rockall score, have limitations in accurately predicting the need for endoscopic interventions. All patients diagnosed with UGIB from January 2013 to October 2023 who underwent endoscopy were included in the study. Variables extracted included demographics, social history ,clinical history, clinical presentation and symptoms, drug history, management prior to endoscopy, findings during endoscopy, laboratory variables and vitals, and post-endoscopic results. Three machine learning models including Random Forest Classifier (RFC), Gradient Boosting Classifier (GBC), and AdaBoost Classifier were used to evaluate the need for intervention during endoscopy in our study. A total of 1372 patients were included from three major hospitals in Jordan, of whom 242 underwent endoscopic intervention. The GBC outperformed all other models and pre-endoscopic scores in predicting the need for endoscopic intervention with an area under the curve of 0.861. Findings during endoscopy, platelet count, pulse rate and systolic blood pressure during admission were the most contributing features in predicting the need for the need of endoscopic intervention. This study highlights the potential of machine learning models in enhancing decision making for UGIB management.

Lower limb exoskeletons have the potential to reduce the prevalence of work-related musculoskeletal disorders; however, they often lack user-oriented control strategies. Human-in-the-loop (HITL) controls can adapt an exoskeleton’s assistance in real-time, to optimize the user-exoskeleton interaction. This study presents a HITL control for a knee exoskeleton to minimize the users’ physical effort, a parameter innovatively evaluated by their interaction torque with the exoskeleton (a muscular effort indicator) and metabolic cost. This work innovates by estimating the user’s metabolic cost within the HITL control through a machine-learning model. The regression model was able to estimate the metabolic cost, in real-time, with a root-mean-squared error of 0.66 W/kg and a mean absolute percentage error of 26%, making faster (10s) and less noisy estimations than a respirometer (K5, Cosmed) device. The HITL reduced the user’s metabolic cost and interaction torque by 7.3% and 32.3%, respectively, when compared to a zero-torque control. The developed HITL control surpassed both a non-exoskeleton and a zero-torque condition regarding the user’s physical effort, even for a simple task such as slow walking. Furthermore, the user-specific control enabled a lower metabolic cost than the non-user-specific assistance. This proof-of-concept demonstrated the potential for HITL controls in assisted working.

This paper introduces PatchFusion, an innovative approach for nonrigid tracking and reconstruction of deformable objects using a single RGB-D sensor. Existing methods face challenges in accurately capturing the rapid deformations of soft and flexible objects, thereby limiting their utility in diverse scenarios. Our approach overcomes this challenge by employing a dynamic patch-based framework that adapts to rapid inter-frame motions. Firstly, patch-wise rigid transformation fields for non-overlapping patches are solved via Iterative Closest Point (ICP) by incorporating geometric features as additional similarity constraints, thereby enhancing robustness and accuracy. Secondly, deformation optimization based on a nonrigid solver is applied to refine the coarse transformation fields. In order to enable simultaneous tracking and reconstruction of deformable objects, the patch-based rigid solver is designed to run in parallel with the nonrigid solver, serving as a plug-and-play module requiring minimal modifications for integration while enabling real-time performance. Following a comprehensive evaluation, PatchFusion showcases superior performance in effectively dealing with rapid inter-frame deformations when compared to existing techniques, rendering it a promising solution with broad applicability across domains such as robotics, computer vision, and human-computer interaction.

Background Popular movement-based injury risk screens have been shown to lack predictive precision, leading to interest in multifactorial models. Furthermore, there is a lack of research regarding injury risk assessment for those currently or planning to be recreationally active. This study aims to provide injury risk insights by analyzing multifactorial injury risk models and as-sociated clinical measures in the U.S. population. Methods Data related to injury, inflammatory markers, physical functioning, body composition, physical activity, and other variables from 21,033 respondents were extracted from NHANES. Odds ratios for self-reported injury were calculated for single predictors and risk models. Case-control and principal component analyses (PCA) were conducted to elucidate confounders and identify risk factor clusters, respectively. Receiver operating characteristic analysis was used to test the precision of a risk factor cluster to identify pain points and functional difficulties. Results Sociodemographic, individual, and lifestyle factors were strongly associated with higher odds of injury. Increases in fibrinogen and C-reactive protein were significantly associated with all risk groups. Membership to the high-risk group (age over 40, obesity, no muscle-strengthening activities, sedentary lifestyle, and low back pain) predicted at least one functional difficulty with 67.4% sensitivity and 87.2% specificity. In the injury group, bone turnover markers were higher, yet confounded by age and there was a significantly higher prevalence of self-reported osteoporosis compared to the control. In males, low testosterone was associated with injury, and higher estradiol was associated with pain and functional difficulties. In females, higher levels of follicle-stimulating hormone were associated with functional difficulties. PCA revealed four high-risk profiles, with markers and activities showing distinct loadings. Conclusion A comprehensive approach to injury risk assessment should consider the nexus of aging, lifestyle, and chronic disease to enhance tailored injury prevention strategies, fostering safe and effective physical activity participation and reducing the burden of musculoskeletal disorders.

This retrospective study examines 248 test-bolus examinations preceding contrast-enhanced magnetic resonance angiography (CE-MRA) to extract clinically relevant data for critical limb ischemia (CLI) management. Methods involved a retrospective review of test-bolus exams, analysing 60 graphs for time-to-peak (TTP), full-width half-maximum (FWHM) time, and time to continual rise in signal intensity. These values were correlated with heart function parameters (ejection fraction, ASA-Classification, Lee-Index, and MET-Score). Results indicate a mean TTP of 31.2 ± 7.3s, showing a correlation between ejection fraction and ASA classification. Patients with atrial fibrillation exhibited prolonged TTP compared to those without. Despite population heterogeneity, findings facilitate risk stratification for limb-saving interventions in CLI. TTP emerges as a potential clinical cardiovascular parameter and a risk factor for vascular interventions. Given the variation in injection protocols across centres, this study underscores the importance of precise bolus arrival time documentation for future multicentre studies.

Contemporary global policy, driven by concern for the environment, imposes increasingly stringent goals for reducing CO2 emissions. Therefore, there is an urgent need to develop effective models that allow an accurate prediction of CO2 emissions from vehicles powered by alternative fuels such as CNG. This article presents the process of creating one of the first models of CO2 emission for a vehicle powered by CNG. Emission modelling is based on data obtained from chassis dynamometer tests and road tests using the portable emission measurement system (PEMS). CO2 emission modelling was conducted in Python programming language using the Optuna framework for the XGBoost technique. The models obtained were validated, with indicators R2 0.9 and RMSE 0.49 for data from chassis dynamometer tests, and R2 0.7, RMSE 0.71 for road test data. This work has the potential to be used by transportation decision makers involved in environmental analyses and policymaking for urban areas.

Health comprises physical, mental and social dimensions whose interactions influence users’ experiences. Health experiences are within the context of environments. These contexts are definitive contributors to experiences – primarily because of the link to social dimensions as human beings - psychological and economic. Therefore, the study aims to investigate health resort users’ psycho-social and socio-economic characteristics to improve their access to quality healthcare. The objectives are identifying the socio-economic characteristics of an inclusive health resort, analysing the psycho-social characteristics of the inclusive health resort user, and analysing the effects of users’ psycho-social and socio-economic characteristics on their access to healthcare. The study employs the mixed research method (qualitative and quantitative). The researchers engaged in a pragmatic research philosophy that underscores positivist and interpretivist paradigms. The data collection instruments include survey questionnaires, an interview guide with a digital recorder, a direct participant observation schedule, field notes and photographs. The data analysis process involves the clustering and categorisation of data and examining concepts and themes. The research findings show a correlation between the users’ socio-economic status and access to quality healthcare in an inclusive health resort. The result further reveals that psycho-social and socio-economic characteristics of health resort users are quality healthcare access predictors. Therefore, the users’ social, psychological, and economic status should play a vital role in the design of an inclusive health resort by all stakeholders.

Background: Recent reports on the national temporal trends of sepsis-related mortality in the United States (US) suggested outcome improvement in several race and ethnicity groups. However, it is unknown whether national data reflect state-level trajectories. Methods: We used the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research Multiple Cause of Death dataset to identify all decedents with sepsis in the US during 2010-2019. Negative binomial regression models were fit to estimate national and state-level trends of age-adjusted sepsis-related mortality rates within race and ethnicity groups. Results: There were 1,852,610 sepsis-related deaths in the US during 2010-2019. Nationally, sepsis-related mortality rates decreased among Blacks and Asians, were unchanged among Hispanics and Native Americans, and rose among Whites. The percent of states with similar trends were 30.0% among Blacks, 32.1% among Asians, 74.3% among Hispanics, 75.0% among Native Americans, and 66.7%% among Whites, while trending in opposite direction from 3.6% among Asians to 15.0% among Blacks. Conclusions: National trends in sepsis-related mortality in the US did not represent state-level trajectories in race and ethnicity groups. Gains in sepsis outcomes among race and ethnicity groups at the national level were not shared equitably at the state level.

The gold deposits of the eastern region of Cuba are genetically related to the lithological formations of the island arc and the ophiolitic complex, which have been studied and exploited since the time of the Spanish colonization in the mid-sixteenth century. These deposits are part of the so-called Aguas Claras-Guajabales mineral field, in the Holguín Province (Cuba) and lie in an extensive elongated strip of approximately 15 km in length. The object of this work is to make an orderly, detailed, and chronological review of the geological and mining work carried out in this region as well as to highlight the degree of study achieved in each of the stages of research. To facilitate this work, an extensive bibliographic review of all available materials was planned and carried out, such as reports, manuals, monographs, and articles. The results obtained from this study highlight that gold mineralization is closely linked to metasomatic processes produced by the circulation of hydrothermal fluids that affected different lithologies of both the volcanic island arc and the ophiolitic complex, it is noteworthy that the highest gold contents are mainly where the lithologies contact each other. This highlights the fact that the presence of alterations such as serpentinization, listvenitization, rodingitization and propylitization have played a primary role in the deposition of gold during mineralization processes. This work could be a very useful guide for future research in this region, as it is an orderly, concrete, and practical compilation of the characteristics of the mineralization and alterations, as well as a precise indication of the spatial position, thicknesses, and contents of the gold horizons.

Nitraria tangutorum Bobrov is a berry shrub with white flowers and red fruits, which grows in the deserts in the Tibetan Plateau, Mongolia, and western China. Its fruit N. tangutorum fruit (NTF) contains various bioactive compounds, with anti-fatigue, anti-inflammatory, and neuroprotective functions. However, the high saccharide content of NTF makes it unsuitable for diabetic patients. In this study, we fermented NTF to obtain N. tangutorum fermented juice (NTJ), and N. tangutorum fermented residue (NTR), which are suitable for diabetics to consume. We characterized the bioactive compounds in NTF, NTR, and NTJ, and found that fermentation increased the diversity of bioactive compounds, and greatly reduced sucrose, glucose, and fructose content while generating trehalose, which has the potential to manage blood glucose levels. Further, NTJ displays anti-diabetic potential due to various compounds anti-diabetic properties. This study provides a basis for further clinical research on NTJ's anti-diabetic function in humans.

With the trend of public infrastructure becoming more sustainable, large multi-purpose sports venues (LMPSVs) have become one of the world's most complex architectural projects and one of the landmark buildings of an international city. LMPSVs will lead the world in sustainable design, construction and operational innovations, and play a crucial role in raising awareness of sustainability around the world. System Thinking (ST), System Dynamics (SD) and Sustainable System Development (SSD) theories are three interrelated concepts that together form a methodological framework for solving complex system problems and driving strategies. The purpose of this study is to examine how LMPSVs can implement environmental, social, governance, and innovation (ESGI) enterprise transformation strategy (ETS) based on a sustainable systems development (SSD) framework. In view of the current global environmental challenges and social responsibility requirements, the motivation of this study is to provide an integrated transformation pathway for LMPSVs to achieve the goal of sustainable development and to contribute to the field of related disciplines. The methodology of this research adopts a combination of literature review and case study analysis, and the theoretical basis is mainly drawn from cutting-edge research in the fields of sustainable development, corporate social responsibility (CSR) and environmental management. Then, by analyzing successful transformation cases in China, we extract data and information to explore the application and effectiveness of these strategies in practice. The results of the study show that by implementing ESGI-based transformation strategy, LMPSVs can not only make significant progress in terms of environmental protection, social responsibility, and governance structure, but also drive long-term corporate growth and competitiveness through innovation. Specifically, these results are realized in terms of increased efficiency in energy use, improved waste management, community involvement and increased stakeholder satisfaction. The study concludes by emphasizing that the SSD-based ESGI Transformation Strategic framework provides a sustainable pathway for LMPSVs. In the future, the extension of this transformation strategy will help a wider range of industry sectors to achieve sustainable development goals, and has wide application potential and far-reaching social significance.

The purpose of this study is to investigate the failure mechanism and preventive strengthening methods of prefabricated full length small box girder (PSBG) under car explosion. After damage analysis during blast loads using the commercial software Autodyn, three strengthening methods are presented to improve the blast mitigation performance. The results show that the failure modes and bearing capacity are significantly different with various strengthening measures. Adhering U-shaped steel plate can effectively enhance the shear performance of PSBG under blast loads. Strengthening the bottom of the upper flange of box girder with steel plate can effectively mitigate the local bending failure, and enhance the overall flexural capacity during car explosion.

A case of low level windshear at Beijing Daxing International Airport is studied in the present pa-per. It is related to the synoptic scale/mesoscale changes of the airflow pattern over northern China. The shear was captured well by the Doppler LIDAR at the airport and timely alerts had been issued. This study considers the technical feasibility of forecasting the shear feature using a high resolution numerical weather prediction model with a lead time of several hours. It turns out that the shear feature could be forecast well, and is generally consistent with the actual observations. However, there are still discrepancies between reality and the simulation, such as the strength of the shear and persistency of the feature. More cases of windshear at Daxing airport would be studied in the fu-ture in order to understand the nature of windshear over there.

Diabetes is one of the fastest spreading diseases of civilisation in the 21st century. The aim of the study was twofold: 1) to find differences in personality traits, self-esteem, body- esteem, and imagery between healthy women and women with diabetes 2) to check whether there are differences in analyzed factors in women with diabetes who participate in sports compared to women who do not. We used 3 questionnaires: Imagination: in sport - short form, Self-Esteem Scale (SES), and BFIS Personality, which were tested online. We found that women with diabetes were characterised by significantly higher neuroticism and lower extraversion and higher conscientiousness (marginally significant). We also found that women with diabetes who practice sport rated their bodies more highly in terms of sexual attractiveness and made better use of imagined affirmations than healthy women who were not active. Our study provides new insights into diabetics in terms of coping with the disease.

Introduction The monitoring of cerebral perfusion in patients with brain damage is a major clinical challenge. Monitoring cerebral oxygenation (rSO2) by NIRS was introduced at the turn of the 1980s, and many clinicians believed it was a valuable method for assessing cerebral perfusion and subsequent measures to optimize cerebral flow. The main problem of NIRS usage is the presence of the intermediate structures-skin, skull, meninges, cerebrospinal fluid-and their influence on the outcome of the test. Therefore, it seems that NIRS assessment performed on a patient during brain death attempts, can give an idea of the magnitude of the influence of these intermediate structures on the monitoring result. Case We present a retrospective analysis of cerebral oxygenation measurements of a patient undergoing a brain death diagnostic procedure. A clinical situation where the cerebral blood flow is stopped can give an idea of the specificity of the method, particularly the impact of the influence of intermediate structures on the monitoring outcome. In this case, the NIRS result is increased by the oxygenation of the patient before the apnoea test. The influence of chromophores in the tissues surrounding the CNS, reflections and scattering of the light wave spectrum have a very significant effect on the final result of cerebral saturation measurement. Discussion The majority of research observations describing changes in cerebral perfusion or its optimisation may be burdened by the problem described, i.e. the significant influence of measured oxygenation from intermediate structures. The specificity of NIRS to assess cerebral perfusion requires careful analysis. The therapeutic implications of monitoring cerebral oxygenation with NIRS are of great importance and, from the example presented and the literature provided, the method should be used with caution. It has been shown that in a patient with brain death, the result of NIRS oxygenation measurements depends on the surrounding structures of the brain.

Leaf springs are suspension components constituted of several structural and assembly components. Once the leaves are assembled, a stress state due to the assembly process is developed. Thus, the quantification of the assembly stress level should be known in order to be accounted for in the structural design. The aim of this article is precisely to quantify the assembly stress level in parabolic leaf springs for railway freight wagons. An experimental method with the aid of extensometry is considered to evaluate elastic assembly stresses. Next, a numerical model of the leaf spring assembly process with the required boundary conditions is developed to support the experimental results and allow obtaining a distribution of surface stresses along the master leaf length. The development of this work resulted in a surface stress profile along the length of the master leaf generated by the assembly process, where the deviations of the numerical outcomes regarding the analysed spots with strain gauges are mostly of little relevance.

Biochar (BC) is a carbonaceous material obtained by pyrolysis at 200−1000 °C in the limited presence of O2 of different vegetable and animal biomass feedstocks. BC has demonstrated great potential, mainly in environmental applications, due to its high sorption ability and persistent free radicals (PFRs) content. These characteristics enable BCs to carry out the direct and PFRs-mediated removal/degradation of environmental organic and inorganic contaminants. The types of PFRs possibly present in BC depend mainly on the pyrolysis temperature and the kind of pristine biomass. Since they also can cause ecological and human damage, a systematic evaluation of the environmental behavior, risks, or management techniques of BC-derived PFRs is urgent. PFRs generally could consist of a mixture of carbon- and oxygen-centered radicals, and of oxygenated carbon-centered radicals, depending on the pyrolytic conditions. Here, to promote a more productive and beneficial use of BC and related PFRs and stimulate further studies to make them environmentally safer and less hazardous to humans, we have first reviewed the most common methods used to produce BC, its main environmental applications, the primary mechanisms by which BC remove xenobiotics, as well as the reported mechanisms for PFRs formation in BCs. Secondly, we have discussed the PFRs environmental migration and transformation; we have reported the main PFRs-mediated applications of BCs to degrade inorganic and organic pollutants, the correlated environmental potential risks, and the possible strategies to limit them.

This study explores religious diversity in Romania and how the trends of indices of religious fractionalization and polarization manifest at the county level in the post-communist period. The county is selected as the relevant level for analysis due to its spatial confessional dynamics being more clearly visible. Recent studies have revealed that erosion of diversity represents an important aspect for any country and needs to be considered as an important aspect of democracy. This paper highlights that religious polarization and fractionalization in Romania has been generally maintained, although the regions of Transylvania, Banat, Dobrogea and Western Moldova remain areas where there are different confessions. Besides the general aspect of religion diversity depending the ethnic trends, there is a rise of Pentecostals and Baptists at the county level. This aspect can inform policymakers to create new institutions for dialogue between majority Orthodox communities and Protestants so that potential conflicts do not appear between the Orthodox and emerging religious communities, but also to ensure objective, cultural, religious coherence.

This study investigates the effect of scaffold architecture on bone regeneration, focusing on 3D-printed polylactic acid-bioceramic calcium phosphate (PLA-bioCaP) composite scaffolds in rabbit femoral condyle critical defects. To assess their influence on bone healing and scaffold performance, we explored two distinct scaffold designs, alternate and helical laydown patterns. The scaffolds were meticulously characterized for pore size, strut thickness, porosity, pore accessibility, and mechanical properties. The in vivo efficacy of these scaffolds was evaluated using a rabbit femoral condyle critical defect model. Our findings indicate that both scaffold architectures are biocompatible and support bone formation. The helical scaffolds, characterized by larger pore sizes and higher porosity, demonstrated significantly greater bone regeneration than the alternate structures. However, their lower mechanical strength presented limitations for use in load-bearing sites. This study highlights the importance of scaffold architecture in bone tissue engineering and underscores the need to balance porosity and mechanical strength for optimal bone regeneration. The findings provide crucial insights for the design of 3D- printed scaffolds in clinical applications, particularly in the context of critical-sized bone defects. The study also outlines potential areas for future research, including exploring hybrid scaffold designs to achieve optimal porosity without compromising mechanical integrity.

In Australia, traditional methods of cat management by local government (councils) animal management officers (AMO) have been ineffective, with cat-related calls and cat impoundments continuing to increase, resulting in many healthy cats being euthanized. This has detrimental effects on the mental health of AMOs, pound and shelter staff and veterinarians. The City of Banyule, Victoria implemented a free cat sterilization, microchipping and registration (licensing) program in 2013-14. Initially targeted to three low socioeconomic suburbs with the highest cat-related calls and intake, where enforcement action had little effect. An average of 4.1 cats/1000 residents per year were sterilized over eight years. The program was available to all cats in the area, including stray cats being fed by caregivers, provided they took ownership of the cats. There were no limitations on the number of cats enrolled per household and free transport was provided if required. The program was later expanded city-wide. Over eight years, city-wide cat intake decreased by 66%, euthanasia by 82%, with an increase in proportion of cats reclaimed by owners from a baseline of 6% of intake (2012-13) to 16% (2020-21). Cat-related calls decreased in the target area by 51% and city-wide by 36%. The council’s financial outlay was $84,000, which resulted in decreased costs as-sociated with cat-related calls of $266,225.00. Instead of traditional trap-adopt- kill, proactive management of urban cats based on targeted sterilization should be utilized by government and animal welfare agencies in Australia and internationally. These types of programs are effective at reducing intake and euthanasia and are cost-effective.

This study investigates the historical variability in annual average precipitation in the northwest region of Mexico, aiming to evaluate the cumulative impact of precipitation on soil degradation and associated risks posed by rainfall. Despite being known as "The Agricultural Heart of Mexico," the region's soil has experienced significant damage to its granulometric structure due to unpredictable rainfall patterns attributed to climate change. Sixteen historical series of average annual rainfall were analyzed as stationary stochastic processes for spectral analysis. The results revealed exponential decay curves in each radial spectrum, indicating a linear relationship between frequency and amplitude. These curves identified initial impulses correlated with moments of severity for structural damages caused by rainfall-induced degradation. The degradation process, exacerbated by water stress, accelerates, as evidenced by maps illustrating approximately 75% soil damage. In the context of climate change and the uncertainty surrounding soil responses to extreme meteorological events, understanding this phenomenon becomes crucial. Recognizing the dynamic nature of soil responses to environmental stressors is essential for effective soil management. Emphasizing the need to employ numerical processes tailored to new environmental considerations related to observed soil damages is crucial for sustainable soil management practices in any region.

Background: After the increasingly common anterior cruciate ligament reconstruction (ACLR) procedure in competitive athletes, rehabilitation is crucial for facilitating a timely return to sports (RTS) and preventing re-injury. This pilot study investigates the biomechanical and psychological outcomes of postoperative rehabilitation in competitive athletes, comparing supervised rehabilita-tion (SVR) and home-based rehabilitation (HBR). Methods: After ACLR, 60 (out of 74 screened) athletes were recruited and equally divided into 2 groups using non-probability convenience sam-pling: 30 HBR and 30 SVR (each group comprising 15 males and 15 females). Rehabilitation out-comes in respective groups were evaluated at 8 months using measures (Tegner-Activity-Scale [TAS], International Knee Documentation Committee subjective knee form [IKDC-SKF], ACL Return to Sport after Injury [ACL-RSI]) and objective parameters (isometric muscle strength, hamstring/quadriceps asymmetry). RTS was evaluated at 9 months; with ACL re-injury rates rec-orded approximately 6 months post-RTS. Results: Both groups exhibited decreased TAS scores (HBR: 8 to 6, SVR: 8 to 7), with the SVR group demonstrating superior post-operative IKDC-SKF scores (81.82 vs. 68.43) and lower ACL-RSI scores (49.46 vs. 55.25). Isometric and isokinetic mus-cle strength, along with asymmetry values, favored the SVR group 8 months post-ACLR (p

Aim: M. oleifera, a tree that have medicinal applications. A.hispidum has been utilized in traditional medicine as a cure for microbial and other infections. The aim of this study is to evaluate the bioactive compounds of A.hispidum and M.oleifera and determination of Antioxidant, Anticancer, Antifungal and Antibacterial for their pharmaceutical importance. Methods: Fresh leaves of these plants were collected from Akinmoorin and Awe in Nigeria. Particles Induced X-Ray Emission method was carried out via a 2.5MeV proton beam. Detection of phytochemicals was carried out by HPLC analysis. Disc diffusion method was used to determine MIC for fungi and MIC for bacteria. DPPH radical scavenging activity of these plant leaves was determined. Cancer cells were cultivated using 5% CO2 with 95% air in 100% relative humidity. The adherent cells were seeded and subjected to treatment with increase concentrations of the plant extracts from 48–72 h for anti-cancer activity. Results: The mean ± S.E. of the mean (S.E.M.) for all data were displayed. Three copies of the invitro experiment data were collected. For unpaired data, the student's t-test was applied at P < 0.05, the differences in the data were deemed significant. The ethanolic extracts showed on the average a 50% reduction in cancer cell viability at 24.5μg mL−1 for MO and 16.0μg mL−1 for AH respectively. Conclusions: The results of this study indicated these two plants have Antioxidant, Antitumor, Antifungal and Antibacterial activity and it is recommended that the active constituents be isolated and formulated into suitable dosage form. Keywords: Phytochemical Screening; pharmacological activities; Acanthospermum hispidum; Moringa oleifera.

Newcastle disease (ND) is a viral infection that affects domestic and wild type birds especially poultry and establishing serious economic costs for poultry industry. Newcastle disease virus’ (NDV) HN membrane receptor is attractive therapeutic candidate, contributes to pathogenicity with various functions such as fusion and prevent viral self-agglutination to permit viral spread. No validated HN inhibitor has been reported yet. However, the purpose of current study was to determine potential compounds via pharmacophore-based screening of natural molecules to inhibit HN receptor of NDV. Physicochemical characteristics and phylogenetic analysis were determined to elucidate structural information and phylogeny of target protein across different species as well as members of gene family. Fill missing residues of HN target protein and evaluated via PROCHECK and VERIFY 3D. We employed shape and feature-based pharmacophore model and screen natural compound’s library through numerous scoring schemes. Top 48 hits with 0.8860 pharmacophore fit score were subjected towards structure-based molecular docking. Top 9 compounds was observed witihin the range of -8.9 to -7.5 kcal/mol binding score. Five best-fitting compounds in complex with HN receptor were subjected to predict biological activity and ADMET analysis. Top two hits were selected for MD simulations to validate binding modes and structural stability. Upon scrutinization, A1 (ZINC05223166) emerges as potential HN inhibitor to treat ND, necessitating further validation via clinical trials.

Additive manufacturing (AM) techniques are widely investigated for the cost-effective use of titanium (Ti) alloys in various aerospace applications. One of the AM techniques developed for such applications is plasma transferred arc solid free-form fabrication (PTA-SFFF). Materials manufactured through AM techniques often exhibit anisotropies in mechanical properties due to the layer-by-layer material build. In this regard, the present study investigates the isothermal directional fatigue of Ti-TiB metal matrix composite (MMC) manufactured by PTA-SFFF. This investigation includes rotating beam fatigue test, electron microscopy, and fatigue calculations. The fatigue experiments were performed at 350 ºC using specimen with the test axis oriented diagonally (45º) and parallel (90º) to the AM builds directions. The fatigue values from the current experiments along with literature data find that Ti MMC manufactured via PTA-SFFF exhibit fatigue anisotropy reporting highest strength in 90º and lowest in perpendicular (0º) AM build directions. Further, the electron microscopy investigations on 0º, 45º, and 90º AM build specimens reveal frequent TiB clusters in all three AM build directions and suggest that the spread of these TiB clusters play a role in fatigue anisotropy. Moreover, the fatigue calculations were performed using both the Paris’ and recently reported modified Paris’ equations. Comparison of R^2 values for these calculations show that modified Paris’ equation predicts the fatigue life of AM Ti-TiB MMC more accurately than the Paris’ equation.

The study focused on the technical and scale efficiency of smallholder pineapple farmers in the Central Region of Ghana. The input-oriented Data Envelopment Analysis (DEA) was used to estimate technical, pure and scale efficiencies of the smallholder pineapple farmers, of which a random sampling procedure was used to select 320 respondents. The study revealed that the farmers were technically inefficient with mean technical efficiency under Constant Returns to Scale (CRS), pure efficiency under Variable Returns to Scale (VRS) and the Scale Efficiency levels of 0.505, 0.641 and 0.772, respectively, due to farmers’ inability to exploit fully the available technology while experiencing evident post-harvest losses resulting from low adoption of post-harvest technologies. Such findings are meaningful and could help the farming communities and relevant policymakers to understand the issues in farming production and hence undertake necessary actions to potentially improve farmers’ technical and scale efficiencies in the study area.

Amidst the challenges posed by the COVID-19 crisis, marked variations in individuals' resilience and vulnerability have emerged. This eight-month longitudinal study engaged 535 community adults (58% female, M_age = 43.97) to explore the nuanced aspects of coping and personal growth during the challenging period. Grounded in Self-Determination Theory, the research examines the influence of autonomy support from close others—manifested through active listening and providing choices—on psychological need satisfaction (i.e., autonomy, competence, and relatedness), integrative regulation of emotions; posttraumatic growth; and subjective well-being (positive affect and life satisfaction). Structural equation modeling revealed that, over time, the experience of psychological need satisfaction was intricately related to integrative regulation, posttraumatic growth, positive affect, and life satisfaction. Notably, the impact was partially mediated by autonomy support. These findings shed light on the pivotal role that autonomy supported relationships play in fostering personal growth and meaning making during life's difficult junctures. The study underscores the practical significance of purposeful support from close others and paves the way for future research endeavors.

The COVID-19-medical emergency has ended worldwide, yet there is still a need to evaluate the psychological impact of these years of unprecedented changes on students’ life. Methods: This study aims to assess and compare COVID-19-related stressors (Relationships-and-Academic-Life; Isolation; Fear-of-Contagion) and psychophysical symptoms reported by university students in April-2020, April 2021, and April 2022. The predictive role of COVID-19-related stressors on psychophysical symptoms within each time was also tested. Data were collected among 637 university students in April-2020 (n = 197), April-2021 (n = 200), April-2022 (n = 240). Results: In April-2022, perceived Isolation and Fear-of-Contagion decreased from the peak registered in April-2021, but stress related to Relationships-and-Academic-Life remained noteworthy high. A sharp and ongoing increase in psychophysical symptoms was found, with more than 50% of students reporting clinical levels of Sleep-Disorders, Depression, Psychoticism, and Interpersonal-Sensitivity. In April-2022, students still perceiving stress related to Relationships-and-Academic-Life and Isolation were at risk for Anxiety, Somatization, and Sleep-Disorders, while those still perceiving stress related to Fear-of-Contagion were also at risk for Depression, Obsessive-Compulsive, and Psychoticism. Conclusion: Findings emphasized the long-lasting detrimental effects of the COVID-19-related stress. Interventions must pinpoint the complex post-pandemic adjustment process and their effects on university students' psychophysical health.

Combustion power plants emit carbon dioxide (CO₂), a major contributor to climate change. Direct emissions measurement is cost-prohibitive globally, while reporting varies in detail, recency, and granularity. To fill this gap and greatly increase the number of power plants worldwide with independent emissions monitoring, we developed and applied machine learning (ML) models using power plant plumes as proxy signals to estimate electric power generation and CO₂ emissions using Landsat 8, Sentinel-2, and PlanetScope imagery. Our ML models estimated power plant activity on each image snapshot, and then an aggregation model predicted plant utilization over a 30-day period. Lastly, emissions factors specific to region, fuel, and plant technology were used to convert estimated electricity generation to CO₂ emissions. Models were trained with reported hourly generation data in the US, Europe, and Australia and were validated with additional generation and emissions data from the US, Europe, Australia, Türkiye, and India. All results with sufficiently large sample sizes indicate that our models outperformed baseline approaches. In conducting external validation to compare modeled versus reported annual generation and emissions in the countries where available, we calculated the root mean square error overall for modeled countries with validation data as respectively 1.75 TWh (236 plants across 17 countries over 4 years) and 2.04 Mt CO₂ (207 plants across 17 countries over 4 years). Ultimately, we applied our ML method to plants that comprise 32% of global power plant CO₂ emissions averaged over 2015-2022. This dataset is the most comprehensive independent and free-of-cost global power plant point-source emissions monitoring system currently known to the authors and is publicly available at climatetrace.org to support global emissions reduction.

Forage fish are crucial to human nutrition, especially in developing countries. However, in these countries, most forage fish catches are used to make aquafeeds for aquaculture, which leaves only a small quantity for direct human consumption. This practice increases fish prices in local markets and undermines people's nutrition. Overfishing forage fish for industrial purposes harms the ecosystem, reduces the catch of larger fish, and marginalizes local fishermen. Although previous discussions have touched qualitatively on the ethics and injustice of this practice, this article provides quantitative scales to measure the impact of the practice on the finances and forage fish consumption of low-income consumers using reasonable assumptions and literature values. Increasing the annual supply of forage fish by 25% to the 5 million MT of fresh fish markets globally could save consumers several billion US dollars annually. Families could consume a higher percentage of nutritious fish for less money. Furthermore, leaving forage fish in the sea could benefit wildlife and increase the capture of larger fish, such as mackerel, which are in demand in local markets and fished by local fishermen. The unintentional and involuntary contributions of low-income societies to enable the growth of high-value fish and shrimp for affluent societies seem unjust and warrant further investigation.

E-scooters are a micromobility transportation option for completing short trips. In recent years, many ‎cities welcomed shared e-scooters in an effort to offer more mode choices, increase travelers' ‎convenience, and reduce automobile use in their service areas. However, a knowledge gap still remains ‎regarding the acceptability of shared e-scooters as a transportation option, which motivates additional ‎research on user and non-user preferences and attitudes toward e-scooter use. This study investigates ‎latent variables impacting the adoption of shared e-scooters in urban areas, focusing on mode choice ‎factors and attitudes towards e-scooter use and car use. The study utilizes machine learning (ML) ‎techniques and SHAP analysis to analyze survey data (N=1196) collected from travelers in Washington, ‎D.C., Miami, FL, and Los Angeles, CA, in 2021 and 2022. A comparative analysis is performed to develop ‎comprehensive demographic profiles of e-scooter users. The analysis reveals gender (male), age (25-39 ‎years age group), higher income, and educational background as the most relevant factors toward e-‎scooter use. Attitudinal variations among e-scooter users and non-users underscore the complexity of ‎perceptions toward e-scooter use, with significant differences in mode choice factors and attitudes ‎toward the use of e-scooters and private vehicles. Notably, educational background ranked as a significant ‎factor in Washington, D.C., and Miami, while Factor 3, derived from factor analysis and encompassing car ‎use attitudes and the utilization of technology, emerged as influential in Los Angeles. This research ‎contributes fresh insights into factors shaping e-scooter adoption, offering a foundation for informed ‎urban transportation planning and policymaking. The holistic approach showcased in this study enhances ‎understanding of shared micromobility and its implications for urban mobility.

Garlic, as an important economic crop in China, still has room for improvement in terms of identification using remote sensing technology, Among them, high-precision classification of garlic has become an important subject. The Erhai Lake is an important freshwater lake in China. Under the influence of technology and policies, significant changes have occurred in the cultivation of garlic crops. this study constructed multidimensional features for crop classification suitable for Google Earth Engine, and Propose a method for identifying garlic crops using sample and feature datasets under limited conditions. The results indicate that: 1) In the land-use classification of the Erhai Lake Basin, the importance ranking of characteristic bands, from high to low, is as follows: spectral features, vegetation features, texture features, and terrain features. 2) The Random Forest method based on feature selection demonstrates high classification accuracy in land-use classification within the Erhai Lake Basin in Yunnan Province. The overall classification accuracy reaches 95.79%, with a Kappa coefficient of 0.9481. 3) The expansion direction of garlic cultivation in the Erhai Lake Basin initially strengthened and then weakened from 1999 to 2023. The vertical development of garlic cultivation reached saturation, showing a slow trend towards horizontal expansion between 2005 and 2018. The planting distribution in various townships in the Erhai Lake Basin gradually shifted from a relatively uniform distribution to an upstream development in the basin. This study utilizes the Google Earth Engine (GEE) cloud computing platform and machine learning algorithms to compensate for the lack of statistical data on garlic cultivation in the Erhai Lake Basin. Simultaneously, it accurately, rapidly, and efficiently extracts planting information, demonstrating significant potential for practical applications.

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

This article studies electrostatic fields and potentials in the presence of conductors and point charges under the framework of solving Laplace’s equation with specifi ed boundary conditions. The results demonstrate that many problems posed and solved in elementary electrostatics through various heuristics such as the method of images, can be more rigorously treated under the solution framework of Laplace’s equation.

B4GALNT2 is a vital candidate gene that affects the growth traits litter size in and growth traits of sheep, but whether it has the same function in goats remains to be further investigated. In this study, we utilized 348 Nanjiang Yellow goats as experimental subjects, conducted a whole exon, and the conserved the non-coding region SNP scanning of the B4GALNT2 gene. Our results revealed the presence of a synonymous mutation, rs672215506, within the exon of the B4GALNT2 gene in the Nanjiang Yellow goat population. This mutation was found to be associated with reduced mRNA stability of the B4GALNT2 gene. The results of SNPs detection of conserved non-coding region of B4GALNT2 gene showed that there were five potential regulatory SNPs in the Nanjiang Yellow goat population, except for rs66095343, the ~500 bp fragments of four SNPs (rs649127714, rs649573228, rs652899012 and rs639183528) could significantly increase luciferase activity both in goat skeletal muscle cells and 293T cells . Genetic diversity indexes indicated low or intermediate levels for all six SNPs analyzed, each conforming to Hardy-Weinberg equilibrium regarding genotypic frequencies. Association analysis indicated that rs660965343, rs649127714 and rs649573228 were significantly correlated with growth traits in the later stage of growth and development of Nanjiang Yellow goat. The haplotype combinations of H2H3 and H2H2 had higher body weight and greater body size; moreover, H2H2 haplotype combinations were significantly correlated with the litter size of Nanjiang Yellow goat. The results of our study demonstrate the potential utility of the B4GALNT2 gene as a functional genetic marker in breeding programs for Nanjiang Yellow goats.

Collaborative robotics is a major topic in current robotics research posing new challenges, especially in Human-Robot Interaction. The crucial aspect in this area of research focuses on understanding the behavior of robots when engaging with humans, where reinforcement learning is a key discipline that allows us to explore sophisticated emerging reactions. This review aims to delve into the relevance of different sensors and techniques, with special attention to EEG (electroencephalography data on brain activity) and its influence on the behavior of robots interacting with humans. In addition, mechanisms available to mitigate potential risks during the experimentation process such as virtual reality will also be addressed. In the final part of the paper, future lines of research combining the areas of collaborative robotics, reinforcement learning, virtual reality and human factors will be explored, as this last aspect is vital to ensure safe and effective Human-Robot Interactions.

This study determines the equivalent stress intensity factor (SIF) model that best fits the experimental behavior of low-carbon steel under mixed mode (I and II). The study assessed Tanaka, Richard, and Pook's equivalent SIF models. The theoretical values used for comparison correspond to experimental results in a modified C(T) geometry by machining a hole ahead of the crack tip subjected to fatigue loads with a load ratio of R = 0.1. The comparison involved the SIF for six experimental points and the values computed through the numerical simulation. The Paris, Klesnil, and modified Forman-Newman crack growth models were used with each equivalent SIF to analyze the prediction in the estimated number of cycles. The Klesnil model showed the closest prediction since the error between the calculated and experimentally recorded number of cycles is the lowest. However, the material behavior reflects a reduced crack propagation rate attributed to plasticity in the crack tip. Results suggest that Asaro equivalent SIF conservatively estimates the element lifespan with increasing errors from 2.3% at the start of growth to 27 % at the end of the calculation.

The multifunctional carbon-catabolite repression-negative on TATA box less complex (CCR4-NOT) is a multi-subunit complex present in all eukaryotes, including fungi. This complex plays an essential role in gene expression; however, a functional study of the CCR4-NOT complex in the rice blast fungus Magnaporthe oryzae has not been conducted. Seven genes encoding the putative CCR4-NOT complex were identified in the M. oryzae genome. Among these, a homologous gene, MoNOT3, was overexpressed during appressorium development in a previous study. Deletion of MoNOT3 in M. oryzae resulted in a significant reduction in hyphal growth, conidiation, abnormal septation in conidia, conidial germination, and appressorium formation compared to the wild-type. Transcriptional analyses suggested that the MoNOT3 gene affects conidiation and conidial morphology by regulating COS1 and COM1 in M. oryzae. Furthermore, monot3 exhibited a lack of pathogenicity, both with and without wounding, which is attributable to deficiencies in the development of invasive growth in planta. This result was also observed in onion epidermal cells, which are non-host plants. In addition, the MoNOT3 gene was involved in cell wall stress responses and heat shock. Taken together, these observations suggest that the MoNOT3 gene is required for fungal infection-related cell development and stress responses in M. oryzae.

In the last decade, robotic-mediated rehabilitation has emerged as a potential solution to improve repetitive task training. Each device in this field has a unique development history shaped by engineers’ expertise in specific programming languages or platforms. In this work we adopt an approach that tries to abstract from the final implementation with the aim to make control logic more shareable and understandable. The authors will present the outcomes of the application of a Rapid Control Prototyping strategy to an upper-limb robotic exoskeleton. A model-based design approach implemented on a real-time target machine is presented. This modern design approach was explored with several control strategies and was used to test the exoskeleton’s performances. The proposed method highlights how it is possible to develop the entire control architecture in a single programming environment.

This article is devoted to the problem of genetically coding of inherited cyclic structures in biological bodies, whose life activity is based on a great inherited set of mutually coordinated cyclic processes. The author puts forward and arguments the idea that the genetic coding system is capable of encoding inherited cyclic processes because it itself is a system of cyclic codes connected with Boolean algebra of logic. In other words, the physiological processes in question are cyclical because they are genetically encoded by cyclic codes. In support of this idea, the author presents a set of his results on the connection of the genetic coding system with cyclic Gray codes, which are one of many known types of cyclic codes. This opens up the possibility of using for modeling inherited cyclic biostructures those algebraic and logical theories and constructions that are associated with Gray codes and have long been used in engineering technologies: Karnaugh maps, Hilbert curve, Hadamard matrices, Walsh functions, dyadic analysis, etc. Additionally, the connections of these constructions with statistical rules of genomic DNAs and binary-genomic numbers are considered.

Edible oils have commercial and nutritional value due to the presence of essential fatty acids. They can be consumed fresh in the form of capsules known as nutraceuticals. The quality of such products is of interest to the consumer. In this context, this study describes a method based on high resolution nuclear magnetic resonance (NMR) and Fourier transform mid-infrared spectroscopic analysis (FTIR), combined with statistical analyzes to differentiate different edible oils used as nutraceuticals in Brazil by fatty acid content. Through the analysis of 1H NMR spectra, the levels of saturated and unsaturated fatty acids in edible oils were characterized and quantified. Statistical analysis of the data confirmed the real distinction between nutraceutical raw materials, with emphasis on ω-9, ω-6 and ω-3 fatty acids. The analytical approach presented also demonstrated potential to identify the origin (animal or vegetable) of edible oils used as nutraceuticals.

Detecting the presence of explosives is important to protect human lives in military conflicts and peacetime. Gas-phase detection of explosives can make use of the change of material properties, which can be sensitive to environmental conditions such as temperature and humidity. This paper describes a remote-controlled automatic shutter method for environmental impact assessment of photoluminescence (PL) sensors under near-open conditions. Utilizing the remote-sensing method, we obtained environmental effects without being exposed to sensing vapor molecules, and explained how PL intensity was influenced by the temperature, humidity, and exposure time. We also developed a theoretical model including the effect of exciton diffusion for PL quenching, which worked well under limited molecular diffusions. Incomplete recovery of PL intensity, or degradation effect, was considered as an additional factor in the model.

In the present work, the interactions between hydrocortisone and cyclodextrins were investigated. The cyclodextrins selected for this study were hydroxypropyl-α-cyclodextrin, hydroxypropyl-β-cyclodextrin and hydroxypropyl-γ-cyclodextrin. The study was carried out using density measurements, 1H-NMR and FT-IR spectroscopy. Preliminary studies show that hydroxypropyl-α-cyclodextrin has a low affinity for hydrocortisone, while hydroxypropyl-β-cyclodextrin and hydroxypropyl-γ-cyclodextrin have a good affinity for hydrocortisone in both solid state and solution. The study was carried out at two temperatures: 298.15 K and 310.15 K. The results suggest that at both temperatures, the system 2-HP-β-CD + HC induces an increase in the solvent structure, with increasing the solute concentration in the solution, while on the contrary the system 2-HP-γ-CD + HC induces a decrease in the solvent structure when the concentration of the solute in the system increases.

Biotechnological potential of Thermoanaerobacter strain AK15 to produce ethanol and valuable alcohols from carbohydrates and amino acids were evaluated in present study. The strain is highly ethanologenic, producing a maximum of 1.57 mol ethanol per mol of glucose degraded at high liquid-gas phase ratios. The strain degrades most of the sugars tested as well as starch and pretreated hydrolysates of biopolymers (Whatman paper, newspaper, Timothy grass, Rhubarb leaves, and several macroalgae species) to ethanol mainly. The strains degraded serine and threonine when used as a single substrate, producing mainly acetate and ethanol as end products, and the branched-chain amino acids (leucine, isoleucine, valine) when cultivated in the presence of thiosulfate. The main end products from branched-chain amino acids were a mixture of their corresponding branched-chain fatty acids and alcohols. Finally, the strain was also shown to use butyrate as an electron sink during glucose degradation resulting in the reduced product butanol in addition to end products produced from glucose. Thus, strain AK15 is a promising candidate for ethanol and fine chemical production from a range of lignocellulosic and algal biomass.

Glioblastoma, a deadly brain tumor, shows limited response to standard therapies like te-mozolomide (TMZ). Recent findings from the REGOMA trial underscore a significant survival improvement offered by regorafenib (REGO) in recurrent glioblastoma. Our study aimed to propose a 3D ex vivo drug response precision medicine approach to investigate recurrent glio-blastoma sensitivity to REGO and elucidate the underlying molecular mechanisms involved in tumor resistance or responsiveness to treatment. 3D glioblastoma organoids (GB-EXPs) obtained from 18 patients’ resected recurrent glioblastoma tumors were treated with TMZ and REGO. Drug responses were evaluated using NAD(P)H FLIM, stratifying tumors as responders (Resp) or non-responders (NR). Whole-exome sequencing was performed on 16 tissue samples, and whole-transcriptome analysis on 13 GB-EXPs treated and untreated. We found 35% (n=9) and 77% (n=20) of tumors responded to TMZ and REGO, respectively, with no instances of TMZ-Resp be-ing REGO-NR. Exome analysis revealed a unique mutational profile in REGO-Resp tumors compared to NR tumors. Transcriptome analysis identified distinct expression patterns in Resp and NR tumors, impacting Rho GTPase and NOTCH signaling, known to be involved in drug response. In conclusion, recurrent glioblastoma tumors were more responsive to REGO com-pared to TMZ treatment. Importantly, our approach enables a comprehensive longitudinal ex-ploration of the molecular changes induced by treatment, unveiling promising biomarkers in-dicative of drug response.

In horses, quantitative assessment of gait parameters, as the use of inertial measurement units system (IMUs), might help in the decision-making process. However, it requires financial investment, is time-consuming, and lacks accuracy if displaced. An innovative Artificial Intelligence marker-less Motion Tracking System (AI-MTS) may overcome these limitations in the field. Our aim was to compare the level of agreement and accuracy between both systems and visual clinical assessment. Twenty horses underwent locomotion analysis by visual assessment, IMUs and AI- MTS systems, in the following conditions: straight hard (SH), straight soft (SS), left and right circle hard (LCH, RCH) and soft (LCS, RCS). A greater number of horses were considered sound by clinical examination, compared to those identified as symmetric by the two gait analysis systems. More limbs were considered asymmetric by the AI-MTS compared to IMUs, suggesting its greater sensitivity. The greatest agreement between the two systems was found for the difference between two minima in vertical head position in SH, while the lowest for the difference between two minima in vertical pelvis position in SS, reflecting the difficulties in assessing asymmetry of hindlimbs. Some degree of asymmetry may be clinically relevant, suggesting its regular use in training horses.

Antimicrobial resistance (AMR) is a worldwide healthcare problem. Multidrug resistant organisms (MDRO) have the ability to spread quickly owing to their resistance mechanisms. Although colonized individuals are crucial MDRO dispensers, colonizing microbes have the potential to turn pathogenic under certain conditions, leading to symptomatic infections in carriers. Carbapenemase producing Enterobacterales (CPE) are among the most important MDRO involved in infections and colonizations, associating with multiple resistance mechanisms and virulence factors, causing infections with severe outcomes. All research papers identified in the most comprehensive online databases which contained information related to the topic of this article were analyzed, and relevant data was extracted and included. The first information on CPE could be traced back to the mid-2000s, but pertinent data for many African countries was established in the past 5-8 years. Information is presented chronologically for each country. Although no clear conclusions could be drawn for some countries, it was observed that CPE colonizations are present in most African countries and carbapenem-resistance levels are rising. The most common CPE involved are Klebsiella pneumoniae and Escherichia coli, and the most prevalent carbapenemases are NDM-type and OXA-48-type enzymes. Prophylactic measures, such as screening, are required to combat this phenomenon.

In rock blasting for mining production, stress waves play a major role in rock fracturing along with explosion gases. Better energy distribution improves fragmentation and safety, lowers production costs, increases productivity, and controls ore losses and dilution. Blast outcomes vary significantly with the choice of the explosive and the properties of the rock mass encountered. This study analyzes the effects of rock mass and explosives properties on the blast outcomes through numerical simulation using data from the case study and later validates the simulation results from the field blast fragmentation. The outcomes suggest that, for a given set of rock properties, the choice of explosive has a major influence on the resulting fragmentation. Strong explosives favor large fracture extents in hard rocks, while less strong explosives offer a better distribution of explosive energy and fractures. The presence of rock structures such as rock con-tacts and joints influences the propagation of stress waves and fractures depending on the structures' material properties, intensity and orientations, and the direction and strength of the stress wave. To achieve effective fragmentation, the blast design should mitigate the effect of variability in the rock mass by ensuring adequate energy distribution within the limits of geo-metrical design.

Background: Waterborne diseases pose a significant global public health threat, compelling enhanced comprehensive surveillance. This study investigates the current infectious disease and antimicrobial resistance (AMR) surveillance systems, including wastewater and environmental surveillance (WES), in three sub-Saharan African countries: Tanzania, Burkina Faso, and the Democratic Republic of the Congo (DRC). The three countries have their specificities regarding wastewater networks and logistic systems. So, emphasizing the need to strengthen existing disease surveillance, the paper advocates for incorporating WES systems specifically designed for countries' context to monitor waterborne and re-emerging pathogens, as well as AMR.Methods: National workshops were conducted to assess the current clinical and environmental surveillance systems and identify priority pathogens for new environmental monitoring. Data were collected through surveys from experts in academia, research, policy, and healthcare. Results: Prioritized pathogens for WES include waterborne (poliovirus, Salmonella Typhi, Vibrio cholerae), respiratory (influenza A&B, SARS-CoV-2), other (Measles and Rubella, Mycobacterium tuberculosis). Recommended AMR pathogens include drug-resistant Mycobacterium tuberculosis, Salmonella spp., methicillin-resistant Staphylococcus aureus, and extended-spectrum beta-lactamase and carbapenemase-producing E. coli. Tanzania, Burkina Faso, and the DRC employ DHSI2-based centralized electronic systems for clinical data collection, complemented by Excel and paper-based registries. The WES approach is commonly employed for monitoring poliovirus and rarely for AMR and other pathogens. Discussion and conclusions: WES is a valuable tool for early detection of locally circulating human-derived pathogens, aiding in outbreak detection, data-driven epidemic response, and prevention. The availability of WES results underscores the importance of effective sanitation for safeguarding human, animal, and environmental health. WES is a pivotal tool for integrated risk management, preventing waterborne outbreaks, protecting drinking water sources, and ultimately gaining various UN Sustainable Development Goals. The study highlights the importance of customized WES systems in line with each country's context, emphasizing localized approaches for effective monitoring of waterborne pathogens and AMR.

Measuring and predicting Carbon Emission (CE) is important to enabling the main culprit of various urgent environmental issues including global warming. However, prior studies did not fully incorporate the impact of micro-level urban streetscapes, which might lead to biased prediction of urban CE. To fill the gap, we developed an effective framework to predict residential CE in urban areas from widely existing and publicly available street-view images (SVI) using machine learning. First, we used a semantic segmentation algorithm to classify more than 30 streetscape elements from SVI images to describe the built environment whose features might affect residential and transportation CE. Second, based on the streetscapes quantified, we trained a 10-fold cross-validation method with various machine learning models to predict the CE at the 1KM grid level using CE data from the PlanetData. We found first, built environment features such as sidewalks, roads, fences, buildings, and walls are significantly correlated with the residential CE. Second, the presence of buildings and subtle streetscape features (e.g., walls, fences) indicates higher-density residential areas which are related to more residential CE. Third, vegetation (e.g., trees and grass) are reversely related to residential CE. Our findings shed light on the feasibility of using a single and open data source (i.e., the SVI) to effectively model neighborhood-level CE for regions across diverse urban forms. Our framework is useful for urban planners to inform new town development and urban regeneration towards the low CE goals.

To better understand how immunity develops against SARS-CoV-2 during the pandemic period of 2020 to 2022, we analyzed the immune response of a small group of university staff and students who were either infected or vaccinated. We investigated the levels of receptor-binding domain (RBD)-specific and nucleocapsid (N)-specific IgG and IgA antibodies in serum and saliva samples taken early (around 10 days after infection or vaccination) and later (around 1 month later), as well as N-specific T-cell responses. One patient who had been infected in 2020 developed serum RBD and N-specific IgG antibodies, but declined 8 months later, then mRNA vaccination in 2021 produced a higher level of anti-RBD IgG than natural infection. In the vaccination of naïve individuals, vaccines induced anti-RBD IgG, but it declined after 6 months. A third vaccination boosted the IgG level again, albeit to a lower level than after the second. In 2022, when the Omicron variant became dominant, familial transmission occurred even among vaccinated people. In infected individuals, the levels of serum anti-RBD IgG antibodies increased later, while anti-N IgG peaked earlier. The N-specific activated T cells expressing IFN- or CD107a were detected early. In saliva, SARS-CoV-2-specific IgG but not IgA was detected. Interestingly, two individuals showed a temporary peak in RBD- and N-specific IgA antibodies in their saliva on the second day after infection. Thus, SARS-CoV-2 infection triggers typical immune responses in humans against acute viral infections, but mucosal immune responses, which are temporarily induced early during infection, may be more important for protection than current intramuscular vaccines.

The ageing global population and changing labor force participation are having a profound impact on state pension programs worldwide, including Malaysia. However, the effects of an ageing workforce and declining fertility rates are having a significant impact on future trends in labor force participation and the duration of retirement. This paper presents an innovative examination of labor force participation rate (LFPR) forecasting within the context of an aging workforce, utilizing the Lee-Carter and Cairns-Blake Dowd stochastic models, traditionally applied to mortality data. By adapting these models to LFPR data, the study offers a novel perspective on predicting workforce participation trends and understanding the dynamics of retirement planning from year 2001 to 2047. Additionally, by incorporating the mortality forecasts from the United Nations, the research navigates through the complexities of applying actuarial methods to labor economics, revealing differentiated pathways for male and female participation in the labor market and the anticipated length of retirement. This study offers a unique comparison between the Lee-Carter and the Cairns-Blake-Dowd (CBD) LFPR models. It focuses on fitting and forecasting the LFPR of senior employees aged 50 to 64. The results highlighted discrepancies among models that demonstrated evidence of model risk for extended retirement duration.

AbstractThe escalating impact of artificial intelligence (AI) has birthed the fascinating technology of deepfakes, capable of meticulously crafting hyper-realistic audio-visual manipulations. Within the realm of healthcare, this technology presents a double-edged sword, brimming with potential for revolutionizing various facets of care delivery while simultaneously harboring significant ethical and practical challenges. This research delves into the complex narrative surrounding AI deepfakes in healthcare, meticulously analyzing both the exciting opportunities they offer, and the inherent risks associated with their implementation.Background:Traditional healthcare practices face limitations in patient engagement, accessibility, and training efficacy. Deepfakes, with their ability to simulate real-world scenarios and interactions, emerge as a potential solution, offering personalized patient education, immersive mental health interventions, remote consultations with virtual avatars, and realistic training simulations for medical professionals.Objective:This research aims to comprehensively understand the multifaceted impact of AI deepfakes in healthcare systems. It seeks to: Identify and analyze the potential benefits of deepfakes in specific healthcare applications. Assess the ethical and practical challenges associated with deepfake implementation in healthcare settings. Propose recommendations for safe, responsible, and ethical integration of deepfakes within the healthcare system.Results/Conclusion:The research findings illuminate a landscape replete with opportunities and challenges. Deepfakes offer the potential to enhance patient education, personalize mental health interventions, facilitate remote consultations, and revolutionize medical training. However, concerns regarding misinformation, ethical breaches, data privacy, and technical limitations pose significant challenges.The conclusion emphasizes the need for a balanced approach that capitalizes on the innovative potential of deepfakes while mitigating potential harm. Collaborative efforts involving healthcare professionals, technologists, and policymakers are crucial for establishing ethical frameworks, ensuring responsible development, and harnessing the positive power of deepfakes to build a future where healthcare benefits from cutting-edge technology while prioritizing patient well-being and ethical principles.

The increasing global concern over plastic waste and its environmental impact has led to a growing interest in the development of sustainable packaging alternatives. This study focuses on the innovative use of expired dairy products as a potential resource for producing edible packaging materials. Expired dairy products, which are typically discarded, contribute to food waste and environmental pollution. By modifying these products to packaging materials, a dual-purpose solution addressing both waste reduction and sustainable packaging is evaluated. Expired milk and yogurt were selected as the primary raw materials due to their protein and carbohydrate content. The extracted casein was combined with various concentrations of chitosan while in some cases glycerol was used. The materials were characterized with attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy and X-ray analysis (XRD) to examine the interactions between the components of the formed binary blend. Scanning electron microscopy (SEM) was used to evaluate the surface morphology of the blends, while dynamic mechanical analysis (DMA) and tensile experiments were conducted to study the thermomechanical properties of the materials. Barrier properties, including water vapor transmission (WVTR) and oxygen permeability (OTR), were measured to assess the materials' potential to preserve food freshness. The findings reveal that expired dairy-based edible packaging materials exhibit promising mechanical properties, comparable to conventional plastic packaging. The barrier properties and especially the zero oxygen permeability of the membranes, indicate that these materials have the potential to effectively protect food products from external factors that could compromise quality and shelf life. The materials show encouraging signs of eco-friendliness, with a notable reduction in environmental persistence compared to conventional plastic packaging.

Predictions of crop production in the Chi basin are of major importance for decision support tools in countries such as Thailand, which aim to increase domestic income and global food security by implementing the appropriate policies. This research aims to establish a predictive model for predicting crop production for an internal crop growth season prior of harvest at the province scale for fourteen provinces in Thailand's Chi basin between 2011 and 2019. We provide approaches for reducing redundant variables and multicollinearity in remotely sensed (RS) and meteorological data to avoid overfitting models using correlation analysis (CA) and variance inflation factor (VIF). Temperature condition index (TCI), normalized difference vegetation index (NDVI), land surface temperature (LSTnight), and mean temperature (Tmean) were the resulting variables in the prediction model with a p-value &lt; 0.05 and a VIF &lt; 5. The baseline data (2011–2017: June to November) were used to train four regression models, which revealed that eXtreme Gradient Boosting (XGBoost), random forest (RF), and XGBoost achieved R2 values of 0.95, 0.94, and 0.93, respectively. In addition, the testing dataset (2018–2019) displayed a minimum root mean square error (RMSE) of 0.18 ton/ha for the optimal solution by integrating variables and applying the XGBoost model. Accordingly, it is estimated that between 2020 and 2022, the total crop production in the Chi basin region would be 7.88, 7.64, and 7.72 million tons, respectively. The results demonstrated that the proposed model is proficient at greatly improving crop yield prediction accuracy when compared to a conventional regression method and that it may be deployed in different regions to assist farmers and policymakers in making more informed decisions about agricultural practices and resource allocation.

: AliCPT-1 is the first Cosmic Microwave Background (CMB) experiment in China, dedicated to achieve accurate measurements of B-mode polarization. Situated in Ali of Tibet, China, this telescope is currently undergoing deployment and will operate in two frequency bands centered at 90 and 150 GHz. The Far-Field Flat Mirror（FFF）is a calibration device of AliCPT-1 telescope for far-field beam mapping. The design of FFF is optimized for easy assembly and adjustment. Meteorological station data reveals that the maximum wind speed near FFF is 17.5 m/s, while the maximum wind speed on the windward side is 8 m/s. The wind pressure on FFF was analysed using a maximum wind speed of 17.5m/s as the input condition, based on the fluid-structure coupling method in ANSYS. The results demonstrate that it is safe and reliable when withstanding combined gravity and wind pressure loads. The torque on the mount is within the motor rated torque. The flatness of the FFF reflective surface can be adjusted to an RMS value of 0.05 mm when taken into account the effect of gravity and assembly accuracy. The deformation caused by the maximum wind loads is approximately 0.0587 mm under the protection of wind-proof wall. The combined deformation is 0.077 mm in RMS value combining the two influences, which is less than 1/20 of wavelength. The FFF mirror assembly is stable and precisely for telescope calibration.

The effects of chemical composition and solidification rate on the solidification behavior of high-Cr white irons were investigated through directional solidification. Increasing the solidi-fication rate in hypoeutectic alloys caused the finer dendrite arm spacing as expected. The eutec-tic structure which formed in the interdendritic region comprised of M7C3 and austenite, how-ever, secondary dendrite arms of hypoeutectic alloys contained a few M7C3 particles that solidi-fied prior to the eutectic structure. The transition from cellular to dendritic solidification oc-curred at a solidification rate between 50 µm/s and 100 µm/s in a near eutectic alloy. In the near eutectic alloy with cellular solidification, a directionally arrayed in-situ composite of M7C3/austenite formed within the cell. Speckle-like feature appeared in the intercellular region due to M23C6 carbide precipitation during subsequent cooling after freezing. Like dendrite arm spacing in hypoeutectic alloys, the inter-speckle spacing and the inter-fibre spacing became finer with increasing solidification rate in the cellular solidification range.

The article presents the issues related to load sharing in direct current grid and a novel control method which has advantages over known solutions. Unlikely of many similar sounding papers this article shows attempt of creation fully controllable non-isolated system which allows load sharing between permanent magnet alternator equipped with machine side converter (MSC) and dual active bridge (DAB) tied to batteries or supercapacitor. The power sharing is essential feature of parallel connected direct current generators and all types of voltage sources in this way are contributing power to the system. Such system should have possibility of the rapid voltage build up in the case of sudden electrical load changes. To keep the optimal efficiency of the alternator the rotational speed changes according to proper mapping of driving combustion engine. When rotational speed is too low then sudden electrical load can cause significant voltage drop and time needed for voltage build up will vary according to RPM increase. In such situations the undervoltage system can trip the breaker and finally there may be a blackout. To avoid such problem the DC systems which consist of batteries and supercapacitor were introduced. System components include a self-excited synchronous generator (SESG) operating at variable shaft speed as well as batteries and supercapacitors that provide electricity for sudden electrical load changes on the distribution grid. The core of presented system is in power distribution method which consists of programmed controllers structure allowing precise currents distribution. A novelty in the proposed method is the use of a cascaded system of current and DC voltage regulators which allows power distribution precise control. In contrary to previously presented solutions, the proposed system allows fast and accurate control of currents loading parallel connected DC voltage sources for wide range generator speed changes. In presented solution both converters have been equipped with Schottky diodes preventing flow of equalizing currents between closed transistors in the parallel mode of operation. An experimental test-stand of the described system is presented with its theoretical basis and experimental results.

Feedback from the earthquake zone in Kahramanmaraş, Turkey has established that the emerging field of Crisis Translation and Interpreting (CTInt) requires a free smartphone application, to enable Crisis Translators and Interpreters (CTIs) to access multilingual terminology resources on-/offline when assisting Search and Rescue (SAR) teams responding to man-made and/or natural disasters.The aim is to design not only a multilingual compilation of Crisis Terminology (CTerm), downloadable to smartphones enabling access when there is a failure in the internet connection, but also a unified search tool which will browse and redirect the user to existing termbanks when the internet is accessible. Nevertheless, terminological records available in the domain of CTerm are inadequate and dispersed, with different interfaces and language combinations, requiring enhancement and harmonisation. Furthermore, automated translation and interpreting software/systems supported by the multilingual compilation of the crisis terminology portal (CTermPort) ideally need to be developed or, alternatively, existing ones integrated into the crisis termbank (CTermBank) collection for those who would lack the support of CTIs.The design of the CTermPort will significantly impact civil societies by providing a lifesaving tool for CTIs who need a reliable terminological reference point and automated translation options, and those unable to be assisted. In this respect, the project also promises strong prospects of sustainability past the project duration, as the tool to be developed will serve international SAR teams working closely with CInts during response times, but also medical staff in field hospitals collaborating with CTIs in rehabilitation and recovery phases, and beyond.

Healthy eating is a vital component of a sustainable daily life, especially after the pandemic of COVID-19. In this study we investigated the perceptions and attitudes of the members of a Greek University community especially the young members of this on: i) health itself, ii) healthy eating, and iii) healthy eating campaigns today. The research was conducted in the last three months of 2023, via a questionnaire survey electronically, and 1406 members-consumers, participated. Sta-tistical analysis included descriptive and cluster analysis to group respondents into homogenous segments was performed by employing One-Way Anova. The highlights of the results indicate that consumers perceive physical, mental health and energy efficiency as health preconditions, while they perceive a balanced and sustainable diet as the main parameter of healthy eating. They are influenced mostly by doctors and health providers and use information mostly based on common sense and upbringing for their healthy eating choices. The cluster analysis revealed two distinctive groups of consumers categorized by this study as the “approachables”(54,5%) effected by the todays sustainable knowledge and concepts on healthy eating, and the “conservatives” (45,5%) who they reluctant to accepted these as such.

The performance analysis of the internal/external flows around a high speed vehicle in near-space is fundamental and critical to the configuration and structure design for high speed aircraft. In this paper, the two-dimensional coupled implicit Reynolds Average Navier-Stokes (RANS) solver and RNG k–ε turbulence model is employed to numerically simulate the flow field of an integrated high speed vehicle. The flow field are divided three parts to solve separately and compared with that solved by integrated simulation. The flow field are decomposed to save computer storage and simulation time. The first part is inlet/isolator, the second part is combustion chamber and the third is nozzle. In the computation process, the outlet condition of isolator is endowed to the inlet boundary of combustion chamber and the outlet boundary of combustion chamber is endowed to the inlet boundary of nozzle, then the whole flow field of integrated high speed vehicle is solved. Aerodynamic characteristic of fragment-computation and integration-computation is comparatively analyzed at different angles of attack, the results show that the maximum deviation of lift coefficient obtained by fragment-computation is less than 3% compared with that by integration, the maximum deviation of drag coefficient fragment-computation is less than 5% compared with that by integration, while pitching moment coefficient deviation less than 12%. However, for simulation time-consumption, the time used by fragment-computation reduces 45% compared with integration-computation. Meanwhile, by components force analysis, it can be concluded that the aerodynamic property of inlet/isolator can been obtained separately and hardly effected by other parts.

Everyone should therefore consistently get access to enough and safe water. The operation of the existing distribution network as well as the proper optimization and implementation of the new distribution systems are required for a sufficient and safe water supply. In Sekota town sufficient amount of water was not reached to the beneficiaries due to shortage of water at the source. The primary goal of this study was to evaluate the performance and optimize the existing Sekota water supply distribution system using Bentley Water GEMS.The system's hydraulic modeling is carried out by considering as a continuous supply system, and the evaluation procedure used the extended period simulation approach after calibration was done. Calibration is used to ensure the performance of the model using the observed pressure values. The output of the existing system shows pressure is very high means above the maximum pressure and velocity is very low at peak hour demand. The results of velocity and pressure before optimization have negative effect on the performance of the system. The number of pipes and junctions their velocities and pressures which were in admissible ranges are 15 and 42 pipes for velocities and zero and 59 junctions for pressure before and after optimization were evaluated respectively.

Avian Influenza viruses (AIVs) has posed a significant pandemic threat since their discovery. This review mainly focuses on the epidemiology, virology, and pathogenesis, and treatments of avian influenza viruses. We delve into the global spread, past pandemics, clinical symptoms, severity, and immune response related to AIVs. The review also discusses various control measures, including antiviral drugs, vaccines, and potential future directions in influenza treatment and prevention. Lastly, by summarizing the insights from the previous pandemic control, this review aims to direct effective strategies for managing future influenza pandemics.

Verticillium wilt (VW) is an important and widespread disease of cotton and once established is long lived and difficult to manage. In Australia, the non-defoliating pathotype of Verticillium dahliae is the most common, and extremely virulent. Breeding cotton varieties with increased VW resistance is the most economical and effective method of controlling this disease and is greatly aided by understanding the genetics of resistance. In this study, VW resistance was investigated in 240 F7 recombinant inbred lines (RIL) derived from a cross between MCU-5 that has good resistance and Siokra 1-4 which is susceptible. Using a controlled environment bioassay, we found that resistance based on plant survival or shoot biomass was complex but with major contributions from chromosomes D03 and D09, with genomic prediction analysis estimating a prediction accuracy of 0.73 based on survival scores compared to 0.36 for shoot biomass. Transcriptome analysis of MCU-5 and Siokra 1-4 roots uninfected or infected with V. dahliae revealed that the two cultivars displayed very different root transcriptomes and responded differently to V. dahliae infection. Ninety-nine differentially expressed genes were located in the two mapped resistance regions and so are potential candidates for further identifying the genes responsible for VW resistance.

Glucagon-like peptide-1 (GLP-1) is an incretin hormone that acts on the pancreas to increase insulin and decrease glucagon secretion. Albuminuria is the pivotal marker for diabetic nephropathy, which is the leading microvascular complication of diabetes mellitus. Most of the previous studies mainly focused on the clinical trials of the therapeutic renal protective effect after administration of GLP-1 receptor agonists (GLP-1 RAs), not prior to administration. Therefore, this study aimed to investigate the association between fasting plasma GLP-1 levels and albuminuria before GLP-1 RA administration. A cross-sectional study was designed to evaluate the association between fasting plasma GLP-1 levels and albuminuria in patients with type 2 diabetes mellitus (T2DM). A total of 68 T2DM participants were analyzed from the data at Wonkwang University Hospital in Iksan, Korea. Logistic regression analysis was performed to evaluate the odds ratio (OR) and 95% confidence interval (CI) of the incidence of albuminuria between the GLP-1 low group (Group L) and the high group (Group H). The OR (95% CI) for the incidence of albuminuria comparing the Group L with the Group H of fasting plasma GLP-1 levels was 3.410 (1.160-10.023), p = 0.026 after adjustment for age, gender, fasting plasma glucose, HbA1c, C-peptide, the use of ACE inhibitors or ARBs, SGLT-2 inhibitors, and DPP-4 inhibitors. As a continuous variable, the OR (95% CI) for the incidence of albuminuria associated with the reduction of each 1 pmol/L in fasting plasma GLP-1 levels was 1.673 (1.173-1.870), p = 0.018, after full adjustment. This study showed the negative association between fasting plasma GLP-1 levels and the incidence of albuminuria in Korean patients with T2DM, before GLP-1 RA administration. This result suggests that endogenous GLP-1 may play a role in attenuating albuminuria.

In a digitally oriented society, smartphones provide continual online accessibility to daily life, while simultaneously predisposing adolescents to engage in prolonged connections for various purposes, thus escalating the risk of Internet Addiction (IA). Cognitive processes such as multitasking and attentional shifting are frequently associated with smartphone activities. Additionally, online engagements may serve as emotional strategies for regulating negative states (e.g., boredom and distress), redirecting attention towards more gratifying activities, such as social media content. This study delves into cognitive-emotional processes (emotion regulation, attention impulsiveness, online vigilance, and multitasking) and emotional/behavioural factors (emotional problems, conduct problems, hyperactivity/inattention, peer relationships, and prosocial behaviours) that may be implicated in smartphone activities and technology addiction among adolescents. A community sample (N=676) of Italian high school students (42.2% females) completed the Smartphone Distraction Scale (SDS), the Strength and Difficulties Questionnaire for internalizing/externalizing symptoms (SDQ), and the Internet Addiction Test (IAT) to assess the presence and severity of IA. The scores on the Smartphone Distraction Scale were found to be positively associated with IA levels. Furthermore, students exhibiting higher internalizing/externalizing symptoms, particularly those with traits of Attention Deficit Hyperactivity Disorder (ADHD), are more likely to manifest problematic smartphone usage. The implications for screening adolescents more susceptible to developing IA symptoms and for implementing preventive interventions are discussed.

The storm 'Daniel' has caused the most severe flood phenomenon that Greece has ever experienced, with thousands of hectares of farmland submerged for days. This led to sediment deposition in the inundated areas, which significantly altered the chemical properties of the soil, as revealed by extensive soil sampling and laboratory analysis. Causal relationships between soil chemical properties and sediment deposition were extracted using the DirectLiNGAM algorithm. Results of causality analysis showed that the sediment deposition affected the CaCO3 concentration in the soil. Also, causal relationships were identified between CaCO3 and available phosphorus (P-Olsen), as well as between sediment deposit depth and available manganese. The quantified relationships between the soil variables were then used to generate data using a Multiple Linear Perceptron (MLP) regressor for various levels of deposit depth (0, 5, 10, 15, 20, 25 and 30 cm). Then linear regression equations were fitted across the different levels of deposit depth to determine the effect of deposit depth on CaCO3, P, and Mn. The results show that there is a linear slope of 0.12, -0.16, and 0.13, for CaCO3, P, and Mn with deposit depth, respectively. Statistical analysis indicates that corn growing in soils with sediment over 10 cm requires a 31.8% increase in P rate to prevent yield decline. Additional notifications regarding cropping strategies in the near future are also discussed.

Population events such as natural disasters, pandemics, extreme weather, and wars might cause jumps that have an immediate impact on mortality rates. The recent COVID-19 pandemic has demonstrated that these events should not be treated as nonrepetitive exogenous interventions. Therefore, mortality models incorporating jump effects are particularly important to capture the adverse mortality shocks. The mortality models with jumps, proposed by Cox. et al. , Chen and Cox , and Özen and Şahin , which we consider in this study, differ in terms of the duration of the jumps - transitory or permanent, frequency of the jumps, and size of the jumps. To illustrate the effect of jumps, we also consider benchmark mortality models without jump effects, such as the Lee-Carter , Renshaw and Haberman and the Cairns-Blake-Dowd models. We discuss the performance of all the models by analysing their ability to capture the mortality deterioration caused by COVID-19. We use data from different countries to simulate the mortality rates for the pandemic years and examine their accuracy in forecasting the mortality jumps due to the pandemic. Moreover, we also analyse the impact of mortality jump models on catastrophe bond pricing.

Diabetic retinopathy (DR), a major complication of prolonged diabetes, poses a significant risk of vision loss. Early detection is critical for effective treatment, yet traditional diagnostic methods by ophthalmologists are time-consuming, costly, and subject to variability. This study introduces a novel approach employing a hybrid Convolutional Neural Network-Radial Basis Function (CNN-RBF) classifier integrated with Multi-Scale Discriminative Robust Local Binary Pattern (MS-DRLBP) features for enhanced DR detection. We implemented advanced image preprocessing techniques, including noise reduction, morphological operations, and Otsu’s thresholding, to optimize blood vessel segmentation from retinal images. Our method demonstrates exceptional performance in screening DR, achieving an average of 96.10% precision, 95.35% sensitivity, 97.06% specificity, and 96.10% accuracy. These results significantly outperform traditional methods and offer a promising tool for remote and efficient screening of DR. Applied to publicly available datasets, this research contributes to the development of accessible, accurate diagnostic methods in ophthalmology, potentially reducing the global burden of diabetic vision loss.

Developing prolonged antigen delivery systems that mimick the long-term exposure to pathogens appears as a promising, still poorly explored approach to reach durable immunities. In this study, we have used a simple technology by which his-tagged proteins can be assembled, assisted by divalent cations, as supramolecular complexes with progressive complexity, namely protein-only nanoparticles and microparticles. Microparticles produced out of nanoparticles are biomimetics of secretory granules from the mammalian hormonal system. Upon subcutaneous administration, they slowly disintegrate, acting as an endocrine-like secretory system, and rendering the building block nanoparticles progressively bioavailable. The performance of such materials, previously validated for drug delivery in oncology, has been tested here regarding the potential for time-prolonged antigen release. This has been done by taking, as building blocks, a nanostructured version of p30, a main structural immunogen from the African swine fever virus (ASFV). By challenging the system in both mice and pigs, we have observed unusually potent pro-inflammatory activity in porcine macrophages, and long-lasting humoral and cellular responses in vivo, which might overcome the need for an adjuvant. The robustness of both innate and adaptive responses tag, for the first time, these dynamic depot materials as a novel and valuable instrument with transversal applicability in immune stimulation and vaccinology.

Keywords: Innovation ecosystems, Economic sustainability, Hydrocarbon-based economies, Economic diversification, Qualitative approach

The purpose of this study was to evaluate the morpho-functional change of the patellar ligament in dogs affected by cranial cruciate ligament rupture. The hypothesis is that it may show increased thickening and stiffness with increasing days from trauma to diagnosis. Understanding this aspect have implications on the choice of timing to treat patients suffering from cranial cruciate ligament rupture, and also in the contextualization of patellar ligament desmitis pictures after surgical treatment with tibial plateau levelling osteotomy or tibial tuberosity advanced. Thirty-three dogs were affected affected by unilateral cranial cruciate rupture were examined and divided into three groups based on the time elapsed from the onset of lameness to diagnosis: Group 1 (from 1 to 15 days), Group 2 (from 16 to 60 days), Group 3 (over 60 days). Conventional B-mode ultrasonographic and elastosonographic examinations of patellar ligament were performed without sedation for each dog. At the ultrasonographic examination, all dogs showed alterations in the echostructure of the patellar ligament. In addition, the patellar ligament tended to become harder and less soft with increasing days after rupture, although there were not significant differences between groups. Our results showed that as time increases between the onset of cranial cruciate ligament rupture and diagnosis and treatment, the patellar ligament progressively thickens and loses its elasticity.

Heat waves are a significant consequence of climate change threatening public health by increased morbidity and mortality. The aim of this study was to estimate individuals’ knowledge, attitudes and practice related to heat waves. We conducted an exploratory cross-sectional study in Greece during September 2023. We employed a convenience sample of 1055 participants. We used the heat wave knowledge, awareness, practice and behavior scale (HWKAPBS) to measure our outcome. We measured several socio-demographic variables, such as gender, age, educational level, etc. as potential determinants. Mean scores for the knowledge, awareness, practice and behavior factors were 12.5, 22.7, 22.2 and 12.1 respectively. Females had higher scores on the four factors compared with males. We found a positive relationship between self-perceived health status and awareness, practice and behavior about heat waves. Similarly, we identified a positive relationship between self-perceived financial status and awareness and behavior about heat waves. Increased age was associated with increased practice score, while increased educational level was associated with increased knowledge score. Additionally, behavior score was higher among participants in urban areas than those in rural areas. We found statistically significant positive correlations between the four factors. Levels of knowledge, awareness, practice and behavior about heat waves were high in our sample. Several socio-demographic variables affect participants’ knowledge, awareness, practice and behavior concerning heat waves.

Buildings are rapidly becoming more digitized, to a large extent due to developments in IoT. This will provide many opportunities but also a number of challenges. One of the central challenges in the process of digitizing buildings is the ability to monitor the building’s status effectively. This monitoring is essential for various services that rely on information about the presence and activities of individuals within different areas of the building. Occupancy information, including people counting, occupancy detection, location tracking, and activity detection, plays a vital role in the management of smart buildings. In this article, our primary focus is on the use of Passive Infrared (PIR) sensors for gathering occupancy information. PIR sensors are among the most widely used sensors for this purpose due to their consideration of privacy concerns, cost-effectiveness, and low processing complexity compared to many others. Despite numerous literature review articles in the field of occupancy information, there currently isn’t a specialized literature review dedicated to occupancy information derived specifically from PIR sensors.Therefore, this study analyzes articles that specifically explore the application of PIR sensors for occupancy information. This article provides a comprehensive literature review of PIR sensor technology from 2015 to 2023, with a focus on applications in people counting, activity detection, and localization (traking and location). It consolidates findings from a number of articles that have explored and enhanced the capabilities of PIR sensors in these interconnected domains. This review thoroughly examines the application of various techniques, machine learning algorithms, and configurations for PIR sensors in indoor building environments, emphasizing not only the data processing aspects but also their advantages, limitations, and efficacy in producing accurate occupancy information.These developments are crucial for improving building management systems in terms of energy efficiency, security, and user comfort, among other operational aspects.These developments are crucial for improving building management systems in terms of energy efficiency, security, and user comfort, among other operational aspects. The paper seeks to offer a thorough analysis of the present state and potential future advancements of PIR sensor technology in efficiently monitoring and understanding occupancy information by classifying and analyzing improvements in these domains.

FacioScapuloHumeral Dystrophy (FSHD) is one of the most prevalent inherited muscle disorders, and is linked to the inappropriate expression of the DUX4 transcription factor in adult muscles. The deregulated molecular network causing FSHD skeletal muscle dysfunction and pathology is still not well understood. It has been shown that the hypoxia response factor HIF1α is critically disturbed in FSHD and has a major role in DUX4 induced cell death. In this study, we further explore the relationship between DUX4 and HIF1α. We found that the DUX4 and HIF1α link differed according to the stage of myogenic differentiation and was conserved between human and mouse muscle. Furthermore, we found that HIF1α knock-down in a mouse model of DUX4 local expression exacerbated DUX4-mediated muscle fibrosis. Our data indicate that the suggested role of HIF1α in DUX4 toxicity is complex and that targeting HIF1α might be challenging in the context of FSHD therapeutic approaches.

The microglia, displaying diverse phenotypes, play a significant regulatory role in the development, progression, and prognosis of Parkinson's disease. Research has established that glycolytic reprogramming serves as a critical regulator of inflammation initiation in pro-inflammatory macrophages. Furthermore, the modulation of glycolytic reprogramming has the potential to reverse the polarized state of these macrophages. Previous studies have shown that levetistilide A (LA), a phthalide component derived from Angelica sinensis, possesses a range of pharmacological effects, including anti-inflammatory, antioxidant, and neuroprotective properties. In our study, we have examined the impact of LA on inflammatory cytokines and glucose metabolism in microglia induced by lipopolysaccharide (LPS). Furthermore, we explored the effects of LA on the AMPK/mTOR pathway and assessed its neuroprotective potential both in vitro and in vivo. The findings revealed that LA notably diminished the expression of M1 pro-inflammatory factors induced by LPS in microglia, while leaving M2 anti-inflammatory factor expression unaltered. Additionally, it reduced ROS production and suppressed IκB-α phosphorylation levels as well as NF-κB p65 nuclear translocation. Notably, LA exhibited the ability to reverse microglial glucose metabolism reprogramming and modulate the phosphorylation levels of AMPK/mTOR. In vivo experiments further corroborated these findings, demonstrating that LA mitigated the death of TH-positive dopaminergic neurons and reduced microglia activation in the ventral SNpc brain region of the midbrain and the striatum. In summary, LA exhibited neuroprotective benefits by modulating the polarization state of microglia and altering glucose metabolism, highlighting its therapeutic potential.