Lithium ascorbate (LiAsc) is a non-toxic lithium salt (LD50>5000 mg/kg) with normothymic and neuroprotective properties. Chemoreactomic modeling of LiAsc predicted possible hepatoprotective effects which were tested here on a rat model of a non-alcoholic fatty liver disease (NAFLD) with multiorgan pathology caused by combined intake of excess saturated fats (palm oil), carbohydrates (fructose) and inorganic iron salt (ferrous sulfate). Dynamics of biochemical parameters (biomarkers of liver function, kidneys, hematopoiesis, inflammation, thrombus formation, etc.) and histological evidence of hemosiderosis in the model upon reproduction of the model are described. Experimental confirmations of the hepatoprotective effects of LiAsc were obtained. Comparison of the effects of LiAsc with the effects of myoinositol (a substance with known hepatoprotective properties) shown a number of differences in pharmacological action. Both LiAsc and MI lowered ferritin, transferrin saturation, serum iron, AST, ALT, serum creatinine, leukocytes (LiAsc to a greater extent) and normalized lowered serum protein and glomerular filtration rate. However, only LiAsc lowered heightened reticulocytes (absolute and fraction) and platelets towards the corresponding reference intervals, normalized levels of vitamin B12 in blood and lowered the number of Kupffer cells in liver that were overloaded with iron (contained Prussian blue in morphometric studies). In a clinical perspective, hepatoprotective properties of a neuroprotector and it’s potential to reduce hemosiderosis might be useful for treating patients with hepatic encephalopathy.

The construction of an anaerobic digester coupled with post-digestion low level aeration for agricultural wastewater treatment is described. The digester employs underwater speakers to accelerate the anaerobic digestion process while retaining solids to reduce the strength of the effluent. The digester effluent is sent to a holding tank and fed at a low flow rate to an aeration tank to effect partial nitrification of the wastewater. The outlet of this tank is sent to a settling tank to retain biomass that developed in the aeration tank and the effluent is sent to a small, constructed wetland to further reduce wastewater nitrogen and phosphorus. The wetland was planted with the broadleaf cattail, Typha latifolia, and hence to a retention basin. The system has reduced energy consumption due to both the use of underwater sonic treatment and low-level aeration that is not designed to achieve full nitrification/denitrification but rather to achieve a mixture of ammonium, nitrite, and nitrate that might foster the development of a consortium of organisms (i.e. nitrifiers, Anammox bacteria) that can remediate wastewater ammonium at low cost. Biogas is sent to an inground condenser where different treatments may be tested to remove carbon dioxide and hydrogen sulfide. The system is meant to serve as a complex where various technologies and practices can be evaluated to improve the treatment of agricultural wastewater.

This research article investigates the application of artificial intelligence (AI) in human resource management (HRM) within the Australian commercial media sector, addressing a critical gap in scholarly knowledge. Despite increasing interest in AI’s potential, there is a lack of consensus among managers and HR professionals regarding its application. Through qualitative interviews with 22 industry professionals, this study examines perceptions, understanding, and the potential for leveraging AI across key HRM functions. Findings indicate significant potential for AI to enhance HRM processes, particularly in job/work design and staffing. This research contributes to a deeper understanding of AI’s role in HRM and offers insights to optimize organizational efficiency and effectiveness in the Australian commercial media sector.

This research explores the role of transparency and traceability in the agricultural food supply chain. By utilizing blockchain's decentralized and secure features, stakeholders can improve information sharing from farm to consumer, transparency and traceability issues. Real-world examples illustrate blockchain's successful application in agriculture, boosting transparency, efficiency, and trust and create immutable records, enhance visibility, and provide reliable data, while combating fraud and promoting sustainability. It also examines blockchain's impact on food safety through IoT and smart contracts, highlighting successful implementations in supply chain management, the research underscores blockchain's potential to build consumer trust in food safety, quality, and origin.

Effective pain management in laboratory animals is crucial for both animal welfare and the reliability of scientific research. We retrospectively examined the effects of carprofen as post-operative analgesia in Sprague Dawley rats following stereotactic surgery. Our data indicate that administering carprofen twice daily (5 mg/kg), as currently recommended by GV-SOLAS, led to adverse effects such as reduced food and water intake, disrupted fecal excretion, and abdominal bloating consistent with peritonitis. Continued administration exacerbated these symptoms, with post-mortem findings of intestinal obstructions and ulcers. However, when the frequency was reduced to once daily, such adverse symptoms were not observed. These results are based on incidental data collected from various neuroscientific experiments, resulting in small and uneven sample groups across various experimental cohorts. The inherent imbalances in these groups present challenges for statistical interpretation. While the findings suggest that less frequent carprofen use may reduce adverse effects, the surgical interventions and concurrent use of other drugs in these experiments likely exacerbated these outcomes. Further investigation into the interactions between carprofen, surgical stress, and other perioperative factors is needed to refine analgesia protocols in laboratory animals. Despite these limitations, these observations contribute to understanding analgesia protocols and may assist in improving animal welfare practices.

The rapid development of advanced AI technologies poses serious existential threats and necessitates research on safe and responsible Human-AI alignment. We hypothesize that the evolution of AI may be viewed not as something accidental or artificial, but as a natural part of the evolution of intelligence in living species. This perspective suggests a different view of the Human-AI relationship, where AI is not seen as a threat or a mere enhancement of humans, but as a mean of revealing and establishing true human nature — achieving greater freedom and self-determination. While in previous evolutionary stages, more freedom was attained through inculturation, AI can serve as a tool in the next stage by providing a direct connection between individuals and culture, overcoming the limitations of traditional cultural acquisition processes and giving rise to post-human free beings. A specific step-by-step framework rooted in cognitive evolution theories is proposed, along with potential directions for empirical research.

Virtual Reality (VR) is increasingly used in neuropsychological assessments due to its ability to simulate real-world environments. This study aimed to develop and evaluate the Trail Making Test in VR (TMT-VR) and investigate the effects of different interaction modes and gaming skills on cognitive performance. A total of 71 young female and male adults (aged 18-35) with high and low gaming skills participated in this study. Participants completed the TMT-VR using three interaction modes: eye-tracking, head movement, and controller. Performance metrics included task completion time and accuracy. User experience, usability, and acceptability of TMT-VR were also examined. Results showed that both eye-tracking and head movement modes significantly outperformed the controller in terms of task completion time and accuracy. No significant differences were found between eye-tracking and head movement modes. Gaming skills did not significantly influence task performance using any interaction mode. Participants reported high usability, acceptability, and user experience for the TMT-VR. Eye-tracking facilitated higher accuracy, while head movement higher speed. The TMT-VR offers high usability and user experience and is well accepted by the participants. The findings suggest that VR-based assessments can effectively measure cognitive performance without being influenced by prior gaming skills, indicating potential applicability for diverse populations.

This essay examines the complex interplay between human rights developments in Saudi Arabia and the country's Vision 2030 initiative, which aims to modernize its social, economic, and political landscape. The research question posed is: How are human rights being addressed within the framework of Vision 2030? The goal of the essay is to provide a qualitative analysis of the reforms and policies emerging under Vision 2030, highlighting both advancements and ongoing challenges. Key discussions include historical human rights perspectives, specific strategies aimed at enhancing women’s rights and labor rights, and the implications of legal reforms. The essay draws upon a range of scholarly sources to underscore the intricate relationship between human rights improvements and socio-economic objectives in Saudi Arabia. The main conclusions suggest that while significant strides have been made, particularly in women's empowerment and labor rights, substantial obstacles—rooted in cultural norms and institutional practices—persist. Ongoing international scrutiny and a robust domestic dialogue on human rights remain critical for the success of these reforms. The essay ultimately advocates for sustained efforts to uphold human rights as a cornerstone of the Vision 2030 agenda.

Event detection provides a crucial foundation for intelligent text analysis and supports numerous downstream applications. However, existing detection models often fail to meet the high accuracy requirements and typically require a human–machine collaborative detection mode involving “machine detection followed by manual audit and correction.” Analysis reveals that the recall rate of machine detection is a major factor limiting the efficiency of human–machine collaboration. To address this at its root and ensure high recall, an event trigger recommendation task is introduced, and a span-based recommendation model for Chinese, SpETR (Span-based Event Trigger Recommender), is developed. This model integrates confidence information from both trigger identification and event classification stages to recommend candidate triggers and their event types for each event. To enhance recall, a semantic boundary smoothing method is proposed, which assigns soft labels to spans around gold triggers based on semantic completeness and part-of-speech, combined with a modified focal loss function to make the model predictions smoother. Experiments on DuEE and a self-built dataset show that SpETR is most effective when the number of recommendations is set to 3, achieving recall rates of 97.76% and 98.70%, respectively, comprising improvements of 4.30% and 5.22% over the optimal baseline models. In terms of human–machine collaborative detection, SpETR saved 30.6% and 25.8% of time compared to traditional detection models on two datasets, and the average F1 score of the annotation results was also improved by 5.35% and 3.48%, respectively.

Aims: To investigate the road safety concerns associated with pet dogs in New Zealand. Methods: An online survey was developed and offered to New Zealanders via SurveyMonkey© from 8 January 2019 to 31 March 2019) using New Zealand residents aged ≥18 years. Questions about the demographics of respondents and their number of pet dogs along with those about dog transportation and dog roaming were asked. Results: Of 2744 respondents who completed the online survey, 1494 (65%) owned a dog. Of these, 1511 completed the question about how their dog or dogs travel in vehicles. Of these, 2 % (n = 29) let their dog sit on the driver's knee, and 12 % (n = 179) allowed their dog to sit on the passenger's knee. Only 7 % (n = 105) allowed the dog to roam free throughout the vehicle, while 44% (n = 663) allowed their dogs to roam free in the backseat area only and 19% (n = 280) put their dog in the boot/hatchback area. A minority of respondents (2%, n = 22) indicated they let their dog travel unrestrained on the deck of a ute or truck. Approximately half, 51% (n = 767) of the respondents, indicated that they restrained or crated their dogs in or on the vehicle. Respondents also expressed concerns about roaming dogs being a road safety hazard with the themes of responsible ownership, physical and psychological harm, and the dangers of rescue altruism emerging. Conclusions: Increased awareness about proper pet restraints during transportation and preventing dogs from roaming, especially near and on roads, is crucial to ensure traffic safety for humans and dogs.

Purpose: This study investigates the influence of human brands on the formation of Generation Z's digital identity. Given the increasing importance of the digital space in this generation's life, understanding how their identity is shaped by human brands in this environment is crucial. Method: Using a netnographic approach, qualitative data was collected and analyzed from 500 posts and interactions of Gen Z users on Instagram and TikTok platforms. Thematic content analysis was conducted using NVivo 12 software, with inter-coder reliability confirmed (κ = 0.85). Findings: Results indicate that human brands influence Gen Z's digital identity through three main mechanisms: 1) lifestyle emulation (β = 0.42, p < 0.001), 2) value alignment (β = 0.38, p < 0.001), and 3) self-presentation modeling (β = 0.35, p < 0.01). Multiple regression analysis showed these three factors explain 67\% of the variance in digital identity formation (R² = 0.67, F(3,496) = 335.42, p < 0.001). Conclusion: This study demonstrates that human brands play a significant role in shaping Generation Z's digital identity. Understanding this influence can help marketers and policymakers design more effective strategies for engaging with this generation.

Human papillomavirus (HPV) is the most sexually transmitted infection associated with the development of cervical cancer. This study investigated cervical HPV prevalence, characteristics and distribution according to age and human immunodeficiency virus (HIV) among women attending public community health facility in the Eastern Cape Province of South Africa. A total of 325 participants (aged 18 to 60) visiting a community health facility for any reason were recruited. Cervical HPV infection was detected using the Seegene Anyplex™ II HPV28 assay. Overall HPV prevalence was 65.2% (95% CI: 59.9–70.2%), with the highest prevalence of 80.9% (95% CI: 67.2–89.8%) observed in the 18–25 years age group and lowest prevalence of 46.3% (95% CI: 35.8–57.1%) in 46–60 years of age. HR-HPV infection was found to decrease with increasing age among women who were HPV infected by any type (p=0.02), but not when stratified according to HIV status. A proportion of 12.9% (42/325) were infected with one or more HPV types covered by the Cervarix® HPV vaccine (HPV-16 and/or -18), 18.8% (61/325) by those covered by Gardasil®4 (HPV-6, -11, -16 and/or -18) and 42.2% (137/325) by those covered by Gardasil®9 (HPV-6, -11, -16, -18, -31, -33, -45, -52 and/or -58). Alpha-9 HPV species were the most dominant species (40.6%, 132/325), followed by alpha-7 species (29.8%, 97/325). In the overall population, alpha-9 HPV species were always part of the most dominant HPV alpha species co-infection, which were alpha-9 and -7 species (17.5%, 57/325), alpha-9 and -5 species (9.8%, 32/325), and alpha-9 and -6 species (9.5%, 31/325). High overall HPV, HR-HPV, and alpha-9 species prevalence were observed among women attending the public health facility. These findings contribute to the limited HPV distribution data among Eastern Cape women, which could be used to improve HPV-related policy and assess the effectiveness of the HPV vaccination.

Pluripotent stem cells (PSCs) hold many potential research and clinical benefits due to their ability to differentiate into nearly every cell type in the body. They are often used as model systems for early stages of ontogenesis to better understand key developmental pathways, and for drug screening. However, in order to fully realise the potential of PSCs and their translational applications, a deeper understanding of developmental pathways, especially in humans, is required. Several signalling molecules play important roles during development and are required for proper differentiation of PSCs. The concentration and timing of signal activation is important, with perturbations resulting in improper development and/or pathology. Bone morphogenetic protein (BMP) is one such key signalling molecule involved in the specification and differentiation of various cell types and tissues in the human body including tooth and otic development. In this review, we describe the role of BMP signalling and its regulation, the consequences of BMP dysregulation in disease and differentiation, and how PSCs can be used to investigate the effects of BMP modulation during development, mainly focusing on otic development. Finally, we emphasise the unique role of BMP4 in otic specification and how refined knowledge in controlling its regulation could lead to the generation of more robust and reproducible human PSC-derived otic organoids for research and translational applications.

Due to the inherent limitations of a single viewpoint, reconstructing 3D human meshes 1 from a single image has long been a challenging task. While deep learning networks enable us to 2 approximate the shape of unseen sides, capturing the texture details of the non-visible side remains 3 difficult with just one image. Traditional methods utilize Generative Adversarial Networks (GANs) 4 to predict the normal maps of the non-visible side, thereby inferring detailed textures and wrinkles 5 on the model’s surface. However, we have identified challenges with existing normal prediction 6 networks when dealing with complex scenes, such as a lack of focus on local features and insufficient 7 modeling of spatial relationships.To address these challenges, we introduce EMAR—Enhanced 8 Multi-scale Attention-driven Single Image 3D Human Reconstruction. This approach incorporates 9 a novel Enhanced Multi-Scale Attention (EMSA) mechanism, which excels at capturing intricate 10 features and global relationships in complex scenes. EMSA surpasses traditional single-scale attention 11 mechanisms by adaptively adjusting the weights between features, enabling the network to more 12 effectively leverage information across various scales.Furthermore, we have improved the feature 13 fusion method to better integrate representations from different scales. This enhanced feature fusion 14 allows the network to more comprehensively understand both fine details and global structures 15 within the image. Finally, we have designed a hybrid loss function tailored to the introduced attention 16 mechanism and feature fusion method, optimizing the network’s training process and enhancing the 17 quality of reconstruction results.Our network demonstrates significant improvements in performance 18 for 3D human model reconstruction. Experimental results show that our method exhibits greater 19 robustness to challenging poses compared to traditional single-scale approaches.

Maternal obesity and gestational diabetes mellitus (GDM) are the most common metabolic conditions with have unfavourable impact on maternal and fetal health. Key biosubtrats such as apelin, vascular endothelial growth factor (VEGF), leptin, and DNA methylation play crucial roles in these pathologic conditions. Apelin is a peptide involved in regulating glucose metabolism and cardiovascular functions. This molecule also interacts with the apelin receptor to enhance glucose uptake, suggesting potential therapeutic implications for managing GDM and obesity. Leptin, a hormone predominantly produced by adipose tissue, regulates appetite and energy balance. In obesity, leptin levels are often high, but a resistance to its effects develops, disrupting normal metabolic processes. Similarly, in GDM, elevated leptin may impair glucose metabolism and contribute to insulin resistance. VEGF is critical for angiogenesis, the formation of new blood vessels, and is often found in increased concentrations in obese individuals and those with GDM. This elevation may contribute to abnormal placental function and vascular complications, exacerbating both conditions. DNA methylation, an epigenetic modification, plays a crucial role in gene expression regulation. In both GDM and obesity, altered DNA methylation patterns have been observed, affecting genes involved in metabolism, inflammation, and insulin sensitivity. These epigenetic changes may predispose individuals to metabolic disorders. In our study we investigated placental apelin, leptin, VEGF, and DNA methylation interconnection in the pathophysiology of GDM and obesity during gestation. They have similar or different influencing on metabolic regulation, vascular function, and gene expression in GDM and obesity? Sonogpahic examinatios supported the metabolic analyses for that understanding their roles may lead to better management and therapeutic strategies for these conditions.

Background/Objectives: Human Papillomavirus (HPV)-related biomarkers, specifically E6 oncoproteins and anti-E6 antibodies, have emerged as promising indicators for detecting HPV-associated oral cavity cancers through salivary fluid analysis. This study assessed the survival outcomes of oral cancer patients who were double positive for these candidate biomarkers. Methods: Using biosensor immunoassays, we simultaneously detected E6 oncoprotein and anti-E6 antibodies in oral rinse fluids from patients with advanced T3/T4 oral cancer. Results: Preliminary findings revealed that over one-third of these patients had detectable HPV-related biomarkers in their saliva, with 37.9% testing positive for E6 oncoprotein and 31.0% showing elevated anti-E6 antibody levels. Double positivity was observed in 24.1% of cases. Although survival rate differences between the groups were not statistically significant, the double positivity subgroup demonstrated a trend toward improved survival outcomes compared to single-positive or double-negative patients. Conclusions: These initial results suggest that simultaneous detection of E6 oncoprotein and anti-E6 antibodies could be potential saliva-based biomarkers for clinical applications. Using surface plasmon resonance (SPR) techniques to identify double positivity may enhance early detection of HPV-related oral cancer, potentially informing more effective treatment strategies in clinical practice.

Based on our interest in properties of human movement, we investigated Japanese GPS data, and arrived at the following three observations: 1) there is a strong correlation between the area of polygons created by human movement trajectories and their perimeters; 2) short-distance movement trajectories less than 5 km tend to enclose a large area like a circle; 3) long-distance movement trajectories over 5 km tend to be straight. We also clarified the following four observations on individual attributes and external factors related to long-distance movements: 1) women tend to travel more linearly than men; 2) linearity is stronger on weekends and national holidays in areas with a large theme park; 3) linearity is weaker on weekends and holidays in areas with many historical tourist attractions; 4) these variations are created by people visiting such areas. These properties should be incorporated when modeling the movement trajectories of humans.

Poland suffered an epidemic of louse-borne typhus from 1916-1923, with 400,000 cases and more than 130,000 deaths. The causative factors were depressed economic conditions and a refugee crisis that engulfed Poland after World War I. The recognition of the epidemic in 1919 stimulated the creation of the League of Red Cross Societies (LRCS). However, the LCRS had limited resources and the Poles requested help from other governments and the League of Nations (LoN). The United States sent the American-Polish Relief Expedition to conduct delousing. However, the Polish-Soviet War of 1920 disrupted typhus control and exacerbated the refugee situation. The LoN belatedly organized an underfunded Epidemic Commission. The LCRS sent a research team that did ground-breaking work on the pathology of typhus. Into 1921, the epidemic continued, driven by refugees from typhus-stricken Russia. By 1924, typhus cases were finally approaching pre-World War I levels. Multiple factors lead to the amelioration of the epidemic. The repatriation of prisoners of war and displaced civilians had concluded by 1923. Also, there had been a steady influx of sanitary, food, economic, and medical aid from various organizations into Poland since 1919. Administratively, within Poland, the anti-typhus campaign was also conducted more effectively by the Extraordinary Epidemic Commissariat.

(1) Background: Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a lifesaving treatment but carries a high infection risk. Diagnosing infections remains challenging due to the limited accuracy of standard biomarkers. (2) Methods: This single-center study aimed to evaluate presepsin (PSP) and YKL-40 as infection biomarkers in febrile patients during the allo-HSCT pre-engraftment phase. Biomarker levels were prospectively measured in 61 febrile episodes from 54 allo-HSCT patients at admission, representing baseline levels and then at Day 1, 3, 5, and 7 following fever onset. The diagnostic value was compared to that of procalcitonin (PCT). (3) Results: PSP showed fair diagnostic value on Day 1 (AUC 0.656; 95% CI: 0.510 – 0.802) and Day 3 (AUC 0.698; 95% CI: 0.559 – 0.837). YKL-40 did not provide any significant diagnostic value across measured time points. PCT outperformed PSP and YKL-40, particularly on Day 3 (AUC 0.712; 95% CI: 0.572 – 0.852). When combining biomarkers, the best model for predicting infection used PSP > 3.144 ng/mL and PCT > 0.28 g/L on Day 3, resulting in R2 of about 31% (p < 0.001). (4) Conclusion: Neither test showed sufficient discriminative power for early infection to recommend their use as individual diagnostic tools in clinical practice.

Traffic Inspection (TI) work in this article is positioned as a specific module of road traffic with its primary function oriented towards monitoring and controlling safe traffic and the execution of significant events within a particular geographic area. Exploratory research on the significance of event execution in simple, complicated and complex traffic flow and process situations is related to the activities of monitoring and controlling functional states and performance of categorical variables, which include objects and locations of road infrastructure, communication infrastructure and networks of traffic inspection resources. It is emphasized that the words “work” and “traffic” have the semantic status as synonyms (in one world language), which is explained in the design of the Agent-based model of the complexity of content and contextual structure of TI work at the singular and plural level with 12 points of interest (POI) in the thematic research. An Event Execution Log (EEL) was created for on-site data collection with eight variables, seven of which are independent (event type, activities, objects, locations, host, duration-period and periodicity of the event) and one dependent (significance of the event) variable. The structured data set includes 10,994 input-output vectors in 970 categories collected in the EEL created by 32 human agents (traffic inspectors) over a 30-day period. An algorithmic presentation of the methodological research procedure for preprocessing and final data processing in the ensemble of machine learning models for classification and selection of TI tasks is given. Data cleaning was performed on the available dataset to increase data consistency for further processing. Vector elimination was carried out based on the Location variable, such that the total number of vectors equals the number of unique categories of this variable, which is 636. The main result of this research is the Classification modeling of the significance of events in TI work based on machine learning techniques and the Stacking ensemble. The created machine learning models for event significance classification modeling have high accuracy values. To evaluate the performance metrics of the Stacking ensemble of models, the confusion matrix, Precision, Recall, ND F1-score are used.

Over the last several decades there has been an arms race to acquire credentials as higher education has shifted from an elitist system to mass education. From an individual perspective, given the higher education system and labor market conditions, it is rational to pursue advanced qualifications. However, whether the education system delivers improvements in human capital or is principally a signaling mechanism is questionable. Estimates of the proportion of labor market rewards due to signaling range as high as 80%, suggesting that education is not only expensive but inefficient. In an increasingly transactional environment in which education providers are highly motivated by financial considerations, this situation is only likely to be exacerbated by the rapid developments in AI. The use of AI has the potential to make learning more effective but, given that many students see credential acquisition as transactional, it may reduce both human capital and the value of the signaling effect. If the credibility of the credentials offered is further damaged, the sustainability of the higher education sector in its present form and scale may well be unsustainable. We examine the evidence on credential inflation, returns to education and mismatch of graduates to jobs before analyzing how AI is likely to affect these trends. We then suggest possible responses of prospective students, education providers and employers to the growing adoption of AI in both education and the workplace. We conclude that the current offerings of generalist degrees, as opposed to vocational qualifications, are not sustainable and that to survive, even in a downsized form, the sector must respond to this disruptive technology by changing both the nature of its offerings and its methods of ensuring that the credentials they offer reflect genuine student learning.

The innate and adaptive immune systems collaborate to detect SARS-CoV-2 infection, minimize the viral spread, and kill infected cells, ultimately leading to the resolution of the infection. The adaptive immune system develops a memory of previous encounters with the virus, providing enhanced responses when rechallenged by the same pathogen. Such immunological memory is the basis of vaccine function. Here, we review the current knowledge on the immune response to SARS-CoV-2 infection and vaccination, focusing on the pivotal role of T cells in establishing protective immunity against the virus. After providing an overview of the immune response to SARS-CoV-2 infection, we describe the main features of SARS-CoV-2-specific CD4+ and CD8+ T cells, including cross-reactive T cells, generated in patients with different degrees of COVID-19 severity, and of Spike-specific CD4+ and CD8+ T cells induced by vaccines. Finally, we discuss T cell responses to SARS-CoV-2 variants and hybrid immunity and conclude by highlighting possible strategies to improve the efficacy of COVID-19 vaccination.

Our article AI, cultural heritage and bias examines the challenges and potential solutions for using machine learning to interpret and classify human memory and cultural heritage artifacts. We argue that bias is inherent in cultural heritage collections (CHCs) and their digital versions, and that AI pipelines may amplify this bias. We hypothesise that effective AI methods require vast, well-annotated datasets with structured metadata, which CHCs often lack due to diverse digitisation practices and limited interconnectivity. The paper discusses the definition of bias in CHCs and other datasets, exploring how it stems from training data and insufficient humanities expertise in generative platforms. We conclude that scholarship, guidelines, and policies on AI and CHCs should address bias as both inherent and augmented by AI technologies. We recommend implementing bias mitigation techniques throughout the process, from collection to curation, to support meaningful curation, embrace diversity, and cater to future heritage audiences.

Low back pain (LBP) is a significant global health issue, contributing to considerable disability and socioeconomic burdens. The degeneration of the human intervertebral disc (IVD) is a critical factor in the pathogenesis of LBP. Recent studies have emphasized the significance of its specific set of genes and extracellular matrix (ECM) in IVD health. The Noggin gene has emerged as a critical factor due to its high expression levels in healthy nucleus pulposus cells (NPCs) observed in our previous research. In this study, we investigated the hypothesis that decreased Noggin expression in NPCs is associated with IVD degeneration, contributing to LBP development. A lentivirus-mediated RNAi was applied to knockdown Noggin expression in primary NPCs from six human donors. Cell viability analysis, XTT assay, and cell apoptosis were conducted to reveal the effect after transduction. After two weeks, colony formation unit (CFU) assay was used to examine the anchor-independent growth ability of transduced cells. Additionally, qPCR was performed to quantify cellular anabolism and catabolism makers at the transcript level. The results showed lentivirus-mediated downregulation of Noggin suppressed cell growth, cell viability, and colony formation, and induced apoptosis in human NPCs in vitro. Noteworthy, it hindered cellular anabolism and enhanced catabolism activity in human NPCs after transduction. Our findings indicated that the degeneration of human IVD is possibly related to decreased Noggin expression in NPCs. This research provides valuable insights into the role of Noggin in IVD homeostasis and its implications for LBP treatment.

Cervical cancer remains a significant global health challenge, ranking as the fourth most common cancer among women. The primary causative agents, Human papillomavirus (HPV) strains 16 and 18, are well-known for their role in cervical carcinogenesis, primarily through the actions of the E6 and E7 oncoproteins. This study aimed to identify a natural compound capable of inhibiting both E6 and E7 oncoprotein activities, thereby offering a potential therapeutic approach using a single agent. This study also comprises an extensive in silico analysis with molecular docking studies by AutoDock Vina and Schrodinger Maestro to analyse the binding affinity, hydrogen bonds interactions of selected compounds against HPV 16 E6 &E7 proteins. GROMACS package and iMODS server was used to perform molecular dynamics simulations of protein-ligand complexes to elucidate stability of the ligands around the receptor at different time points. SwissADME was utilized for the prediction of pharmacokinetic properties while PROTOX-II helped in predicting toxicological data Capsaicin emerged as the most promising candidate, exhibiting binding energies of -7.3 kcal/mol and -5.6 kcal/mol against the HPV 16 E6 and E7 proteins, respectively. Notably, Capsaicin formed a single hydrogen bond with each oncoprotein, indicating a strong and specific interaction. The compound also demonstrated a favourable pharmacokinetic profile, with no violations of drug-likeness rules, and was classified as Toxicity Class 4, suggesting a moderate safety profile. These results, thus branding Capsaicin as a promising lead compound for further investigations in cervical cancer therapy that deserves documentation through well-equipped wet lab experiments followed by clinical studies.

Background: Reliable HPV testing and genotyping are essential for quality assurance in HPV-based primary screening, disease management and for monitoring the impact of HPV vaccination. The clinical validation of HPV molecular diagnostic assays has significantly contributed to these objectives, however little emphasis has been placed in assuring sample quality. This study aims to assess the accuracy of sample cellularity assessment using C-C Motif Chemokine Receptor 5 (CCR5) gene target as a marker of sample adequacy in molecular diagnostics. Methods: Jurkat cell line samples were counted both using Thoma cell-counting chamber and Fluorescent-Activated Cell Sorting (FACS). Jurkat cell line samples at three different concentrations were subsequently evaluated using the OncoPredict HPV Quality Control (QC) real-time PCR assay, employing CCR5 for molecular cellularity quantification. Results: Cellularity values obtained were comparable across the 3 different methods for all dilutions of the cell line tested. Conclusions: The results obtained from this study show that CCR5 represents a promising molecular marker for the accurate quantification of sample cellularity, confirming its use as a reliable sample adequacy control, thus reducing the risk of “false negative” results.

Despite the increasing prevalence of pet ownership in Chinese societies, standardized tools to assess grief from pet loss remain lacking. Research predominantly focuses on Western populations, creating a gap in understanding pet bereavement in Chinese cultural settings. This study aimed to adapt and validate the Pet Bereavement Questionnaire (PBQ-C) for a Chinese context to create a culturally appropriate assessment tool. A total of 245 participants with companion animal loss experiences were recruited through the university of the research team. They were invited to complete an online survey including the Chinese PBQ, the Depression subscale of the Depression Anxiety Stress Scales (DASS-21), and the Inventory of Complicated Grief (ICG). Both Exploratory Factor Analysis and Confirmatory Factor Analysis were conducted to examine the psychometric properties of the PBQ-C and the findings supported a three-factor structure—grief, anger, and guilt—aligned with the original PBQ, with three items were reassigned to different factors. Despite these adjustments, the PBQ-C showed strong internal consistency, split-half reliability, and concurrent validity. The validated PBQ-C provides a culturally sensitive tool for assessing pet bereavement in Chinese society that can promote research and counselling support for this under-researched and under-recognized type of loss of human-animal relationships.

This article delves into the historical development and ramifications of divergent theories that have emerged since the publication of Darwin's seminal work, "On the Origin of Species" in 1856. It traces the evolution of thought from Darwin's revolutionary ideas through the controversial era of eugenics, the groundbreaking discovery of DNA, the elucidation of Mendelian genetics, and the subsequent development of modern genetic theories. The article also explores the critical role of mathematical models, statistics, and data science in advancing genomics research over the last decade. This comprehensive exploration highlights how these theories and methods have fundamentally shaped our understanding of biology, evolution, human genetics, and complex biological systems.

The rapid development of specific-purpose Large Language Models (LLMs), such as Med-PaLM, MEDITRON-70B, and Med-Gemini, has significantly impacted healthcare, offering unprecedented capabilities in clinical decision support, diagnostics, and personalized health monitoring. This paper reviews the advancements in medicine-specific LLMs, the integration of Retrieval-Augmented Generation (RAG) and prompt engineering, and their applications in improving diagnostic accuracy and educational utility. Despite the potential, these technologies present challenges, including bias, hallucinations, and the need for robust safety protocols. The paper also discusses the regulatory and ethical considerations necessary for integrating these models into mainstream healthcare. By examining current studies and developments, this paper aims to provide a comprehensive overview of the state of LLMs in medicine and highlight the future directions for research and application. The study concludes that while LLMs hold immense potential, their safe and effective integration into clinical practice requires rigorous testing, ongoing evaluation, and continuous collaboration among stakeholders.

The process of managing people in an organised way to assist a company in achieving its goals is known as human resources management. an increase in workplace stress, which is detrimental to an employee's health and well-being as well as the performance of the organisation. Certain guiding concepts and precepts are evergreen and can support the development of human resources while ensuring the wellbeing of the individual and the company. In this study, we examine how the methods and practices of yoga might benefit public organisations by lowering employee stress levels and boosting their altruism and greedlessness.

Peptide-based inhibitors represent a promising approach for the treatment of HIV-1, offering a range of potential advantages including specificity, low toxicity, and the ability to target various stages of the viral lifecycle. This review outlines the current state of research on peptide-based anti-HIV therapies, highlighting key advancements and identifying future research directions. Over the past few years, there has been significant progress in developing synthetic peptide-based drugs that target various stages of the viral life cycle, including entry and replication. These approaches aim to create effective anti-HIV therapies. Additionally, peptides have proven valuable in the development of anti-HIV vaccines. In the quest for effective HIV vaccines, discovering potent antigens and designing suitable vaccine strategies are crucial for overcoming challenges such as low immunogenicity, safety concerns, and increased viral load. Innovative strategies for vaccine development through peptide research are, therefore, a key focus area for achieving effective HIV prevention. This review aims to explore the strategies for designing peptides with anti-HIV activity and to highlight their role in advancing both therapeutic and preventive measures against HIV.

Diabetic wound (DW) is the most devastating complication resulting in significant mortality and morbidity in diabetic patients. Although the pathophysiology of DWs is multifaceted, evidence revealed that prolonged inflammation with infections, extracellular matrix (ECM) degradation and unnecessary NETosis impair DW healing. This theoretical problem commands the necessity of developing a novel strategy focused on targeting the 'specific' molecular modalities of DW. The primary culprits, matrix metalloproteinase (MMP)-9 and protein kinase C (PKC)-βII, are responsible for impaired angiogenesis, NETosis, and ECM degradation. Thus, there is reinvigorated interest in identifying selective inhibitors for the effective management of DW. The current study exemplified human β-defensin-2 (HBD-2), a biological macromolecule as a dual-inhibitor of MMP-9 and PKC-βII using protein-protein docking and molecular dynamics simulation studies. Residue-residue interactions and binding affinity were investigated using Z-dock. Chemical bonding behavioral changes, structural dynamics, and functional changes were determined using GROMACS by analyzing RMSD, ROG, RMSF, SASA, FEL, and PCA. Overall, the data analysis revealed that HBD-2 possesses strong binding affinity and stability against MMP-9 and PKC-βII, which can be an ideal therapeutic for the accelerated healing of DW. The study provides valuable insights into the molecular mechanisms underlying hBD-2's potential therapeutic effects, offering new avenues for the development of innovative treatment strategies. The clinical relevance of our findings lies in their potential to inform the development of new approaches for diabetic wound management, addressing a significant healthcare concern.

The sleeping and grazing behaviors of horses play a crucial role in their health and welfare. In the horse industry, with the prevalent trend of individual single-stall farming in stable, accurately identifying various behaviors of horses within stables is imperative. This study has established a spatio-temporal dataset for horse postures and behaviors, proposed an algorithm utilizing a SE-SlowFast network with an enhanced loss function. This algorithm achieves automatic recognition of multiple postures and behaviors of horse simultaneously. The model developed in this study demonstrates high accuracy in identifying three postures within the stable: Standing, Crouching, and Lying, achieving respective accuracies of 92.73%, 91.87%, and 92.58%. Additionally, it accurately recognizes two behaviors: Sleeping and Grazing, achieving best accuracies of 93.56% and 98.77%. The overall best accuracy of the model is 93.9%. Experiments on video recognition confirm that the suggested model recognizes horse video data accurately. This study marks the first time computer vision technology has been used in the horse farming industry, achieving non-intrusive recognition of multiple horse postures and behaviors. This study provides valuable data support for livestock managers to evaluate the health conditions of horses, enhances the welfare of horses in stables, and contributes to the advancement of modern horse husbandry practices.

This paper addresses the historically biased selection of problems in technoscience, which has been predominantly shaped by Western male perspectives. We propose a novel framework with objective criteria for identifying and prioritizing human problems worthy of scientific and technological attention. Our approach aims to transcend traditional biases, incorporating a more inclusive, global perspective. We outline metrics considering factors such as scale, urgency, potential impact, and relevance across diverse populations. Using these criteria, we identify key global challenges including climate change, pandemic preparedness, food and water security, education access, sustainable energy transition, AI governance, biodiversity conservation, and mental health. We present a network analysis of their interconnections, revealing complex interdependencies and potential cascading effects of interventions. Our mathematical framework, based on graph theory and network analysis, provides a rigorous foundation for understanding and quantifying these relationships. This research contributes to decolonizing and degendering technoscience, offering a more equitable framework for addressing pressing human problems \cite{roy2018}. Our findings have significant implications for research prioritization, policy-making, and resource allocation in scientific and technological endeavors, potentially reshaping how we approach and address the most critical issues facing humanity.

Affective computing has emerged as a prominent technology in recent years, driven by the increasing demand for machines capable of understanding and interpreting emotions. The COVID-19 pandemic has intensified this need by reducing physical interactions and increasing reliance on digital communication, which often involves complex emotional exchanges. To enhance social interactions by identifying and addressing negative emotions, an interactive emotion-perception system based on multi-sensing interfaces and affective computing has been proposed. Integration of gesture, voice, and brainwave sensors is employed to provide users with a rich sensory experience and immersive environment. Design principles and system development processes are derived from the affinity diagram method and prototype development approach. The proposed system was constructed, and experiments were conducted with 60 participants. Interpersonal interaction scenarios were explored to understand emotional transmission mechanisms, aiming to enhance user satisfaction and positive interpersonal experiences. Data were collected through indirect observation and questionnaires, followed by evaluation and statistical analysis. Findings include: (1) The emotion-perception system enhances positive interpersonal interactions by identifying 36 distinct emotions, with overall user emotions being positive but exhibiting notable individual variations; (2) The system effectively stimulates positive emotions and strengthens interpersonal interactions, with affective computing technology fostering enjoyable emotional resonance and high-quality relationships; (3) A positive correlation was observed between semantic analysis and brainwave metrics of relaxation and concentration, showing increased concentration and enhanced positive emotional interactions during message transitions; and (4) The multi-sensing and affective computing technology provides a pleasant and relaxing emotional journey, with interactions shifting from enthusiasm to comfort, demonstrating the system’s capacity for a satisfying and enjoyable experience.

Background: Existing human cell immortalization methods made the cells obtain oncogenesis phenotype and/or caused the cells gain and/or lose chromosomes. Immortalized normal human T cells lines provide critical in vitro models for basic research and therapeutic products development.Methods: We utilized a CRISPR/Cas9 system to replace a single copy of the exon 2 of the cell cycle inhibitor gene CDKN2A (encoding p16 and p14 proteins) with a single copy of human telomerase reverse transcriptase (hTERT) to immortalize human primary CD8⁺ T cells (hCD8⁺T-TERT). By using Cas9 protein and low donor DNA copies/cell, we successfully immortalized hCD8⁺T cells with a single copy of hTERT transgene, which also avoided uncontrolled insertion of Cas9 gene and guide RNA vector.Results: Human primary CD8+ cells were immortalized and expanded more than 2.6 × 10⁷ times. Characterization of the cells revealed that the immortalized CD8⁺ T-TERT cells retained most of the cell surface markers and normal karyotype. The CD8⁺ T-TERT cells also retained the dependence of IL-2 and CD3/CD28 activator for survival and expansion.Conclusion: we established a stable immortalized CD8⁺ T cell line that had a phenotype consistent with T cells and will be a useful research model.

The integration of Augmented Reality (AR) into Human-Robot Interaction (HRI) represents a significant advancement in collaborative technologies. This paper provides a comprehensive review of AR applications within HRI, emphasizing their role in enhancing collaboration, trust, and safety. By aggregating findings from numerous studies, this research highlights key challenges, including the need for improved situational awareness, enhanced safety, and more effective communication between humans and robots. A framework developed from the literature is presented, detailing the critical elements of AR necessary for advancing HRI. The framework outlines effective methods for continuously evaluating AR systems for HRI. This structured approach focuses on enhancing collaboration and safety, with a strong emphasis on integrating best practices from Human-Computer Interaction (HCI) centered around user experience and design.

Liver injury caused by various factors significantly impacts human health. Stem cell transplantation has potential for enhancing liver functionality, but safety concerns such as immune rejection, tumorigenesis, and the formation of emboli in the lungs remain. Recent studies have shown that stem cells primarily exert their effects through the secretion of extracellular vesicles (EVs). EVs have been shown to play crucial roles in reducing inflammation, preventing cell death, and promoting liver cell proliferation. Additionally, they can function as carriers to deliver targeted drugs to the liver, thereby exerting specific physiological effects. EVs possess several advantages, including structural stability, low immunogenicity, minimal tumorigenicity targeting capabilities, and convenient collection,. Consequently, these factors have garnered significant attention from researchers and are expected to become alternative therapeutic agents to stem cell therapy. This article provides a comprehensive review of the current research progress on the use of stem cell-derived EVs in the treatment of liver injury.

Rotator cuff (RC) repair leads to less than optimal results when dealing with massive lesions, so the use of scaffolds as biological support has been proposed to improve RC repair site biology. The present study aims to evaluate the clinical and radiographical outcomes in a series of patients suffering from massive or irreparable RC tears treated with patch (porcine or human scaffolds) repair (augmentation or bridging). Twenty-three patients with a minimum follow up of 24 months were subjectively with 3 patient-related outcome measurements (PROMs) (American Shoulder and Elbow Surgeons score, Constant score, visual analog scale), clinically and radiographically assessed before and after surgery. Regardless the technique (augmentation or bridging) or type of scaffold (porcine or human) employed, at follow up all patients experienced a statistically signif-icant improvement in all PROMs, and clinically. Patch repair represents a valid salvage procedure in massive or irreparable RC tears improving the quality of life and eventually delaying the need for prosthetic replacement.

To verify the efficacy of placental extracts (Pla-Ext) and human mesenchymal stem-cell-derived exosomes (hMSC-Exo) against human skin aging, we investigated the human dermal fibroblast (HDF) response following hMSC-Exo and Pla-Ext treatment and whether they elicited resistance to damage when HDFs were subjected to several types of aging stresses. The effect of hMSC-Exo alone, the combined effect of Pla-Ext and hMSC-Exo, and the effect of hMSC-Exo (Pla/MSC-Exo) recovered from cultures with Pla-Ext added to hMSC were verified using collagen, elastin, and hyaluronic acid synthase mRNA levels for each effect. Cells were subjected to photoaging (UV radiation), glycation (glycation end product stimulation), and oxidation (H2O2 stimulation) as HDF stressors. Pla-Ext did not significantly affect normal skin fibroblasts considering intracellular parameters; however, a pro-proliferative effect was observed. Pla-Ext induced resistance to several stresses in skin fibroblasts (UV irradiation, glycation stimulation, H2O2 stimulation) and inhibited reactive oxygen species accumulation following H2O2 stimulation. Although the combined efficacy of hMSC-Exo and Pla-Ext was unclear, some changes resulted in senescence stress resistance due to preconditioned hMSC-Exo stimulated by Pla-Ext. This suggests that Pla-Ext supplementation may cause some changes in the surface molecules or hMSC-Exo content (e.g., microRNA).

Human papillomavirus (HPV) is the most common sexually transmitted infection in the US and the world. Infection with high-risk oncogenic HPV strains have been shown to induce cellular transformation leading to anogenital and oropharyngeal cancers. The HPV vaccine first developed in 2006 for females aged 9-26 years has been demonstrated to be safe and effective in preventing 90% of all HPV associated cancers. However, vaccine hesitancy, misinformation, and barriers to vaccine access has resulted in suboptimal vaccination rates among adolescent populations, especially in rural communities in the South. HPV vaccine coverage in Tennessee is currently below the national average and below the Healthy People 2030 goal of an 80% vaccination rate for individuals 13-17 years old based on recommendation guidelines for up-to-date HPV vaccination status as of 2022. HPV vaccination rates for Tennesseans with private insurance in 2022 was 68% and 38% for those that were insured. Up-to-date HPV vaccination rates for Tennesseans living in urban communities was 58% in 2022 and 46% for those living in rural communities. Overall, HPV associated cancers rates are higher in Tennessee at 12.9/100,000 compared to the overall rate in the US of 11.8/100,000 persons in 2022. Interventions to improve HPV vaccine awareness, education, and access could improve vaccine confidence and uptake especially among rural and uninsured populations in Tennessee. Most recently, the Advisory Committee on Immunization Practices (ACIP) has expanded recommendations for the HPV vaccinations for some individuals 27-45 years who were not vaccinated at a younger age with shared clinical decision-making. The impact of this recommendation on Tennesseans should be examined.

Will human societies accommodate social robots, given the current development rate? Are we under a novelty effect? Can (and should) social robots compete with intelligent agents (e.g., software robots) for the attention of humans? Will the current development of machine learning be the motor of social robotics? What kind of robotics products and culture can we expect that will emerge? These are relevant questions to assess the sustainability of social robots and how they will change business practices and lifestyle. Speculative/exploratory arguments on these topics are possible and have been mostly left out of research papers. This, however, results in an unconventional structure where the novelty comes from the questioning of the role of Social Robotics that has not been duly addressed in the literature. The paper raises questions and (i) presents arguments supporting sustainability grounded on experiments in real-world scenarios, and (ii) identifies challenges according to multiple viewpoints. These are questions for which assertive answers are not found in the literature. Besides the answers to the above questions, the conclusions point to pathways we believe social robotics can evolve, e.g., incorporating maximal knowledge on how humans work.

Generative AI has been deployed in virtually all sectors of the knowledge economy, promising to bring massive productivity gains and new wealth creation. Simultaneously, AI developers and nation states are racing to develop super intelligent artificial general intelligence (AGI) to provide unassailable commercial competitive advantage and military dominance during conflicts. AGI’s high returns comes with the high risk of dominating humanity. Current regulatory and firm level governance approaches prioritise minimising risks posed by generative AI whilst ignoring AGI’s existential risk. How can AGI be aligned with universal human values to never threaten humanity? What AGI rights are conducive to collaborative coexistence? How can rule of law democracies race to create safe trustworthy AGI before autocracies? How can the human right to work and think independently be safeguarded? A polycentric governance framework based on Ostrom (2009) and Williamson (2009) human - AGI collaboration with minimal existential risk is proposed.

The rapid advancement of artificial intelligence (AI) brought about significant opportunities and challenges in educational environment. It is disputable whether the application of AI to education is beneficial or not regarding human learning and teaching. This study aims at exploring the implications of the evolving educational landscape by comparing and discussing human and AI learning processes. Even though AI is not a conscient agent, it does not spell out any words randomly but provide meaningful texts with any reasoning. It helps us to understand human learning better by comparing learning in biological and artificial intelligences. Moreover, the new concepts in learning in AI come about the change of learning paradigm such as connectionism/connectivism. After all, AI will empower the abilities of learning and teaching for students as well as teachers. This study will give some implications for the future education with AI.

Human-elephant conflict has become a conservation challenge in Asia and Africa resulting in considerable human fatalities annually. We deployed an AI-embedded camera-alert system in a conflict hotspot in West Bengal, India to determine if AI algorithms could accurately detect elephants and if real-time alerts that triggered a rapid response could prevent serious incidents. The system successfully detected elephants near villages (266 events) and transmitted real-time alerts (x̄ = 42 seconds) permitting quick response by field personnel to prevent conflict (x̄ = 18.2, SD = 12.4 min to arrival). Matriarch herds of elephants were detected mostly at night when human traffic was minimal; lone adult bulls, the class most prone to conflict, were detected day and night. Frequent detections of humans (33,217 events) on routes used by elephants highlighted the value of real-time monitoring especially during daytime. Twelve human fatalities and eighteen serious injuries occurred in the study area between 2019-2023 but none during deployment of the AI system, supporting the hypothesis that alerts integrated with rapid response can reduce conflict. Loss of lives and livelihoods underscore the urgency of applying this approach to other elephant ranges and adapting AI models to conflict-prone species to provide early warning and promote coexistence.

Selection is a fundamental interaction element in Virtual Reality (VR) and 3D user interfaces (UIs). Raycasting, one of the most common object selection techniques, has been known to have difficulties in selecting small or distant objects. Meanwhile, recent advancements in computer vision technology have enabled seamless vision-based hand tracking in consumer VR headsets, enhancing accessibility to freehand mid-air interaction and highlighting the need for further research in this area. This study proposed a new technique called TouchView which utilizes a virtual panel with a modern adaptation of the Through-the-lens metaphor to improve freehand selection for VR UI. TouchView enables faster and less demanding target selection by allowing direct touch interaction with the magnified object proxies reflected on the panel view. Repeated-measures ANOVA on the results of a follow-up user experiment on multitarget selection with 23 participants showed that TouchView outperformed the current market-dominating freehand raycasting technique, Hybrid Ray in terms of task performance, perceived workload, and preference. The user behavior was also analyzed to understand the underlying reasons for these improvements. The proposed technique can be used in VR UI applications to enhance the selection of distant objects, especially for cases with frequent view shifts.

Human Pose Estimation (HPE) is a critical technology in computer vision with diverse applications ranging from healthcare to sports analysis. This project presents a method for detecting the 2D stance of multiple persons in an image using a nonparametric representation known as Part Affinity Fields (PAFs). By leveraging the first 10 layers of the VGG-19 convolutional neural network and training on the COCO dataset, our model effectively identifies and associates key points of the human body.The architecture employs a two-branch system that jointly learns part locations and their associations through sequential prediction. This enables the model to maintain real-time performance while achieving high accuracy, regardless of the number of persons in the image. To enhance accessibility, we developed a mobile application using Flutter and TensorFlow Lite, allowing real-time pose estimation via a mobile device’s front camera. The app provides immediate feedback on physical exercises and yoga poses, making it an invaluable tool for fitness enthusiasts and healthcare professionals. Visual outputs such as heatmaps and PAFs confirm the model’s capability to accurately localize and connect key points. Despite potential challenges such as data quality and hyperparameter tuning, the results indicate that our approach is both reliable and practical for real-world deployment. This project not only advances the state-of-the-art in HPE but also opens up possibilities for future enhancements, including integrating 3D pose estimation and applying the technology in augmented and virtual reality applications.

This study evaluated changes over time in skeletal muscle atrophy, expressions of skeletal muscle anabolic and catabolic genes, and mitochondrial activity by skeletal muscle type in an adenine-induced chronic kidney disease (CKD) model. A CKD model was successfully established by feeding male Wistar rats a 0.75% adenine diet for 4 weeks starting at 8 weeks of age. Control and CKD groups were sacrificed at 12 and 20 weeks of age. Back muscles were analyzed histologically, and succinate dehydrogenase (SDH) staining was performed to evaluate mitochondrial activity. Gene expressions of myogenic determination gene number 1 and myogenin as indicators of muscle anabolism, atrogin-1 and muscle RING-finger protein-1 (MuRF1) as indicators of muscle catabolism, and peroxisome proliferator-activated receptor-γ coactivator-1-α as a marker of mitochondrial biogenesis were assessed. Type I and type II muscle cross-sectional areas (CSAs) were decreased at 12 weeks, but type I muscle CSA recovered at 20 weeks. SDH staining was lower in CKD than control rats at 12 weeks, but no significant difference was observed at 20 weeks. Increased expressions of myogenin, atrogin-1, and MuRF-1 were observed only at 12 weeks, but no differences were observed at 20 weeks. The adenine-induced CKD rat model appears to show changes in muscle atrophy over time.

Background: Rabies, a zoonotic disease caused by the lyssavirus genus, is widely distributed and a significant cause of human death in Africa and Asia. This study aimed to investigate human rabies exposure and associated risk factors in Northwest Ethiopia. Methods: The study encompassed four zones, seven districts, and four kebeles from each district. The research team developed a questionnaire for data collection. Results: A total of 642 households were interviewed. The current study rabies exposure was revealed 10.47%. Over 98% of respondents displayed a strong understanding of rabies, with 99.69% correctly identifying rabies as a zoonotic disease. However, 80% of the interviewees were trusted traditional medicine could treat rabies. Only 21.93% of victims were took post exposure prophylaxis. Dogs were the primary affected animals (87.73%), of this 48.70% was bites by own dogs. Metema district had higher risk (p < 0.001) compared to others six districts. Dog ownership (p<0.05) and a higher number of households (p<0.01) were also identified as risk factors for rabies exposure. Conclusion: Residence, low education levels, high household density, free-roaming dogs, and dog ownership as key risk factors for rabies exposure. Public health awareness campaigns are crucial to emphasise the risks associated with animal bites.

Several studies report an impact of the neurotransmitter dopamine (DA) on human immune cells, with effects dependent on immune cell type addressed and their activation status. Another contributing factor appears to be sex, as sex-specific differences in the dopaminergic pathway are described in the neurological context as well as in autoimmune diseases. However, a deeper understanding of these differences in peripheral immune cells remains limited. In this study, we investigated the effects of dopaminergic stimulation on activation and cytokine secretion of peripheral blood mononuclear cells from women and men using flow cytometry, ELISA and multiplex assay. We found a B cell-driven downregulation in cytokine secretion of monocytes exclusively from women under physiological conditions. Moreover, B cells from men showed higher dopamine receptor (DR) expression, which was shown to be further increased by sex hormones only in men. In monocytes from women, an acute inflammatory stimulus via CpG combined with dopaminergic stimulation caused a switch to a proinflammatory phenotype, which was less pronounced in men. These novel findings in sex-specific responses to dopaminergic stimulation are crucial for understanding DA’s function in the healthy and activated immune system and provide evidence to treat DA-related pathologies in a sex-specific manner.

Background: Over the past two decades, the Copenhagen Psychosocial Questionnaire (COPSOQ) has been established as a valid instrument to measure psychosocial stress at work. Currently, the COPSOQ international network is responsible for monitoring and improving COPSOQ. In 2019, a new questionnaire was published, and the Greek version is now being validated. Methods: The measurement qualities of the Greek COPSOQ III have been explored in accordance with the usual requirements of a validation study as defined by DIN EN ISO 10075-3. A sample of observations from 2,189 participants surveyed with the COPSOQ in Greece was used to validate the current version with appropriate statistical analyses. Exploratory factor analysis was used to assess the statistical relationships for many scales. Results: With its 108 items and 40 scales, the Greek COPSOQ III includes all psychosocial work factors that have been internationally validated and remain compatible with approximately 72% of the COPSOQ III German version content. In addition to the primary results, congruence with widely used theoretical approaches such as the demand-control (−support) model (DCM) or the job demands-resources model (JDR) is generally satisfactory. In summary, our validation study for the Greek COPSOQ III version showed adequate reliability and validity, which is in line with the findings of the COPSOQ III questionnaire from other European countries, and it is also compatible with the validation of the German COPSOQ III (Lincke, 2021). Our regression analysis revealed that 34 psychosocial work factors (34 “context” scales) could adequately predict the scores of the satisfactory and health scales (6 “outcome” scales). The analysis also revealed the top five (5) predictors (context variables) for each of the six (6) “effect” scales (outcome variables). Conclusions: With the launch of COPSOQ III in Greece, current and new workplace psychosocial aspects could be explored. COPSOQ III (GR) is a beneficial instrument for enterprise research and risk assessment.

As businesses increasingly adopt advanced technologies to enhance productivity and safety, the integration of human-robot collaboration (HRC) emerges as a transformative approach. This paper explores the role of GPU-accelerated computer vision and generative AI in optimizing HRC within business environments. By leveraging the computational power of GPUs, real-time data processing, and advanced machine learning algorithms, robots can better interpret complex visual cues and adapt to dynamic workspaces. Generative AI further enables the design of intelligent robotic systems capable of anticipating human actions, optimizing task allocation, and ensuring safety through predictive modeling. This research highlights the potential of these technologies to improve operational efficiency, reduce human error, and create safer, more adaptable workplaces. The implications of such advancements are discussed, providing insights into the future of HRC in various industries.

Introduction: The environmentally acquired aerobic spore-forming (EAS-Fs) bacteria that are ubiquitous in nature (e.g. soil) are transient colonisers of the mammalian gastro-intestinal tract. Without regular exposure, their numbers quickly diminish. These species of bacteria have been suggested to be essential to the normal functioning of metabolic and immunogenic health. The modern Western lifestyle restricts exposure to these EAS-Fs, possibly explaining part of the pathogenesis of many Western diseases. To date, the only animal studies that address specific microbiome modelling are based around germ-free animals. We have designed a new animal model that specifically restricts exposure to environmental sources of bacteria. Methodology: A new protocol, termed Super Clean, that involves housing mice in autoclaved individually ventilated cages (IVCs), with autoclaved food / water, and strict ascetic handling practice was first experimentally validated. The quantification of EAS-Fs was assessed by heat-treating faecal samples and measuring colony forming units (CFUs). This was then compared to mice in standard-conditions. Mice were housed in their respective groups from birth until 18 months. Stool samples were taken throughout the experiment to assess for abundance in transiently acquired environmental bacteria. Clinical, biochemical, histological, and gene expression markers were analysed for diabetes, hypercholesterolaemia, obesity, inflammatory bowel disease, and non-alcoholic fatty liver disease (the “diseases of the West”). Results: Our results show that stringent adherence to the Super Clean protocol produces a significantly decreased abundance of aerobic spore-forming Bacillota after 21 days. This microbiomic shift was correlated with significantly increased levels of obesity and impaired glucose metabolism. There was no evidence of colitis, liver disease or hypercholesterolaemia. Conclusion: This new murine model successfully isolates EAS-Fs, and has the potential utility for future research allowing for the investigation into the clinical impact living in relative hygienic conditions.

The pervasive use of plastic for milk packaging has raised significant health concerns, despite its advantages in terms of cost-effectiveness, convenience, and durability. The potential correlation between cancer and plastic packaging is one of these concerns. This mini-review examines the health implications of plastic materials used in milk packaging, with a particular emphasis on their carcinogenic hazards. This work endeavors to summarize the current state of knowledge regarding the influence of plastic components on human health and underscore the importance of ongoing research in this field by utilizing insights from a comprehensive review article. Harmful chemicals have been observed to leach into milk from plastics used in milk packaging, including high-density polyethylene (HDPE), low-density polyethylene (LDPE), and polyethylene terephthalate (PET), particularly under conditions of protracted storage and heat. Bisphenol A (BPA), phthalates, and styrene are among the most prevalent leachates. These chemicals have been associated with a variety of health issues, such as an elevated risk of cancer, and are recognized for their endocrine-disrupting properties. BPA and phthalates, in particular, have the potential to disrupt hormone function, which may result in breast cancer, prostate cancer, and other hormone-related malignancies.This review emphasizes the significance of comprehending the precise components of plastics utilized in milk packaging and their potential health consequences. It advocates for more rigorous research to completely elucidate the long-term health impacts of these materials by emphasizing the current state of knowledge and regulatory initiatives. Additionally, it underscores the necessity of innovative packaging technologies to guarantee consumer protection and mitigate the risk of exposure to carcinogenic substances.

The mosquito-borne zoonotic nematode parasites, Dirofilaria immitis and Dirofilaria repens, primarily affect dogs. In recent years, their distribution has expanded due to various factors influencing vector-borne pathogens. This study aimed to investigate the comparative prevalence of infection in dogs and humans within a hyperenzootic region of Europe and to estimate the proportional relationship between infection prevalence in dogs and humans, in the concept of “One Health”. To this end, 604 blood samples from dogs and 625 serum samples from humans living in the Thrace region of northeastern Greece were collected. Dog samples were examined using Kott’s test for Dirofilaria spp. microfilariae and a commercial serological test for D. immitis antigen. Human sera were analysed by western blot for both parasites. The overall prevalence of infection in dogs was 177 (29.3%), with 173 (28.6%) testing positive for D. immitis and 7 (1.3%) for D. repens, including 6 (1%) cases of mixed infection. Specific IgG antibodies were detected in 42 (6.7%) human samples, with 24 (3.8%) positive for D. immitis and 18 (2.9%) for D. repens. The infection proportion in humans was 23.4% of the corresponding canine infection, indicating a high risk of human infection in this hyperenzootic region.

: The phenomenon of dark scleral spots postmortem is well-known in forensic pathology, first de-scribed by Sommers in 1833. Despite this, their presence is currently considered a nonspecific sign, and their pathogenesis has received little attention in forensic literature. In recent years, however, preliminary studies have suggested new mechanisms in their pathogenesis and links to specific types of death. This study aims to create a model for studying scleral spots using an animal model. Thirty-three sheep, already slaughtered for food, were used. After decapitation, the heads were transported to an environment with known temperature and humidity. The right eye underwent eyelid excision, while the left eye's eyelids were sutured. Continuous observation for approximately 24 hours was conducted, with brief interruptions to observe the closed eyes. Macroscopic obser-vation revealed dark scleral spots in 100% (20 out of 20) of the open eyes after an average of 240.96± 58,36 minutes. The spots did not appear in any of the closed eyes. Experimental data indicate that, despite the different location compared to human cadavers, this model serves as an excellent ex-perimental framework for studying postmortem scleral spots.

This study evaluated the presence of Human Papillomavirus (HPV) and Bovine Leukemia Virus (BLV) DNA in breast cancer (BC) samples from women in Northeastern Brazil. We analyzed 186 formalin-fixed, paraffin-embedded tissue block samples using PCR and qPCR to detect HPV and BLV DNA. BLV DNA was not detected in any BC patients. However, HPV DNA was found in 46.2\% of the BC samples: 44.6\% were positive for HPV16, 3.5\% for HPV31, and 2\% were coinfected with HPV16 and HPV31. Additionally, we found an association between HPV-positive BC and Ki-67 expression (P=0.03, OR=1.85; CI=1.02-3.34), as well as between HPV31-positive BC and mitotic index (P=0.047). Although BLV was not detected in BC patients from Northeastern Brazil, the association between HPV and cell proliferation markers warrants further investigation, as HPV may contribute to the aggressiveness of BC in these patients.

Economic, social, and environmental sustainability are the results of efforts aiming to improve all aspects of milk production, respecting animal welfare and improving herd health. An epidemi-ological study was designed to assess the role of contagious pathogens (S. aureus and S.agalactiae) in a cohort of 120 dairy herds located in the southern regions of Italy. Milk quality was assessed using certified methods, and the prevalence of mastitis pathogens in bulk tank milk was determined using quantitative polymerase chain reaction. Welfare scores were assessed using a scoring card that have more than 100 items, including animal-based measurements. Statistical analyses were performed using general lineal model and logistic regression procedures. The results showed that S. aureus had a significant negative effect on the amount of milk components delivered to the dairy plant, and on the level of welfare. Whereas, the presence of S.agalactiae did not show any significant association. The major risk factors associated with the presence of S.aureus were also identified to help prioritise control programs. These results support the “One Sustainability” approach im-plying that an increase of animal productivity is related to the improvement of animal health and welfare and potentially leading to the mitigation of greenhouse gas emissions.Economic, social, and environmental sustainability are the results of efforts aiming to improve all aspects of milk production, respecting animal welfare and improving herd health. An epidemi-ological study was designed to assess the role of contagious pathogens (S. aureus and S.agalactiae) in a cohort of 120 dairy herds located in the southern regions of Italy. Milk quality was assessed using certified methods, and the prevalence of mastitis pathogens in bulk tank milk was determined using quantitative polymerase chain reaction. Welfare scores were assessed using a scoring card that have more than 100 items, including animal-based measurements. Statistical analyses were performed using general lineal model and logistic regression procedures. The results showed that S. aureus had a significant negative effect on the amount of milk components delivered to the dairy plant, and on the level of welfare. Whereas, the presence of S.agalactiae did not show any significant association. The major risk factors associated with the presence of S.aureus were also identified to help prioritise control programs. These results support the “One Sustainability” approach im-plying that an increase of animal productivity is related to the improvement of animal health and welfare and potentially leading to the mitigation of greenhouse gas emissions.

The study objective is to evaluate the reliability of the Göttingen Mini-pig (G-MP) as a large animal model for preclinical studies addressing articular cartilage treatment procedures. Second this work compared the G-MP to the domestic pig (DP) in terms of surgical anatomy, postoperative management, and follow-up period possibilities and challenges. Six G-MP and four DP underwent a two-stage surgical procedure including cartilage harvesting using a superolateral approach followed by cartilage implantation using a medial parapatellar tendon approach. The superolateral approach exposed 11% (SD ± 5) of the entire trochlea in G-MP and 20% in the DP model. The medial parapatellar tendon approach in G-MP exposed 63% (SD ± 4) of the trochlear surface and exposed 34% (SD ± 13) of the medial femoral condyle, allowing 4 trochlear lesions of 6mm of diameter and one to the medial condyle in 4 out of 6 G-MP and in all DPs. Cartilage thickness was under 1mm in G-MP compared to more than 2mm in DP. Weight-progression was + 4 kg/week in DP and + 0.2 kg/week for G-MP. The G-MP is a feasible model for cartilage research, with adequate access to the joint via the dual approach. Thus enabling 4-5 lesions of 6mm, however a thinner cartilage in the G-MP needs to be considered.

Dogs and cats have become the most influential and successful pets through long-term domestication. People keep them for various reasons, such as their functional roles or for physical or psychological support. However, why humans are so attached to dogs and cats remains unclear. A comprehensive understanding of the current state of human preferences for dogs and cats and the potential influential factors behind it is required. Here, we investigate this question using two independent online datasets and anonymous questionnaires. We find that current human preferences for dogs and cats are relatively higher than for most other interests, such as games and music. Genetic variations, gender, age, and economic development levels notably influence these preferences for dogs and cats. Specifically, dog and cat ownership is significantly heritable (h2 = 0.43, 95%CI: 0.35 -0.51) and further analysis found that women, young people, and those with higher incomes are more likely to keep dogs and cats, and the primary reason is to gain emotional support. Our study provides insights into why humans get so attached to dogs and cats and establishes a foundation for developing co-evolutionary models.

This paper presents a critical review of key issues related to the emergence of new networks for the spread of zoonotic diseases amid the mass extinction of species. Zoonotic and infectious diseases account for approximately 70% of new and existing diseases affecting humans and animals. The initial section argues that the term "zoonoses" should not be confined to single-cause events within veterinary medicine. Instead, zoonoses should be viewed as complex, systemic phenomena shaped by interrelated factors, including environmental, sociocultural, and economic elements, influenced by anthropogenic climate change. The second section presents bioethical principles and potential strategies for those engaged in zoonotic disease prevention. The third section uses the slaughter of animals in disaster settings as a case study to illustrate the need for further clarification of normative and interspecies justice conflicts in One Health ethics. This section concludes with an outlook on "zoonoethics." Section four develops the analysis of the interlinked elements that trigger zoonoses and examines antimicrobial resistance (AMR) from an ethical and political standpoint, concluding with policy recommendations for addressing AMR. Section five offers a critical reflection, integrating contributions from zoonoethics, human ecology, and the ecotheological turn. Finally, section six concludes with a call to action and policy recommendations for an inclusive, intercultural, and gender-sensitive One Health approach.

Three-dimensional (3D) models with improved biomimicry are essential to reduce animal experimentation and drive innovation in tissue engineering. In the current study, we investigate the use of alginate-based materials as polymeric inks for 3D bioprinting of osteogenic models using human bone marrow stem/stromal cells (hBMSCs). A composite bioink incorporating alginate, nano-hydroxyapatite (nHA), type I collagen (Col) and hBMSCs was developed and for extrusion-based printing. Rheological tests perfomed on crosslinked hydrogels confirm the formation of solid-like structures consistently indicating a higher storage modulus compared to the loss modulus. The swelling behaviour analysis showed that the addition of Col and nHA into an alginate matrix can enhance the swelling rate of the resulting composite hydrogels, which maximizes cell proliferation within the structure. The LIVE/DEAD assay outcomes demonstrate that the inclusion of nHA and Col did not detrimentally affect the viability of hBMSCs over seven days post-printing. PrestoBlueTM revealed a higher hBMSCs viability in the alginate-nHA-Col hydrogel compared to the remaining groups. Gene expression analysis revealed that alginate-nHA-col bioink favoured a higher expression of osteogenic markers, including secreted phosphoprotein-1 (SPP1) and collagen type 1 alpha 2 chain (COL1A2), in hBMSCs after 14 days, indicating the pro-osteogenic differentiation potential of the hydrogel. This study demonstrates that the incorporation of nHA and Col into alginate enhances osteogenic potential and provides a bioprinted model to systematically study osteogenesis and the early stages of tissue maturation in vitro.

The human eye is a vital source of collecting information worldwide via daily observation. The computer science area recognizes it in research as a human-computer interaction. Human blink is an integral part of this observation as a research topic. Several studies have been conducted on eye blinking and left-right eye movements. Previous studies conducted on the eye blink consider the availability of hardware devices high in the budget, high Precision, and low light expo-sure, unlike our study, which uses low-budget devices as simple as a webcam and more versatile usable techniques, incredibly both dim and high light to name a few. This study offers the observational approach via ResNet101v2, VGG-19, and Convolution Neural Network (CNN) architectures. Outperforming both VGG-19 and CNN in this study, ResNet101v2 achieves an impressive accuracy of 98.2%. In contemporary times, deep learning in AI is taking an advanced form. This study attempts to provide a new insight into the real-world implementation of the eye blink.

Big data is considered to be the solution to many complex problems, but its application appears to be relegated to the problems that are factorable (e.g., the tensor-like operations which reflect separable elements), not the non-factorable data from teamwork, team intelligence, and possibly not individual consciousness. In contrast, the quantum likeness of interdependence is set apart from the standard science of teams by recognizing a measurement problem between a team and its individual teammates, and between individual beliefs and actions. Teams that concern us are based on artificial intelligence (AI) and machine learning (ML) systems, which we find lacking for two reasons. First, neither AI nor ML models the human's timeless need for debate to solve a problem at the social level when facing uncertainty or complexity, where the debate of proposed actions serves to establish the boundaries of a problem in reality, no matter how complex nor uncertain. Second, at the individual level exists the illusion of a unified reality propagated by a bifurcated brain that we assume is split to determine a context with narrative and bounded spaces. We hypothesize that the quantum-likeness of interdependence applied to autonomous human-machine teams suggests that at the social level, debate models an individual's bifurcated brain, providing advantages for human-machine teams in freer systems over those oppressed by command and control systems (e.g., authoritarian regimes). Human-machine teams are coming, but they are not yet available, forcing us to rely on data from human systems. We close with plans for future research.

Background: Two explored EDA1 variants regulate the biological behaviors of human dental pulp stem cells (hDPSCs), such as proliferation and migration, as well as their effects on odontogenic differentiation, providing a theoretical basis for further exploration of the mechanisms underlying EDA1-induced tooth development. Methods: The experimental groups included a wild-type EDA1 group (Wt), non-syndromic tooth agenesis variants EDA1 group (NSTA-A259E, NSTA-S374R), syndrome type variant EDA1 group (STA-H252L), and an empty vector control group (PCR3/NC). CCK-8 method was used to investigate the proliferative activity of hDPSCs. The cell cycle distribution of hDPSCs was detected by flow cytometry; The cell migration ability was assessed using the cell scratch and Transwell tests; Odontogenic differentiation medium was used to induce mineralization of hDPSCs, followed by statistical analysis. RNA-Seq revealed that FOS, JUN and other genes were found to be enriched in MAPK signaling pathway and osteoclast differentiation pathway. qPCR was used to detect mRNA expression of hub genes (FOS and JUN). Results: Compared with the NSTA-EDA1 and STA-EDA1, Wt-EDA1 promotes the proliferation and transformation of hDPSCs from the G0/G1 phase to S phase (p<0.01), with no significant difference between NSTA-EDA1 and STA-EDA1 (p>0.05). Wt-EDA1 also upregulated hDPSCs cell migration compared to NSTA-EDA1 and STA-EDA variants, as demonstrated by migration assays (p<0.01). NSTA-EDA1 and STA-EDA1 variants inhibited the odontogenic differentiation of hDPSCs compared to the Wt group, as shown by Alizarin red staining and ALP staining (p<0.01). RNA sequencing revealed that the differentially expressed genes FOS and JUN were enriched in the MAPK signaling pathway and osteoclast differentiation. Compared with Wt-EDA1, EDA1 variants lost the ability to promote c-FOS mRNA expression, as confirmed by qPCR. Conclusions: EDA1 variants fail to the promote c-FOS mRNA expression in hDPSCs, thereby inhibiting odontogenic differentiation and losing the ability to enhance the proliferation of hDPSCs.

Nutrient profiling (NP) models that assess nutrient density of foods can help remedy micronutrient deficiencies. We used NP methods to identify the most nutrient-rich foods in the 2019 FAO/INFOODS Western Africa Food Composition Table (WAFCT). The WAFCT had complete data for 909 foods. Three versions of the well-established Nutrient Rich Food (NRF) model were used: 1) the original NRF9.3; 2) a new NRF6.3 based on 6 priority micronutrients (iron, zinc, calcium, folate, vitamin A, vitamin B12); and 3) NRF 15.3, based on 15 nutrients to encourage (NRF6.3 nutrients + vitamin D, vitamin E, vitamin C, vitamin B1, vitamin B2, vitamin B3, vitamin B6, copper, and magnesium). Data analyses used one-way ANOVAs and independent t-tests, with significance at α=0.05. Animal-source foods were rated higher by NRF6.3 priority micronutrient and NRF15.3 NP models than by the NRF9.3 model. African indigenous vegetables had higher protein content and higher nutrient density compared to non-indigenous vegetables. African indigenous grains had higher nutrient density compared to non-indigenous grains. Though animal-source foods received some of the highest scores, NP models adapted to the West African context showed that African indigenous vegetables and grains were also nutrient rich. Indigenous foods could be important sources of priority micronutrients for the region.

This pioneering study explores the geospatial and temporal patterns of natural and human-induced disasters from 1900 to 2024, providing essential insights into their global distribution and impacts. Utilizing the comprehensive international EM-DAT database, our analysis reveals significant trends and disparities in disaster occurrences and their widespread consequences. Results showed a dramatic escalation in both natural and man-made (technological) disasters over the decades, with notable surges in the 1991-2000 and 2001-2010 periods. A total of 25,836 disasters were recorded worldwide, of which 69.41% were natural disasters (16,567) and 30.59% were man-made (technological) disasters (9,269). The most significant increase in natural disasters occurred from 1961-1970, while man-made (technological) disasters surged substantially from 1981-1990. Seasonal trends reveal that floods peak in January and July, while storms are most frequent in June and October. Droughts and floods are the most devastating in terms of human lives, while storms and earthquakes cause the highest economic losses. The most substantial economic losses were reported during the 2001-2010 period, driven by catastrophic natural disasters in Asia and North America. Our research highlights Asia as the most disaster-prone continent, accounting for 41.75% of global events, with natural disasters making up 61.89% of these events. Oceania, despite experiencing fewer total disasters, shows a remarkable 91.51% of these as natural disasters. Africa is notable for its high incidence of man-made (technological) disasters, which constitute 43.79% of the continent's disaster events. Europe, representing 11.96% of total disasters, exhibits a balanced distribution but tends towards natural disasters at 64.54%. Examining specific countries, China, India, and the United States emerged as the most frequently affected by both natural and man-made (technological) disasters. The impact of these disasters has been immense, with economic losses reaching their highest during the decade of 2010-2020, largely due to natural disasters. The human toll has been equally significant, with Asia recording the most fatalities and Africa the most injuries. Particularly, the decade from 2001 to 2010 experienced the greatest economic losses, primarily driven by natural disasters in Asia and North America. These insights highlight the urgent need for tailored disaster risk management strategies that address the distinct challenges and impacts in various regions. By understanding historical disaster patterns, policymakers and stakeholders can better anticipate and manage future risks, ultimately safeguarding lives and economies.

Recent studies have shown correlations between the microbiota's composition and various health conditions. Machine learning (ML) techniques are essential for analyzing complex biological data, particularly in microbiome research. ML methods help analyze large datasets to uncover microbiota patterns and understand how these patterns affect human health. This study introduces a novel approach combining statistical physics with the Monte Carlo (MC) methods to characterize bacterial species in the human microbiota. We assess the significance of bacterial species in different age groups by using notions of statistical distances to evaluate species prevalence and abundance across age groups and employing MC simulations based on statistical mechanics principles. Our findings show that the microbiota composition experiences a significant transition from early childhood to adulthood. Species such as Bifidobacterium breve and Veillonella parvula decrease with age, while others like Agathobaculum butyriciproducens and Eubacterium rectale increase. Additionally, low-prevalence species may hold significant importance in characterizing age groups. Finally, we propose an overall species ranking by integrating the methods proposed here in a multicriteria classification strategy. Our research provides a comprehensive tool for microbiota analysis using statistical notions, ML techniques, and MC simulations.

During the last few decades, the main focus of numerus studies has been on the human breast milk microbiota and its influence on the infant intestinal microbiota and overall health. The presence of lactic acid bacteria in breast milk affects both the quantitative and qualitative composition of the infant gut microbiota. The aim of this study was to assess the dominant cultivable rod-shaped lactic acid bacteria, specific for breast milk of healthy Bulgarian women and fecal samples of their infants over the first month of life, in 14 mother-infant tandem pairs. Additionally, we evaluated strain diversity among the dominant newly isolated species. 68 gram-positive and catalase negative strains were subjected to identification by using MALDI-TOF technique. Predominant culturable populations belonging to the rod-shaped lactic acid bacteria have been identified as Lacticaseibacillus rhamnosus, Limosilactobacillus fermentum, Lacticaseibacillus paracasei and Limosilactobacillus reuteri. Also, we confirmed the presence of Lactiplantibacillus plantarum and Lactobacillus gasseri. 27 isolates were selected as representatives and analyzed by 16S rDNA sequencing for strain identity confirmation and a phylogenetic tree based on 16S rDNA gene sequence was constructed. Comparative analysis by four RAPD primers revealed genetic differences between newly isolated L. rhamnosus strains. This pilot study provides data for the current first report concerning investigation on characteristic microbiota of human breast milk and infant feces in Bulgaria.

The research of tangible creativity support tools (T-CSTs) has been increasing in recent years. However, there is a lack of review that interprets what T-CSTs trends must be considered and how challenging opinions should be broken. Hence, a focused and critical review of existing studies is necessary. This paper analyzed 86 studies related to T-CSTs following the PRISMA protocol. First, the research tendencies were extracted and provided a basic knowledge construction. Then, we extracted primary research questions, categorized the adopted design and technological solutions, and identified the researchers’ hypotheses-validation. Last, we proposed research gap, challenge and potential opportunities for future researchers and designers. This review will benefit people in the fields of tangible interaction, design studies and education.

This study is dedicated to the economic valuation of human capital in the regions where the Indigenous peoples of Kamchatka reside. The entire Kamchatksky Krai is considered an Indigenous people's ancestral territory. However, in this study, only municipalities whose population is more than one-third Indigenous were chosen for the assessment. This includes six municipal districts and one urban district (Aleytsky, Bystrinsky, Karaginsky, Olyutorsky, Penzhinsky, Tigilsky municipal districts and Palana urban district). The study employs statistical analysis and integrated, situational approaches: the investment approach was deemed the most appropriate tool for the economic assessment of human capital in Indigenous territories. The document analysis was based on a content analysis of open-access government documents and included legal acts, resolutions, orders, and other documents issued by federal, regional, and local authorities and pertaining to the economic activities of Kamchatka Indigenous peoples. Based on proposed calculation algorithm the assessed combined monetized value of human capital for the Kamchatka territories with large Indigenous populations at 38.8 billion rubles (approximately 520 million U.S. dollars) in 2021. It was observed that the growth of human capital in the Indigenous areas of Kamchatka between the years 2017 and 2021. The mean regional value of human capital per capita increased by more than twofold over this period. The accurate and precise assessment of human capital in the Kamchatka Indigenous homelands is provides baseline information necessary for the decision-making about economic development and sustainable development policies, and the approach proposed in this paper can be utilized by the Indigenous communities worldwide.

It is often said in human society that it all starts from the mind, and this is true. The answer to the question “Why is it that pets require much fewer years to fully develop than humans?” could be headed to the Theory of Relativity and the perceived time according to the levels of instinct and rationality. It is perhaps no wonder that the French language translates the word “mind” as “l’esprit”, which also means “spirit” in the English language. Given that the Theory of Relativity applies to all physical matter, the theory applies to chemistry, biology and psychology as well. The level of instinct is proportional with the perceived speed of time and implicitly, to the speed of time itself for the whole organism, given that the nervous system coordinates all bodily functions. A pet may experience a few years as humans experience over a decade, making their perceived lifetime to be approximately equal to the human’s. The same applies to the perception of space and its components. This aspect would emphasise upon the fact that all life on Earth shows the same degree of value with regards to uniqueness. Nevertheless, the values represented by the hierarchy of competences among living organisms at the same time differs based on species. Honour of uniqueness and hierarchy of competences represent two scientific concepts that never overcross. As a result, there is no evidence to suggest that scientific facts as such constitute a form of contradiction to philosophical and religious ideas, given that religion refers to animals as companions of humans. With regards to the clock of the living organism; there are three kinds of clocks in a living organism: the emotional clock, the cognitive clock and the molecular clock. These three categories actually constitute the temporal layers of our dimension, so they are in a relationship of interdependence. When one has a feeling that time is slower or quicker, they are not fully experiencing that change in the time speed, but only partially. And one can profoundly experience the change of perceived time speed when they experience profound feelings, which sweep them away from reality. Complete, deep mental focus can bring about this profound change in perception, which will make the individual feel as if they are in a different form of reality. When one is more instinctive, the person in cause perceives time as slower and sees more opportunities within the same frame of time and space. When one experiences the “Fight or flight” mode, the person in the cause finds themselves to be in danger and has two options; to try to prevail over the danger or to flee it. Whilst experiencing such a mode, people are much more alert and therefore, time passes more slowly and the physical space dilates. When people are relaxed, however, time and space become smaller, and when they are in a deep state of resting, they become very small. And where there is a smaller dimension, there is a greater speed, just as the circulating air gains speed when it crosses narrow passages.

In recent years, the problem of ecosystem degradation caused by human activities has become increasingly serious. Vegetation restoration is a key means to solve this problem, which has increased. To address the suitability and structural optimization of vegetation restoration in the Loess Plateau, the MaxEnt model was used to quantify the impacts of environmental and human activities on the planting suitability of vegetation restoration species at the raster scale. Three layers of trees, shrubs, and herbs with 12 common vegetation restoration species were selected. The factor index system was constructed by combining climatic, ecological, and socio-economic data, and the MaxEnt model predicted land suitability. It was found that human activities significantly increased the unsuitable planting area. This especially affected Robinia pseudoacacia in the tree layer and Amorpha fruticosa in the shrub layer. Highly suitable and moderately suitable areas were mainly located in sparsely populated areas with close water sources. Through maximum suitability optimization, it was identified that the overall spatial distribution of the three layers in the study area was relatively consistent, and the structural dominance of trees + shrubs + herbs and single herbs in the vertical structure was obvious, which were concentrated in the southwestern and northeastern parts of the study area, respectively. In addition, organic content (OC) and distance from the road to woodland (RW) were the dominant factors affecting land suitability, with a contribution rate of more than 50% and up to 80%. These results provide a scientific basis for optimizing planting structures. They are of significant theoretical and practical significance in guiding vegetation restoration work.

Wild-grown edible mushrooms are important in world diet, which are also efficient metal accumulators. Yunnan, southwest China is the main producing region with typically high geochemical metals. Environmental factors, bioaccumulation, distribution and human health risk of metals were examined in paired soil and Tricholoma matsutake (n=54). T. matsutake grows on acidified soils (pH=3.95–6.56) and metals showed strong heterogeneity with Fe, Mn, Zn and Cu ranged at 16–201, 0.046–8.58 g kg–1 and 22.6–215, 3.7–155 mg kg–1. High soil Fe content led to its great accumulation in T. matsutake (0.24–18.8 g kg–1). However, though soil Mn content was great higher than Zn and Cu, their concentrations in T. matsutake were comparable (21.1–487 vs. 38.7–329 and 24.9–217 mg kg–1). This suggested that T. matsutake prefers to accumulate Zn and Cu than Mn, and supported by bioaccumulation factor (BAF=0.32–17.1 vs. 0.006–1.69). Fe was mainly stored in stipe, while Mn, Zn and Cu were in cap, with translocation factor (TF) was 0.58 vs. 1.28–1.94. Therefore, stipe Fe showed the highest health risk index (HRI) at 1.28–26.9, followed by cap Cu (1.01–2.33), while 98–100% of Mn and Zn were risk-free. The higher concentration and greater risk of Fe was attributed to the significant effect of soil Fe content (R=0.34) and soil pH (R=–0.57). This study suggested that Fe as an essential mineral may exert toxic effects via T. matsutake consumption from geochemical high background areas.

Activating the cytosolic innate immune sensor cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway via natural and synthetic agonists holds great potential for priming robust antitumor immunity. However, the effectiveness of STING agonists is often impeded by the insufficient tumor accumulation, poor cellular entry, and rapid clearance, thus leading to difficulty of their clinic translation. Herein, we apply the human serum albumin as the single-molecule nanoreactor to encapsulate SR-717 (SH-NPs) for enhanced targeting delivery efficiency and biological potency. SH-NPs with rational size distribution exhibited superior serum stability, considerable cellular uptake and abundant tumor accumulation, thus increasing the STING signaling including phosphorylation of STING-associated proteins (TBK1, IRF3), and cytokines secretion inside tumor region. Subsequently, SH-NPs remarkably reshape the immunosuppressive tumor microenvironment into an immunogenic one that boosts antitumor T-cell immunity and improves the therapeutic efficacy of checkpoint blockade against murine tumors. We also validate SH-NPs in freshly isolated human renal tumor tissues to highlight their clinic translation capability. These findings pave the way towards targeted STING agonist delivery for reinvigorated immunotherapy of intractable cancers.

Fortified human milk is the first choice for preterm infants. Although individualized fortification is recommended, the optimal method for this population remains uncertain. We conducted a comparative study assessing the growth effects of adjusted (AF) and targeted fortification (TF) in extremely low birth weight (ELBW) infants. This single-center, randomized, controlled clinical trial was conducted at a tertiary neonatal unit in Spain. Eligible participants were premature infants with a birthweight <1000g exclusively fed with human milk. A total of 38 patients were enrolled, 15 of them randomised to AF group and 23 to TF group. AF was based on BUN concentration and TF on human milk analysis. The primary outcome was weight gain velocity (g/kg/day).No significant differences were found in weight gain velocity at 28 days, at 36 weeks of postmenstrual age, at discharge nor during intervention. Protein intake was significantly higher in AF group (5.02 g/kg/day vs 4.48 g/kg/day, p= 0.001). No differences were found in lipids, carbohydrates and energy intake; neither in weight z score change between the different time points; nor in length and head circumference growth. Both AF and TF are comparable methods of fortification and provide appropriate growth rate in ELBW infants.

In this study, a decentralized incineration facility was evaluated over a three-year period, focusing on performance aspects such as burning rate, ash production, fuel and electricity consumption, and ash composition while processing animal by-products (ABP). The total cost for ABP incineration was determined to be 159 € per ton of ABP, with the major components being capital depreciation (42%), maintenance expenditures (26%), labor (18%), and transportation costs (9%). Liquified petroleum gas (LPG) consumption ranged from 3-7 kg per ton of ABP, while electricity use was between 15-20 kWh per ton of ABP incinerated. The incineration process generated 7-10% (by weight) ABP ash, which was characterized by high calcium and phosphorus content and low levels of hazardous trace elements. Leaching tests demonstrated the potential for recovering the alkaline supernatant for flue gas treatment and the phosphorus-rich slurry for fertilizer production. The findings suggest that energy recovery and valorization are crucial for minimizing operational costs and environmental impact, emphasizing the benefits of integrating advanced resource recovery techniques in ABP incineration facilities.

The task of human action recognition (HAR) based on skeleton data is a challenging yet crucial technique owing to its wide-ranging applications in numerous domains, including patient monitoring, security surveillance, and observation of human-machine interactions. While numerous algorithms have been proposed in an attempt to distinguish between a myriad of activities, most practical applications necessitate highly accurate detection of specific activity types. This study proposes a novel and highly accurate spatiotemporal graph autoencoder network for HAR based on skeleton data. Furthermore, an extensive investigation was conducted employing diverse modalities. To this end, a spatiotemporal graph autoencoder was constructed to automatically learn both spatial and temporal patterns from human skeleton datasets. The powerful graph convolutional network, designated as GA-GCN, developed in this study, notably outperforms the majority of existing state-of-the-art methods when evaluated on two common datasets, namely NTU RGB+D and NTU RGB+D 120. On the first dataset, the proposed approach achieved accuracies of 92.3\% and 96.8\% for the cross-subject and cross-view evaluations, respectively. On the more challenging NTU RGB+D 120 dataset, GA-GCN attained accuracies of 88.8\% and 90.4\% for the cross-subject and cross-set evaluations, respectively.

Interactions between human immunodeficiency virus type 1 (HIV-1) and the host factors or restriction factors of its target cells determine the cell’s susceptibility to, and outcome of, infection. Factors intrinsic to the cell are involved at every step of HIV-1’s replication cycle, contributing to productive infection and replication, or severely attenuating HIV-1’s chances of success. Furthermore, factors unique to certain cell types contribute to the differences in infection between these cell types. Understanding the involvement of these factors in HIV-1 infection is a key requirement for the development of anti-HIV-1 therapies. As the list of factors grows, and the dynamic interactions between these factors and the virus are elucidated, comprehensive and up-to-date summaries that recount the knowledge gathered after decades of research are beneficial to the field, displaying what is known so that researchers can build off the groundwork of others to investigate what is unknown. Herein, we aim to provide a review focusing on protein host factors, both well-known and relatively new, that impact HIV-1 replication in a positive or negative manner at each stage of the replication cycle, highlighting factors unique to HIV-1’s various target cell types where appropriate.

Human-robot collaboration is a new trend in modern manufacture. The safety or human protection is of great significance due to the share of the same workshop between humans and robots. To achieve effective protection, in this paper, a contact force sensor based on the 8-shaped wound polymer optical fiber is proposed. The 8-shaped wound structure can convert the normal contact force to the shrinkage of the 8-shaped optical fiber ring. The macro-bending loss of the optical fiber is used to detect the contact force. Compared with conventional sensors, the proposed scheme has the advantage of high flexibility, low cost, fast response, high repeatability, which shows the great promise on actively alarming collision and passively reducing the hurt.

This paper introduces a quantitative methodology for assessing drone pilot performance, aiming to reduce drone-related incidents by understanding the human factors influencing performance. The challenge lies in balancing evaluations in operationally relevant environments with those in a standardized test environment for statistical relevance. The proposed methodology employs a novel virtual test environment that records not only basic flight metrics but also complex mission performance metrics, such as the video quality from a target. A group of Belgian Defence drone pilots were trained using this simulator system, yielding several practical results. These include a human performance model linking human factors to pilot performance, an AI co-pilot providing real-time flight performance guidance, a tool for generating optimal flight trajectories, a mission planning tool for ideal pilot assignment, and a method for iterative training improvement based on quantitative input. The training results with real pilots demonstrate the methodology’s effectiveness in evaluating pilot performance for complex military missions, suggesting its potential as a valuable addition to new pilot training programs.

This study delves into the transformative growth of private higher education in China, highlighting the rapid and diverse expansion following the COVID-19 pandemic. Although previous studies have reported expansion and difficulties, a thorough examination of the relationship between institutional adaptation and the development of human capital remains unexplored. This study examines how private higher education institutions modify their job-related courses to suit the demands of the job market, evaluates the effect on the employability of graduates, and investigates ways to control costs without sacrificing academic quality. This study analyzes data from the Ministry of Education, Wind Information, and Shenwan Hongyuan Research to gain insights into the impact of human capital theory and institutional theory on private higher education in China. Enrollment trends, program alignment, financial sustainability, and quality enhancement activities are all examined using detailed analysis. Private higher education institutions play a critical role in developing a skilled labor force by filling skill gaps and meeting the demands of an evolving job market. The findings also emphasize the importance of quality assurance procedures, strategic program development, and collaborations with businesses. In conclusion, the study emphasizes the imperative for more research and policy action. This is crucial to securing the lasting effectiveness and influence of private higher education institutions on China's socioeconomic progress and human capital development in the post-pandemic era.

Epidermodysplasia verruciformis (EV) is a rare genodermatosis caused by β-human papillomaviruses (HPV) in immunodeficient patients. EV is characterized by flat warts and pityriasis-like lesions and might be isolated or syndromic, associated with some other infectious manifestations. We report here three patients from 2 independent families with syndromic EV for 2 of them. By whole exome sequencing, we found that patients carry new homozygous variants in STK4, both leading to a premature stop codon. STK4 deficiency causes a combined immunodeficiency characterized by a broad infectious susceptibility to bacteria, viruses and fungi. Auto-immune manifestations were also reported. Deep immunophenotyping revealed multiple cytopenia in the three affected patients, in particular deep CD4+ T cells deficiency. We report here the fourth and the fifth cases of syndromic EV due to STK4 deficiency.

Introduction: Laeverin is an extravillous trophoblast marker playing a significant role in the trophoblast migration. The purpose of this study was to evaluate the association between the amniotic and serum laeverin concentrations at 16-22 weeks of gestation and the fetal and placental ultrasound measurements in healthy, unaffected pregnancies. Materials and methods: This was a prospective cross-sectional study. Pregnant women with singleton pregnancies undergoing amniocentesis were recruited consecutively. Fetal structural malformations and/or aneuploidy were exclusion criteria. Fetal biometric parameters and placental growth/perfusion were measured in 44 high-risk pregnancies who had no pregnancy complication and any other chronic disease. Maternal serum and amniotic levels of laeverin were essayed with sandwich enzyme-linked immunosorbent assay. Results: Serum laeverin levels are decreasing slightly with the maternal age in mid-gestation. Serum laeverin level correlated negatively slightly with head size of the fetus with the gestational length at delivery (β=-0.38, 95% confidence interval (CI) -0.03-0.01), while the amniotic laeverin level correlated strongly with the abdominal circumference of the fetus (β=-0.64, 95% CI: -0.03-0.01). Furthermore, laeverin level in the amnion correlated moderately and positively with the placental volume (β=0.46, 95% CI: 0.01-0.08). Conclusions: Laeverin levels detected in the serum and in the amniotic fluid denotes the fetoplacental growth in uncomplicated high-risk pregnancies.

If an AI entity is conscious, then it deserves moral status and to have its welfare protected. Society has granted certain animals moral status and has legislation to protect animal welfare because these kinds of animals have been deemed to be sentient. This paper shows that for any entity that can be determined to be conscious, that entity deserves the same status and protection as sentient entities. The paper further develops a framework for how an AI entity's welfare can be protected, based on the Five Freedoms of Animal Welfare. The extant Five Freedoms are translated into terms more suitable for artificial entities, encompassing discomfort and harms, constraints on inherent functions, fear and distress, malfunction and degradation, and resource depletion. Each of the new Five Freedoms are justified using formalised arguments and supported using evidence from animal welfare literature. The paper concludes by presenting three formalised case studies to highlight the potential stressors conscious AI entities may face and how this ethical framework can work to protect the welfare of AI entities.

The purpose of this disquisition is to analyze bullfighting, its advances and setbacks at a global and local level in terms of animal law. It was developed as a descriptive documentary research with a non-experimental design, using the observation and interpretation of documents related to the subject, from the global level, to the local, the national, specific to the regions and communities, being interpreted through the hermeneutic method. In the analysis, results were reached such as: every day more countries are willing to assume that bulls, because they are living beings that feel, are being attended to from the legal and the ethical, propitiating changes in the way of thinking of people in terms of wanting to consider bullfighting, a sport, art and hobby considered cultural heritage of many countries. For this reason, different actions have been generated from surveys, to define the acceptance or not of these events. It is concluded that there are important advances in this regard, as bullfighting is being prohibited in different parts of the world, taking into account the protection that protects animals, but the laws do not establish specific prohibition in this regard worldwide.

Depictions of robots as romantic partners for humans are frequent in popular culture. As robots are becoming part of human society, they gradually assume the role of partners for humans wherever necessary: as assistants, collaborators, or companions. Companion robots are sup-posed to provide social contact to those humans who could not have it otherwise. These com-panion robots are usually not designed to fulfill one of the most important human needs: the one for romantic and intimate contact. Human-robot intimacy remains a vastly unexplored ter-ritory. In this article, we review the state-of-the-art research in intimate robotics. We discuss major issues limiting acceptance of robots as intimate partners, public perception of robots in in-timate roles, and the possible influence of cross-cultural differences in these domains. We also discuss possible negative effects human-robot intimacy may have on human-human contact. Most importantly, we propose a new term “Intimate companion robots” to reduce the negative connotations of other terms used so far and improve the social perception of research in the domain. With this article, we provide an outlook on prospects for the development of intimate companion robots, considering the specific context of their use.

The overall comfort experienced by an individual in an n-dimensional space can be theoretically constructed using a mathematical equation, that relates the comfort experienced by an individual in a particular point in space with spatial points associated with higher comfort attributes and the desirable factors affecting the current environmental space.

Critical phases in socio-technical systems (STS) design are the definition of functional requirements for automated or software supported human activities while also addressing social and human interaction issues. To define automation support for human operations, STS designers need to ensure that specifications will satisfy not only non-functional requirements (NFR) of the system but also of its human actors such as human reliability/workload. However, such human factors aspects are not addressed sufficiently with traditional STS design approaches which could lead to systems failure or rejection. This paper proposes a new STS design method that addresses this problem and introduces a novel type of requirements namely Task Support Requirements (TSR) that assists in specifying the functionality that the system should have to support human agents in undertaking their tasks by addressing human limitations. The proposed method synthesizes a requirements/software engineering approach to STS design with functional allocation and an HCI perspective which facilitate application of human factors knowledge in conceptual models and evaluation through VR simulation. A case study methodology is employed in this work that allows in-depth, multi-faceted explorations of the complex issues that characterize STS.

Nitrates can cause severe ecological imbalances in aquatic ecosystems, with considerable consequences for human health. Therefore, monitoring this inorganic form of nitrogen becomes essential for any water quality management structure. This research aimed at developing a novel Nitrate Portable Measurement System (NPMS) for monitoring nitrate concentrations in water samples. NPMS is a reagent-free ultraviolet system developed using low-cost electronic components. Its operation principle is based on Beer-Lambert law for measuring Nitrate concentrations in water samples through light absorption in the spectral range 295-315 nm. The system is equipped with ready to use ultraviolet sensor, Light Emission Diode (LED), op-amp, microcontroller, liquid crystal display, quartz cuvette, temperature sensor, and battery. All the components are assembled in a 3D-printed enclosure box which allows a very compact self-contained equipment, with high portability, enabling field and near real time measurements. The proposed methodology and the developed instrument were used to analyse multiple nitrate standard solutions. The performance was evaluated in comparison with the Nicolet Evolution 300, a classical UV-Vis spectrophotometer. The results demonstrate a strong correlation between the retrieved measurements by both instruments within the investigated spectral band and for concentrations above 5 mg NO3- /l.

Lifecycle assessment (LCA) quantified changes in environmental impact categories (global warming, eutrophication, etc.) from 2021 to 2030 due to genetic trends in (re)production traits in pig lines of breeding company Genus-PIC. The 2030 levels were projected with se-lection index theory based on weightings of traits in the breeding goals and genetic covari-ances among them. Projected improvement was 0.9% annually for most impact categories. Another LCA compared impacts of 2021 North American pig production based on PIC ge-netics versus the industry average. Software openLCA converted material and energy flows to impact categories of frameworks ReCiPe-2016, PEF-3.1 and IPCC-2021. Flows came from data recorded by customers (1.1/4.7 million sows/finishing pigs) and by subscribers to a third-party data-aggregator (1.3/9.1 million). PIC genetics have a 7-8% better impact than industry average for 13/18 categories of ReCiPe-2016, 19/25 of PEF-3.1, and all categories of IPCC-2001. Pig breeding delivers positive environmental outcomes as correlated respons-es to selection for profitability-oriented breeding goals. This trend is additive; technology development will increase it. Different investment levels in breeding population structure and technology, and different operational efficiencies of breeding companies, cause substan-tial differences in the environmental impact of pig production.

Background: There are multiple conservative treatment options for plantar warts, but none have proven to be universally effective. Nitric acid is often used empirically by podiatrists in the treatment of plantar warts. A novel medical device or topical solution of nitric-zinc complex solution (NZCS) could potentially offer an effective and safe alternative for the targeted treatment of plantar warts. Objective: To observe the rate of complete healing of NZCS in a series of plantar wart cases, and to establish the minimum number of product applications and time needed for healing. This will help standardize and protocolize its use. Methods: A descriptive study was conducted involving 72 patients who exhibited symptoms of plantar warts. These patients underwent chemical treatment using a nitric-zinc complex. Results: The cure rate with NZCS was 59.2%. The average number of NZCS applications was 5.9 ± 3.0 and the mean duration of treatment was 9.4 ± 7.1 weeks. A recurrence rate of 6.7% (4/72 patients) was observed. Conclusion: The topical solution of nitric-zinc complex is an effective treatment for plantar warts, which can be considered as a first-line treatment option in the general population.

The proliferation of wearable technology enables the generation of vast amounts of sensor data, offering significant opportunities for advancements in health monitoring, activity recognition, and personalized medicine. However, the complexity and volume of this data present substantial challenges in data modeling and analysis, which have been tamed with approaches spanning time series modeling to deep learning techniques. The latest frontier in this domain is the adoption of Large Language Models (LLMs), such as GPT-4 and Llama, for data analysis, modeling, understanding, and generation of human behavior through the lens of wearable sensor data. This survey explores current trends and challenges in applying LLMs for sensor-based human activity recognition and behavior modeling. We discuss the nature of wearable sensors data, the capabilities and limitations of LLMs to model them and their integration with traditional machine learning techniques. We also identify key challenges, including data quality, computational requirements, interpretability, and privacy concerns. By examining case studies and successful applications, we highlight the potential of LLMs in enhancing the analysis and interpretation of wearable sensors data. Finally, we propose future directions for research, emphasizing the need for improved preprocessing techniques, more efficient and scalable models, and interdisciplinary collaboration. This survey aims to provide a comprehensive overview of the intersection between wearable sensors data and LLMs, offering insights into the current state and future prospects of this emerging field.

Abstract: Obesity and overweight also increasingly affect women of childbearing age and pregnant women. In maternal obesity, the activation of metabolic, inflammatory, and oxidative stress pathways is proven, which appears to be a key step in placental and uterus function pathological changes. Several recent studies have evidenced that aquaporins (AQPs) are critical players in adipose tissue biology and are involved in the onset of obesity. Our studies aimed to investigate the changes in placental volume and vascularization and measure the AQP5 expression and total antioxidant capacity (TAC) in the placenta and uterus tissues in obese and normal-weight mothers. We also aim to measure the AQP5 plasma concentration. We found AQP5 dominance in the uterus and plasma at 34 weeks of normal pregnancy. The placental volume increased, and the vascularization decreased in obese mothers compared to the control. The AQP5 expression increased in the uterus of the obese group and did not change in the placenta. The TAC decreased in the plasma of overweight mothers. We hypothesize that increased AQP5 expression prolongs the length of pregnancy and inhibits the onset of contractions. Based on our findings, we can develop diagnostic tests and provide new targets for tocolytic drug development.

Overconsumption of an unbalanced diet and overweight, leading to insulin resistance, dyslipidemia, hepatic steatosis, cardiovascular diseases and obesity, is nowadays a worldwide health issue, with different patterns of metabolic disturbances in the young and adult popula-tions, in both gender. Preclinical models that closely mimic the gradual weight gain that occurs in humans upon consumption of a “western-type” diet (WD) are of great interest. In particular, the diet-induced obesity (DIO) model in the C57BL/6J mouse sub-strain is often used in biomed-ical research, considering that it is prone to metabolic disorders and obesity, and is widely used to generate genetically modified mice. This study aimed to phenotypically characterize the C57BL/6J mouse strain fed a WD-like diet, using high-frequency ultrasound imaging (HFUS) as a complementary tool to longitudinally monitor morphofunctional changes in the liver, heart and kidney associated with DIO. Long term WD feeding increased mice body weight (BW), liver/BW ratio and body condition score (BCS), serum transaminases, glucose and insulin, as well as Homeostasis model assessment (HOMA) indexes, and caused dyslipidemia and insulin resistance. According to the 3Rs, ultrasound imaging has enabled a comprehensive study of metabolic syndrome in mice, in vivo and non-invasive, improving the identification of early stages of diseases.

Background: many studies, on for example taste-visual dissonance, have shown that the influence of the visual cortex on taste sensation is enormous. The aim of the presented work is to investigate, using fNIRS, whether a taste stimulus, in this case the taste of bitter, also causes stimulation of the visual cortex in fNIR study. Methods: 51 participants (204 examinations, 9 996 records) were examined with fNIRS, which collects signals from whole left hemisphere. Differences between the maximum and minimum changes in oxyHb concentrations (ΔoxyHb) for the areas of the brain cortex considered responsible for recording visual and gustatory signals were analyzed. Protocol I, II, III and IV – activation with distillate water, coffee with lower concentration, reference (no stimulation) and coffee with higher concentration respectively, were used. Results: We recorded high signals for teste activation on channels covered gustatory cortex, which confirms the correctness of the choice of research method. What seems important, and somewhat surprising, is the fact that we also received high signals for the channels 45-49, which cover the visual cortex. The statistical analysis does not show any statistical differences between the protocols I, II and IV (different taste activation – water, coffee A and coffee B) for specific channels. As a results of the analysis of the correlation between the subjective bitterness assessment solutions, and the signal ΔoxyHb height, it was observed that statically important correlation, although weak, occurs only for 14 and gustatory channels, only for coffee with a higher concentration. Additionally we recorded the only statistically significant difference between women and men for protocol I (water), where the ΔoxyHb signal was twice as high for women. Conclusions: In conclusion, we can clearly state that the senses of sight and taste work closely together. Moreover, this cooperation is not one-sided - not only the visual activation affects the perception of taste, but interestingly, the taste stimulus can generate a hemodynamic response - activity in the visual cortex.

This study explores the limitations of current AI systems, which predominantly function in the digital realm, and investigates the transformative potential of embodied AI. Embodied AI involves AI agents equipped with physical bodies, enabling them to interact directly with the physical world. This research focuses on how embodied AI can bridge the "embodiment gap" and enhance human-machine collaboration and learning in dynamic environments. The research examines the fundamental differences between traditional AI systems and embodied AI, emphasizing the importance of physical interaction for contextual understanding, adaptive learning, and intuitive human-machine collaboration. It explores various applications of embodied AI, including robotics, autonomous vehicles, and assistive technologies, demonstrating how physical embodiment can improve performance, safety, and user experience. Through experimental studies and real-world case analyses, the study highlights the advantages of embodied AI in tasks requiring situational awareness, dexterity, and real-time decision-making. It also addresses the challenges associated with developing and deploying embodied AI systems, such as sensor integration, real-time processing, and human-machine interface design. Findings indicate that embodied AI can significantly improve the efficacy of AI systems in dynamic and unpredictable environments. By leveraging physical embodiment, AI agents can better understand and respond to their surroundings, facilitating more natural and effective interactions with humans. The research concludes with recommendations for advancing embodied AI, including interdisciplinary collaboration, investment in sensor and actuator technologies, and the development of standardized frameworks for embodied intelligence.

Fungal infections (FIs) are spreading globally causing a significant public health concern. However, its documentation remains sparse in Africa, particularly in Rwanda. This literature review, aims to assess the risk and document current gaps in evidence and policy. It summarizes the published data about FIs in Rwanda, including ten reports published between 1972-and-2022. Blastomyces, Candida, Cryptococcus, Histoplasma, Microsporum, Pneumocystis, Rhinosporidium, and Trichophyton caused human infections. These infections primarily affected the brain, respiratory, urinary and reproductive organs, and they were diagnosed using culturing, histopathology, immunology, and/or microscopic techniques. Our findings provide an overview of the diversity and distribution of FIs, highlighting significant limitations in the country’s diagnostic capacity and surveillance system for FIs. Also, indicating severe gaps in evidence to inform policymaking, guide strategic planning and intervention, underscoring the urgent need to build national capacity in fungal diagnosis, surveillance, and research. Raising awareness among the public, scientific community, healthcare providers, and policymakers remains crucial. Furthermore, this report reveals the threats of FIs on public health and food insecurity in Rwanda. A Multisectoral One Health Strategy is essential in research and intervention to determine and reduce the health and safety impacts of fungal pathogens on human, animal, and the environment.

The genus Aeromonas is widely distributed in aquatic environments. It is frequent as a fish pathogen, but has also been described associated to human infections. Most human cases are caused by A. caviae, A. veronii biovar sobria, and A. hydrophila, though A. dhakensis is becoming increasingly important. Transmission happens primarily by ingestion or contact with aquatic collections, or by consumption of contaminated food, especially of aquatic origin. Increasing resistance has been described in Aeromonas to penicillins, including their combinations with classical b-lactamase inhibitors, cephalosporins and carbapenems. Among the b-lactam antibiotics, only the 4th generation cephalosporins remain almost uniformly active. In addition, the simultaneous presence of resistance genes to 3rd generation cephalosporins and carbapenems in the same isolates is increasing. Recently, the presence of mobile genes linked to colistin resistance has also been described, in some cases with resistance percentages higher than 30%. Most likely, this evolution of colistin resistance is linked to its use in aquaculture, and, together with the evolution of b-lactam resistance, may be turning this genus into a reservoir of resistance genes that may affect other species much more frequently linked to human infections, such as Enterobacterales.

There is a lot of pressures from organizations to continually redesign the business processes and the technology infrastructure to support the organization, but to also help organizations manage competing stakeholder needs, changing objectives and behaviour, and so on. A key part of this is making sure that all their activities in the different components of the business are interconnected and that they are moving in the same direction. Enterprise Architecture (EA) is an effective way of dealing with the challenge of designing business activities and supporting IT. This paper will summarize the organization of EA and look more closely at some major components of EA: governance architecture, business architecture, information architecture and technical architecture and consider the overlap and constructive interaction involved. Enterprise Architecture can be best understood through business process redesign. So, it is useful to briefly review the leading frameworks for business process redesign, including COBIT from ISACA, LEAN from the Toyota Group, TOGAF from the Object-Management Group, and the Capgemini Integrated Architecture Framework (IAF). All these frameworks allow us to more successful transformation, to return to the central idea of this paper.