: This study investigates the workplace experiences of mothers of children with intellectual disabilities. These mothers may face challenges in balancing motherhood, disability, and employment. Therefore, it is important to understand the challenges they are facing and the mechanisms they use to cope with caregiving and work responsibilities in managing the stress that develops throughout this ongoing experience. The purpose of this research was to investigate the workplace experiences of single mothers of children with intellectual disabilities. A review of the literature was conducted. For this research, a qualitative methodology was adopted to gain an in-depth understanding of the mothers’ experiences. A narrative method was used for data collection. Thematic analysis was utilized to obtain a clear understanding. The findings suggest that mothers of children with intellectual disabilities face difficulties in balancing between caregiving for their child with a disability and their job responsibilities, in addition to showing that there is a lack of flexibility in the workplace, less awareness from colleagues and bosses of the challenges these mothers face, and a lack of organizational legislation that supports these mothers. According to our findings, workplaces should provide assistance to mothers of children with intellectual disabilities in order to ensure that they are not disadvantaged in their employment.

In recent years, in order to serve as effective solutions to outdoor human thermal environments under the influence of urban heat islands, adaptation measures such as awnings, louvers, directional reflective materials, mist sprays, and evaporative materials have been developed. In this study, a simplified evaluation framework for adaptation measures to urban heat islands is examined. Adaptation measures to urban heat islands are classified into the following three categories; measures to reduce solar radiation incident on the human body, measures to control and cool ground and wall surface temperature, and measures to control and cool air temperature and human body. Case studies are conducted to evaluate the effects of the implementation of cool water circulation sunshade and to examine the adverse effects of cool pavements on the human thermal environment, in addition to the effects of mist sprays on the human body. The effect of the sunshade, watering road, and mist spray, which are typical adaptation measures to urban heat islands, on the human thermal environment was estimated using Wet Bulb Globe Temperature (WBGT) as an indicator for heat stroke prevention and Standard New Effective Temperature (SET*) as an indicator for thermal comfort assessment.

When analyzing user geospatial information through deep learning methods, it is typically necessary to annotate existing geospatial data. Currently, manual annotation methods are commonly employed, suffering from issues related to low efficiency and accuracy. This design is based on the TensorFlow deep learning framework and first realizes the BiLSTM+CRF+AGG deep learning model. Among the models, AGG is the aggregation layer, which is introduced to solve the problem of solid particle size equilibrium. Secondly, based on the characteristics of original data and professional data, an automatic labeling algorithm is proposed. The algorithm first preprocesses the acquired original data set and professional data set, The most valuable unlabeled data set which can make the training model converge quickly is selected from the original data set as the target data set. Sort the target data set based on preset rules and set annotation parameters for the sorted target data set. Based on the set annotation parameters, the corpus is synthesized and used as the annotation result. Thirdly, based on the active learning strategy, a manual annotation auxiliary scheme is proposed, and an Excel generation module that is convenient for manual annotation correction is designed and developed to further improve the efficiency and quality of annotation through iterative processing. The combination of the BiLSTM+CRF+AGG deep learning model and high-quality annotation can accurately identify non-standard, incomplete, or even incorrect geographical information entities. This annotation method has found successful practical application within the context of the research project and has been granted an invention patent.

Visual Patient Avatar ICU is an innovative approach to patient monitoring enhancing the user's situation awareness in intensive care settings. It dynamically displays the patient's current vital signs through changes in color, shape and animation. The technology can also indicate patient-inserted devices, such as arterial lines, central lines and urinary catheters, along with their insertion locations. We conducted an international, multi-center study using a sequential qualitative-quantitative design to evaluate users' perception of Visual Patient Avatar ICU among physicians and nurses. Twenty-five nurses and twenty-five physicians from the ICU participated in the structured interviews. Forty of them completed the online survey. Overall, ICU professionals expressed a positive outlook on Visual Patient Avatar ICU. They described Visual Patient Avatar ICU as a simple and intuitive tool that improved information retention and facilitated problem identification. However, a subset of participants expressed concerns about potential information overload and a sense of incompleteness due to missing exact numerical values. These findings provide valuable insights into user perceptions of Visual Patient Avatar ICU and encourage further technology development before clinical implementation.

Background: In March 2020, a COVID-19 outbreak associated with the Falles Festival in Borriana, Spain, led to significant infections. Methods: In June 2022, we conducted a cross-sectional follow-up study of 473 socially engaged adults aged 18 to 64, examining the cumulative experience after SARS-CoV-2 infection and vaccination responses. Data included demographic details, lifestyle habits, medical history, infection records, and vaccinations from a population-based vaccine registry. Blood samples were analyzed for SARS-CoV-2 antibodies and cellular immunity. We employed a doubly robust inverse weighted probability analysis to estimate the booster vaccine dose's impact on long COVID prevalence and symptom count. Results: 28.1% of participants met the WHO criteria for long COVID, with older individuals showing higher rates. Not complying with long COVID criteria associated with factors including O blood group, higher occupational status, physical activity, three vaccine doses, strong SARS-CoV-2-S-reactive IFNγ‐producing‐CD8+ response, and infection during the Omicron period. Conversely, increased age, high or low social activity, underlying health conditions, a severe initial COVID episode, and reinfection associated with higher long COVID likelihood. A booster dose, compared to one or two doses, reduced long COVID risk by 74% (95% CI: 56.4% to 91.7%) and symptom count by 55.2% (95% CI: 31.6% to 78.7%). Conclusion: Long COVID was prevalent in a significant portion of those who contracted COVID-19, underscoring the need for sustained follow-up and therapeutic strategies. Vaccinations, notably the booster dose, had a substantial beneficial effect on long-term infection outcomes, affirming the vaccination’s role in mitigating SARS-CoV-2 infection consequences.

This article explores the possible ramifications of incorporating ideas from AEC Industry 6.0 into the design and construction of intelligent, environmentally friendly, and long-lasting structures. This statement highlights the need to shift away from the current methods seen in the AEC Industry 5.0 to effectively respond to the increasing requirement for creative and environmentally sustainable infrastructures. The preceding methodology, AEC Industry 6.0, has substantially improved the efficacy and sustainability of construction by using new technology, digitalization, and environmentally conscious methods. Extensive discussions have occurred on the various benefits of AEC Industry 5.0. These merits include heightened stakeholder involvement, increased efficiency via automation and robots, decision-making processes centered around data, and the optimization of resources. Nevertheless, this study also examines the obstacles linked to the complete adoption of AEC Industry 6.0. These challenges require proficient professionals who can effectively utilize contemporary technologies, manage diverse stakeholder technological competencies, establish interoperable systems and standards, and reinforce cybersecurity measures. This study examines the viability of implementing concepts from Industry 6.0 to create intelligent, sustainable, and environmentally friendly structures. The objective is to showcase the potentially revolutionary impact that these principles may have on the construction industry. This study explores the possible applications of AEC Industry 6.0 within the Architecture, Engineering, and Construction (AEC) sector, explicitly highlighting the anticipated industry-wide consequences of the forthcoming paradigm shift. This paper comprehensively examines big data analytics, the Internet of Things (IoT), and collaborative robots as they pertain to the AEC Industry 6.0. This research investigates the interplay between organizational dynamics, human actors, and robotic systems to provide light on the opportunities and obstacles associated with integrating AEC Industry 6.0 concepts into the construction of buildings.

Our lives are comprised of moment-to-moment activity experiences. According to the Model of Human Occupation (MOHO), our occupational experiences can be affected by volition, which consists of personal causation, values, and interests. This study investigated how momentary volition affected occupational satisfaction and mind-wandering while performing occupations. This study also examined the relationship between momentary volition and the overall life perspectives of life satisfaction and life balance. Undergraduate students participated in this cross-sectional study. The experience sampling method (ESM) was used to measure students’ momentary states such as activity, volition, occupational satisfaction, and mind-wandering. After conducting the ESM, the participants’ life satisfaction was measured using the Satisfaction With Life Scale (SWLS), and their life balance was measured by the Life Balance Inventory (LBI). Forty-two participants and 1,092 sampling data were included in the analysis. Momentary personal causation, values, and interests contributed to occupational satisfaction. Mind-wandering was predicted negatively by interests but positively by personal causation. Momentary interests were positively correlated with SWLS and LBI scores. This study demonstrated that momentary volition was associated with occupational satisfaction and engagement, as well as life satisfaction and balance, in undergraduate students.

There is a growing interest in glial cells in the central nervous system due to their important role in maintaining brain homeostasis both under physiological conditions and after injury. A significant amount of evidence has been accumulated regarding their capacity to exert either pro-inflammatory or anti-inflammatory effects under different pathological conditions. In combination with their known proliferative potential, they contribute not only to the limitation of brain damage and tissue remodeling but also to neuronal repair and synaptic recovery. Moreover, reactive glial cells can modulate the processes of neurogenesis, proliferation, and migration of neurons in the existing neural circuits in the adult brain. By discovering precise signals within specific niches, the regulation of sequential processes in adult neurogenesis holds the potential to unlock strategies that can stimulate the generation of functional neurons, whether in response to injury or as a means of addressing degenerative neurological conditions. Cerebral ischemic stroke, a condition falling within the realm of acute vascular disorders affecting the circulation of the brain, stands as a prominent global cause of disability and mortality. Extensive investigations into glial plasticity and their intricate interactions with other cells in the central nervous system have predominantly relied on studies conducted on experimental animals, including rodents and primates. However, valuable insights have also been gleaned from in vivo studies involving post-stroke patients, utilizing highly specialized imaging techniques. Following the attempts to map brain cells, the role of various transcription factors in modulating gene expression in response to cerebral ischemia is gaining increasing popularity. Although the results obtained thus far remain incomplete and occasionally ambiguous, they serve as a solid foundation for the development of strategies aimed at influencing the recovery process after ischemic brain injury.

Classic mitochondrial DNA phylogenetic and phylogeographic studies on the aboriginal, historical, and extant human populations of the Canary Islands have contributed to reconstructing the origin and settlement on the islands of the pre-European colonizers. The recent use of new ancient DNA targeted enrichment and next-generation sequencing techniques on new Canary Islands samples has greatly improved these molecular results, but it has also revealed significant contamination in the islands' previous aboriginal genetic pool. Following a thorough review of these cases, new phylogeographic analysis revealed the existence of a heterogeneous aboriginal population, asymmetrically distributed across the various islands, and most likely descended from a unique main settlement. These new results and new proposed coalescent ages are compatible with a Roman-mediated arrival driven by the exploitation of the purple on the Canary Islands.

This article presents a state-of-the-art literature review to understand people’s perceptions and opinions of Autonomous Vehicles (AVs) and the factors that influence AV adoption. A strategic literature search was conducted to select articles for this review. Most of the articles were published within the last five years and they used a household questionnaire survey to collect data. Mostly, they used statistical and econometric methods to evaluate the factors that affect people’s intentions to adopt AVs. The results show that psychological factors often appear as the most important internal factors of people’s willingness to adopt AVs. Additionally, other internal factors such as the socioeconomic profile of individuals and their household, and knowledge and familiarity with AV technologies would affect AV adoption tendencies. User attributes also indirectly affect AV adoption by influencing the psychological factors of users. We identify several critical external factors such as opportunities (e.g., safety and security, low congestion, energy use) and challenges (e.g., system failure, privacy breach, and legal issues), while another influential group includes transportation factors (e.g., travel mode, distance, and time), urban form (e.g., urban/rural, density, land use diversity), affinity to new technology, and the institutional regulatory environment. We discuss some recommendations for policy makers, auto industries, and private stakeholders to formulate policies and strategies to increase market share of AVs. Finally, we identify some limitations of previous studies and provide a blueprint for future research on AV adoption.

This study aims to investigate the impact of body heat loss on the thermal and aerodynamic conditions in a whole-body cryotherapy chamber. The underlying hypothesis is that the heat generated by the human body alters the thermal and aerodynamic environment inside the cabin. A numerical study was conducted to test this hypothesis to analyze the thermodynamic exchanges between the human body and the cabin during a 3-minute whole-body cryotherapy session. The computational fluid dynamics (CFD) approach was used to study the unsteady heat transfer between the human body and the interior of the cryotherapy cabin. A thermal boundary condition, based on a mathematical model developed from experimental data, was applied to simulate skin cooling kinetics over time. The post-processing of the 3D results, including temperature, velocity fields, and thermal flux maps at the body surface, provided insight into the thermo-convective mechanisms involved in a whole-body cryotherapy session. The study found that body heat loss significantly affects the temperature fields inside the cabin, leading to global modifications of the aeraulic and thermal conditions. These findings suggest that cryotherapy protocols may need to be adjusted or the cabin set temperature optimized to enhance the therapeutic benefits.

To understand the evolution of the human norovirus GII.P6-GII.6 and GII.P7-GII.6 strains, we analyzed both the RdRp region and VP1 gene in globally collected strains using authentic bioinformatics technologies. A common ancestor of the P6- and P7-type RdRp region emerged approximately 50 years ago and a common ancestor of the P6- and P7-type VP1 gene emerged approximately 110 years ago. Subsequently, the RdRp region and VP1 gene evolved. Moreover, the evolutionary rates were significantly faster for the P6-type RdRp region and VP1 gene than the P7-type RdRp region and VP1 genes. Large genetic divergence was observed in the P7-type RdRp region and VP1 gene compared with the P6-type RdRp region and VP1 gene. The phylodynamics of the RdRp region and VP1 gene fluctuated after the year 2000. Positive selection sites in VP1 proteins were located in the antigenicity-related protruding 2 domain, and these sites overlapped with conformational epitopes. These results suggest that the GII.6 VP1 gene and VP1 proteins evolved uniquely due to recombination between the P6- and P7-type RdRp regions in the HuNoV GII.P6-GII.6 and GII.P7-GII.6 virus strains.

The flora and vegetation of oceanic islands have been deeply affected by human settlement and further landscape modifications during prehistoric and historical times. The study of these transformations is of interest not only for understanding how current island biotas and ecological communities have been shaped but also for informing biodiversity and ecosystem conservation. This paper compares two oceanic insular entities of disparate geographical, environmental, biological, historical and cultural characteristics – Rapa Nui (Pacific Ocean) and the Azores Islands (Atlantic Ocean) – in terms of human settlement and further landscape anthropization. The similarities and differences between these islands/archipelagos are discussed considering their permanent colonization, the possibility of earlier settlements, the removal of the original forests and the further landscape transformations leading to either full floristic/vegetational degradation (Rapa Nui) or major replacement (Azores). This comparison uses evidence from varied disciplines, notably paleoecology, archaeology, anthropology and history, to obtain a holistic view of the development of the respective socioeconomic systems from a human ecodynamic perspective. The most relevant issues still to be resolved are identified and some prospects for future research are suggested. The cases of Rapa Nui and Azores Islands may help set a conceptual basis for ocean-wide global comparisons among oceanic islands/archipelagos.

Virtual reality experiences are frequently created using game engines, yet they are not simple for novices and unskilled professionals who don’t have programming and 3D modeling skills. Concurrently, there is a knowledge gap in software project design for intuitive virtual reality authoring tools, which were supposed to be easier to use. This work compiles design guidelines derived from a systematic literature review to contribute in the development of more intuitive virtual reality authoring tools. We searched the Scopus and Web of Science databases for works published between 2018 and 2021 and discovered 14 papers. We compiled 14 requirement and feature design guidelines, such as Visual Programming, Immersive Authoring, Reutilization, Sharing and Collaboration, Metaphors, and Movement Freedom, among others. The collected guidelines have the potential to either guide the development of new authoring tools or to evaluate the intuitiveness of existing tools. Furthermore, they can also support the development of the metaverse, since virtual content creation is one of its bases.

Tuberculosis (TB) is still a worldwide major health problem and models using non-human primates (NHP) provide the most relevant approach for vaccine testing. In this study we have analysed CT images collected from cynomolgus and rhesus macaques, following exposure to ultra-low dose Mycobacterium tuberculosis (Mtb) aerosols, and monitored them for 16 weeks to evaluate the impact of prior intradermal or inhaled BCG-vaccination on the progression of lung disease. All lesions found (2553) have been classified according to their size and we have subclassified small micronodules (<4.4 mm) as ‘isolated’, or as ‘daughter’ when they are in contact with consolidation (described as lesions ≥ 4.5 mm). Our data links the higher capacity to contain Mtb infection in cynomolgus with the reduced incidence of daughter micronodules, thus avoiding the development of consolidated lesions and their consequent enlargement and evolution to cavitation. In the case of rhesus, intradermal vaccination has a higher capacity to reduce the formation of daughter. This study supports the ‘Bubble Model’ defined with the C3HBe/FeJ mice and proposes a new method to evaluate outcome in experimental models of TB in NHP based on CT images, which would fit a future machine learning approach to evaluate new vaccines.

The real challenge in Human Robot Interaction (HRI) is to build machines capable of perceiving human emotions so that robots can interact with humans in a proper manner. It is well known from the literature that emotion varies accordingly to many factors. Among these, gender represents one of the most influencing one, and so an appropriate gender-dependent emotion recognition system is recommended. In this paper, a two-level hierarchical Speech Emotion Recognition (SER) system is proposed: the first level is represented by the Gender Recognition (GR) module for the speaker’s gender identification; the second is a gender-specific SER block. Specifically for this work, the attention was focused on the optimisation of the first level of the proposed architecture. The system was designed to be installed on social robots for hospitalised and living at home elderly patients monitoring. Hence, the importance of reducing the software computational effort of the architecture also minimizing the hardware bulkiness, in order for the system to be suitable for social robots. The algorithm was executed on the Raspberry Pi hardware. For the training, the Italian emotional database EMOVO was used. Results show a GR accuracy value of 97.8%, comparable with the ones found in literature.

Microbiome First Medicine is a suggested 21st century healthcare paradigm that prioritizes the entire human, the human superorganism, beginning with the microbiome. To date, much of medicine has protected and treated patients as if they were a single species. This has resulted in unintended damage to the microbiome and an epidemic of chronic disorders [e.g., noncommunicable diseases and conditions (NCDs)]. Along with NCDs came loss of colonization re-sistance, increased susceptibility to infectious diseases, and increasing multimorbidity and polypharmacy over the life course. To move toward sustainable healthcare, the human micro-biome needs to be front and center. This paper presents microbiome-human physiology from the view of systems biology regulation. It also details the ongoing NCD epidemic including the role of existing drugs and other factors that damage the human microbiome. Examples are provided for two entryway NCDs, asthma and obesity, regarding their extensive network of comorbid NCDs. Finally, the challenges of ensuring safety for the microbiome are detailed. Under Microbiome First Medicine and considering the importance of keystone bacteria and critical windows of development, changes in even a few microbiota-prioritized medical decisions could make a significant difference in health across the life course.

In recent years in Bangladesh, there has been regular cyclonic event, flooding and erratic pre-monsoons precipitation that has hampered production greatly and forced Bangladesh to import salt from abroad to manage market deficiency. There is much uncertainty about the effects of climate change on the frequency and intensity of small-scale, sudden onset weather phenomena such as heavy rainfall and subsequent loss and damage (L&D). But, several studies indicate that an obvious strong relationship exists between irregular rainfall and associated L&D. Nowadays, severe changing rainfall patterns are observed in Bangladesh, which is rapid-onset in nature, but low exposed in terms of response. The current study explored a ‘double-exposed’ burden combined of both climatic (e.g., uneven rainfall) and non-climatic governance factors (e.g., imperfect trade policy, the absence of risk transfer mechanisms) which are hindering salt production and pushing the country from the aspiration of salt exporting to the net buyer. This chapter mainly assesses the impacts of L&D due to climatic events that are causing overwhelming effects on the well-being of marginal salt farmers at Kutubdia Upazila of Bangladesh. Data were mainly collected through Participatory Vulnerability Analysis (PVA), Key informant interviews (KII), and Sample Surveys (SS). This study would provide insights for improved disaster management policy and an appropriate adaptive measure to address such extreme events as well as to initiate a further study for understanding the nexus of ‘nature and market’ in building resilience among the marginal salt farmers.

Open-plan office (OPO) layouts emerged to allow organizations to adapt to changing workplace demands. We explore the potential for OPOs to provide such adaptive capacity to respond to two contemporary issues for organizations: the chronic challenge of environmental sustainability, and the acute challenges emerging from the great COVID-19 homeworking experiment. We apply a socio-technical systems perspective and green ergonomics principles to investigate the relationship between an OPO environment and the occupants working within it. In doing so, we consider the relevant technical and human factors such as green technology and employee green behavior. We also consider how a green OPO might provide non-carbon benefits such as improving occupant wellbeing and supporting the emergence of a green organizational culture. Our investigation highlights several avenues through which an OPO designed with green ergonomic principles could benefit occupants, the organizations they work for, and the natural environment of which they are a part and on which they depend. We find reason to suspect that green OPOs could play an important role in sustainable development; and offer a research agenda to help determine whether in fact OPOs are another example of how going green is good business.

Groundwater habitats in the Dinaric Karst are home to the only known cave-adapted genus of bivalve mollusks, which currently survives as three distinct species with a highly fragmented distribution. Over the past few decades, Congeria populations suffered a steep decline across their range, as a result of human activities. Here, we identify the most pressing issues concerning the current conservation status of Congeria and identify key priorities for its scientific study. The building of dams and other hydrotechnical constructions have led to a significant decrease in the water inputs that used to supply underground systems where Congeria lives, contributing to a reduction of the cave habitats feasible for bivalve settlement. This is relatively well documented in Popovo polje where, as a result of hydrotechnical interventions on Trebisnjica river, water level drop destroyed well over 99 % of Congeria kusceri population in Zira cave and caused their complete disappearance in other caves. Similar factors are likely to have also affected the sister species Congeria jalzici in the Lika region. In addition, the salinization of Neretva river, lack of proper wastewater management, intense agriculture, tourist exploitation, and additional hydrotechnical plans add to the ongoing decline of the quality of Congeria habitats. These threats are expected to least to drastic reductions in population size within the next few decades, and this situation might be further aggravated by the lack of regulations and active measures for Congeria protection, as well by the limited understanding of its biology. Future scientific studies should be aimed at better elucidating microhabitat preference, defining the range of tolerance of environmental parameters, and assessing the size and genetic viability of existing Congeria populations. However, we highlight that these efforts would most certainly require the collaboration of local authorities and the allocation of appropriate financial resources in order to be effective.

Objectives: Our objective was to assess employer preparedness to protect their employees’ health and safety and promote their well-being in the face of potential disasters in a sample of Northeast United States employers. We developed survey instrument and index based on our model of Total Worker Health® (TWH) Employer Preparedness.Methods: We conducted a 40-question on-line survey with the membership of the Northeast Human Resources Association (US). Human resource managers reported their perceptions of their employers’ preparedness in seven domains: planning, human resources policies, hazard reduction, training, staffing, communications, and resources for resilience. Respondents were categorized by size, sector and reach and their responses scored.Results: Seventy-six individuals representing a diverse group of employers responded to the survey. Mean preparedness was “moderate,” with almost an equal number reporting a high level of preparedness as no preparedness. Employers were most prepared for severe weather events and least prepared for acts of violence. There were no significant differences by sector, size, or reach, although the healthcare sector was more prepared than others.Conclusions: There is a range of TWH® Employer Preparedness among Northeast US employers. The survey and model are important tools that can aid employers in the face of growing threats to “business as usual.”

A crewed mission to and from Mars may include an exciting array of enabling biotechnologies that leverage inherent mass, power, and volume advantages over traditional abiotic approaches. In this perspective, we articulate the scientific and engineering goals and constraints, along with example systems, that guide the design of a surface biomanufactory. Extending past arguments for exploiting stand-alone elements of biology, we argue for an integrated biomanufacturing plant replete with modules for microbial \textit{in situ} resource utilization, production, and recycling of food, pharmaceuticals, and biomaterials required for sustaining future intrepid astronauts. We also discuss aspirational technology trends in each of these target areas in the context of human and robotic exploration missions in the coming century.

Pesticides have a vital contribution to the agricultural industry in Australia. However, pesticide applications may not always selective to its target organism. Exposure to pesticide has been associated with negative impacts to human health. One of the ways to reduce pesticide risk to the population and the environment is through government regulations. To put Australia pesticide regulations into perspective, comparisons were made between Australia and other nation’s pesticides regulations. The EU pesticide regulatory system was chosen for comparison with the Australian’s in the aspect of protecting the population from pesticide exposure. The comparison showed that the assessment to authorize a pesticide in Australia is based on the risk while in the EU, the assessment is based on the hazard of the pesticide. A registered active substance in Australia can be authorized for use indefinitely unless it is nominated for reconsideration while the period of registration of an active substance in the EU lasts for 10 years. In addition, no routine systematic chemical residue surveys are conducted in Australia for food commodities. The results highlight areas for improvement in the Australian pesticide regulatory system from the perspective of controlling undue exposure among the general population.

The recent growth of high-resolution spatial data, especially in developing urban environments, is enabling new approaches to civic activism, urban planning and the provision of services necessary for sustainable development. A special area of great potential and urgent need deals with urban expansion through informal settlements (slums). These neighborhoods are too often characterized by a lack of connections, both physical and socioeconomic, with detrimental effects to residents and their cities. Here, we show how a scalable computational approach based on the topological properties of digital maps can identify local infrastructural deficits and propose context-appropriate minimal solutions. We analyze 1 terabyte of OpenStreetMap (OSM) crowdsourced data to create worldwide indices of street block accessibility and local cadastral maps and propose infrastructure extensions with a focus on 120 Low and Middle Income Countries (LMIC) in the Global South. We illustrate how the lack of physical accessibility can be identified in detail, how the complexity and costs of solutions can be assessed and how detailed spatial proposals are generated. We discuss how these diagnostics and solutions provide a multiscalar set of new capabilities – from individual neighborhoods to global regions – that can coordinate local community knowledge with political agency, technical capability, and further research.

In December 2019, pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection emerged in Wuhan City, Hubei Province, China. Early in 2020, the World Health Organization (WHO) announced a new name for the 2019-nCoV-caused epidemic disease: coronavirus disease 2019 (COVID-19) and declared COVID-19 to be the sixth international public health emergency. Cellular co-infection is a critical determinant of both viral fitness and infection outcome and plays a crucial role in shaping the host immune response to infections. In this study, sixty-eight public next-generation sequencing libraries from SARS-CoV-2 infected patients were retrieved from the NCBI Sequence Read Archive database using SRA-Toolkit. Using an alignment-free method based on K-mer mapping and extension, SARS-CoV-2 was identified in all except three patients. Influenza A H7N9 (3/68), Human immunodeficiency virus 1 (1/68), rhabdovirus isolate (3/68), Human metapneumovirus (1/68), coronaviruses NL63 (1/68), Parvovirus (1/68), Simian virus 40 (1/68), and hepatitis virus (1/68) genome sequences were detected in SARS-CoV-2 infected patients.

The Sustainable Development Goals (SDGs) raise quality employability, gender equity in access to employment and increase coverage in education, however, in Colombia, high unemployment rates and informality of young people are risks of fulfilling these objectives. This is verified by a study with cohorts on access to employment, labor mobility and entry to quality occupations, through the use of probabilistic models. This study found that young people are less likely to be employed than adults, education has increased in the new generations and allowing them to enter a higher quality occupation, job segmentation and lack of experience of young people are the main cause of unemployment and Women are less likely to be employed than men and to do so in quality jobs. To comply with the SDGs, you must increase coverage in education, make a differential gender policy and expand programs as learners and insert dual education.

Given the high prevalence of cutaneous genus beta human papillomavirus (β-HPV) infections, it is important to understand how they are manipulating their host cells. This is particularly true for cellular responses to UV damage, since our skin is continually exposed to UV. The E6 protein from β-HPV (β-HPV E6) decreases the abundance of two essential UV-repair kinases (ATM and ATR). Since β-HPV E6 reduces their availability, the impact on downstream signaling events has been uncertain. We demonstrate that β-HPV E6 decreases ATM and ATR activation. This inhibition extended to XPA, an ATR target necessary for UV repair, lowering both its phosphorylation and accumulation. β-HPV E6 hinders POLη phosphorylation and foci formation, critical steps in translesion synthesis. ATM’s phosphorylation of BRCA1 is also attenuated by β-HPV E6. However, β-HPV E6’s hindrance of ATM/ATR signaling during UV-associated cell cycle arrest was incomplete. While there was less phosphorylation of immediate downstream targets (CHK1), events further down the cascade were not decreased. These observations are consistent with β-HPV infections making UV radiation more deleterious and support the proposed role of β-HPV in early stages of non-melanoma skin cancer development.

Exoskeleton robots are a rising technology in industrial contexts to assist humans in onerous applications. Mechanical and control design solutions are intensively investigated to achieve a high performance human-robot collaboration (e.g., transparency, ergonomics, safety, etc.). However, the most of the investigated solutions involve high-cost hardware, complex design solutions and standard actuation. In the presented work, an industrial exoskeleton for lifting and transportation of heavy parts is proposed. A low-cost mechanical design solution is proposed, exploiting compliant actuation at the shoulder joint to increase safety and transparency in human-robot cooperation. A hierarchic model-based controller is then proposed (including the modeling of the compliant actuator) to actively assist the human while executing the task. An inner optimal controller is proposed for trajectory tracking, while an outer fuzzy logic controller is proposed to online deform the task trajectory on the basis of the human’s intention of motion. A gain scheduler is also designed to calculate the optimal control gains on the basis of the performed trajectory. Simulations have been performed in order to validate the performance of the proposed device, showing promising results. The prototype is under realization.

The Human immunodeficiency virus-1 (HIV-1) matrix (MA) domain is involved in the highly regulated assembly process of the virus particles that occur at the host cell’s plasma membrane. High-resolution structures of the MA domain determined using cryo X-ray crystallography have provided initial insights into the possible steps in the viral assembly process. However, these structural studies have relied on large and frozen crystals in order to reduce radiation damage caused by the intense X-rays. Here, we report the first XFEL study of the HIV-1 MA domain’s interaction with inositol hexaphosphate (IP6), a phospholipid headgroup mimic. We also describe the purification, characterization and microcrystallization of two MA crystal forms obtained in the presence of IP6. In addition, we describe the capabilities of serial femtosecond X-ray crystallography (SFX) using X-ray free-electron laser (XFEL) to elucidate the diffraction data of MA-IP6 complex microcrystals in liquid suspension at ambient temperature. Two different microcrystal forms of MA-IP6 complex both diffracted to beyond 3.5 Å resolution, demonstrating the feasibility of using SFX to study the complexes of MA domain of HIV-1 Gag polyprotein with IP6 at near-physiological temperatures. Further optimization of the experimental and data analysis procedures will lead to better understanding of the MA domain of HIV-1 Gag and IP6 interaction at high resolution and provide basis for optimization of the lead compounds for efficient inhibition of the Gag protein recruitment to the plasma membrane prior to virion formation.

Designing motion representations for the problem of 3D human action recognition from skeleton sequences is an important yet challenging task. An effective representation should be robust to noise, invariant to viewpoint changes and result in a good performance with low-computational demand. Two main challenges in this task include how to efficiently represent spatio-temporal patterns of skeletal movements and how to learn their discriminative features for classification task. This paper presents a novel skeleton-based representation and a deep learning framework for 3D action recognition using RGB-D sensors. We propose to build an action map called SPMF (Skeleton Posture-Motion Feature), which is a compact image representation built from skeleton poses and their motions. An Adaptive Histogram Equalization (AHE) algorithm is then applied on the SPMF to enhance their local patterns and form an enhanced action map, namely Enhanced-SPMF. For learning and classification tasks, we exploit Deep Convolutional Neural Networks based on the DenseNet architecture to learn directly an end-to-end mapping between input skeleton sequences and their action labels via the Enhanced-SPMFs. The proposed method is evaluated on four challenging benchmark datasets, including both individual actions, interactions, multiview and large-scale datasets. The experimental results demonstrate that the proposed method outperforms previous state-of-the-art approaches on all benchmark tasks, whilst requiring low computational time for training and inference.

Damage to crops from wildlife interference is a common threat to food security among rural communities in or near Game Management Areas (GMAs) in Zambia. This study uses a two-stage econometric model and cross-sectional data from a survey of 2,769 households to determine the impact of land use planning on the probability and extent of wildlife-inflicted crop damage. The results show that crop damage is higher in GMAs as compared to non-GMAs, and that land use planning could be an effective tool to significantly reduce the likelihood of such damage. These findings suggest that there is merit in the current drive to develop and implement land use plans as means to minimize human-wildlife conflict such as crop damage. This is especially critical as Zambian conservation policies do not have an explicit provision for compensation in the event of damage from wildlife.

Introduction The authors reviewed the published evidence on the presence of oligosaccharides in human milk (HMO) and their benefits in in vitro and in vivo studies, as well as to evaluate published data on the addition of some of HMOs to infant formula. Method PubMed was searched from inception to April 2018 Results The presence of HMOs is a dynamic process, determined by many factors such as duration of lactation, environmental and genetic factors. HMOs may support immune function development and provide protection against infectious diseases directly through the interaction of the gut epithelial cells or indirectly through the modulation of the gut microbiota, including the stimulation of the bifidobacteria. Only a few of the many HMOs can be made industrially, and are added to infant formula. They have been shown to be safe and well tolerated, including normal growth and a trend towards health benefit. Conclusions HMOs are one of the major differences between cow’s milk and human milk , and evidence indicates that these components do have a health promoting benefit. The addition of one or two of these components to infant formula is safe, and brings infant formula closer to human milk.

This paper proposes an Integrated Fire Management (IFM) framework that can be used to support communities and resource managers in finding effective and efficient approaches to prevent damaging fires, as well as maintain desirable fire regimes in Kenya. Designing and implementing an IFM approach in Kenya calls for a systematic understanding of the various uses of fire and the underlying perceptions and traditional ecological knowledge of the local people. The here proposed IFM framework allows an evaluation of the risks posed by fires, while balancing them with their beneficial ecological and economic effects, and thus developing effective fire management approaches. A case study of the proposed IFM framework was conducted in Gathiuru Forest that is part of the larger Mt. Kenya Forest Ecosystem. Focus group discussions were held with key resource persons, primary and secondary data on socio-economic activities were studied, fire and weather records were analyzed and the current fire management plans were consulted. Questionnaires were used to assess how the IFM is implemented in the Gathiuru Forest Station. The results show that the proposed IFM framework is scalable and can be applied in places with fire-dependent ecosystems as well as in places with fire-sensitive ecosystems in Kenya. The effectiveness is dependent on the active participation, formulation and implementation of the IFM activities by the main stakeholder groups (Kenya Forest Service (KFS), Kenya Wildlife Service (KWS), and the Community Forest Associations (CFA)). The proposed IFM framework helps in implementing cost-effective approaches to prevent damaging fires and maintain desirable fire regimes in Kenya.

Human footprint is having a unique set of ridges unmatched by any other human being, and therefore it can be used in different identity documents for example birth certificate, Indian biometric identification system AADHAR card, driving license, PAN card, and passport. There are many instances of the crime scene where an accused must walk around and left the footwear impressions as well as barefoot prints and therefore it is very crucial to recovering the footprints to identify the criminals. Footprint-based biometric is a considerably newer technique for personal identification. Fingerprints, retina, iris and face recognition are the methods most useful for attendance record of the person. This time world is facing the problem of global terrorism. It is challenging to identify the terrorist because they are living as regular as the citizens do. Their soft target includes the industries of special interests such as defense, silicon and nanotechnology chip manufacturing units, pharmacy sectors. They pretend themselves as religious persons, so temples and other holy places, even in markets is in their targets. These are the places where one can obtain their footprints easily. The gait itself is sufficient to predict the behaviour of the suspects. The present research is driven to identify the usefulness of footprint and gait as an alternative to personal identification.

The increasing number of registered road crashes involving cyclists during the last decade, and the high proportion of road crashes resulting in severe injuries and fatalities among cyclists constitutes a global issue for community health, urban development, and sustainability. Nowadays, the incidence of many risk factors for road crashes of cyclists remains largely unexplained. Given the importance of this issue, the present study has been conducted with the aim of determining relationships between infrastructural, human factors and safety outcomes of cyclists. Objectives: This study aimed, first, to examine the relationship between key infrastructural and human factors present in cycling, bicycle-user characteristics, and their self-reported experience with road crashes. And second, to determine whether a set of key infrastructural and human factors may predict their self-reported road crashes. Methods: For this cross-sectional study, a total of 1064 cyclists (38.8% women, 61.2% men; M = 32.8 years of age) from 20 different countries across Europe, South America and North America, participated in an online survey composed of four sections: demographic data and cycling-related factors, human factors, perceptions on infrastructural factors, and road crashes suffered. Results: The results of this study showed significant associations between human factors, infrastructural conditions and self-reported road crashes. Also, a logistic regression model found that self-reported road crashes of cyclists could be predicted through variables such as age, riding intensity, risky behaviors, and problematic user/infrastructure interactions. Conclusions: The results of this study suggest that self-reported road crashes of cyclists are influenced by features related to the user and their interaction with infrastructural characteristics of the road.

The role of human resource management practices and organizational loyalty dealing with employee retention has been widely explored and examined in the existing literature. The majority of human resource management researchers have focused on the role of policies and practices in different sectors related to employee retention. However, less attention has been given to identifying the practices and procedures common across all industries and sectors. The present study attempts to determine and examine the most important constructs like HR practices and organizational loyalty of employee retention management and proposes a comprehensive structural equation model to measure the impact of these constructs on employee retention. After an extensive review of the literature, organizational loyalty, and human resources management practices like recruitment and selection, compensation and benefit, training and development, supervision and evaluation have been identified as four essential practices dealing with employee retention and are common across all industries. These practices constitute the component factors of an employee retention management predicting employee’s turnover intentions. The survey method was adopted, and the original data obtained through the self-administered questionnaire. The valid one hundred and eighty-nine (189) respondents analyzed by using Lisrel 8.7, Structural equation model (SEM) analysis results shows that human resource management practices and organizational loyalty have strong positive impact on employee retention. This study tends to assist human resource managers and decision makers in selecting the appropriate motivating factors to retain and satisfy their employees

Flavonoids, compounds present in many dietary supplements, affect growth of different bacterial species when tested as purified or synthetic substances. Here, we asked if soy isoflavone extracts, commonly used in many products sold as anti-menopausal dietary supplements, influence bacterial growth similarly to synthetic isoflavone, genistein. Four commercially available products were tested in amounts corresponding to genistein concentrations causing inhibition of growth of Vibrio harveyi (a model bacterium sensitive to this isoflavone) and Escherichia coli (a model bacterium resistant to genistein). Differential effects of various extracts on V. harveyi and E. coli growth, from stimulation, through no changes, to inhibition, were observed. Moreover, contrary to genistein, tested extracts caused a decrease (to different extends) in viability of human dermal fibroblasts. These results indicate that effects of various soy isoflavone extracts on bacterial growth and viability of human cells are different, despite similar declared composition of the commercially available products.

The question of the relevance of human and natural capital, as well as the potential adverse effect of natural capital on economic growth, has gained increased attention in development economics. The aim of this paper is to theoretically and empirically assess the relevance of several forms of capital on economic growth in small economies that are dependent upon tourism or natural resources. The empirical framework is based on Impulse Response Functions obtained from Vector Autoregressive models in which we focus on the model where economic growth is the dependent variable for ten small economies that are dependent upon either tourism or natural resources. We find that there is evidence of the ‘’natural resource curse’’, especially in the economies that have a strong dependence on resources that are easily substitutable and whose prices constantly fluctuate. We further find that in the majority of observed cases the type of capital these small economies are most dependent on for their economic growth causes negative impulses in the majority of the observed periods. The main policy recommendation should be to assure that even these small economies should strive towards further diversification and avoid dependence on only one segment of their economy.

For many tick-borne organisms, dogs may be utilized as sentinel hosts to estimate the risk of human infection. The detection of antibodies in these animals indicates the circulation of pathogens in each location for a set period of time. The standard protocol for the surveillance of tick-borne diseases established by the Brazilian National Reference Laboratory for Rickettsiosis at the Ezequiel Dias Foundation (FUNED) includes testing the seropositivity of dogs for Rickettsia spp. and Ehrlichia canis. Dog serum samples were collected during FUNED’s surveillance protocol in a preserved area in Brazil. Despite Anaplasma phagocytophilum being endemic in Brazil, this agent is not included in FUNED’s standard protocol. To determine if A. phagocytophilum should be included in the standard testing protocol, a collaboration with Fuller Laboratories was established and the seropositivity for A. phagocytophilum was tested. The estimated prevalence for singular infections: 25% Rickettsia spp.; 52.3% E. canis; and 70.5% A. phagocytophilum. The estimated prevalence for co-infections: 17% Rickettsia spp. and E. canis; 18.2% Rickettsia spp. and A. phagocytophilum; 39.8% E. canis and A. phagocytophilum; and 13.6% Rickettsia spp., E. canis, and A. phagocytophilum. These results confirmed a significant presence of A. phagocytophilum and establishes a potential threat upon the public health.

The aim of this study is to develop a software solution for real-time recognition of sign language words using two arms. This will enable communication between hearing-impaired individuals and those who can hear. Several sign language recognition systems have been developed using different technologies, including cameras, armbands, and gloves. The system developed in this study utilizes surface electromyography (muscle activity) and inertial measurement unit (motion dynamics) data from both arms. Other methods often have drawbacks, such as high costs, low accuracy due to ambient light and obstacles, and complex hardware requirements, which have prevented their practical application. A software has been developed that can run on different operating systems using digital signal processing and machine learning methods specific to the study. For the test, we created a dataset of 80 words based on their frequency of use in daily life and performed a thorough feature extraction process. We tested the recognition performance using various classifiers and parameters and compared the results. The Random Forest algorithm was found to have the highest success rate with 99.875% accuracy, while the Naive Bayes algorithm had the lowest success rate with 87.625% accuracy. Feedback from a test group of 10 people indicated that the system is user-friendly, aesthetically appealing, and practically useful. The new system enables smoother communication for people with hearing disabilities and promises seamless integration into daily life without compromising user comfort or lifestyle quality.

Aflatoxin being a serious threat to public health and international trade, necessi-tates a comprehensive understanding and calculated response with effective inter-vention strategies. This review methodically looks at several aspects of aflatoxin, starting with how it affects international trade laws through feed and feed ingre-dient regulations. Aflatoxin contamination poses serious challenges to world health and the economy, especially in areas that are already at risk. Examining the varia-bles affecting aflatoxin toxicity, the paper clarifies aflatoxin toxicity's complex me-tabolism and the resulting health effects of exposure. The serious repercussions of aflatoxicosis outbreaks and their connections to illnesses like Aspergillosis and cancer are highlighted by a detailed exploration of prospective decontamination techniques as well as strategies for detecting and capturing aflatoxin. A thorough knowledge of the factors that contribute to aflatoxin contamination demonstrates the intricate interactions between environmental variables, farming methods, stor-age circumstances, and different physical, biological, and nutritional components. Strong detection strategies are required due to aflatoxins’ significant effects on an-imal and human health. The paper describes complete preventative tactics that en-compass manipulation in management strategies. global trade and public health from this pervasive threat.

The objective was to investigate associations of serum vitamin D concentration with depressive symptoms and assess the impact vitamin D concentration has on the occurrence of depressive symptoms in 20–44-year-old pregnant mothers, postpartum mothers, women (non-pregnant/postpartum women), and men, including a separate subgroup analysis of postpartum breastfeeding and non-breastfeeding mothers. The study populations were selected from 2007-2018 NHANES public data. Subjective interview data and objective laboratory data, including depressive symptoms, serum vitamin D concentration, nutrient intake, and demographic information were utilized. Two diet patterns were created using principal component analysis and a Bayesian multinomial model was fit to predict depression outcomes for each subpopulation. The estimates for the log vitamin D slope parameter were negative for all cohorts; as vitamin D increased, the probability of having no depression increased, while the probability of depression decreased. The pregnant cohort had the steepest vitamin D slope, followed by postpartum, then other women and men. Higher vitamin D concentration had more impact on decreasing depression risk in pregnant and postpartum mothers compared to other women and men. Among postpartum mothers, higher vitamin D concentration had a greater influence on decreasing breastfeeding mothers' depression risk than non-breastfeeding mothers.

This study advances the field of infectious disease forecasting by introducing a novel approach to micro-level contact modeling, leveraging human movement patterns to generate realistic temporal dynamic networks. Through the incorporation of human mobility models and parameter tuning, this research presents an innovative method for simulating micro-level encounters that closely mirror infection dynamics within confined spaces. Central to our methodology is the application of Bayesian optimization for parameter selection, which refines our models to emulate both the properties of real-world infection curves and the characteristics of network properties. By focusing on the distinct aspects of infection propagation within confined spaces, our approach significantly improves the realism of temporal-dynamic contact networks, offering a powerful tool for assessing the impact of specific locations on pandemic dynamics. The resulting models shed light on the role of spatial encounters in disease spread and strengthen the capability to forecast and respond to infectious disease outbreaks. This work not only contributes to the scientific understanding of micro-level transmission patterns but also offers practical insights for public health strategies and digital contact tracing efforts, aiming at more effective intervention and containment measures during pandemics.

This paper examines the transformative journey of Artificial Intelligence (AI) agents from copilots to integral coworkers within diverse sectors. Beginning with a foundational overview, we delve into the historical evolution of AI agents, highlighting key technological milestones and the shift from simple automated tools to sophisticated decision-making systems capable of learning and adapting over time. We explore the capabilities of AI agents, including problem-solving, predictive analytics, and automation, and their applications across healthcare, business, and education, showcasing their role in diagnostics, customer service, and personalized learning, among other areas. We also address the integration of AI agents in the workplace, presenting strategies for collaboration between humans and AI, and outline the challenges and ethical considerations that accompany the development and deployment of AI technologies. A comprehensive tutorial provides insight into the development process of AI agents, emphasizing goal definition, data handling, algorithm selection, and ethical guidelines. We also consider the pathway towards Artificial General Intelligence (AGI) and the societal and ethical implications of widespread AI integration, proposing strategies for equitable and ethical AI use.

Viral co-infections, where a host is infected by multiple viruses simultaneously, are common in the human population. Human viral co-infections can lead to complex interactions between viruses and the host immune system, affecting the clinical outcome and posing challenges for treatment. Understanding the types, mechanisms, impacts, and identification methods of human viral co-infections is crucial for the prevention and control of viral diseases. In this review, we first introduce the significance of studying human viral co-infections and summarize the current research progress and gaps in this field. We then classify human viral co-infections into four types based on the pathogenic properties and species of the viruses involved. Next, we discuss the molecular mechanisms of viral co-infections, focusing on virus-virus interactions, host immune responses, and clinical manifestations. We also summarize the experimental and computational methods for identifying viral co-infections, emphasizing the latest advances in high-throughput sequencing and bioinformatics approaches. Finally, we highlight the challenges and future directions in human viral co-infection research, aiming to provide new insights and strategies for the prevention, control, diagnosis, and treatment of viral diseases. This review provides a comprehensive overview of the current knowledge and future perspectives on human viral co-infections, and underscores the need for interdisciplinary collaborations to address this complex and important topic.

Recently, due to the decrease in labor force, increase in labor costs, and the desire for improved quality of life, research on robots has been actively conducted to address these issues. However, it is currently difficult to find robots that physically interact with humans. The reason is that the actuators of robots do not have high torque density on their own. To solve this problem, high torque density motors, such as proprioceptive actuators, are being researched. However, the torque density is still insufficient for physical interaction with humans, so we have developed a motor with higher torque density. However, high torque density motors have the disadvantage of lower speed characteristics due to increased Back-EMF. Therefore, to address the deterioration of speed characteristics in the developed motor, we applied the Independent 3-Phase winding structure to improve the speed characteristics. Consequently, through comparison with Y-Connection and Delta-Connection, we propose the most suitable winding structure for high torque density motors intended for physical interaction with humans.

Abstract: Colistin is a last-resort antimicrobial for treating multidrug-resistant Gram-negative bacteria. Phe-notypic colistin resistance is highly associated with plasmid-mediated mobile colistin resistance (mcr) genes. mcr-bearing Enterobacteriaceae have been detected in many countries, with the emergence of colistin-resistant pathogens a global concern. This study assessed the distribution of mcr-1, mcr-2, mcr-3, mcr-4, and mcr-5 genes with the phenotypic colistin resistance in isolates from diarrheal infants and children in Bangladesh. Bacteria were identified using the API-20E biochemical panel and 16s rDNA gene sequencing. Polymerase chain reac-tions detected mcr gene variants in the isolates. Their susceptibilities to colistin were determined by agar dilu-tion and E-test by minimal inhibitory concentration (MIC) measurements. Over 30.0% (69/225) of isolates showed colistin resistance by agar dilution assessment (MIC> 2.0 μg/mL). Overall, 15.5% of isolates carried mcr genes (7, mcr-1; 17, mcr-2; 13, mcr-3; and co-occurrence occurred in 2 isolates). Clinical breakout MIC val-ues (≥ 4 μg/mL) were associated with 91.3% of mcr-positive isolates. The mcr-positive pathogens include twenty Escherichia spp., five Shigella flexneri, five Citrobacter spp., two Klebsiella pneumoniae, and three Pseudo-monas parafulva. mcr-genes appeared to be significantly associated with phenotypic colistin resistance phe-nomena (p=0.000), with 100% colistin-resistant isolates showing MDR phenomena. Age and sex of patients showed no significant association with detected mcr variants. Overall, mcr-associated colistin-resistant bacte-ria have emerged in Bangladesh, which warrants further research to determine their spread and instigate ac-tivities to reduce resistance.

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

Wastewater-Based Epidemiology (WBE) is currently used to monitor not only the spread of the pandemic virus SARS-CoV-2 but also for other viruses in endemic conditions, particularly in the absence of syndromic surveillance. Continuous monitoring of sewage requires high costs and significant time investment, highlighting the need for standardized methods and structured monitoring strategies. In this context, we conducted weekly wastewater monitoring in northwestern Italy, targeting Human Adenovirus (HAdV), Norovirus Genogroup II (NoVggII), Enterovirus (EV), and SARS-CoV-2. Samples collected at the entrance of treatment plants were concentrated using PEG/NaCl precipitation and viral nucleic acids were extracted and detected by real-time (RT-)qPCR. NoVggII resulted the most identified target (84.4%), followed by HAdV, SARS-CoV-2, and EV. Only HAdV and EV exhibited seasonal peaks in spring and summer. SARS-CoV-2 results compared with data previously collected in the same study area (February 2021 to September 2021) revealed a shift from an epidemic to a pandemic status, likely due to the evolution of variants. In conclusion, WBE, using standardized methods and an efficient monitoring strategy, proves valuable for virus surveillance in pandemic and epidemic scenarios, enabling the identification of temporal-local distribution patterns that are useful for making informed public health decision.

Human papillomavirus (HPV) infections, primarily transmitted through sexual contact, have been linked to various cancers, including cervical, penile, anal, oropharynx, breast, and prostate cancers. This study presents a unique case of concurrent high-risk HPV35, HPV45, and HPV59 infections in both prostate and bladder cancer tissues from a single patient, representing the first documented instance worldwide with identical HPV types detected in two adjacent organs of the same individual. Employing a multiplex-PCR approach, gel electrophoresis, and Sanger sequencing, we confirmed the presence of these high-risk HPV types. Additionally, Western blot analysis using an HPV E7 antibody demonstrated the active expression of HPV oncoproteins in both cancer types. This discovery underscores the potential for HPV intra-organ transmission and necessitates further exploration of alternative transmission routes. The implications of our results offer new insights into the complex dynamics of HPV transmission in cancer pathogenesis.

This study explores the potential of natural compounds, including Daidzin, Luteolin, and Silibinin, as inhibitors of human monoamine oxidase B (MAO-B) for the treatment of Parkinson's disease. Docking simulations were performed using Autodock Vina with Pyrx program to evaluate the binding affinities of these compounds with MAO-B. Results indicate that Daidzin, Luteolin, and Silibinin exhibit promising binding affinities with MAO-B, with Daidzin demonstrating the highest affinity. Toxicity parameters were further predicted using the PkCSM Server, confirming the low toxicity of these compounds. Overall, the findings suggest that Daidzin, Luteolin, and Silibinin have the potential to be effective and safe treatments for Parkinson's disease through their inhibition of MAO-B. Further experimental validation is warranted to support their therapeutic efficacy in clinical settings.

This study examines the moderating effect of trained human capital on the associations of accounting information systems, generalized auditing software, and technology adoption with the performance of external auditors among Saudi listed companies. This study used a survey-based methodology. The final sample consisted of 136 responses with an 8% response rate. Using Smart-PL4 analysis, the results showed that there is a positive correlation between accounting information systems and external auditors. Conversely, a negative relationship between generalized auditing software and external auditors has been documented. In addition, this study reported a negative association between technology adoption and external auditors. However, the results highlight the positive relationship between trained human capital and external auditors. Overall, this study provides valuable insights for accounting and auditing policymakers on how external auditors’ performance is influenced by several factors in the Saudi audit market.

This paper maps the causes of the demographic, economic and social decline of a selected border micro-region during the last century. The decline occurred due to the location being remote, lacking natural resources and having an unsuitable industrial structure. Historical events associated with the post-war deportation of the German population and efforts to create a classless society also played a role in the decline. The results are an 87% population decrease, the demise of most companies, a very low level of human capital and unemployment reaching up to 5%. In order to comprehend the current state of the border micro-region and predict future development, it is necessary to understand the development that has occurred since approximately the middle of the nineteenth century. The European countryside is certainly not homogeneous, and different regions have shown unique mixes of positional, natural, economic and political factors. Some hope has been raised in relation to the transition to a post-productive economy, a transition that turns the remoteness of the region into an advantage. This is confirmed by the positive migration balances of the smallest municipalities in the last decade.

Deficient wound healing is frequently observed in patients diagnosed with diabetes, a clinical complication that compromises mobility and leads to limb amputation, decreasing patient autonomy and family lifestyle. Fibroblasts are crucial for secreting the extracellular matrix to pave the wound site for endothelial and keratinocyte regeneration. The biosynthetic pathways for collagen production are one of the main components of the extracellular matrix, as the crosslinking of extracellular collagen fibers is intimately related to fibroblast redox homeostasis. In this study, human dermic fibroblasts were cultured with 1 mM sodium selenite (inorganic) and 1 mM of two selenium amino acids (organic), Se-cysteine and Se-methionine. This concentration was compatible with long-term exposure necessary for extracellular matrix production and allowed us to examine the impact of these three compounds on the state and response of the thiol-based HyPer biosensor expressed in the cytoplasm. In addition, the abundance of extracellular matrix and ultrastructural properties were evaluated by Picrus Sirius red staining and scanning electronic microscopy, respectively. We also evaluated whether these selenium compounds effectively ameliorated the perturbations induced by culturing fibroblasts at high glucose levels (25 mM) regarding cytoplasmic redox, extracellular matrix, and glycation on collagen fibers. Our results indicate that cytoplasm protein oxidation was sensitive to selenium compound supplementation. Selenium amino acids increased the sensitivity to protein oxidation, and only Se-cysteine increased the disulfide bond reduction in fibroblasts maintained in high glucose. Despite the lack of effect of selenium compounds on the glu-cose-induced increase in matrix fiber thickness, we found that endothelial migration improved in the matrix generated by high glucose-cultured fibroblasts.

Lipophilic oligonucleotide derivatives are a potent approach to the intracellular delivery of nucleic acids. The binding of these derivatives to serum albumin is a major determinant of their fate in the body, as its structure contains several sites of high affinity for hydrophobic compounds. This study focuses on the features of self-association and non-covalent interactions with human serum albumin of novel self-penetrating oligonucleotide derivatives. The study revealed that the introduction of a triazinyl phosphoramidate modification bearing two dodecyl groups at the 3' end region of the oligonucleotide sequence has a negligible effect on its affinity for the complementary sequence. Dynamic light scattering verified that the amphiphilic oligonucleotides under study can self-assemble into micelle-like particles ranging from 8 to 15 nm in size. The oligonucleotides with dodecyl groups form stable complexes with human serum albumin with a dissociation constant of approximately 10-6 M. The oligonucleotide micelles are simultaneously destroyed upon binding to albumin. Using an electrophoretic mobility shift assay and affinity modification, we examined the ability of DNA duplexes containing triazinyl phosphoramidate oligonucleotides to interact with Ku antigen and PARP1, as well as the mutual influence of PARP1 and albumin or Ku antigen and albumin upon interaction with DNA duplexes. These findings, together with the capability of dodecyl-containing derivatives to effectively penetrate different cells, such as HEK293 and T98G, indicate that the oligonucleotides under study can be considered as a platform for the development of therapeutic preparations with a target effect.

Recruitment is a fundamental aspect of Human Resource Management to drive organizational performance. Traditional recruitment processes, with manual stages, are time-consuming and inefficient. Artificial Intelligence (AI), which demonstrates its potential in various sectors such as healthcare, education and notable cases of ChatGPT, is currently reshaping recruitment by automating tasks to improve efficiency. However, in Thailand, where there is a growing demand for talents, the application of AI in recruitment remains relatively limited. This research focuses on human resources (HR) and recruitment professionals in Thailand, aiming to understand their perspectives on the integration of AI in recruitment. It extended the Unified Theory for Acceptance and Use of Technology (UTAUT) model, customized to suit the specific requirements of Thai recruitment practices. The study explores the factors influencing users' intention to adopt AI in recruitment. Survey questionnaire items were created based on prior literatures and refined with insights from HR and recruitment experts to ensure applicability in the context of recruitment in Thailand. A survey involving 364 HR and recruiting professionals in Bangkok metropolitan area supplied comprehensive responses. The research reveals that several factors, including Perceived Value, Perceived Autonomy, Effort Expectancy, and Facilitating Conditions, significantly impact the intention to adopt AI for recruitment. While Social Influence and Trust in AI Technology do not have a direct influence on intention, Social Influence directly affects Perceived Value. Trust in AI Technology positively influences Effort Expectancy. This study provides valuable benefits for HR and recruitment professionals, organizations and AI developers by offering insights into AI adoption and sustainability, enhancing recruitment processes and promoting the effective use of AI tools in this sector.

This comprehensive review explores the principles, applications, and future directions of human-powered energy generation technologies. It begins by providing a detailed examination of viable human energy sources, elucidating the physical principles behind various energy harvesting devices. The review then compiles and assesses existing products in the field of human power generation, while also outlining the opportunities and challenges it presents. Finally, an innovative concept of an eco-village system is introduced to demonstrate a future potential application scenario for human-generated electricity. It outlines two developmental stages for this system and underscores its significance in the construction of the harmonious and sustainable communities. This forward-thinking approach could pave the way for broader discussions on sustainable living and eco-friendly energy generation in a world increasingly focused on environmental concerns and social stability.

Virtual reality software might be challenging to utilize for beginners and unskilled professionals who do not have a programming or 3D modeling background. Concurrently, there is a knowledge gap in software project design for intuitive virtual reality authoring tools, which were supposed to be easier to use. These tools are frequently insufficient due to a lack of support and standard operating procedures. Adopting the Design Science Research paradigm, this study aims to evaluate the validity of fourteen design guidelines for the development of intuitive virtual reality authoring tools as an artifact. While a previous study completed the first steps of the Design Science Research, by identifying problems, defining solution objectives, and developing and demonstrating the design guidelines, this work seeks to qualitatively evaluate their application in a practical experiment. A group of engineering students with no prior experience in creating virtual worlds were tasked with examining the design guidelines while using the NVIDIA Omniverse Enterprise as an exemplary use case and responding to a questionnaire and a focus group interview about how they perceived these guidelines. A correlation analysis confirmed that most guidelines scores behaved as expected and were ranked according to the use-case functionality. The participants understood the guidelines' definition and could decide if they agreed or disagreed with their presence during the experiment. We conclude that, in accordance with the Design Science Research, the proposed artifact is useful, i.e., the design guidelines for virtual reality authoring tools perform what they are designed to do and are operationally reliable in accomplishing their goals.

HSF1 is a well-known Heat Shock Protein expression regulator in response to stress. It also regulates processes important for growth, development, or tumorigenesis. Here, we studied the HSF1 influence on the phenotype of non-tumorigenic human mammary epithelial (MCF10A and MCF12A) and several triple-negative breast cancer cell lines. MCF10A and MCF12A differ by HSF1 levels, morphology, growth in the matrigel, expression of epithelial (CDH1) and mesenchymal (VIM) markers (MCF10A are epithelial cells, MCF12A resemble mesenchymal cells). HSF1 down-regulation led to reduced proliferation rate and spheroid formation in matrigel by MCF10A cells, while it did not affect the MCF12A proliferation but led to CDH1 up-regulation and the formation of better-organized spheroids. HSF1 overexpression in MCF10A resulted in reduced CDH1 and increased VIM expression, and the acquisition of elongated fibroblast-like morphology. The above results suggest that elevated levels of HSF1 may direct mammary epithelial cells toward a mesenchymal phenotype while lowering HSF1 could reverse the mesenchymal phenotype to an epithelial one. Therefore, HSF1 may be involved in the remodeling of mammary gland architecture over the female lifetime. Moreover, HSF1 levels positively correlated with the invasive phenotype of triple-negative breast cancer cells, and their growth was inhibited by the HSF1 inhibitor, DTHIB.

There are strong indications that the built environment intertwines consistently with the advent of Covid-19 and the need for post-disaster recovery. The advent of the Covid-19 pandemic has exerted adverse effects on both human and global developments; while the efforts to combat this menace call for an integrated human social capital index. This research seeks to adequately enhance the comprehension of how the built environment can be enhanced through resilience in the backdrop of the Covid-19 pandemic. The study's goal is to investigate the impact of a resilient built environment on increasing resilience in the aftermath of the Covid-19 pandemic in Nigeria. Overall, the quantitative study test the impact of four built environments resilience indices (Built Environment capitals; Disaster management indices, Awareness of the Covid-19 Pandemic, and Built Environment adaptive strategies) on Human social capital and Covid-19 pandemic Indices. This study reveals the role of human social capital in achieving a resilient built environment in the wake of Covid 19 pandemic in Nigeria. Also, built environment capitals, disaster management indices, and awareness on the Covid-19 have indirect effects on Covid-19 pandemic indices through the human social capital. The implication of the study is useful for Post-Covid 19 recovery; which is important for future planning of the built environment in Nigeria.

HIV-associated cognitive dysfunction during combination antiretroviral therapy (cART) involves mitochondrial dysfunction, but the impact of contemporary cART on chronic metabolic changes in the brain and in latent HIV infection is unclear. We interrogated mitochondrial function in a human microglia (hμglia) cell line harboring inducible HIV provirus, and in SH-SY5Y cells, after exposure to individual antiretroviral drugs or cART, using the MitoStress assay. cART-induced changes in protein expression, reactive oxygen species (ROS) production, mitochondrial DNA copy number, and cellular iron were also explored. Finally, we evaluated the ability of ROS scavengers or plasmid-mediated overexpression of the antioxidant iron-binding protein, Fth1, to reverse mitochondrial defects. Contemporary antiretroviral drugs, particularly bictegravir, depressed multiple facets of mitochondrial function by 20-30%, with most pronounced effects in latently infected-HIV+ hμglia and SH-SY5Y cells. Latently HIV-infected hμglia exhibited upregulated glycolysis. Increases in total and/or mitochondrial ROS, mitochondrial DNA copy number, and cellular iron accompanied mitochondrial defects in hμglia and SH-SY5Y cells. In SH-SY5Y cells, cART reduced mitochondrial iron-sulfur-cluster-containing supercomplex and subunit expression and increased Nox2 expression. Fth1 overexpression or pre-treatment with N-acetylcysteine prevented cART-induced mitochondrial dysfunction. Contemporary cART impairs mitochondrial bioenergetics in hμglia and SH-SY5Y cells, partly through cellular iron accumulation; some effects differ by HIV latency.

In a search for a reliable, inexpensive, and versatile technique for high-throughput kinetic assays of drug metabolism, we elected to rehire an old-school approach based on the determination of formaldehyde (FA) formed in cytochrome P450-dependent demethylation reactions. After evaluating several fluorometric techniques of FA detection, we choose the method based on the Hantzsch reaction with acetoacetanilide as the most sensitive, robust, and adaptable to high-throughput implementation. Here we provide a detailed protocol for the use of our new technique for automatized assays of cytochrome P450-dependent drug demethylations and discuss its applicability for high-throughput scanning of the pathways of drug metabolism in the human liver. To probe our method further, we applied it to re-evaluating the pathways of metabolism of ketamine, a dissociative anesthetic, and potent antidepressant increasingly used in the treatment of alcohol withdrawal syndrome. Probing the kinetic parameters of ketamine demethylation by 11 major cytochrome P450 (CYP) enzymes, we demonstrate that besides CYP2B6 and CYP3A enzymes, which were initially recognized as the primary metabolizers of ketamine, an important role is also played by CYP2C19, and CYP2D6, while the involvement of CYP2C9 suggested in the previous reports deemed insignificant.

A tricalcium silicate nanoparticle-containing cement (NPC) was developed to overcome the disadvantages of existing mineral trioxide aggregate (MTA) dental materials. This study aimed at evaluating the effects of NPC on the osteogenic differentiation of human periodontal ligament fibroblasts (HPLFs) in vitro, and on the healing of furcal perforations created experimentally in rat molars in vivo, in comparison to MTA. The in vitro studies performed the following assays; pH measurement using a pH meter, the release of calcium ions using a calcium assay kit, cell attachment and morphology using SEM, cell proliferation using a coulter counter, marker expression using quantitative reverse transcription polymerase chain reaction (qRT-PCR) and cell mineralized deposit formation using Alizarin Red S (ARS) staining. In the in vivo studies, MTA and NPC were used to fill the rat molar perforations. Rat molars were processed at 7, 14 and 28 days for analysis of inflammatory processes using hematoxylin and eosin (HE) staining, immunohistochemical staining of Runx2 and tartrate-resistant acid phosphate (TRAP) staining. The results demonstrate that the nanoparticle size distribution of NPC is critical for osteogenic potential at an earlier stage compared to MTA. Further studies are required to elucidate the mechanism of action of NPC in osteogenic differentiation.

Companion animals play a central role in many families and are especially valued by those who are socially isolated. Crisis situations such as acute hospitalizations, homelessness and natural disasters can make it difficult to preserve the human-animal bond and can result in animals being surrendered or euthanized. Social support programs like the RSPCA NSW Emergency Boarding and Homelessness program support people experiencing crisis situations with emergency pet boarding, access veterinary treatment and individualized case management. This study aimed to estimate the social return on investment (SROI) for this program using standard SROI methodology. In-depth interviews were conducted with 13 program stakeholders and questionnaire responses were received from 29 program clients. Outcomes were quantified for four stakeholder groups: program clients, client’s animals, RSPCA Inspectors, animal pounds and shelters. Clients and their animals experienced the bulk of the benefit from the program, estimated to have a combined value of over $5 million AUD for the 2020-21 financial year. The estimated social return on investment was $8.21 for each $1 invested. The study demonstrates that keeping people together with their companion animals, or ensuring they are reunited as soon as possible, can reduce stressors, and improve outcomes for people and animals.

Background: The most important causative agents of neoplasms in the anogenital area is the human papillomavirus (HPV). Due to the anatomical proximity of the genital and anus area and the ease with which HPV infection is transmitted, it seems that patients after treatment of HPV-related gynecological diseases may have increased risk of developing a second HPV-related neoplasm- anal cancer. The aim of the study was to determine the risk of anal intraepithelial neoplasia (AIN) and anal cancer (AC) among patients after treatment of HPV-related gynecological diseases. Methods: We conducted a comprehensive review of available literature in multiple databases. The study was performed following Cochrane Reviewers' Handbook and Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2009 guidelines. Moreover, we assessed the quality of each study using QUADAS-2. Results: Twenty five studies were included in the final analysis. Patients after treatment of HPV-related gynecological diseases have a significantly higher risk of AC (mean standardized incidence ratio [SIR]= 5.387, mean incidence risk [IR]= 0.096%, mean IR per 100,000 person-years= 10.37), and AIN (mean IR= 23.683%) compared to the population risk. Conclusions: Patients with HPV-related gynecological diseases should constitute a group for which an appropriate primary and secondary screening for AC should be introduced.

Best practices in global health training prioritize leadership and engagement from investigators from low- and middle-income countries (LMICs), along with more conscientious community consultation and research that benefits local participants and autochthonous communities. However, well into the 20th century, international research and clinical care were rife with paternalism, extractive practices, and racist ideation, with race presumed to explain both vulnerability or protection from various diseases despite scientific evidence for more precise mechanisms for infectious disease. We highlight experiences in global research on health and illness among indigenous populations in LMICs, seeking to clarify what is both scientifically essential and ethically desirable in research with human subjects; we apply a critical view towards race and racism as historically distorting elements that must be acknowledged and overcome.

Converting natural language into machine language that can be recognized by distributed systems is the core challenge of intelligent interactive interfaces and human-machine dialogue systems. The human-machine interface interaction of large distributed SCADA measurement and control system is tedious and the operation and maintenance cost is high, so it is significant to design an intelligent natural language interaction interface for distributed measurement and control system. In this paper, we design the intermediate language format of SCADA system, i.e., Key-value logic form, and then formulate the Text2SCADA framework and propose the TICS algorithm and SDPA algorithm, the former adopts the keyword extraction and cosine similarity optimization algorithm to complete the structured extraction of natural language for basic natural language instructions, and the latter adopts the keyword extraction and cosine similarity optimization algorithm to complete the structured extraction of natural language for relatively The latter one adopts the algorithm of dependent syntactic analysis for the structured representation of natural language instructions with relatively complex natural language instructions. Based on the above algorithms, a lightweight information extraction model based on DGCNN and probabilistic graph ideas is constructed, aiming to enhance the scientific generalization ability of the framework on unknown instruction sets. The experimental results show that the proposed intelligent natural language interface can better solve the human-machine interface interaction problem of distributed SCADA measurement and control system. The average accuracy, recall and F-value of instruction parsing reach 89.27\%, 89.28\% and 89.27\%, respectively. The average response time is 1.593 s. Especially, it provides a more convenient means of interaction for industrial and agricultural information control.

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

Cervical cancer is preventable through vaccination, early detection, and treatment of precancerous lesions. However, global inequalities mean that the disease remains a leading cause of cancer death around the world, with over 80% of new cases and 90% of deaths occurring in low and middle-income countries (LMICs). In El Salvador, joint efforts between the Ministry of Health (MoH) and the non-profit organization Basic Health International (BHI) have been in place since 2008 with the goal of reducing the country’s disease burden. While the World Health Organization’s (WHO) call to action to eliminate cervical cancer provided worldwide momentum to implement new public health initiatives, the COVID-19 pandemic disrupted ongoing programs and jeopardized plans for the future. The purpose of this manuscript is to describe the progress that El Salvador has achieved in improving cervical cancer prevention, the impact of the pandemic on current strategies, and potential solutions that can help the country meet the WHO’s strategic targets by 2030 to accelerate the elimination of cervical cancer.

The classical human satellite DNAs, also referred to as human satellites 1, 2 and 3 (HSat1, HSat2, HSat3, collectively HSat1-3) constitute the largest individual arrays of tandemly repeated DNA sequences in the genome. Even though they were among the first human DNA sequences to be isolated and characterized at the dawn of molecular biology, HSat1-3 have been left behind in the genomics era and remain among the most enigmatic sequences in the human genome. Although HSat1-3 total roughly 3% of the genome on average, they were almost entirely missing from the human genome reference assembly for 20 years. Recently, the Telomere-to-Telomere Consortium produced the first truly complete assembly of a human genome, including the enormous HSat1-3 arrays, opening them up for a new wave of discovery. Towards this end, here, I provide an account of the history and current understanding of HSat1-3 genomics, evolution, and roles in disease.

Artificial Intelligence models are increasingly used in manufacturing to inform decision-making. Responsible decision-making requires accurate forecasts and an understanding of the models’ behavior. Furthermore, the insights into models’ rationale can be enriched with domain knowledge. This research builds explanations considering feature rankings for a particular forecast, enriching them with media news entries, datasets’ metadata, and entries from the Google Knowledge Graph. We compare two approaches (embeddings-based and semantic-based) on a real-world use case regarding demand forecasting.

Recent years have shown that traditional regulatory techniques alone are not effective in achieving behavior change in important fields such as environmental sustainability. Governments all over the world have been progressively including behaviourally informed considerations in policy and law-making with the aim of improving the acceptance and impact of sustainability-oriented measures. This led to the arrival of alternative regulatory tools, such as nudges. The effectiveness of nudges for environmental sustainability (green nudges) has been largely reported but the practical and ethical implications are still largely neglected by academic research. In this contribution, “nudges” are conceptually distinguished from “boosts” and their ethical briefly explained. The analysis is made at the light of the current mostly European and US American academic literature.

The incidence of Type 1 Diabetes (T1D) in the Arab world, particularly, oil and gas rich Gulf Cooperative Council (GCC) countries has more than doubled in the last twenty years. Therefore, there is a dire need for careful systematic familial cohort studies, especially in high-risk populations. Several immunogenetic factors affect the pathogenesis of the disease. Genes in the human leukocyte antigen (HLA) account for the major genetic susceptibility to the disease. The triggering agents initiate disease onset by destruction of pancreatic β-cells. The autoantibodies against glutamic acid decarboxylase (GADA), insulinoma antigen-2 (IA-2A), insulin (IAA), and zinc transporter-8 (ZnT-8A) comprise the most reliable biomarkers for T1D in both children and adults. Although three of the GCC countries, namely Kuwait, Saudi Arabia and Qatar are among the top 10 countries with high incidence rate of T1D, no proper diagnostic and prediction tools were applied in the region. Understanding the disease sequelae in a homogenous gene pool with high consanguinity in the GCC could help solve the challenges in understanding pathogenesis, as well as hasten the prevention of T1D. Arab states must incorporate T1D predictive and intervention policies on a war-footing basis to minimize the burden of this serious disease.

We live in the time of profound transformations commonly labelled with the word “globalization”. The rise of one ecological-technological-social system encompassing our whole planet is an important element of these processes. Solving big global problems demands knowledge of two complementary sorts: on the one hand – going “in depth”, on the other – going “in breadth”. The present paper assumes the second (in a sense: philosophical) perspective. It tries to analyze some relations between the development of technology (IT) and the development of democracy. The notion of democracy, its various forms and axiological reasons for it are considered first. In the subsequent chapter different consequences (both positive and negative) the IT development has for contemporary democracy are discussed. In the next chapter the evolutionary nature of the technological development is debated as well as the question of (democratic) control of this process. The development of Artificial General Intelligence is presented as a challenge for democracy

RAS oncogenes are amongst the most commonly mutated proteins in human cancers. They regulate a wide range of effector pathways that control cell proliferation, survival, differentiation, migration and metabolic status. Including aberrations in these pathways, RAS dependent signaling is altered in more than half of human cancers. Targeting mutant RAS proteins and their downstream oncogenic signaling pathways has been elusive. However, recent results comprising detailed molecular studies, large scale omics studies and computational modeling have painted a new and more comprehensive portrait of RAS signaling that helps us to understand the intricacies of RAS, how its physiological and pathophysiological functions are regulated, and how we can target them. Here, we review these efforts particularly trying to relate the detailed mechanistic studies with global functional studies. We highlight the importance of computational modeling and data integration to derive an actionable understanding of RAS signaling that will allow us to design new mechanism based therapies for RAS mutated cancers.

Generative models for images, audio, text and other low-dimension data have achieved great success in recent years. Generating artificial human movements can also be useful for many applications, including improvement of data augmentation methods for human gesture recognition. The object of this research is to develop a generative model for skeletal human movement, allowing to control the action type of generated motion while keeping the authenticity of the result and the natural style variability of gesture execution. We propose to use a conditional Deep Convolutional Generative Adversarial Network (DC-GAN) applied to pseudo-images representing skeletal pose sequences using Tree Structure Skeleton Image format. We evaluate our approach on the 3D-skeleton data provided in the large NTU RGB+D public dataset. Our generative model can output qualitatively correct skeletal human movements for any of its 60 action classes. We also quantitatively evaluate the performance of our model by computing Frechet Inception Distances, which shows strong correlation to human judgement. Up to our knowledge, our work is the first successful class-conditioned generative model for human skeletal motions based on pseudo-image representation of skeletal pose sequences.

— In a smart healthcare system," Human Activity Recognition (HAR)" is considered as an efficient approach in pervasive computing from activity sensor readings. The "Ambient Assisted Living (AAL)" in the home or community helps the people to provide independent care and enhanced living quality. However, many AAL models are restricted to multiple factors that include both the computational cost and system complexity. Moreover, the HAR concept has more relevance because of its applications, such as content-based video search, sports play analysis, crowd behavior prediction systems, patient monitoring systems, and surveillance systems. This paper attempts to implement the HAR system using a popular deep learning algorithm, namely "Recurrent Neural Network (RNN)" with the activity data collected from smart activity sensors over time, and it is publicly available in the "UC Irvine Machine Learning Repository (UCI)". The proposed model involves three processes: (1) data collection, (b) optimal feature learning, and (c) activity recognition. The data gathered from the benchmark repository was initially subjected to optimal feature selection that helped to select the most significant features. The proposed optimal feature selection method is based on a new meta-heuristic algorithm called "Colliding Bodies Optimization (CBO)". An objective function derived from the recognition accuracy has been used for accomplishing the optimal feature selection. The proposed model on the concerned benchmark dataset outperformed the conventional models with enhanced performance.

Due to their unique properties, perfluorinated substances (PFAS) are widely used in multiple industrial and commercial applications, but they are toxic for animals, humans included. This review presents some available data on the PFAS environmental distribution in the world, and in particular in Europe and in Veneto region of Italy, where it has become a serious problem for human health. The consumption of contaminated food and drinking water is considered one of the major source of exposure for humans. Worldwide epidemiological studies report the negative effects that PFAS have on human health, due to environmental pollution, including infertility, steroid hormone perturbation, thyroid, liver and kidney disorders and metabolic disfunctions. In vitro and in vivo researches correlated PFAS exposure to oxidative stress effects (in mammals as well as in other vertebrates of human interest), produced by a PFAS-induced increase of reactive oxygen species formation. The cellular antioxidant defense system is activated by PFAS, but it is only partially able to avoid the oxidative damage to biomolecules.

There are guidelines on lactation following maternal analgo-sedative exposure, but these do not consider the effect of maternal fasting, nor fluid abstention on human milk macronutrient composition. We therefore performed a structured search (PubMed) on ‘human milk composition’ and screened title, abstract and full paper on ‘fasting’ or ‘abstention’ and ‘macronutrient composition’ (lactose, protein, fat, solids, triglycerides, cholesterol). This resulted in 6 papers and one abstract related to religious fasting (n=129 women) and observational studies in lactating women (n=23, healthy volunteers, fasting). These data reflect two different ‘fasting’ patterns: an acute (18-25h) model in 71 (healthy volunteers, Yom Kippur/Ninth of Av) women and a chronic fasting (Ramadan) model in 81 women. Changes were most related to electrolytes and were moderate, with almost no changes in macronutrients during acute fasting. We therefor conclude that neither short term fasting nor fluid abstention (18-25h) affect human milk macronutrient composition, so that women can be reassured when this topic were raised during consulting. Besides the nutritional relevance, this also matters as clinical research samples – especially to estimate analgo-sedative exposure by lactation - are commonly collected after maternal procedural sedation, associated with maternal fasting and physiology-based pharmacokinetic (PBPK) models assume stable human milk composition.

Animal-assisted interventions (AAI) use human-animal interactions to positive effect in various contexts including cancer care. This systematic literature review is the first part of a two-part paper series focusing on the research methods and quantitative results of AAI studies in oncology. We find methodological consistency in the use of canines as therapy animals, in the types of high-risk patients excluded from studies, and in the infection precautions taken with therapy animals throughout cancer wards. The investigated patient endpoints are not significantly affected by AAI, with the exceptions of improvements in oxygen consumption, quality of life, depression, mood, and satisfaction with therapy. The AAI field in oncology has progressed significantly since its inception and has great potential to positively impact future patient outcomes. To advance the field, AAI research in oncology should consistently improve the methodological design of studies, report data more completely, and focus on the therapy animal’s well-being.

A new circuit model of the self-powered device for heart rate measurement is presented in this paper. This device consists of piezoelectric energy harvester (PEH), power management circuit (PMC) with energy storage, microcontroller, Photoplethysmography (PPG) sensor, and Wi-Fi module. The PEH is placed under the insole to harvest the pressure energy from human foot-step to generate ac power. In our model, a PEH is represented by sine voltage source, where its parameters were taken from experiments with 20 volunteers. The PMC is simplified by a switch with gain δ placed in series with the main circuit. The model of the main circuit is RC elements in parallel, where C is the capacitance of the storage device, and R is the equivalent parallel resistance of the microcontroller, PPG sensor, and Wi-Fi modules, respectively. The value of R depends on the power and current absorbed by those modules during sleep, deep sleep, sense, and transmit modes which collected from the datasheet. Finally, the proposed circuit model of the self-powered device was built and simulated in SPICE. The simulation results were compared with the laboratory experiment using commercial devices. Based on the results, the proposed model had small gaps compared to the real self-powered devices in terms of average current, voltage, power and efficiency.

Health of migrant is a widely studied topic. It has been argued that migrant health may deteriorate over time. Though migrants are ‘a hard to reach’ population in survey data, this paper builds on a unique dataset provided by Médecins du Monde from five countries. We study self perceived health (SPH) in connection with socio-economic and demographic factors and length of stay. Results show different results for men and women. Asylum seekers compared to other documented migrants have a worse health. Migrants with better living conditions tend to be in better health. Employment and stable accommodation has a positive effect on SPH. Women from poorer countries have a better physical SPH after 3 months of residing in the host country. This paper contributes widely to knowledge of health of migrants. Contrarily to other evidence, health of migrants tends to improve for some migrants.

Many causal factors to marine traffic accidents (MTA) influence each other and have associated effects. It is necessary to quantify the correlation path mode of these factors to improve accident prevention measures and their effects. In the application of human factors to the accident mechanisms, the complex structural chains on causes to MTA systems were analyzed combining the Human Failure Analysis and Classification System (HFACS) with theoretical Structural Equation Modeling (SEM). First, the accident causation model was established as a human error analysis classification in sight of MTA, and the constituent elements of the causes of accident was conducted. Second, a hypothetical model of Human factors classification was proposed applying the practice of the structural model. Third, with the data resource from ship accident cases, this hypothetical model was discussed and simulated, and as a result the relationship path dependency mode between the latent independent variable of the accident was quantitatively analyzed based on the observed dependent variable of human behaviors. Application examples show that relationships in HFACS are verified and in line with the path developing mode, and resource management factors have a pronounced influence and a strong relevance to the causal chain of the accidents. Appropriate algorithms for the theoretical model can be used to numerically understand the safety performance of marine traffic systems under different parameters through mathematical analysis. Hierarchical assumptions in the HFACS model are quantitatively verified.

Under optimal conditions, just 3–6 ms of visual stimulation suffices for humans to see motion. Motion perception on this time scale implies that the visual system under these conditions reliably encodes, transmits, and processes neural signals with near-millisecond precision. Motivated by in vitro evidence for high temporal precision of motion signals in the primate retina, we investigated how neuronal and perceptual limits of motion encoding relate. Specifically, we examined the correspondence between the time scale at which cat retinal ganglion cells in vivo represent motion information and temporal thresholds for human motion discrimination. The time scale for motion encoding by ganglion cells ranged from 4.6–91 ms, depended nonlinearly on temporal frequency but not on contrast. Human psychophysics revealed that minimal stimulus durations required for perceiving motion direction were similarly brief, 5.6–65 ms, similarly depended on temporal frequency but, above ~10%, not on contrast. Notably, physiological and psychophysical measurements corresponded closely throughout (r = 0.99), despite more than a 20-fold variation in both human thresholds and optimal time scales for motion encoding in the retina. These results demonstrate that neural circuits for motion vision in cortex can maintain and make use of the high temporal fidelity of the retinal output signals.

Detection of human movement requires lightweight, flexible systems to detect mechanical parameters (like strain and pressure) not interfering with user activity, and that he/she can wear comfortably. In this work we address such multifaceted challenge with the development of smart garments for lower limb motion detection, like a textile kneepad and anklet in which soft sensors and readout electronics are embedded for detecting movement of the specific joint. Stretchable capacitive sensors with a three-electrode configuration are built combining conductive textiles and elastomeric layers, and distributed at knee and ankle. They show an excellent behavior in the ~30% strain range, hence the correlation between their responses and the optically tracked Euler angles is allowed for basic lower limb movements. Bending during knee flexion/extension is detected, and it is discriminated from any external contact by implementing in real time a low computational algorithm. The smart anklet is designed to address joint motion detection in and off the sagittal plane. In this work, ankle dorsi/plantar flexion, adduction/abduction, and rotation are retrieved. Both smart garments show a high accuracy in movement detection, with a RMSE less than 4° in the worst case.

The peroxiredoxin (PRDX) family, a new family of proteins with a pivotal antioxidative function, is ubiquitously synthesized and abundantly identified in various organisms. In contrast to the intracellular localization of other family members (PRDX1/2/3/5/6), PRDX4 is the only known secretory form and protects against oxidative damage by scavenging reactive oxygen species in both the intracellular (especially the endoplasmic reticulum) compartments and the extracellular space. Recently, we generated unique human PRDX4 (hPRDX4) transgenic (Tg) mice on a C57BL/6J background and investigated the critical and diverse protective roles of PRDX4 against diabetes mellitus, atherosclerosis, insulin resistance, and nonalcoholic fatty liver disease (NAFLD) as well as evaluated its role in the intestinal function in various animal models. Our published data have shown that PRDX4 helps prevent the progression of metabolic syndrome by reducing local and systemic oxidative stress and synergistically suppressing steatosis, inflammatory reactions, and/or apoptotic activity. These observations suggest that Tg mice may be a useful animal model for studying the relevance of oxidative stress on inflammation and the dysregulation of lipid/bile acid/glucose metabolism upon the progression of human metabolic syndrome, and that specific accelerators of PRDX4 may be useful as therapeutic agents for ameliorating various chronic inflammatory diseases.

This qualitative research investigates the pivotal role of Human Resource Management (HRM) in enhancing supply chain effectiveness. Through semi-structured interviews with 25 professionals across various industries, the study explores how HRM practices influence key aspects of supply chain management (SCM), including talent management, training and development, leadership, organizational culture, and technology integration. Findings highlight the strategic alignment between HRM and SCM as crucial for optimizing supply chain performance and responsiveness. Effective talent management strategies, such as recruitment, development, and succession planning, emerged as critical factors in ensuring operational stability and innovation within supply chains. Training programs were identified as instrumental in equipping employees with the necessary skills to navigate technological advancements and market complexities, fostering collaboration and enhancing decision-making capabilities. Leadership development initiatives were also found to be pivotal in promoting organizational effectiveness and fostering a culture of continuous improvement. The study further underscores the role of HRM in cultivating a collaborative and inclusive organizational culture that enhances communication, trust, and teamwork among supply chain stakeholders. Additionally, the integration of digital technologies and sustainability considerations emerged as transformative trends shaping modern supply chains, with HRM practices playing a crucial role in facilitating technological adoption and promoting environmentally responsible practices. Addressing challenges such as resource constraints, regulatory compliance, economic uncertainties, and global supply chain complexities remains crucial for organizations aiming to optimize HRM practices and achieve sustainable supply chain performance. Overall, this research contributes to a deeper understanding of how HRM can drive innovation, collaboration, and resilience within supply chains, positioning organizations for long-term success and growth.

This paper explores strategies for fostering efficient vocal communication and collaboration between human workers and collaborative robots (cobots) in assembly processes. Vocal communication enables division of attention of the worker, as it frees the visual attention, and the worker’s hands, dedicated to the task at hand. Speech generation and speech recognition are pre-requisites for effective vocal communication. The study focuses on cobot assistive tasks, where the human is in charge of the work and performs the main tasks while the cobot assists the worker in various peripheral jobs, such as bringing tools, parts, or materials, and returning them, or disposing them; or screwing or packaging the products. A nuanced understanding is necessary for understanding how human-robot interactions can be optimized to enhance overall productivity and safety. Through a comprehensive review of relevant literature and empirical studies, this manuscript identifies key factors influencing successful vocal communication, and proposes practical strategies for implementation.

This study investigates the transformative impact of ChatGPT, a cutting-edge AI language model developed by OpenAI, on the financial sector. We explore ChatGPT's applications in financial analysis, focusing on its ability to perform tasks traditionally handled by human analysts. By creating a set of multi-step and advanced reasoning financial tasks, and establishing several task-specific evaluation metrics, our experimental results demonstrate that ChatGPT-4o can effectively perform both basic and some complex financial analysis tasks comparable to those executed by humans. However, our empirical evaluation reveals limitations in its performance on complex tasks that require comprehensive understanding and critical thinking. The study highlights the necessity for meticulous task formulation and robust evaluation to achieve consistent functionality. While ChatGPT enhances efficiency in financial analysis, its integration with human expertise remains crucial for effective decision-making. This study contributes to the understanding of AI's role in finance and provides insights into its potential and constraints, guiding future integration of AI technologies in financial practices.

Nutrition therapy is the best solution to human chronic diseases, especially beer and barley which play an important role in human health and civilization. We demonstrated the actional mechanism of functional ingredients in beer and barley to combat chronic diseases, based on PubMed, google, CNKI, and ISI Web of Science databases from 1997 to 2024. Beer is rich in functional ingredients that is a complex of barley malt and hops; the health effect of beer against 26 chronic diseases is highly similar to that of barley, due to molecular mechanism of polyphenols (phenolic acids, flavonoids), melatonin, minerals, bitter acids, vitamins, and peptides. The ancient German Beer Purity Law provides much scientific basis today, especially indirectly supporting the human one cell disease theory. Low purine beer can be produced by enzymatic and biological degradation and adsorption of purines as well as dandelion addition. Functional beer with low purine and high active ingredients made from Beer Purity and barley malt as well as functional foods addition will be the key and important development direction, such as ginger beer and ginseng beer, especially coix-lily beer at the ancestors ca. 9000 years ago. This review paper not only reveals the actional mechanism of beer overcoming human chronic diseases, but also provides scientific basis for the development of functional beer for the prevention and treatment of human chronic diseases.

This study investigates the impact of intellectual capital on the sustainable performance of banks in Saudi Arabia, focusing on the period from 2012 to 2022. Utilizing data from ten major Saudi banks, the research examines how different components of intellectual capital—Human Capital Efficiency (HCE), Structural Capital Efficiency (SCE), and Capital Employed Efficiency (CEE)—influence key financial performance indicators such as Return on Equity (ROE) and Net Profit Margin (NPM). The study is grounded in the resource-based view of the firm, which suggests that a firm’s internal resources can provide a sustainable competitive advantage. The analysis employs panel data techniques, including fixed and random effects models, to assess the relationships between intellectual capital components and bank performance while controlling for variables like bank size, financial leverage, GDP growth, inflation, and the impact of the COVID-19 pandemic. The findings reveal that intellectual capital significantly enhances bank performance in Saudi Arabia, with human capital efficiency showing the most decisive influence on ROE and NPM. Structural capital and capital employed efficiency also contribute positively but vary in their impact on different performance measures. This research contributes to the theoretical and practical understanding of the role of intellectual capital in promoting sustainable banking practices. It underscores the importance of strategic management of intellectual capital in enhancing financial performance and achieving sustainability goals, particularly in the context of Saudi Arabia's Vision 2030. The study's insights are relevant for bank managers and policymakers who leverage intellectual capital for economic diversification and sustainable development.

This research investigates the intricate dynamics between intellectual Capital (VAIC) and the stability of banks in the evolving context of Saudi Arabia's banking sector. Against the backdrop of rapid economic reforms under Vision 2030 and the challenges imposed by the COVID-19 pan-demic, the research provides a nuanced analysis of how intellectual capital and intellectual capital's components—Human Capital Efficiency (HCE), Structural Capital Efficiency (SCE), and Capital Employed Efficiency (CEE)—affect the financial stability of Saudi banks. The research analyses a decade-long panel dataset from 2012 to 2022, utilizing both fixed effects and cross-section random effects models to discern the impact of intellectual capital on bank stability. The findings reveal a positive overall influence of intellectual capital on bank stability; however, individual compo-nents present a complex relationship, with CEE showing a positive association and HCE and SCE demonstrating unexpected negative correlations with bank stability. The research identifies lev-erage (LEV) as a significant factor negatively impacting stability. Operational efficiency (OPEF) and size (SIZE) also negatively affect stability. Surprisingly, macroeconomic indicators and bank size exhibit non-significant effects on bank stability. Similarly, the direct impact of the COVID-19 pandemic was found to be non-significant, suggesting a resilient banking environment or the presence of effective mitigating strategies. As Saudi Arabia continues its ambitious economic transformation, this research underscores the critical role of effectively managed intellectual capital in ensuring the banking sector's stability. It provides a foundation for ongoing research in this vital area.

Integrated disaster risk reduction in schools represents a key component of safety strategies within the educational sector of every country. In this study, a series of 850 face-to-face interviews (650 with students and 200 with teachers) were conducted throughout 2023 in 10 out of the total 18 municipalities in the Western Morava Basin of the Republic of Serbia. The paper proposes two central hypotheses regarding school-based disaster risk reduction. Firstly, it suggests that gender, age, parent's employment, academic achievement, living situation, paternal and maternal education levels, and engagement with social media collectively influence students' perspectives on this matter. Secondly, it posits that gender, age, marital status, parenthood, and educational background significantly impact teachers' viewpoints on school-based disaster risk reduction. Multivariate linear regression was used to explore predictors of students' and teachers' insights on school-based disaster risk reduction. Various statistical tests including Chi-square, t-tests, one-way ANOVA, and Pearson's correlation were employed to investigate the influence of demographic and socioeconomic factors on these insights. The results of multivariate regression analyses indicate that age, gender and marital emerge as the primary predictors across various facets of students' and teachers' insights on school-based disaster risk reduction (awareness of disasters, disaster education activities, attitudes on disaster risk reduction education, enhancement of disaster information accessibility, etc). The results of this study provide insight into the key factors influencing students' and teachers' perceptions of disaster risk reduction in schools. As such, they can serve as a basis for improving educational programs, developing policies and strategies, normative educational frameworks, teacher training, and further research in disaster education.

Infant mortality remains a major global concern. Sudden unexpected death in infancy (SUDI) is reported globally and in the Western Cape of South Africa it accounted for 40% of all infant deaths between 2012 and 2016. Research highlighting molecular typing of respiratory viruses in SUDI cases is lacking. A total of 116 PCR-positive human rhinovirus (HRV) and respiratory syncytial virus (RSV) swab samples collected from the lungs and trachea of SUDI cases admitted to Tygerberg Medico-legal Mortuary in Cape Town between 2015 and 2019 were included and underwent sequencing and phylogenetic analysis. Three distinct HRV species were identified; HRV-A (n=28), HRV-C (n=11), and HRV-B (n=4), including eight HRV-A, seven HRV-C and one HRV-B genotypes. For RSV, both RSV-A (n=5) and -B (n=5) were detected, but no RSV-A. After amino acid alignment indicating 20 amino acid duplication and nine substitutions, two BA9 genotypes were confirmed. This study describes the first molecular and phylogenetic characterisation of respiratory viruses in SUDI cases in South Africa. The rapid decline in viral viability in post-mortem samples and the retrospective study design employed for the current study did not allow for any correlations between viral genotypes and cause of death and future prospective studies should investigate temporality and specific viral strains associated with clinical disease severity.

Spatial planners are nowadays strongly interested in the benefits of greenspace for the health of urban residents. However, concrete and context-specific guidance on effective greening strategies is still lacking. We present a novel, model-based approach to support the development of such strategies. The approach is quantitative and spatially-explicit, and accounts for multiple health benefits as well as burdens. In this study, we applied the approach to the city of Maastricht (The Netherlands), and conducted an integrated, city-scale assessment of the health benefits and burdens of four urban greenspace designs. These included: ‘No greenspace’, ‘Current greenspace’, ‘Green parking lots and squares’, and ‘Optimized greenspace locations’. For each greenspace design, indicator values were calculated for five health determinants: heat stress, air pollution, perceived unsafety, unattractive views, and tick-bite risk. To assess the health contribution of urban greenspace in a given design, these indicator values were compared with the values in the ‘No greenspace’ design. The study produced clear, quantitative conclusions about the health benefits and burdens of the urban greenspace designs for the case of Maastricht, but also generated novel, more general insights relevant to planning of urban greenspace for health. These insights concern the importance of translating health policy objectives into specific target values or thresholds, and the importance of ‘smart’ choices in greenspace type and location that can effectively reduce trade-offs between health benefits and burdens. Priorities for future research, addressing limitations of the presented approach, concern a further expansion of the range of health benefits and burdens covered by the model, and the development of a common metric for the entire range of health benefits and burdens allowing optimization of greenspace design to maximize its overall net health benefit.

: Microplastics and nanoplastics (MNPs) are becoming an increasingly severe global problem due to their widespread distribution and complex impact on living organisms. Apart from their environmental impact, the effects of MNPs on living organisms have also continued to attract attention. The harmful impact of MNPs has been extensively documented in marine invertebrates and larger marine vertebrates like fish. However, the research on the toxicity of these particles on mammals is still limited, and their possible effects on humans are poorly understood. Considering that MNPs are commonly found in food or food packaging, humans are primarily exposed to them through ingestion. It would be valuable to investigate the potential harmful effects of these particles on gut health. This review focuses on recent research exploring the toxicological impacts of micro- and nanoplastics on the gut, as observed in human cell lines and mammalian models. Available data from various studies indicate that the accumulation of MNPs in mammalian models and human cells may result in adverse consequences, in terms of epithelial toxicity, immune toxicity, and disruption of gut microbiota. The paper also discusses the current research limitations and prospects in this field, aiming to provide a scientific basis and reference for further studies on the toxic mechanisms of micro- and nanoplastics.

The existence of low-cost and accurate tools that can equip the First Responders (FRs) to detect trapped victims and provide insights about their health condition in the aftermath of a disaster, is imperative. To address the problem of detecting trapped victims behind walls or debris, we have developed a tool that exploits an Ultra-Wide Band (UWB) radar sensor for data collection and Machine Learning (ML) algorithms for data analysis. To evaluate the efficacy of our approach, we collected data from nine humans, both in standing and lying down positions. Next, we applied various ML algorithms to the collected dataset for two discrete sub-tasks that are of interest from an FR’s perspective. The first task is the detection of the victim’s presence, where the algorithms attained more than 95% accuracy and F1-Score. The second task is the estimation of the distance between the radar sensor and the victim, where the tool showed an average error of less than 40 cm.

Rotational jumps are crucial techniques in sports competitions. Estimating ground reaction forces (GRFs), one of the components constituting jumps, through a biomechanical model-based approach enables analysis even in environments where force plates or machine learning training data cannot be utilized. In this study, rotational jump movements involving twists on land were measured using inertial measurement units (IMUs) and estimated GRFs and body loads using a 3D forward dynamics model. Our estimation method, based on forward dynamics and optimization calculations, generated and optimized body movements using cost functions defined by motion measurements and internal body loads. To reduce the influence of the dynamic acceleration in the optimization calculation, the 3D orientation using sensor fusion composed of acceleration and angular velocity data obtained from IMUs and an extended Kalman filter was estimated. As a result, by generating movements based on the cost function, it was possible to calculate biomechanically valid GRFs while following the measured movements even if not all joints are covered by IMUs. This estimation method allows for 3D motion analysis independent of measurement conditions or training data.

This study examines the dynamic relationship between Green Human Resource Management (Green HRM), Environmental Performance (EP), Green Employee Behavior (GEB), and Environmental Knowledge and Awareness (EKAW) within the Egyptian hospitality sector context. Using Pearson correlation coefficients and regression analyses on a sample of 400 staff members from hotels and tourist villages in Egypt, the study examines Green HRM practices’ influence on EP, mediated by GEB and moderated by EKAW. The findings reveal significant positive correlations between Green HRM practices and these mediators, indicating that comprehensive environmental strategies and incentive management are pivotal in promoting eco-friendly practices among employees. The study further confirms GEB and EKAW’s substantial mediating role in enhancing EP. The results also suggest that while EKAW and GEB independently contribute to EP, their interaction and the role of environmental awareness as a potential moderator warrant further examination. This research contributes to the literature on sustainable business practices by underscoring human resource strategies’ integral role in achieving environmental sustainability goals, highlighting the importance of incentivizing green practices, and cultivating an organizational culture that prioritizes EKAW. These insights are particularly valuable for organizations seeking to enhance their ecological footprint through effective Green HRM practices.

Urban Green Space (UGS) has important impacts on human health, but an integrated participatory approach to UGS design for improved residents’ health was lacking to date. The aim of our study was to develop and evaluate such a novel approach to address this gap. The approach was developed following guiding principles from the literature, and tested with groups of children and elderly as participants in two neighborhoods of Maastricht (The Netherlands) with a low score on economic and health indicators. Novel aspects of the approach are the inclusion of both positive and negative health effects, the combination of participant self-assessment and model-based assessment of the health effects of UGS designs, and the use of maps to visualize UGS designs and health effects. The participant-generated UGS designs resulted in a considerable self-assessed increase in use of the UGS for meeting, stress reduction or leisure-based physical activity, as compared to the current situation. The model-assessed positive and negative health effects of the participant-generated UGS designs were limited. The major strength of the developed approach is that it combines active participation of residents in UGS (re)design with assessment of the health effects of these UGS designs. Whereas in other participatory approaches to UGS design it often remains unclear whether the resulting designs represent an improvement in terms of health, our combination of computer model-based assessment and a participatory process produced clear outcomes regarding the health benefits and use of UGS designs.