The prevalence of chronic diseases is dramatically increasing demand for emergency healthcare. Existing systems rely on patients self-identifying symptoms, causing dangerous delays. This study develops an AI and IoT-powered “digital twin” solution to enable continuous real-time monitoring and timely prediction of diverse medical emergencies. A digital twin is a virtual representation of an individual, modeled using multidimensional physiological data from wearable sensors. Machine learning techniques analyze patterns in this data to identify anomalies and predict emergencies like heart attacks or falls. A key contribution is an optimized ensemble algorithm combining gradient boosted trees, neural networks, and other techniques to accurately detect emergency events. Evaluation on a dataset of 9158 samples shows the digital twin identifies key emergencies with over 90% recall, enabling prevention and rapid response. It allows risk stratification and personalized interventions based on early warnings, circumventing over 2 million avoidable emergency room visits annually. This study demonstrates the feasibility of an integrated, predictive, patient-centric emergency response system enabled by digital twin technology.

Wetlands are ecosystems that are essential to ecological balance and biodiversity, never-theless human activity is a constant threat to them. Excess nutrients are caused by inten-sive livestock and agricultural operations, pollution, and population growth, which in turn leads to uncontrolled microbiological development. This impairment in water quality can constitute a risk to animal, human, and environmental health. To thoroughly charac-terize the microbial communities, shotgun metagenomics was used to characterize the taxonomic and functional pattern of microorganisms that inhabit urban wetlands in the Los Lagos Region of Chile. The main objective was to identify microorganisms of veteri-nary relevance, assess their potential antibiotic resistance, and characterize the main vir-ulence mechanism. As expected, a high diversity of microorganisms was identified, in-cluding bacteria described as animal or human pathogens. Also, a diverse repertory of an-timicrobial-resistant genes (ARGs) was detected, which confers mainly resistance to be-ta-lactams, consistent with the families of antibiotics most used in Chile. Besides, a di-verse collection of virulence mechanisms was also identified. Given the significance of the relationship between environmental, animal, and human health—a concept known as One Health—there is a need to establish molecular surveillance programs. This work is the first report of the presence of these harmful biological elements in urban wetlands subjected to anthropogenic pressure, located in the south of Chile.

Injury to the central nervous system (CNS), in most vertebrate animals, results in permanent damage and lack of function, due to their limited regenerative capacities. In contrast, echinoderms can fully regenerate their radial nerve cord (RNC) following transection, with little or no scarring. Investigators have associated the regenerative capacity of some organisms with the stress response and inflammation produced by the injury. Here we explore the gene activation profile of the stressed holothurian CNS. To do this, we performed RNA sequencing on isolated RNC explants submitted to the stress of transection and enzyme dissection and compared them to explants kept in culture for 3 days following dissection. We describe stress-associated genes, including members of heat-shock families, ubiquitin-related pathways, transposons, and apoptosis that were differentially expressed. Surprisingly, the stress response does not induce apoptosis in this system. Other genes associated with stress in other animal models, such as hero proteins and those associated with the integrated stress response, were not found to be differentially expressed either. Our results provide a new viewpoint on the stress response in the nervous system of an organism with an amazing regenerative capacity. This is the first step to deciphering the molecular processes that allow echinoderms to undergo fully functional CNS regeneration while also providing a comparative view for students of the stress response in other organisms.

Antimicrobial resistance has been stated to be a global health problem. In Chile, the use of antibiotics should be declared by medical prescription, however, it is unknown what happens to the drugs once the treatment ends. One possibility is that these end up being disposed of in the trash or down the drain. In both scenarios, antibiotics could accumulate in the environment, stimulating the emergence of antimicrobial resistance mechanisms and their transfer between microorganisms. Unfortunately, sometimes wastewater ends up in bodies of water, due to the dragging of elements by rain, or by the presence of illegal water discharges. In this work, we use shotgun metagenomics to elucidate the functional and microbial composition of biohazard elements in the bay of Puerto Varas City, Chile. As expected, we found a high diversity in microbial communities, with bacterial elements described as human or animal pathogens. Also, we detect a diverse repertory of virulence and antibiotic-resistant genes (ARGs), related with macrolides, beta-lactams, and tetracyclines resistance, which are consistent with the families of antibiotics most used in Chile. Similar ARGs were identified in DNA mobile elements. In addition, we tested the AMR ability in 20 bacterial strains recovered from the Llanquihue lake. This is the first report of the presence of genomic elements that could constitute a health problem for the people who live around the Llanquihue Lake of Chile, considering the importance of the interconnection between environmental, animal, and human health, a concept known as One Health.

After brings about a brief review of the theoretical explanations and researches on the reasons for being a victim, this article is organized into two sections. The first presents a comparative analysis of the data for 1999 and 2016 in terms of perceptions, profiles and most significant sociodemographic and socioeconomic variables. The second one shows an explanatory analysis based on a multivariate logistical regression model using as an independent variable lifestyle of the population and socioeconomic variables, and as dependent variables individual’s susceptibility to becoming a victim of certain crimes. The results points towards an explanatory model of victimization in which sociodemographic variables play an increasingly less important role while variables related to lifestyle and subjective perceptions make a significant contribution to greater understanding of the nature of being the victim of a crime.

This study evaluated the epidemiological and genetic susceptibility profile caused by coronavirus 2 (SARS-CoV-2) in children ≤3 years of age with acute gastroenteritis (AGE) or acute respiratory infection (ARI), living in the northwestern region of the Amazon (NWAR). Fecal and saliva sam-ples collected from 202 children (n=404) were subjected to detection of SARS-CoV-2 by RT-qPCR. Polymorphisms in the angiotensin-converting enzyme (ACE rs4646994) and ACE2 G8780A; rs2285666) genes were detected by SYBR GREEN real-time PCR and PCR/Alul digestion, respec-tively. Secretory and Lewis status of histo-blood group antigen (HBGA) was performed using phenotyping/ELISA. Frequencies for the AGE group: SARS-CoV-2; 8.9%; ARI group: SARS-CoV-2; 2.9%. The ACE I/I homozygous polymorphism gene was majority. Males with the ACE2 G8780A SNP were more susceptible to ARI symptoms than AGE (OR = 3.85; 95% CI-1.42-10.38; P 0.007). Most children were secretory FUT2 phenotype (92.6%). Surveillance of diarrhea and respiratory infections in children, along with understanding their causes, are crucial for identifying preven-tion and control strategies and for prioritizing and developing new vaccines. Clinical manifesta-tions of COVID-19 in children ≤3 years of age include AGE.

Fabry disease is a lysosomal storage disorder caused by the deficiency of the α-galactosidase-A enzyme. Cardiac, renal, and neurological involvement significantly reduces life expectancy. Until a few years ago, treatment options for Fabry disease were limited to enzyme replacement therapy with agalsidase alfa or beta administered by intravenous infusion every 2 weeks. Migalastat (Galafold®) is an oral pharmacological chaperone that increases enzyme activity of “amenable” mutations. The safety and efficacy of migalastat were supported in the phase III FACETS and ATTRACT studies, compared to available enzyme replacement therapies; showing a reduction in left ventricular mass, and stabilization of kidney function and plasma Lyso-Gb3. Similar results were confirmed in subsequent extension publications, both in patients who started migalastat as their first treatment and in patients who were previously on enzyme replacement therapy and switched to migalastat. In this review we describe the safety and efficacy of switching from enzyme replacement therapy to migalastat in patients with Fabry disease and “amenable” mutations, referring to publications available to date.

The acoustic environment in learning spaces significantly influences learning effectiveness and occupant well-being. Recent studies have shown that a series of architectural factors within physical learning environments can impact students' educational experiences. This research delves into the relationship between architectural characteristics and the perceived acoustic environment among 467 primary students in 19 learning spaces across 9 schools in Chile. The survey comprises a student questionnaire, a checklist evaluating space characteristics, and acoustic measurements of indoor noise levels during occupied conditions. Examined topics include Indoor Environmental Quality (IEQ) comfort perception, noise annoyance, hearing ability, and acoustic preference. Architectural characteristics considered encompass flexible and acoustic space design parameters. The results indicated that noise discomfort was a common issue, especially in traditional learning spaces without acoustic treatment. The type of learning space (traditional or flexible settings) has a greater impact on acoustic perception particularly concerning noise discomfort and acoustic preference. However, poorly acoustic spaces lacking absorbing materials or exhibiting lower spatial density (m2 per student) contribute to increased indoor noise levels affecting noise annoyance caused by children's talking inside. The study emphasizes the importance of considering both architectural design and acoustic conditioning for optimizing the acoustic experience in educational spaces.

Abstract: Canine ehrlichiosis is a zoonotic disease transmitted by ticks, posing a formidable challenge to both veterinary and public health sectors worldwide. Across continents and regions, the prevalence rates of Ehrlichia canis exhibit significant variation, underlining the necessity for a nuanced and globally informed approach to understanding and combating this disease. The review navigates through this complexity, shedding light on the intricate pathogenesis of the illness. Central to this understanding is the bacterium's adept manipulation of the host's immune response, contributing to the diverse clinical manifestations observed in infected animals. Diagnostic methodologies, crucial for timely intervention and management, are subjected to critical assessment. From traditional microscopy to modern molecular techniques and serology, each approach is scrutinized for its strengths and limitations. By acknowledging these nuances, the review aims to equip practitioners with the knowledge necessary to make informed diagnostic decisions. A central tenet of this review is the advocacy for an integrated "One Health" approach. By leveraging advancements in genomics, proteomics, and artificial intelligence, there is a potential to enhance diagnostic accuracy and develop innovative therapeutic and preventive strategies globally. This collaborative approach recognizes the interconnectedness of human, animal, and environmental health, offering a holistic framework for tackling complex zoonotic diseases like canine ehrlichiosis. In conclusion, this review serves as a beacon of knowledge, illuminating the multifaceted landscape of canine ehrlichiosis. Through its synthesis of scientific literature and emphasis on methodological rigor, it provides a foundation upon which future research and interventions can be built. With a unified commitment to "One Health" principles and the integration of cutting-edge technologies, there exists the potential to mitigate the impact of this disease and safeguard both animal and human well-being worldwide

This study aimed to evaluate the biological activities of two Allium species (Garlic and onion) as well as diallyl disulphide (DADS) and dipropyl disulphide (DPDS) as their representative bioactive compounds in a multi-assay experimental design. The genotoxic, antigenotoxic and lifespan effects of garlic, onion, DADS and DPDS were checked in Drosophila melanogaster and their cytotoxic, pro-apoptotic and DNA-clastogenic activities were analysed using HL60 tumoral cells. All compounds were non-genotoxic and antigenotoxic against H2O2-induced DNA damage with a positive dose-response effect and different inhibition percentages (the highest value: 95% for DADS) at all tested concentrations. Daily intake of Allium vegetables, DADS or DPDS had no positive effects on flies’ lifespan and healthspan. Garlic and DADS exerted the highest cytotoxic effects in a positive dose-dependent manner. Garlic and DADS exerted a DNA-internucleosomal fragmentation as an index of induced proapoptotic activity on HL60 cells. Allium vegetables and DADS were able to induce clastogenic strand breaks in the DNA of HL60 cells. This study showed the genomic safety of the assayed substances and their protective genetic effects against the hydrogen peroxide genotoxine. Long-term treatments during the whole life of Drosophila genetic model were beneficial only at low-median concentrations. The chemopreventive activity of garlic could be associated to its distinctive organosulphur DADS. We suggest that supplementary studies are needed to clarify the cell death pathway against garlic and DADS.

We review past and present results on the non-local form-factors of the effective action of semiclassical gravity in two and four dimensions computed by means of a covariant expansion of the heat kernel up to the second order in the curvatures. We discuss the importance of these form-factors in the construction of mass-dependent beta functions for the Newton's constant and the other gravitational couplings.

In genetic conflicts, driver and killer elements achieve biased survival, replication, or transmission over sensitive and targeted elements through a wide range of molecular mechanisms, including mimicry. Driving mechanisms manifest at all organismal levels, from the biased propagation of individual genes, as demonstrated by transposable elements, to the biased transmission of genomes, as illustrated by viruses, to the biased transmission of cell lineages, as in cancer. Targeted genomes are vulnerable to molecular mimicry through the conserved motifs they use for their own signaling and regulation. Mimicking these motifs enables a selfish element to control core target processes, and can occur at the sequence, structure, or functional level. Molecular mimicry was first appreciated as an important phenomenon more than twenty years ago. Modern genomics technologies, databases, and machine learning approaches offer tremendous potential to study the distribution of molecular mimicry across genetic conflicts in nature. Here, we explore the theoretical expectations for molecular mimicry between conflicting genomes, the trends in molecular mimicry mechanisms across known genetic conflicts, and outline how new examples can be gleaned from population genomic datasets. We discuss how mimics involving short sequence-based motifs or gene duplications can evolve convergently from new mutations. Whereas, processes that involve divergent domains or fully-folded structures occur among genomes by horizontal gene transfer. These trends are largely based on a small number of organisms and should be reevaluated in a general, phylogenetically independent framework. Currently, publicly available databases can be mined for genotypes driving non-mendelian inheritance patterns, epistatic interactions, and convergent protein structures. A subset of these conflicting elements may be molecular mimics. We propose approaches for detecting genetic conflict and molecular mimicry from these datasets.

Abstract: Coal bed methane (CBM) reservoirs are complex systems whose properties differ from those of conventional reservoirs. Coal seams are dual-porosity systems that comprise the porosities of the matrix and cleat system. Gas in the coal seams can be stored as free gas in the cleat system and as adsorbed gas in the porous medium. The flow mechanisms of the natural gas through the formation include desorption, diffusion, and Darcy’s flow regimes. The permeability of CBM reservoirs is more sensitive to pressure variations than conventional gas reservoirs. To study the flow behavior of CBM reservoirs it is mandatory to use a model that considers their unique characteristics. The objective of this study was to propose a physical and mathematical model of production performance for horizontal wells in CBM reservoirs whose permeability is dependent on pressure. A solution for the model was obtained by applying Pedrosa´s transformation, perturbation theory, Laplace transformation, the point source method, and Sthefest´s algorithm. The solution to this problem was validated with previous work thoroughly. The type curves of the model were built and the pressure transient behavior of the model was analyzed and discussed. The effects of several parameters on pressure behavior were also discussed.

The satisfaction of basic psychological needs leads students to engage in a sport modality on their own initiative. In the Spanish public educational system, mixed and heterogeneous, the gender and sport experience of students influence the teaching and motivation of invasion sports. This study investigated whether students' gender and sport experience, and method influence the psychological variables (basic psychological needs and sport adherence) when teaching school soccer and basketball. Furthermore, correlations were calculated between these psychological variables. The study involved 165 fifth and sixth grade students (age, 11.27 ± 0.68 years old) from several Spanish state schools in the same autonomous community. A non-random convenience sample was used. The needs for autonomy, perceived competence and social relationships were measured using the Basic Psychological Needs in Physical Exercise Scale. Sport adherence was measured using the Measure of Intentionality to be Physically Active. A Confirmatory Factor Analysis and Cronbach's alpha were used to analyze the psychometric properties of the scales. Descriptive and inferential analyses were performed with the Mann-Whitney U and Kruskal-Wallis H tests. There were significant differences in the needs for autonomy and perceived competence according to the students’ gender (boys > girls). Attending to sport adherence, there were also significant differences according to the students’ gender (boys > girls) and sport experience (experienced students > inexperienced students). Likewise, a regression analysis (structural equation model) revealed that the autonomy need showed low association with sport adherence. Higher perceived competence (β = 0.52) and social relationships (β = 0.36) were associated with greater adherence to sport (R2 = 0.65). Increased sport adherence will have health benefits.

Making sustainable business models, especially in manufacturing, is a key approach for organizations to adopt in order to create more sustainable processes. New technologies are needed to implement new policies that can minimize the economic, environmental, and social consequences of industrial activity. Sustainable maintenance is decisive to guarantee the availability, reliability, and safety of assets, surpassing traditional maintenance policies and embracing the principles of the circular economy. The main objective of Maintenance 4.0 is to increase the lifespan and availability of the equipment by preventing unplanned downtime, reducing planned shutdowns, and improving safety. This research focuses on the integration of advanced Industry 4.0 tools with conventional monitoring and control techniques in process industries. The article suggests that while complex neural networks might provide good predictions, simpler solutions can generalize well and have lower prediction errors because they can capture the underlying relationships between variables in a specific asset better. The combination of maintenance function, Industry 4.0 tools, and advanced statistical solutions to obtain sustainable processes can facilitate organizational change and aid decision-making in equipment management. These solutions seek to reduce interruptions and expenses through the unnecessary utilization of labor and spare parts. All these considerations improve communication and data processing, resulting in improved maintenance of a hydrogen compressor in the petrochemical industry.

Classical antibacterial drugs were designed to target specific bacterial properties distinct from host human cells to maximize potency and selectivity. These designs were quite effective as they could be easily derivatized to bear next generation drugs. However, the rapid mutation of bacteria and their associated acquired drug resistance have led to the rise of highly pathogenic superbug bacterial strains for which treatment with first line drugs is no match. More than ever, there is a dire need for antibacterial drug design that goes beyond conventional standards. Taking inspiration by the body’s innate immune response to employ its own supply of labile copper ions in a toxic attack against pathogenic bacteria, which have a very low Cu tolerance, this review article examines the feasibility of Cu-centric strategies for antibacterial preventative and therapeutic applications. Promising results are shown for the use of Cu-containing materials in the hospital setting to minimize patient bacterial infections. Studies directed at disrupting bacterial Cu regulatory pathways elucidate new drug targets that can enable toxic increase of Cu levels and perturb bacterial dependence on iron. Likewise, Cu intracellular chelation/prochelation strategies effectively induce bacterial Cu toxicity. Cu-based small molecules and nanoparticles demonstrate the importance of the Cu ions in their mechanism and display potential synergism with classical drugs.

While there are extensive studies on the mineralogy and geochemistry of laterites worldwide, the temporal and spatial mineralogical development of a typical nickel laterite profile is still poorly constrained. In this study, we present a detailed mineralogical and geochemical characterization of samples systematically collected from a nickel laterite profile at the Sta. Cruz nickel laterite deposit, Zambales, Philippines, to describe the temporal and spatial development of the laterite profile. Wavelength-dispersive X-ray fluorescence spectroscopy (WDSXRF), mass balance-element mobility calculations, transmitted and reflected light microscopy, and previously reported results from coupled X-ray diffraction (XRD) and Rietveld refinement analyses, reveal that the laterite profile investigated is composed of two main horizons: the limonite and saprolite zones, separated by a thin transitional zone. The main zones are further subdivided into subzones based primarily on the mineral assemblage and major element chemistry: upper limonite, lower limonite, transitional zone, upper saprolite, and lower saprolite. Late-stage Ni-rich serpentine veins were observed cutting the upper and lower saprolite subzones. Investigation of the structure of goethite within the limonite zone via Rietveld refinement show that the crystallinity of goethite decreases with increasing Ni content and increasing crystallite size. This suggests that upwards through the limonite zone, as goethite ages, its crystallinity increases which possibly results in the removal of Ni from its crystal structure and eventual remobilization to the lower laterite zones. We propose a genetic model of the formation of the Sta. Cruz laterite consisting of four stages: (1) early-stage alteration, (2) continued serpentinization and volume expansion, (3) late stage serpentinization, dissolution, and incipient oxide formation, and (4) goethite ageing and Ni-rich serpentine vein formation. Overall, our results suggest that serpentinization is an important aspect of Ni laterite formation, both before and after the emplacement of the peridotite protolith.

This article focuses on the comparison and perception of the potential of water’s surface in selected parts of the waterfront in two contrasting cities. The aim is to define the potential of the water’s surface in terms of psychology and its effects on climate. The analysis was performed on the example of Prague with its waterfront on the river Vltava, and Santa Cruz de Tenerife with its Atlantic coastline. Data was sourced from maps, questionnaire surveys and interviews with waterfront users during October 2020. The research showed a higher importance of the water’s surface for users in Prague, than in Santa Cruz. The main finding is that the psychological perception of the waterfront by its the users is affected by the possibility of a visual contact with the water’s surface, the design and composition of the space, and the climate situation of a site affected by the presence of an urban heat island (UHI). The results promote an adherence to ecosystem-based approaches in future design projects and modifications of existing public spaces. The purpose of the work is to open a broader debate on the sustainability of the potential of waterfronts and their positive impact on human health.

The Kalanchoe genus is composed of more than 100 species that usually thrive in tropical environments, which have been used in folkloric medicine to treat various illnesses, including dermatological conditions. With this, the present study assesses the pharmacognostical and pharmacological properties of different species of the Kalanchoe genus as elements for a potential treatment for dermatological-related conditions, from findings of existing literature and studies. It was analyzed that the Kalanchoe pinnata plant, or one of the most common species of Kalanchoe, have been observed to have distinct morphological and microscopic characteristics. Further, it was discovered that different species of Kalanchoe have anti-inflammatory, antioxidant, antibacterial, and wound healing properties, which enable the plant to be used for dermatological products that are available to the market. With this, it is recommended that further studies be conducted in other understudied species of Kalanchoe regarding their pharmacological properties, as well as the use of other structures of the Kalanchoe plant for treatment of various dermatological conditions.

With the continuous growth of electric and electronic appliances’ usage, the waste produced with obsolete material (e-waste) has an increasing environmental impact. Also, the production of such appliances bears to increased consumption of natural resources and produces a multitude of toxic and hazardous substances, which typically are not properly treated. One of the approaches that may be adopted to reduce such problems relies on the circularization of the current linear model, commonly adopted in the EEE value chain. This includes recovering eol products and reintroducing its parts, components, or raw materials into the value chain (e.g. semiconductors, circuit boards, raw metals, etc.), thus contributing to a more sustainable value chain. In this article, we present a state-of-art review that focuses on approaches and solutions for the EEE value chain traceability, and analyses the technologies that may be beneficial for promoting and implementing the CE model in this value chain.

Keywords: knowledge; behaviour; ergonomics; posture; musculoskeletal; pain; university; students; survey.

The different sociocultural context and lifestyle may influence oral health. To evaluate the interference of these factors, we conducted a quantitative-qualitative cross-sectional study. The research was carried out in a private dental office, in an urban area, and in the Family Health Unit (USF), in a rural area. Fifty patients of each location participated on the research. A semi-structured questionnaire covering sociocultural profile, oral hygiene habits, drug consumption, use of medicinal plants, and antibiotics usage was applied. Also, laboratory tests to evaluate the tendency to have dental decay and Streptococcus sp colony counting was performed. There was no significant difference between patients in the two groups regarding gender, race, marital status, type of residence, number of residents in the same household, and type of employment. Private clinic participants were more prone to consuming alcohol and/or cigarettes and reported to brush the teeth more often. There was no association between salivary acidity and higher biofilm bacterial density. The usage of medicinal plants was more evident in the public service. Data presented here revealed that social inequality between private and public dental assistance are greater from the point of view of investment in public health for the population with difficult access and not from cultural or educational level diversity.

Several sun models suggest the radioactive balance where the concentration of greenhouse gases and the albedo effect are related to the Earth's surface temperature. There is a considerable increment of greenhouse gases due to anthropogenic activities. Climate change correlates with this alteration in the atmosphere and an increase in surface temperature. Efficient forecasting of climate change and its impacts of 1.5°C global warming above pre-industrial levels could be helpful to respond to the threat of c.c. and develop sustainably. Many studies have predicted the temperature change in the coming years. The global community has to create a model that can realize good predictions to ensure the best way to deal with the warming. Thus, we propose a finite-time thermodynamic (FTT) approach in the present work. The FTT can solve problems such as the faint young sun paradox. In addition, we use different machine learning models to evaluate our method and compare the experimental prediction and results.

Instead of simplified steady-state models, with modern computers, one can solve the complete aero-thermodynamics happening in gas turbine engines. In the present article, we describe a mathematical model and numerical procedure to represent the transient response of a PT6A gas turbine engine operating at off-design conditions. The aero-thermal model consists of a set of algebraic and ordinary differential equations that arise from the application of the mass, linear momentum, angular momentum, and energy balances in each engine's component. The solution code has been developed in Matlab-Simulink using a block-oriented approach. Transient simulations of the PT6A engine start-up have been carried out by changing the original Jet-A1 fuel with biodiesel blends. Time plots of the main thermodynamic variables are shown, especially those regarding the structural integrity of the burner. Numerical results have been validated against reported experimental measurements and GasTurb simulations. The computer model has been capable to predict acceptable fuel blends, such that the real PT6A engine can be substituted to avoid the risk of damaging it.

Brazilian garimpeiros are a highly hard-to-reach and mobile population, with little access to basic hygiene and health services, and have been crossing the border to work irregularly in gold mines in French Guiana since the 90s. This study aimed to characterize this population and identify their main health problems. A cross-sectional study was carried out in the municipality of Oiapoque-AP, with two surveys: before (2018) and after (2019) the implementation of Malakit. Individuals were recruited from resting places and submitted to a questionnaire with demographic variables, history and knowledge of malaria, and health issues in the mines. Simultaneously, a clinical evaluation was performed. The garimpeiros were mainly men from Maranhão, Pará, and Amapá, with a low educational level and worked on average for 10 years in the mining sites. The study population mentioned numerous health problems: malaria, followed by leishmaniasis, flu, body aches, headaches, and digestive problems. Other diseases mentioned were skin diseases, bat bites, hepatitis, and HIV infection. This vulnerable population is constantly subjected to heavy routines and exposed to different diseases and infections that can spread across borders. Knowledge of this is essential for developing public health policies that can be integrated into specific epidemiological situations.

Family Parvoviridae consists of small, non-enveloped viruses with linear, single-stranded DNA genomes of approximately 4-6 kilobases, subdivided into 3 subfamilies: Parvovirinae, Densovirinae and Hamaparvovirinae. Parvoviruses of aquatic animals infect crustaceans, mollusks, and finfish. In this review, these parvoviruses, which are highly host-specific and are associated with mass morbidity and mortality in both farmed and wild aquatic animals are described. They include Cherax quadricarinatus densovirus (CqDV) in freshwater crayfish; Sea star-associated densovirus (SSaDV) in sunflower sea star on the Northeastern Pacific Coast; Clinch densovirus 1 in freshwater mussels in the Clinch River, Virginia, and Tennessee, USA, in subfamily Densovirinae; Hepatopancreatic parvovirus (HPV) and Infectious hypodermal and hematopoietic necrosis virus (IHHNV) in farmed shrimp worldwide; Syngnathid ichthamaparvovirus 1 in gulf pipefish in the Gulf of Mexico and parts of South America; and Tilapia parvovirus (TiPV) in farmed tilapia in China and Thailand, in the subfamily Hamaparvovirinae. In addition, virus megataxonomy has enabled the inclusion of novel parvoviruses detected in both diseased and healthy animals using metagenomic sequencing for virus discovery, such as the novel zander parvovirus from zander in Hungary, novel salmon parvovirus from sockeye salmon smolts in British Columbia-Canada, and Spawner-isolated mortality virus (SMV) from shrimp broodstock in Australia.

Artificial Intelligence (AI) has emerged as a disruptive technology in various areas, and medicine is no exception. In the last decade, there has been rapid progress in the application of AI in healthcare, from diagnosing and prognosticating diseases to improving operational efficiency in hospitals. This literature review explores the advances of artificial intelligence in the field of medicine, discusses its benefits, and discusses the ethical and regulatory challenges that need to be addressed to maximize its potential.

Abstract: Rhizobia are soil proteobacteria able to engage in a nitrogen-fixing symbiotic interaction with legumes which involves root rhizobial infection and bacterial invasion of new organs formed by the plant in response to the presence of appropriate bacterial partners. This interaction relies on a complex molecular dialogue between both symbionts. Bacterial N-acetyl-glucosamine oligomers called Nod factors are indispensable in most cases for early steps of the symbiotic interaction. In addition, different rhizobial surface polysaccharides, such as exopolysaccharides (EPS), may also be symbiotically relevant. EPS are acidic polysaccharides located out of the cell with little or no cell association that carry out important roles both in free-life and in symbiosis. EPS production is very complexly modulated and, frequently, co-regulated with that of Nod factors, but the type of co-regulation varies depending on the rhizobial strain. Many studies point out a signalling role of EPS-derived oligosaccharides in root infection and nodule invasion but, in certain symbiotic couples, EPS can be dispensable for a successful interaction. In summary, the complex regulation of the production of rhizobial EPS varies in different rhizobia and the relevance of this polysaccharide in symbiosis with legumes depends on the specific interacting couple.

The Textile and Clothing (T\&C) value chain is one of the most polluting in the world and one that produces the most waste. It is, therefore, important to encourage the Circular Economy (CE) model in this sector, to reduce pollution and mitigate the effects of waste production, and consequently increase environmental sustainability. For that, the involvement of the final consumer is essential. And, the final consumer's use of an Eco-gamified application for registering and promoting Consumer-to-Consumer (C2C) and Consumer-to-Business (C2B) activities, which extends the life time of textile products, is of utmost importance. In this article, we survey gamification frameworks for analyzing system design level techniques that enable engaging the final consumer in the CE process. Then, we select and use one of such frameworks, Gameful Design Heuristics (GDH), for defining the gamification structure needed to implement on a Business-to-Consumer-to-Consumer (B2C2C) context of a circular economy. As result, we present a B2C2C circular business process model for the T\&C value chain, and propose the design model of a gamified platform for the final consumers, which allows them to register the C2B and C2C activities, from the circular value chain's business process, and benefit from a game-like experience. All model features have been mapped to GDH framework heuristics, validating that it is possible to support a set of defined heuristics of applied gamification for promoting CE in the T\&C value chain.

Urbanization has impacted biodiversity and ecosystems at a global scale. At the same time, it has been recognized as a driver of the gap between humans and nature. The lack of direct contact with nature can deteriorate several aspects of human wellbeing, and change knowledge and attitudes of people towards the environment. However, this phenomenon is still poorly understood in Megacities outside developed countries. Here, we explore the relationship between ecological knowledge and self-reported wellbeing in an important urban park in Santiago, Chile. We conducted semi-structured surveys to park users to explore their notions, preferences, ecological knowledge of plants and birds and self-reported wellbeing. Citizens associated urban parks mainly with “nature”, and particularly with the presence of trees and plants. Trees were recognized as the most relevant elements of urban parks, in turn, birds were ranked as the less relevant. Regarding ecological knowledge, respondents correctly identified an average of 2.01 plants and 2.44 birds out of a total of 10 for each taxon, and exotic species were more likely to be recognized. Park users also reported high scores for self-reported wellbeing. Interestingly, variance of self-reported wellbeing scores tended to increase at low levels of ecological knowledge of trees, but no significant relationship was detected with knowledge of birds, nor native species. These results suggest that parks can positively contribute to bring people closer to nature. Ecological knowledge was related to self-reported wellbeing. Improving ecological knowledge can be critical to restore the relationship between humans and nature in megacities.

Autism Spectrum Disorder (ASD), a neurodevelopmental disorder, is increasingly diagnosed and significantly affects communication, behavior, and social interaction. The current diagnostic framework, guided by the DSM-5, has limitations that may lead to clinical gaps due to overlapping symptoms of ASD and other disorders. This study proposes a comprehensive approach to enhance ASD diagnosis through clinical stratification based on comorbidities. We applied precision medicine techniques to identify and categorize ASD into ten clinical profiles. Our findings contribute to a more profound understanding of ASD, including its varied clinical manifestations and comorbidities, and facilitate the development of personalized therapeutic strategies.

Embryonic and larval Danio rerio is increasingly used as a toxicological model to conduct rapid in vivo tests and developmental toxicity assays; the zebrafish features as high genetic homology to mammals; robust phenotypes; and its value in high-throughput genetic and chemical screening have made it a powerful tool to evaluate in vivo toxicity. New methodologies of genome editing as CRISPR/Cas9; ZFN or Talen make it a suitable model to perform studies to pair human genetic diseases as well. This review surveys recent studies; employing zebrafish as experimental model; comparing it with other in vivo and in vitro models; presenting zebrafish as a potent vertebrate tool to evaluate drug toxicity to facilitate more extensive; easy and comprehensive knowledge of new generation drugs.

Despite effective vaccines, yellow fever outbreaks persist, increasing the urgency to find antivirals for patient treatment. This study aimed to discover compounds with potential antiviral properties against the wild-type yellow fever virus (wt-YFV) in Hippeastrum puniceum, of the Amaryllidaceae family, through bioassay-guided fractionation of the crude bulb extract using ultra-high-performance liquid chromatography (UHPLC) coupled with high-resolution ESI-QTOF mass spectrometry and subsequent analysis of the pharmacokinetic and toxicological properties (ADMET) of the annotated compounds. In the active fractions against wt-YFV, six alkaloids were proposed such as bulbisine, cathinone, trigonelline, tetrahydroharman-3-carboxylic acid, and 2,7-dimethoxyhomolycorine (or 3-O-acetylnarcissidine). Co-occurring in these fractions were the amino acids arginine, asparagine, tryptophan, and glutamic acid. In silico ADMET analysis of the alkaloids predicted good absorption, distribution, excretion, favorable metabolization profiles, and non-mutagenic toxicity, indicating their potential for drug development. These findings justify further in vitro assessment of the compounds against YFV and in vivo testing in animal models. This strategy seems to be an efficient approach for discovering antiviral compounds against YFV. Such discoveries hold promise not only in combating YFV but also in addressing a spectrum of other flaviviruses.

Leishmaniasis represents a severe global health problem. In the last decades, there have been significant challenges in controlling this disease due to the unavailability of licensed vaccines, the high toxicity of the available drugs, and an unrestrained surge of drug-resistant parasites, and human immunodeficiency virus (HIV)–Leishmania co-infections. Leishmania spp. preferentially invade macrophage lineage cells of vertebrates for replication after subverting cellular functions of humans and other mammals. These early events in host–parasite interactions are likely to influence the future course of the disease. Thus, there is a continuing need to discover a simple cellular model that reproduces the in vivo pathogenesis. Acanthamoeba spp. are non-mammalian phagocytic amoeba with remarkable similarity to the cellular and functional aspects of macrophages. We aimed to assess whether the similarity reported between macrophages and Acanthamoeba spp. is sufficient to reproduce the infectivity of Leishmania spp. Herein, we analyzed co-cultures of Acanthamoeba castellanii or Acanthamoeba polyphaga with Leishmania infantum, Leishmania amazonensis, Leishmania major, and Leishmania braziliensis. Light and fluorescence microscopy revealed that the flagellated promastigotes attach to the A. castellanii and/or A. polyphaga in a bipolar and or random manner, which initiates their uptake via pseudopods. Once inside the cells, the promastigotes undergo significant changes, which result in the obligatory amastigote-like intracellular form. There was a productive infection with a continuous increase in intracellular parasites. However, we frequently observed intracellular amastigotes in vacuoles, phagolysosomes, and the cytosol of Acanthamoeba spp. Our findings corroborate that Leishmania spp. infects Acanthamoeba spp. and replicates in them but does not cause their rapid degeneration or lysis. Overall, the evidence presented here confirms that Acanthamoeba spp. have all prerequisites and can help elucidate how Leishmania spp. infect mammalian cells. Future work exposing the mechanisms of these interactions should yield novel insights into how these pathogens exploit amoebae.

Mechanical ventilation systems, which are used for breathing support when a person is not able to do it by their own, requires a device for measuring the air flow to the patient in order to monitoring and a assure the magnitude establish by a medical staff. Flow sensors are the conventional devices used for the air flow measuring; however, there were not available in Peru, because of the international demand during COVID-19 pandemic. In this sense, a novel air flow sensor based on orifice plate and an intelligent transducer stage were developed as an integrated design. Advanced methodologies in simulations and experiments using specially designed equipment for this application were carried out. The obtained data was used for a mathematical characterization and dimensions validation of the integrated design. The device was tested in its real working conditions, it was implemented in a breathing circuit connected to a low-cost mechanical ventilation system based on cams. Results indicate that the designed air flow sensor/transducer is a low-cost complete medical device for mechanical ventilators able to provide satisfactorily all the ventilation parameters air flow, pressure and volume over time by measuring the air flow and calculating the others. Furthermore, this device provides directly a filtered equivalent electrical signal for a display or a computer.

In the past decades, one of the most widely reported phenomena on Caribbean reefs is the general fall in coral cover and rise in macroalgae. Reefs with low coral cover and high macroalgal abun-dances are often presumed to provide poorer ecosystem functions and services. In this study, we assessed the condition of coral reefs on the Caribbean Coast of Costa Rica and determined how eight key ecosystem metrics varied in response to differential coral and fleshy macroalgae covers. Most reefs surveyed had high fleshy macroalgae and low live coral covers, with an average (± SD) of 31 ± 28% and 14 ± 13% per site. We found that the rugosity, urchin density, fish richness, total fish biomass, large fish density, and the potential fishery value of the reef were higher in sites with low fleshy macroalgae covers (>10%). The value of many of the ecosystem metrics estimated for coral reefs of the region appears to be lower than what’s been reported for other areas in the Caribbean, which may be related to the high macroalgae covers found on the reefs. Our results concur with the prevailing paradigm that an increase in macroalgae abundance could reduce the ecosystem services provided by coral reefs.

With limited state budget, developed nation public higher education have increased their fees making education expensive for most developing nation students. Some developing nations have set up regional low-cost education hubs to attract developed nation universities to offer their reputable degree programs. However, the intense competition for student enrolment in both has led to the marketisation of education. Students as paying customers need to experience satisfying stress-free teaching and learning to sustain enrolment. With employers increasingly unhappy with the quality of human capital, has the marketisation of higher education led to nominal human capital development? Can substantive human capital be developed in the new normal of marketisation of higher education? An adaptation of randomised control trials was used to measure learning outcomes desired by future employers for two teaching and learning approaches namely students as customers (n=497) and employers as customers (n=355). Findings show both approaches have good learning outcomes with the latter generally more superior. However, the former leads to nominal learning outcomes. This research extends the literature on achieving substantive learning outcomes conducive to employability. Implications for student satisfaction, lecturer professionalism, employability and quality assurance are discussed.

This study aims to characterize the molecular profile of hepatitis B virus (HBV) among socially vulnerable immigrants residing in Brazil to investigate the introduction of uncommon HBV strains into the country. Serum samples from 102 immigrants with positive serology for HBV core antibody (anti-HBc) were tested for the presence of HBV DNA by PCR assays. Among these, 24 were also positive for the HBV surface antigen (HBsAg). The full or partial genome was sequenced to determine genotype by phylogenetic analysis. Participants were from Haiti (79.4%), Guinea Bissau (11.8%), Venezuela (7.8%), and Colombia (1%). Of the 21 HBV DNA-positive samples, subgenotypes A1 (52.4%), A5 (28.6%), E (9.5%), F2 (4.8%), and F3 (4.8%) were identified. Among the 78 HBsAg-negative participants, four were positive for HBV DNA, resulting in an occult HBV infection rate of 5.1%. Phylogenetic analysis suggested that most strains were likely introduced to Brazil by migration. Importantly, 80% of A5 sequences had the A1762T/G1764A double mutation, linked to an increased risk of hepatocellular carcinoma development. In conclusion, this study is the first report of HBV subgenotype A5 in Brazil, shedding new light on the diversity of HBV strains circulating in the country. Understanding the genetic diversity of HBV in immigrant communities can lead to better prevention and control strategies, benefiting both immigrants and the broader society.

Scientists and astronomers have attached Scientists and astronomers have attached great importance to the task of discovering new exoplanets, even more so if they are in the habitable zone. To date, more than 4300 exoplanets have been confirmed by NASA, using various discovery techniques, including planetary transits, in addition to the use of various databases provided by space and ground-based telescopes. This article proposes the development of a deep learning system for detecting planetary transits in Kepler Telescope lightcurves. The approach is based on related work from the literature and enhanced to validation with real lightcurves. A CNN classification model is trained from a mixture of real and synthetic data, and validated only with real data and different from those used in the training stage. The best ratio of synthetic data is determined by the perform of an optimisation technique and a sensitivity analysis. The precision, accuracy and true positive rate of the best model obtained are determined and compared with other similar works. The results demonstrate that the use of synthetic data on the training stage can improve the transit detection performance on real light curves.

The present study aimed to determine the genetic diversity of isolates of Mycobacterium tuberculosis (Mtb) from presumed drug resistant tuberculosis patients from several states of Brazil. The isolates had been submitted to conventional drug susceptibility testing for first- and second-line drugs. Multidrug-resistant (MDR-TB) (54.8%) was the most frequent phenotypic resistance profile, in addition to an important high frequency of pre-extensively resistant (p-XDR-TB) (9.2%). Using whole-genome sequencing (WGS), we characterized 298 Mtb isolates from Brazil. Besides analysis of genotype distribution and possible correlations between molecular and clinical data, we determined the performance of an in-house WGS pipeline with other online pipelines for Mtb lineages and drug resistance profile definition. Sub-lineage 4.3 (52%) was the most frequent genotype and the genomic approach revealed a p-XDR-TB level of 22.5%. We detected 20 novel mutations in three resistance genes, and six of these were observed in eight phenotypically resistant isolates. Cluster analysis of 170 isolates showed that 43.5% of the TB patients belonged to 24 genomic clusters, suggesting considerable ongoing transmission of DR-TB, including two interstate transmissions. The in-house WGS pipeline showed the best overall performance in drug-resistance prediction, presenting the best accuracy values to five of nine drugs tested. Significant associations were observed between suffering from fatal disease and genotypic p-XDR-TB (p = 0.03) and either phenotypic (p = 0.006) and genotypic (p = 0.0007) ethambutol resistance. The use of WGS analysis improved our understanding of the population structure of MTBC in Brazil, genetic and clinical data correlations and demonstrating its utility for surveillance efforts for spread of DR-TB, hopefully helping to avoid the emergence of even more resistant strains and to reduce TB incidence and mortality rates.

Geopolymers, made from aluminosilicate raw materials, offer significant environmental advantages over conventional concrete (CC) mixes. This study explores the compressive strength, setting time, and durability of geopolymer concrete (GPC) cylinders, some of which include an additional ordinary portland cement (OPC) mix. Consistent material composition and testing methods are emphasized to achieve reliable results. MATLAB was utilized to develop and assess a neural network model predicting the compressive strength of GPC based on key variables. The model was validated using 16 experimental samples and 1047 samples from various studies. The performance plot displayed the Mean Squared Error (MSE) over iterations, identifying the best training performance at epoch 658 with an MSE of 5.3408. The Error Histogram highlighted distribution errors between predicted and actual compressive strength values, with the highest range from -1.015 to 0.3587, meaning that the predicted values were mostly within a small margin of error from the actual values. This narrow error range indicates that the ANN model has high accuracy in its predictions, as most errors are small and clustered around zero, demonstrating reliable performance in estimating compressive strength. Regression analysis showed varying correlation coefficients (training set R=0.98373, test set R=0.88164, and whole set R=0.96982), indicating adequate predictive accuracy. The results demonstrate that properly trained neural networks can effectively predict the compressive strength of GPC, highlighting its potential as a sustainable construction material.

The city of Lisbon, has any other capital of a European country, has a large number of issues while managing the waste and recycling containers spread throughout the city. This document presents the results of a study promoted by the Lisbon City Council for trialing LPWAN technology on the waste management vertical under the Lisbon Smart City initiative. Current waste management is done using GSM sensors, and the aim is to use LPWAN to reduce the costs, improve range and reduce provisioning times when changing the communications provider. After an initial study, LoRa was selected as the LPWAN of choice for the trials. The study is composed of multiple use cases at different distances, types of recycling waste containers, placements (underground and surface) and different kinds of waste level measurement LoRa sensors, deployed in order to assess the impact of the different use cases on the LoRa sensor usage. The results shown that the underground waste containers present the most difficult challenge, where the container itself imposes attenuation levels of 26dB on the link budget. The results promoted the deployment of a city wide LoRa network available to all departments inside the Lisbon City Council, and considering the network capacity the network, the network is also available to citizens to be used freely.

Textile and clothing is one of the most important industrial sectors, not only due to the significant number of jobs generated, but also because it addresses one of the people’s fundamental needs (clothing). It is, however, a sector with a huge environmental impact, all over the world, and also an important social impact, especially in developing countries. Sustainability in the Textile & Clothing value chain is a known issue, concerning both environmental, and economical-social facets of sustainability. One way to improve sustainability in this sector is by measuring the environmental, economic and social impacts of value chain activities and, ultimately, computing an Environmental and Circular score for each batch of textile and clothing product, and an Economical and Social score for each involved firm, reflected in their products. The consumer will then have the opportunity and responsibility for selecting products with the least negative environmental, economical and social impact. This article presents the results of STVgoDigital project - PPS1, developed in Portugal with the aim of implementing the traceability of textile and clothing products, boosting sustainability in this sector, and preparing the ground for the implementation of the circular economy. More exactly, a blockchain-based textile and clothing value-chain traceability platform is presented, for tracing textile product lots and activities, along the value chain, classifying them with a score, which measures their environmental and social impact. The environmental, economic and social impact scores are based on a set of proposed indicators. The results are assessed through the presentation of a case study of a face towel (home textile) and a case study of a T-shirt (clothing).

This study provides an evaluation of a web-based platform for game management and sales, developed using PHP, MySQL, and SASS. The development process utilized the SCRUM methodology, concentrating on essential modules such as user management, game catalog, payment processing, and technical support. The platform's performance was assessed using Google's Lighthouse tool, which evaluates four critical areas: performance, accessibility, best practices, and SEO. The results demonstrated exceptional performance with a score of 99/100 and perfect adherence to best practices with a score of 100/100, reflecting high efficiency and compliance with web development standards. Accessibility received a score of 83/100, indicating potential areas for improvement, while SEO achieved a score of 91/100, suggesting effective search engine optimization. The findings reveal that the platform exhibits high levels of optimization and operational efficiency. However, there remains an opportunity to enhance accessibility features. This study highlights the significance of rigorous web development practices and optimization efforts in achieving superior performance and user experience in web-based systems.

This study focuses on the creation and implementation of a platform to improve personal financial management for scholarship students of the National Program of Scholarships and Educational Credit (Pronabec) in Peru. Using a mixed methodology that combines qualitative and quantitative techniques, the effectiveness and user satisfaction with the platform were evaluated. The results indicated that 50\% of users found the tool useful, 55\% considered it easy to use, 70\% reported a positive impact on their personal budget planning, and 85\% expressed high overall satisfaction. In addition to providing tools for financial recording and analysis, the platform promotes financial education among its users, significantly contributing to improving their financial management skills.

In this work a new method is proposed to tackle down the multiple objective optimization problem of the calculation of cation distribution in spinels structure, through the difference of intensity ratios between experimental and calculated intensities of cation sensitive Bragg planes, by introducing a new factor, Rabs, in Bertaut method. This factor is introduced as the sum of absolute R factors, and it is minimized by varying cation distribution. To test this method aluminate manganese spinel where synthesized though modified Pechini method and characterized though XRD. The results show to be in agreement with literature for the aluminum inversion in tetrahedral sites, which is near to the reported value of 10%. Also, it was noticed that the manganese atoms are present in octahedral sites with a mixed valence state of +2 and +3. Which might be an indicator that oxygen vacancies are present in the structure, so the vacancies value of oxygen is proposed considering the total charge of cations and thus proposing the value of 3.678 mol per formula unit of the spinel, thus having the next stoichiometry considering normalized Al and Mn, MnAl2O3.678. Finally, the last cation distribution proposed was [Mn0.867^(+2) Al0.129^(+3) ][Mn0.034^(+2) Mn0.098^(+3) Al1.871^(+3) ] O3.678 with a Rabs factor value of 0.6466, which considers the cation distribution and oxygen vacancies.

Academic interest in social and human capital is growing significantly. Similarly, their relationship with sustainability is increasing, especially compared to sustainability’s relationship with natural capital and financial and economic capital. Bibliometric and visualization research on these relationships is nonetheless insufficient. This study analyzes the evolution of the literature on natural capital, financial and economic capital, and social and human capital related to sustainability. On the other hand, the study presents a bibliometric analysis on social capital and human capital (SHC) related to sustainability. The article studies 635 references collected from the Web of Science (WoS) Core Collection database and utilizes visualization of similarities (VOS) viewer program to graphically map the material. The analysis involves co-occurrence of keywords, co-citation, and co-authorship. The results reveal not only the state of the art and the leading trends, but also the evolution regarding impact, main journals, documents, topics, authors, institutions, and countries. The study provides researchers and practitioners with a visual and schematic frame of the research on this topic.

Crop production has become a priority issue in the last few years due to the exponential growth of the world population and the need to substitute chemical fertilizers. This last matter is under the spotlight to achieve a more sustainable approach in a cost-effective way. Biostimulants have gained attention as an alternative to chemical fertilizers. Although they are not considered fertilisers as inputs of nutrients, they stimulate plants’ nutrition and tolerance to stress, among other characteristics. Amino acid-based biostimulants have been found to be effective in literature. This review focuses on the effectiveness of biostimulants, their presence in the global market, and mainly in their production with fish by-products as a source, using enzymatic hydrolysis and autolysis, focusing especially on fish viscera, their possibilities in the agricultural sector and their availability in Europe for possible opportunities. Fish viscera protein hydrolysates for biostimulant production seems a feasible alternative to fishmeal production in Europe, mainly in areas located far away from fishmeal plants.

This paper reports the novel design of a touch mode capacitive pressure sensor (TMCPS) system with a wireless approach for a full-range continuous monitoring of ventricular pressure. The system consists of two modules: an implantable set and an external reading device. The implantable set, restricted to a 2x2 cm² area, consists of a TMCPS array connected with a dual-layer coil, for making a reliable resonant circuit for communication with the external device. The capacitive array is modelled considering the small deflection regime for achieving a dynamic and full 5-300 mmHg pressure range. In this design, the two inductive-coupled modules are calculated considering proper electromagnetic alignment, based on two planar coils and considering the following: 13.56 MHz frequency to avoid tissue damage and three types of biological tissue as core (skin, fat and muscle). The system was validated with the Comsol Multiphysics and CoventorWare softwares; showing a 90% power transmission efficiency at a 3.5 cm distance between coils. The implantable module includes aluminum- and polyimide-based devices, which allows ergonomic, robust, reproducible, and technologically feasible integrated sensors. In addition, the module shows a simplified and low cost design approach based on PolyMEMS INAOE® technology, featured by low-temperature processing.

Multidrug Artemisin-resistant (ART-R) Plasmodium falciparum (Pf) parasites represent a challenge for malaria elimination worldwide. Molecular monitoring in the Kelch domain region (pfk13) gene allows tracking mutations in parasite resistance to artemisinin. The increase of illegal miners in Roraima Yanomami indigenous land (IYL) could favor ART-R parasites. Thus, the study aimed to investigate ART-R in patients from illegal gold mining in the YIL of Roraima, Brazil. A questionnaire was applied and blood was collected from 48 patients diagnosed with P. falciparum or mixed malaria (Pf +P. vivax). The DNA was extracted and the pfk13 gene was amplified by PCR. The amplicons were subjected to DNA Sangers sequenced; the entire amplified fragment was analyzed. Among patients, 96% (46) were from illegal mining areas of the YIL. All parasite samples carried the wild-type genotypes / ART-sensitive phenotypes. These data reinforce the continued use of ACTs in Roraima as well as the maintenance of systematic monitoring for early detection of parasite populations resistant to ART, mainly in areas exposed to the individual’s influx from mining areas, such as the YIL. This is especially true when the achievement of falciparum malaria elimination in Brazil is planned and expected by 2030.

This work presents the development and implementation of a distributed navigation system based on computer vision. The autonomous system consists of a wheeled mobile robot with an integrated colour camera. The robot navigates through a laboratory scenario where the track and several traffic signals must be detected and recognized by using the images acquired with its on-board camera. The images are sent to a computer server that processes them and calculates the corresponding speeds of the robot using a cascade of trained classifiers. These speeds are sent back to the robot, which acts to carry out the corresponding manoeuvre. The classifier cascade should be trained before experimentation with two sets of positive and negative images. The number of images in these sets should be considered to limit the training stage time and avoid overtraining the system.

Additive Manufacturing (AM) has been proving suitable to support or even replace traditional manufacturing in several industries, offering many advantages such as delivery time and reduction in terms of material waste, energy consumption and greenhouse gas (GHG) emissions. This study aimed to carry out a comparative assessment of the life cycle, from gate to gate, in the production of a low alloy carbon steel flange part using ER-90 wire. The methods utilized were Wire and Arc Additive Manufacturing (WAAM) and conventional manufacturing (CM) by forging, and comparative factors were energy demands, GHG emissions and generated solid waste. The total energy consumption in WAAM was 10,239.40 MJ, total carbon footprint in CO2 equivalent (CO2e) was 714.1 kgCO2e kg-1, and generated solid waste was 68.6 kg, respectively, 90%, 95% and 76% lower than consumption calculated in conventional manufacturing.

This study was conducted to search for green technology that can extract metabolites from neem leaves for use in the development of botanical pesticide against Bactrocera dorsalis (Hendel) (Diptera:Tephritidae). Rice wine, rice wash, vinegar and distilled water were used as solvents and hot infusion, maceration, hot continuous reflux (Soxhlet), and fermentation were the methods employed. The different leaf extracts prepared by green technology were evaluated for their potentials as pesticide against B. dorsalis. Vinegar extract via Soxhlet extraction (V-S) for eight (8) h registered to have the highest mortality but not significantly different from vinegar - fermentation (V-F), rice wash - Soxhlet (RWa-S), vinegar - maceration (V-M), distilled water - fermentation (DW-F), and rice wash - fermentation (RWa-F) extracts. Phythochemicals present in the extracts are affected by the solvent-extraction interaction. Among the sixteen solvent-extraction interactions, the use of rice wash and fermentation is the most economical method in extracting the extracting the active components of neem leaves against B. dorsalis. Rice wash is a waste that can be utilized in the development of a biopesticide from neem leaves for pest management of B. dorsalis. This is the first report that rice wash is used as extracting solvent in green synthesis.

Global climate change has induced a rise in sea surface temperature (SST), although this increase is not uniform across the world. Significant variations exist between coastal and offshore waters, particularly in regions affected by upwelling processes. This study focuses on the Canary Current Upwelling System (CCUS), stretching from Northwest Iberia to Northwest Africa. High-resolution remotely sensed SST data (0.05°) from the ODYSSEA Level 4 Sea Surface Temperature Reprocessed dataset were validated with in-situ measurements and employed to establish a regional climatological baseline for 1982 – 2012. Subsequent years were compared to this baseline to construct SST anomaly maps, revealing SST changes since 2012. The study area was further divided into sub-regions for comparative analysis. Results indicate that SST consistently increased at a higher rate offshore compared to the adjacent nearshore regions. A reference dataset spanning 1951 – 1981 was used to gauge SST variability between the two baselines. SST exhibited a 0.59°C increase from 1951 – 1981 to 1982 – 2012, with a slowing of SST trends beyond the 1982 – 2012 baseline. This research offers valuable insights into the climatological dynamics of the CCUS. These findings enhance our understanding of this critical coastal system's climatology, laying the groundwork for future investigations into evolving climate patterns in coastal regions.

Coffee berry borer (CBB), Hypothenemus hampei (Ferrari) (Coleoptera: Curculionidae: Scolytinae), is the pest that causes the most economic damage to coffee crops. Chemical control of this insect is based on the use of insecticides that can affect the environment and nontarget organisms. Despite the fact that caffeine has shown potential as an insecticide, a caffeine-based product for field use is currently not available on the market. As a new alternative to control CBB and other coffee pests, such as Monalonion velezangeli, a caffeine-oleate was developed. The caffeine oleate formulation showed laboratory efficacy by causing mortality of more than 90% of CBB adults in preventive tests in which the insecticide was sprayed prior to insect attack on the coffee fruits. In the curative tests, in which spraying occurred after CBB infested the fruits, the formulation caused 77% mortality of the insects. Under controlled field conditions, the product kept CBB infestation below 20%, reducing the number of fruits attacked by the insect by up to 70%. In addition, no phytotoxic effects were observed in coffee plants. The insecticide was also effective against M. velezangeli causing 100% mortality. A caffeine oleate formulation that could be part of a strategy for integrated CBB management as well as other pests of coffee was developed. The components of the insecticide are food grade; the product would provide greater security to the coffee ecosystem and coffee growers.

This paper reviews the appearance of joint lesions during arthroscopic surgery of inter-est to the arthroscopic surgeon and their interpretation within the continuum of joint disease. It also points out the relevance of surgical findings as well as giving directions to the surgeon as to how to approach an appropriate decision-making process during an arthroscopic procedure and what therapeutic options are optimal.

Urban mobility is experiencing a profound change. On the one hand, mobility patterns are becoming more complex, and typical home-work-home travel is no longer the rule, as journeys now tend to connect multiple points in a rather inconstant pattern. This has changed the approach to transport planning, in that the existing transportation planning and operation approaches have been focussed on the ability to identify typical home-work/school-home travel and subsequently plan the transport system accordingly. The traditional approach has been: forecast -> plan -> deliver, as new mobility solutions are emerging. These are characterised by greater flexibility, in that they take advantage of the “sharing concept” and simultaneously provide solutions that have lower GHG emissions. Urban mobility follows a fuzzier pattern, with even the urban transportation system behaving like an active organism, where solutions are often quickly replaced. This dynamic and evolving environment raises several new challenges at different levels. The best digital solution system is the Mobility-as-a-Service (MaaS) one. This system transforms the physical transportation system into a commodity and takes advantage of the internet of things (IoT). However, the onset of MaaS solutions is anything but linear. Several business models have emerged, with different partners originating from different industries (e.g., technological, transport operators, infrastructure managers, etc.) developing their own solutions, often in competition with others. It is not unusual to find different MaaS solutions in the same city, which integrate different solutions.

The spatial and temporal changes in social vulnerability to natural hazards in Mexico are analyzed. To this end, using census data from 2000, 2010, and 2020 and a statistical method, different indices were computed, and with a GIS-based approach, patterns of social vulnerability are examined. In addition, a risk assessment test for severe weather (thunderstorms, hailstorms, and tornadoes) is made out. The results show different common social vulnerability driving factors in the three analyzed years, with root causes that have not been addressed since the beginning of the century. Likewise, a wider gap between Mexico's most and least vulnerable populations is identified. The changes in spatial patterns respond to different historical situations, such as migration, urbanization, and increased population. Also, poverty, ethnicity, and marginalization factors located in very particular regions in Mexico have remained relatively the same in the last few years. These situations have strongly influenced the spatial-temporal distribution of vulnerability in the country. The role of social vulnerability in the disaster risk to extreme events such as thunderstorms, hailstorms, and tornadoes in Mexico is fundamental to understanding changes in disaster distribution at the national level, and it is the first step to generating improvements in integrated risk management.

In this work, the structural, magnetic, and mechanical properties of Nd16Fe76-xCoxB8 alloys varying the Co content at x = 0, 10, 20 and 25, were experimentally investigated by X-Ray Diffraction (XRD), Mössbauer Spectrometry (MS), Vibrating Sample Magnetometry (VSM) at room temperature (RT), and microhardness test were performed too. The system presents the hard Nd2Fe14B and the Nd1.1Fe4B4 phases for samples with x = 0 and 10. When concentration increases to x= 20 and 25, the CoO phase appears. All MS show the ferromagnetic behavior (eight sextets: sites 16k1, 16k2, 8j1, 8j2, 4c, 4e, sb) associated to the hard and soft magnetic phases, and one paramagnetic component (doublet: site d) associated to the minority Nd1.1Fe4B4 phase, which was not identified by XRD. All samples are magnetically hard present a hard magnetic behavior. The increase of Co content in these samples did not improve the hard magnetic behavior, but increased the critical temperature of the system and decrease the crystallite size of the hard phase. The hysteresis loop showed that predominates the Nd2Fe14B hard magnetic phase. There is a general tendency to increase microhardness with cobalt content, attributable to cobalt doping reduces the lattice parameters and porosities in the sample improving it hardness.

Effortful control (EC) describes individual differences in self-regulation, with a strong attentional basis. Moreover, during early childhood EC has a central role on children’s socio-emotional adjustment and academic achievement. The aim of the current study was to predict the development of EC at 36 months of age from early attentional and environmental measures taken in infancy using a machine learning approach. A sample of 75 infants participated in a longitudinal study running different waves of data collection at 6, 9 and 36 months of age. Attentional tasks were administered at 6 months of age and two additional measures were collected at 9 months of age. Parents reported household environment variables during wave 1, and their child’s EC at 36 months. A machine -learning algorithm was implemented to identify children with low EC scores at 36 months of age. An “attention only” model showed greater predictive sensitivity than the “environmental only” model. However, a model including both attentional and environmental variables was able to classify the groups (Low-EC vs Average-to-High EC) with 100% accuracy. Sensitivity analyses indicate that socio-economic variables together with attention control processes at 6-months, and self-restraint capacity at 9-months, are the most important predictors of EC. Results suggest a foundational role of executive attention processes in the development of EC in complex interaction with household environment and provide a new tool to identify early markers of socio-emotional regulation development.

Currently, in a context of biorefinery and bioeconomy, lignocellulosic biomass is increasingly used to produce biofuels, biochemicals and value-added products. Microwaves and ultrasounds are emerging techniques that enable efficient and environmentally more sustainable routes in the transformation of lignocellulosic biomass. This review is divided into four parts. In Part I, the theoretical foundations of microwaves and ultrasounds are revisited. Dielectric constants for biomass, factors that influence pre-treatment, are some of the subjects addressed. In Part II, the effects that these technologies have on lignocellulosic biomass (on the size and surface area of the particle; on the content of lignin, hemicellulose and cellulose; on the crystallinity index of cellulose; on the effect of solubilization of organic matter; on hydrolysis and reduction of sugars) are analyzed. In Part III, emphasis is given on how microwaves and ultrasounds can contribute to the achievement of value-added products. In this context, several examples of liquefactions and extractions are presented. Part IV describes examples of sonocatalysis of lignocellulosic biomass to obtain value-added products such as for instancethe production of furfural, which is significantly reduced by ultrasound.

Continuous glucose monitoring devices allow diabetes condition management. However, when limited data is available, one option is to increase their size by generating synthetic samples. From a homemade wearable prototype was created a real dataset with 18 instances and 53 attributes that capture characteristics of capillary and venous blood glucose, oxygen concentration, pulse rate, skin temperature, and 24 modules and 24 phases related to bio-impedance. The objective of this article is to generate synthetic datasets, and also it investigates the ideal features subset and optimal model for non-invasive diabetes prediction. Gaussian-Copulas (GC), conditional generative adversarial networks (CG), variational autoencoders, and Copula-GAN techniques' were used to generate five synthetic datasets. Experiments show that GC1 and GC2 datasets follow min/max boundaries and are not copies of the original data. Multilayer perceptron regressor outperformed (train and test) with 2.17, 2.51 in MAE; 9.29, 13.59 in MSE; 3.05, 3.69 in RMSE, and 0.95, 0.92 in R2 in GC1, and 2.64, 3.02 in MAE; 11.43, 15.11 in MSE; 3.38, 3.89 in RMSE, and 0.94, 0.92 in R2 in GC2 with eight features. Future work is necessary to explore autoencoder and generative architectures, datasets with diverse characteristics, and the effect of the number of features.

Chronic non-communicable diseases (NCDs) are major public health problems and a significant financial burden on public health systems. By 2030, mortality due to NCDs, such as cardiovascular diseases, cancer, respiratory diseases, and diabetes, is predicted to increase in Brazil. A peculiar aspect of NCDs involves their long-term and integrated care management. This paper proposes a chronic disease management platform based on artificial intelligence to deliver digital health services everywhere. The proposed platform is anchored and built with healthcare 4.0 technologies, such as wearable devices, the internet of medical things, and artificial intelligence cloud-based solutions that allow the deployment of a smart healthcare system. In addition, the paper presents the feasibility of the platform in a diabetes prediction study case. For the study case, an initial dataset was established with bio-impedance, oxygen concentration, pulse rate, skin impedance, and skin temperature attributes. A baseline was implemented with ten regression models to assess the prediction performance of the mean squared error, root mean squared error, and r-squared score to compare predictive findings with capillary blood glucose measurements. Results evidence that the decision tree regressor and three ensemble methods (bagging decision tree regressor, random forest regressor, and AdaBoost regressor) yielded improvement over the other models. Moreover, a comparison among those models revealed that the decision tree regressor outperforms them and presents promissory outcomes.

With the arrival of SARS-CoV-2 vaccines, a new stage of the pandemic commenced, with new challenges ahead. During the coming months, countries will be implementing their COVID-19 vaccination programs depending on their implementation of vaccine availability and its prescription on risk stratification. Although children will not benefit from active immunization programs, now, with the beginning of the era of the anti-COVID19 vaccines, the suffering of children can no longer be ethically tolerated or neglected. The time has come to provide specific lasting strategies for children living in the COVID-19 era. Here we propose a child-focused indirect COVID-19 vaccination strategy.For better or worse, children depend on their natural caregivers (adults) and the rest of society for their well-being and achieving their full potential. We believe that including in the priority categories also those adults in close contact with children could ensure a safety net of child protection.A child-focused vaccination strategy would allow the faster return to "normality" for children and their families. Such an approach would not only enable the reopening and continuity of essential services for children but also would allow adults to return to their routine economic/productive activities.

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

Introduction: Determination of radiological bone age (BA) is a diagnostic method that consists of estimating chronological age (CA) from the bone maturation of children. Although environmental and hormonal factors can interfere with bone ossification, the process is essentially dependent on ancestral inheritance. These ethnic backgrounds are not usually considered, which can lead to biased interpretations and inadequate decision-making by pediatricians or forensic experts. The objective of this study was to determine the precision and accuracy of these radiological procedures among different ethnic groups. Methods: A qualitative systematic review carried out following MOOSE statement and previously registered in the International Prospective Registry of Systematic Reviews PROSPERO (CRD42023449512). Search was performed in MEDLINE (PubMed) (n=561), Cochrane Library (n=261), CINAHL (n=103), Web of Science (WOS) (n=181) and public institutional repositories (n=37) from inception to 31st December 2022 using Mesh as “Diagnostic Techniques and Procedures”, “Diagnostic imaging”, “Radiography”, “Age Determination by Skeleton” and free terms combining with booleans “AND” and “OR”. PEDro scale, and Risk of Bias in non-randomized Studies of Exposure (ROBINS-E) were used to assess methodological quality and risk of bias of included studies respectively. Results: 51 articles (n=19,531) were included according to the inclusion criteria previously established. There was a good to moderate methodological quality and a high to very high risk of bias. Skeletal methods for determining BA were precised in terms of intra-observer and inter-observer reliability in all ethnic groups. Regarding to accuracy of Skeletal methods in Caucasians and Hispanic children, GPA was accurate at all ages, but in youths, TW3 RUS could be a consistent alternative. In Asian and Arab, GPA and TW3 overestimated BA in adolescents near adulthood. In African youths, GPA overestimated BA while TW3 was more accurate in estimating CA. Dental and Cervical radiographic methods are equally precise but lesser accurate than Skeletal BA determination. Conclusion: Skeletal radiographic methods GPA and TW3 are both precise for BA determination among all ethnical groups, but their accuracy in estimating CA can be altered by racial bias.

The research explores the impact of financial indicators on the credit ratings of companies listed on the S&P 500, employing a Sys-GMM Model to address endogeneity concerns. The study investigated three independent variables categorized as market and survival factors alongside with seven control variables sourced from leverage, liquidity, interest coverage, profitability, market, survival, and macroeconomic domains. The sample comprised 2398 observations from Capital IQ Pro, spanning nine years (2013 to 2021) and encompassing 240 public companies. The findings suggest that neither Tobin's Q (TQ) and Total Shareholder Return (TSR) lack significant correlations with credit ratings, implying that stock market performance and total shareholder return do not directly impact credit ratings. In contrast, the Altman Z-score (AZS) emerged as a significant predictor, indicating its importance in assessing credit risk. These insights enhance understanding of financial indicators' impact on credit ratings, aiding financial institutions and companies in prudent lending and financing decisions.

⦁ Introduction: The challenging context, resulting from a post-pandemic scenario, wars, and various natural disasters, does not allow for the ideal assurance of efficiency in the Agri-food supply chain. ⦁ Research significance Currently, Agri-food supply chains and Reverse logistics show critical characteristics such as centralization, limited flexibility, distrust, bureaucratization, Border and Documentary Compliance and there are problems about efficiency, security, and safety Agri-Food. using the Supply Chain Operations Reference (SCOR) framework, with the purpose of achieving Sustainable Development Goals, promoting transparency, traceability, and non-linearization of the agri-food supply chain. ⦁ Methodology The methodology is combined, the first part uses Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) identifying 72 articles with the principal contribution in the literature. The second part combines the application of Supply Chain Operations References (SCOR) and the Blockchain Technology aiming to decentralize the linear Agri-food Supply Chain and Reverse logistics. ⦁ Results/findings The results revealed a transformation of the traditional Agri-food Supply Chain, transitioning from linear management to a circular one. Additionally, after application it is possible to know a new way to manage the Reverse Logistic with more decentralization, flexibility, traceability, and reducing the unnecessary activities, which include Border and Documentary Compliance. The originality of this research is the novel combination of SCOR Model and Blockchain showing a priority about the key activities that add value and come close to the Sustainable practices. ⦁ Conclusion / Implications Based on the results is possible to conclude that the synergy between Blockchain and SCOR Model enables a new way to manage the Agri-food supply chain, improving efficiency and reducing activities without value. Also, it is possible to ensure that the practices of Reverse Logistics are improved based on terms of cost and time, and the reduction of the exposition on the Defective Product Risk. ⦁ Social Implications This paper could enhance confidence in all operations of the Agri-food supply chain as there are numerous issues regarding the security and safety of food. Additionally, it will aid in diminishing unnecessary activities and inefficient resource consumption practices, thereby accomplishing objectives 2 "zero hunger", 9 "Industry, Innovation, and Infrastructure", and 12 "Responsible consumption and production", along with their respective indicators. ⦁ Practical implications Regarding the practical implications, this research could contribute to analyses of the application of technology Blockchain in different sectors and identify the possible limitations when the main objective is to apply it on a big scale.

Development of non-conventional hybrids (NCHs) responds to the demand for the Elotes Occidentales 'EO' race for production of pozole. The effect of: crop cycle (2019, 2020 and 2021) on physical characteristics, flowered grain quality and phytochemical content of two HNC (Pz1 and Pz2) of pozolero maize, as well as the effect of the presence or absence of pedicel, type of pollination (open and controlled, 2019), and progenitor lines (female and male, 2020) on flowered grain quality and content of phytochemical compounds were evaluated. Size, hardness, color, total phenols and anthocyanins in unprocessed grain were determined, and yield, volume and puncture strength in flowered grain. Results were analyzed with a factorial arrangement in a completely randomized design. There were significant differences (p≤0.05) in most of the variables studied by effect of crop cycle and genotype. NCHs had large grains (40 g 100 grains-1), soft endosperm (IF> 60), pink-purple color, and phenol and anthocyanin contents similar to those reported for the 'EO' race. The presence or absence of the pedicel did not affect flowered grain quality. Controlled pollination favored anthocyanin synthesis. The anthocyanin content of NCHs was determined by the female line. Thermal processing reduced anthocyanins by 60%; however, they leached into the flowering broth, so that the pozole made from NCHs improves the nutraceutical value of the pozole, relative to that of pozole made with Cacahuacintle maize.

This article presents a methodology for the design of rehabilitation devices that considers factors involved in a clinical environment. This methodology integrates different disciplines that work together. The methodology is composed by 3 phases and 13 stages with specific tasks, the first phase includes the clinical context considering the requirements of the patient and therapist during the rehabilitation, the second phase is focused in engineering based on the philosophy of digital twin, and in the third phase is evaluated the device. This article explains the characteristics of the methodology and how it was applied in the design of an exoskeleton for passive rehabilitation of the upper limb.

NSD3 is a member of the NSD histone methyltransferase family of proteins. In recent years, it has been identified as a potential oncogene in certain types of cancer. NSD3 gene encodes three isoforms, the full length, a short (NSD3S) and WHISTLE isoforms. Importantly, NSD3S isoform corresponds to the N-terminal of the full-length protein, lacking the methyltransferase domain. The chromosomal location of NSD3 is frequently amplified across cancer types, such as breast, lung, colon, among others. Recently, this amplification has been correlated to a chromothripsis event, that could explain the different NSD3 alterations found in cancer. Fusion proteins containing NSD3 have also been reported, such as leukemia NSD3-NUP98, and in NUT midline carcinoma (NMC), NSD3-NUT fusion. Its role as an oncogene has been described by modulating different cancer pathways through its methyltransferase activity, or the short isoform of the protein, through protein interactions. Specifically, in this review we will focus on stating the functions that have been characterized as methyltransferase dependent, and those that have been correlated with the expression of the NSD3S isoform. Altogether, there is evidence that both isoforms of NSD3 are relevant for cancer progression, establishing NSD3 as a therapeutic target. However, further functional studies are needed to differentiate NSD3 oncogenic activity as dependent or independent of the catalytic domain of the protein, as well as the contribution of each isoform and its clinical significance in cancer progression.

This study delves into the complex interplay among attachment styles, hypersexuality, and sexual and couple satisfaction in emerging adults within the Mexican population. Despite established correlations between anxious and avoidant attachment styles and emotion dysregulation and hypersexuality, the roles of sexual and couple satisfaction in this context have remained relatively unexplored. This study aims to fill this gap by examining how these variables interact and contribute to psychological distress and sexual risk behaviors. Data analysis on 214 emerging adults, utilizing the Experiences in Close Relationships scale, Couple Satisfaction Index, Sexual Satisfaction Scale, SCL-90, and SAST-R, revealed a significant association between risky sexual behaviors—such as a higher number of sexual partners, drug and alcohol use during sexual activity, and lack of sexual protection—and heightened levels of hypersexuality. Notably, individuals with hypersexual tendencies reported diminished levels of sexual satisfaction but elevated levels of couple satisfaction. Avoidant attachment emerged as the attachment style most strongly correlated with early sexual experiences. Moreover, the abbreviated versions of the Couple Satisfaction Index (CSI-4) and the Experiences in Close Relationships scale (ECR-8) exhibited commendable psychometric properties, enhancing their applicability for research and clinical purposes. This research furnishes valuable insights into the complex dynamics among attachment styles, hypersexuality, and couple and sexual satisfaction, emphasizing the need for targeted interventions to foster healthier sexual and relationship behaviors among emerging adults.

Aedes aegypti and Aedes albopictus are responsible for transmitting major human arboviruses such as dengue, Zika, and Chikungunya, posing a global threat to public health. The lack of etio-logical treatments and efficient vaccines makes vector control strategies essential for reducing vector population density and interrupting pathogen transmission cycle. This study evaluated the impact of long-term pyriproxyfen exposure on the genetic structure and diversity of Ae. aegypti and Ae. albopictus mosquito populations. The study was conducted in Manaus, Amazonas, Bra-zil, where pyriproxyfen dissemination stations have been monitored since 2014 up to the present day. Double digest restriction-site associated DNA sequencing was performed, revealing that despite significant local population reductions, focal pyriproxyfen interventions have no signifi-cant impact on the population stratification of Ae. aegypti and Ae. albopictus in urban scenarios. The genetic structuring level of Ae. aegypti suggests it is more stratified and directly affected by PPF intervention, while for Ae. albopictus exhibits a more homogeneous and less structured popu-lation. The results suggest that although slight differences are observed among mosquitoes sub-populations, intervention focused on neighborhoods in a capital city is not efficient in terms of genetic structuring, indicating that larger-scale pyriproxyfen interventions should be considered for more effective urban mosquito control.

For the majority of the contractual arrangements used in construction projects, the owner is not responsible for the cost deviations due to the variability of labor productivity or material price, amongst many other aspects. Consequently, the cost performance of a project may be entirely distinct for the owner and the contractor. Since the majority of the quantitative research on cost estimation and deviation found in the literature adopts the owners’ perspective, this research provides a contribution towards modelling costs and cost deviation from a contractors’ perspective. From an initial sample of 13 residential building and 10 office building projects, it was possible to develop models for cost estimation at the early stage of development including both endogenous and exogenous variables. Although the sample is relatively small, the authors were able to fully analyze all the cost data, using no secondary sources of data (very frequent in cost modelling studies). The statistically significant variables in the cost estimation models were the areas above and below ground and the years following the 2008 financial crisis, including the international bailout (2011-2014) period. For estimating the unit cost, a nonlinear model was obtained with the number of underground and total floor, the floor ratio and the years following the 2008 financial crisis, including the international bailout (2011-2014) period as predictors. For the office buildings, it was also found a statistically significant correlation between the cost deviation and the number of underground floors.

Life Cycle Assessment (LCA) is a technique developed to measure possible environmental impacts during the manufacture and use of a given product or service. Additive Manufacturing (AM) has proven to be suitable in several industries, especially wire and arc additive manufacturing (WAAM), offering many advantages such as delivery time and reduction in terms of material waste, energy consumption and equivalent CO₂ emissions (CO₂e). This study aimed to develop a methodology to evaluate environmental indicators during the life cycle assessment, from gate-to-gate, in the production of two low-alloy carbon steel metal parts (flanges) using ER-90 wire and allowed identifying the main stages that most influence environmental indicators. The total energy consumption in the production of flanges 1 and 2 were, respectively, 10,239.0 MJ, 12,754.0 MJ and the total carbon footprint, respectively, 714.1 kgCO₂e kg^-1 and 749.3 kgCO₂e kg^-1.

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

We propose a toy model of a spherical universe made up of an exotic dark gas with temperature $T$ in thermal equilibrium with a black-body. Each particle of this exotic gas mimics a kind of particle of dark energy. So, each dark particle occupies a very small area of space so-called Planck area $L_p^{2}$, which represents the minimum area of the whole space-time given by the spherical surface with area $4\pi R_H^2$, where $R_H$ is the Hubble radius. We realize that such spherical surface is the surface of the black-body for representing the dark universe as if it were the surface of an expanding balloon. Thus, we are able to derive the law of universal gravitation, thus leading us to understand the cosmological anti-gravity. We estimate the tiny order of magnitude of the cosmological constant and the acceleration of expansion of the dark sphere. In this toy model, as the dark universe can be thought of as a large black body, when we obtain its power and frequency of emission of radiation, we find very low values. We conclude that such radiation and frequency of the black body made up of dark energy is a background gravitational wave with very low frequency in the order of $\sim 10^{-17}$Hz due to the slight stretching of the fabric of space-time.

Glioblastoma multiforme (GBM) is the most frequent and aggressive primary brain tumor. GBM is formed by a very heterogeneous astrocyte population, neurons, neovascularization and infiltrating myeloid cells (microglia and monocyte derived macrophages). The IQGAP1 scaffold protein interacts with components of the cytoskeleton, cell adhesion molecules, and several signaling molecules to regulate cell morphology and motility, cell cycle and other cellular functions. IQGAP1 overexpression and delocalization has been observed in several tumors, suggesting a role for this protein in cell proliferation, transformation and invasion. IQGAP1 has been identified as a marker of amplifying cancer cells in GBMs. To determine the involvement of IQGAP1 in the onco-biology of GBM, we performed immunohistochemical confocal microscopic analysis of the IQGAP1 protein in human GBM tissue samples using cell type-specific markers. IQGAP1 immunostaining and subcellular localization was heterogeneous; the protein was located in the plasma membrane and, at variable levels, in nucleus and/or cytosol. Moreover, IQGAP1 positive staining was found in podosome/invadopodia-like structures. IQGAP1⁺ staining was observed in neurons (Map2⁺ cells), in cancer stem cells (CSC; nestin⁺) and in several macrophages (CD31⁺ or Iba1⁺). Our results indicate that the IQGAP1 protein is involved in normal cell physiology as well as oncologic processes.

Prosthechea karwinskii is an orchid endemic to Mexico, threatened by the destruction of its habitat and the extraction of specimens to meet its demand for ornamental and religious use. Most of its populations, and the most locally abundant ones, are found in Oaxaca state. Variations in some floral traits have been observed in these populations. We implemented a morphometric analysis to assess their floral variation and identify the most significant characters in the morphological patterns of this orchid. Floral samples were collected from 17 populations of P. karwinskii in Oaxaca, as well as from specimens used as ornaments during Easter in a Oaxacan community (Zaachila), whose origin is unknown. Sampling of natural populations covered the environmental, geographic and morphological variation of the species. We performed an analysis of variance (ANOVA), principal component analysis (PCA), and canonical variate analysis (CVA), and cluster analysis including 185 individuals and 45 variables (13 of them were discarded in the multivariate analyzes due to high correlation). Characters of the column, lateral sepal, and labellum were most informative about the observed morphological patterns. Albarradas showed the greatest morphological differentiation, mainly due to the column. In general, individuals from the same locality tended to overlap more, especially the populations of Jaltianguis and Yahuiche, which were different from the geographically close population of Etla. Teposcolula presented the highest values in perianth characters, unlike Sola_Rancho Viejo. The specimens recovered from religious ornaments were morphologically more similar to those from the Mixtec region and surroundings of Etla. Our work encourages working on collaborative conservation strategies to ensure the long-term permanence of both the species and its traditional uses.

A substantial body of phenomenological and theoretical work over the last few years strengthens the possibility that the vacuum energy density (VED) of the universe is dynamical, and in particular that it adopts the `running vacuum model' (RVM) form, in which the VED evolves mildly as $\delta \rho_{\rm vac}(H)\sim \nu_{\rm eff} m_{\rm Pl}^2{\cal O}\left(H^2\right)$, where $H$ is the Hubble rate and $\nu_{\rm eff}$ is a (small) free parameter. This dynamical scenario is grounded on recent studies of quantum field theory (QFT) in curved spacetime and also on string theory. It turns out that what we call the `cosmological constant', $\Lambda$, is no longer a rigid parameter but the nearly sustained value of $8\pi G(H)\rho_{\rm vac}(H)$ around (any) given epoch $H(t)$, where $G(H)$ is the gravitational coupling, which can also be very mildly running (logarithmically). Of particular interest is the possibility suggested in past works that such a running may help to cure the cosmological tensions afflicting the $\Lambda$CDM. In the current study, we reanalyze it in full and we find it becomes further buttressed. Using the modern cosmological data, namely a compilation of the latest SNIa+BAO+$H(z)$+LSS+CMB observations, we probe to which extent the RVM provides a quality fit better than the concordance $\Lambda$CDM model, paying particular emphasis on its impact on the $\sigma_8$ and $H_0$ tensions. We utilize the Einstein-Boltzmann system solver \texttt{CLASS} and the Monte Carlo sampler \texttt{MontePython} for the statistical analysis, as well as the statistical DIC criterion to compare the running vacuum against the rigid vacuum ($\nu_{\rm eff} = 0$). On fundamental grounds, $\nu_{\rm eff}$ receives contributions from all the quantized matter fields in FLRW spacetime. We show that with a tiny amount of vacuum dynamics ($|\nu_{\rm eff}|\ll 1$) the global fit can improve significantly with respect to the $\CC$CDM and the mentioned tensions may subside to inconspicuous levels.

Background: Strong nursing faculty is paramount to promote disciplinary leadership and to prepare future nurses for practice. Our understanding of the factors associated with or predictive of nurse faculty retention and/or turnover is lacking. Purpose: The aim of this review is to identify and synthesize the existing literature on factors contributing to nurse faculty shortage in Canada and implications on nursing practice. Methods: A scoping review based on the Arskey and O’Malley’s five stage framework for scoping reviews was undertaken. Utilising the PRISMA protocol, a comprehensive and structured literature search was conducted in five databases of studies published in English.Findings: Limited through search inclusion and relevance of research, nine studies out of 220 papers met the criteria for this review and were thematically analyzed. Identified themes were: supply versus demand; employment conditions; organizational support; and personal factors.Discussion: Impending retirement of faculty, unsupportive leadership, and stressful work environments were frequently reported as significant contributing factors to the faculty shortage.Conclusions: This scoping review provide insights into how Canada’s schools of nursing could engage in grounded efforts to lessen nursing faculty shortage, both nationally and globally. We identified a gap in the literature that indicates that foundational work is needed to create context-specific solutions. The limited studies published in Canada suggests that this is a critical area for future research and funding.

Wearable Biosensor Technology (WBT) has emerged as a transformative tool in the educational system over the past decade. This systematic review encompasses a comprehensive analysis of WBT utilization in educational settings over a 10-year span (2012-2022), highlighting both the evolution of this field and its integration to address challenges in education by integrating technology to solve specific educational challenges, such as enhancing student engagement, monitoring stress and cognitive load, improving learning experiences, and providing real-time feedback for both students and educators. By exploring these aspects, the review sheds light on the potential implications of WBT for the future of learning. A rigorous and systematic search of major academic databases, including Google Scholar and Scopus, was conducted in accordance with PRISMA guidelines. Relevant studies were selected based on predefined inclusion and exclusion criteria. The articles selected were assessed for methodological quality and bias using established tools. The process of data extraction and synthesis followed a structured framework. Key findings include the shift from theoretical exploration to practical implementation with the EEG being the predominant measurement, aiming to explore mental states, physiological constructs, and teaching effectiveness. Wearable biosensors are significantly impacting the educational field, serving as an important resource for educators and a tool for students. Their application has the potential to transform and optimize academic practices through sensors that capture biometric data, enabling the implementation of metrics and models to understand the development and performance of students and professors in an academic environment, as well as to gain insights into the learning process.

The global warming our generation is experiencing is just one of the great environmental crises of the Anthropocene, a geological period that began with the use of fossil fuels and that, in merely one century and a few decades of industrial activity, has altered ecosystemic processes that sustain human health and well-being. Beyond the loss of the “intrinsic value of nature”, changes in the magnitude and direction of biogeochemical cycles and increases in temperature are phenomena that not only accompany the loss of habitats and species but impair resilience by ultimately generating greater and more complex numbers and types of exposures that constitute a danger to human health. In this study, we attempted to offer some notes about the margin, understood as that space with the greatest inequity and therefore the fastest growth of risk: the collision area where deprivation marks the social determinants of health and where the greatest interaction with causes of disease occur.

A major goal of neuroscience is understanding how neurons arrange themselves into neural networks that result in behavior. Most theoretical and experimental efforts have focused on a top-down approach which seeks to identify neuronal correlates of behaviors. This has been accomplished by effectively mapping specific behaviors to distinct neural patterns, or by creating computational models that produce a desired behavioral outcome. Nonetheless, these approaches have only implicitly considered the fact that neural tissue, like any other physical system, is subjected to several restrictions and boundaries of operations.Here, we propose a new, bottom-up conceptual paradigm: The Energy Homeostasis Principle, where the balance between energy income, expenditure, and availability are the key parameters in determining the dynamics of the found neuronal phenomena from molecular to behavioral levels. Neurons display high energy consumption relative to other cells, with metabolic consumption of the brain representing 20% of the whole-body oxygen uptake, contrasting with this organ representing only 2% of the body weight. Also, neurons have specialized surrounding tissue providing the necessary energy which, in the case of the brain, is provided by astrocytes. Moreover, and unlike other cell types with high energy demands such as muscle cells, neurons have strict aerobic metabolism. These facts indicate that neurons are highly sensitive to energy limitations, with Gibb’s free energy dictating the direction of all cellular metabolic processes. From this activity, the largest energy, by far, is expended by action potentials and post-synaptic potentials; therefore, plasticity can be reinterpreted in terms of their energy context. Consequently, neurons, through their synapses, impose energy demands over post-synaptic neurons in a close loop-manner, modulating the dynamics of local circuits. Subsequently, the energy dynamics end up impacting the homeostatic mechanisms of neuronal networks. Furthermore, local energy management also emerges as a neural population property, where most of the energy expenses are triggered by sensory or other modulatory inputs. Local energy management in neurons may be sufficient to explain the emergence of behavior, enabling the assessment of which properties arise in neural circuits and how. Essentially, the proposal of the Energy Homeostasis Principle is also readily testable for simple neuronal networks.

“Minas Frescal” cheese is a high moisture product, subject to the proliferation of several microorganisms. Essential oils are natural antimicrobial alternatives that can increase the quality of dairy products. This study aimed to analyze the antimicrobial action of oregano (Origanum vulgare) and rosemary (Rosmarinus officinalis) essential oils against Escherichia coli and Staphylococcus aureus. An antimicrobial test by diffusion and microdilution was performed to calculate the MIC (Minimum Inhibitory Concentration) and MBC (Minimum Bactericidal Concentration). The behavior of E. coli in “Minas Frescal” cheese added with oregano oil was evaluated. The MIC of oregano oil was 0.25% against E. coli and 1% against S. aureus. For rosemary essential oil, the MIC was 8% of against E. coli. There was no activity of rosemary oil against S. aureus. The MBC observed for oregano essential oil was 1% and 0.25% respectively for S. aureus and E. coli. Bacterial analysis during cheese storage with E. coli indicated inhibition of microorganisms by oregano essential oil at a concentration of 0.25%. No alterations were observed regards to physical-chemical attributes. The use of essential oil as an antimicrobial agent has potential for industrial use, and type of microorganism, oil and sensory reflexes in the product must be observed.

WHO estimates that around 600 million people suffer from high blood pressure which causes high costs for health systems and influences the economy of these countries. In this study, we investigate the sociodemographic characteristics and risk factors related to hypertension among individuals from Huambo, Angola. This cross-sectional study was conducted with 158 participants consulted in the Cardiology services at Hospital Geral do Huambo, between January and July 2023. A total of 67.1% of the studied patients were hypertensive. The mean age of the hypertensive (55.8±11.3) patients was higher than non-hypertensive (53.1±13.4) patients, although no significance was observed (p=0.199). Patients aged between 30 and 40 (OR=1.19, P=0493), male (OR=1.17, P=660), employees (OR=9.94, P=0935), patients consuming alcohol (OR=1.11, P=0.864), and practising physical activity (OR=1.12, P=0.742) presented a high chance of developing hypertension, while those living in urbanized areas (OR=0.78, P=0.59) and with a low educational level (OR=0.43, P=0.194), had a low chance to develop hypertension. There was no statistical significance between demographic or behavioural characteristics with hypertension (P>0.05). Regarding clinical characteristics, body mass index was statistically related to hypertension (p=0.011). Our findings show that hypertension is a major health problem for the young population of Huambo. There is an urgent need to create strategies to improve the prevention, diagnosis, and treatment of hypertension, not only in Huambo but throughout the country. Further studies to understand determinants related to hypertension should be carried out among the young population in Angola.

This study investigates the implementation and evaluation of a university bot designed to improve communication and management of academic events in educational environments. With the rapid evolution of digital technology, bots have emerged as powerful tools with applications in various sectors such as e-commerce, education, and healthcare. In particular, the use of bots in customer service and event management has demonstrated significant benefits by handling frequent inquiries, providing real-time information and assisting with administrative tasks, freeing up human resources for more strategic functions. This project adopted a mixed methodological approach combining qualitative and quantitative methods to assess usability and user satisfaction with the bot. The Usability Scale System (SUS) and the User Experience Questionnaire (UEQ) were used as standard tools to collect data on user perception. The results highlighted a high acceptance of the bot, with an acceptance rate of 90\%, indicating high user interest in using the application. This high acceptance underscores the bot's ability to effectively present the information users are looking for. The bot provides a list of academic events categorized by type, making it easy to find and manage information about grants, conferences, courses and other events. Its design focuses on a friendly and accessible interface that allows direct consultation without the need for conversational interaction. This project contributes to operational optimization in educational environments by providing a practical solution for the management of academic events and offers valuable insights on how to efficiently present information in similar applications. These findings are fundamental for future research and development in the creation of information systems in the educational environment.

The interest in obtaining new composite materials with diverse properties has created a growing interest in natural fi-bers as reinforcement in polymers, which has generated an impact in sectors such as automotive and construction, dis-placing synthetic fibers. Properties such as low density, low cost, and rene.wable make these fibers an attractive alterna-tive to reduce environmental impact. Their application in polymers, such as polypropylene, polyethylene, and epoxy resins, has allowed the modification of polymeric composite materials' mechanical and physical properties (NFRP). This review focuses on investigating the status of natural fiber-reinforced polymers. It analyzes their worldwide demand, chemical characteristics, physical and mechanical properties, and various applications in different sectors and indus-tries. In addition, the advantages and disadvantages of NFRPs are highlighted, highlighting their potential for new ap-plications.

In this research paper we describe the development phase of a low-cost LoRa IoT solution applied to a kindergarten school with three years results. A set of sensors solution was developed in a LoRa communication board, battery powered, providing a simplified setup process. These sensors were used in order to measure temperature, humidity, luminosity, air quality and presence. Also, energy monitor solutions were integrated. The acquired data is transmitted and analysed for knowledge extraction, identifying savings and other related KPIs. From data, automatic saving actions were performed towards heating and cooling systems, lighting and a set of if-then actions were developed for automatic cost-saving actions, based on infrared signals to heating/cooling systems using some procedure of external command devices. This approach avoids the usage of proprietary vendor solutions in a flexible approach that can easily be deployed to any building facility. This is an important achievement since most of the building consumption is based on heating and cooling systems. In a three years test of the solution, the total energy consumption savings surpassed 20%

Social Business Intelligence (SBI) enables companies to capture strategic information from public social networks. Contrary to traditional Business Intelligence (BI), SBI has to face the high dynamicity of both the social network contents and the company analytical requests, as well as the enormous amount of noisy data. Effective exploitation of these continuous sources of data requires efficient processing of the streamed data to be semantically shaped into insightful facts. In this paper, we propose a multidimensional formalism to represent and evaluate social indicators directly from fact streams derived in turn from social network data. This formalism relies on two main aspects: the semantic representation of facts via Linked Open Data and the support of OLAP-like multidimensional analysis models. Contrary to traditional BI formalisms, we start the process by modeling the required social indicators according to the strategic goals of the company. From these specifications, all the required fact streams are modeled and deployed to trace the indicators. The main advantages of this approach are the easy definition of on-demand social indicators, and the treatment of changing dimensions and metrics through streamed facts. We demonstrate its usefulness by introducing a real scenario user case in the automotive sector.

This study evaluated the microbiological quality of farm oysters, cultivated in an estuary in northeastern Pará, Brazil, before and after purification process. Water and oyster samples were collected in June, August, October, and December 2019. Oysters underwent purification for up to 36 h in a small-scale adapted debugger. Microbiological analyses were performed in oysters and water depuration collected at different times of purification (0 h pre-treatment, 6 h, 12 h, 2 4h, and 36 h), using the multiple tube technique, to determine the most probable number (MPN) of Escherichia coli, thermotolerant coliforms - TTC, and total coliforms - TC. Bacterial isolation was used to determine the presence of Salmonella spp. Before purification, oysters had E. coli counts above the limit allowed by Brazilian legislation (≤ 230 MPN/100g). High TTC, and TC counts were observed in all the months of the study, and Salmonella spp. was present in August. All water samples were contaminated by TTC beyond the level allowed (> 43 MPN/100mL) in two months. The purification process of 36 h was effective in reducing the load of E. coli, TTC, and TC and eliminating Salmonella spp. in oysters.

Industry 4.0 (I4.0) epitomizes the nexus of technological evolution and manufacturing process enhancements, underpinned by four critical pillars: Cyber-Physical Systems (CPS), Digital Twins (DT), the Industrial Internet of Things (IIoT), and Cloud Computing (CC). Through the lens of the German Reference Architectural Model Industrie (RAMI) 4.0, these components are integral to fostering Smart Manufacturing (SM) practices. In conjunction, the Asset Administration Shell (AAS) facilitates seamless inter-company communication and enables adaptability to fluctuating market demands. This paper delves into the structural intricacies of AAS and SM within the RAMI 4.0 framework, unveiling three distinct implementation strategies. Furthermore, it meticulously scrutinizes challenges that hinder the full realization of I4.0 potential, such as interoperability, security concerns, and standardized communication protocols. By examining these models and identifying current barriers, the study illuminates pathways for future research, particularly in enhancing the integration of AAS and SM systems, ensuring robust security measures, and advocating for the development of universal standards. This exploration aims to contribute to the ongoing discourse on I4.0, proposing avenues for advancing manufacturing technologies and operational frameworks in alignment with the principles of RAMI 4.0.

Background: Resistance to antimalarial drugs often used in emerging countries, including combination therapies, has forced scientists to search for and develop drugs with novel mechanisms of action, especially resistance to Plasmodium falciparum and Plasmodium vivax, which are highly prevalent in Southeast Asia, Africa, and South America. Objective: evaluate whether there is a relationship between urinalysis and resistance to in-hospital treatment of malaria in Angola. Methodology: This was a cross-sectional, prospective study with a quantitative approach. Results: of the 214 patients, the resistance rate was 24.1%, men (53.6%), between 21 and 40 years old (72.7%), employees (46.4%), from peri-urban regions (77.7%), treated with artemether (90.9), with high parasitemia (57.7%) and after 5 days of treatment, remained hospitalized (61.4%). Was a significant relationship between resistance in unemployed individuals [OR: 0.03 (95% CI: 0.01-0.29), p =0.003] and high levels of parasitemia [OR: 1.09 (95% CI: 1.09-3.95), p=0.040], remained hospitalized for more than 5 days [OR: 5.28 (95% CI: 0.65-43.1), p=0.121] and death [OR: 2.59 (95% CI: 0.32-20.9), p=0.371] when compared with other subgroups. Was a significant relationship between resistance to clear urine [OR: 5.55 (95% CI: 0.72-42.7), p =0.016], few urinary crystals [OR: 11.3 (95% CI: 5.07-25.3), p <0.001] and who presented some microorganisms that were not bacteria or fungi [OR: 3.02 (95% CI: 1 .32-6.90), p=0.009]. Conclusion: urine results, especially the appearance of cloudy urine, the presence of few crystals, and the presence of other microorganisms that are not bacteria or fungi, may be clear signs of resistance to hospital treatment with injectable antimalarials.

Water footprint has been widely used to illustrate the consumption of water in many situations; for instance, in products, processes or regions of interest. In this work, we analyzed – using a sensitivity analysis approach – the effect of some variables in the calculation of the water footprint in the viticulture in Brazilian Serra Gaúcha (the major producing region of Brazilian Wine).The classical Penman-Monteith model for evapotransporation was considered, with uncertainties in some parameters (dead mulch covering fraction in the vineyard, maximum temperatures for some months, altitudes and latitudes of the site). The sensitivity analysis was conducted using the SAFE toolbox under Octave framework. The results indicated that the the portion of the water footprint corresponding to the evapotranspiration is more sensitive to the values of mulch covering fraction and the altitude of the site in comparison with the latitude and the maximum temperatures.

Poro-poro is an important native fruit used in traditional Peruvian medicine with relevant agro-industrial and pharmaceutical potential for its antioxidant capacity for human health. However, to date, there have been few genetic studies. The lack of genomic exploration limits the possibility of expanding our knowledge of its molecular evolution, new molecular pathways, genetic traits, and evolutionary relationships. Here, we report the plastid genome sequence of Passiflora tripartita var. mollissima and the reconstructed phylogenetic tree to infer the phylogenetic relationships among Passiflora species. Our phylogenetic analysis showed that poro-poro is most closely related to Passiflora menispermifolia and Passiflora oerstedii. In summary, our study provides the basis for developing new molecular markers that constitutes a valuable resource for studying molecular evolution and domestication. It also provides a powerful foundation for conservation genetics research and plant breeding programs. To our knowledge, this is the first report on the plastid genome of Passiflora tripartita var. mollissima from Peru.

On these days, issues such as environmental degradation, wealth gap and unequal access to op-portunities and resources are increasing. These concerns have increased the need for sustainable entrepreneurship, defined as sustainable business practices. Entrepreneurship is central in transi-tioning towards a more sustainable future, whereas aligning the social, economic, and ecological objectives and ecological entrepreneurs play a role. This literature review analyzes the field of sustainable entrepreneurship and the extent of their integration in the global business arena. It aims to analyze the depth of existing pieces of literature on sustainable entrepreneurship, its defi-nitions and applications in business practices. The analysis relies upon a literature search on the SCOPUS database around the keywords ‘Sustainability’ and ‘Sustainable Entrepreneurship’. The scientific software VOSviewe is used to better ilustrate the linkage of major categories and correspondent trends, related both with business growth and maintenance of ecological systems. It concludes that the desired levels of sustainability require collaborations between all stakehold-ers, while the transition towards service‐oriented business models has contributed to the growth of sustainable entrepreneurship. Nevertheless, existing institutional structures favor current unsustainable businesses and systems over the newer sustainable ones, demanding from eco-preneurs to initiate institutional changes

Over the past decade, there has been a remarkable acceleration in the evolution of smart cities and intelligent spaces, driven by breakthroughs in technologies such as the Internet of Things (IoT), edge-fog-cloud computing, and machine learning (ML)/Artificial Intelligence (AI). As society begins to harness the full potential of these smart environments, the horizon brightens with the promise of an immersive, interconnected 3D world. The forthcoming paradigm shift in how we live, work, and interact owes much to groundbreaking innovations in augmented reality (AR), virtual reality (VR), extended reality (XR), Blockchain, and Digital Twins (DT). However, realizing the expansive digital vista in our daily lives is challenging. Current limitations include an incomplete integration of pivotal techniques, daunting bandwidth requirements, and the critical need for near-instantaneous data transmission, all impeding the digital VR Metaverse from fully manifesting as envisioned by its proponents. This paper seeks to delve deeply into the intricacies of the immersive, interconnected 3D realm, particularly in applications demanding high levels of intelligence. Specifically, this paper introduces Microverse, a task-oriented, edge-scale, pragmatic solution for smart cities. Unlike an all-encompassing Metaverses, each Microverse instance serves a specific task as a manageable digital twin of an individual network slice. Each Microverse enables on-site/near-site data processing, information fusion, and real-time decision-making within the edge-fog-cloud computing framework. The Microverse concept is verified using smart public safety surveillance (SPSS) for smart communities as a case study, demonstrating its feasibility in practical smart city applications. The aim is to stimulate discussions and inspire fresh ideas in our community, guiding us as we navigate the evolving digital landscape of smart cities to embrace the potential of the Metaverse.

Polycystic ovary syndrome (PCOS) usually comes along with metabolic disturbances attributed to androgen excess and obesity, but the contribution of each has not been defined, and the occurrence of metabolic disturbances is frequently not investigated. We evaluated 99 PCOS and 41 non-PCOS women. Clinical biomarkers of glucose-, liver-, and endothelial-related metabolic alterations were measured; participants were categorized into four groups according with obesity (OB) and hyperandrogenemia (HA) statuses: Healthy (no-HA, lean), HA (HA, lean), OB (no-HA, OB), and HAOB (HA, OB). Metabolic disturbances were highly frequent in PCOS women (70%). BMI correlated with all biomarkers, while free testosterone (FT) only with glucose- and hepatic-related indicators. Despite insulin sensitivity and liver enzymes were associated with FT, women with obesity exhibited lower M [coeff = 8.56 – 0.080(FT) –3.71(Ob); p &lt;0.001)] and higher aspartate aminotransferase (coeff = 26.27 + 0.532(FT) + 8.08(Ob); p = 0.015)] than lean at the same level of FT. Women with obesity exhibited greater risk of metabolic disorders than lean, independently of hyperandrogenemia. Clinicians are compelled to search for metabolic alterations in PCOS women; obesity must be handled in all cases, but hyperandrogenemia needs to be managed also in those with glucose- or liver-related disturbances.

Forest management aims to preserve ecosystem integrity, maintaining resilience thresholds. For this, conservation and invasion patterns must be determined in managed landscapes. The objective was to identify proxies (landscape and environmental patterns) that allowed the plant species invasion and define thresholds of human impacts to improve management practices. We also want to identify indicator species for the different kinds of impacts and environments. 165 plots were measured in Nothofagus antarctica forests and associated open-lands (dry and wet grasslands) in Tierra del Fuego (Argentina). We found differences in the studied variables across landscape and among different uses and impact types. Human impacts influenced over land types, emphasizing the importance of managing intensities. Indicator plant species allowed to identify potential ecological thresholds related to human impacts and the establishment of species linked to ecological and economic degradation, e.g. Bolax gummifera and Azorella trifurcata were associated with high grazing pressure in grasslands and fire in forested areas, while Rumex acetosella and Achillea millefolium, typically associated with forested areas, were related to high harvesting pressure and fire impacts. These findings contribute to understanding the long-term effects of some impacts, and allow us to define variables of monitoring and indicator species for each impact type.

Multiple sclerosis (MS) is a chronic autoimmune inflammatory disease that affects the nervous system. Peripheral blood leukocyte telomere length (LTL) and mitochondrial DNA copy number (mtDNA-CN) are potential biomarkers of disability and neurological damage. The present work evaluated LTL and mtDNA-CN in 75 relapsing-remittent MS (RRMS) patients 50 of whom had an Expanded Disability Status Scale (EDSS) 0 to 3 (mild-moderate disability), and 25 had an EDSS of 3.5 to 7 (severe disability). Absolute LTL and absolute mtDNA-CN were measured via real-time polymerase chain reaction (qPCR). The LTL and mtDNA-CN were significantly lower in RRMS severe disability than in RRMS mild-moderate disability (3.924 ± 0.124 vs 2.854 ± 0.092, p<00001; 75.14 ± 1.77 vs 68.06 ± 1.608, p<0.00001, respectively). The LTL and mtDNA-CN showed a linear correlation in RRMS with mild-moderate disability (r=0.2986, p=0.0351). In addition, in a binary logistic regression model the LTL can predict severe disability (AUC=0.697, p=0.0031, cutoff ≤ 3.0875 Kb, sensitivity= 73.1%, specificity=62.5%), the prediction is improved by including age to the model (AUC=0.765, <0.0001, sensitivity=78.26%, specificity=81.25%). Aging is closely linked to the development of disability in RRMS and can be evaluated through LTL and mtDNA-CN absolute quantification.