Protein malnutrition is present in developing countries but also in developed ones, due by the actual eating habits with insufficient protein intake, in addition to this it is estimated by the Food and Agricultural Organization of the United Nations an increase of world population of 9.1 billion people in less those 30 years, posing the challenge of nourish the mankind. There are different strategies to afford this challenge, one of the most promising ones is to approach novel protein sources like plants, microorganisms, and insects from dry lands.

Social networks have captured the attention of many people worldwide. However, these services have also attracted a considerable number of malicious users whose purpose is to compromise digital assets of other members by using messages as an attack vector to execute different variants of cyberattacks against them. Therefore, this work presents an approach based on Natural Language Processing tools and a Convolutional Neural Network architecture to detect and classify, on social network messages, four types of cyberattacks, such as malware, phishing, spam, and even one whose purpose is deceiving the user into spreading malicious messages to other users, which in this work is identified as bot attacks. One notable feature of this work is that it analyzes textual content without depending on any characteristics from a specific social network, making its analysis independent from particular data sources. Finally, this work was tested on real data, demonstrating its results in two stages. The first detects the existence of any of the four cyberattacks within the message, obtaining an accuracy value of 0.91. After detecting a message as a cyberattack, the next stage is to classify it into one of the four types of cyberattack, achieving an accuracy value of 0.82.

Optoacoustic imaging is an emerging technology that holds great promise for improving general clinical practice since it offers a unique combination of optical absorption contrast, high resolution, and high penetration depth. This combination of factors provides a distinct advantage over alternative imaging modalities in oncology, cardiology, dermatology, or endocrinology among other medical fields. Optoacoustic technology affords the medical practitioner the possibility of visualizing light-absorbing biomolecules like water, lipids, oxy/deoxy hemoglobin, or melanin in deep tissue with relatively cheap and small form factor instruments, without the need of contrast agents or ionizing radiation. Moreover, exogenous fluorescent contrast agents like indocyanine green or methylene blue can also be observed. Driven by its potential for new applications in the clinic, the field has experienced intense changes in the last 20 years. Continuous technological advancements in instrumentation, image formation methods, or acquisition geometries, have led to the development of numerous clinical devices also motivating the creation of several startup companies that aim to translate the technology from the lab to the clinic. Thus, the question arises: how far are we from clinical adoption? In this article, we aim to shed light on such question by reviewing the clinical studies that have been performed in the last 10 years. Our intention is to go beyond the classical review format by providing a brief general overview of the steps that new imaging methods undergo on their journey from the lab to clinical adoption. Then we examine the progress that optoacoustic technology has made on such a journey.

Methotrexate is an antimetabolic agent with proliferative and immunosuppressive activity. It has been demonstrated to be an effective treatment for acute lymphoblastic leukemia (ALL) in children. However, there is evidence of an association between methotrexate and toxicity risks, which influences the personalization of treatment, particularly in the case of childhood ALL. This article presents the development and implementation of an algorithm based on artificial neural networks to detect methotrexate toxicity in pediatric patients with acute lymphoblastic leukemia. The algorithm utilizes historical clinical and laboratory data, with an effectiveness of 99% in the tests performed with the patients dataset. The use of neural networks in medicine is often linked to disease diagnosis systems. However, neural networks are not only capable of recognizing examples, but also hold very important information. For this reason, one of the main areas of application of neural networks is the interpretation of medical data. In this article we diagnose with the application of neural networks in medicine with a concrete example: Detecting Methotrexate in Pediatric Patient in its early stages.

We are experiencing an unprecedented urbanization process that alongside with physical, social and economic developments is having a significant impact on population’s health. Due to higher apprehensions of pollution, violence and poverty, our modern cities no longer ensure a good quality of life so they become unhealthy environments. This study aims to measure the socio-environmental and hematologic profile of residents of Santo André’s landfill – “Bairro Espírito Santo” by using the contextualization of the studied area. The research method is Observational type and from Retrospective cohort and by convenience sampling in Santo André in the Greater ABC region. The study determined a socio environmental profile and the hematologic diseases screening related to a close location to the landfill. The disease manifests itself within a broad spectrum of symptoms that causes changes in blood count parameters. The full blood counts analysis was performed, indicating that the blood counts of residents living near the landfill led to positive hematological changes and diseases like Leukopenia, Anemia, Neutropenia and lymphocytosis were the most common changes. However it is considered that the proof of the relation of cause- effect to environmental exposures that may trigger chronic manifestations in humans requires specific studies that are often complicated.

Seasonal snow cover is a fundamental component of both the global energy budget and the water cycle. Its properties such as fractional snow cover or albedo are particularly affected by climate change. Several methods based on satellite data products are available to estimate these properties, each one with its pros and cons. This work presents a novel methodology that integrates three indexes applied to MODIS satellite data (Spectral Mixture Analysis (SMA), Normalized Difference Snow Index (NDSI) and Melt Area Detection Index (MADI)), to perform a spatio-temporal reconstruction of the fractional snow cover and albedo at 250 m spatial resolution in the Brunswick Peninsula, southwest Patagonia during the cold season (April-October) for the period 2000-2020. Three main steps are included: (1) the increase of the spatial resolution of MODIS (MOD09) data to 250 m using a spectral fusion technique; (2) the snow-cloud discrimination; (3) the daily spatio-temporal reconstruction of snow extent and its albedo signature with subpixel detection using the endmembers extraction and spectral mixture analysis. The results show a 98% agreement between MODIS snow detection and ground-based snow measurement at the automatic weather station Tres Morros (53.3174 °S, 71.2790 °W), with fractional snow cover values between 20% and 50%, showing a close relationship between snow and vegetation type. The number of snow days compiled from the MODIS data indicates a good performance (Pearson correlation of 0.9) compared with the number of skiing days at Cerro Mirador ski centre near Punta Arenas. Although the number of seasonal snow days show a significant increase trend of 0.54 days/year in Brunswick Peninsula during the 2000-2020 period a significant decreasing trend of -4.64 days/year was detected during 2010-2020, and also below the 400 m a.s.l. elevation, which is the most affected area. A reconstruction of the monthly mean temperature using the ERA5 Land reanalysis product shows a significant warming trend in May (0.068 ºC/year) and October (0.098 ºC/year) in the 2000-2020 period. Under the future emission scenario RCP8.5, the regional climate model RegCM4 predicts further warming during 2020-2050 of 0.059 ºC/year in July, 0.088 ºC/year in August, and 0.019 ºC/year in October, which will further reduce snow cover.

Grafting polyethylene glycol (PEG) on polymers surface is widely used to improve biocompatibility by reducing protein and cell adhesion. Although PEG is considered to be bioinert, its incorporation to biomaterials has shown to improve cell viability depending on the amount and molecular weight (MW) used. This phenomenon was studied here by grafting PEG of three MW onto polyurethane (PU) substrata at three molar concentrations to assess their effect on PU surface properties and on the viability of osteoblasts and fibroblasts. PEG formed a covering on the substrata which increased the hydrophilicity and surface energy of PUs. Among the results it was observed that osteoblast viability increased for all MW and grafting densities of PEG employed compared with unmodified PU. However, fibroblast viability only increased at certain combinations of MW and grafting densities of PEG, suggesting an optimal level of these parameters. PEG grafting also promoted a more spread cell morphology than that exhibited by unmodified PU; nevertheless, cells became apoptotic-like as PEG MW and grafting density were increased. These effects on cells could be due to PEG affecting culture medium pH, which became more alkaline at higher MW and concentrations of PEG. Results support the hypothesis that surface energy of PU substrates can be tuned by controlling the MW and grafting density of PEG, but these parameters should be optimized to promote cell viability without inducing apoptotic-like behavior.

This paper presents new above-ground biomass (AGB) and biomass components equations for seventeen forest species in the temperate forests of northwestern Mexico. A data set corresponding to 1336 destructively sampled oak and pine trees was used to fit the models. Generalized method of moments was used to simultaneously fit systems of equations for biomass components and AGB, to ensure additivity. Additionally, the carbon content of each tree component was calculated by the dry combustion method, in a TOC analyser. The fitted equations accounted for on average 91, 83, 84 and 78% of the observed variance in stem wood and stem bark, branch and foliage biomass, respectively, whereas the total AGB equations explained on average 93% of the total observed variance in AGB. The inclusion of h or d²h as additional predictor in the d-only based equations systems slightly improved estimates of stem wood, stem bark and total above-ground biomass, and greatly improved the estimates produced by the branch and foliage biomass equations. The fitted equations were used to estimate AGB stocks at stand level from a database on growing stock from 429 permanent sampling plots. Three machine-learning techniques were used to model the estimated stand level AGB and carbon contents; the selected models were applied to map the AGB and carbon distributions in the study area, which yielded mean values of 129.84 Mg ha^-1 and 63.80 Mg ha^-1, respectively.

This study investigated the development of Aedes aegypti density in houses of the urban locality of Poblado Miguel Alemán Valdes, in the Sonora state of Mexico, after application of 1% propoxur paint as full wall coverage (IP) and targeted indoor painting (IP 1m) in comparison to IRS with propoxur 70% WP (full wall coverage). The 1% propoxur paint was applied by the homeowners by brushing and rolling at the recommended dose of 1L/8 m², equivalent to 1.5 g a.i./m², while IRS was conducted by professionals with Propoxur 70% WP at a dose of 1 g a.i./m². Adult mosquito surveys were conducted in a random sample of houses in each block one week before the interventions and at week 1, month 1 to 4, month 6, month 9 and month 12 post-interventions. All three propoxur based treatments provided similar reductions (43.7%, 44.9% and 41.3% for IP, IP 1m and IRS respectively) in the fraction of houses positive in female Aedes aegypti resting indoor and outdoor as one year average of 8 follow up surveys. Indoor resting density of Aedes females during the one-year evaluation was reduced by 77.5% through IP followed by IP 1m with 64.2% reduction and 30% reduction with IRS. Culex mosquitoes’ interior density was affected as well by the insecticide treatments with similar average reductions for IP 1m (50.0%) and IRS (57.8%) in comparison with control. Aedes breeding was impacted by the insecticide paint in similar extent for both interventions, expressed by a substantial reduction of the House Index (20.1% IP, 31.2% IP 1m) and especially the Container Index (51.8% IP, 61.7% IP 1m) during the one-year surveys in comparison to control. In contrast, IRS treated block experienced an increase in both indexes. However, despite IP and IP 1m impacted in Aedes adult and immature indexes with noticeable reductions, the differences in all cases were not significative among the different insecticide treatments. The low sample size and mosquito population levels may have influenced the statistical outcomes. More than 80% of the interviewed residents were satisfied with the effectiveness of the paint and IRS treatments. The determination of the blood cholinesterase activity of tested individuals after the use of the carbamate paint and IRS in this study did not exceed acceptable inhibition limits. This study suggests that the application of propoxur paint by homeowners as full house coverage or as targeted indoor painting can be a safe and accepted intervention method for density reduction of Aedes aegypti populations in urban environments.

Electromyographic (EMG) signals provide information about a person's muscle activity. For hand movements, in particular, the execution of each gesture involves the activation of different combinations of the forearm muscles, which generate distinct electrical patterns. Conversely, the analysis of these muscle activation patterns, represented by EMG signals, allows recognizing which gesture is being performed. In this study, we aimed to implement an automatic identification system of hand or wrist gestures based on supervised Machine Learning (ML) techniques. We trained different computational models and determined which of these showed the best capacity to identify six hand or wrist gestures and generalize between different subjects. We used an open access database containing recordings of EMG signals from 36 subjects. Among the results obtained, we highlight the performance of the Random Forest model, with an accuracy of 95.39%, and the performance of a convolutional neural network with an accuracy of 94.77%.

With young adults (18-30 years) exhibiting the lowest vegetable intake, primarily due to in-adequate cooking skills, this study aims to explore the usability and desirability of educational tools such as written recipes and cooking videos to foster sustainable eating habits. Employing a descriptive, qualitative, and user-centered design, three focus groups were held at a major urban university campus in New Zealand, engaging students, and staff within the target age group. Discussions with 15 participants identified key facilitators for vegetable-based cooking, including access to ingredients, ease of recipe visualization, and cost-effectiveness. Conse-quently, 13 vegetable-centric recipes and instructional videos were created, incorporating nu-tritional value, affordability, and preparation efficiency. These resources, tailored to young adults' preferences, were designed to mitigate the identified barriers to vegetable use, con-tributing to sustainable food practices. The application of a user-centered approach in devel-oping educational content yielded a set of recipes and videos that not only address the gaps in cooking skills among young adults but also promote the broader goals of sustainability in food consumption patterns. This approach offers actionable insights for practitioners and food marketers to enhance vegetable utilization and sustainable eating behaviors in this demo-graphic.

Heritage bridges constitute an integral feature of the urban landscape in numerous cities. However, it is common for these structures to surpass their life cycle, rendering them ill-equipped to withstand the dynamic demands of users and extreme events, particularly hydrological occurrences. This research presents a methodology for the assessment of heritage riverine bridges, with a focus on the Grau Bridge in Peru as a case study. The investigation commences with an exhaustive literature review, complemented by a historical examination, followed by a preliminary diagnosis. Subsequently, hydrological and hydraulic studies are conducted, encompassing drone surveys of the riverbed and the bridge, soil analyses, and the application of 1D and 2D models in HEC-RAS. The outcomes of this comprehensive analysis reveal the high vulnerability of the Grau Bridge. Finally, strategic recommendations for its conservation are recommended.

Acute lymphoblastic leukemia (ALL) is the most common cancer among children worldwide, characterized by an overproduction of undifferentiated lymphoblasts in the bone marrow. The treatment of choice for this disease is the enzyme L-asparaginase (ASNase) from bacterial sources. ASNase hydrolyzes circulating L-asparagine in plasma, leading to starvation of leukemic cells. The ASNase formulations of E. coli and E. chrysanthemi present notorious adverse effects, especially the immunogenicity they generate, which undermines both their effectiveness as drugs and patient safety. In this study, we developed a humanized chimeric enzyme from E. coli L-asparaginase, which would reduce the immunological problems associated with current L-asparaginase therapy. For these, the immunogenic epitopes of E. coli L-asparaginase (PDB: 3ECA) were determined and replaced with those of the less immunogenic Homo sapiens asparaginase (PDB:4O0H). The structures were modeled using the Pymol software and the chimeric enzyme was modeled using the SWISS MODEL service. A humanized chimeric enzyme with four subunits similar to the template structure was obtained, and the presence of asparaginase enzymatic activity was predicted by protein-ligand docking.

Data is the most valuable asset of a company or organisation nowadays, for the management of such data there are several techniques used for the storage and analysis of these data, if the organisation chooses wrongly among the alternatives it could face a very costly problem. Based on the above information we will study a very important issue today in the business world, with the global economic growth has also grown the world of technology and therefore organizations or companies also need to move forward with firm and fast pace how business evolves; Its weaknesses, strengths and the need to always be at the forefront of technological tools we will dive into the subject of business intelligence or also known as Business Intelligence (BI), Datawarehouse and Data Mining which is nothing more than a group of applications and tools that allow you to extract, transform and load some data to get to get information and knowledge in order to make a quick decision, accurate and efficient in the organization to achieve the objectives outlined. Due to the fact that there are still companies or organisations that make blind decisions in their customer or strategic processes. In order to solve this problem we rely on data mining as an alternative to minimise risks, which can lead to major and valuable losses within an organisation. In the case of a private company where data mining is applied to study patterns of customer behaviour on their own parameters of location, consumption, etc.. And third party data. The search for information is profitable for the business administration. Data mining is applied as a tool for the development of marketing tactics in competitive production and industrial sectors. This technology attempts to help perceive the attachment of databases. Data mining works on a preferential level looking for patterns, behaviours, orders or groupings that can create a model that allows us to better understand the concept and help in decision making so organisations rely on different systems such as CRM, ERP and many others, but to move from just information to generate business intelligence must be centralised in a single place where you can run data analysis of all types to discover trends that help decision making that place can be mainly a Lake or a Warehouse.

Course-based Undergraduate Research Experiences (CUREs) in high-enrollment, introductory classes are a 37 potentially transformative approach to retaining more students in STEM majors. We developed and piloted a CURE 38 in the introductory biology courses at the University of Washington. This CURE focuses on analyzing experimental 39 evolution of antibiotic resistance in Escherichia coli and generates data on two topics relevant to clinical practice: 40 compensatory mutations and cross-drug effects. By studying mutations in central cellular machinery that confer drug 41 resistance, students not only gain insight into fundamental cellular phenomena, but also recognize the molecular 42 basis of a medically important form of evolutionary change, connecting genetics, microbiology, and evolution.

This article critically examines existing wastewater management legislation, highlighting its detrimental impact on environmental and public health. It emphasizes the urgent need for a mentality shift among water managers, advocating responsible stewardship of water resources. By promoting collaboration between regulatory bodies and scientific communities, the article seeks tailored solutions for complex challenges. It underscores the necessity of integrating technological innovation, rigorous monitoring, and public engagement for sustainable management. Additionally, it calls for the implementation of easy-to-adopt technological solutions, alongside rigorous monitoring and financial support. Ultimately, the article advocates for a paradigm shift in wastewater management policies towards accountability, innovation, and environmental sustainability. Directives governing wastewater management in Europe, particularly in Spain, have faced scrutiny due to significant shortcomings. Legislation has inadvertently facilitated untreated or poorly treated wastewater discharge, resulting in widespread pollution. Despite EU efforts, punitive measures have proven ineffective, with fines often borne by the public sector, although private sector responsibility. The lack of robust monitoring mechanisms and technical support exacerbates the situation, perpetuating a regressive mindset among water managers. Urgent reforms are needed to enforce strict discharge prohibitions, promote reuse, and provide financial and technical assistance. However, systemic barriers and entrenched mentalities pose formidable challenges to meaningful change.

The Mexican Republic ranks fifth in the world in terms of amphibian diversity, and within Mexico, the state of Oaxaca has the greatest amphibian richness and endemism. Unfortunately, various factors, such as land use change and global warming, have caused a global crisis that threatens the conservation of this class. In the state of Oaxaca, few studies of amphibians have been carried out at the state level. Several research has shown that an analysis of beta diversity provides information that can be applied to conservation strategies. In this work, we analyzed the beta diversity at the species level and higher taxon level for the amphibians of Oaxaca and their replacement components and the differences in richness for anurans and caudates separately between physiographic subprovinces. Very high beta diversity was recorded, with higher diversity occurring among caudates than among anurans. Replacement was the component that most contributed to this result, and the subprovinces with substantial environmental differences had the most dissimilar amphibian communities. The results of this study show the need to implement conservation strategies in subprovinces with high amphibian richness and endemism levels, following the example of Sierra Madre de Oaxaca (SMO)

The only solution to avoid pollution due to sewage is to treat the effluent and reuse water and sludge at the wastewater production site. This makes it necessary to install treatment plants distributed along the sewer system to prevent the movement of effluents with the consequent losses to the aquifer. This new management is called decentralized wastewater treatment. To make this change possible, it is necessary to develop treatment plants that do not represent a health hazard for citizens, eliminating the nuisance caused by traditional plants. These plants need to be robust, operate autonomously, have reduced maintenance and exhaustive control of each process, where each cubic meter of effluent is perfectly controlled, avoiding losses to the aquifer or discharges that may occur due to deficiencies in their purification capacity; constantly producing water and sludge, which are directly reusable with all the health and environmental guarantees regardless of variations in inlet effluent or environmental conditions. This article presents a paradigmatic case of a decentralized solution with conditions of maximum complexity that has been solved efficiently, saving around 98% of the initial investment, completely avoiding wastewater discharges into the environment and reusing 100% of the treated water, in 14 years of operation.

This study examines the recovery efforts at Gran Tarajal Harbor following a significant oil spill, employing innovative technologies. Initial response efforts were hampered by inadequate contingency plans and bureaucratic delays, underscoring the need for improved preparedness. Cleanup operations utilized advanced methods such as enhanced absorbent sponges, absorbent granulates, bioremediation with allochthonous species, and a combination of barriers and sponges. These technologies proved effective in minimizing environmental impact, reducing hydrocarbon concentrations in sediments from nearly 60,000 mg/kg to less than 1,600 mg/kg in seven months. Heavy metal analysis revealed lead and copper concentrations associated as well as with routine port activities, while mercury levels linked to the spill decreased over time. Tissue analysis indicated minimal contamination in local organisms, suggesting limited impact from the spill, and evaluation of the biological communities in sediments suggest an ecological recovery. Study underscores the importance of rapid response, advanced technologies, and detailed contingency plans tailored to each port. Despite the successful cleanup and ecosystem recovery, political and bureaucratic challenges remain significant obstacles to implementing these improved methods. The findings advocate for a re-evaluation of current oil spill response protocols to incorporate more effective, sustainable, and cost-efficient technologies, aligning with the principles of a circular economy.

Chile faces a serious crisis on housing affordability given that most of the population is unable to secure a house. While housing prices between 2008 increased by 70.96%, wages only increased by 20.43%. This article presents the analysis of the housing prices configuration for the main district in the country: Santiago Centro. The assessment focuses on verticalised housing buildings constructed between 2015 and 2019. The article develops an exploratory study on the price of housing in the city of Santiago de Chile, to generate a diagnosis to identify the role played by expectations of profitability when configuring that price. Based on the information generated, we seek to contribute to the discussion on public policies that advance towards the development of affordable housing for households in central communes with high urban value, as is the case of Santiago Centro. We hypothesize that profitability expectations of real estate developers play a key role in the housing prices and an adjustment in the profit ratios may increase the affordability keeping the housing market over profitable rates. The research is relevant due to the lack of data transparency in the Chilean housing market, where access to investment costs, land values, yields and house price formation are not part of the public discussion, even though this implies that many households are facing severe difficulties in paying for access to decent housing.

Among the knowledge areas in which process mining has had an impact, the audit domain is particularly striking. Traditionally, audits seek evidence in a data sample that allows to make inferences about a population. Mistakes are usually committed when generalizing the results and anomalies, therefore, appear in unprocessed sets. However, there are some efforts to address these limitations using process mining-based approaches for fraud detection. To the best of our knowledge, no fraud audit method exists that combines process mining techniques and visual analytics to identify relevant patterns. This paper presents a fraud audit approach based on the combination of process mining techniques and visual analytics. The main advantages are: (i) a method is included that guides the use of the visual capabilities of process mining to detect fraud data patterns during an audit; (ii) the approach can be generalized to any business domain; (iii) well-known process mining techniques are used (Dotted Chart, Trace Alignment, Fuzzy Miner…). The techniques were selected by a group of experts and were extended to enable filtering for contextual analysis, to handle levels of process abstraction, and to facilitate implementation in the area of fraud audits. Based on the proposed approach, we developed a software solution that is currently being used in the financial sector as well as in the telecommunications and hospitality sector. Finally, for demonstration purposes, we present a real hotel management use case in which we detected suspected fraud behaviors, thus validating the effectiveness of the approach.

This document makes a comprehensive analysis of the inequality of the water market in Chile, measured by the Gini coefficient method. The situation of water rights in Chile is of particular interest because it is a completely privatized system, where rights are traded in the market and therefore water is presented as a commodity. This privatization of water in Chile occurred as part of the process of neoliberalization since the 1981 Water Code. The results of this study indicate that both the concentration and the inequality in the distribution of water rights is very high. It proposes a profound revision of applying a mercantile logic to a scarce basic resource for life such as water and exploring the importance of its role as a national good for public use.

The enterprise software sector is experiencing a significant transformation driven by rapid technological progress and evolving business needs. An effective release management process is crucial for the solution providers and customers, as they incorporate the principles of Industry 4.0 and 5.0. With the growing dependence on software solutions and services, ensuring their quality, reliability, and security is highly necessary. The release management process incorporates strategic planning, regression testing, accurate deployment, and continuous monitoring of software updates. However, the rapid advancements in artificial intelligence (AI) and machine learning (ML) create a unique challenge to the release management process. The existing research needs to address the necessary adaptations for Industry 5.0, mainly in product-based software organizations, to the release management process without a change management system. After working with several software solution stakeholders, based on the responses from SaaS project stakeholders, we have presented a revised software release readiness workflow by incorporating a change management module. The preliminary result based on data over a limited period of time indicates that the revised workflow has the potential to improve the management of slippage, particularly by more effectively addressing NFR-related issues, thereby resulting in more predictable and reliable release cycles.

The administration of regional neuraxial analgesia for pain relief during labor is widely recognized as a safe and effective method involving medication delivery into the epidural or subarachnoid space in the lower back. This study proposes an innovative semantic image segmentation methodology emphasizing enhanced interpretability using convolutional Random Fourier Features and layer-wise weighted class-activation maps tailored explicitly for foot segmentation in regional analgesia monitoring. Namely, our contribution is twofold: i) a novel Random Fourier Features layer is introduced to deal with image data to enhance three well-known architectures (FCN, UNet, and ResUNet); ii) three novel quantitive measures are presented to evaluate the interpretability of a given deep learning model devoted to segmentation tasks. Our approach is rigorously evaluated on a demanding dataset of foot thermal images from pregnant women who received epidural anesthesia. Its small size and considerable variability characterize the dataset. Our validation results demonstrate that the proposed methodology not only achieves competitive foot segmentation performance but also significantly enhances the explainability of the process, rendering it well-suited for applications such as epidural insertion during labor.

Population studies have demonstrated an association between sodium (Na) and po-tassium (K) intake and levels of blood pressure (BP) and cholesterol. The aim of this study was to describe the dietary intake and distribution of Na and K in Mexicans, and their as-sociation with metabolic risk outcomes. We analyzed a national survey that included 4,219 participants. Dietary information was obtained through a 24-hour recall. Foods and beverages were classified based on the degree of processing. BP and biomarkers in blood and urine were measured. The mean intake (mg/d) of Na was 1512 in pre-schoolchildren, 2844 in schoolchildren, 3743 in adolescents, and 3132 in adults. The mean intake of K was 1616 in pre-schoolchildren, 2256 in schoolchildren, 2967 in adolescents, and 3401 in adults. Processed and ultra-processed foods (UPF) contribute to sodium intake: 49% in preschool and schoolchildren, 47% in adolescents, and 39% in adults. Adults in the fourth quartile of sodium intake had lower serum concentrations of cholesterol (181.4 mg/dL) and HDL-c (35.5 mg/dL). The Mexican population has high Na and low K intakes. There is a relationship between Na sodium consumption and cholesterol, and LDL levels. UPF contributes to almost 40% of the sodium consumed by Mexicans.

Deep learning machines are computational models composed of multiple processing layers of adaptive weights to learn representations of data with multiple levels of abstraction. Their structure is mainly reflecting the intuitive plausibility of decomposing a problem into multiple levels of computation and representation since it is believed that higher layers of representation allow a system to learn complex functions. Surprisingly, after decades of research, from learning and design perspectives these models are still deployed in a heuristic manner. In this paper, deep learning feed-forward machines are modeled from a statistical mechanics point of view as disordered physical systems where its macroscopic behavior is determined in terms of the interactions defined between the basic constituent of these models, namely, the artificial neuron. They are viewed as the equilibrium states of a theoretical body that is subject to the law of increase of the entropy. The study of the changes in energy of the body when passing from one equilibrium state to another is used to understand the structure and role of the phase space of the system, the stability of the equilibrium states, and the resulting degree of disorder. It is shown that the topology of these models is strongly linked to their stability and resulting level of disorder. Furthermore, the proposed theoretical characterization permit to assess the thermodynamic efficiency with which information can be processed by these models, and to provide a practical methodology to quantitatively estimate and compare their expected learning and generalization capabilities. These theoretical results provides new insights to the theory of deep learning and their implications are shown to be consistent through a set of benchmarks designed to experimentally assess their validity.

Aqueous and ethanolic extracts of Hibiscus sabdariffa were spray-drying using maltodextrin (MD) and gum arabic (GA) as carriers agents. An experimental design Taguchi L8 with seven variables was implemented. Physicochemical properties in the encapsulates were evaluated by UV-Vis, XRD, spectroscopy and gravimetric techniques. Treatments with aqueous extracts showed the highest concentration of total soluble polyphenols (TSP) 32.12- 21.23 mg EAG/g DW, and antioxidant capacity (AOX) for ABTS assay. The best treatment for TSP and AOX was T4: 2.5% Hibiscus w/w, aqueous extracts, decoction, extract-to-carrier ratio 1:1 (w/w), proportion to carriers (MD:GA) 80:20 (w/w), 10000 rpm, 150°C. Taguchi L8 model is a tool that allows the use of multiple variables with a low number of treatments that indicate the drying conditions that give the best parameters, focusing mainly on TSP and AOX, in addition, is a good alternative for the preservation and stability of the PC in Hibiscus.

Technology has transformed aeroponics, providing numerous advantages over traditional soil-based agriculture. However, there remains a need for comprehensive information on the types of technology employed in aeroponics and their impact on the growing process. This paper presents a literature review of 47 studies published between 2012 and 2023 in peer-reviewed journals and conference proceedings. As a result, it identifies the status and tendencies in the usage of technology in aeroponics as well as the main opportunities and challenges. Furthermore, this paper introduces the Technology Adoption and Integration in Sustainable Agriculture (TAISA) model. TAISA is a model that identifies the degree of technology integration in any sustainable agriculture system to determine how technology affects production and quality. Overall, the systematic review suggests that technology can play a vital role in improving the efficiency and sustainability of aeroponic farming. However, careful consideration must be given to the costs and technical requirements associated with using these technologies. Moreover, the TAISA model reveals that technology has primarily been employed in creating new processes that are not possible to implement without the help of technology. Therefore, we conclude that technology use has taken root in aeroponics and can be promoted to improve sustainable agriculture.

The main goal of the study was to obtain objective measures of the impact of a complete pre-season of amateur football on the players’ physical activity parameters. 17 amateur football players (24.47 ± 4.53 years) enrolled in the same team agreed to participate. They were asked to wear one accelerometer on the right hip during each training practice. Moderate-to-Vigorous physical activity (MVPA), steps and metabolic-equivalent (METs), among other parameters, were obtained and analyzed. Results showed that players spent an average 54.86% of each training session in MVPA levels, for a total of 100.33 minutes every week (3 training sessions per week). Therefore, this group of amateur football players did not meet the requirements to obtain health benefits from their physical activity program: amateur football. This finding could be considered noteworthy because there are thousands of adults worldwide who play amateur football to maintain a healthy lifestyle. They should be aware that their weekly training load is not enough to help them meet the necessary requirements. They either need more practice time (90-minute sessions) or more sessions. The pre-season training program was rated as “somewhat hard” by the participants, and quadriceps and hamstrings were mentioned as the most exerted muscles

Cheese consumption provides humans with minerals, proteins, carbohydrates, and vitamins. In Mexico, several cheese varieties are produced, each with its texture, scent, and flavor. The artisanal cheeses made in the states of Tabasco and Chiapas —including, among others, the varieties named crema (cream), doble crema (double cream), oaxaca, panela, fresco, bola, poro, Cotija, and asadero— have a high demand in the domestic and foreign markets. The intensification of anthropic activity in these states causes an increased emission to the environment of contaminants like heavy metals, which could reach human foodstuffs through the food chains. In particular, heavy metal contents in cheeses consumed daily by these states' local population might represent a public health risk. Because of that, our objectives in this work were to determine the concentrations of lead, cadmium, nickel, copper, zinc, and iron in artisanal cheeses produced in the states of Tabasco and Chiapas, and to determine the values of the Hazard Quotient (HQ), Total Hazard Quotient (THQ), and Cancer Risk Total (CRT) for adult and young men and women. The results of our analyses of cheese samples from the states of Tabasco and Chiapas showed that the average concentrations (mg kg-1) of cadmium (0.0023±0.002, 0.0023±0.002 mg kg-1, respectively for each state), lead (0.0047±0.00, 0.0051±0.002), nickel (0.0039±0.0046, 0.0031±0.0039), copper (0.0199±0.021, 0.0202±0.022), zinc (0.1611±0.18, 0.194±0.21), and iron (61.84±4.23, 65.76±6.61 mg kg-1), the first three values lower than the limits established by the FAO/WHO and Codex Alimentarius. The value of THQ that we obtained was less than one, and that of CRT was within the limits established by the US-EPA, which means that the consumption of artisanal cheeses from Tabasco and Chiapas by humans does not imply a risk of disease or cancer.

JmjC-family of lysine demethylases (JMJC-KDMs) plays an essential role controlling gene expression and chromatin structure. In most cases, their function has been attributed to the demethylase activity. However, accumulating evidence demonstrates that these proteins play roles distinct from histone demethylation. This raises the possibility that they might share domains that contribute to their functional outcome. Here, we show that the JMJC-KDMs contain low complexity domains as well as intrinsically disordered regions, which in some cases reached 70% of the protein. Our data revealed that PHF2, KDM2A and KDM4B cluster by phase-separation in vitro and in vivo. Moreover, our molecular analysis demonstrated that these domains are important to regulate transcription, suggesting that clustering via phase -separation is a common feature that JMJC-KDMs utilize, in addition to their catalytic activity, to facilitate their functional responses. Our study uncovers a novel potential function for the JMJC-KDM family that sheds light on the mechanisms to achieve the competent concentration of molecules in time and space within the cell nucleus.

Among the many Lysosomal Storage Disorders (LSDs) that would benefit from the establish-ment of novel cell models, either patient-derived or genetically engineered, is Mucopolysaccha-ridosis type II (MPS II). In fact, even though a specific therapeutic approach does exist for this disorder (Enzyme Replacement Therapy, ERT, with recombinant human IDS) and haematopoiet-ic stem cell transplantation (HSCT) may also hold promise whenever the disorder is diagnosed soon enough, both approaches have their own drawbacks. Here we present our results on the establishment and characterization of two MPS II pa-tient-derived stem cell line(s) from deciduous baby teeth. To the best of our knowledge, this is the first time a stem cell population is isolated from LSD patient samples obtained from the oral cavity. Taking into account our results on the molecular and biochemical characterization of those cells and our first insights on their subcellular MPS phenotype, we consider these cells will be a valuable tool for both pathophysiological assessments and drugs screenings. Ultimately, we believe patient-derived dental pulp stem cells (DPSC) may represent a feasible alternative to induced pluripotent stem cells (iPSC) in many labs with standard cell culture con-ditions and limited (human and economic) resources.

The research focuses on the electrochemical behavior of TiVN trilayers in a liquid that simulates a physiological environment (blood plasma). TiVN films are obtained through Physical Direct Current Vapor (PVD) Deposition on titanium bases, depositing TiN and VN layers as an intermediate layer during the procedure. Impedance measurements are carried out before and during the wear test to determine the impact on the sample. The results show that the TiVN trilayer enhances corrosion resistance according to the time of exposure to the electrolyte. Initially, the load resistance (Rct) was 10.50 Ohms, but after 16 days, the Rct rose markedly to 13.87 Ohms, signaling an advance in corrosion resistance, a valuable property for wide applications.

This study delves into the foundational aspects of electrocardiographic (ECG) lead systems, specifically focusing on Einthoven’s Triangle and Wilson’s Central Terminal. We introduce the innovative concept of a Precordial Central Terminal, a strategic arrangement of thoracic electrodes that establishes two Einthoven’s triangles within the horizontal plane, in accordance with physical-mathematical principles. Furthermore, we meticulously scrutinize Goldberger’s contributions to the field of ECG, particularly augmented leads, which shed light on the development of our theory. Additionally, we propose the implementation of a novel standardized electrocardiograph, characterized by its use of exclusively “precordial” electrodes, yet capable of providing a comprehensive three-dimensional perspective of cardiac electrical activity. By amalgamating theoretical underpinnings with empirical experimentation, our study lays the groundwork for future investigations, including the experimental validation of our innovative Precordial Terminal. This validation holds the promise of yielding substantial advancements in the realm of clinical electrocardiography.

We introduce a novel algebraic structure, termed algebra B, which generalizes Lie algebras through the definition of a non-associative and unital algebra. We demonstrate that algebra B retains essential properties such as bilinearity and antisymmetry, and satisfies both the Jacobi and Malcev identities; this occurs when the product operations of Lie and Malcev algebras are derived from the product operation defined in our algebra. By examining the connections between algebra B, Malcev algebras, and Lie algebras, we establish that algebra B effectively generalizes these structures. Furthermore, we show that algebra B can generate complex entities with a novel structure distinct from those currently known. Our findings lay the groundwork for future investigations into the practical applications and further theoretical development of this new algebraic framework.

The preparation of new materials based on starch for the development of biodegradable packaging is increasing, however, the poor properties of this biopolymer for this application causes an area of opportunities for the improvement of water vapour permeability (WVP), mechanical properties, thermal properties, hydrophilicity, water absorption, among others. Hence, starch has been combined with other polymers such as polyvinyl alcohol, which has shown an improvement in the mechanical properties of starch, also, the use of clays suggests that the properties of response to water can be improved. Therefore, in this work, the preparation and characterization of starch-PVA-nanoclay films prepared by solvent casting is reported. The results obtained suggest that the sonication of nanoclay is necessary to reach a good dispersion, which promotes a strong interaction among starch-PVA-nanoclay. In addition, the properties of WVP and mechanical properties of films improved with incorporation of nanoclay, the concentration of 0.5% w/v of nanoclay showed to be the best concentration due to concentrations of 1.0 and 1.5% w/v were poorer than 0.5% w/v. Accordingly, the successful incorporation of nanoclays into the matrix starch-PVA suggests that this material is a good candidate for use as packaging.

Mn-promoted bulk iron catalysts with high specific surface area (82-211 m2.g-1) were synthesized by coprecipitation followed by drying under supercritical conditions. The catalysts were tested in the CO2 hydrogenation reaction. The Mn-promoted iron catalysts showed better textural properties than the bare Fe2O3 catalyst, allowing better dispersion of the active phase, easier reduction of iron oxide, better carburization of iron oxides and higher catalytic activity than the bare Fe2O3 catalyst. The best activity results were obtained by catalyst promotion with a very low amount of Mn (Mn/Fe ratio of 0.05). Upon steady-state conditions (T=340 ºC, total pressure of 20 bar and H2/CO2=3), this catalyst showed high CO2 conversion (44.2%) and selectivity to C2-C4 hydrocarbons (68%, olefin to paraffin ratio of 0.54), while the selectivity to C5+ hydrocarbons, CH4 and CO was about 3.2, 38.5 and 5%, respectively. A close correlation was found between catalyst textural properties and CO2 conversion. The most active MnFe-0.05 catalyst shows high stability during 72 h of reaction related to low amount of soft coke formation and catalyst activation through the formation of χ-Fe5C2 phase during the on-stream reaction.

In the provinces of the region, empirical constructions reached maximum points with these practices. The effects and pathologies appear as physical, chemical and mechanical failures in pillars, walls and roofs, generating uncertainty for the user. The current powerful design can detect the interior deterioration of coatings in adobe, brick and concrete constructions, and prevent collapses, material and economic losses. Experimental methods performed affirm the serious validity. The accuracy of the simulation and design provide a pre-test reliability of 95%. Five piles constructed of various materials participate in the prototype performance test, there is a correlation (R=0.9997) between the magnetic field range "B" (cm) and density "ρ" (g/cm³), also by increasing the current (i) in transit Q1 and coil L1, the induction of the "B" increases proportionally until penetrating the density of the wall of the building, having 5% reading error.

Wildfires have always been a part of the history of Mediterranean forests. However, forest regeneration after a wildfire is not certain. It depends on many factors, some of which may be influenced by land management activities. Failure of regeneration will cause a regime shift in the ecosystem, reducing the provision of ecosystem services and ultimately leading to desertification. How can we increase Mediterranean forests’ resilience to fire? To answer this question, we did a literature review, investigating chains of processes that allow forests to regenerate (which we label “regeneration mechanisms”), and assessed the impact of selected management practices documented in the WOCAT database on the regeneration mechanisms. We identified three distinct regeneration mechanisms that enable Mediterranean forests to recover, as well as the time frame before and after a fire in which they are at work, and factors that can hinder or support resilience. The three regeneration mechanisms enabling a forest to regenerate after a fire consist of regeneration (1) from a seed bank; (2) from resprouting individuals; and (3) from unburned plants that escaped the fire. Management practices were grouped into four categories: (1) fuel breaks, (2) fuel management, (3) afforestation, and (4) mulching. We assessed how and under what conditions land management modifies the ecosystem’s resilience. The results show that land management influences resilience by interacting with resilience mechanisms before and after the fire, and not just by modifying the fire regime. Our analysis demonstrates a need for adaptive – i.e. context- and time-specific – management strategies.

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder characterised by poor social interaction and communication, as well as restricted and stereotyped interests. Due of the high prevalence of gastrointestinal disorders in individuals with ASD, researchers have investigated the gut microbiota as a potential contributor to its aetiology. The relationship between the microbiome, gut, and brain (microbiome-gut-brain axis) has been acknowledged as a key factor in modulating brain function and social behaviour, but its connection to the aetiology of ASD is not well understood. Recently, there has been increasing attention on the relationship between the immune system, gastrointestinal disorders, and neurological issues in ASD, particularly in relation to the loss of specific species or a decrease in microbial diversity. It focuses on how gut microbiota dysbiosis can affect gut permeability, immune function, and microbiota metabolites in ASD. Although a very complete study suggests that dysbiosis is a consequence of the disease and that it has practically no effect on autistic manifestations. This is a review of the relationship between the immune system, microbial diversity, and the microbiome-gut-brain axis in the development of autistic symptoms severity and, a proposal of a novel role of gut microbiome in ASD, where dysbiosis is a consequence of ASD-related behaviour and where dysbiosis in turn accentuates the autistic manifestations of the patients via microbiome-gut-brain axis in a feedback circuit.

Purpose: To assess the tolerability, safety, and efficacy of an ophthalmic topical formulation containing helenalin from Arnica montana and hyaluronic acid 0.4% (HA) in patients with mild to moderate dry eye disease (DED) exhibiting positive Matrix Metalloproteinase 9 (MMP-9) test results. Methods: Tolerability and safety were evaluated in 24 healthy subjects. Participants were in-structed to routinely apply one drop of the formulation three times a day in the study eye, for a period of two weeks, followed by a clinical follow-up of 21 days. Efficacy was studied in 48 DED patients randomized into Study (Group 1/ receiving the study formulation) or Control (Group 2/ Receiving HA 0.4% eye lubricant) groups, for 4 weeks. Assessments included MMP-9 positivity, conjunctival impression cytology (CIC), Ocular Surface Disease Index (OSDI), non-invasive tear film breakup time (NIF-BUT), non-invasive average breakup time (NIAvg-BUT), ocular surface staining, Schirmer's test, and meibomiography. A crossover design with a four-week follow-up was applied to the control group. Results: Healthy subjects receiving the study formulation exhibited good tolerability and no ad-verse events. Group 1 showed significant MMP-9 reduction (25% positivity rate) unlike Group 2 (87.5% positivity rate). Group 1 displayed improved CIC (33.3% vs. 0% SSD) compared to Group 2 (29.1%). OSDI and NIF-BUT scores improved in both groups (p < 0.001). Only Group 1 showed improved NIAvg-BUT and Schirmer’s test scores (p < 0.001), while Group 2 did not (p > 0.05). MMP-9-positive subjects shifted from 25% to 91.6% in Group 1 and 87.5% to 20.8% in Group 2 after the follow-up. Conclusion: The topical formulation containing helenalin from Arnica montana and hyaluronic acid is well tolerated and has a good safety profile. Our formulation reduces DED sympto-matology and modulates the ocular surface inflammatory process; this is evidenced by the en-hancement of CIC, the improvement of DED-related tear film status, and the reduction of MMP-9 positivity rate.

Circular Economy (CE) is a growing topic among scholars, industry and government aiming at decoupling economic growth and development from the consumption of finite resources. CE incorporates different meanings, from reduce, reuse and recycle activities to environmental degradation or resource scarcity, and supported by specific indicators to attain sustainable development. However, so far, there has been no agreement to measure how effective an industry/product is in making the transition from linear to circular approaches, particularly those affected the society. This research work aims to perform a systematic literature review (n=60) to analyze and discuss how social aspects have been considered and integrated in the CE research so far. Moreover, this review provides and overview of the literature on social impact within CE, that resulted in three main outputs: a knowledge map of the CE, an analysis of social aspects within CE, and the theories/frameworks used to evaluate social impact of CE. Finally, this study brings to light how CE implementation can affect society and highlights the importance of social dimension in the domains of CE and policy-making community, which could help moving CE towards a sustainable development.

The licensing of talimogene laherparepvec (T-Vec) represented a landmark moment for oncolytic virotherapy, since it provided unequivocal evidence for the long-touted potential of genetically modified replicating viruses as anti-cancer agents. Whilst T-Vec is promising as a locally delivered virotherapy, especially in combination with immune-checkpoint inhibitors, the quest continues for a virus capable of specific tumour cell killing via systemic administration. One candidate is oncolytic adenovirus (Ad); it’s double stranded DNA genome is easily manipulated and a wide range of strategies and technologies have been employed to empower the vector with improved pharmacokinetics and tumour targeting ability. As well characterised clinical and experimental agents, we have detailed knowledge of adenoviruses’ mechanisms of pathogenicity, supported by detailed virological studies and in vivo interactions. In this review we highlight the strides made in the engineering of bespoke adenoviral vectors to specifically infect, replicate within, and destroy tumour cells. We discuss how mutations in genes regulating adenoviral replication after cell entry can be used to restrict replication to the tumour, and summarise how detailed knowledge of viral capsid interactions enable rational modification to eliminate native tropisms, and simultaneously promote active uptake by cancerous tissues. We argue that these designer-viruses, exploiting the viruses natural mechanisms and regulated at every level of replication, represent the ideal platforms for local overexpression of therapeutic transgenes such as immunomodulatory agents. Where T-Vec has paved the way, Ad-based vectors now follow. The era of designer oncolytic virotherapies looks decidedly as though it will soon become a reality.

Applying a procedure similar to that of E.S. Bring, by using a 4^th degree Tschirnhaus transformation, it was possible to transform the Bring-Jerrard normal quintic (BJQ) equation into a De Moivre form (DMQ), so that it could be solved by radicals. The general solution by radicals of the De Moivre equations of any degree is presented. By the same procedure the BJSx (normal sextic) equation was taken to another one without the 2^nd, 4^th and 6^th terms which was transformed into a cubic (solvable) equation. By applying a 6^th degree Tschirnhaus transformation to the BJSp (normal septic) equation its binormal (without the 2^nd, 3^rd, 4^th and 5^th terms) form was obtained.

Applying a procedure similar to that of E.S. Bring, by using a 4^th degree Tschirnhaus transformation, it was possible to transform the Bring-Jerrard normal quintic (BJQ) equation into a De Moivre form (DMQ), so that it could be solved by radicals. The general solution by radicals of the De Moivre equations of any degree is presented. By the same procedure the BJSx (normal sextic) equation was taken to another one without the 2^nd, 4^th and 6^th terms which was transformed into a cubic (solvable) equation. By applying a 6^th degree Tschirnhaus transformation to the BJSp (normal septic) equation its Bring-Jerrard binormal (without the 2^nd, 3^rd, 4^th and 5^th terms) form was obtained.

In South Sudan, three case-control studies found a positive association between Nodding Syn-drome (NS) and a Mansonella perstans infection. To investigate whether M. perstans could play the primary and sole causal role in the development of NS, we examined blood films of persons with and without epilepsy in rural villages affected by NS in Mahenge, Tanzania, to identify M. perstans infections. Study participants were also examined for onchocercal nodules and skin lesions and tested for the presence of anti-O. volvulus antibodies (Ov16 ELISA). One hundred and thirteen epilepsy cases and 132 controls were enrolled, with a mean age of 28.3 years (interquartile range 22 – 34 years); 125 (51%) were females. Of the persons with epilepsy, 43 (38.1%) met the probable NS criteria. M. perstans infection was absent in all participants, but Ov16 prevalence and oncho-cerciasis-associated skin manifestations were positively associated with epilepsy, including probable NS. Onchocercal nodules in the mothers of cases were also positively associated with epilepsy. In conclusion, in contrast with O. volvulus, M. perstans is likely not endemic in Mahenge and therefore cannot be a co-factor for NS in the area. Hence, this filaria cannot be the primary and sole causal factor in the development of NS.

This paper presents additional results of the generalized bathtub model for urban networks, including a simpler derivation and exact solutions for uniformly distributed trip lengths. It is shown that in steady state this trip-based model is equivalent to the more parsimonious accumulation-based model, and that the trip-length distribution has merely a transient effect on traffic dynamics, which converge to the same point in the macroscopic fundamental diagram (MFD). To understand the statistical properties of the system, a queueing approximation method is proposed to compute the network accumulation variance. It is found that (i) the accumulation variance is much larger than predicted by traditional queueing models, due to the nonlinear dynamics imposed by the MFD, (ii) the trip-length distribution has no effect on the accumulation variance, indicating that the proposed formula for the variance might be universal, (iii) the system exhibits critical behavior near the capacity state where the variance diverges to infinity. This indicates that the tools from critical phenomena and phase transitions might be useful to understand congestion in cities.

Starch is a biopolymer with wide potential for the generation of new biodegradable packages due to its high availability and low price. However, due to its weak functional properties, it is necessary to limit the interaction of some hydroxyl, and to evaluate blends with other polymers to improve their performance. Glycerol plasticized acetylated corn starch films were developed by the casting method, and the impact of incorporating chitosan (TPS:CH) at various proportions (75:25, 50:50, and 25:75 v/v) was studied. The effect of the chitosan ratios on the films' physical, mechanical, water vapor barrier, and thermal properties was evaluated. Chitosan protonated amino groups promote the formation of intermolecular bonds, improving the tensile strength, the thermal stability, the water adsorption capacity, and the gas barrier of starch films. Where the film composed of TPS25-CH75 was the one that presented the best barrier to water vapor. These composite films are a good option for development of biodegradable packaging.

The Chagas disease (CD) is an endemic infectious disease in a large part of Latin America. This disease is characterized by the fact of being caused by the parasite Trypanosoma cruzi. Some symptoms of this disease are cardiopathies and gastrointestinal problems. Therefore, the commonly used treatment consists of nitro drugs such as benznidazole and nifurtimox, which target the nitroreductase enzyme that docks to the coenzyme flavin mononucleotide (FMN) and an oxidation-reduction reaction is generated. From this reaction, the nitro chemical function of benznidazole and nifurtimox is reduced to amine. This amine in turn interacts with the parasite´s DNA. In vitro tests experimentally help in the study of the parasite resistance to the drug benznidazole. This fact could explain how nonsynonymous mutations in the nitroreductase (NTR) enzyme do not allow the anchorage of the FMN coenzyme and as a consequence the parasite susceptibility to benznidazole decreases as the drug cannot be reduced. The structural relations from the hybrid Quantum Mechanics-Molecular Mechanics (QM/MM) allow to detect the small changes generated in the system, considering a charge distribution associated with the structure, angle changes, interaction distances, potential surface calculations between the wildtype enzyme and the mutation found.

With the current increase in the demand from animal and agricultural products, management of agrowaste has become critical to avoid greenhouse gas emissions. The present article investigates the applicability of ammonium bicarbonate synthesis via flash distillation to valorize and stabilize several types of anaerobic digestate produced from individual fermentations of amino acids. Prior to the development of the model in Aspen Plus v12, the description of the system aqua-ammonia-carbon dioxide provided by the electrolyte non-random two-liquid property method was validated with empirical data available in the literature. The content of CO₂ in the digestate was found to be responsible of the OH alkalinity (0.4 equivalents of acid/kg digestate), while the partial and total alkalinities (0.8 eq/kg digestate) were essentially derived from the content of NH₃. The most suitable conditions for the flash distillation were 95 ⁰C and 1 bar with the condensation occurring at 25 ⁰C. However, in order to attain the precipitation of NH₄HCO₃ in the distillate, it was necessary to consider digestates with a moisture content of 50 wt.%, since the minimum levels of inorganic nitrogen and inorganic carbon were not attained otherwise. Even under these conditions, few amino acids (i.e. arginine, glycine, and histidine) were able to provide an anaerobic digestate, upon fermentation, that would be suitable for NH₄HCO₃ stabilization. Despite alanine digestate and glutamine digestate presented sufficient concentrations of inorganic nitrogen and inorganic carbon, the NH₄HCO₃-stabilization was not feasible due to the limited volatilization of NH₃. The process of stabilization with a capacity of a tonne of digestate per hour was improved by adding hydrochloric acid or sodium hydroxide at rates 44 kg/h, leading to production of 34 kg NH₄HCO₃/h. The economic viability of this process needs to be investigated considering not only the market value of the isolated inorganic fertilizer but the carbon credits saved, resulting from handling a more stabilized organic manure. Furthermore, given the role of the volatile elements of the biogas as endogenous stripping agents, it is recommended to use a fresh and saturated digestate as feed for the flash distillation.

We have much to learn from historic buildings. The fact that they are still standing is obvious, but unfortunately often not appreciated. In this paper the results obtained from a series of parametric analyses, where the influence that geometric and mechanical parameters have in the structural response of existing cob walls within an Irish context, are presented. A design of experiments using central composite designs was implemented along with analysis of variance following two computational approaches, namely, finite element method and kinematic limit analysis. As results, a series of response surfaces and parametric equations with which it is possible to compute safety factors and collapse multipliers (within the range of values studied) are provided. Based on the results obtained, it could be concluded that traditional cob walls in Ireland are very robust. Relatively high acceleration values, unlikely to happen in a low seismic hazard region such as Ireland, would be needed to start the collapse mechanisms studied or cause yielding in typical vernacular cob walls. Furthermore, the equations generated with the refined regression models, can be used by practitioners as a first approach to estimate the safety levels of existing cob buildings with similar characteristics.

In ref. [1], we pointed out that certain anomalies observed in the published data for ac magnetic susceptibility of a room temperature superconductor reported in Nature 586, 373 (2020) [2] would be cleared up once the measured raw data were made available. Part of the measured raw data were recently posted in arXiv:2111.15017 [3]. Here we report the results of our analysis of these raw data and our conclusion that they are incompatible with the published data. Implications of these results to the claim that the material is a room temperature superconductor are discussed.

Apple snails of the genus Pomacea (Mollusca: Caenogastropoda: Ampullariidae) are native to the Neotropics and exhibit high species diversity. They hold cultural and ecological significance, serving as an important protein source in Peru. However, this genus has also received broad interest worldwide due to its invasive capacity, especially in Southeast Asia, where some species such as Pomacea canaliculata (Lamarck, 1822) and P. maculata Perry, 1810 are considered significant pests. Consequently, most genetic studies have focused almost exclusively on these invasive species. In contrast, few efforts have been made to understand the evolutionary relationships of the South American native species, especially at the genomic level. In this study, we assembled and annotated the mitochondrial genome of two Pomacea species native to the Peruvian Amazon: Pomacea reevei Ampuero &amp; Ramírez, 2023 and P. aulanieri (Deville &amp; Huppé, 1850). Through a comprehensive comparison with available mitogenomes on NCBI, we found that the length and organization of these mitogenomes fall within the range of what is currently known in Pomacea. Comparisons between these mitogenomes with those previously published revealed differences in the overlapping of adjacent genes, the size of certain protein-coding genes (PCGs) and the secondary structure of some tRNAs which are consistent with the phylogenetic relationships between these species. These findings provide valuable insights into the systematics and genomics of the genus Pomacea.

Participatory landscape conservation is an innovative approach that weaves theory and practice to bridge the gap between theoretical models and practical applications. Intertropical regions as the case of Mexico face challenges to conciliate regional governability, social justice, and nature conservation. The State of Michoacan is one of these regions where the challenges exacerbate since nature conservation is last due to its ongoing territorial disputes. We implemented the participatory landscape conservation approach by creating a complementary form of protected areas with ongoing conflicts, drought conditions, and extreme poverty. We conducted participatory mapping and land cover/use analyses as main methodological tools to reach consensus among stakeholders. We integrated, macro, micro and social scales to provide sound arguments to integrate local, scholar and policy makers perceptions. The outcomes of the participatory mapping analyses were assessed. The present papers provide evidence of the positive outcome of using a Participatory Landscape Conservation to establish a Biosphere Reserve, safeguarding one of the most biologically diverse and delicate ecosystems consisting of seasonally dry tropical forests within a rather disputed region. We discussed the relevance of our findings and compared them to ongoing regional and global trends in the light of other forms of establishing protected areas.

A common fault in turbomachinery is rotor--casing rub. Shaft vibration, measured with proximity probes, is the most powerful indicator of rotor-stator rub. However, in machines such as aeroderivative turbines, with increasing industrial relevance in power generation, constructive reasons prevent the use of those sensors, being only acceleration signals at selected casing locations available. This implies several shortcomings in the characterization of the machinery condition, associated with a lower information content about the machine dynamics. In this work we evaluate the performance of the Continuous Wavelet Transform to isolate the accelerometer signal features that characterize rotor-casing rub in an aeroderivative turbine. The evaluation is carried out on a novel rotor model of a rotor flexible casing system. Due to damped transients and other short-lived features that rub induces in the signals, the Continuous Wavelet Transform proves being more effective than both Fourier and Cepstrum Analysis. This creates the chance for enabling early fault diagnosis of rub before it may cause machine shutdown or damage.

Forty-five male Dorper crossbred lambs (40.17 ± 0.35 kg BW) were used in order to investigate the effects of the duration of calcium propionate (CaPr) supplementation in lambs finished with zilpaterol hydrochloride (ZH) on the productive performance, carcass characteristics, and meat quality. Lambs were individually housed and fed a finishing-diet for 42 d before being slaughtered. Lambs received the following treatments: 1) No additives (CTL), 2) ZH supplementation for 28 d (with 3 d ZH withdrawal before slaughter) at a dosage of at 7.2 mg/kg diet (ZH), for treatments 3, 4, and 5, lambs received ZH and 10g CaPr/lamb/d throughout the entire phase (42 d), or during the last 28 or 14 d before slaughter. Compared to CTL, ZH lambs exhibited a similar average daily gain (ADG) but had lower dry matter intake (DMI), leading to increased feed efficiency. Supplementing with ZH alone did not affect carcass traits, visceral mass, whole cuts, or meat quality. Lambs that received both CaPr and ZH exhibited quadratic increases (p &lt; 0.05) in final BW (FBW), ADG, and dressing percentage (D%). These increases were optimal at an estimated inclusion durations of 26 d for FBW, 30 for ADG, and 39 d for D%. The ADG:DMI ratio and the longissimus muscle area (LMA) both exhibited quadratic increases (p &lt; 0.05). The optimal duration of CaPr supplementation for ADG:DMI ratio was found to be 28 d, while for LMA, it was 14 d. As the period of CaPr supplementation increased, there was a linear increase (p &lt;0.05) in hot carcass weight, leg circumference, and whole cuts of breast IMPS209 and shoulder IMPS207. Cook loss percent increased quadratically (p &lt; 0.05), being higher when CaPr was included for an estimated duration of 26 d. As the duration of CaPr supplementation increased, the purge loss percentage (PLR) also increased linearly (p &lt; 0.05). In conclusion, including CaPr in the diet for a duration of 28 d in lambs improved the response to ZH supplementation on the productive performance, carcass weight and some whole cuts. However, it can also have a negative effect on PRL%.

Less than half of e-waste plastics is sorted worldwide and this rate is likely to decline as major processing countries have banned importation of e-waste plastics. This forces the development of decentralized processing facilities, also known as microfactories. The present work investigates the recyclability of different grades of acrylonitrile-butadiene-styrene (ABS) copolymer, polycarbonate, and polypropylene, which were found to be very abundant in a recycling site in the UK. The determination of the matrix relied on the resin identification code imprinted in the e-waste plastic and subsequent FTIR analysis. The melt-blend extrusion technology enabled the valorization of the wasted thermoplastics as 3D filament without significant degradation of the polymers. The recycled materials maintained the tensile strength around 2.5 MPa in agreement with the specifications offered by virgin polymers. Further characterization was done by means of laser microscope, thermogravimetric analysis, and XRF to determine the commercial viability of the recycled filament. A modified solvent-based method was developed with acetone to remove the brominated flame retardants: 25g/100mL, 30 minutes of contact time, and 4 extraction steps. The FTIR results show that the degradation of the rubbery dispersed phase corresponding to the butadiene can be accumulated in the less soluble fraction of the waste ABS.

Cloud platforms are widely employed in today's educational context to enhance collaborative learning and the overall quality of the teaching-learning process. In 2016, Nextcloud was im-plemented in the Faculty of Chemical Engineering at the Technological University of Havana "José Antonio Echeverría" (CUJAE), Cuba. Subsequently, an evaluative phase was conducted to ensure the continuous development of the platform. The objective was to assess the use and ac-ceptance of the Nextcloud platform from the perspective of students and professors in the Fac-ulty. An exploratory, non-experimental, and cross-sectional study was conducted. Data was col-lected through observation and a survey. Matomo Analytics tool was employed for observation, revealing low visitation numbers. The survey was based on the Unified Theory of Acceptance and Use of Technology model. Better results were obtained in positive acceptances compared to negative ones, both for professors and students. It is concluded that the evaluation of the Next-cloud platform is infrequently used by users; however, there were higher positive acceptances than negatives from the perspectives of both students and professors.

In the area of health, namely hospitals, we can agree that the intrinsic need to have multidisciplinary teams, highly specialized and indispensable resources leads us to a degree of complexity that requires, daily, the best performance, not running away from the logistics area to the rule. The centralization of resources, namely distribution warehouses, emerges as a challenge and possible solution for health institutions to respond in the best possible way to their main purpose: to put the right material in the right place at the right price in the right time space. As regards the advantages of this type of organization, there are several authors who argues that the need for human resources training, ease of coordination and the use of economies of scale are the main advantage. As far as the disadvantages are concerned, there is no special agreement on them, there are disparate factors from author to author, such as: routine, centralization, objectives or operation costs.

Natural products (NPs) are a rich source of structurally novel molecules, and the chemical space they encompass is far from being fully explored. Over history, NPs have represented a significant source of bioactive molecules and have served as a source of inspiration for developing many drugs on the market. On the other hand, computer-aided drug design (CADD) has contributed to drug discovery research, mitigating costs and time. In this sense, compound databases represent a fundamental element for the CADD. This work reviews the progress toward developing compound databases of natural origin, particularly databases developed in Latin America, and their practical applications in the drug discovery area. We also survey the computational methods, emphasizing chemoinformatic approaches to profile natural product databases.

Abstract: Understanding the reliability and sensitivity of jump testing is essential to determine the neuromuscular progress of athletes and make informed decisions. This study aimed to assess the reliability and sensitivity of countermovement jump (CMJ) and drop jump (DJ) tests metrics in female volleyball players. Sixteen semi-professional female volleyball players participated in the study. Intrasession and intersession reliability of CMJ and DJ metrics were evaluated using a randomized cross-over design. Dual force platform was used to collect data, and several dependent variables were calculated using forward dynamics. Intraclass correlation coefficients (ICC), coefficients of variation (CV) and minimum difference (MD) were calculated. The third attempt presented the highest values for both test, and changes in jump strategy in DJ. CMJ is consistent across sessions, while DJ also shows intersession differences (p<0.05) in 11 out of 15 variables. Most CMJ variables exhibit excellent reliability while DJ variables have lower reliability and higher variability. Concentric and eccentric impulses for DJ showed excellent reliability. Most CMJ variables showed excellent reliability and variability, DJ had lower reliability, higher variability, and lower sensitivity. These findings provide valuable information when assessing athletes' performance and highlight the reliability, sensitivity, and variability in jump performance for CMJ and DJ tests.

Education 4.0 postulates the flexible combining of digital literacy, critical thinking, and problem-solving in training environments linked to real-world scenarios. Therefore, teachers are challenged to find or develop new methods and resources to integrate into their curricula to help students develop these desirable and necessary skills; hence, the question: What are the characteristics of a teacher to consider within the framework of Education 4.0? This article presents a study carried out in a higher education institution in Ecuador. The objective was to identify the teaching profile required in new careers within the framework of Education 4.0. The descriptive, exploratory methodology applied quantitative and qualitative instruments (surveys) to 337 undergraduate students in education careers and 313 graduates. It also included interviews with 20 experts in the educational field and five focus groups with 32 rectors, school principals, university professors and specialists in the educational area. The data was triangulated, and the results were categorized in (a) processes as facilitators (b), soft skills, (c) human sense and (d) use of technologies. This article may be of value to administrators, educational and social entrepreneurs, trainers, and decision-makers interested in implementing innovative training programs.

The strong couplings among ecological, economic, social and technological processes explains the complexification of human-made systems, and phenomena such as globalization, climate change, the increased urbanization and inequality of human societies, the power of information, and the COVID-19 syndemics. Among complexification’s essential features are non-decomposability, asynchronous behavior, components with many degrees of freedom, increased likelihood of catastrophic events, irreversibility, nonlinear phase spaces with immense combinatorial sizes, and the impossibility of long-term, detailed prediction. Sustainability for complex systems implies enough efficiency to explore and exploit their dynamic phase spaces and enough flexibility to coevolve with their environments. This in turn means solving intractable nonlinear semi-structured dynamic multi-objective optimization problems, with conflicting, incommensurable, non-cooperative objectives and purposes, under dynamic uncertainty, restricted access to materials, energy and information, and a given time horizon, aiming at enhancing the co-evolutionary power of the Biosphere and its human subsystems. Giving the high-stakes, the need for effective, efficient, diverse solutions, their local-global, present-future effects, and their unforeseen short, medium and long-term impacts, achieving sustainable complex systems implies the need for Sustainability-designed Universal Intelligent Agents, harnessing the strong functional coupling between human, artificial and nonhuman biological intelligence in a no-zero-sum game to achieve sustainability.

The wave energy converter (WEC) technology constantly develops new designs and models. To encourage its development within the energy sector, research is required to improve current designs and create durable and effective devices. However, it is also crucial to investigate the suitability of a WEC to a site-specific sea condition as this can impact its optimal power absorption and constructability. This study evaluates and compares the efficiency of a heaving buoy with varied geometries in one of the most energetic places along the Mexican coast. A statistical analysis of the wave climate on the coast of Ensenada during the last 42 years is performed to define the conditions to which the device is subjected. The location of the WEC in shallow waters is chosen using a computational model which solves the modified mild slope equation in its elliptic shape. The heaving buoy floater is studied using three distinct geometries: a semi-sphere, a cylinder, and a proposed rounded semi-rectangle. The hydrodynamic response of the three geometries is then analysed in the frequency and time domain using ANSYS AQWA. The hydrodynamic study involves the assessment of the floating body dynamics, exerted forces, the power absorbed as well as the suitability of the proposed power take-off (PTO) system. Findings reveal that the proposed geometry absorbs the most energy, with an annual power of 135.11 MW, and that the transmission PTO design is appropriate for this type of technology.

One mechanism by which fructose could exert deleterious effect in metabolism and inflammation is via its potency vis-à-vis de Maillard reaction. We employed simulated stomach and duodenum digestion of ovalbumin to test the hypothesis that indeed AGEs are formed by fructose during simulated digestion of an ubiquitous food protein with intrinsic allergenic potential and under model physiological conditions. Methods: OVA was subjected to simulated gastric and intestinal digestion using standard models, in presence of fructose or glucose (0-100 mM). Peptide fractions were analyzed by fluorescence spectroscopy and intensity at Excitation: λ370 nm, Emission: λ 440nm. Results: AGE adducts form between fructose and OVA which can be found in peptide fractions (< 5 kDa) at times (30 min) and concentration ranges (10 mM) plausibly found in the intestines, whereas no reaction occurs with glucose. The reaction is inhibited by chlorogenic acid at concentrations compatible with those found in the gut. The reaction is inhibited by AG, a specific antiglycation agent. Conclusion: Our proof of principle study shows that fructose-AGE formation on an ubiquitous allergenic protein indeed occurs in one hour and thereby may pave the way for the study of yet another mechanism by which the excess fructose in our Western diets is contributing to disease: intestinal AGE formation, absorption and RAGE engagement.

This document evaluates the impact of computer use on wages in Colombia in 2018. For this analysis, a Propensity Score Matching model is used to evaluate the impact of the use of learning technologies on the wages and years of education of Colombians, based on the 2018 quality of life survey. The results show that the use of the computer, laptop, tablet, internet, transferred files, Excel and radio for learning have a positive impact on the wages of Colombians. This research allows a better understanding of the technological effects on wages and provides information for the design of public policies in the development of technological skills.

This paper has a twofold objective. The first aim is to present a comprehensive bibliographical analysis of journal articles and book chapters on fuzzy-random option pricing (FROP) over the WoS and SCOPUS databases. It follows PRISMA criteria and takes special care of developments in continuous time. Thus, we described the principal findings about the research streams, outlets and authors of this topic and lets us suggest further research. The second contribution is motivated by the fact that the bibliographical revision has identified a lack of developments on equilibrium models on the yield curve. This question motivates extending Vasicek’s yield curve equilibrium model to introduce fuzziness in the parameters that govern interest rate movements (speed of reversion, equilibrium short-term interest rate, and volatility). Likewise, this paper develops an empirical application on the term structure of fixed income public bonds with the highest credit rating in the Euro area.

Vulvovaginal candidiasis (VVC) is a prevalent condition affecting women worldwide. This study aimed to develop a rapid qPCR assay for accurate identification of VVC etiological agents and reduced azole susceptibility. One hundred and twenty nine vaginal samples from an outpatient clinic (Bilbao-Spain) were analyzed using culture-based methods and multiplex qPCR targeting fungal species, Candida albicans being the predominant species. Antifungal susceptibility tests revealed reduced azole susceptibility in three (3,48%) isolates. Molecular analysis identified several mutations in genes associated with azole resistance and novel mutations in TAC1 and MRR1 genes were also identified, which could contribute to drug resistance.

Rural women constitute one of the most marginalized and vulnerable groups in the world. Despite playing a critical role in sustainable development and food security, they face systemic inequalities and structural constraints that limit their access to resources, services and opportunities. The purpose of this research is to identify advances and setbacks in the formulation of 17 SDG indicators for rural women. Systematic Review Registered in PROSPERO: CRD42023420583. Sixteen articles were included. Three indicators were identified: entrepreneurship, empowerment and gender equality. Due to its relevance in rural areas where women have an active role in family income through cooperatives, associations and companies to improve quality of life and that of their community, however, aspects of discrimination are still evident in gender and inequality in participation in economic spheres and decision making.

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.

Biodiversity conservation questions human practices towards biodiversity and, therefore, largely conflicts with ordinary societal aspirations. Decisions on the location of protected areas, one of the most convincing conservation tools, reflect such a competitive endeavor. Operations Research (OR) brings a set of analytical models and tools capable of resolving the conflicting interests between ecology and economy. Recent technological advances have boosted the size and variety of data available to planners, thus challenging conventional approaches bounded on optimized solutions. New models and methods are requested to use such a massive amount of data in integrative schemes addressing a large variety of concerns. Here, we provide an overview on the past, present and future challenges that characterize spatial conservation models supported by OR. By enlarging the spatial, temporal, taxonomic and societal horizons of biodiversity conservation planners navigate around multiple bio-socioeconomic equilibria and are able to decide on cost-effective strategies to improve biodiversity persistence.

The main point in the present article was the comparison of the Technical Efficiency (TE) in four years for milk production in Ecuador by the period 2018 – 2021, before and after the pandemic, and the determination of the factors related to the TE for the last year. The information from the official public database in the country were analyzed by the nonparametric technique called DEA including a bootstrap simulation. Once different variables were selected including aspects as livestock and labor, the TE with Variable Returns to Scale (VRS) with “output” orientation was calculated by each year and province. Among the provinces, statistically significant differences were found (P<0.1) for the TE means, and most of the efficient units were found throughout the Andean zone, in each year. Between the most important findings, it was important that the TE average after the beginning of the pandemic was statistically lower than the last 3 consecutive years under study (P<0.1) with 3% approximately of decrease, and the main factors related to this were multiple including labor characteristics, the field composition, and the supplies access during the pandemic. Finally, some implications for public policy were found around the gender in agriculture activities, the social security, and the difficulties in supplies access.

Background: It is well known the adverse effect of mercury exposure on pregnant women and newborns. Interactions between environmental factors and individual genetic susceptibility have been identified, particularly polymorphisms of codifying genes for the Glutathione S-transferase family (GSTs). Herein, we report a case series of patients with high Hg levels in biosamples. Case Series: Fourteen cases with high Hg levels were identified. Non-occupational or home exposure risk factors were identified. All mothers reported fish consumption during pregnancy. Almost 60% of the individuals were null for either one GSTs gene. To date, in the subsequent mother-child pairs toxicology controls no signs or symptoms of poisoning were identified and most of the mercury levels decreased and are below the accepted limit. Discussion: In this case series we found some similarities with the literature; among them, the relation of Hg ratio in maternal blood and umbilical cord, a possible exposure factor is the consumption of fish during pregnancy and, the high levels of Hg may be related with susceptibility biomarkers such as GSTs gene polymorphisms. This case series highlights the need to develop studies that evaluate the interactions between environmental factors and individual genetic susceptibility. Additionally, the importance of evaluating which Colombian fish species present the highest levels of Hg.

Hyperspectral images are an important tool to assess ecosystem biodiversity both on terrestrial and benthic habitats. To obtain more precise analysis of biodiversity indicators that agree with indicators obtained using field data, analysis of spectral diversity calculated from images have to be validated with field based diversity estimates. The plant species richness is one of the most important indicators of biodiversity. This indicator can be measured in hyperspectral images considering the Spectral Variation Hypothesis (SVH) which states that the spectral heterogeneity is related to spatial heterogeneity and thus to species richness. The goal of this research is to capture spectral heterogeneity from hyperspectral images for a terrestrial neo tropical forest site using Vector Quantization (VQ) method and then use the result for prediction of plant species richness. The results are compared with that of Hierarchical Agglomerative Clustering (HAC). The validation of the process index is done calculating the Pearson correlation coefficient between the Shannon entropy from actual field data and the Shannon entropy computed in the images. Terrestrial dry forest and marine coastal hyperspectral images with different resolutions have been used for spectral diversity feature validation.

Earthworms are iteroparous organisms with indeterminate growth, i.e. they continue to increase in size throughout their life and after completion of sexual development. Terrestrial oligochaetes vary greatly in size. Depending on the species, adult earthworms can reach between 10 mm and 3 m in length and between &lt;1 mm and &gt;25 mm in width, with most being of length 5-15 cm. Among the more than 7000 species described to date, very few (~20) reach lengths greater than 1 m. The longest earthworm on record is Amynthas mekongianus, which is found in the mud banks of the Mekong River in Southeast Asia and which reaches almost 3 m in length. It is about the same size as Megascolides australis, the ‘Giant Gippsland Earthworm’. These atypically giant earthworm species remain a scientific curiosity in terms of their biology, but they cannot be considered cases of gigantism. Gigantism occurs when organisms are much larger than normal or exhibit excessive growth. Earthworms obtain energy from the organic matter on which they feed, and their growth mainly depends on the quality of the resource and on the species, as well as on food availability, environmental factors, which can directly or indirectly affect growth by modifying food availability, and other factors such as competition. This is particularly evident in earthworms, which display indeterminate growth and large species-dependent variations in size. The biology, life cycle and growth and reproduction rates of Eisenia fetida (Savigny 1826) and Eisenia andrei (Bouché 1972), the earthworm species most commonly used in vermicomposting and vermiculture, have been widely reported. Here we present details of the enormous growth of individual specimens of Eisenia andrei and Dendrobaena hortensis reared under particular culture conditions and fed a special diet. Individuals almost 20 times the average weight of individuals of the species have been obtained. Possible explanations for this interesting phenomenon are discussed.

It was recently shown that urban networks might exhibit two different critical points, one for the percolation of congested links through the network, and another one for the flow of vehicles through the network. It was observed that the percolation critical point happens after the flow critical point, where network throughput is maximized. This result is important because if a causal relationship exists between these two processes, it can be leveraged for improving control methods to avoid network collapse. This paper presents the results of numerical experiments to understand the possible causal relationship between the percolation and flow processes by focusing on the relative timing between the two critical points. The goal is to understand the impacts of important factors such as: (i) urban network type: long- and short-block networks, (ii) signal timing control type: fixed, random, responsive, and (iii) route choice: turning proportions at intersections. We find that the threshold density $k^*_c$ to determine if a link is congested has the main impact on the timing of the percolation transition, where lower values trigger earlier transitions. This implies that $k^*_c$ can be set such that the percolation transition happens before the flow critical point, opening the door for improved congestion management strategies. If $k^*_c$ is set to the average network critical density, maximum network throughput happen simultaneously with the percolation transition. Surprisingly, it appears that these results, and more generally, the relationship between the percolation and flow processes is independent of (i) and (ii) above.

The importance of diet and the gut-brain axis for brain health and cognitive function is increasingly acknowledged. Dietary interventions are tested for their potential to prevent and/or treat brain disorders. Intermittent fasting (IF), the abstinence or strong limitation of calories for 12 to 48 hours, alternated with periods of regular food intake, has shown promising results on neurobiological health in animal models. In this review article, we discuss the potential benefits of IF on cognitive function and the possible effects on the prevention and progress of brain-related disorders in animals and humans. We do so by summarizing the effects of IF which - through metabolic, cellular and circadian mechanisms - lead to anatomical and functional changes in the brain. Our review shows that there is no clear evidence of a positive short-term effect of IF on cognition in healthy subjects. Clinical studies show benefits of IF for epilepsy, Alzheimer’s disease and multiple sclerosis on disease symptoms and progress. Findings from animal studies show mechanisms by which Parkinson’s disease, ischaemic stroke, autism spectrum disorder and mood- and anxiety disorders could benefit from IF. Future research should disentangle whether positive effects of IF hold true regardless of age or the presence of obesity. Also, variations in fasting patterns, total caloric intake and intake of specific nutrients may be relevant components of IF success. Longitudinal studies and Randomized Clinical Trials (RCTs) will provide a window into the long-term effects of IF on the development and progress of brain-related diseases.

Few Sclerophyllous plants from the central coast of Chile have been systematically studied. This work describes the phytochemical composition and antimicrobial properties of Baccharis concava Pers. (sin. B. macraei), a shrub found in the first line and nearby the pacific coast between latitudes 29-38⁰S. B. concava has been traditionally used by indigenous inhabitants of today central Chile for their anthelmintic properties, wound healing properties and as a diuretic. Hydro-alcoholic extracts of B. concava were prepared from leaves and small branches. The qualitative phytochemical characterization indicated presence of alkaloids, steroids, terpenoids, flavonoids, phenolic and tannins compounds. The antimicrobial activity of this extract was assessed in a panel of microorganisms including Gram-positive, Gram-negative bacteria and pathogenic yeasts. The extract displayed important antimicrobial effects against Gram positive, Candida albicans, and Cryptococcus neoformans, but not against Gram negative, for which an intact Lipopolysaccharide (LPS) is apparently the determinant of resistant to B. concava extracts. The hydroalcoholic extract was then fractionated through a sephadex LH-20/methanol-ethyl acetate column. Followed, the fractions were pooled according to a similar composition that was visualized by TLC/UV analysis. Fractions obtained by this criterion were assessed for their antimicrobial activity against Staphylococcus aureus. The fraction presenting the most antimicrobial activity was HPLC-ESI-MS/MS analyzed obtaining a composition rich in structures derived from caffeoylquinic acid, dicaffeoylquinic acid and quercetin, among others. In conclusion, the extracts of B. concava show a strong antimicrobial activity probably due to their composition rich in metabolites derived from caffeoylquinic acid and quercetin, that in turn could be responsible for helping with wound healing, as reported from its ancient cultural use. In addition, the development of antimicrobial therapies based in the molecules found in B. concava could help to combat infection caused by pathogenic yeasts and Gram-positive bacteria, without affecting the Gram-negative microbiota.

Current adaptive cruise control (ACC) systems adopt fixed desired time headway, which leads to an abrupt speed reduction after being cut-in by a lane changer in front or when changing lanes too close to the new leader. In contrast, human drivers behave differently and feature a variable spacing within 20 or 30 seconds right after a cut-in or lane change. Motivated by the smooth transition found in driver relaxation, the paper aims to incorporate relaxation into ACC systems. Based on the open-source ACC platform, Openpilot, Comma.ai, the paper proposes a feasible relaxation model compatible with current factory ACCs, which has also been tested using a market car with stock ACC hardware. The study further investigates the impact of relaxation ACC on traffic operation. Numerical simulation suggests that incorporating relaxation into ACC can help: i) reduce the magnitude of speed perturbations in both cut-in vehicles and followers; ii) stabilize the lane-changing traffic by reducing the speed variance and prevent the lateral propagation of congestion, and iii) increase the average vehicle speed and capacity in merging traffic.

(1) Background/Objectives: Accurate determination of chronological age is crucial in legal dental identification. This study aimed to compare the effectiveness of different formulas in estimating the age of a Brazilian subpopulation by analyzing the pulp/tooth ratio of the maxillary canine and mandibular second premolar in panoramic and periapical radiographs. (2) Methods: The sample consisted of panoramic and periapical radiographs of 247 individuals. The file of each radiograph was opened in the Adobe Photoshop CS4® program to outline and obtain values in pixels for calculating the pulp/tooth ratio. Statistical analysis was conducted using the SPSS program, with a significance level set at 5%. (3) Results: The interclass correlation coefficient demonstrated excellent intra-observer agreement (0.990 – 0.999). The determination coefficients (R2) suggested that only 30-35% of the actual age results could be explained by the pulp/tooth ratio. Smallest differences were observed with Cameriere's formula for the mandibular second premolar on panoramic radiographs (+4.1 years). The greatest differences were found with the formulas for the mandibular second premolar in panoramic radiographs of the Korean (+12.5 years) and Portuguese (-12.1 years) populations. (4) Conclusions: The equations employed allowed for estimating the age of a Brazilian subpopulation and showed little agreement between the actual age and the estimated age.

This paper presents a methodology to detect the erosion and progradation effects in the Atrato river delta, located in the Gulf of Urabá in Colombia using SAR (Synthetic Aperture Radar) data. Other authors have studied this area by using optical images, encountering difficulties given the persistent presence of clouds in this region. SAR imagery is rescaled, despeckled, composed, classified, registered and processed to obtain a heatmap that shows the overall changes during eight years (2016–2023) in one single image. Since this technology uses microwave active signals, the presence of clouds and other environmental phenomena was not a problem, and all the images from the selected dates could be processed and analyzed. Also, detection of the dynamic processes was obtained for every period considered in this study with respect to the previous one in time, calculating areas and detecting the regions subject to the erosion and progradation processes. The multitemporal analysis performed found that the newly created mouth is the most active area for these processes, coinciding with other studies. A comparison of these findings with the Oceanic Niño Index (ONI) showed a relative delayed coupling to the erosion process and a coupling of progradation with dry and wet seasons.

The present review provides an in-depth look into the complex topic of delimiting species in sea anemones. For most part of history this has been based on a small number of variable anatomic traits, many of which are used indistinctly across multiple taxonomic ranks. Early attempts to classify this group succeeded to comprise much of the diversity known to date, yet numerous taxa were mostly characterized by the lack of features rather than synapomorphies. Of the total number of species names within Actiniaria, about 77% are currently considered valid and more than half of them have several synonyms. Besides the nominal problem caused by large intraspecific variations and ambiguously described characters, genetic studies show that morphological convergences are also widespread among molecular phylogenies. On the contrary, spatial distribution has been emerging as a more reliable parameter to explain cryptic relationships among sea anemones. Integrative approaches and genome-wide data have been especially helpful to unveil the mechanisms behind the speciation process, which is typically marked by large genetic differences among populations, even from neighbouring localities. This paper further discusses current gaps in our knowledge and offers some future directions on how to address the issue of species delimitation in the extremely polymorphic group of sea anemones.

Audio recording in classrooms is a common practice in educational research, with applications ranging from detecting classroom activities to analysing student behaviour. Previous research has employed neural networks for classroom activity detection and speaker role identification. However, these recordings are often affected by background noise that can hinder further analysis, and the literature has only sought to identify noise with general filters and not specifically designed for classrooms. Although the use of high-end microphones and environmental monitoring can mitigate this problem, these solutions can be costly and potentially disruptive to the natural classroom environment. In this context, we propose the development of a neural network model that can specifically detect and filter out background noise in classroom recordings. This model would allow the use of lower quality recordings without compromising analysis capability, thus facilitating data collection in natural educational environments and reducing the costs associated with high-end recording equipment.

An exact solution for the Nagel-Schreckenberg model for v_max = 1 is known since the 90s, yet for v_max > 1 it remains an open question. It is conjectured here that this general solution can be generated from the basic solution (for v_max = 1) by a linear coordinate transformation, the shear mapping, which requires no additional parameters in the deterministic case, and two additional parameters otherwise. The proposed solutions show remarkable agreement with existing numerical solutions, except in the congested regime where the Monte Carlo data shows more concavity than the more linear congested branches predicted by the theory. More research is needed to investigate this bias.

Self-organized criticality (SOC) is a celebrated paradigm from the 90’s for understanding dynamical systems naturally driven to its critical point, where the power-law dynamics taking place make predictions practically impossible, such as in stock prices, earthquakes, pandemics and many other problems in science related to phase transitions. Shortly thereafter, it was realized that traffic flow might be in the SOC category, implying that conventional traffic management strategies seeking to maximize the local flows can become detrimental. This paper shows that the Kinematic Wave model with triangular fundamental diagram, and many other related traffic models, indeed exhibit SOC, thanks in part to the fractal nature of traffic exposed here on the one hand, and our need to get to our destinations as soon as possible, on the other hand. Important implications for congestion management of traffic near the critical region are discussed, such as: (i) Jam sizes obey a power-law distribution with exponent 1/2, implying that both its mean and variance become ill-defined and therefore impossible to estimate. (ii) Traffic in the critical region is chaotic in the sense that predictions becomes extremely sensitive to initial conditions. (iii) However, aggregate measures of performance such as delays and average speeds are not heavy tailed, and can be characterized exactly by different scalings of the Airy distribution, (iv) Traffic state time-space “heat maps” are self-affine fractals where the basic unit is a triangle, in the shape of the fundamental diagram, containing 3 traffic states: voids, capacity and jams. This fractal nature of traffic flow calls for analysis methods currently not used in our field.

The analogy between the theory of phase transitions in simple fluids and vehicular traffic flow has long been suspected, promising a new level of understanding of urban congestion by standing on one of the firmer foundations in physics. The obstacle has been the interpretation of the thermal energy of the gas-particle system, which remains unknown. This paper proposes the flow of cars through the network as a viable interpretation, where the fundamental diagram for traffic flow would be analogous to the coexistence curve in gas-liquid phase transitions. Thanks to the power-law form of the coexistence curve, it was possible to formalize that the resulting network traffic model belongs to the Kardar-Parisi-Zhang universality class. The scaling relationships arising in this universality class are found to be consistent with West's scaling theory for cities. It is shown that congestion costs (delays + fuel consumption) scale superlinearly with city population, possibly and worryingly more so than predicted by West's theory. Implications for sustainability and resiliency are discussed.

It has been suggested that the measured magnetic properties of hydrides under pressure claimed to be high temperature superconductors indicate that the materials are granular superconductors. Such materials will show reduced or no magnetic field expulsion under field cooling, and will trap magnetic fields when the external magnetic field is removed. They will also exhibit hysteretic behavior in magnetoresistance and other transport properties. Here we point out that hysteresis in transport properties has never been reported for hydrides under pressure. Its presence, with the expected features, would indicate that the materials trap magnetic flux, hence that they can sustain persistent currents without dissipation, something that all superconductors can do. Conversely, its absence would indicate that these materials are not superconductors.

In Ref. [1] Snider et al reported room temperature superconductivity in carbonaceous sulfur hydride (CSH) under high pressure. Recently the data for the temperature dependent ac magnetic susceptibility shown in figures of Ref [1] have appeared in the form of tables corresponding to different pressures [2]. Here we provide an analysis of the data for a pressure of 160 GPa. This work was performed in collaboration with D. van der Marel.

Applying a procedure similar to that of E.S. Bring, by using a 4^th degree Tschirnhaus transformation, it was possible to transform the Bring-Jerrard normal quintic (BJQ) equation into a De Moivre form (DMQ), so that it could be solved by radicals. The general solution by radicals of the De Moivre equations of any degree is presented. By the same procedure the BJSx (normal sextic) equation was taken to another one without the 2^nd, 4^th and 6^th terms which was transformed into a cubic (solvable) equation. By applying a 6^th degree Tschirnhaus transformation to the BJSp (normal septic) equation its binormal (without the 2^nd, 3^rd, 4^th and 5^th terms) form was obtained.

Room temperature superconductivity has recently been reported for a carbonaceous sulfur hydride (CSH) under high pressure by Snider et al [1]. The paper reports sharp drops in magnetic susceptibility as a function of temperature for five different pressures, that are interpreted as signaling a superconducting transition. Here I question the validity and faithfulness of the magnetic susceptibility data presented in the paper by comparison with the measured raw data reported by two of the authors of ref. [2]. This casts doubt on the assertion of the paper [1] that the susceptibility measurements support the case for superconductivity in this compound.

Applying a procedure similar to that of E.S. Bring, by using a 4^th degree Tschirnhaus transformation, it was possible to transform the Bring-Jerrard normal quintic (BJQ) equation into a De Moivre form (DMQ), so that it could be solved by radicals. The general solution by radicals of the De Moivre equations of any degree is presented. By the same procedure the BJSx (normal sextic) equation was taken to another one without the 2^nd, 4^th and 6^th terms which was transformed into a cubic (solvable) equation. By applying a 6^th degree Tschirnhaus transformation to the BJSp (normal septic) equation its binormal (without the 2^nd, 3^rd, 4^th and 5^th terms) form was obtained.

This paper shows that the percolation clusters from elementary cellular automata {30, 45, 60, 86, 99, 105, 129, 150, 153, 169, 182, 183, 184, 195 and 225 exhibit strong power law behavior, either under random initial conditions, a single occupied cell, or both. Most of the tail exponents are less than unity, implying diverging means and variances of cluster sizes. The analysis presented here is admittedly coarse in an effort to expedite its dissemination.

In this work, we investigated for the first time the complexation of sepiapterin (SP), the natural precursor of the natural essential cofactor tetrahydrobiopterin, that displays mild water-solubility and short biological half-life, with the hydrophobic triacetyl-β-cyclodextrin (TAβCD) to improve its encapsulation within methoxy-poly(ethylene-glycol)-poly(epsilon-caprolactone) (mPEG-PCL) nanoparticles. First, TAβCD-SP complexes were produced by spray-drying of TAβCD/SP binary solutions by utilizing the Nano Spray Dryer B-90 HP. Then, dry powders were characterized by differential scanning calorimetry (DSC), Fourier-transform infrared spectroscopy (FTIR) and transmission and scanning electron microscopy (SEM and TEM, respectively) and compared to the complex components and physical mixtures (PMs). Next, SP was encapsulated within methoxy-poly(ethylene-glycol)-poly(epsilon-caprolactone) (mPEG-PCL) nanoparticles by nanoprecipitation of a SP/TAβCD complex/mPEG-PCL solution. In addition to complex nanoencapsulation, we assessed encapsulation of pure SP by nanoprecipitation with an intermediate step, which comprised the co-drying of SP, TAβCD and mPEG-PCL copolymer solution in organic solvent; this step aimed to promote the formation of molecular interactions between SP, TAβCD and the PCL blocks in the copolymer. SP-loaded mPEG-PCL nanoparticles were characterized by dynamic light scattering (DLS) and SEM. Nanoparticles with size of 74-75 nm and small polydispersity index (PDI <0.1) were obtained when SP-TAβCD equimolar spray-dried complex was used for nanoencapsulation, and SEM analysis indicated the absence of free SP crystals. Moreover, the encapsulation efficiency (%EE) and drug loading (DL) were 85% and 2.6%, respectively, as opposed to those achieved with pure SP encapsulation (14% and 0.6%, respectively). Overall, our results confirm that spray-drying of SP/TAβCD solutions at the appropriate molar ratio leads to the hydrophobization of the relatively hydrophilic SP molecule, enabling its encapsulation within mPEG-PCL nanoparticles.

Floods are one of the most wide-spread, frequent, and devastating natural disasters that continue to increase in frequency and intensity. Remote sensing, specifically synthetic aperture radar (SAR), has been widely used to detect surface water inundation to provide retrospective and near-real time (NRT) information due to its high-spatial resolution, self-illumination, and low atmospheric attenuation. However, the efficacy of flood inundation mapping with SAR is susceptible to reflections and scattering from a variety of factors including dense vegetation and urban areas. In this study, the topographic dataset height above nearest drainage (HAND) was investigated as a potential supplement to Sentinel-1A C-Band SAR along with supervised machine learning to improve the detection of inundation in heterogeneous areas. Three machine learning classifiers were trained on two sets of features SAR only (VV & VH) and VV, VH & HAND to map inundated areas. Three study sites along the Neuse River in North Carolina, USA during the record flood of Hurricane Matthew in October 2016 were selected. The binary classification analysis (inundated as positive vs. non-inundated as negative) revealed significant improvements when incorporating HAND in several metrics including classification accuracy (ACC) (+37.1%), true positive rate (TPR) (+51.2%), and negative predictive value (NPV) (+23.7%), A marginal improvement of +1.4% was seen for positive predictive value (PPV), but true negative rate (TNR) fell -15.1%. By incorporating HAND, a significant number of areas with high SAR backscatter but low HAND values were detected as inundated which increased true positives. This in turn also increased the false positives detected but to a lesser extent as evident in the metrics. This study demonstrates that HAND could be considered a valuable feature to enhance SAR flood inundation mapping especially in areas with heterogeneous land covers with dense vegetation that interfere with SAR.

Inside hippocampal circuits, neuroplasticity events that individual cells may undergo during synaptic transmissions occur in the form of Long Term Potentiation (LTP) and Long Term Depression (LTD). The high density of NMDA receptors expressed on the surface of the dendritic CA1 spines confers to hippocampal CA3-CA1 synapses, the ability to easily undergo NMDA-mediated LTP and LTD, that is essential for some forms of explicit learning in mammals. Providing a comprehensive kinetic model that can be used for running computer simulations of the synaptic transmission process is currently a major challenge. Here, we propose a compartmentalized kinetic model for CA3-CA1 synaptic transmission. Our major goal was to tune our model in order to predict the functional impact caused by disease associated variants of NMDA receptors related to severe cognitive impairment. Indeed, for variants Glu413Gly and Cys461Phe, our model predicts negative shifts in the glutamate affinity and changes in the kinetic behavior, consistent with experimental data. These results pinpoint to the predictive power of this multiscale viewpoint, which aims to integrate the quantitative kinetic description of large interaction networks typical of system biology approaches with a focus on the quality of few, key, molecular interactions typical of structural biology ones.

Data from NASA’s Soil Moisture Active Passive Mission (SMAP) and from the California Cooperative Oceanic Fisheries Investigations (CalCOFI) were used to examine the freshening that occurred during 2015-2016 in the Southern California Current System. Overall the freshening was found to be related to the 2014-2016 Northeast Pacific Warm Anomaly. The primary goal was to determine the feasibility of using SMAP data to observe the surface salinity signal associated with the warming. As a first step direct comparisons were done with salinity from the CalCOFI data at one-meter depth. During 2015 SMAP was saltier than CalCOFI by 0.5 PSU, but biases were reduced to < 0.1 PSU during 2016. South of 33°N, and within 100 km of the coast, SMAP was fresher in 2015 by almost 0.2 PSU. CalCOFI showed freshening of 0.1 PSU. North of 33°N SMAP and CalCOFI saw significant freshening in 2016, SMAP by 0.4 PSU and CalCOFI by 0.2 PSU. Differences between SMAP and CalCOFI are consistent with the increased stratification in 2015 and changes in the mixed layer depth.

In addition to their importance in statistical thermodynamics, probabilistic entropy measurements are crucial for understanding and analyzing complex systems, with diverse applications in time series and one-dimensional profiles. However, extending these methods to two- and three-dimensional data still requires further development. In this study, we present a new method to classify spatiotemporal processes based on entropy measurements. To test and validate the method, we selected four classes of similar processes related to the evolution of random patterns: dynamic colored noises ((i)~white and (ii)~red); (iii)~weak turbulence from reaction-diffusion; (iv)~hydrodynamic fully developed turbulence, and (v)~plasma turbulence from MHD. Considering seven possible ways to measure entropy from a matrix, we present the method as a parameter space composed of the two best separating measures of the five selected classes. The results highlight better combined performance of Shannon Permutation Entropy ($S^p_H$) and a new approach based on Tsallis Spectral Permutation Entropy ($S^s_q$). Notably, our observations reveal the segregation of reaction terms in this $S^p_H \times S^s_q$ space, a result that identifies specific sectors for each class of dynamic process, and can be used to train machine learning models for automatic classification of complex spatiotemporal patterns.

Manufacturing corporations has the acceptance of the Outsourcing Process (OP) to improve industrial activities as well as to archive the revenue objectives, and with this, Risk Analysis (RA) tools are constantly used to assure expected results. Failure Mode and Effect Analysis (FMEA) is one of preferred RA tools, moreover, it is proven that FMEA adds uncertainty because of the human participation at the RA, afterward it is demonstrated that Pythagorean Fuzzy Dimensional Analysis – FMEA – Value Stream Mapping (PFDA-FMEA-VSM) method removes the uncertainty in RA, likewise it aids to the stakeholders for decision making, giving more advantages improving the use of the resources on the project. This document exhibits a real case scenario in a manufacturing firm applying PFDA-FMEA-VSM method adapted for manufacturing OP. The application of PFDA-FMEA-VSM shows solid RA results, removing the human intervention uncertainty added to the risk ranking, gives advantages to the stakeholders for visualize the main risks in detailed diagram, as well as make easier to take better decisions on where to apply resources and mitigate risks during OP.

With confirmed COVID-19 cases surpassing the 8.5 million mark around the globe, there is an imperative need to deepen the efforts from the international scientific community to gain comprehensive understanding of SARS-CoV-2. Although the main clinical manifestations are associated with respiratory or intestinal symptoms, reports of specific and non-specific neurological signs and symptoms, both at presentation or during the course of the acute phase, are increasing. Approximately 25-40% of the patients present neurological symptoms. The etiology of these neurological manifestations remains obscure, and probably involves several direct pathways, not excluding the direct entry of the virus to the Central Nervous System (CNS) through the olfactory epithelium, circumventricular organs, or disrupted blood-brain barrier (BBB). Furthermore, neuroinflammation might occur in response to the strong systemic cytokine storm described for COVID-19, or due to dysregulation of the CNS angiotensin system. Descriptions of neurological manifestations in patients in the previous coronavirus (CoV) outbreaks have been numerous for the SARS-CoV and lesser for MERS-CoV. Strong evidence from patients and experimental models suggests that some human variants of CoV have the ability to reach the CNS and that neurons, astrocytes and/or microglia can be target cells for CoV. A growing body of evidence shows that astrocytes and microglia have a major role in neuroinflammation, responding to local CNS inflammation and/or to dysbalanced peripheral inflammation. This is another potential mechanism for SARS-CoV-2 damage to the CNS. In this work we will summarize the known neurological manifestations of SARS-CoV-2, SARS-CoV and MERS-CoV, explore the potential role for astrocytes and microglia in the infection and neuroinflammation, and compare them with the previously described human and animal CoV that showed neurotropism. We also propose possible underlying mechanisms by focusing on our knowledge of glia, neurons, and their dynamic intricate communication with the immune system.

This paper investigates calendar anomalies, volatility patterns, and the best forecasting model for predicting volatility in the cryptocurrency market, focusing on ten prominent cryptocurrencies: Binance USD, Bitcoin, Binance Coin, Cardano, Dogecoin, Ethereum, Solana, Tether, USD Coin, and Ripple. Spanning from January 2016 to December 2023, the study utilizes sophisticated statistical models such as GARCH (p,q), EGARCH (p,q), and GJR-GARCH (p,q) to analyze precise changes in market dynamics and the impact of day-of-week fluctuations on cryptocurrency returns. Empirical evidence reveals significant findings regarding the persistence of volatility, positive and negative news effects on volatility, and day-of-week effects on cryptocurrency returns. Post-COVID-19, Sunday emerges as the least volatile day for cryptocurrencies, while Thursdays and Tuesdays exhibit greater volatility. Binance, Ethereum, Dogecoin, and Tether show anomalies where returns on Tuesday and Thursday significantly differed from those on other days of the week. Many other currencies, like the USD coin, Cardano, and Ripple, show anomalies only in the pre-COVID-19 period. The findings highlight the best forecast model for volatility for each top cryptocurrency, offering practical implications for investors, traders, regulators, and policymakers. These insights emphasize the importance of understanding and addressing calendar anomalies in the cryptocurrency market for informed decision-making, trading strategies, regulatory frameworks, and market stability.