Obesity is a complex chronic disease characterized by excess of body fat. It represents a significant public health problem due to the health-related risk factors. There are growing evidences showing that maternal obesity can program the offspring, which influence neonatal phenotype and predispose offspring to a higher prevalence of metabolic disorders such as obesity. This increased risk may also be epigenetically transmitted across generations. Thus, there is an urgent need to find effective reprogramming approaches in order to resume normal fetal development. Polyphenols are bioactive compounds found in fruits and vegetables that exert their anti-obesity effect through its powerful anti-oxidant and anti-inflammatory activities. Polyphenols supplementation has been proven to counteract the deleterious effects of maternal obesity programming on offspring. Indeed, some polyphenols can cross the placenta and protect the fetal predisposition against obesity. The present review summarizes the effects of dietary polyphenols on obesity-induced maternal reprogramming as an offspring anti-obesity approach.

The article delves into the crucial realm of compressing hydrogen in its gaseous state, a pivotal process for enhancing its viability in both civil and industrial sectors. The study initiates by providing a concise overview and comparison of diverse hydrogen storage methodologies, laying the groundwork with an in-depth analysis of hydrogen's thermophysical properties. It scrutinizes plausible configurations for hydrogen compression, aiming to strike a delicate balance between energy consumption, predominantly derived from the fuel itself, and the requisite number of compression stages. Notably, to render hydrogen storage competitive in terms of volume, pressures of at least 350 bar are deemed essential, albeit at an energy cost amounting to approximately 10% of the fuel's calorific value. Multi-stage compression emerges as a crucial strategy, not solely for energy efficiency, but also to curtail temperature rise, with an upper limit set at 200°C. This nuanced approach is underlined by the exploration of compression levels commonly cited in the literature, particularly 350 bar and 700 bar. Ultimately, the study advocates for a three-stage compression system as a pragmatic compromise, capable of achieving high-pressure solutions while keeping compression work below 10 MJ/kg, a threshold indicative of sustainable energy utilization.

Covid-19 is a disease caused by SARS-CoV-2, which has spread worldwide since the beginning of 2020. Several pharmaceutical and non-pharmaceutical strategies were proposed to contain the virus dissemination, including vaccination and lockdowns. One of the consequences of the pandemic was the denial or delay of access to convenient health care services, but also potentially the increase of adverse events within those services, like the number of hospital infections. Therefore, the main question here is: What happened to the performance and sustainability of hospitals? The main goal of this work was to test if the Portuguese public hospitals' performance has been affected by the SARS-CoV-2 pandemic. We used the Benefit-of-Doubt method integrated with the Malmquist Index to analyze the performance evolution over time. Then, we employed a multiple regression model to test whether some pandemic-related variables could explain the performance results. We considered a database of 40 Portuguese public hospitals evaluated from January 2017 to May 2022. The period 2017 to 2019 corresponds to the baseline (pre-pandemic), against which the remaining period will be compared (during the pandemic). We also considered fourteen variables characterizing hospital quality, divided into three main performance definitions (efficiency and productivity; access; safety and care appropriateness). As potential explanatory variables, we consider seven dimensions, including vaccination rate and the need for intensive care for Covid-19 infected people. Results suggest that Covid-19 pandemic features help explain the drop on access after 2020, but not the evolution of safety and appropriateness of care, which surpris-ingly increased the whole time.

Emerging autologous cellular therapies that utilize platelet-rich plasma (PRP) applications have the potential to play adjunctive roles in a variety of regenerative medicine treatment plans. There is a global unmet need for tissue repair strategies to treat musculoskeletal (MSK) and spinal disorders, osteoarthritis (OA), and patients with chronic complex and recalcitrant wounds. PRP therapy is based on the fact that platelet growth factors (PGFs) support the three phases of wound healing and repair cascade (inflammation, proliferation, remodeling). Many different PRP formulations have been evaluated, originating from human, in vitro, and animal studies. However, recommendations from in vitro and animal research often lead to different clinical outcomes because it is difficult to translate non-clinical study outcomes and methodology recommendations to human clinical treatment protocols. In recent years, progress has been made in understanding PRP technology and the concepts for bioformulation, and new research directives and new indications have been suggested. In this review, we will discuss recent developments regarding PRP preparation and composition regarding platelet dosing, leukocyte activities concerning innate and adaptive immunomodulation, serotonin (5-HT) effects and pain killing. Furthermore, we discuss PRP mechanisms related to inflammation and angiogenesis in tissue repair and regenerative processes. Lastly, we will review the effect of certain drugs on PRP activity, and the combination of PRP and rehabilitation protocols.

In view of the preparation for a post-LHC collider, the high-energy physics (HEP) community started from 2010 to discuss various options, including the use of HTS for very high field dipoles. Therefore, a small program was set in Europe aiming at exploring the possibility of using HTS for accelerator quality magnets. Based on various EU funded programs, though at modest levels, has enabled the European community of accelerator magnets to start getting experience in HTS and addressing a few issues. The program was based on use of REBCO tapes to form 10 kA Roebel cables, to be used to wind small dipoles of 30-40 mm aperture in the 5 T range. The dipoles are designed to be later inserted in a background dipole field (in Nb3Sn), to reach eventually a field level in the 16-20 T range, beyond the reach of LTS. The program is currently underway: more than 1 km tape of high performance (Je > 500 A/mm2 at 20 T, 4.2 K has been manufactured and characterized, various 30 m long Roebel cables have been assembled and validated up to 13 kA, a few dipoles have been wound and tested, reaching at present 4.5 T in stand-alone (while a dipole made from race track coils with no-bore exceeded 5 T using stacked tape cable) and a test in a background field is being organized.

This article discusses the relationship between the discourse of evangelical churches and the production of conservative neoliberal political rationalities. We start from the premise that the Large Evangelical Corporations (in Brazil), operate within the neoliberal logic, and offer biographical solutions to social exclusion systems, indicating the individual and spiritual causes for poverty and suffering, while identifying the "deserving" of blessings, suggesting elevation through personal responsibility. In this turn, they merge self-entrepreneur individualism with rhetoric that interweaves elements of conservative communitarianism, such as tradition, naturalizing gender roles, and cultivating traditional family models, seen as key to rehabilitating the wider society. We hypothesize that, in the Brazilian case of the state of Rio de Janeiro, evangelical churches are central parts of this gear, acting as one of the main "resonance machines" (Connolly) of neoliberal policies, providing individualized solutions for structural systems of social exclusion, in a pedagogical, efficient and extensive manner. In this sense, this work benefits from fieldwork and interviews conducted in the state of Rio de Janeiro with its large evangelical churches.

The evolution of digital media in adolescents has changed the patterns and motives of use and the impact on their communication choices in their social and family networks. The objectives of this study are to understand how peers communicate adopting a social network (SN) or by voice and their social desirability. After the informant consent signature, the adolescents completed a series of self-report questionnaires on the use of SN, on communication preferences, and on social desirability through online. Most of the adolescents belonged to the 17-19 age group (83.6%) and were female (68.9%). Adolescents spent more than 3 hours/day on Whatsapp and more than 2 hours/day on Instagram, while the use of Facebook was on average only 35 minutes/day. Females used digital media for longer than males. Adolescents aged 17-19 years choose more Facebook and voice modes compared to adolescents aged 14 and 16 years. The alternative modes of Whatsapp and voice were chosen more than the social networks in their communication strategies, especially for negative topics. Motives for use were, in addition to boredom, related to maintaining one's social sphere with peers. Some educative considerations were made based on these results.

In this article we investigate the determinants of marketing or organizational innovators in Europe for 36 countries in the period 2010-2019. We have used data from the European Innovation Scoreboard-EIS of the European Commission. We perform different econometric models i.e. Dynamic Panel, Pooled OLS, Panel Data with Fixed Effects, Panel Data with Random Effects, WLS. Results show that the level of marketing or organizational innovators in positively associated, among others variables to “Innovation Index”, “Innovators” and “Knowledge Intensive Service Exports”, while is negatively associated with “Sales Impacts”, “Foreign Controlled Enterprises Share of Value Added” and “Government procurement of advanced technology products”.

The Sunyaev-Zeldovich effect (SZe) is a global distortion of Cosmic Microwave Bckground (CMB) spectrum as result of its interaction with a hot electron plasma in the intracluster medium for large gravitational virialized structures such as galaxy clusters. Furthermore, this hot gas of electrons emits X-Rays due to its fall in the gravitational potential well of the cluster. The analysis of SZe and X-Ray data, provide a method for calculating distances to galaxy clusters at any redshift (Angular diameter distance (d_A) and gas mass fraction (f_gas)). On the other side, many of these galaxy clusters produce a Strong Gravitational Lens effect (SGL), which has become an useful astrophysical tool for cosmology. We use these cosmological tests, in addition to the more traditional ones (SNIa, CMB, BAO), to constraint alternative models of dark energy (ωCDM, CPL, IDE, EDE) and study the history of expansion through the cosmographic parameters (H(z), q(z), j(z)). Using Akaike and Bayesian Information Criterion (AIC, BIC) we find that the ωCDM and ΛCDM models are the most favored by the observational data. In addition, we found that at low redshift appears an peculiar behavior of slowdown of aceleration, which occurs only on dynamical dark energy models using only galaxy clusters (d_A,clusters + f_gas).

Turbulence is a fluid dynamic problem refractory to mathematical treatment. Examining a theoretical model of liquid water flowing in a cylinder at different Raleigh numbers, we propose a novel approach to elucidate the first stages of turbulent flows. The weakly bonded molecular assemblies of liquid water form a fluctuating branched polymer in which every micro-cluster displays different density. Against the common view of liquid water as an incompressible and continuous fluid, we suggest that the occurrence of transient local aggregates could be able to generate the vortices and eddies that are the hallmarks of turbulence. We quantify the local changes in velocity, diameter and density required to engender “obstacles” to the average flow. Then, we show how these microstructures, equipped with different Raleigh numbers and characterized by high percolation index, could generate boundary layers that contribute to micro-vortices production. We conclude that the genesis of turbulence cannot be assessed in terms of collective phenomena, rather is sustained, among many other factors, by the underrated microscopic inhomogeneities of fluids like liquid water.

The complexity of the current social context leads healthcare professionals to deal daily with users who are increasingly varied in terms of culture, language and religion. Transcultural nursing is a practical discipline that aims to respond to the patient's need for assistance, but must not ignore the study and knowledge of the patient, with his history, his culture, but also with his expectations, in order to respond to his care needs with effectiveness, efficiency, adequacy and respect. This work originates from the desire to investigate the "state of health" of the relationship between nurses/health workers and migrant patients, researching the variables that improve or worsen it. It aims to investigate how diversity affects the care provided to migrant people, highlighting the difficulties felt by nurses and define the areas of possible care improvements. It seems possible to affirm that the nurses and health workers interviewed still respond to the problem of migrant patients with a strong spirit of participation and availability, without, however, this motivational charge being accompanied by a widespread "nursing" awareness of the problem.

In this article we analyze the determinants and the export trend of European countries of medium and high technology products. The data were analyzed using various econometric models, namely WLS, Pooled OLS, Dynamic Panel, Panel Data with Fixed Effects, Panel Data with Random Effects. The results show that exports of medium and high-tech products are positively associated, among other variables, with the value of “Average Annual GDP Growth”, “Total Entrepreneurial Activity” and “Sales Impacts”, and negatively associated with, among other variables, “Human Resources”, “Government and Procurement of Advanced Technology Products” and “Buyer Sophistication”. A cluster analysis was realized with the k-Means algorithm optimized with the Silhouette coefficient. The result showed the presence of only two clusters. Since this result was considered poorly representative of the industrial complexity of the European Union countries, a further analysis was carried out with the Elbow method. The result showed the presence of 6 clusters with the dominance of Germany and the economies connected to the German economy. In addition, a network analysis was carried out using the distance to Manhattan. Four complex network structures and two simplified network structures were detected. A comparison was then made between 10 machine learning algorithms for predicting the value of exports of medium and high-tech products. The result shows that the best performing algorithm is the SGD. An analysis with Augmented Data-AD was implemented with a comparison between 10 machine learning algorithms for prediction and the result shows that the Linear Regression algorithm is the best predictor. The prediction with the Augmented Data-AD allows to reduce the MAE by about 0.0022131 compared to the prediction with the Original Data-OD.

In this article we investigate the determinants of the European “Most Cited Publications”. We use data from the European Innovation Scoreboard-EIS of the European Commission for the period 2010-2019. Data are analyzed with Panel Data with Fixed Effects, Panel Data with Random Effects, WLS, and Pooled OLS. Results show that the level of “Most Cited Publications” is positively associated, among others, to “Innovation Index” and “Enterprise Birth” and negatively associated, among others, to “Government Procurement of Advanced Technology Products” and “Human Resources”. Furthermore, we perform a cluster analysis with the k-Means algorithm either with the Silhouette Coefficient and the Elbow Method. We find that the Elbow Method shows better results than the Silhouette Coefficient with a number of clusters equal to 3. In adjunct we perform a network analysis with the Manhattan distance, and we find the presence of 4 complex and 2 simplified network structures. Finally, we present a confrontation among 10 machine learning algorithms to predict the level of “Most Cited Publication” either with Original Data-OD either with Augmented Data-AD. Results show that the best machine learning algorithm to predict the level of “Most Cited Publication” with Original Data-OD is SGD, while Linear Regression is the best machine learning algorithm for the prediction of “Most Cited Publications” with Augmented Data-AD.

In this article we investigate the role of “Renewable Energy Consumption” in the context of Circular Economy. We use data from the World Bank for 193 countries in the period 2011-2020. We perform several econometric techniques i.e., Panel Data with Fixed Effects, Panel Data with Random Effects, Pooled OLS, WLS. Our results show that “Renewable Energy Consumption” is positively associated among others to “Cooling Degree Days” and “Adjusted savings: net forest depletion” and negatively associated among others to “GHG net emissions/removals by LUCF” and “Mean Drought Index”. Furthermore, we perform a cluster analysis with the application of the k-Means algorithm optimized with the Silhouette Coefficient and we find the presence of two clusters. Finally, we compare eight different machine learning algorithms to predict the value of Renewable Energy Consumption. Our results show that the Polynomial Regression is the best algorithm in the sense of prediction and that on average the renewable energy consumption is expected to growth of 2.61%.

In no-tillage systems, there is an accumulation of crop residues (CR) which plays an important role in available of soil-N. A study was set up to provide information regarding the CR N credit, and the influence of N mineral fertilizer. An incubation was run in a loam soil with addition of a similar rate of residue (10 Mg ha-1; sugarcane, soybean, and brachiaria) and N mineral fertilizer (urea; 120 kg N ha-1). After the stabilization of biological activity, soil and remaining residues were collected, and N monitored. Results showed that the N credit was positive with application of soybean, sugarcane, and brachiaria. There was an expressive performance of soybean N credit represented by a positive balance, and a reduction from 2.49 to 0.9 g kg-1 of N in residue, with direct increase of 90% of soil-N. There is no need of N fertilizer to potentialize the soybean N credit, but it is requested to potentialize N credit of brachiaria and sugarcane. The urea demonstrated be a good enhancer of brachiaria N credit, but it was not adequate to sugarcane residues. Based in our result, the accumulation and incorporation of CR can be considered as a N credit with positive contribution in soil-N.

The aim of this study was to assess the effect of added cultures of probiotic lactic acid bacteria on physicochemical, textural, and sensory characteristics of fresh cheese as well as their viability. Probiotic strains Lactobacillus acidophilus and L. rhamnosus were evaluated at two inoculation times (before the renneting and salting processes) following a factorial treatment arrangement. The bacterial count (log CFU g-1), acidity determination (% lactic acid), pH and percentage of syneresis were evaluated at 0, 1, 7, 14 and 21 days of refrigerated storage (4–5 °C). The texture profile analysis and an extended preference test were carried out at 21 days of storage. At the end of storage, fresh cheeses containing L. rhamnosus, added prior to the renneting process, had similar acidity values (0.18% lactic acid), pH (5.36) and percentage of syneresis (4.71%) compared to those for the cheeses without probiotics or control. Excluding adhesiveness, no differences were observed in texture profile parameters among the assessed cheeses. The fresh cheese supplemented with L. rhamnosus before the renneting process had a microorganism count greater than 6 logarithmic cycle/g, and the highest preference among treatments. The results from this study suggest that fresh cheese can be an excellent matrix for probiotic microorganisms, in particular L. rhamnosus.

Following the unprecedented and global health crisis of COVID-19, without a doubt, there has been a tremendous impact on international tourism for two reasons: the imposed travel restrictions discourage people from traveling, while travelers watch increased anxiety when responding to the new travel landscape. We address the problem of travelers’ changing travel risk perceptions in the COVID-19 pandemic aftermath. Our main goal is to identify and weigh critical emerging travel risks and create a risk evaluation index in which one can measure the destinations and strategic interventions’ performance for South African travelers. We found that tourist perceived risks are multidimensional, including categories like additional expenses, exchange rates, and refund-related factors. These three criteria are the most important to overall travel risk perception. We applied the developed risk evaluation index to five tourist destinations to evaluate their performance regarding the identified risks, being the UK the country with the best performance.

: The paper aims to present a conceptual framework for developing territorial development strategies based on crowdsourcing technologies to enhance intangible heritage, setting this framework within the context of Italian inner areas defined by a policy framework oriented towards the territorial development of marginal areas. For this reason, the work intends to provide the necessary background information for the development of such strategies, examining the technological aspects, a precise definition of the concept of intangible heritage, the application of a socially innovative strategy for marginal territories, and a framework of strategic actions necessary to implement solutions capable of involving local communities from the bottom up and ensuring a widespread redistribution of the benefits in the development of these technologies. The paper's objective is, therefore, to bridge the gap between different debates: technological innovation, the enhancement of intangible heritage, and territorial development based on socially innovative strategies, providing a key information framework for experts and scholars who intend to approach these topics or develop projects based on these tools and objectives.

In this article we estimate the level of Government Effectiveness-GE in 193 countries in the period 2011-2020 using data of the ESG World Bank Database. Different econometric techniques are used i.e. Panel Data with Random Effects, Panel Data with Fixed Effects, and Pooled OLS. Results show that GE is positively related among others to “Control of Corruption”, “Political Stability and Absence of Violence/Terrorism”, and negatively associated with “Percentage Annual GDP Growth”. We perform a cluster analysis with the k-Means algorithm optimized with the Elbow Method and we find the presence of four clusters. Finally, we confront eight machine learning algorithms for the prediction of GE. Results show that the Polynomial Regression is the best predictive algorithm. The value of GE is expected to growth on average by 15.97%.

In this article we estimate the level of Control of Corruption for 193 countries in the period 2011-2020 using data from the ESG World Bank Database. Various econometric techniques are applied i.e.: Panel Data with Random Effects, Panel Data with Fixed Effects, Pooled OLS, WLS. Results show that “Control of Corruption” is positively associated, among others, to “Government Effectiveness” and “Political Stability and Absence of Violence/Terrorism”, while it is negatively associated among others to “Agriculture, Forestry, and Fishing Value Added as Percentage of GDP” and “GHG Net Emissions/Removals by LUCF”. A cluster analysis implemented with the k-Means algorithm optimized with the Elbow Method shows four clusters. A confrontation among eight Machine Learning algorithms is proposed for the prediction of Control of Corruption. Polynomial Regression is the best predictor for the training data. The level of Control of Corruption is expected to growth by 10.36% on average.

In this article we investigate the impact of “Renewable Electricity Output” on green economy in the context of circular economy for 193 countries in the period 2011-2020. We use data from World Bank ESG framework. We perform Panel Data with Fixed Effects, Panel Data with Random Effects, WLS, and Pooled OLS. Our results show that Renewable Electricity Output is positively associated, among others, to “Adjusted Savings-Net Forest Depletion” and “Renewable Energy Consumption” and negatively associated, among others, to “CO2 Emission” and “Cooling Degree Days”. Furthermore, we perform a cluster analysis implementing the k-Means algorithm optimized with the Elbow Method and we find the presence of 4 clusters. Finally, we confront seven different machine learning algorithms to predict the future level of “Renewable Electricity Output”. Our results show that Linear Regression is the best algorithm and that the future value of renewable electricity output is predicted to growth on average at a rate of 0.83% for the selected countries.

We investigate the innovational determinants of “Patent Applications” in Europe. We use data from the European Innovation Scoreboard-EIS of the European Commission for 36 countries in the period 2010-2019. We use Panel Data with Fixed Effects, Panel Data with Random Effects, Pooled OLS, WLS and Dynamic Panel. We found that the variables that have a deeper positive association with “Patent Applications” are “Human Resources” and “Intellectual Assets”, while the variables that show a more intense negative relation with Patent Applications are “Employment Share in Manufacturing” and “Total Entrepreneurial Activity”. A cluster analysis with the k-Means algorithm optimized with the Silhouette Coefficient has been realized. The results show the presence of two clusters. A network analysis with the distance of Manhattan has been performed and we find three different complex network structures. Finally, a comparison is made among eight machine learning algorithms for the prediction of the future value of the “Patent Applications”. We found that PNN-Probabilistic Neural Network is the best performing algorithm. Using PNN the results show that the mean future value of “Patent Applications” in the estimated countries is expected to decrease of -0.1%.

In this article we have estimated the value of “Opportunity Driven Entrepreneurship” in Europe. We use data from European Innovation Scoreboard-EIS of the European Commission for 36 countries in the period 2010-2019. We use Panel Data with Fixed Effects, Panel Data with Random Effects, WLS, Pooled OLS, and Dynamic Panel. Our results show that “Opportunity Driven Entrepreneurship” is positively associated, among others, to “Innovation Friendly Environment” and “Turnover Share Large Enterprises”, while it is negatively associated, among others, to “Sales Impacts” and “R&D Expenditure Business Sectors”.

In this article we estimate the value of “Non-R&D Innovation Expenditures” in Europe. We use data from the European Innovation Scoreboard-EIS of the European Commission from the period 2010-2019. We test data with the following econometric models i.e.: Pooled OLS, Dynamic Panel, Panel Data with Fixed Effects, Panel Data with Random Effects, WLS. We found that “Non-R&D Innovation Expenditures” is positively associated among others to “Innovation Index” and “Firm Investments” and negatively associated among others to “Human Resources” and “Government Procurement of Advanced Technology Products”. We use the k-Means algorithm with either the Silhouette Coefficient and the Elbow Method in a confrontation with the network analysis optimized with the Distance of Manhattan and we find that the optimal number of clusters is four. Furthermore, we propose a confrontation among eight machine learning algorithms to predict the level of “Non-R&D Innovation Expenditures” either with Original Data-OD either with Augmented Data-AD. We found that Gradient Boost Trees Regression is the best predictor for OD while Tree Ensemble Regression is the best Predictor for AD. Finally, we verify that the prediction with AD is more efficient of that with OD with a reduction in the average value of statistical errors equal to 40,50%.

In this article we investigate the determinants of “New Doctorate Graduates” in Europe. We use data from the EIS-European Innovation Scoreboard of the European Commission for 36 countries in the period 2010-2019 with Pooled OLS, Dynamic Panel, WLS, Panel Data with Fixed Effects and Panel Data with Random Effects. We found that “New Doctorate Graduates” is positively associated, among others, with “Human Resources” and “Government Procurement of Advanced Technology Products” and negatively, associated among others, with “Total Entrepreneurial Activity” and “Innovation Index”. We apply a clusterization with k-Means algorithm either with the Silhouette Coefficient either with the Elbow Method and we found that in both cases the optimal number of clusters is three. Furthermore, we use the Network Analysis with the Distance of Manhattan, and we find the presence of seven network structures. Finally, we propose a confrontation among ten machine learning algorithms to predict the value of “New Doctorate Graduates” either with Original Data-OD either with Augmented Data-AD. Results show that SGD-Stochastic Gradient Descendent is the best predictor for OD while Linear Regression performs better for AD.

The article affords the question of lifelong learning in Europe using data from the European Innovation Scoreboard-EIS in the period 2010-2019 for 36 countries. The econometric analysis is realized using WLS, Dynamic Panel, Pooled OLS, Panel Data with Fixed Effects and Random Effects. The results show that lifelong learning is, among other variables, positively associated to “Human Resources” and “Government procurement of advanced technology products” and is negatively associated, among others, to “Average annual GDP growth” and “Innovation Index”. A clusterization is realized using the k-Means algorithm with a confrontation between the Elbow Method and the Silhouette Coefficient. Subsequently, a Network Analysis was applied with the distance of Manhattan. The results show the presence of 4 complex and 2 simplified network structures. Finally, a comparison was made among eight machine learning algorithms for the prediction of the value of lifelong learning. The results show that the linear regression is the best predictor algorithm and that the level of lifelong learning is expected to growth on average by 1.12%.

In the following article, the value of the "Knowledge Intensive Services Exports in Europe" in 36 European countries is estimated. The data were analyzed through a set of econometric models or: Poled OLS, Dynamic Panel, Panel Data with Fixed Effects, Panel Data with Random Effects, WLS. The results show that “Knowledge Intensive Services Exports” is negatively associated, among others, with "Buyer Sophistication", "Government Procurement of Advanced Technology Products", and positively associated with the following variables i.e. "Innovation Index", "Sales Impacts" and "Total Entrepreneurial Activity". Then a clusterization with k-Means algorithm was made with the Elbow method. The results show the presence of 3 clusters. A network analysis was later built and 4 complex network structures and three structures with simplified networks were detected. To predict the future trend of the variable, a comparison was made with eight different machine learning algorithms. The results show that prediction with Augmented Data-AD is more efficient than prediction with Original Data-AD with a reduction of the mean of statistical errors equal to 55,94%.

The following article analyzes the determinants of the innovation index in Europe. The data refer to the European Innovation Scoreboard-EIS of the European Commission for the period between 2010 and 2019 for 36 countries. The data are analyzed using the following econometric techniques: Panel Data with Random Effects, Panel Data with Fixed Effects, Dynamic Panel Data, Pooled OLS, WLS. The results show that the Innovation Index is negatively connected to some variables, among which the most significant are "GDP per capita", "R&D expenditure public sector", "Venture capital", "Tertiary education", and positively connected to some variables among which the most relevant are: "Government procurement of advanced technology products", "Average annual population growth", "Finance and support", "Human resources", "Marketing or organisational innovators", "Linkages". A clustering was then carried out using the unsupervised k-Means algorithm optimized with the Silhouette coefficient which shows the presence of 2 clusters per value of the Innovation Index. Eight machine learning algorithms has been used for prediction with real data. The Tree Ensemble Regression algorithm has been chosen as best performer. A further prediction has been made with the augmented data. The result shows that the best performing algorithm is Linear Regression with an innovation index value predicted to grow by approximately 3.38%.

The Combined Inversion of Surface and AeRosols (CISAR) algorithm for the joint retrieval of surface and aerosol single scattering properties has been further developed in order to extend the retrieval to clouds and overcome the need for an external cloud mask. Pixels located in the transition zone between pure cloud and pure aerosol are often discarded by both aerosol and cloud algorithms, despite being essential for studying aerosol-cloud interactions, which still represent the largest source of uncertainty in climate predictions. The proposed approach aims at filling this gap and deepening the understanding of aerosol properties in cloudy environments. The new CISAR version is applied to Sentinel-3A/SLSTR observations and evaluated against different satellite products and ground measurements. The spatial coverage is greatly improved with respect to algorithms processing only pixels flagged as clear sky by the SLSTR cloud mask. The continuous retrieval of aerosol properties without any safety zone around clouds opens new possibilities for studying aerosol properties in cloudy environments.

Monocarboxylate transporter 8 (MCT8) and organic anion-transporting polypeptide 1C1 (OATP1C1) are thyroid hormones (TH) transmembrane transporters relevant for the availability of TH in neural cells, crucial for their proper development and function. Mutations in MCT8 or OATP1C1 result in severe disorders with dramatic movement disability related to alterations in basal ganglia motor circuits. Mapping the expression of MCT8/OATP1C1 in those circuits is necessary to explain their involvement in motor control. We studied the distribution of both transporters in the neuronal subpopulations that configure the direct and indirect basal ganglia motor circuits using immunohistochemistry and double/multiple labeling immunofluorescence for TH transporters and neuronal biomarkers. We found their expression in the medium-sized spiny neurons of the striatum (the receptor neurons of the corticostriatal pathway), and in various types of its local microcircuitry interneurons, including the cholinergic. We also demonstrate the presence of both transporters in projection neurons of intrinsic and output nuclei of the basal ganglia, motor thalamus and nucleus basalis of Meynert, suggesting an important role of MCT8/OATP1C1 for modulating the motor system. Our findings suggest that a lack of function of these transporters in the basal ganglia circuits would significantly impact motor system modulation, leading to clinically severe movement impairment.

Verification of inclusivity of molecular detection methods gives indications on the reliability of viral infections diagnosis because of the tendency of viral pathogens to undergo sequence variation. This study was aimed to select inclusive probe based reverse transcription quantitative PCR (RT-qPCR) assays for the diagnosis of the most widespread and detrimental viruses infecting honeybees, namely the acute bee paralysis virus (ABPV), the black queen cell virus (BQCV), the chronic paralysis bee virus (CBPV), the deformed wing virus variants A (DWVA) and B (DWVB), and the sacbrood virus (SBV). Therefore, detection methods previously described were re-evaluated in silico for specificity and inclusivity. Based on this evaluation, selected methods were modified or new ones were designed and tested in duplex RT-qPCR reactions. The limits of detection (LODs), effect of multiplexing on sensitivity and viral RNA quantification potential in bees and hive debris were assessed. This study made available diagnostic assays able to detect an increased number of virus variants compared to previously described tests and two viral pathogens in a single PCR reaction.

The predictability of wind information in a given location is essential for the evaluation of a wind power project. Predicting wind speed accurately improves the planning of wind power generation, reducing costs and improving the use of resources. This paper seeks to predict the mean hourly wind speed in anemometric towers (at a height of 50 meters) at two locations: a coastal region and one with complex terrain characteristics. To this end, the Holt-Winters (HW), Artificial Neural Networks (ANN) and Hybrid time-series models were used. Observational data evaluated by the Modern-Era Retrospective analysis for Research and Applications-Version 2 (MERRA-2) reanalysis at the same height of the towers. The results show that the hybrid model had a better performance in relation to the others, including when compared to the evaluation with MERRA-2. For example, in terms of statistical residuals, RMSE and MAE were 0.91 and 0.62 m/s, respectively. As such, the hybrid models are a good method to forecast wind speed data for wind generation.

Pigs are a social species and they stablish hierarchies for a better use of resources and to reduce conflicts. However, in pig production, the opportunities for growing can differ in dominant and subordinate animals. In the present study a system was tested to perform a Dominance versus Subordinate test in growing pigs to investigate how the hierarchy affects feeding behaviour, growth and gut microbiota assessed in faeces. 64 animals housed in eight different pens were used, with four castrated males and four females in each one, weighing 18kg at arrival and maintained during the whole growing period, until 140 kg. Three stool samplings were obtained from the animals directly from the anus to avoid contamination of the faeces on 58, 100 and 133 days after the start of the study to investigate the microbiota composition. The dominant animals had higher gains during the growing period that the subordinate. In addition, they were performing more visits to the feeder throughout the day. Differential abundance patterns were observed in five bacterial genera, Oliverpabstia, Peptococcus, and Faecalbacterium being more abundant in dominant animals and Holdemanella and Acetitomaculum being overrepresented in subordinate ones. This microbial biomarker accurately classified dominant versus subordinate groups of samples with an AUC of 0.92.

One of the most broadly used models for membrane fouling is the Hermia model, which separates this phenomenon into four blocking mechanisms, each with an associated parameter n. These mechanisms are complete blocking (n=2), intermediate blocking (n=1), standard blocking (n=3/2), and cake formation (n=3/2). The original model, which was obtained through experimental data, is given by an Ordinary Differential Equation (ODE) dependent on n. At the time, this ODE was only solved for these four values of n, which limits the effectiveness of the model when adjusted to experimental data. This paper aims to not only mathematically prove the original Hermia model but also to broaden the scope of this model for any real number n by using the original ODE, the equations of fluid mechanics, and the properties of single and multivariable calculus. The extended Hermia model (EHM) is given by a power law for any n≠2 and is given by an exponential function at n=2. To better test the model, we have performed the model fitting of the EHM and compared its performance to the original four pore-blocking mechanisms in 6 micro- and ultrafiltration examples. In all examples, the EHM performed consistently better than the four original pore-blocking mechanisms. Changes in the blocking mechanisms concerning transmembrane pressure (TMP), crossflow rate (CFR), crossflow velocity (CFV), membrane composition, and pretreatments are also discussed.

Synthesis of nickel oxide nanoparticles (NiO NPs) is a low cost and ecofriendly route that brings great benefits over chemical and physical methods of synthesis. Our approach consisted of using aqueous extracts from treated waste of Manihot Esculenta (Cassava) as reducing, stabilizing and capping agents for the synthesis of NiO NPs. The results proved this approach might be a viable alternative. Extracts were mixed during 30 minutes with Ni(NO3)2.6H2O leading to NPs formation. NiO NPs were characterized through FTIR, XRD, TEM and Raman spectroscopy. NiO NPs showed different shapes and sizes around 5-10 nm in agreement with the particle size calculated by XRD Scherrer equation.

Titica vine fibers (TVFs) extracted from aerial roots of Heteropsis flexuosa, from the Amazon region, were 10, 20, 30 and 40 vol% incorporated into an epoxy matrix for applications in ballistic multilayered armor systems (MASs) and stand-alone tests for personal protection against high-velocity 7.62 mm ammunition. The back-face signature (BFS) depth measured for composites with 20 and 40 vol% TVFs used as an intermediate layer in MASs was 25.6 and 32.5 mm, respectively, below the maximum limit set by the international standard. Fracture mechanisms found by scanning electron microscopy (SEM) attested the relevance of increasing the fiber fraction for applications in MASs. The results of stand-alone tests showed that the control (0 vol%) and samples with 20 vol% TVFs absorbed the highest impact energy (Eabs) (212 – 176 J), and consequently limit velocity (VL) values (213 – 194 m/s), when compared with 40 vol% fiber fractions. However, the macroscopic evaluation found that the plain epoxy, referring to control samples, shattered completely. In addition, for 10 and 20 vol% TVFs, the composites were fragmented or exhibited delamination fracture, which contributed to their physical integrity. On the other hand, the composite with 30 and 40 vol% TVFs, whose Eabs and VL varied between 166 – 130 J and 189 – 167 m/s, respectively, showed the best dimensional stability. The SEM images indicated that for composites with 10 and 20 vol% TVFs the fracture mode was predominantly brittle, due to the greater performance of the epoxy resin and the discrete action of the fibers. While for composites with 30 and 40 vol% TVFs, there was the activation of more complex mechanisms such as pullout, shearing and fiber rupture.

Evaluating mutation testing behavior can help decide whether refactoring successfully maintains the expected initial test results. Moreover, manually performing this analytical work is both time-consuming and prone to errors. This paper extends an approach to assess test code behavior and proposes a tool called MeteoR. This tool comprises an IDE plugin to detect issues that may arise during test code refactoring, reducing the effort required to perform evaluations. A preliminary assessment was conducted to validate the tool and ensure the proposed test code refactoring approach is adequate. By analyzing not only the mutation score but also the generated mutants in the pre- and post-refactoring process, results show that the approach is capable of checking whether the behavior of the mutants remains unchanged throughout the refactoring process. This proposal represents one more step toward the practice of test code refactoring. It can improve overall software quality, allowing developers and testers to safely refactor the test code in a scalable and automated way.

Advanced-Differential Interferometric SAR (A-DInSAR) has been used to monitor surface deformations in open pit mines and tailings dams. In this paper, ground deformations have been detected on the area of the tailings Dam-I at the Córrego do Feijão Mine (Brumadinho, Brazil) before its catastrophic failure occurred on 25 January 2019. Two techniques optimized for different scattering models, SBAS (Small BAseline Subset) and PSI (Persistent Scatterer Interferometry), were used to perform the analysis based on 26 Sentinel-1B images in IW mode, acquired on descending orbits from 03 March 2018 to 22 January 2019. A WorldDEM DSM product was used to remove the topographic phase component. The results provided by both techniques showed a synoptic and informative view of the deformation process affecting the study area, with a detection of persistent trend of deformations on the top, middle and bottom sectors of the dam face until its collapse, as well as the expected natural settlements on the tailings. It is worth noting the detection of an acceleration in the displacement time-series for a short period near the failure. The maximum accumulated displacements detected along the downstream slope face were -39 mm (SBAS) and -48 mm (PSI). It is reasonable to consider that Sentinel-1 would provide decision makers complementary motion information to the in-situ monitoring system for risk assessment and for a better understanding of on-going instability phenomena affecting the tailings dam.

Eryngium foetidum L., a biennial herb with diverse applications in food and traditional medicine, holds economic and pharmacological significance. Given its growing commercial interest, implementing biotechnological approaches like plant tissue culture is vital for sustainable propagation and metabolite production. In this study, we investigated the in vitro photoautotrophic potential of E. foetidum, examining growth, chlorophyll a fluorescence, photosynthetic pigments, and anatomical features under different sucrose concentrations and gas exchange rates. Acclimatization and survival rates of plants after ex vitro transfer were also assessed. E. foetidum exhibited robust growth in both photoautotrophic and photomixotrophic conditions, with natural ventilation significantly enhancing plant development. Chlorophyll a fluorescence and photosynthetic performance were influenced by sucrose and gas exchange, highlighting the importance of these factors in plant micropropagation. Moreover, the species demonstrated remarkable plasticity during acclimatization, with high survival rates and rapid inflorescence emission. The research provides valuable insights into optimizing in vitro cultivation conditions for E. foetidum, emphasizing the potential for large-scale clonal propagation and exploring secondary metabolites. The observed phenotypic plasticity underscores the adaptability of the species to diverse environments. These biotechnological strategies open avenues for future studies, including the application of elicitors for enhanced secondary metabolite production.

In the last three decades the presence of phospholipids in the nucleus has been shown and thoroughly investigated. A great interest raised about nuclear inositol lipids mainly because of their role in signalling acting. Here we review the main issues of nuclear phospholipid localization and the role of nuclear inositol lipids and their related enzymes in cellular signaling both in physiological and pathological conditions.

As recommended in the ICH Guidelines (S5-R2 and S6-R1), and based on bioethical concerns, we chose bovine embryos (BE) to check the in vitro embryo development considering the use of different amounts of rHGAL-1 as supplementations of in vitro embryo culture (IVP) mediums. Based on procedures for commercial BE in vitro production, using oocytes aspirated from slaughterhouse ovaries, the rHGAL-1 supplementation performed in two experiments (#01 on the oocyte maturation - IVM medium supplemented and experiment #2 on culture step IVC, supplemented SOF medium). There were IVP commercial procedures done, with 3 IVP batches per experiment and distributed the oocytes in four groups of treatment (one control group and three different dosages of rHGAL-1 to supplement both IVM and SOF mediums, using (2, 20 and 40µg.mL-1 respectively). A total of 962 (experiment 1) and 1,213 (experiment 2) oocytes were aspirated and submitted to IVP procedure. There was no damage to in vitro bovine embryos growth, considering cleavage percentage (%CLE), blastocysts development on day 7 (BlD7, BxD7, BhD7), or hatching blastocysts maturation on day 8 (BhD8%), regardless of rHGAL-1 supplementation. The immunohistochemistry assay with D8 embryos cultivated with rHGAL-1 supplementation on the culture medium (SOF medium) could demonstrate the presence of exogenous GAL-1, distributed in mass cell and trophoblastic cells, and the profile observed is dependent of exogenous supplementation and it was more evident in hatched embryos. The findings reassure the use of a reasonable amount of rHGAL-1 for in vitro embryonic development and make using rHGAL-1 in assisted reproduction in humans more reliable and safer.

Ventricina del Vastese is a traditional dry fermented sausage from Central Italy not yet charac-terized for occurrence, identity and safety of coagulase negative staphylococci (CNS), a bacterial group technologically important for this kind of products. Therefore, in this study, 98 CNS isolates from four manufacturers were differentiated by Repetitive element palindromic PCR (Rep-PCR) and identified by 16S rRNA gene sequencing. These were examined for genes encoding biogenic amine (BA) production, resistance to aminoglycosides, β-lactams and tetracyclines and staphylococcal enterotoxins (SEs). Staphylococcus succinus (55%) predominated, followed by S. xylosus (30%), S. epidermidis (7.4%), S. equorum (3.1%), S. saprophyticus (3.1%) and S. warneri (1%). One S. succinus subsp. casei isolate was slightly β-hemolytic. SEs and the histidine decarboxylase gene hdcA were not detected, while the tyrosine decarboxylase gene tdcA was detected in four S. xylosus isolates. A blaZ beta-lactamase gene and tetracycline resistance genes tetK (six isolates) and tetA (one isolate also bearing tetK) were found, respectively. However, fewer hazardous and AR traits compared to CNS examined in other studies were found, as a probable consequence of using meat from animals reared in conditions that allow to minimize pathogen circulation and antibiotic use. Therefore, appropriate production conditions can reduce these threats.

This study was aimed to examine the recent trends of antibiotic resistance (AR) prevalence in Staphylococcus aureus isolated from milk of animals with clinical mastitis in areas of the Abruzzo and Molise regions in central Italy. Fifty-four S. aureus isolates could be obtained from routine testing for clinical mastitis agents carried out in the author institution in years 2021 and 2022. These were analyzed for phenotypic resistance to eight antibiotics recommended for testing by European norms and belonging to the antibiotic classes used for mastitis treatment in milk producing animals. Moreover, the presence of 14 transferable genetic determinants encoding resistance to the same antibiotics was analyzed by qPCR tests developed in this study. Phenotypic resistance to non-β-lactams was infrequent, with only one 2022 isolate resistant to clindamycin. However, low level resistance to the β-lactam cefoxitin was observed in 59.2% isolates in both years making these isolates classifiable as methicillin resistant. The AR genotypes detected were blaZ gene (50% 2021 isolates and 44.4% 2022 isolates), ermC/T- aphA3-blaZ (one 2021 isolate), ant6-ermC/T-aphA3-blaZ (one 2021 isolate), ermB-blaZ (one 2022 isolate) and mecA-mph (one 2022 isolate). An interview to the veterinarians who conferred the samples, regarding antimicrobials prescribed for mastitis treatment and criteria of usage, indicated a possible causal relation with the AR test results. The low prevalence of AR genotypes, not increasing in time, most probably reflecting the reported management of antibiotic therapies in farms. However, the frequently observed cefoxitin resistance needs to be explained genotypically, further monitored and limited by modifying antibiotic usage practices. The identification of a mecA positive isolate in 2022 suggests to investigate further if this genotype is emerging locally.

Musculoskeletal disorders are increasingly prevalent worldwide, causing significant socioeconomic burdens and diminished quality of life. Notably, patellar chondropathy (PC) is among the most widespread conditions affecting the joint structures, resulting in profound pain and disability. Hyaluronic acid (HA) and platelet-rich plasma (PRP) have emerged as reliable, effective, and minimally invasive alternatives. Continuous research spanning from laboratory settings to clinical applications demonstrate the numerous advantages of both products. These encompass lubrication, anti-inflammation, and stimulation of cellular behaviors linked to proliferation, differentiation, migration, and the release of essential growth factors. Cumulatively, these benefits support the rejuvenation of bone and cartilaginous tissues, which are otherwise compromised due to the prevailing degenerative and inflammatory responses characteristic of tissue damage. While existing literature delves into the physical, mechanical, and biological facets of these products, as well as their commercial variants and distinct clinical uses, there is limited discussion on their interconnected roles. We explore basic science concepts, product variations, and clinical strategies. This comprehensive examination provides physicians with an alternative insight into the pathophysiology of PC as well as biological mechanisms stimulated by both HA and PRP that contribute to tissue restoration.

The safe and reliable operation of autonomous vehicles in complex and dynamic environments is heavily dependent upon exteroceptive and proprioceptive sensors. A LiDAR system generates accurate 3D point clouds, which are crucial for the detection, classification, and tracking of multiple targets. LiDAR data, however, presents significant challenges due to its density, noise, and varying sampling rates. In this study, various clustering and MTT techniques for LiDAR point clouds will be identified and classified within the context of autonomous driving to assess the state-of-the-art methods’ key challenges and their performances. We have categorized clustering and MTT methods used in AV applications, identified research gaps and challenges and analyzed existing algorithms and their challenges in detail. Researchers and practitioners in the field of autonomous driving will find this review to be a valuable resource.

Background: Triple negative breast cancer (TNBC) is the most aggressive form of breast cancer with poor outcomes. The molecular basis of TNBC remains poorly understood. The objective of this study was to explore the relationship between obesity and TNBC in premenopausal and postmenopausal Caucasian women using whole genome transcription profiling. Methods: We compared gene expression levels of tumor samples drawn from normal weight, overweight and obese in pre and postmenopausal women diagnosed with TNBC. We performed hierarchical clustering to assess similarity in patterns of gene expression profiles, and conducted network and pathway analysis to identify molecular networks and biological pathways. Results: We discovered gene signatures distinguishing normal weight from obese, normal weight from overweight and overweight from obese individuals in both premenopausal and postmenopausal women. The analysis revealed molecular networks and biological pathways dysregulated in response to obesity. Among the discovered pathways included the unfolded protein response, endoplasmatic reticulum stress, B cell receptor and the autophagy signaling pathways in obese premenopausal women and the integrin, axonal guidance, ERK/MAPK and Glutathione biosynthesis signaling pathways obese postmenopausal women. Conclusions: The results suggest that both overweight and obesity are associated with TNBC, highlighting the need for conformation of these results in independent studies.

With the rising trends in elderly populations around the world, there is a growing interest in understanding how climate sensitivity is related to their thermal perception. Therefore, we analyzed the associations between mortality in the elderly due to cardiovascular (CVD) and respiratory diseases (RD) and meteorological variables, for three cities in the State of São Paulo, Brazil: Campos do Jordão, Ribeirão Preto and Santos, from 1996 to 2017. We applied the Autoregressive Model Integrated with Moving Average (ARIMA) and the Principal Component Analysis (PCA) in order to evaluate statistical associations. Results showed CVD as a major cause of mortality, particularly in the cold period, when a high mortality rate is also observed due to RD. The mortality rate was higher in Campos do Jordão and lower in Santos (and intermediate values in Ribeirão Preto). Campos do Jordão results indicate an increased probability of mortality from CVD and RD due to lower temperatures. In Ribeirão Preto, the lower relative humidity may be related to the increase in CVD and RD deaths. This study emphasizes that, even among subtropical climates, there are significant differences. Therefore, this can assist decision makers in the implementation of mitigating and adaptive measures.

Having valid and reliable tools that help health professionals to assess fear in children undergoing medical procedures is essential to offer humanized and quality of care in the paediatric population. The aim of this study was to develop the cross-cultural adaptation and the evaluation of the psychometric properties of the Spanish version of the “Child Medical Fear Scale” in its shortened version (CMFS-R). The design consisted of two phases, first of cross-cultural adaptation and second of the psychometric validation of the CMFS-R with a sample of 262 children from Spain. Confirmatory factor analysis was conducted to assess construct validity and the Cronbach alpha and the adjusted item-total score correlation coefficients were performed to study reliability. The results confirmed internal consistency and construct validity of the Spanish version of the CMFS-R, indicating that the scale has an acceptable level of validity and reliability. Therefore, this study brings a new version of the scale to assess fear related to medical procedures for use in the Spanish paediatric population.

We have estimated the level of Risk Weighted Assets among 30 countries in Europe, in 30 trimesters, using data of the European Banking Authority-EBA of 139 variables. We perform an econometric model using Pooled OLS, Panel Data with Fixed Effects, Panel Data with Random Effects, Weighted Least Squares. We found that Risk Weighted Assets is negatively associated, among others, to the level of NFC loans in mining and quarrying, in public administration and defence, and in financial and insurance activities and positively associated, among others to distribution of NFC loans in human health services and social work activities, in education and the level of net fee and commission income. Furthermore, we apply a cluster analysis with the k-Means algorithm, and we find the presence of two clusters. A comparison was then made between eight different machine learning algorithms for predicting the value of the RWAs and we found that the best predictor is the linear regression. The RWA value is predicted to increase by 1.5%.

The determinants of the presence of “Foreign Doctorate Students” among 36 European Countries for the period 2010-2019 are analyzed in this article. Panel Data with Fixed Effects, Random Effects, WLS, Pooled OLS, and Dynamic Panel are used to investigate the data. We found that the presence of Foreign Doctorate Students is positively associated to “Attractive Research Systems”, “Finance and Support”, “Rule of Law”, “Sales Impacts”, “New Doctorate Graduates”, “Basic School Entrepreneurial Education and Training”, “Tertiary Education” and negatively associated to “Innovative Sales Share”, “Innovation Friendly Environment”, “Linkages”, “Trademark Applications”, “Government Procurement of Advanced Technology Products”, “R&D Expenditure Public Sectors”. A cluster analysis was then carried out through the application of the unsupervised k-Means algorithm optimized using the Silhouette coefficient with the identification of 5 clusters. Finally, eight different machine learning algorithms were used to predict the value of the "Foreign Doctorate Students" variable. The results show that the best predictor algorithm is the "Tree Ensemble Regression" with a predicted value growing at a rate of 114.03%.

The determinants of enterprises providing ICT training in Europe are analyzed in this article. Data are collected from the European Innovation Scoreboard-EIS of the European Commission for 36 European countries in the period 2000-2019. Data are analyzed with Panel Data with Fixed Effects, Panel Data with Random Effects, Dynamic Panel, WLS and Pooled OLS. Results show that the number of enterprises providing ICT training in Europe is positively associate with “Innovation Index”, “Innovators”, “New Doctorate Graduates”, “Tertiary Education” and negatively associated with “Government Procurement of Advanced Technology Products”, “Human Resources”, and “Marketing or Organisational Innovators”. In adjunct a cluster analysis is performed by using k-Means algorithm optimized with the Silhouette Coefficient and we find the presence of four clusters. Finally, we use eight different machine learning algorithms to predict the value of the enterprises providing ICT training in Europe. We found that the Simple Tree Regression is the best predictor and that the number of enterprises providing ICT training in Europe is expected to growth of the 5,02%.

Drying grains in a fixed bed can be an interesting alternative to prevent undesirable breaks and fractures of solids due to mechanical shocks, something that cannot be avoided when drying in moving beds. A disadvantage of fixed bed drying is that there can be significant gradients in the critical variables if the layer of particulate solids is thick. This work shows that periodically changing the direction of drying air flow is an effective technique to reduce differences within the bed and allow better uniformity of the product. Drying in a thick layer of 10 cm of sorghum grains was carried out at 50 and 60oC for air flow velocity of 2.1 m.s-1. The results showed that despite increasing the total drying time, the technique actually allowed a significant decrease in the temperature gradients and moisture content of the sorghum grains. The change in direction of the air flow caused the drying front to be displaced, sometimes towards the top, sometimes towards the base of the bed. At 50oC, drying lasted a total of 240 min, bringing the sorghum grains to an average overall moisture content of 0.13 on a dry basis.

This research investigates the exposure of plant species to extreme drought events in the Brazilian Atlantic Forest, employing an extensive dataset collected from 205 automatic weather stations across the region. Meteorological indicators derived from hourly data, encompassing precipitation, maximum and minimum air temperature, were utilized to quantify past, current, and future drought conditions. The dataset, comprising 10,299,236 data points, spans a substantial temporal window and exhibits a modest percentage of missing data. Missing data were excluded from analysis, aligning with the decision to refrain from imputation methods due to potential bias. Drought quantification involved the computation of the Aridity Index, the analysis of consecutive hours without precipitation, and the classification of wet and dry days per month. Mann-Kendall trend analysis was applied to assess trends in evapotranspiration and maximum air temperature, considering their significance. The hazard assessment, incorporating environmental factors influencing tree growth dynamics, facilitated the ranking of meteorological indicators to identify regions most exposed to drought events. The results revealed consistent occurrences of extreme rainfall events, indicated by positive outliers in monthly precipitation values. However, significant trends were observed, including an increase in daily maximum temperature and consecutive hours without precipitation, coupled with a decrease in daily precipitation across the Brazilian Atlantic Forest. No significant correlation between vulnerability ranks and weather station latitudes and elevation were found, suggesting geographical location and elevation does not strongly influence observed dryness trends.

The effect of the different dental implants positioning region on the stress performance of the implant-supported prosthesis is not yet clear. This study evaluated the dental treatment with six dental implants in three different models and three different occlusal loading conditions, in terms of the biomechanical response of implants, prosthetic screw and maxilla, using three-dimensional finite element analysis. The finite element models were modelled containing external hexagon implants, as well as a Cobalt-Chromium superstructure. Three types of loads were applied: in the area of ​​the central incisors, first premolar and in the second molars. For the finite element simulations, the von-Mises stress peaks in the implant and in the surrounding cortical bone were analyzed. All recorded results reported higher values ​​for the implant-supported prosthesis in group C compared to the groups A and B. The highest stress values, ​​regardless the evaluated model, was in the prosthesis in group C and in screws, the smallest were in group A.

This review summarizes the most recent developments of research on protozoan parasite infections ac-quired through food and drinking water and is aimed at gathering updated knowledge on the risk factors, illnesses caused, and measures for prevention. Reports included dated from 2019 to the present and regarded recent outbreaks and cases of severe infec-tions, prevalence in different population segments and food handlers, and occurrence in food and drinking water. Cryptosporidium spp., Entamoeba histolytica, Giardia intestinalis, Trypanosoma cruzi and Toxoplasma gondii were the microorganisms most frequently involved in large outbreaks and/or severe infections, while Cyclospora cayetanensis was most frequently involved in single case reports. Cystoisospora belli was implied in severe infections in immunocompromised patients, while Blastocystis homi-nis, Sarcocystis spp., Dientamoeba fragilis, Endolimax nana and Pentatrichomonas hominis appeared to be less relevant for number of symptomatic infections and pathogenic potential. A progressive improvement in surveillance of protozoan infections and infection sources was highlighted, especially in developed countries. The apparent increase in cases was concomitant with the implementa-tion of reporting systems and the application of molecular diagnostic methods that represent valuable in-struments for establishing epidemiological links and preventing or limiting outbreaks. The pathogenic role and sources of infection should be better elucidated for some species.

With the advancement of Additive Manufacturing and its applications in various industrial segments, it becomes increasingly important to investigate the processability parameters associated with nano-reinforcement. This study examines the influence of infill parameters, such as patterns (hexagonal, triangular and concentric), shape (solid and honeycomb) and concentrations by mass of Carbon Nanotubes (CNTs) at 1.0 wt% and 2.0 wt% on the mechanical compression properties of the 3D printed material. In this sense, nanocomposites based on Polylactic Acid (PLA) matrix nano-reinforced by CNTs were characterized using the Scanning Electron Microscopy -SEM, X-ray Diffraction, Raman Spectroscopy techniques and mechanical analysis. The mechanical properties of both the matrix and the nanocomposites were determined through mechanical compression tests, in accordance with [1]. SEM revealed compacted regions, voids, and detachment in the structures. XRD characterization indicated PLA predominantly amorphous nature, while CNTs exhibited characteristic diffractions of carbon nanotubes. Raman characterization showcased bands and characteristic vibrations of CNTs and PLA, nanocomposites' vibrational modes combine those of CNTs and PLA. Mechanical compression analysis indicates a direct influence of infill pattern, shape, and nano-reinforcement. The triangle pattern outperformed other patterns, exhibiting a 15.03% increase compared to concentric and 8.8% compared to hexagon infill. In nanocomposites, all showed higher compressive strength than the matrix. For PLA/1.0%CNTs, strength was 16.8%, and for PLA/2.0%CNTs, it reached 39.2%. In honeycomb shapes with infill variations, the triangular pattern excelled with a 0.97% increase over concentric and 6.12% over hexagon patterns. Honeycomb results indicate a 59.6% increase for (PLA/1.0%CNTs) and a 0.48% increase for (PLA/2.0%CNTs) compared to the matrix. This study highlights 3D printing parameters, emphasizing the effectiveness of the triangular pattern and the enhanced strength with the addition of CNTs, providing insights to enhance products manufactured through Additive Manufacturing.

Regardless of the SARS-CoV-2 pandemic containment, it remains paramount to comprehensively understand its underlying mechanisms to mitigate potential future health and economic impacts, comparable to those experienced throughout the course of the pandemic. The angiotensin-converting enzyme 2 (ACE2) provide anchorage for SARS-CoV-2 binding, thus implicating that ACE and ACE2 might contribute to the variability in infection severity. This study aimed to elucidate predisposing factors influencing the disease course among people infected by SARS-CoV-2, focusing on angiotensin-converting enzyme (ACE) and ACE2 polymorphisms. Notably, despite similar demographics and comorbidities, COVID-19 patients exhibit substantial differences in prognosis. Genetic polymorphisms in ACE and ACE2 have been implicated in disease progression, prompting our investigation into their role in COVID-19 evolution. Using next-generation sequencing (NGS), we analyzed ACE and ACE2 genes in a sample group comprising six subjects infected by SARS-CoV-2. Our findings revealed a correlation between specific polymorphisms and COVID-19 outcomes. Specifically, ACE and ACE2 intronic deletions were observed in all deceased patients, suggesting a potential association with mortality. These results highlight the significance of genetic factors in shaping the clinical course of COVID-19, emphasizing the importance of further research into the impact of genetic variations on COVID-19 severity.

The Atmospheric Dynamics Mission ADM-Aeolus was successfully launched in August 2018 by the European Space Agency (ESA). The Aeolus mission carried a single instrument, the first-ever Doppler Wind Lidar (DWL) in space, called Atmospheric LAser Doppler INstrument (ALADIN). Aeolus circled the Earth in a polar sun-synchronous orbit at about 320 km altitude with a repeat cycle of 7 days, providing vertical profiles of horizontal line-of-sight (HLOS) winds on a global scale. Exceeding scientific expectations, Aeolus, initially designed for a 3-year lifetime, provided global coverage of wind profiles for almost five years. In this long-term validation study, we assessed the accuracy of the Level 2B (L2B) Rayleigh-clear and Mie-cloudy wind products by collecting radiosonde data from three stations in the Brazilian Amazon: Cruzeiro do Sul (7.62° S, 72.67° W), Porto Velho (8.76° S, 63.91° W), and Rio Branco (10.00° S, 67.80° W). Statistical validation was conducted by comparing Aeolus L2B wind products and radiosonde data, launched daily at 12:00 UTC from October 2018 to March 2023. Considering all data collected during the mission period, Pearson’s coefficient (R) of 0.73 was observed in Rayleigh-clear and 0.85 in Mie-cloudy, revealing a strong correlation between Aeolus and radiosonde winds. No significant biases were detected, with values of -0.14 m/s for Rayleigh-clear and -0.40 m/s for Mie-cloud, fulfilling the mission requirement of having absolute biases below 0.7 m/s. However, when analyzed annually, in 2022, the bias for Rayleigh-clear was -0.95 m/s, exceeding the mission requirements.

Bovine herpesvirus (BoHV)-5 is a worldwide distributed pathogen usually associated with a lethal neurological disease (meningoencephalitis) in dairy and beef cattle resulting in important economic losses due to the cattle industry. Using recombinant glycoprotein D of BoHV-5 (rgD5), we evaluated the long-duration humoral immunity of the recombinant vaccines in a cattle model. Here we report that two doses of intramuscular immunization, particularly with the rgD5ISA vaccine, are superior to iBoHV-5ISA immunization in the induction of long-lasting antibody responses. Recombinant gD5 antigen elicited tightly mRNA transcription of the Bcl6 and the chemokine receptor CXCR5 which mediate memory B cells and long-lived plasma cells in germinal centers (GCs). In addition, using an in-house Enzyme-Linked Immunosorbent Assay (ELISA) we observed higher and earlier responses of rgD5-specific IgG antibody and the upregulation of mRNA transcription of IL2, IL4, IL10, IL15 and IFN-γ cytokines in rgD5 vaccinated cattle, indicating a mixed immune response. We further show that rgD5 immunization provides protection against both BoHV -1 and -5. Our findings indicate that the rgD5-based vaccine represents an effective vaccine strategy to induce an efficient control of alpha-herpesviruses.

Traditional dry fermented meat products are obtained artisanally in many countries, where they represent a gastronomic heritage well distinguished from industrial counterparts. This food category is most often obtained from red meat, a food commodity that is under attack because of evidences of increased risk of cancer and degenerative diseases with high consumption. However, traditional fermented meat products are intended for moderate consumption and gastronomic experience and, as such, their production must be continued also to safeguard culture and economy of the geographical areas of origin. In this review, the main risks attributed to these products are considered and how these risks are minimized by following precise production norms, respectful of the ancient manufacturing processes is described. Moreover, results obtained in studies reporting use of autochthonous microbial cultures of lactic acid bacteria (LAB), coagulase negative staphylococci (CNS), Debaryomyces hansenii and Penicillium nalgiovense to improve safety and quality of traditional fermented meats are summarized. The role of these products as a source of microorganisms that can be beneficial to the host are also considered. From the results of the studies reviewed here it appears that the development of autochthonous cultures for these foods ensure safety and stabilize sensory characteristics with possibility to be extended to the large variety of traditional productions.

During embryo development, the endoplasmic reticulum (ER) acts as an important site for protein biosynthesis, however, in vitro culture (IVC) can negatively affect ER homeostasis. Thereby, the aim of our study was to evaluate the effects of supplementation of tauroursodeoxycholic acid (TUDCA), an ER stress inhibitor, in the IVC of bovine embryos. Two experiments were carried out: Exp. 1: evaluation of blastocyst rate, hatching kinetics and gene expression of hatched embryos after being treated with different concentrations of TUDCA (50, 200 or 1,000 μM) in the IVC; Exp. 2: evaluation of the re-expansion, hatching, and gene expression of hatched embryos previously treated with 200 µM of TUDCA at IVC and submitted to vitrification. There was no increase in the blastocyst and hatched blastocyst rates treated with TUDCA in the IVC. However, embryos submitted to vitrification after treatment with 200 µM of TUDCA, increased hatching rate post-warming, together with a down-regulation in the expression of ER stress-related genes and the accumulation of lipids. In conclusion, this work showed that the addition of TUDCA during in vitro culture can improve the cryotolerance of the bovine blastocyst through the putative modulation of ER and oxidative stress.

Shear thickening fluids (STF) are a class of fluids whose viscosity significantly rises under external loads. The research on these fluids has been advancing in recent years regarding prospective practical applications, including developing impact-absorbing composites. Following the green agendas governments and legislators advocate, this study investigates the combination of STF and other sustainable materials. Cork is a naturally occurring cellular material with a negative carbon footprint and superior energy absorption properties. With varying concentrations of STF material, cork agglomerates were formed. Notably, the analysed blends are homogeneous, contrasting with previous literary works. A series of experiments were conducted in quasi-static and dynamic conditions to determine the various mechanical responses. STF appears to influence the mechanical behaviour of cork agglomerates by providing softer deceleration rates and dispersing more energy through disaggregation mechanisms.

This literature review was aimed to identifying the opportunistic bacterial pathogens that can be transmitted by contaminated food and represent a current threat for patients particularly suscep-tible to infections because of underlying conditions or predisposing factors. The analysis was focused on recent case or outbreak reports, and systematic reviews published in years 2019 - 2023 and resulted in sorting 24 bacterial groups comprising genera or species able to cause a variety of systemic or invasive infections if ingested with food or drinking water. These included both bacteria known to cause mild infections in immunocompetent persons and bacteria considered innocuous that are used in food fermentation or as probiotics. No recent cases from dietary routes were reported for bacteria of critical importance as nosocomial pathogens and widely occurring in food products, primarily, Acinetobacter baumanii and Klebsiella pneumoniae. However, the very first sources of their introduction in the clinical environment still need to be estab-lished. In many instances, risky dietary habits such as eating raw fish, seafood, raw meat, unpasteurized milk and derived products or the lack of control on fermentation processes led to the reported illnesses, pointing out to the necessity to improve the hygiene of production and consumer’s awareness of risks.

Deploying UAVs as aerial base stations is an exceptional approach to reinforce terrestrial infrastructure owing to their remarkable flexibility and superior agility. However, it is essential to design their flight trajectory effectively to make the most of UAV-assisted wireless communications. This paper presents a novel method for improving wireless connectivity between UAVs and terrestrial users through effective path planning. This is achieved by developing a goal-directed trajectory planning method using active inference. First, we create a global dictionary using TSPWP instances executed on various training examples. This dictionary contains letters representing available hotspots, tokens representing local paths, and words depicting complete trajectories and hotspot order. By using this world model, the UAV can understand the TSPWP’s decision-making grammar and how to use the available letters to form tokens and words at various levels of abstraction and time scales. With this knowledge, the UAV can assess encountered situations and deduce optimal routes based on the belief encoded in the world model. Our proposed method outperforms traditional Q-learning by providing fast, stable, and reliable solutions with good generalization ability.

IHepatitis C virus (HCV) has a high genetic diversity, with seven genotypes with 86 subtypes. This genetic variability confers persistence in the infection and escape of the immune system with evolution to cirrhosis and cancer. Environmental factors can contribute to different disease progression, being essential to assess the viral genotype in the infection and discuss the environmental particularities of Eastern Amazon, and the frequencies of Liver fibrosis between different HCV genotypes in patients living in a region of the Brazilian Eastern Brazilian Amazon. Consists in an observational cross-sectional study. Sociodemographic and clinical data of 76 individuals diagnosed with Hepatitis C between 2019 and 2020 in public health services were selected. Data collected was tabulated in Microsoft Excel 2010TM spreadsheets and analysed in GraphPad Prism 5.0TM. Liver fibrosis was associated with genetic subtypes. Subtype 1b was predominant (42.1%), followed by 1a (13%) and 3a (1.3%). 69.7% of participants had chronic hepatitis, with mild fibrosis (F1/F2) being the most prevalent (38.1%). Severe fibrosis was detected in 75% of individuals infected with the subtype 1b, that is associated with more severe disease. We suggest further studies, to assess other communities in the region, as well as the monitoring of these patients with Liver Elastography to determine the disease evolution and its better management.

Equipping autonomous agents for dynamic interaction and navigation is a significant challenge in intelligent transportation systems. This study aims to address this by implementing a brain-inspired model for decision-making in autonomous vehicles. We employ active inference, a Bayesian approach that models decision-making processes similar to the human brain, focusing on the agent's preferences and the principle of free energy. This approach is combined with imitation learning to enhance the vehicle's ability to adapt to new observations and make human-like decisions. The research involved developing a multi-modal self-awareness architecture for autonomous driving systems and testing this model in driving scenarios, including abnormal observations. The results demonstrated the model's effectiveness in enabling the vehicle to make safe decisions, particularly in unobserved or dynamic environments. The study concludes that the integration of active inference with imitation learning significantly improves the performance of autonomous vehicles, offering a promising direction for future developments in intelligent transportation systems.

Chitin and its derivative, chitosan, have diverse applications in fields such as agriculture, medicine, and biosensors, amongst others. Extraction is primarily conducted from marine sources, such as crustaceans, which have been the focus of optimization process studies. However, there are other sources that are more readily available, such as insects, where insufficient research has been conducted. The house cricket (Acheta domesticus) is a promising source for chitin extraction because of its high chitin content, availability, and short lifespan. Modern chemical chitin extraction methods have not been standardized due to the use of different reagents, molar concentrations, temperatures, and reaction times across publications. Therefore, in this study, the compositional analysis of Acheta domesticus cricket flour was determined: 2.62% humidity, 4.3% ash content, 56.29% protein, 13.35% fat, 23.44% carbohydrates, and 15.71% crude fiber content. After a drying, defatting, demineralization, deproteinization, and bleaching process, chitin extraction was performed, and chitosan was obtained via a deacetylation reaction. The demineralization process was standardized at 30ºC for 3 hours using HCl 2M, resulting in 95.85 ± 0.012%. The deproteinization process was optimized at 80ºC for 45 minutes using NaOH 2.56 M, yielding 46.37 ± 3.86%. Finally, the identity and physicochemical characteristics of the compounds were determined through characterization with FTIR, XRD, SEM and DSC.

Traumatic Brain Injury represents a significant public health concern due to its role in traumatic death and disability, often caused by head impacts or rapid accelerations. Despite advancements in Finite Element Head Models, existing models primarily represent adult males, neglecting anatomical and physiological differences between genders and age groups. Additionally, the mechanistic roles of specific intracranial tissues, such as the dura mater, have conventionally been overlooked. To better understand the mechanical behavior of the brain and its injured regions in the context of TBI, including the dura mater, this study proposes the development of a Female Finite Element Head Model. This model, representative of a middle-aged female subject, was developed using medical image-derived geometry and finite element modeling techniques. The validation results demonstrate a similarity between the numerical displacement curves and those obtained experimentally. In the model with dura mater, the numerical results show analogous behavior to the experimental results, despite minimal variations in the amplitude of the curves. These advancements highlight the significance of including the dura mater in biomechanical brain modeling. Incorporating the dura mater in Finite Element Head Models produces more realistic results than models without it. This emphasizes the importance of enhancing biomechanical models to better represent anatomical complexity.

Abstract: (1) Background: After the COVID-19 pandemic, there is increasing concern regarding the immunity of population to SARS-CoV-2 variants, particularly the Omi-cron variant and its sub-lineages. (2) Methods: The study involved analyzing the im-mune response and symptomatology of 27 vaccinated individuals who were subse-quently infected by Omicron sub-lineages. Blood samples were collected for serological analysis, including the detection of IgG antibodies reactive to the Nucleocapsid (N) and Spike (S) antigens of SARS-CoV-2. Additionally, participants were interviewed to assess the intensity of symptoms during the infection. (3) Results: Despite the high levels of anti-Spike IgG observed after vaccination, all participants were infected by Omicron sub-lineages. The most common symptoms reported by participants were fever or chills, sore throat, and cough. Surprisingly, the levels of anti-Spike IgG found prior to infection did not correlate with symptom severity post-infection. However, it was observed that high post-infection anti-Nucleocapsid IgG levels correlates with mild symptoms during the course of the disease, suggesting a potential role for anti-N antibodies in disease resolution. (4) Conclusions: The high levels of IgG anti-Spike resulting from vaccination may not provide complete protection against infection by the Omicron variant. Addi-tionally, our data suggest that anti-Nucleocapsid IgG titers are negatively correlated with the intensity of the symptoms during mild infections. These findings underscore the importance of ongoing surveillance of viral variants and continuous adaptation of vaccination strategies to ensure efficacy against SARS-CoV-2 variants.

Growing agricultural demands for the global population are unlocking the path to developing innovative solutions for efficient water management. Herein, an intelligent variable rate irrigation system (fuzzy-VRI) is proposed for rapid decision-making to achieve optimized irrigation in various delimited zones. The proposed system automatically creates irrigation maps for a center pivot irrigation system for a variable-rate application of water. Primary inputs are spatial imagery on remotely sensed soil moisture (SSM), soil adjusted vegetation index (SAVI), canopy temperature (CT), and nitrogen content (NI). To eliminate localized issues with soil characteristics, we used the crop nitrogen content map to provide a focused insight on issues related to water shortage. The system relates these inputs to set reference values for the rotation speed controllers and individual openings of each central pivot sprinkler valve. The results showed that the system can detect and characterize the spatial variability of the crop and further, the fuzzy logic solved the uncertainties of an irrigation system and defined a control model for high-precision irrigation. The proposed approach is validated through the comparison between the recommended irrigation and actual irrigation at two field sites, and the results showed that the developed approach gives an accurate estimation of irrigation with a reduction in the volume of irrigated water of up to 27% in some cases. Future research should implement the fuzzy-VRI real-time during field trials in order to quantify its effect on irrigation use, yield, and water use efficiency.

The flavor, aroma and color of coffee may change due to mechanical damage, reducing its qual-ity. To measure the mechanical response of materials, compression tests can be performed, de-termining the effect of force application on the mechanical behavior of the fruit at different stages of ripeness. In this context, this study aimed to analyze the deformation, strain energy and equivalent von Mises stress of coffee fruits at mature, semi-mature and immature maturation stages and compressed by collapse forces. Compression in three directions (x, y and z) was sim-ulated on coffee fruit models using the finite element method, with a compression support in the direction opposite to the force application axis. The numerical simulation of the compression process allowed to verify that the more mature the fruit, the greater the associated mean defor-mation (2.20 mm mm-1, 0.78 mm mm-1 and 0.88 mm mm-1), the lower the mean strain energy (0.07 mJ, 0.21 mJ and 0. 34 mJ) and the lower the mean equivalent von Mises stress (0.25 MPa, 1.03 MPa and 1.25 MPa), corresponding to ripe, semi-ripe and immature fruits; and these proper-ties may be used to analyze how processes in the production chain affect the amount of mechan-ical damage.

Considering the current needs of industry 4.0, especially in the condition of systems linked to artificial intelligence, this multidisciplinary concept work and difficult to execute, proposes the main idea of recognizing patterns using mathematical concepts of simple access and logical resolution of great potential. The objective of this work is to demonstrate a process for pattern recognition by applying the Fibonacci concept to vibration signals of hybrid dynamical systems. For this to be possible, it was necessary to use the concepts of preprocessing in a vector for pattern recognition, together with the concepts of the golden rule of Fibonacci, finally, all applied in the theorem of Jeffcott Rotors. The general result, from a technical point of view, demonstrates positivity and relationship of patterns, because, considering the aspect of the location between the values of the experimental and numerical result, both signs have similarities.

Diabetes Mellitus is one of the most prevalent chronic diseases in the world and one of its main features is chronic hyperglycemia. Among the therapeutic forms used to control the pathology are pharmacotherapy and the use of other alternatives such as regular exercise, which participates in glycemic control and the ingestion of plant extracts with antioxidant effects in the body. Among the different plants used, curcumin is a possible plant to be used to attenuate the hyperglycemic picture triggered by Diabetes Mellitus. Some studies suggest that this plant is antioxidant and hypoglycemic. The review aimed to know the antioxidant and hypoglycemic potential of curcumin supplementation in DM. The search was performed considering articles published between 2010 to 2019, in English and Portuguese, and a theoretical survey of relevant information was conducted in the main databases of scientific publications: Virtual Health Library and its indexed databases as Pubmed, LILACS, Scielo and Scientific Electronic Library Online. The associated use Turmeric and Physical Exercise demonstrated antioxidant, anti-inflammatory and hypoglycemic activity caused by Diabetes Mellitus. We may suggest that these are potential therapeutic ways to improve the quality and survival of diabetic patients.

Adaptations to climate change rely on understanding the dynamics of plant biomass stocks on the planet. The high levels of deforestation in Cerrado have transformed this biome into the second-largest Brazilian source of carbon emissions. The objective of this study was to develop a method to accurately estimate aboveground and total biomass values among shrublands, savannas, and forests located in the Cerrado biome, using an allometric equation adjusted from canopy height, obtained through optical and laser sensors. The results show similarity between the estimates employed by our method and the data found in the literature review for different phytophysiognomies in the Cerrado biome. Shrubland formations showed higher biomass estimation uncertainties due to the discontinuity of isolated trees and the lower canopy height when compared to more clustered tree canopies in savannas and taller canopies in forests. Aboveground biomass estimates were related to expansion factors, and specific maps were developed for each compartment by root, litter, and necromass. The sum of these compartments is presented in the aboveground and below forest biomass map. This study presents, for the first time, the mapping of total biomass in 10 m pixels of all regions of the Cerrado biome.

Abstract: Lipodystrophies (LDs) are rare, complex disorders of the adipose tissue characterized by selective fat loss, altered adipokines profile and metabolic impairment. Sirtuins (SIRTs) are class III NAD+-dependent histone-deacetylases linked to fat metabolism. SIRT1 plays a critical role in metabolic health by deacetylating target proteins in tissues including liver, muscle and adipose tissue. Circulating SIRT1 levels have been found to be reduced in obesity while increased in anorexia nervosa and in patients experiencing weight loss. We evaluated circulating SIRT1 levels in relation to fat amount in 32 lipodystrophic patients affected by congenital or acquired LDs compared to non-LD subjects (24 with anorexia nervosa, 22 normal weight and 24 with obe-sity). SIRT1 serum levels were higher in LDs as compared with normal weight subjects (mean ± SEM: 4.17 ± 0.48 vs. 2.59 ± 0.20 ng/mL) or subjects with obesity (1.7 ± 0.39 ng/mL), whereas they were close to those measured in anorexia nervosa (3.44 ± 0.46 ng/mL). Our findings show that within the LD group there was no relationship between SIRT1 levels and the amount of body fat. The mechanisms responsible for secretion and regulation of SIRT1 in LD deserve further investi-gation.

The first treatments with dental implants had low success rates (75%). Nowadays, oral rehabilitation with titanium dental implants has a high success rate (95-98%). The success rate significantly increases due to increased scientific knowledge about osseointegration, changes in surgical techniques, and the development of implant surface treatments. Despite the high success rate of implants, no protocol defines the time for the prosthesis to be installed and loaded after surgery. This work compares a new dental implant's primary (mechanical) and secondary (osseointegration) stability. Dental implant with micro- and nano-roughness surface was placed in 24 patients with a minimum of 35 N.cm and a maximum of 60 N.cm. Primary stability was quantified with a torque wrench and Ostell Mentor. The secondary stability 45 and 60 days after surgery was measured with Ostell. The results showed no statistical difference in secondary stability at 45 and 60 days postoperatively among implants. The success rate of dental implants can be associated with the surface morphology with micro and nano-roughness and the shape of the fillets of the implant threads. When the manufacturer's guidelines are followed, it is possible to prosthetically rehabilitate the patient with an implant 45 days after surgery.

Over the last decade, the therapeutic scenario for advanced non-small-cell lung cancer (NSCLC) has undergone a major paradigm shift. Immune checkpoint inhibitors (ICIs) have shown a meaningful clinical and survival improvement in different settings of the disease. However, the real benefit of this therapeutic approach remains controversial in selected NSCLC subsets, such as those of the elderly with active brain metastases or oncogene-addicted mutations. This is mainly due to the exclusion or underrepresentation of these patient subpopulations in most of the pivotal phase III studies; this precludes the generalization of the ICI efficacy in this context. Moreover, no predictive biomarkers of ICI response exist that can help with patient selection for this therapeutic approach. Here, we critically summarize the current state of ICI efficacy in the most common “special” NSCLC subpopulations.

This literature review was aimed to collect investigations on the in vivo evidences for bacteria associated to fermented dairy foods to behave as probiotics with beneficial effects in the prevention and treatment of various diseases. All main bacterial groups commonly present in high numbers in fermented milks or cheeses were taken into account, namely starter lactic acid bacteria (SLAB) Lactobacillus delbrueckii subsp. bulgaricus and lactis, L. helveticus, Lactococcus lactis, Strepto-coccus thermophilus, non starter LAB (NSLAB) Lacticaseibacillus spp., Lactiplantibacillus plantarum, dairy propionibacteria and other less frequently encountered species. Only studies regarding strains of proven dairy origin were considered. Studies in animal models and clinical studies showed that dairy bacteria ameliorate symptoms of inflammatory bowel disease (IBD), mucositis, metabolic syndrome, aging and oxidative stress, cancer, bone diseases, atopic dermatitis, allergies, infections and damages caused by pollutants, mild stress and depression. Immunomodulation and changes in the intestinal microbiota were the mechanisms most often involved in the observed effects. The results of the studies considered indicated that milk and dairy products are a rich source of beneficial bacteria that should be further exploited to the advantage of human and animal health.

Using the sustainable livelihoods analytical framework, adaptability of cattle raising to multiple stressors (e.g. climate change and market conditions) in the dry tropics of Chiapas, Mexico was evaluated. Three case studies located in the Frailesca region of Chiapas were analyzed: (I) peasant cattle raising in a rural village in the Frailesca Valley; (II) peasant cattle raising in a rural village in a natural protected area in the Frailesca Highlands; and (III) holistic cattle raising by farmers with private land ownership in the Frailesca Valley. Adaptability was evaluated using an index on a scale of one to a hundred; average values were: case I = 20.9 ± 1.4; case II = 32.1 ± 1.8; and case III = 63.6 ± 3.5. In order to increase farms adaptability and reduce the vulnerability of cattle raising families, there is a need to modify public policy to take into account the conditions of the most vulnerable farmers (cases I and II). Given the economic, environmental, and social context of Mexico´s dry tropics, establishing ecological or organic cattle raising and silvopastoral systems may reduce the vulnerability of farm families and increase their level of adaptability of their farms to multiple stressors.

In recent years, many studies have highlighted the consistent finding of amoxicillin in waters destined for wastewater treatment plants, in addition to superficial waters of rivers and lakes in both Europe and North America. In this paper, the amoxicillin degradation pathway was investigated by simulating the chlorination process normally used in a wastewater treatment plant to reduce similar emerging pollutants at three different pH values. The structures of 16 isolated degradation byproducts (DPs), one of which was isolated for the first time, were separated on a C-18 column via a gradient HPLC method. Then, combining mass spectrometry (MALDI-MS/TOF) and nuclear magnetic resonance, we compared commercial standards and justified a proposed formation mechanism beginning from the parent drug. Microbial growth inhibition bioassays with Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus were performed to determine the potential loss of antibacterial activity in isolated degradation byproducts. An increase of antibacterial activity in the DPs was observed compared to the parent compound.

The impact of systemic vascular resistance (SVR) in hypertrophic (HCM) and amyloid cardio-myopathies has been seldom investigated. We studied pressure-strain loop derived myocardial work (MW) indices and SVR in patients with either sarcomere HCM or wild type transthyretin cardiac amyloidosis (ATTR), presented with heart failure and preserved left ventricular ejection fraction (HFpEF) at the outpatient cardiology units at Messina and Catania University Hospitals (Italy). Patients were in sinus rhythm and needed to have good transthoracic ultrasound imaging quality to undergo transthoracic strain-echocardiography. Other than conventional parameters, SVR and GWI (global work index) were measured. Based on cross-tabulation (a way to assess the ventricular-arterial coupling), the patients were then classified in 4 classes according to the cut-off values suggested by previous studies of 1,440 dyne/s/cm-5 for SVR (Stefadouros et al., 1973) and 1576 mm Hg% for GWI (Olsen et al., 2022). Sixty patients, 30 in each group, aged 61±16 years, 78% males, were studied. HCM were younger than ATTR patients and in a better clinical status (23% HCM vs 77% ATTR were NYHA class 3, p<0.001). Overall, 51 patients (85%) showed high SVR, of whom 21 were HCM (70%) and 30 ATTR (100%) (p<0.005). Both, SVR and GWI were impaired (the poorest class C) in 43% HCM patients (with greater left ventricular concentric hypertrophy) vs 93% of ATTR patients (in advanced NYHA class) (p<0.001). In conclusion, assessing SVR and GWI in HFpEF patients with HCM or ATTR can help clinicians to interpret the pathophysiological and clinical features of such complex diseases.

The consumption of fiber in the human diet is a global recommendation to ensure a healthy diet. Quinoa (Chenopodium quinoa Willd.), a gluten-free grain, and chia (Salvia hispanica), a seed, contain high fiber content and both have the potential to be explored in the development of nutraceutical and pharmaceutical formulations. An interesting characteristic of chia is its ability to form viscous mucilage when in contact with water, bringing the prospect of a binder in solid formulations. To produce tablets with a high fiber content, it is more appropriate to transform the material into granules using a wet process, with the help of a tool that exploits this possibility. Therefore, the objective of the present work was to study, using the Mixer Torque Rheometer, the feasibility of using chia as a binder to produce granulated quinoa and the development of chewable tablets. To this end, an experimental design was carried out to evaluate the impact of variables on the rheometer results for subsequent granulation. It was possible to obtain the granulation point for the formulations and after producing the granules, physical tests were carried out in which we noticed improvements in the flow. In the end, a formulation was selected for the development of chewable tablets containing quinoa and chia fibers.

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

The evolution of knowledge in biological and medical areas which made possible scientific and technological advances are attributed to anatomical studies, physiology and immunology in animals, contributing to the discovery of prophylactic measures and treatments of diseases that affect humans and animals. Currently, substitution is suggested by alternative methods that do not use laboratory animals, however in vitro methods may never be able to provide similar results to in vivo methods. Mice and rats are the most used animals in experimental researches, the anatomical, histological and genetic differences between species should be carefully evaluated, to better apply the study model and avoid unnecessary waste avoid. This study, aimed at an anatomical comparative and histological relationship between a rat´s and a mouse´s organs, is of great importance in experimental studies. For such, 30 Mus musculus (Swiss) mice and 15 Rattus norvegicus (Wistar) male and heterogenic rats, were used. All animals were kept free of pathogenic microorganisms, with the absence of surgical interventions that could cause anatomical and physiological changes. It was possible to observe significant anatomical and histological differences between spleens, brains, hearts, stomachs and intestines, livers, eyes, lungs and kidneys among species, which will serve as a basis to assist in choosing the most satisfactory research model. Few studies relate specific characteristics among laboratory animals, being restricted to a few veterinary and zoology books. The greater the organic, physiological and anatomical similarities are with the human being, the greater is the applicability of the animals in studies. However, it is not possible to lay down general rules to validate the extrapolation from one species to another.

In virology, the term reverse genetics refers to a set of methodologies in which changes are introduced into the viral genome and their effects on the generation of infectious viral progeny and their phenotypic features are assessed. Reverse genetics emerged thanks to advances in recombinant DNA technology, which made the isolation, cloning, and modification of genes through mutagenesis possible. Most virus reverse genetics studies depend on our capacity to rescue an infectious wild-type virus progeny from cell cultures transfected with an “infectious clone”. This infectious clone generally consists of a circular DNA plasmid containing a functional copy of the full-length viral genome, under the control of an appropriate polymerase promoter. For most DNA viruses, reverse genetics systems are very straightforward, since DNA virus genomes are relatively easy to handle and modify and are also (with few notable exceptions) infectious per se. This is not true for RNA viruses, whose genomes need to be reverse transcribed into cDNA before any modification can be done. Establishing reverse genetics systems for members of the Caliciviridae has proven exceptionally challenging, due to the low number of members of this family that propagate in cell culture. Despite the early successful rescue of a calicivirus from a genome-length cDNA more than two decades ago, reverse genetics methods are not routine procedures that can be easily extrapolated to other members of the family. Reports of calicivirus reverse genetics systems have been few and far between. In this review, we discuss the main pitfalls, failures, and delays behind the generation of several successful calicivirus infectious clones.

Angiogenesis is new blood vessel formation from existing vessels and is a critical first step in tissue repair following chronic disturbances in healing and degenerative tissues. Chronic pathoanatomic tissues are characterized by a high number of inflammatory cells, overexpression of inflammatory mediators, such as tumor necrosis factor-α (TNF-α) and interleukin-1 (IL-1), the presence of mast cells, T cells, reactive oxygen species, and matrix metalloproteinases, and a decreased angiogenic capacity. Multiple studies have demonstrated that autologous orthobiological cellular preparations (e.g., platelet-rich plasma [PRP]) im-prove tissue repair and regenerate tissues. There are many PRP devices on the market. Unfortunately, they differ greatly in platelet numbers, cellular composition, and bioformulation. PRP is a platelet concentrate consisting of a high concentration of platelets with or without certain leukocytes, platelet-derived growth factors (PGFs), cytokines, molecules, and signaling cells. Several PRP products have immunomodulatory capacities that can influence resident cells in a diseased microenvironment, inducing tissue repair or re-generation. Generally, PRP is a blood-derived product, regardless of its platelet number and bioformulation, and the literature indicates both positive and negative patient treatment outcomes. Strangely, the literature does not designate specific PRP preparation qualifications that can potentially contribute to tissue re-pair. Moreover, the literature scarcely addresses the impact of platelets and leukocytes in PRP on (neo)angiogenesis other than a general one-size-fits-all statement that “PRP has angiogenic capabilities.” Here, we review the cellular composition of all PRP constituents, including leukocytes, and describe the importance of platelet dosing and bioformulation strategies in orthobiological applications to initiate angiogenic pathways that re-establish microvasculature networks, facilitating the supply of oxygen and nutrients to impaired tissues.

Nowadays, we can observe a worldwide trend towards the development of synthetic biomaterials. Numerous researches have been carried out in order to better understand the cellular behavior involved in the inflammation and bone healing processes related to living tissues. The aim of this study is to evaluate the tissue behavior of two different types of biomaterials: synthetic nano-hydroxyapatite / beta-tricalcium phosphate and hydroxyapatite in non-critical bone defects in rat calvaria. Twenty four rats underwent surgery in which two 3 mm defects in each cavity were performed. The rats were divided into 2 groups: Group 1, using xenogen hydroxyapatite (Bio oss ™); Group 2, using synthetic nano-hydroxyapatite / beta-tricalcium phosphate (Blue Bone ™). Sixty days after the surgery, the calvaria bone defect was filled with biomaterial, the animals were sacrificed and marked with Masson's trichrome and PAS staining, and immunohistochemistry (TNF-α, MMP-9) and electron microscopy analyzes were performed. Histomorphometric analysis indicates a greater presence in the protein matrix in Group 2, in addition to higher levels of TNF-α, MMP-9. The ultrastructural analysis shows an association of material with fibroblasts in the tissue regeneration stage. Paired statistical data indicates that Blue Bone ™ can improve bone formation / remodeling when compared to biomaterials of xenogenous origin.

Every year around 800 000 people commit suicide, this represents one death every 40 seconds. In the search for possible biological biomarkers associated with suicide and/or psychiatric disorders, serum cholesterol levels have been extensively explored. Several studies have indicated that cholesterol and associated proteins, especially apolipoproteins (Apos), may play an important role in the diagnosis, prognosis, and susceptibility of suicide. Here, we describe the current knowledge and findings in the relationship between apolipoproteins and suicide.

Autologous platelet-rich plasma (PRP) preparations are prepared at point of care. Centrifugation cellular density separation sequesters a fresh unit of blood into three main fractions: a platelet-poor plasma (PPP) fraction, a stratum rich in platelets (platelet concentrate) and, bioformulation dependent, also leukocyte and erythrocyte fractions. The employment of autologous platelet concentrates facilitates the biological potential to accelerate and support in numerous cellular activities that can lead to tissue repair, tissue regeneration, wound healing, and ultimately functional structural repair. Normally, after PRP preparation the PPP fraction is discarded. One of the less well known, but equally important features of PPP is that particular growth factors (GFs) are not abundantly present in PRP, as they reside outside the platelet alpha granules. Precisely, insulin-like growth factor-1 (IGF-1) and hepatocyte growth factor (HGF) are mainly present in the PPP fraction. In addition to their roles as angiogenesis activators, these plasma-based GFs are also known to inhibit inflammation, fibrosis, and they promote keratinocyte migration and support in tissue repair and wound healing. Additionally, PPP is known for the presence of exosomes and other macrovesicles, exerting cell-cell communication and cell signaling. Newly developed ultrafiltration technologies incorporate PPP processing methods by eliminating in a fast and efficient manner plasma water, cytokines, molecules, and plasma proteins with a molecular mass (weight) less than the pore size of the fibers. Consequently, a viable and viscous protein concentrate of functional, total proteins, like fibrinogen, albumin, and alpha-2-macroglobulin is created. Consolidating a small volume of high platelet concentrate with a small volume of highly concentrated protein-rich PPP creates a protein rich platelet concentrate (PRPC) biological preparation. After the activation of proteins, mainly fibrinogen, the PRPC matrix retains and facilitates interactions between invading resident cells, like macrophages, fibroblast, and mesenchymal stem cells (MSCs), and the embedded concentrated PRP cells and molecules. The administered PRPC biologic will ultimately undergo fibrinolysis, leading to a sustained release of concentrated cells and molecules that have been retained in the PRPC matrix until the matrix is dissolved. We will discuss the unique biological and tissue reparative and regenerative properties of PRPC matrix.

Firocoxib is a non-steroidal anti-inflammatory drug specifically formulated for veterinary medicine and selectively acts on inhibiting the cyclooxygenase 2 enzyme(COX-2). This study aimed to evaluate the possible adverse effects of administering oral therapeutic firocoxib on gastric mucosa, hematological parameters, coagulation cascade, and hepatic and renal biochemistry in healthy horses. Nine clinically healthy Arabian horses, approximately nine years old, received 0.1mg/kg of oral firocoxib for 14 days. Before beginning treatment, a gastroscopic examination was conducted, and venous blood samples were obtained for laboratory tests on D0. Follow-up blood samples and gastroscopic examinations were taken on D7 and D14 after starting treatment and one week after completing treatment on D21. No changes were found in the gastroscopic and hematological tests. Additionally, coagulation and serum biochemistry levels remain between normal values for this particular species. However, the increased activated partial thromboplastin time (aPTT) and prothrombin time (PT) indicate reduced blood coagulation capacity, which contradicts the expected effect of treatment with selective COX-2 inhibitors, as these drugs theoretically promote coagulation. Administering Firocoxib to horses is safe as it does not cause any significant adverse reactions. Therefore, it is a suitable option for managing inflammatory conditions in these animals.

Marine environments represent a great opportunity for the discovery of compounds with a wide spectrum of bioactive properties. Due to the privileged conditions of natural selection, marine natural products are subject to overcome the pressure put on identify novel drugs; not only in the case of newly discovered bioactive metabolites, but also in those previously known. Since drug resistance has caused an increase in infections caused by tuberculous and nontuberculous Mycobacteria, the re-evaluation of known bioactive metabolites has been suggested as a means to address this problem. In this sense, this study presents an evaluation of in vitro effect of laurinterol (1) and aplysin (2), two brominated sesquiterpenes isolated from Laurencia johnstonii against nine Mycobacterium tuberculosis strains and six nontuberculous mycobacteria. Laurinterol (1) exhibited good anti-tuberculous activity, especially against nontuberculous mycobacteria, being remarkable the effect against M. abscessus with MIC values lower than the reference drug imipenem. This study provides further evidence for the antimycobacterial activity of some sesquiterpenes from L. johnstonii, that can be considered an interesting lead compound for the discovery of novel antimycobacterial molecules to treat NTM infections.

Today, polymeric Drug Delivery Systems (DDS) appear as an interesting solution against bacterial resistance, having great advantages such as low toxicity, biocompatibility, and biodegradability. In this work, two polyketones (PK) have been post-functionalized with taurinate (PKT) or sulfanilate (PKSK) and employed as biocompatible carriers for Vancomycin against bacterial infections. Mod-ified PKs were easily prepared by Paal-Knorr reaction and loaded with Vancomycin at variable pH. All polymers were characterized by FT-IR, DSC, TGA, SEM and elemental analysis. Antimicrobial activity was tested against Gram positive Staphylococcus aureus ATCC 25923 and correlated to the different pH used for its loading (between 2.3 and 8.8). Distinctively, minimum inhibitory con-centrations achieved with PKT and PKSK loaded with Vancomycin are similar, 0.23μg/mL and 0.24μg/mL respectively, i.e. six times lower that Vancomycin alone. The use of post-functionalized aliphatic polyketones has thus been demonstrated to be a promising way to obtain very efficient polymeric DDS.

The aim of this study was to evaluate whether alterations in food availability compromise the metabolic homeostasis of honey bees exposed to three fungicides alone or together. Ten honey bee colonies were utilized, with half receiving energy-protein supplementation for 15 weeks while another five colonies had their protein supply reduced with pollen traps. Subsequently, forager bees were collected and exposed by contact to 1 or 7 µg of bixafen, prothioconazole, and trifloxystrobin, either individually or in combination. After 48 hours, abdomens without the intestine was used for the analysis of expression of antioxidant genes (SOD-1, CAT, and GPX-1), detoxification genes (GST-1 and CYP306A1), the storage protein gene vitellogenin, and immune system antimicrobial peptide genes (Defensin-1, Abaecin, Hymenoptaecin, and Apidaecin), through real-time PCR. All pesticide treatments induced changes in gene expression, with bixafen showing the most prominent upregulation. Exposure to 1 µg of each of the three pesticides resulted in upregulation of genes associated with detoxification and nutrition processes, and downregulation of immune system genes. When the three pesticides were combined at a dose of 7 µg each, there was a pronounced downregulation of all genes. Dietary supplementation led to a slight reduction in gene expression alterations provoked by the fungicides.

Water resources are under pressure because of human activities. Its management faces the challenge of enhancing long-term water security while minimizing undesirable economic, social, and environmental impacts along with its production chain. Since water and wastewater treatment plants are designed to maintain and conserve freshwater provisioning services, it is paramount to understand how it operates before proposing options for sustainability. At this point, the diagnosis phase claims for methods scientifically-based, systemic, and more objective to provide information for decision-makers towards strategic management of water resources. This work applies the five-sector sustainability model (5SenSu) to assess Brazil's twenty major water and wastewater treatment companies (WWTC) to quantify their sustainability levels that allow ranking procedures and the establishment of benchmarks for improvements. Under comparative basis, results identified the top-three sustainable companies, CORSAN, CASAN, and SANEPAR, which should be considered examples of best practices. Specifically, the following best-ranked companies in each sector within 5SenSu should be used as benchmark patterns for more oriented best practices: SANEAGO, sector 1; AGESISA, sector 2; CORSAN, sector 3; CASAL, sector 4; MA, sector 5. This work contributes to the advancement in modeling sustainability assessment of human-managed systems (applied in WWTCs in this present study) from a systemic and epistemologically rooted approach, avoiding shortcomings and misleading discussions on the sustainability issue. Quantifying sustainability of WWTCS from 5SenSu allows the identification of those sectors/indicators that requires immediate cleaner production practices by decision-makers to improve overall sustainability, besides identifying those companies more aligned with the requirements of UN SDGs.

There is only a very short reaction time for people to find the best way out of a building in a fire outbreak. Software applications can be used to assist the rapid evacuation of victims; however, this is an arduous task, which requires an understanding of advanced technologies. Since well-known pathway algorithms (such as, Dijkstra, Bellman-Ford and A*) can lead to serious problems over performance, we decided to make use of deep reinforcement learning techniques. A wide range of strategies including a random initialization of replay buffer and transfer learning were assessed in three projects involving schools of different sizes. The results showed the proposal was viable and that in most cases the performance of transfer learning was superior. In addition, the study raised challenges that had to be faced in the future.

This study analyzed the relationship between anthropometric measures, cardiorespiratory capacity, strength, power and local muscle endurance with performance in the CrossFit® Open 2020. For this, 17 volunteers (6 women) (29.0 ± 7.2 years; 70.5 ± 9.8 kg) completed, on separate weeks, body composition (dual-energy x-ray absorptiometry), maximal oxygen consumption (2km row test), muscle strength (1RM back and front squat, isometric peak torque), and muscle power (1RM snatch and clean &amp; jerk), and muscle endurance (Tibana test), which were compared with performance during the CrossFit® Open 2020. Multiple linear regression showed that for the CrossFit Open 2020.1 and 2020.2 workouts, the score in the Tibana test was the only variable that explained the outcomes (Beta = -0.78, p &lt; 0.01 for 2020.1 workout and Beta = 0.82, p &lt; 0.01 for 2020.2 workout). Performance in the CrossFit Open 2020.3 and 2020.4 workouts were explained through the relative strength (Beta = 0.58, p = 0.02 for 2020.3 workout and Beta = 0.50, p = 0.04 for 2020.4 workout). Lastly, Tibana test had the greatest influence on CrossFit Open 2020.5 workout (Beta = -0.75, p &lt; 0.01). A local muscle endurance and muscle strength may be used to predict CrossFit® open workout performance.

Helicobacter pylori infection affects over 50% of the world population and leads to chronic inflammation and gastric disorders, being the main pathogen correlated to gastric cancer development. The increasing on antibiotic resistance levels is a major global concern and alternative treatments are needed. Soybean peptides and other compounds might be an alternative in the treatment to avoid, eradicate and/or control symptoms of H. pylori infection. This study aimed to characterize a lunasin-enriched soybean extract (LSE) by proteomics tools and to evaluate its antioxidant, anti-inflammatory and antibacterial properties against H. pylori infection. By LC-MS/MS analysis, 124 proteins were identified, with the 2S albumin (lunasin and large chain subunits) being the fourth most abundant protein (8.9%). Lunasin consisted of 44 amino acid residues and an intramolecular disulfide bond. LSE at a low dose (0.0625 mg/mL) reduced ROS production in both H. pylori-infected and non-infected AGS gastric cells. This led to a significant reduction of 6.71% in the levels of pro-inflammatory interleukin (IL)-8. LSE also showed antibacterial activity against H. pylori which can be attributed to other soybean proteins and phenolic compounds. Our findings suggest that LSE might be a promising alternative in the management of H. pylori infection and associated symptoms.

Honey bee colonies rapidly decline when confined to greenhouses, increasing pollination rental costs as they need to be replaced frequently. We tested a hive system with entrances that can be manipulated to direct bees to inside or outside greenhouses containing a zucchini crop. In one greenhouse, the bees could only forage inside for 15 days; in another, bees were directed to the inside from 5 to 9 AM, after which they foraged outside. This procedure was repeated two more times in each greenhouse with new hives. Data was collected on how the number of bee flower visits affected fruit production, the frequency of flower visits, and the amount of bee brood and food in the hives. Flowers visited by bees four times or more set more and larger fruit. The frequency of flower visits by bees from the hives confined to the greenhouse was reduced after eight days; it was not reduced in the greenhouse with bees that could forage outside. Bee brood area was reduced in the colonies that were confined to the greenhouse, while it was maintained in the semiconfined hives. The hive system with controllable entrances proved effective for pollination, while causing less damage to the bees.

Indices such as Body Mass Index (BMI), Waist Circumference (WC) and Waist to Height Ratio (WHtR) have emerged as tools to assess cardiovascular risks associated with abdominal obesity. The Timed Up and Go Test (TTUG) assesses mobility and the risk of falls, especially in the elderly and individuals with physical limitations. Objective: To correlate anthropometric indicators of cardiovascular risk (BMI, WC, WHtR) and performance in the TTUG in elderly people who practice physical activity. Methods: Cross-sectional study, CAAE: 27116319.1.0000.8044, elderly people, both sexes, average age 68 years. Anthropometric data was collected: BMI, WC, WHtR and TUG test results. Results: Average values: weight (67.8 ± 12.7 kg), height (157.2 ± 8.4 cm), TTUG (10.3 ± 2.5 26 seconds), WC (93.3 ± 10.9 cm), waist-to-height ratio (0.59) and BMI (27.4 ± 4.4): Correlations between 27 TTUG and age (r = -0.086, p = 0.683), TTUG and BMI (r = 0.29, p = 0.892) WC and WHtR (r = 0.927, p 28 < 0.001). Conclusion: This study revealed correlations between anthropometric indicators of cardio vascular risk (BMI, waist circumference, waist-to-height ratio) and performance in the TUG test in the elderly.

The objective of this study was to perform a systematic review and meta-analysis of the articles that addressed the effect BA or carnosine supplementation on physical exercise (PE)-induced oxidative stress (OS). Before May 2018 we searched throughout PubMed, CAPES Periodic and SPORTDiscus human model peer review, randomized control studies with chronic BA or carnosine supplementation on PE-induced OS. A total of 128 citations were found. Only four articles met criteria for inclusion. All four studies used healthy young sedentary, recreationally active or athletic participants. After a chronic BA or carnosine supplementation, the studies evaluated PE-induced OS both immediately and several hours after exercise (0.5 to 48 h). In response to PE-induced OS, when compared to placebo, BA/carnosine supplementation increased total antioxidant capacity [TAC; Effect Size (ES) = 0.35, 95% Confidence Interval (CI) 0.06 to 0.65, p = 0.02] and glutathione (GSH; ES = 0.75, 95% CI 0.32 to 1.19, p = 0.0007) concentrations while decreased direct OS markers (ES = −1.19, 95% CI −1.48 to −0.80, p < 0.01) and superoxide dismutase (SOD) activity (ES = − 0.58, 95% CI −1.10 to −0.06, p = 0.03). BA or carnosine supplementation did not prevent the increase in indirect OS markers (ES: 0.06, 95% CI −0.38 to 0.500, p = 0.80). In humans, following PE-induced OS, initial treatment trials of BA or carnosine supplementation seemed to increase TAC and GSH concentrations, while decreasing SOD activity. Also, albeit mitigating the acute increase in direct OS markers (reactive nitrogen and oxygen species), treatment did not decrease measured values of indirect OS markers (peroxidation or molecule oxidation).