This study investigated the adaptability of Dunaliella salina to different salinity levels, with emphasis on growth, pigment concentration, and desalination potential. It was found that among the 21 salinity levels, salinity 75 produced consistently favorable results in cell count (13.08 x 10³ ± 1.41 x 10³ cells/mL), dry biomass (2.46 ± 0.06 g/L), pigment content (chlorophyll a = 97.5 ± 0.1 µg/L, chlorophyll b = 123.6 ± 0.3 µg/L), and desalination (9.32 ± 0.47 reduction). Therefore, salinity 75 was selected for the final trial (scale-up), which revealed unanticipatedly high cell counts (58.96 x 10³ ± 535.22 cells/mL), with dry biomass weight being statistically different (higher) than the expected (4.21 ± 0.02 g/L) (p<0.0001), most likely due to high cell count and energy reserve storage for high salinity adaption in the form of bio-compounds. Pigment growth continued (chlorophyll a = 95.4 ± 2.2 µg/L, chlorophyll b = 128.1 ± 5.1 µg/L), indicating pigment production under salt stress. Notably, desalination did not occur in this stage, possibly due to the necessity for a bigger initial inoculate, prolonged exposure or bioaccumulation becoming the prevailing mechanism over desalination. Nevertheless, the trial highlights D. salina's strong adaptation to various salinity levels. This suggests a promising future in halophyte research, particularly in understanding the mechanisms that prevent salt accumulation in cells and how to overcome this barrier. Additionally, these results suggest that microalgae could be a viable resource in saline-rich environments unsuitable for conventional agriculture, promoting industrial adaptation to adverse conditions.

Then the purposes of this study were to compare and correlate the aerobic threshold (TH_aer) and anaerobic threshold (TH_anaer) measured during a new single judo specific incremental test and Treadmill Test for aerobic demand evaluation. Eight well-trained male competitive judo players (24.3±7.9 years; height of 169.3±6.7cm; fat mass of 12.7±3.9%) performed a maximal incremental specific test for judo mimicking the UchiKomi drills and on treadmill in different days. There was difference between specific and general TH_aer (P=0.0006) as well as weak correlation for TH_aer (r=0.32; R²=0.1; P=0.2) and TH_anaer (rs=-0.31; R²=0.1; P=0.12). When correlation was applied with normalized data (percentage of peak load) we observed moderate correlation for TH_aer (r=0.76; R²=0.58; P=0.027), but the same was not observed for TH_anaer. We conclude that there is a need of TH_aer and TH_anaer evaluation through a specific test for Judo.

In our study, we investigated the prognostic significance of hematological markers—NLR (Neutrophil-to-Lymphocyte Ratio), PLR (Platelet-to-Lymphocyte Ratio), and RDW-CV (Red Blood Cell Distribution Width - Coefficient of Variation)—in 117 glioblastoma patients. Data collected from January 2016 to December 2018 included demographics, clinical scores, and treatment regimens. Unlike previous research, which often examined these markers solely before surgery, our unique approach analyzed them at multiple stages: preoperative, postoperative, and before adjuvant therapies. We correlated these markers with overall survival (OS) and progression-free survival (PFS) using statistical tools, including ANOVA, Cox regression, and Kaplan-Meier survival analyses, employing SPSS version 29.0. Our findings revealed notable variations in NLR, PLR, and RDW-CV across different treatment stages. NLR and PLR decreased after surgery, with some stabilization post-STUPP phase (NLR: p=0.007, η2p=0.06; PLR: p=0.001, η2p=0.23), while RDW-CV increased post-surgery and during subsequent treatments (RDW-CV: p &lt; 0.001, η2p=0.67). Importantly, we observed significant differences between the preoperative phase and other treatment phases. Additionally, higher NLR and RDW-CV at the second-line treatment and disease progression were associated with an increased risk of death (NLR at 2nd line: HR=1.03, p=0.029; RDW-CV at progression: HR=1.14, p=0.004). We proposed specific marker cutoffs that demonstrated significant associations with survival outcomes when applied to Kaplan-Meier survival curves (NLR at 2nd line &lt; 5: p&lt;0.017; RDW-CV at progression &lt; 15: p=0.007). Elevated NLR and RDW-CV at later treatment stages correlated with poorer OS and PFS. No significant preoperative differences were detected. These biomarkers may serve as non-invasive tools for glioblastoma management.

Commercial classification is essential to spatially describe commerce. Although most of the proposed classifications have been classic functional analyses, rooted on qualitative studies, some recent classifications efforts are found to rely heavily on more quantitative methods, due eventually to increasing data availability and technological advancements. In this paper, a classification is proposed, using k-means clustering and a minimal set of variables (density, diversity and clustering) to derive the commercial structure of Lisbon. The classification is implemented for 1995, 2002 and 2010, using a 150m-sided square grid. The cross-sectional analysis of the results shows the rise of shopping-malls against city centre decline and gentrification, along with changes in cluster composition considering 9 different commercial categories (6 categories of retail, and restaurants, cafes and bars). These findings are in line with literature, thus supporting the obtained classification. Since the classification can be used to accurately describe the commercial structure of the city in different time periods, it is implied that it may also be generalized to different cities. Furthermore, the potential use of cluster membership in retail location models, which is an advantage of the proposed classification, could help strengthen the relationship between location modelling and commercial classification, thus reinforcing the role of commercial studies in urban planning and policymaking.

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) challenges include understanding what triggered SARS-CoV-2 emergence, how this RNA virus is evolving or how the genomic variability may impact the primary structure of proteins that are targets for vaccine. We analyzed 19471 SARS-CoV-2 genomes and 199,984 spike glycoprotein sequences available at the GISAID database from all over the world and 3335 genomes of other Coronoviridae family members available at Genbank, collecting SARS-CoV-2 high-quality genomes and distinct Coronoviridae family genomes. Here, we identify a SARS-CoV-2 emerging cluster containing 13 closely related genomes isolated from bat and pangolin that showed evidence of recombination, which may have contributed to the emergence of SARS-CoV-2. The analyzed SARS-CoV-2 genomes presented 9632 single nucleotide polymorphisms (SNPs) corresponding to a variant density of 0.3 over the genome, and a clear geographic distribution. SNPs are unevenly distributed throughout the genome and hotspots for mutations were found for the spike gene and ORF 1ab. We describe a set of predicted spike protein epitopes whose variability is negligible. All predicted epitopes for the structural E, M and N proteins are highly conserved. This result favors the continuous efficacy of the available vaccines.

Secondary forests (SF) are important carbon sinks, removing CO₂ from the atmosphere through the photosynthesis process and storing photosynthates in their aboveground live biomass (AGB). This process occurring at large-scales partially counteracts C emissions from land-use change, playing, hence, an important role in the global carbon cycle. The absorption rates of carbon in these forests depend on forest physiology, controlled by environmental and climatic conditions as well as on the past land use, which is rarely considered for retrieving AGB from remotely sensed data. In this context, the main goal of this study is to evaluate the potential of full polarimetric ALOS-2 PALSAR-2 data for estimating AGB by taking into account the past-land use of SF areas in the Brazilian Amazon. We surveyed a chronosequence of 42 SF plots (20 ha) near the Tapajós National Forest in Pará state to quantifying AGB growth rates. We explored the full polarimetric data testing three regression models including non-linear (NL), multiple linear regressions models (MLR), and the semi-empirical extended water cloud model (EWCM). The results showed that the intensity of previous use has affected the structure of SF by reducing the AGB accumulation and being noticeable by several polarimetric attributes. The combination of multiple prediction variables with MLR improved the AGB estimation by 70% comparing amongst other models (R² adj. = 0.51; RMSE = 13.2 Mg ha^-1) bias = 2.1 ± 37.9 Mg ha^-1. The error propagation of the MLR model was estimated to be 15%.

In this paper mathematical analysis of the HIV/AIDS deterministic model exposed in [Espitia, C. et. al. Mathematical Model of HIV/AIDS Considering Sexual Preferences Under Antiretroviral Therapy, a Case Study in San Juan de Pasto, Colombia, Journal of Computational Biology 29 (2022) 483–493] is made. The objective is to gain insight into the qualitative dynamics of the model determining the conditions for the persistence or effective control of the disease in the community through the study of basic properties such as positiveness and boundedness, calculus of basic reproduction number, stationary points such as disease free equilibrium (DFE), boundary equilibrium (BE) and endemic equilibrium (EE) are calculated, local stability (LAS) of disease free equilibrium. It research allow to conclude that the best way to reduce contagion and consequently to reach a DFE is thought to be the reduction of homosexual partners rate as they are the most affected population by the virus, and are therefore the most likely to become infected and to spread the infection. Increasing the departure rate of infected individuals, leads to a decrease in untreated infected heterosexual men and untreated infected women.

This study conducted an extensive analysis of campylobacteriosis surveillance in Portugal from 2009 to 2021, aiming to investigate demographic shifts, seasonal variations, and antimicrobial resistance (AMR) within Campylobacter isolates. Surveillance network and sentinel laboratory-based system data revealed a substantial under-notification of campylobacteriosis cases, suggesting an underestimated disease burden. A paradigm shift was observed in notification rates, with a notable prevalence among the pediatric population, particularly in children aged 1-4 years, diverging from European reports. However, the study also highlighted an emerging trend of Campylobacter infections in younger adults (15-44 years). The study unveiled a unique seasonal distribution of cases, defying typical summer peaks seen elsewhere. AMR analysis revealed extremely to very high-level resistance to ciprofloxacin and tetracycline, both in C. jejuni (93.7% and 79.2%, respectively) and in C. coli (96.5% and 93.2%, respectively), stable throughout the studied period (2013-2021). C. coli also exhibited significantly higher resistance to erythromycin, gentamicin, ampicillin, amoxicillin-clavulanic acid (decreased resistance), and ertapenem compared to C. jejuni (P&lt;0.001). In conclusion, the study highlights the need for enhanced surveillance efforts and emphasizes worrying AMR levels. The implementation of WGS-based surveillance is recommended to attain a more profound comprehension of disease patterns and the evolving landscape of AMR.

Mycobacterium tuberculosis (Mtb) the causative agent of human tuberculosis (TB) is one of the most successfully adapted-human pathogens. Human-to-human transmission occurs at high rates through aerosols containing bacteria, but the pathogen evolved prior to the establishment of crowded populations. Mtb has developed a particular strategy to ensure persistence in the host until an opportunity for transmission arise. It has refined its lifestyle to obviate the need for virulence factors such as capsules, flagella, pilli, or toxins to circumvent mucosal barriers. Instead, the pathogen uses host macrophages, where it establishes intracellular niches, for its migration into the lung parenchyma and other tissues and for the induction of long-lived latency in granulomas. Finally, at the end of the infection cycle Mtb induces necrotic cell death of macrophages to escape to extracellular milieu and instructs a strong inflammatory response required for progression from latency to disease and transmission. Common to all these events is ESAT-6, one of the major virulence factors secreted by the pathogen. This review highlights the recent advances in understanding the role of ESAT-6 in hijacking macrophage function to establish a successful infection and transmission and its use as a target for the development of diagnostic tools, and vaccines.

Minimally processed fruits undergo changes that need to be controlled. The objective was to evaluate minimally processed papayas, using edible coatings based on chitosan and gelatin through different techniques. The following treatments were applied: control (distilled water), 1% chitosan, 4% gelatin, 1% chitosan + 4% gelatin (blend) and 1% chitosan under 4% gelatin (layer by layer). The infrared spectroscopy (FTIR) of the coatings was analyzed, and fresh mass, firmness, pulp color (L*, a*, b* and Hue angle), pH, titratable acidity, soluble solids, ascorbic acid, phenolic compounds, lycopene, β-carotene, total sugars and catalase from fruits. Gelatin and the layer-by-layer treatment had a positive effect on the conservation of minimally processed papaya. These coatings were able to reduce the loss of fresh mass, maintaining the firmness and orange color of the mesocarp. The treatments showed low SS content during the storage period, few variations in acidity, influencing maturation. Gelatin had a low polyphenol content, the layer-by-layer treatment did not show changes in vitamin C levels. These treatments did not show changes in lycopene and β-carotene levels over the days, showing a small increase in total sugars. Thus, the use of gelatin polymers and undercoat treatment (LBL) is a viable alternative to preserve minimally processed papayas for at least 8 days.

The present article discusses the institutional model adopted in Brazil regarding energy production through biomass. The theoretical-empirical method is used to conclude that the model's difficulties can be overcome by adopting a network of contracts capable of subjecting renewable energy generation to an energy compensation model.

In recent times, there has been a revolutionary surge in antioxidant research, with a focus on harnessing microalgae to enhance wellness and extend human longevity. Microalgae, a diverse group of unicellular photosynthetic organisms, have emerged as promising sources of natural antioxidants due to their ability to synthesize various bioactive compounds, including carotenoids, polyphenols, and tocopherols. These antioxidants play a pivotal role in scavenging free radicals and reducing oxidative stress, known contributors to aging and chronic diseases. This review provides an overview of recent advancements in understanding microalgae's antioxidant potential, covering their biochemical composition, extraction techniques, and purification methods. Moreover, it delves into compelling in vitro and in vivo studies showcasing microalgae-derived antioxidants' protective effects against oxidative damage, inflammation, cardiovascular diseases, and neurodegenerative disorders. The sustainable cultivation of microalgae in controlled environments further supports the potential for large-scale production and commercialization of their antioxidant compounds. As microalgae continue to revolutionize antioxidant research, they hold immense promise in developing novel preventive and therapeutic strategies to promote human health and wellbeing.

Rocky Mountain or Brazilian spotted fever, caused by Ricketsia ricketssi, is a fulminant, seasonal, and neglected disease that occurs in focal points of North America and South America. Rapid detection are essential for a better prognosis and survival rate of the infected individual. However, disease diagnosis still faces challenges as the accuracy of many of the available laboratory tests fluctuates. Therefore, this review aimed to identify methods for antibody or antigen detection, its gaps, and evolution over time. A search was conducted to find all studies in the Pubmed database that described antibody or antigen detection for Ricketsia ricketsii infection. Initially, a total of 403 articles were screened. Of these articles, only 19 fulfilled the pre-established inclusion criteria and were selected. Among the different methods applied, the IFA technique was the one most frequently found in the studies. However, it presented varied results such as low specificity using the indirect method. Other techniques, such as ELISA and immunohistochemistry, were also found, although in smaller numbers and with their own limitations. Although some studies showed promising results, there is a pressing need to find new techniques to develop a rapid and effective Ricketsia ricketssi infection diagnosis.

The urban mangrove of the Vitória Bay, Espírito Santo, Southern Brazil suffers from anthropogenic impacts, which interfere in the foliar spectral response of its species. Identifying the spectral behavior of these species and creating regression models to indirectly obtain structure data like the Leaf Area Index (LAI) are powerful environmental monitoring tools. In this study, LAI was obtained in 32 plots distributed in four stations. In situ LAI regression analysis with the SAVI resulted in significant positive relationships (r² = 0.58). Forest variability regarding the degree of maturity and structural heterogeneity and LAI influenced the adjustment of vegetation indices (VIs). The highest regression values were obtained for the homogeneous field data, represented by R. mangle plots, which also had higher LAI values. The same field data were correlated with SAVI of a RapidEye image for comparison purposes. The results showed that, images obtained by a UAV have higher spatial resolution than the Rapideye image, and therefore had a greater influence of the background. Another point is that the statistical analysis of the field data with the IVs obtained from the RapidEye image did not present high regression coefficient (r² = 0.7), suggesting that the use of VIs applied to the study of urban mangroves needs to be better evaluated, observing the factors that influence the leaf spectral response.

This paper presents a review on numerical and experimental methods to predict fracture of ad-vanced high strength steels (AHSS). AHSS are widely processed through sheet metal forming processes. Although being an excellent choice when lightweight, high strength and ductility are critical factors, their multi-phase microstructure accentuates forming challenges. To accurately model forming behavior, necking based failure criteria as well as direct fracture models require improvements. As a necking based failure model, the conventional forming limit diagram/curve (FLD/FLC) presents limitations such as in estimating direct fracture (surface cracks, edge cracks, shear cracks), as well as deformation histories under nonlinear strain paths. Thus, significant re-search efforts are being made towards the needs of advanced fracture constitutive models capa-ble of predicting fracture scenarios without necking, more frequently observed in the realm of AHSS. Scientific community research is divided into several directions aiming at improving the forming and fracture behavior accuracy of parts subjected to sheet metal forming operations. In this review paper, a comprehensive overview on ductile fracture modeling is presented. Firstly, the FLD/FLC limitations modeling fracture behavior in sheet metal forming operations are stud-ied. Followed by the recent trends in constitutive material modeling. Afterwards, material char-acterization methods advancements to cover a broad range of stress states are comprised. Final-ly, damage and fracture models predicting failure in AHSS are investigated. This review paper supplies relevant information on the current issues the sheet metal forming community is chal-lenged with due to the trend towards AHSS employment in the automotive industry.

Background: We aimed to assess the association between DII and PD and the mediation effect of DII in the association of PD with systemic inflammation. Using the National Health and Nutrition Examination Survey (NHANES) 2009-2010, 2011-2012 and 2013-2014, participants that received periodontal exam and provided dietary recall data were included. The inflammatory potential of diet was calculated via DII. Periodontitis was defined according to the 2012 case definition. The clinical outcomes of interest were mean periodontal probing (PPD), mean clinical attachment loss (CAL) and thresholds of PPD and CAL. White blood cells (WBC), segmented neutrophils and C-reactive protein (CRP) were used as proxies for systemic inflammation. The periodontal measures were regressed across DII values using adjusted multivariate linear regression. Adjusted mediation analysis appraised the influence of DII in the association of periodontitis and systemic inflammation. 10,178 participants were included. DII was significantly correlated with mean PPD, mean CAL, thresholds of PPD and CAL, WBC, segmented neutrophils and DII (p&lt;0.01). A linear regression logistic adjusted for multiple confounding variables confirmed the association between DII and mean PPD (B = 0.02, Standard Error [SE]: 0.02, p&lt;0.001) and CAL (B = -0.02, SE: 0.01, p&lt;0.001). The association of mean PPD and mean CAL with both white blood cells and segmented neutrophils were mediated by DII (from 2.1 to 3.5%, p&lt;0.001). In the 2009-2010 subset, the association of mean CAL with serum CRP was mediated by DII (52.0%, p&lt;0.01). In conclusion, inflammatory diet and PD may be associated. Also, the inflammatory diet significantly mediated the association of leukocyte counts and systemic inflammation with periodontitis.

In this paper, we introduce the application of Type-I fuzzy inference systems (FIS) as an alternative to improve the prioritization in the FMECA analysis applied in cyber-power grids. Classical FMECA assesses the risk level through the Risk Priority Number (RPN). The multiplication between three integer numbers computes this, called risk factors, representing the severity, occurrence, and detectability of each failure mode and are defined by a team of experts. The RPN does not consider any relative importance between the risk factors and may not necessarily represent the real risk perception of the FMECA team members, usually expressed by natural language; this is the main FMECA shortcoming criticized in the literature. Our approach considers fuzzy variables defined by FMECA experts to represent the uncertainty associated with the human language and a rule base consisting of 125 fuzzy rules to represent the risk perception of the experts. To test our approach, we select a cyber-power grid previously analyzed by the authors using the classical FMECA. The results reveal our proposed fuzzy approach as promissory to represent the uncertainty associated with expert knowledge and to perform an accurate prioritization of failure modes in the context of electrical power systems.

Microbial pigments have many structures and functions with excellent characteristics, such as being biodegradable, non-toxic, and ecologically friendly, constituting an important source of pigments. Industrial production presents a bottleneck in production cost that restricts large-scale commercialization. However, microbial pigments are progressively gaining popularity because of their health advantages. The development of metabolic engineering and cost reduction of the bioprocess using industry by-products opened possibilities for cost and quality improvements in all production phases. We are thus addressing several points related to microbial pigments, including the major classes and structures found, the advantages of use, the biotechnological applications in different industrial sectors, their characteristics, and their impacts on the environment and society.

Deep learning is emerging in many industrial sectors in hand with big data analytics to streamline production. In the biomanufacturing sector, big data infrastructure is lagging comparatively to other industries. A promising approach is to combine Deep Neural Networks (DNN) with prior knowledge in Hybrid Neural Network (HNN) workflows that are less dependent on the quality and quantity of data. This paper reviews published articles over the past 30 years on the topic of HNN applications to bioprocesses. It revealed that HNNs were applied to various bioprocesses, including microbial cultures, animal cells cultures, mixed microbial cultures, and enzyme biocatalysis. HNNs were mainly applied for process analysis, process monitoring, development of software sensors, open- and closed-loop control, batch-to-batch control, model predictive control, intensified design of experiments, quality-by-design, and recently for the development of digital twins. Most previous HNN studies combined shallow Feedforward Neural Networks (FFNNs) with physical laws, such as macroscopic material balance equations, following the semiparametric design principle. Only recently, deep HNNs based on deep FFNNs, Convolution Neural Networks (CNN), Long Short-Term Memory (LSTM) networks and Physics Informed Neural Networks (PINNs) have been reported. The biopharma sector is currently a major driver but applications to biologics quality attributes, new modalities, and downstream processing are significant research gaps.

The number of people with gluten-related illnesses has been increasing and the available treatments include the introduction of a gluten-free diet. In the bakery industry, there are problems with gluten-free products, namely the important characteristics that this component gives to doughs and the low nutritional value they present. A disease that has also increased in recent years is diabetes mellitus, which is characterized by a lack of insulin and the effectiveness of its action (type 1 diabetes) or tissue insensitivity to the hormone (type 2 diabetes). In terms of treatments, there are several approaches: inhibition of digestive enzymes (α-amylase and α-glucosidase) or techniques based on mechanisms of action (stimulation of insulin production and release, insulin transport and decreased glucose absorption). Hyperglycemia is also associated with the production of reactive oxygen species, which leads to cell apoptosis. On the other hand, there was also an association with high levels of cholesterol in the body, which contributed to the development of other types of diseases. In this sense, macroalgae have been studied as a source of natural compounds and used as food supplements, due to their protein, amino acid and mineral content, and the anti-diabetic effect in controlling the glycemic index, oxidative stress and cholesterol have already been demonstrated. Seaweed emerges as a promising source of bioactive nutraceuticals for individuals with coeliac disease, diabetes, and hyperglycemia. The rising prevalence of gluten-related illnesses calls for effective treatments, and seaweed's potential in enhancing the nutritional value of gluten-free products is noteworthy. Additionally, its demonstrated anti-diabetic effects, including glycemic index control, oxidative stress reduction, and cholesterol management, make it a valuable dietary supplement. Further research is needed to explore the specific bioactivities of seaweed compounds and their mechanisms of action. Integrating seaweed-based nutraceuticals into diets could complement traditional treatments, offering potential health benefits to those with coeliac disease and diabetes.

The aim of the present study was to investigate whether chronic undernutrition modifies the response to rostafuroxin in juvenile rats. Chronic undernutrition was induced in male rats using a multideficient diet known as Regional Basic Diet (RBD), mimicking alimentary habits in impoverished regions worldwide. Animals were given RBD – or a control/CTRL normal diet for rodents – from weaning to 90 days, and rostafuroxin (1 mg/kg body mass) or vehicle were orally administered during the last 30 days. Undernourished rats became hypertensive at 55–60 days of age (tail-cuff recording). During the last two days, the rats were hosted in metabolic cages to measure food/energy, water, Na+ ingestion, and urinary volume. Blood and kidneys were collected after euthanasia. Rostafuroxin increased food/energy and Na+ intake in CTRL and RBD rats but had opposite effects on Na+ balance (intake minus urinary excretion): negative in CTRL and positive in RBD. The drug normalized the decreased plasma Na+ concentration found in RBD rats, increased urinary volume in RBD but not in CTRL, and decreased and increased urinary Na+ concentration in the RBD and CTRL groups, respectively. Rostafuroxin decreased the ouabain-sensitive (Na++K+)ATPase and increased the ouabain-resistant, furosemide-sensitive Na+-ATPase from proximal tubule cells in both groups, and normalized the systolic blood pressure in RBD without effect in CTRL rats. We conclude that chronic undernutrition modifies the response of blood pressure, caloric metabolism, Na+ distribution in liquid compartments, mobilization of Na+ from non-osmotic compartments, Na+ and water balance, and activity of renal Na+-transporting ATPases to rostafuroxin.

Stress is an inherent sensation of being unable to handle demands and occurrences. If not properly managed, stress can develop into a chronic condition, leading to the onset of additional chronic health issues like cardiovascular illnesses and diabetes. Various stress meters have been suggested in the past, along with diverse approaches for its estimate. However, in the case of more serious health issues such as hypertension and diabetes, the results can be significantly improved. This study presents the design and implementation of a distributed wearable sensor computing platform with multiple channels. The platform aims to estimate stress levels in diabetes patients by utilizing a fuzzy logic algorithm that is based on the assessment of several physiological indicators. Additionally, a mobile application was created to monitor users' stress levels and integrate data on their blood pressure and blood glucose levels. Validation experiments were performed on patients with chronic diabetes, and the initial findings are presented in the study.

Accurate streamflow forecasting is crucial for effectively managing water resources, particularly in countries like Colombia, where hydroelectric power generation significantly contributes to the national energy grid. Although highly interpretable, traditional deterministic, physically-driven models often suffer from complexity and require extensive parameterization. Data-driven models like Linear Autoregressive (LAR) and Long Short-Term Memory (LSTM) networks offer simplicity and performance but cannot quantify uncertainty. This work introduces Sparse Variational Gaussian Processes (SVGPs) for forecasting streamflow contributions. The proposed SVGP model reduces computational complexity compared to traditional Gaussian Processes, making it highly scalable for large datasets. The methodology employs optimal hyperparameters and shared inducing points to capture short-term and long-term relationships among reservoirs. Training, validation, and analysis of the proposed approach consider the streamflow dataset from 23 geographically dispersed reservoirs recorded during twelve years in Colombia. Performance assessment reveals that the proposal outperforms baseline Linear Autoregressive (LAR) and Long Short-Term Memory (LSTM) models in three key aspects: adaptability to changing dynamics, provision of informative confidence intervals through Bayesian inference, and enhanced forecasting accuracy. Therefore, the SVGP-based forecasting methodology offers a scalable and interpretable solution for multi-output streamflow forecasting, thereby contributing to more effective water resource management and hydroelectric planning.

In the present study, a numerical model was developed to predict the flow pattern inside a broiler building. The model intends to predict the velocities fields inside the domain and ammonia (NH3) emitted or released by litter from poultry housing. The numerical model developed in Computational Fluid Dynamics (CFD) commercial code, intends to represent a commercial broiler building, and intends to simulate the 3D and heat transfer, in steady state flow. The evaporative cooling pads were also included in the model. The validation of the model was based in experimental measurements obtained in previous studies. The simulations were focused on Summer, Winter and also Mid-Season situation. The numerical results of NH3 concentration were compared with the experimental measurements, and a quite good agreement was verified. The numerical results allowed the characterization of: the inside flow pattern developed for the summer and winter situation; the inside NH3 distribution, and the velocity field distribution inside the broiler building. It was found that NH3 concentration increases along the tunnel, especially in low flow rate imposed from the exhaust fan. Also, it was verified that the low velocities inside domain are no sufficient to remove the gaseous pollutants.

Background: Despite advances in diagnosis and treatment, the incidence and mortality of infective endocarditis (IE) have increased in recent decades despite advances in diagnosis and treatment. Studies on the risk factors for mortality in endocarditis in Latin America are scarce. Methods: This retrospective cohort study included 240 patients diagnosed with IE according to the modified Duke criteria who were admitted to two university hospitals in Rio de Janeiro, Brazil from January 2009 to June 2021. Poisson regression analysis was performed for trend tests. The multivariate Cox proportional hazards model was used to estimate the hazard ratio (HR) of predictors of in-hospital mortality. Findings: The median age was 55 years (IQR: 39-66 years), 57% were male, and 41% had a Charlson comorbidity index (CCI) score &gt; 3. Healthcare-associated infective endocarditis (54%), left-sided native valve IE (77.5%), and staphylococcal IE (26%) predominated. Overall in-hospital mortality was 45.8%, and mortality was significantly higher in the following patients: aged ≥ 60 years (53%), CCI score ≥ 3 (60%), healthcare-associated infective endocarditis (HAIE) (53%), left-sided IE (51%), and enterococcal IE (67%). Poisson regression analysis showed no trend in in-hospital mortality per year. The adjusted multivariate model determined that age ≥ 60 years was an independent risk factor for in-hospital mortality (HR = 1.9; 95% CI 1.2-3.1; p = 0.008). Interpretation: In this 12-year retrospective cohort, there was no evidence of an improvement in survival in patients with IE. Since older age is a risk factor for mortality, consensus is needed for the management of IE in this group of patients.

In cardiac surgery, post-sternotomy pain is a significant issue, peaking within 48 hours and requiring proper analgesia for both acute relief and to avoid chronicization. Opioids are commonly used for pain management post-surgery but pose risks like adverse effects and dependency. Post-cardiac surgery pain can stem from various sources - somatic, visceral, and neuropathic, making opioid reliance a concern. Multimodal analgesia, combining different medications and regional anesthesia techniques, is increasingly recommended to decrease opioid use and its related problems. Strategies include acetaminophen, gabapentinoids, NMDA antagonists, alpha-2 agonists, intravenous lidocaine, anti-inflammatory drugs, and regional anesthesia. Implementing these approaches can enhance pain control, lessen opioid reliance, and improve cardiac surgery outcomes. The ERAS® Cardiac Society strongly advocates for an opioid-sparing multimodal approach to benefit patient recovery by reducing complications and enhancing satisfaction. This review aims to consolidate current evidence to assist healthcare providers in customizing pain management for patients post-cardiac surgery, emphasizing reduced opioid use and optimizing the recovery process.

Seaweeds have been the target of much attention due to the known bioactivities of some of their compounds. Although many studies about the application of seaweeds in various areas are available, these data are mostly about the raw extracts and not about specific compounds, such as seaweeds pigments. Moreover, the fungal infections of the skin, nails and hair caused by dermatophytes, are the most common fungal infections in humans. These pathologies require long periods of topical and/or systemic treatment that are associated with adverse effects and contraindications. This study had two objectives, the first was to evaluate the possibility of isolating and characterizing the pigments of Calliblepharis jubata and Fucus vesiculosus; the second was to assess their antifungal activity. The extraction of pigments was performed using a method of extraction by exhaustion; the purification was carried out by column chromatography. Three techniques were used to characterize the pigments, thin layer chromatography (TLC), UV-visible spectrophotometry and Fourier-transform infrared spectroscopy (FTIR). The antifungal activity was evaluated using the micro-dilution method, following the EUCAST international standards, on three dermatophytes, Trichophyton rubrum, Trichophyton mentagrophytes and Microsporum canis. It was possible to observe that the extract obtained from the seaweed C. jubata and F. vesiculosus, corresponding to the purified pigment phycobiliprotein, and the crude extract, an enriched extract, obtained from the seaweed C. jubata showed antifungal activity against the three fungal agents of human skin infection.

Cemeteries can be compared to landfills since their leachate, also known as necroleachate, can be transported and pollute groundwater, surface waters, and soils. In Brazil, the cemeteries management is the responsibility of states and municipalities, to ensure that they do not generate negative environmental impacts and risks to public health. This article aims to discuss Brazilian sanitary-environmental legislation relating to cemetery waste management. Among the Brazilian states, half have sanitary-environmental legislation for cemeteries, and between the municipalities, only 19 have specific legislation. The legislation is broad and has many gaps, leading to environmental vulnerability and risk of contamination for the people who live in the surrounding area.

Seaweed polysaccharides can substitute synthetic compounds present in commercial stimulants and fertilizers, used in agriculture to improve crops yield and vigor. In this study, three different poly-saccharides (alginate, agar and carrageenan) were extracted from one brown seaweed, Saccorhiza polyschides, and two red seaweeds, Gracilaria gracilis and Chondrus crispus, respectively, and applied on potted turnip greens (Brassica napus L.), with intention to analyze their impact on plant growth, development and metabolism. Turnip plants treated with polysaccharides, specially, carrageenan of Chondrus crispus showed the best results in improving the crop’s productivity, such as plant length and weight, number of leaves, nutrient and pigment content, and soil fertility, compared with turnip plants from the negative control or treated with a commercial leaf fertilizer. λ-carrageenan extracted from the tetrasporophyte generation of Chondrus crispus had the highest bioactivity and positive effect in turnip plants among all treatments. λ-carrageenan has shown that can improve plant growth, increase plant’s biomass, and root system, enhance photosynthetic activity, increase the uptake of soil nutrients, and protect plants against abiotic and biotic stresses, stimulating the production of secondary metabolites and manage its defense pathways. Seaweed extracted polysaccharides have the potential to be used in sustainable agriculture.

In the present paper four passive micromixers designs (G1, G2, G3 and G4) inspired on distillation columns trays were proposed. The devices performance was assessed by numerical simulations. The mixing performance was investigated for a Reynolds number range from 0.01 to 100 and channel height of 200 µm, 500 µm and 1000 µm for oil/ethanol flow. G1 and G4 designs provided high mixing index (> 0.975). The G1 device achieved superior mixing performance with a moderate pressure drop (about 0.5 MPa) due to the induced flow recirculation pattern for a relative high flow rate of 0.21 L/min, highlighting the potential use of such microdevice for scale-up and numbering-up of microdevices in modular chemical plant processing.

Using pumps operating as turbines (PATs) offers the possibility of increasing the sustainability of water and energy systems by recovering the excess of energy that would be otherwise lost in pressure reducing valves or head loss chambers. In on-grid applications, there are many research works and implementations of PATs. However, there is still limited research for the optimization of efficiency and stability of PATs operating in off-grid systems. This work contributes to the development of stable direct current (DC) off-grid electric systems based on PATs, by optimizing and analysing the energy efficiency and stability for a wide range of operation. A self-excited induction generator (SEIG) coupled to the PAT is provided to cover the conventional type of electric ma-chines typically coupled to the hydraulic pumps. In this context, a methodology is proposed, based on the hydraulic, mechanical and electric subsystems, to define the PAT-SEIG operational area, to maximize energy conversion and the system efficiency. This will guarantee stable electric output quantities when operating in a DC off-grid system. In addition, an analytical model is proposed to estimate the PAT-SEIG operation under specific conditions. With this, water managers are suitable to design and optimize an off-grid PAT-SEIG system and to define the best hydraulic machines, electronic equipment, and all different control elements to maximize energy conversion within the target of operational limits. To develop and verify this new methodology, two micro PAT-SEIG setups were implemented in the hydraulic laboratory of IST/CERIS under typical operating conditions. The proposed solution proved to be resilient under a variable load regime. The system's maximum efficiency can be adapted using different capacitor values for the excitation of the SEIG, and the operational range is limited to the electric components. Considering the nominal efficiencies of the system’s components, the maximum p.u. efficiency obtained for each PAT-SEIG system were between 0.7 and 0.8 p.u.

With the increase in life expectancy and consequent aging of the world’s population, the prevalence of many neurodegenerative diseases is increasing, without concomitant improvement in diagnostics and therapeutics. These diseases share neuropathological hallmarks, including mitochondrial dysfunction. In fact, as mitochondrial alterations appear prior to neuronal cell death at an early phase of the disease onset, the study and modulation of mitochondrial alterations rise as promising strategies to predict and prevent neurotoxicity and neuronal cell death before the onset of cell viability alterations. In this work, differentiated SH-SY5Y cells were treated with the mitochondrial-targeted neurotoxicants 6-hydroxydopamine and rotenone. These compounds were used at different concentrations and for different time points to understand the similarities and differences in their mechanisms of action. To accomplishing this, data on mitochondrial parameters was acquired and analyzed using unsupervised (hierarchical clustering) and supervised (decision tree) machine learning methods. Both biochemical and computational analyses resulted in an evident distinction between the neurotoxic effects of 6-hydroxydopamine and rotenone, specifically for the highest concentrations of both compounds.

In this paper we propose a computational framework that merges mechanistic modeling with deep neural networks obeying the Systems Biology Markup Language (SBML) standard. Over the last 20 years, the systems biology community has developed a large number of mechanistic models in SBML that are currently stored in public databases. With the proposed framework, existing SBML mechanistic models may be upgraded to hybrid systems through the incorporation of deep neural networks into the model core, using a freely available python tool. The so-formed hybrid mechanistic/neural network models are trained with a deep learning algorithm based on the adaptive moment estimation method (ADAM), stochastic regularization and semidirect sensitivity equations. The trained hybrid models are encoded in SBML and stored back in model databases, where they can be further analyzed as regular SBML models. The application of this approach is illustrated with three well-known case studies: the threonine synthesis model in Escherichia coli, the P58IPK signal transduction model, and the Yeast glycolytic oscillations model. The proposed framework is expected to greatly facilitate the widespread use of hybrid modeling techniques for systems biology applications.

“De-[Constructing] Growth” is offered as a deeper and more useful conceptualization that avoids the negative connotations of, and resistance to, “degrowth” by decoupling profit from unsustainable consumption, production, and inequality.

Nowadays, inquiries are one of the most important tasks to be executed in order to get valued information. When an inquiry is done to gather information about a human behavior there are some problems inherent to it. One of the main problems is how the information about many different persons can be processed to give good information about their environment. Most of the information gathered by these inquiries is used to analyze the behavior of the respondents. It can be used to estimate the success of a certain product on the market or just to validate the satisfaction of current costumers. The veracity of this information can be critical to model environments with some acceptable level of precision. Modelling environments through Artificial Neural Networks (ANN) is highly common because ANN’s are excellent to model predictable environments using a set of data. ANN’s are good in deal with sets of data with some noise, but they are fundamentally surjective mathematical functions and they aren’t able to give different results for the same input. So if an ANN is trained using data where the same input has different images which can be the case of survey data, this can be a problem for the success of modelling the environment. Therefore is necessary to process the data in order to adjust and eliminate invalid data.

Nowadays the dynamism induced by the constant change of strategic decisions on the markets produces an extra difficulty in the management of an organization. The strategic decisions made by managers can become obsolete in a short period of time. One of the major difficulties in managing a commercial organization is to predict, with some precision degree, the impact some strategic decisions have on the financial results. Business Intelligence (BI) is an area widely used to help managers to make strategic decisions. But the methods used, behind the scenes, to achieve the conclusions are kept secret by BI company-based services. Modelling the environment can be a good option to study the impact of an action, provided by a strategic decision, in a real environment. A good model should give an approximate result of an action applied to a previous state of the environment. Artificial Neural Networks (ANNs) are proven to be excellent in modeling environments with some level of data noise. The same strategic action can have different results in different organizations. A tool that allows an evaluation of a strategic action applied to an environment should have a major importance in the management scope. Modeling the environment should save time and money for the organization to improve the performance of the strategic plan. If one evaluates the state of the environment after a strategic action being applied, it can be possible to mitigate the risk of failure of the strategic plan. As we will be able to verify, it is possible to use ANNs to model strategic environments that should allow the prediction of sales and operating results by the used strategies with some precision, although the level of success will be directly related with the user’s necessity.

Background: Despite the existence of a wide variety of anti-inflammatory drugs, the vast majority are classified as steroidal or non-steroidal. Both classes with many side effects that limit usage. Thus, the search for new molecules with anti-inflammatory potential is still important. Methods: Five phenylbenzohydrazides were synthetized and evaluated in pre-clinical models of acute inflammation in vivo and in vitro. Results: Substances significantly reduced cell migration induced by carrageenan. It was also observed an intense inhibition in protein extravasation and cytokines (IL-6, IL-1β, and TNF-α) production as well as nitric oxide reduction. INL-11 demonstrated to be the most potent since the reduction was significant even when compared with dexamethasone. In vitro INLs also reduced cytokines and NO production and iNOS activity. INL-11 was the most effective in reducing cell migration in vitro. Conclusions: our data suggest that these substances are suitable for further development to new series of compounds that could lead to new hits and future drug prototypes for anti-inflammatory conditions.

This paper aims to analyze the effects of Covid-19 on financial markets from the perspective of Complexity. The Covid-19 pandemic has caused turmoil in financial markets and is already one of the most important financial crises in history, causing a fall in several stock markets as well as great volatility. Unlike past crises, which in most cases were caused either by problems of fiscal deficits or in the financial system, this crisis has its origin in an epidemic disease, which occurred in Wuhan, China, and quickly spread across the globe affecting transport networks, commerce and finance, and will affect the public debt of many countries. This is a systemic situation in which there is a need to consider several interconnected systems, financial instability and high financial risk, something that econophysics and some complexity theorists already do. Therefore, this paper intends to show, theoretically, the systemic and complex character of the recent financial crisis caused by Covid-19.

Optical backbone networks constitute the fundamental infrastructure employed today by network operators to deliver services to users. As network capacity is a key factor influencing optical network performance, it is important to understand how topological and physical properties impact its behavior and to have the capability to estimate its value. In this context, we propose here a method to evaluate the network capacity that relies on the optical reach to account for physical layer aspects, in conjunction with constrained routing techniques for traffic routing. As this type of routing can lead to traffic blocking, particularly due to the limitation on the number of wavelengths per fiber, we also propose a fiber assignment algorithm designed to deal with this problem. We apply this method to a set of randomly generated networks using a modified Waxman model, and for a network with 60 nodes, in a scenario without blocking, we obtain capacities of about 2.5 Pbit/s for a symbol rate of 64 Gbaud and about 5 Pbit/s for a symbol rate of 128 Gbaud. Remarkably, this duplication in the total network capacity is achieved by an increase in the total fiber length of only about 51%.

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

Trichomonas vaginalis is an extracellular parasite protozoan that causes human trichomoniasis, a sexually transmitted infection (STI) that affects approximately 200 million people worldwide. The presence of T. vaginalis adhesion to inert substrates has been described in several reports. Still, very few studies on cluster formation and more detailed analyses of the contact regions between the membranes of the parasites in these aggregate formations have not been carried out. We analyzed the formation of parasite monolayers and clusters using high-resolution scanning electron microscopy, transmission electron microscopy, cytochemistry, TEM tomography, and dye injection. Here, we show the formation of a monolayer of tightly adherent cells, epithelium-like, when the parasites are in contact with an inert material. Based on this observation, we analyzed whether this monolayer behaves as an epithelium, analyzing cell junctions, cell communication, and ultrastructural aspects. We also analyzed the cluster formation and the morphological characteristics of parasite aggregation observed in the culture supernatant. We report that monolayer formation differs from cluster formation in many aspects. The monolayers form strong adhesion, whereas the clusters have fragile attachments. There is no fusion or passage of molecules between neighbor-attached cells; there is no need for different strains to form filopodia, cytonemes, and extracellular vesicles during cluster formation.

The saltmarsh plant Halimione portulacoides was shortly exposed to realistic levels of inorganic mercury (iHg), aiming to investigate adaptative processes of the roots and leaves regarding re-dox homeostasis, physiology, and Hg accumulation. Plants were collected at a contaminated (CONT) and a reference (REF) site, addressing the interference of contamination background. The influence of major abiotic variables (i.e., temperature and light) was also examined. Total Hg lev-els, antioxidant enzymes, lipid peroxidation (LPO), and photosynthetic activity were analyzed after 2 and 4 hours of exposure. Accumulation of iHg in the roots was noticed poorly, and no translocation to stems and leaves was found, but plants from CONT seemed more prone to iHg uptake (in winter). Despite that, antioxidant modulation in roots and leaves was found, disclos-ing, in winter, higher thresholds for the induction of enzymatic antioxidants in CONT leaves compared to REF, denoting that the former are better prepared to cope with iHg redox pressure. Consistently, CONT leaves exposed to iHg had remarkably lower LPO levels. Exposure did not impair the photosynthetic activity, pinpointing H. portulacoides ability to cope with iHg toxicity under a very short-term exposure. Biochemical changes were noticed before enhancements in ac-cumulation, reinforcing the relevance of these responses in precociously signaling iHg toxicity.

Biological invasions represent a threat to ecosystems, through competition and habitat destruction, which may result in significant changes of the invaded community. Asparagopsis armata is a red macroalgae (Rodophyta) globally recognized as an invasive species. It is found from the intertidal to shallow subtidal areas, on rock or epiphytic, forming natural vegetation belts on exposed coasts. This study evaluated the variations on native intertidal seaweed and macroinvertebrate assemblages inhabiting rock pools with and without the presence of the invasive macroalgae A. armata. To achieve this, manipulation experiments on Atlantic (Portugal) rock pools were done. Three rock pools were maintained without A. armata by manual removal of macroalgae, and three others were not experimentally manipulated during the study period and A. armata was freely present. In this study the variations between different rock pools were assessed. Results showed different patterns in the macroalgae composition of assemblages but not for the macrobenthic communities. Ellisolandia elongata was the main algal species affected by the invasion of A. armata. Invaded pools tended to show less species richness, showing a more constant and conservative structure, with lower variation of its taxonomic composition than the pools not containing A. armata, where the variability between samples was always higher. Despite the importance of the achieved results, further data based on observation of long-term series are needed, in order to further understand more severe effects of the invader A. armata on native macroalgal assemblage.

The Interdisciplinary Method of Musical Literacy, Education and Artistic Awareness (MILMESA) is developed and applied essentially in higher education (artistic, cultural and teacher training courses), promoting effective endogenous (interarts) and exogenous interconnection (artistic and other non-artistic areas) of an inter and pluridisciplinary matrix, as well as assuming itself as a privileged vehicle of relationship and extension to the community in the frame of the making of artistic-cultural and pedagogical-didactic events in the European, Luso-Brazilian, Luso-African and Hispanic American territories. It was created, tested and evaluated in five consecutive quadrennia (2002–2023), being regularly adapted, adapted and added according to the observed realities, evolving into the deepening of new concepts and models of intervention in these domains (e.g., Expressive and Proximal Didactics). Using the Ethnographic Method and the Case Study, and having the source of data collection as Document Analysis of written and iconographic or visual sources (n = 1386) and Participant Observation, this study aimed to describe and analyse the application and evolution of MILMESA in terms of education and extension to the community. It was concluded that there was a need to promote, with greater regularity and scope, greater technological interaction via digital platforms and social networks, within the framework of the participation of external specialists (e-DEP) and the very experience of MILMESA’s experiences and initiatives, giving it a more meaningful and participatory range.

Tabebuia aurea (Silva Manso) Benth. & Hook. f. The ex S.Moore (yellow ipe), belonging to the Bignoniaceae family, used in the popular for fever, inflammation and healing of skin wounds. The extract was prepared by maceration, using 70% ethanol. Through HPLC analysis, it was possible to identify substances, mainly phenolic, such as lapachol, present in Bignoniaceae. The phenolic content was 21.36 mg / Eag in the antioxidant activity, the effective concentration of 50% was 53.03 ± 1.14 µg / mL. The antimicrobial activity against S.aureus, E. coli and C. albicans was evaluated by microdilution in broth, which verified action against the tested microorganisms. Cell viability has been inhibited for tumor cells, although this has not been observed for normal cells. The LD50 against A.aegypti mosquito larvae was 3504.6 mg / L and there was no mortality in the concentration tested for the snail B.glabrata. Nontoxic or low toxicity for A. salina and T. molitor, respectively, and did not exhibit hemolytic action at concentrations of antibacterial effect. Given the above, it was concluded that the bark extract of the studied species has bioprospecting potential for the future development of antimicrobial products.

Introduction: Bovine tuberculosis is a zoonotic disease of considerable impact, especially in livestock countries, which can cause human disease. Despite its importance, Colombia is a country in which few studies analyse its behaviour, and none develop maps using geographic information systems to characterise it. Objective: To describe the temporal-spatial distribution of bovine tuberculosis in Colombia between 2001 and 2019. Methods: Retrospective cross-sectional descriptive study, based on reports by the Colombian Agricultural Institute, of tuberculosis surveillance in cattle on farms in Colombia from 2001 to 2019. The data were converted into databases in Microsoft Access 365®, and multiple epidemiological maps were generated with the Kosmo RC1®3.0 software coupled to shape files of all the country's departments. Results: During the study period, 5,273 tuberculosis cases in bovines were identified in the different departments of Colombia (mean 278 cases/year). Regarding its temporal distribution, the number of cases varied from a maximum of 903 cases (17.12% of the total) in 2015 to a minimum of 0 between 2001 and 2004 and between 2017 and 2019 (between 2005 and 2016, the minimum was 46 cases, 0.87%). Conclusions: GIS is an essential tool for understanding the temporospatial behaviour of zoonotic diseases in Colombia, as is the case of bovine tuberculosis, with its potential implications for Human and One Health.

Unmanned vehicles (UVs) have become increasingly important in various scenarios of civil and military operations. The present work aims at the conceptual design of a modular Amphibious Unmanned Ground Vehicle (A-UGV), that can be easily adapted for different types of land and/or water missions, with low monetary cost (&lt;5k€, without sensors). Basing the design on the needs highlighted in the 2021 review of the Strategic Directive of the Portuguese Navy, the necessary specifications and requirements are established for two mission scenarios. Then a market research analysis focused on vehicles currently available, and their technological advances, is conducted to identify existing UVs solutions and respective characteristics/capabilities of interest to the current work. To study and define the geometry of the hull and the configuration of the A-UGV itself, preliminary computational structural and fluid analyses are carried out to ensure it complies with the specifications initially established. As a result, one obtains a fully electric vehicle, with approximate dimensions of 1050×670×450mm (length-width-height), enabled with 6×6 traction capable of reaching 20km/h in land, possesses amphibious capabilities of independent propulsion in water up to 8kts, and with an estimated autonomy of over 60 minutes.

Artisanal and Small-scale Gold Mining (ASGM) has caused several environmental impacts, resulting in significant siltation of water bodies due to the deposition of sediments on river banks. Based on this perspective, this study aims to investigate the water bodies and regions most impacted by mining activities, especially in relation to the increase in the Total Suspended Solids (TSS) caused by ASGM, focusing on the territories of Suriname and French Guiana, over the period from 2017 to 2023, through the creation of an algorithm in Google Earth Engine. The research also aims to map and describe active mining in this region using the Classification and Regression Tree (CART) method, which achieved an overall accuracy of 82% and a kappa index of 0.77. The results reveal that from 2017 to 2024 there was an increase of 148.09 km² of mining, with an average increase in TSS of up to 167 mg/l in water bodies most affected by mining activities. Finally, the continued importance of using remote sensing technologies, such as GEE, together with innovative methodological approaches, to monitor and manage natural resources in a sustainable manner is highlighted.

ATLID (ATmospheric LIDar) is the atmospheric backscatter LIDAR (Light Detection and Ranging) on board of the EarthCARE (Earth Cloud, Aerosol and Radiation Explorer) mission, the sixth Earth Explorer Mission of the ESA (European Space Agency) Living Planet Programme [1-5]. ATLID’s purpose is to provide vertical profiles of optically thin cloud and aerosol layers, as well as the altitude of cloud boundaries [6-10]. In order to achieve this objective ATLID emits short duration laser pulses in the UV, at a repetition rate of 51 Hz, while pointing in a near nadir direction along track of the satellite trajectory. The atmospheric backscatter signal is then collected by its 620 mm aperture telescope, filtered through the optics of the instrument focal plane assembly, in order to separate and measure the atmospheric Mie and Rayleigh scattering signals. With the completion of the full instrument assembly in 2019, ATLID has been subjected to an ambient performance test campaign, followed by a successful environmental qualification test campaign, including performance calibration and characterization in thermal vacuum conditions. In this paper the design and operational principle of ATLID is recalled and the major performance test results are presented, addressing the main key receiver and emitter characteristics. Finally, the estimated instrument, in-orbit, flight predictions are presented; these indicate compliance of the ALTID instrument performance against its specification and that it will meet its mission science objectives for the EarthCARE mission, to be launched in 2023.

With the goal of representing common denominators of aging in different organisms López-Otín et al. in 2013 described nine hallmarks of aging. Since then, this representation has become a major reference point for the biogerontology field. The template for the hallmarks of aging account originated from landmark papers by Hanahan and Weinberg (2000, 2011) defining first six and later ten hallmarks of cancer. Here we assess the strengths and weaknesses of the hallmarks of aging account. As a checklist of diverse major foci of current aging research, it has provided a useful shared overview for biogerontology during a time of transition in the field. It also seems useful in applied biogerontology, to identify interventions (e.g. drugs) that impact multiple symptomatic features of aging. However, while the hallmarks of cancer provide a paradigmatic account of the causes of cancer with profound explanatory power, the hallmarks of aging do not. A worry is that as a non-paradigm the hallmarks of aging have obscured the urgent need to define a genuine paradigm, one that can provide a useful basis for understanding the mechanistic causes of the diverse aging pathologies. We argue that biogerontology must look and move beyond the hallmarks to understand the process of aging.

The Serra da Estrela Natural Park (NPSEs) in Portugal stands out as a well-preserved region abundant in medicinal plants, particularly known for their pharmaceutical applications in diabetes prevention and treatment. This comprehensive review explores these plants' botanical diversity, traditional uses, pharmacological applications, and chemical composition. The NPSEs boast a rich diversity with 138 medicinal plants across 55 families identified as traditionally and pharmacologically used against diabetes globally. Notably, the Asteraceae and Lamiaceae families are prevalent in anti-diabetic applications. In vitro studies reveal their significant inhibition of carbohydrate-metabolizing enzymes, and certain plant co-products regulate genes involved in carbohydrate metabolism and insulin secretion. In vivo trials demonstrate anti-diabetic effects, including glycaemia regulation, insulin secretion, antioxidant activity, and lipid profile modulation. Medicinal plants in NPSE exhibit various activities beyond anti-diabetic, such as antioxidant, anti-inflammatory, antibacterial, anticancer, and more. Chemical analysis identifies over fifty compounds like phenolic acids, flavonoids, terpenoids, and polysaccharides responsible for their efficacy against diabetes. The findings underscore the potential of NPSE medicinal plants as anti-diabetic candidates, urging further research to develop effective plant-based anti-diabetic drugs, beverages, and supplements.

This study explores the relationship between positive and negative habits and their rewards over time. Using a bibliographic and documentary approach, we analyze how the temporality of rewards influences the formation and maintenance of habits. We developed the "habit chart", which shows that positive habits, such as reading, healthy eating, physical exercise, meditation and personal relationships, offer incremental and lasting rewards. In contrast, negative habits such as sugar consumption, excessive use of social media and a sedentary lifestyle provide immediate gratification followed by a sharp decline. The analysis was based on studies such as those by Warburton et al. (2006), Lally et al. (2010), and Hu (2003) for positive habits, and Malik et al. (2010) and Kross et al. (2013) for negative habits. We conclude that practical strategies, such as financial incentives and creating enabling environments, can make long-term rewards more tangible, promoting the adoption of healthy behaviors. This study reinforces the importance of the temporality of rewards in habit formation and suggests evidence-based interventions to improve quality of life and general well-being.

Cardiovascular disease is the most common cause of death. Oxidative stress and inflammation are pathophysiological processes involved in the development of cardiovascular diseases, so anti-inflammatory and antioxidant agents that modulate redox balance have become the targets of research to evaluate their molecular mechanisms and therapeutic properties. Astaxanthin, a carotenoid of the xanthophyll group, has potent antioxidant effects due to its molecular structure and its arrangement in the plasma membrane, factors that favor the neutralization of reactive oxygen and nitrogen species. This carotenoid also stands out for its anti-inflammatory activity, possibly interrelated with its antioxidant effect, as well as for its modulation of lipid and glucose metabolism. Considering the potential positive effects of astaxanthin on cardiovascular health evidenced by preclinical and clinical studies, this paper describes the molecular and cellular mechanisms related to the antioxidant and anti-inflammatory properties of this carotenoid in cardiovascular diseases, especially atherosclerosis.

Objective tools to track medication adherence are lacking. A tool to monitor pill intake that can be implemented in mHealth apps without the need for additional devices was developed. We propose a pill intake detection tool that uses digital image processing to analyze images of a blister to detect the presence of pills. The tool uses the circular Hough transform as a feature extraction technique and is therefore primarily useful for the detection of pills with a round shape. This pill detection tool is composed of two steps. First, the registration of a full blister and storing of reference values in a local database. Second, the detection and classification of taken and remaining pills in similar blisters, to determine the actual number of untaken pills. In the registration of round pills in full blisters, 100% of pills in gray blisters or blisters with a transparent cover were successfully detected. In counting of untaken pills in partially opened blisters, 95.2% of remaining and 95.1% of taken pills were detected in gray blisters, while 88.2% of remaining and 80.8% of taken pills were detected in blisters with a transparent cover. The proposed tool provides promising results for the detection of round pills. However, the classification of taken and remaining pills need to be further improved, in particular for the detection of pills with non-oval shapes.

The regulation of multiple bacterial phenotypes was found to depend on different cyclic di-nucleotides (CDNs) that constitute intracellular signalling second messenger systems. Most notably, c-di-GMP, along with proteins related to its synthesis, sensing and degradation, was identified as playing a central role in the switching from biofilm to planktonic modes of growth. Recently, this world has been under expansion, with the discoveries of other signalling CNDs in bacteria (c-di-AMP and cGAMP) and also in eukaryotes, novel protein and RNA receptors of CDNs, and the numerous functions related to these molecules. In this work, we comprehensively review and analyse the structural biology data about the systems that bacteria use to synthesise and recognise CDNs, detailing their interactions at molecular level with their products/ligands. Additional interesting observations were made, including that different receptor types can bind CDNs in similar conformations and that, based on genomic data, different CDN second messenger systems may coexist in many organisms. The large amount of sequence and structural data available allows a broad view of the importance of CDNs in bacteria, but how cells coordinate these molecules to ensure adaptation to changing environmental conditions is still open for much further exploration.

The use of large-scale antenna arrays grants considerable benefits in energy and spectral efficiency to wireless systems due to spatial resolution and array gain techniques. By assuming a dominant line-of-sight environment in a massive MIMO scenario with favorable propagation, we derive analytical expressions for the sum-capacity. % Then, we show that convenient simplifications on the sum-capacity expressions are possible when working at low and high SNR regimes. % Furthermore, in the case of a high SNR regime, it is demonstrated that the Gamma PDF can approximate the PDF of the instantaneous channel sum-capacity as the number of BS antennas grows. A second important demonstration presented in this work is that a Gamma PDF can also be used to approximate the PDF of the summation of the channel's singular values as the number of devices increases. Finally, it is important to highlight that the presented framework is useful for LPWAN's as we show that the transmit power of each device can be made inversely proportional to the number of BS antennas.

In this brief letter we report our initial results on the application of deep-learning to the massive MIMO channel estimation challenge. We show that it is possible to estimate wireless channels and that the possibility of mitigating pilot-contamination with deep-learning is possible given that the leaning model underwent an extensive training-phase and that it has been presented with a large number of different channel conditions.

The Physical Random Access Channel (PRACH) plays an important role in LTE and LTE-A systems. It is through the PRACH channel that the user equipment (UE), based on eNodeB's timing estimates, aligns its uplink transmissions to the eNodeB's uplink and gain access to the network. One of the initial operations executed by the PRACH receiver at eNodeB side is the translation of the PRACH signal back to base band, $i.e.$, center the PRACH signal around DC. This operation is a necessary step for preamble detection and can be carried out through a time-domain frequency shift operation. Therefore, in this paper we present the hardware architecture and implementation details of a configurable and optimized FPGA-based time-domain frequency shifter. It is a hardware-efficient and accurate architecture for converting the relevant received PRACH signal into base band before further signal processing. The architecture is manly based on a customized Numerically Controlled Oscillator (NCO), which is used for generating complex exponentials employing only adders, a Look-Up Table (LUT) and plain logic resources. The main advantage of the proposed hardware architecture is that it completely eliminates the need for storing a large number of long complex exponential sequences by employing a single LUT and exploiting quarter wave symmetry of the basis waveform. Our simulation results show that the proposed customized NCO architecture provides high Spurious Free Dynamic Range (SFDR) signals using a minimal amount of FPGA resources. Moreover, the proposed architecture exhibits spur-suppression ranging from 62.13 to 153.58 dB without using Taylor Series correction.

This paper proposes the use of compressive sensing to tackle the Massive MIMO channel estimation problem. As our results show compressive sensing-based estimators perform as well as the optimum MMSE estimator.

In this letter, we advocate that it is possible to mitigate Pilot Contamination in Massive MIMO systems by scrambling the pilot sequences with a Base Station (BS) scrambling sequence. It is possible if a set of sequences is carefully designed to meet the orthogonality property defined in this letter. Each BS possesses its own scrambling sequence that can be reused the same way frequency reuse is applied to cell deployment. The main advantage of the prosed pilot generation scheme is that the frequency reuse factor can be set to 1, the most aggressive one, while the scrambling sequences can be reused with much less aggressive reuse factors (e.g. 4, 7, 9, 12, etc.), which in consequence results in pilot contamination mitigation and increased system's performance.

Spatial modeling in Geographic Information Systems (GIS) always involves choices. The existence of constraints, either of a financial nature or related to the specifics of the software itself, to the algorithms, the uncertainty and even the reliability of the data, the purposes and the applications of the studies, make this a kind of guiding compass for GIS analysts. Building on a previous exercise of data acquisition (check-ins) based on two Digital Social Networks (DSN—Facebook and Foursquare) and on the awareness of the use of voluntary geographic information generated by tourists sharing their topophilic ties through DSN, the present analysis aims to evaluate the contribution of modern techniques of spatial analysis applied to tourism in the “Alta and University of Coimbra” area. Concepts and procedural tasks related to density determination, cluster analysis and identification of patterns associated with regionalized variables have thus been implemented with the purpose of evaluating and comparing the results obtained through the application of two techniques of spatial analysis, Kernel Density Estimation (KDE) and Optimized Hot-Spot Analysis (OHSA) & Inverse Distance Weighting (IDW) Interpolation.

Kisspeptin, a key neuropeptide derived from the KISS1 gene, is renowned for its critical role in regulating the hypothalamic-pituitary-gonadal axis and reproductive hormone secretion. Beyond its primary function in reproductive biology, emerging research has illuminated its influence in various cancers, mediating significant effects through its interaction with the G-protein coupled receptor, Kisspeptin receptor. This interaction has been implicated in modulating cellular pro-cesses such as proliferation and metastasis, making it a potential target for therapeutic interven-tion. Our study initially screened ten kisspeptin-10 analogs through cytotoxic effects of kisspep-tin-10 (KP10) and its analogs in several cancer types, including cervical, prostate, breast, and gastric cancers, with a particular focus on cervical cancer where the most profound effects were observed. Further exploration using kinase array assays revealed that these analogs specifically alter key kinases involved in cancer progression. Migration assays demonstrated a substantial decrease in cell motility, and Bioluminiscence Resonance Energy Transfer assays confirmed these analogs strong interactions with the kisspeptin receptor. Overall, our results indicate that these KP10 analogs not only hinder cervical cancer cell proliferation but also curtail migration through targeted modulation of kinase signaling, suggesting their potential as therapeutic ayfgents in managing cervical cancer progression. This comprehensive approach underscores the therapeutic promise of exploiting kisspeptin signaling in cancer treatment strategies.

This study explores the multifaceted influence of litter size, maternal care, exercise, and aging on rats' neurobehavioral plasticity and dentate gyrus microglia dynamics. Body weight evolution revealed a progressive increase until maturity, followed by a decline during aging, with larger litters exhibiting lower weights initially. Notably, exercised rats from smaller litters displayed higher body weights during mature and aged stages. Dentate gyrus volumes showed no significant differences among groups, except for aged sedentary rats from smaller litters, which exhibited a reduction. Maternal care varied significantly based on litter size, with large litter dams showing lower frequencies of caregiving behaviors. Behavioral assays highlighted the detrimental impact of a sedentary lifestyle and reduced maternal care/large litters on spatial memory, mitigated by exercise in aged rats from smaller litters. Microglial dynamics in the layers of dentate gyrus revealed age-related changes modulated by litter size and exercise. Exercise interventions mitigated microgliosis associated with aging, particularly in aged rats. These findings underscore the complex interplay between early-life experiences, exercise, microglial dynamics, and neurobehavioral outcomes during aging.

The aim of the present study was to investigate whether chronic undernutrition modifies the response to rostafuroxin in juvenile rats. Chronic undernutrition was induced in male rats using a multideficient diet known as Regional Basic Diet (RBD), mimicking alimentary habits in impoverished regions worldwide. Animals were given RBD – or a control/CTRL normal diet for rodents – from weaning to 90 days, and rostafuroxin (1 mg/kg body mass) or vehicle were orally administered during the last 30 days. Undernourished rats became hypertensive at 55–60 days of age (tail-cuff recording). During the last two days, the rats were hosted in metabolic cages to measure food/energy, water, Na⁺ ingestion, and urinary volume. Blood and kidneys were collected after euthanasia. Rostafuroxin increased food/energy and Na⁺ intake in CTRL and RBD rats but had opposite effects on Na⁺ balance (intake minus urinary excretion): negative in CTRL and positive in RBD. The drug normalized the decreased plasma Na⁺ concentration found in RBD rats, increased urinary volume in RBD but not in CTRL, and decreased and increased urinary Na⁺ concentration in the RBD and CTRL groups, respectively. Rostafuroxin decreased the ouabain-sensitive (Na⁺+K⁺)ATPase and increased the ouabain-resistant, furosemide-sensitive Na⁺-ATPase from proximal tubule cells in both groups, and normalized the systolic blood pressure in RBD without effect in CTRL rats. We conclude that chronic undernutrition modifies the response of blood pressure, caloric metabolism, Na⁺ distribution in liquid compartments, mobilization of Na⁺ from non-osmotic compartments, Na⁺ and water balance, and activity of renal Na⁺-transporting ATPases to rostafuroxin.

The disastrous 2017 fire season in Portugal lead to widespread recognition of the need for a paradigm shift in forest and fire management. We focused our study on Alvares, a parish in central Portugal which had 60% of its area burned in 2017, with a large record of historical. We evaluated how different fuel treatment strategies can reduce wildfire hazard in Alvares, through i) a fuel break network with different priorities and ii) random fuel treatments resulting from stand-level management intensification. To assess this, we developed a stochastic fire simulation system (FUNC-SIM) that integrates uncertainties in fuel distribution over the landscape. If the landscape remains unchanged, Alvares will have large burn probabilities in the north, northeast, and center-east areas of the parish that are very often associated with high fire line intensities. The different fuel treatment scenarios decreased burned area between 12.1-31.2%, resulting from 1%-4.6% increases in annual treatment area, and reduced 10%-40% the likelihood of wildfires larger than 5000 ha. On average, simulated burned area decreased 0.22% per each ha treated, and effectiveness decreased with increasing area treated. Overall, both fuel treatment strategies effectively reduced wildfire hazard and should be part of a larger, holistic and integrated plan to reduce the vulnerability of the Alvares parish to wildfires.

Dipteryx spp. is an important species in reforestation in the Amazon. The objective of this study is to characterize and compare the relationships between dendrometric variables in Dipteryx spp. stands in the Western Amazon by fitting linear regression equations for total height and crown diameter. Six forest stands were evaluated in three municipalities. Dendrometric variables collected included diameter at 1.3 m height (dbh), total height (ht) and crown diameter (dc). Simple and multiple linear regression equations were fitted to characterize the relationships between ht and dc. The total aboveground biomass of Dipteryx spp. trees and the carbon stock of the stands were estimated. The general equations showed higher R² values, exceeding 0.7. The general equations for estimating ht and dc were significant for all coefficients. The trees averaged 22 t/ha of aboveground biomass in the stands. There was a variation in carbon sequestration potential among stands, ranging from 5.12 to 88.91 t CO2.ha-1. Single-input equations using dbh as an independent variable are recommended for estimating dc and ht for individual Dipteryx spp. stands. Stands in the Western Amazon play a significant role in carbon sequestration and accumulation. Trees can sequester an average of 4.8 tons of CO2 per year.

Mercury is classified as one of the world’s most toxic and dangerous pollutants. It tends to bio-accumulate and biomagnify within the trophic chain and is persistent. Various approaches are available to remediate Hg-affected sites, including phytoremediation, which includes the use of plants to clean up contaminated environments. Phytoremediation of mercury contamination is at-tracting increasing attention because of its advantages: it is environmentally friendly, inexpensive, simple, and can improve soil fertility. In this report, VOSviewer, and Bibliometrix software were used to analyze 457 and 697 documents published from 2000 to 2023, retrieved from the data-bases WoS and Scopus, respectively. China, India, the United States, and Spain are the top four most productive countries. The largest topic area was environmental sciences, and the Chinese Academy of Sciences was the organization that contributed the most to the overall number of pub-lications. The keywords with the highest frequency, excluding phytoremediation and mercury in WoS, were heavy metals, accumulation, cadmium, soils, and phytoextraction. In Scopus, the most frequent keywords were bioremediation, heavy metals, soil pollution, bioaccumulation, biodeg-radation, and environmental. From the above analysis, we concluded that future research should focus on 1) finding native plants, 2) increasing remediation ability through assisted phytoremedi-ation, 3) studies of molecular mechanisms in plants with phytoremediation potential, and 4) ge-netic engineering applications. This study provides insight into trending themes and serves as a reference for future research.

The glucose-insulin regulatory system and its glucose oscillations is a recurring theme in the literature because of its impact on human lives, mostly the ones affected by diabetes mellitus. Several approaches were proposed, from mathematical to data-based models, with the aim of modeling the glucose oscillation curve. Having such a curve, it is possible to predict, when injecting insulin in type 1 diabetes (T1D) individuals. However, the literature presents prediction horizons no longer than 6 hours, which could be a problem considering their sleeping time. This work presents Tesseratus, a model that adopts a multi-agent approach to combine machine learning and mathematical modeling to predict the glucose oscillation up to 8 hours. Tesseratus uses the pharmacokinetics of insulins and data collected from T1D individuals. Its outcome can support endocrinologists while prescripting daily treatment for T1D individuals, and provide personalized recommendations for such individuals, to keep their glucose concentration in the ideal range. Tesseratus brings pioneering results for prediction horizons of 8 hours for nighttime, in an experiment with seven real T1D individuals. It is our claim that Tesseratus will be a reference for classification of glucose prediction model, supporting the mitigation of short- and long-term complications in the T1D individuals.

Currently, algae arouse a growing interest in the pharmaceutical and cosmetic area due to the fact that they have a great diversity of bioactive compounds with the potential for pharmacological, cosmetic, and nutraceutical applications. Many of these bioactive compounds are secondary metabolites whose amounts in the algae vary with varying environmental conditions. Free radicals and other active oxygen derivatives are recognized as a natural by-product of aerobic metabolism. However, reactive oxygen species directly participate in mechanisms related to various pathological states such as cancer, diabetes, atherosclerosis, Alzheimer's, and Parkinson's, among others. Diabetes mellitus (DM) is a metabolic disease resulting from changes in glucose metabolism and/or deficient production/action of insulin. This review has as its main objective to reveal the potential antioxidant and antidiabetic capacity of algae extracts.

In healthy adult brain, glial cell line-derived neurotrophic factor (GDNF) is exclusively expressed by neurons and in some instances, it has furthermore been shown to derive from a single neuronal subpopulation. Secreted GDNF acts in a paracrine fashion by forming a complex with GDNF family receptor α1 (GFRα1) which is mainly expressed by neurons and can act in cis as a membrane-bound or in trans as a soluble factor. The GDNF/GFRα1 complex signals through interaction with RET (“rearranged during transfection”) or with a lower affinity with neural cell adhesion molecule (NCAM). GDNF can also signal independently from GFRα1 via interaction with syndecan-3. RET being expressed by neurons involved in several pathways: nigro-striatal dopaminergic neurons, motor neurons, enteric neurons, sensory neurons, etc. could be the main determinant of the specificity of GDNF pro-survival effect. In injured brain, de novo expression of GDNF occurs in glial cells. Neuroinflammation has been reported to induce GDNF expression in activated astrocytes and microglia, infiltrating macrophages, nestin-positive neural stem cells and neuron/glia (NG2) progenitors. This disease-related GDNF overexpression can be either beneficial or detrimental depending on the localization in the brain and the level and duration of glial cells activation. Some reports also describe upregulation of RET and GFRα1 in glial cells, suggesting that GDNF could modulate neuroinflammation.

This paper, based on the "Unified Theory of Forces," rigorously proves the formula of de Broglie's wave function. This helps us better understand the following important issues: 1) Theoretically prove and understand the essence of de Broglie's wave function; 2) Prove that when the particle's momentum P is determined, the greater the mass of the particle, the more concentrated its wave function distribution, and the weaker the interference effect; 3) Correct the spatial distribution of the wave function of free particles, proving that the wave function of free particles is strictly constrained within a finite spatial range, which is consistent with the facts we observe.

Background: COVID-19 is currently one of the most important medical challenges as it affects the entire population with children being infected as easily as adults. Objective: The study evaluated the mortality of under 17-year-olds and compare the frequency with that of adults in a cohort of 8986 COVID-19 positive patients hospitalized in a single care center. Design: retrospective clinical trial, all hospitalizations of COVID-19 positive patients as diagnosed by RT-qPCR were analyzed by revisiting their medical records. Setting: 8986 COVID-19 positive patients hospitalized in a Hospital de Base and the Infant and Maternal Hospital of São Jose do Rio Preto, SP, Brazil (HB/HCM) being these totals of 383 COVID-19 positive under 17-patients. Patients: patients COVID-19 positive under 17-year-olds were grouped by age and evaluated by analyzing their medical records. They were categorized as Group I, children, and adolescents under 19 years old and Group II, adults over 19 years. Results: Overall mortality in under 19-year-olds was 12 deaths, that is, 3.13% of the patients in this age group and 0.55% of the overall mortality from COVID-19. Mortality in the group of adults was 2197 equivalent to 24.45% of the hospitalized adults and 99.45% of overall deaths. Mortality was significantly higher for adults than for under 19-year olds (p-value < 0.0001). Regarding the different ages of children and adolescents, the number of deaths of under 1-year olds was 2/123 (1.62%), of 1-4 years it was 4/95 (2.11%), of 5-9 years it was 1/47 (2.13%), of 10-14 years it was 1/40 (2.5%) and of 15-19 years it was 4/78 (5.13%). There were no statistical differences between the different age groups ( p-value = 0.3). Conclusion: Mortality from COVID-19 in children and adolescents was lower than in adults and generally associated with other comorbidities with the main association being with heart disease.

The endomembrane system in plant cells enables the cell to manage and coordinate a variety of membranous compartments so that they and their contents arrive at the right location. The secretory pathway takes part in this complex network and has its gateway at the Endoplasmic Reticulum. Therefore, alterations at the Endoplasmic reticulum level could condition how protein trafficking takes place or, at least, influence how such cargo leaves this organelle. With this work, we intended to assess how abnormalities at the Endoplasmic Reticulum would interfere with protein sorting and trafficking. Thus, we used a novel Arabidopsis mutant - leb-2 GFP-h -, presenting ER morphology alterations. Our results show that alterations in the leb-2 GFP-h mutant did not disrupt PSI A/B–mCherry transport to the vacuole but influences the expression of endogenous aspartic proteinases. Furthermore, the study of key-endomembrane genes expression revealed an upregulation of the SNAREs AtVAMP722 and AtVAMP723. As a whole, the leb-2 mutant seems not to interfere with vacuolar routes but may be implicated in secretion events.

Because most of the recognized causes of superior gluteal nerve (SGN) injury are iatrogenic, detailed knowledge of the anatomy of the SGN is crucial to prevent its injury associated with surgical procedures. This study aims to describe the precise location of SGN or its branches at the greater sciatic foramen, measure the distances of these nervous structures to palpable bony landmarks, and evaluate the possible correlation between these parameters and pelvis size. Twenty human cadaveric hemipelvises were studied. After dissection to expose the SGN or its branches at the greater sciatic foramen, the distances from these nervous structures to the greater trochanter (GT), to the anterior superior iliac spine (ASIS), to the posterior superior iliac spine (PSIS), to the ischial tuberosity (IT), and to the greater sciatic notch were measured. We found that at the greater sciatic foramen the SGN emerges as a common trunk in 75% of hemipelvises, and already divided in its superior and inferior branches in 25% of hemipelvises. When the SGN exits the pelvis as a common trunk, it does so, in most cases, in contact with the bone at the apex of the greater sciatic notch or superior to it. The median distance from the SGN at the greater sciatic notch to the PSIS, ASIS, GT and IT is 7.6 cm, 10.9 cm, 7.5 cm and 10.8 cm, respectively. We found a positive correlation between some of the analyzed parameters and the size of the pelvis. The anatomical data of this study may serve as pivotal guides during orthopedic pelvic surgery, contributing to minimize SNG iatrogenic lesions with significant implications in the patient's quality of life.

Despite the efforts made to stop the tuberculosis (TB) epidemic, it still remains one of the leading causes of death from an infectious disease. Previous work in the group uncovered a new family of amides which showed promising activities against Mycobacterium tuberculosis. A closer look at the literature showed that these compounds are structurally related to the DNB family of DprE1 inhibitors, so, we decided to study a wide range of substituted amides and determine their activity, focusing on unexplored structures related to the dinitrobenzamides (DNB) found in the literature. To synthesize our library of compounds we started from 3,5-dinitrobenzoic acid to form the nitroaromatic core that is characteristic of the DNB’s, to which we then added linear or cyclic amine moieties. Additionally, the impact of terminal aromatic moieties was also assessed for some derivatives, via an ether, ester, or amide bond. In order to obtain the desired derivatives, multiple synthetic approaches were used, mainly focused on nucleophilic addition/elimination reactions, SN2 reactions and Mitsunobu reactions. The activity was impacted mainly by two structural features, the addition of an aromatic moiety as a terminal group and the type of the linker. The most interesting compounds exhibited activities comparable to isoniazid and DNB1. Computational studies were also performed aimed at understanding their possible interactions with DprE1. The most active compounds are a good starting point for further development, and we plan to study an extended family of compounds based in those structures.

Plants exhibit the capacity for adaptation through their metabolic processes to various changes in environmental conditions. Investigating these adaptations in current and future climatic scenarios is of great importance for ensuring productive agricultural crops. This adaptative potential is commonly employed as an indicator of genotypes with higher potential in breeding programs. However, the complexity and interaction of plant metabolic parameters pose a challenge to selection strategies. In this context, the aim of this study was to explore phenotypic plasticity within the germplasm of Hybrid Timor coffee. Additionally, we assessed the utility of the Phenotypic Plasticity Index (MVPi) as a promising tool to predict genotype performance across diverse climatic conditions. To achieve this, we evaluated the performance of seven accessions from the Hybrid Timor germplasm in comparison to the Rubi and IPR 100 cultivars, known for their susceptibility and resistance to drought, respectively. The experiment was conducted at greenhouse conditions, with two treatments: a control scenario, maintaining soil moisture near its maximum water-holding capacity, and a water deficit scenario involving irrigation cessation followed by rehydration. Data encompassing physiological, biochemical, and growth aspects were collected during three distinct stages: pre-application of water deficit, its imposition, and subsequent rehydration. Furthermore, field evaluations of the productivity of the same genotypes were carried out over two consecutive seasons. Based on physiological and biochemical assessments, the MVPi was computed, employing Euclidean distance between principal component multivariate analysis scores. Subsequently, this index was correlated with growth and productivity data through linear regressions. Our findings reveal that the more plastic genotypes, capable of significantly altering physiological and biochemical parameters in response to environmental stimuli, exhibited reduced biomass loss in both aerial and root parts, consequently positively influencing their productivity. Enhanced plasticity was particularly prominent in accessions from the MG Germplasm Collection: MG 311 - Hybrid Timor UFV 428-02, MG 270 - Hybrid Timor UFV 377-21, and MG 279 - Hybrid Timor UFV 376-31, alongside the Rubi MG 1192 cultivar. The MVPi emerged as a valuable instrument to assess genotype adaptability and predict their performance under varying climatic scenarios.

The last decade has seen remarkable progress in the characterization of methylation clocks that track biological age in humans and many other mammalian species. While the biological processes of aging that underlie these clocks have remained unclear, several clues have pointed to a link to developmental mechanisms. These include the presence in the vicinity of clock CpG sites of genes that specify development, including those of the Hox (homeobox) and polycomb classes. Here we discuss how recent advances in programmatic theories of aging provide a framework within which methylation clocks can be understood as part of a developmental process of aging. This includes how such clocks evolve, how developmental mechanisms cause aging, and how they give rise to late-life disease. The combination of ideas from evolutionary biology, biogerontology and developmental biology open a path to a new discipline, that of developmental gerontology (devo-gero). Drawing on the properties of methylation clocks, we offer several new hypotheses that exemplify devo-gero thinking. We suggest that polycomb controls a trade-off between earlier developmental fidelity and later developmental plasticity. We also propose the existence of an evolutionarily-conserved developmental sequence spanning ontogenesis, adult development and aging, that both constrains and determines the evolution of aging.

Leishmania parasites present astonishing adaptative abilities that represent a matter of life or death within disparate environments during the heteroxenous parasite life cycle. From an evolutionary perspective, organisms develop methods of overcoming such challenges. Strategies that extend beyond the genetic diversity have been discussed and include variability between parasite cells during the infections of their hosts. The occurrence of Leishmania subpopulation fluctuations with variable structural genomic contents demonstrates that a single strain might shelter the variability required to overcome inconsistent environments. Such intrastrain variability provides parasites with an extraordinary ability to adapt and thus survive and propagate. However, different perspectives on this evolution have been proposed. Strains or species living in the same environment can cooperate but also compete. These interactions might increase the replication rate of some parasites but cause the loss of more aggressive competitors for others. Adaptive responses to intra- and interspecific competition can evolve as a fixed strategy (replication is adapted to the average genetic complexity of infections) or an optional strategy (replication varies according to the genetic complexity of the current infection). This review highlights the complexity of interspecies and intrastrain interactions among Leishmania parasites as well as the different factors that influence this interplay.

The Yellow-legged Hornet (Vespa velutina nigrithorax) (YLH) is an invasive insect that arrived in Europe in 2004 and is now spread across nine countries. It is a threat to the native entomofauna and harmful to beekeeping and agriculture, as it is a ravenous predator of the European Honey Bee (Apis mellifera) and other pollinating species. Its expansion has been unstoppable and all resources are needed to fight against it, including native vertebrate predators. Among these, the European Bee-eater (Merops apiaster) (EBE) is a potential one, but little is known about its predation on YLH. In a study carried out in Portugal, remains of YHL were detected in EBE nesting sites, which to the best of our knowledge is the first such report. This means that this bird could be one more agent in the biological control of this pest (although research on predation intensity is still needed), in conjunction with other natural predators and other strategies. In the Iberian Peninsula both species are allopatric in vast regions, so the role of EBE may be more limited. However, in the rest of Europe, at a country or continent scale, the scenario may be different and sympatry may occur to a greater extent.

The bacterial adhesion to food contact surfaces is a threat to human health, as these surfaces can serve as a reservoir of pathogenic bacteria. Escherichia coli is a biofilm-forming bacterium involved in surface contamination. Despite the application of disinfection protocols, contamination continues to occur. Hence, new effective and sustainable approaches are needed. Bacteriophages (or simply phages), viruses that only infect bacteria, have proven to be effective in reducing biofilms. Here, phage phT4A was applied to prevent and reduce E. coli biofilm on plastic and stainless steel. The assays were performed in Tryptic Soy Broth (TSB), at 25 °C. The biofilm formation capacity of phage-resistant and sensitive bacteria, after treatment, was also evaluated. Maximum reductions on E. coli biofilm of 5.5 log colony forming units (CFU)/cm2 (after 6 h) and 4.1 log CFU/cm2 (after 9 h), on plastic and stainless steel, respectively, were observed. In the prevention assays, phage prevented biofilm formation in 3.2 log CFU/cm2, after 12 h. Although the emergence of phage-resistant bacteria has been observed during phage treatment, a lower biofilm formation capacity was observed by phage-resistant bacteria comparatively to phage-sensitive bacteria. Overall, phages have shown to be a promising approach to decontaminate food handling surfaces.

Ruderal plants designate native or exotic plant species that grow spontaneously in anthropized environments, being important from the ecological succession perspective. The present study aimed to identify ruderal plants that occur in an anthropized area of the Campus Floresta of the Federal University of Acre (UFAC), in the municipality of Cruzeiro do Sul, in the Southwest Amazon. Toward this end, botanical material was collected and herborized, and identified based on consultation of the specialized literature, virtual herbariums, and by comparison with the Campus Floresta Herbarium (CFCZS) collection. Finally, these data were incorporated to the referred collection, according to the usual plant systematics procedures. The results revealed 28 species and 28 genera, distributed in 14 families. The most representative families were Fabaceae, Malvaceae and Poaceae, with four species each; followed by Asteraceae with three; Cyperaceae, Rubiaceae and Amaranthaceae with two each; and the others, Plantaginaceae, Ochnaceae, Urticaceae, Verbenaceae, Iridaceae, Lamiaceae and Dennstaedtiaceae with one species each. The occurrence of predominant species in planted pastures, agricultural use, and mining area ecosystems is highlighted, such as Pteridium aquilinum (L.) Kuhn., Andropogon bicornis L., and Crotalaria micans Link.

The aim of this study was to provide information on the levels of toxic (Cd and Pb) and essential (Cu, Fe and Zn) elements in cow’s milk produced in the State of Pernambuco (Brazil). A total of 142 samples of raw milk were collected, and the concentrations of essential and toxic elements were determined by inductively coupled plasma-optical emission spectrometry. In almost 30 % of the samples analyzed, the Pb content exceeded the maximum level established in the Brazilian legislation (0.05 mg/l). By contrast, in all samples the Cd content was below the maximum allowable level (0.02 mg/L). The essential trace elements Cu, Fe and Zn were generally present at lower concentrations than reported in other studies and can be considered within the deficient range for cow’s milk. Statistical and chemometric procedures were used to evaluate the main factors influencing the metal concentrations (proximity to major roads, presence of effluents, and milking method). The study findings demonstrate that the proximity of the farms to major roads influences the concentrations of Cd, Pb and Cu and that this is the main factor explaining the Pb content of milk. In addition, the presence of effluents influenced the concentrations of Cu, while no relationship between the metal content and the milking method was observed. Thus, in accordance with the study findings, consumption of cow’s milk produced in the region can be considered a risk to public health due to the high concentrations of Pb and the low concentrations of other essential minerals such as Cu, Zn and Fe in some of the milk samples.

Brazil has ideal conditions for the large-scale use of cabotage cargo transportation: a vast coastline with almost 7,400 km, approximately 70% of the population resident in a coastal range of up to 200 km from the coast and a strong concentration of activities economic along the coast. However, there is an absolute domain of road modal for the transportation of goods, and cabotage is underused. The purpose of the study was to raise the main barriers that negatively impact the performance of Brazilian cabotage. To this end, it was used to bibliographic and documentary research, based on studies already published in journals, doctoral theses, master's dissertations, congress annals, technical reports and research on government-related government agencies sites, navigation companies and entities related to cabotage. The main barriers that contribute to the low use of cabotage in Brazil were identified and analyzed, as well as possible alternatives of solution for sustainable development of this mode of transport. Such a study will certainly serve as subsidies for the definition of public policies aimed at better use of Brazilian cabotage, as well as to encourage navigation companies to invest more in the transport of goods by cabotage, in order to contribute to the reduction of trucks on highways Brazilian and for environmental preservation.

Intrusion Detection Systems play a crucial role in a network. They can detect different network attacks and raise warnings on them. Machine learning-based IDSs are trained on datasets that, due to the context, are inherently large, since they can contain network traffic from different time periods and often include a large number of features. In this paper, we present two contributions: the study of the importance of feature selection when using an IDS dataset, while striking a balance between performance and the number of features; and the study of the feasibility of using a low-capacity device, the Nvidia Jetson Nano, to implement an IDS in a low-capacity network. The results, comparing the GA with other well-known techniques in feature selection and reduction, show that the GA has a higher F1-score of 76%, although the time to find the optimal set of features surpasses other methods; the reduction of the number of features reduces the processing time without a significant impact in f1-score. The Jetson Nano allows the classification of network traffic with an overhead of 10 times in comparison to a traditional server.

This study evaluated the stability of the Poly-(sorbitol-co-citrate adipate) with potential applica-tion in the biomedical area. Thus, the physical, chemical and microbiological stability of this was investigated. First, the chemical stability in alkaline phosphate buffer (pH 7.4) was evaluated for 5 days. In aqueous solution, the copolymer acidified the medium indicating the presence of residual citric acid. In the moisture absorption test the results obtained followed the pH, reinforcing the presence of citric acid. In the evaluation of the antimicrobial activity the results indicate that the copolymer did not allow the growth of the yeast Saccharomyces cerevisiae, as the only source of carbon. However, in the cell lysis phase and due to the restriction of access to nutrients in the culture medium, the copolymer showed a loss of mass due to its use by the microorganism. Thus, it presented biodegradability property under extreme conditions of cell culture.

: Sputtering of silicon in a Helium magnetron discharge (MS) has been reported as a bottom-up procedure to obtain He-charged silicon films (i.e. He nanobubbles encapsulated in a silicon matrix). The incorporation of heavier noble gases is demonstrated in this work with a synergistic effect producing increased Ne and Ar incorporations when using He-Ne and He-Ar gas mixtures in the MS process. Microstructural and chemical characterizations are reported by ion beam analysis (IBA) and scanning and transmission electron microscopies (SEM and TEM). In addition to gas incorporation, helium promotes the formation of larger nanobubbles. For the case of Ne high resolution X-ray photoelectron and absorption spectroscopies (XPS and XAS) are reported with remarkable dependence of the Ne 1s photoemission and the Ne K-edge absorption on the nanobubbles size and composition. The gas (He, Ne, Ar) charged thin films are proposed as “solid” targets for the characterization of spectroscopic properties of noble gases in a confined state without the need for cryogenics or high-pressure anvils devices. Also their use as targets for nuclear reaction studies is foreseen.

This work reports the role of structure and composition on the determination of the performances of p-type SnOx TFTs deposited by rf magnetron sputtering at room temperature, followed by a post-annealed step up to 200 °C at different oxygen partial pressures (Opp), between 0% and 20%, but where the p-type conduction was only observed between 2.8–3.8%. The role of structure and composition were evaluated by XRD and Mössbauer spectroscopic studies. The study allows to identify the best phases/compositions and thicknesses (around 12 nm) to be used that lead to the production of TFTs with a bottom gate configuration, on glasses coated with conductive Indium Tin Oxide, followed by Aluminium Titanium Oxide dielectric layer with saturation mobility of 4.6 cm²V⁻¹s⁻¹ and on-off ratio above 7 × 10⁴, operating at the enhancement mode with a saturation voltage of −10 V.

Over the last two decades, a considerable amount of equipment has been acquired (spreaders, seeders, sprayers, among others) to respond to the challenges of Precision Agriculture (PA) concept. Most of this equipment has been purchased at a high cost. However, many of them, despite still being functional and equipped with sensors, actuators, and electronic processing units capable of adjusting to variations in speed, have become obsolete in terms of communication, and incompatible with new monitoring and control systems based on the “Isobus” protocol. This work aims to present a solution for updating the control system (“Ferticontrol”) of a “Vicon RS-EDW” spreader with variable rate application (VRA), making it compatible with the “InCommand” system from “Ag Leader”. The solution includes low-cost “Arduino” and “Raspberry Pi” microcontrollers and open-source software. The development shows that it is possible to implement a solution that is accessible to farmers in general. It also provides a niche business opportunity for young researchers to set up small technology-based enterprises associated with universities and research centers. These partnerships guarantee permanent innovation and represent a decisive step towards modern, technological, competitive, and sustainable agriculture.

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

Drought events are evident effects of climate change around the globe and yield several socio-economic impacts. Such effects are even more relevant for South America (SA) since different activities essential for the continent, like agriculture and energy generation, depend highly on water resources. Thus, this study aimed to evaluate future changes in precipitation and hydro-logical droughts occurrence in SA through climate projections from eight global climate models (GCMs) of CMIP6. To this end, statistical downscaling was applied to the projections with the Quantile Delta Mapping technique, and the method proved to be efficient in reducing systematic biases and preserving GCMs’ trends. For the following decades, the results show considerable and statistically significant reductions in precipitation over most of SA, especially during the austral spring, with the most intense signal under the SSP5-8.5 forcing scenario. Furthermore, GCMs showed mixed signals about projections of the frequency and intensity of drought events. Still, they indicated agreement regarding the increase in duration and severity of events over all of SA and a substantial proportion of moderate and severe events over most of Brazil during the 21st century. These results can be helpful for better management of water resources by deci-sion-makers and energy planners.

Ménière's disease (MD) has an unclear cause. The microvascular dysregulation of the inner ear has been increasingly pointed as a potential contributor. This study investigates the prevalence of cardiovascular risk factors (CVRFs) in MD patients compared to those with posterior circulation cerebral infarction (POCI). CVRFs like hypertension, diabetes, dyslipidemia, obesity, coronary heart disease, and smoking were assessed in both MD and POCI patients. Brain MRI identified POCI etiology as "small vessel occlusion" (SVO) or "other etiology" (OE). The study included 64 MD and 84 POCI patients. Compared to MD, POCI OE showed a higher prevalence of CVRFs across various age groups, including hypertension, diabetes, dyslipidemia, and smoking. Notably, the odds of having POCI OE were significantly higher for individuals with hypertension and smoking. On the other hand, POCI SVO showed similar prevalence of CVRFs compared to MD. This study reveals no significant difference in CVRF prevalence between MD and smaller vessel POCI. However, a clear distinction emerges when comparing MD to POCI with involvement of larger blood vessels. Further research is needed to confirm these findings and explore potential shared risk factors between POCI (SVO) and MD.

The article explores Qualitative Comparative Analysis (QCA), an approach for establishing causal relationships between conditions and outcomes. QCA, applied in case studies and empirical analyses, facilitates generalizations for future research and addresses causal complexity by identifying various causal "recipes" leading to the same outcome. Three widely used QCA variants are Crisp-Set QCA (csQCA), Multi-value QCA (mvQCA), and Fuzzy-Set QCA (fsQCA), each with unique approaches. The article emphasizes the significance of bibliometric analysis in mapping a research field's intellectual structure, revealing key contributions and trends. In QCA, bibliometric analysis identifies leading researchers, affiliations, and influential countries. Results show QCA's widespread adoption across disciplines, with continuous growth in article production since 2013. The favored variant is fsQCA, followed by csQCA, and China notably contributes to QCA-related research. In conclusion, QCA proves a potent tool for discerning complex causal relationships in empirical studies, with its increasing interdisciplinary use indicating substantial potential for advancing scientific knowledge.

In contemporary construction, the prevalence of vibration serviceability issues in lightweight and slender structures has become increasingly common, owing to advancements in building materials and construction methods. While these structures often meet the criteria for ultimate limit states, they can still elicit complaints due to excessive vibrations induced by human activity. To address this challenge, the Integral Resonant Control (IRC) technique has emerged as a favored approach for actively damping vibrations in various systems. This study introduces a fresh perspective on implementing a multi-input multi-output (MIMO) IRC scheme for active vibration control (AVC) specifically tailored for pedestrian structures utilizing inertial mass actuators. Building upon a common framework and design methodology outlined in previous research, this work presents a novel application of MIMO IRC for AVC. The designed controller is rigorously tested and implemented on a laboratory floor structure to validate its efficacy.

Accurate channel estimation is of utmost importance for massive MIMO systems that allow providing significant improvements in spectral and energy efficiency. In this work, we investigate the spectral efficiency performance and present a channel estimator for multi-cell massive MIMO systems subjected to pilot-contamination. The proposed channel estimator performs well under moderate to aggressive pilot contamination scenarios without prior knowledge of the inter-cell large-scale channel coefficients and noise power. The estimator approximates the performance of a linear Minimum Mean Square Error (MMSE) as the number of antennas increases. Following, we derive a lower bound closed-form spectral efficiency of the Maximum Ratio Combining (MRC) detector in the proposed channel estimator. The simulation results highlight that the proposed estimator performance approaches the linear minimum mean square error (LMMSE) channel estimator asymptotically.

Changes in food quality can dramatically impair zooplankton fitness, especially in eutrophic water bodies where cyanobacteria are usually predominant. Cyanobacteria are considered a food with low nutritional value, besides some species can produce bioactive secondary metabolites reported as toxic to zooplankton. Considering that cyanobacteria can limit survival, growth and reproduction of zooplankton, we hypothesized that the adverse effects of the dietary exposure of Daphnia species to saxitoxin-producing cyanobacteria depend on the relative abundance of nutitious food source in the diet. Life table experiments were conducted with different diets: 1) without nutritional restriction, where neonates were fed with diets at a constant green algae (Monoraphidium capricornutum) biomass as a nutritious food source, and increasing cyanobacterial concentration (STX-producing Raphidiopsis raciborskii), and 2) with diets consisting of different proportions of M. capricornutum (nutritious) and R. raciborskii (poor food) at a total biomass 1.0 mg C L 1. In general, the presence of high proportions of cyanobacteria promoted a decrease in Daphnia somatic growth, reproduction and intrinsic rate of population increase (r) in both diets with more pronounced effects in the nutritionally restricted diet (90% R. raciborskii). Two-way ANOVA revealed significant effects of species/clone and treatments in both assays, with significant interaction between those factors only in the second assay. Regarding the grazing assay, only D. laevis was negatively affected by increased cyanobacterial proportions in the diet. In the life table assay with constant edible food, a reduction in the reproduction parameters and the intrinsic rate of population increase (r) of all species was observed, In conclusion, we found adverse effects of the toxic cyanobacterial strain R. raciborskii on Daphnia fitness, regardless of the constant amount of nutritious food available, proving the toxic effect of R. raciborskii and the nutritional quality of the food has a greater influence on the fitness of these animals.

. (1) Background: The aim of this study was to verify the differences in body composition, power and lower limb muscle strength in futsal players from three competitive levels. (2) Methods: The study involved 68 players (24.26 ± 4.63 years), divided into three competitive levels: elite, sub-elite and amateur. To assess physical condition, we used the Inbody270, the ChronoJump and the Isokinetic Dynamometer and used the non-parametric Kruskal-Wallis test to compare the three independent variables. (3) Results: There were no differences in body composition between the players at the three competitive levels. With regard to lower limb muscle power and strength, the elite group showed, on average, better performance and capabilities, especially when compared to the amateur group, and all groups showed an H/Q ratio &gt; 60%. (4) Conclusions: We conclude that there are not many differences in physical condition between the three competitive levels of futsal, despite the unequal sporting demands between them. However, the elite group has greater power and muscle strength, and both groups showed a high probability of lower limb muscle injury at this stage of the sporting season, alerting sports training professionals to the importance of individualized analysis of physical condition and performance capacity.

This article provides a comprehensive analysis of the global gas and liquefied natural gas (LNG) markets. The article begins by discussing the increasing demand for gas and LNG, particularly in Asia, as countries aim to transition to cleaner sources of energy. It explores how market volatility has led to energy security interventions and lasting economic and emissions impacts. It then explores the global supply and demand dynamics, highlighting the structural change expected in the market and the competition between Europe and Asia for limited new LNG supply. The article also focuses on Europe's increased flexibility and dependence on LNG imports, which have risen by 60% to 121 million tonnes, offsetting lower Russian pipeline imports. Furthermore, the article delves into global supply and demand dynamics, how the market is expected to remain tight, and how record gas and LNG prices have led to demand reductions. Additionally, it analyzes the future outlook and investment needs, highlighting the continued uptake of gas in heavy-duty transport and the need for further investment to avoid a supply-demand gap. The article concludes with an analysis of the implications for the future of the global gas and LNG markets.

Starch is a widespread natural polymer used in healthcare applications due to its low cost and antibacterial properties. The use of starch in its many forms and its sometimes combination with metallic nanoparticles have all contributed to the advancement of biomaterials. However, few studies have been conducted on biocomposites composed of jackfruit starch and silver nanopar-ticles (AgNPs). As a result, this research aims to study the physicochemical, morphological, and cytotoxic features of a Brazilian jackfruit (Artocarpus heterophyllus) starch-based scaffold loaded with AgNPs. Gelatinization and chemical reduction were used to synthesize the scaffold and AgNPs, respectively. X-ray diffraction (XRD), differential scanning calorimetry (DSC), scanning electron microscopy coupled with energy-dispersive spectroscopy (SEM-EDS), and Fourier transform infrared spectroscopy (FTIR) were utilized to explore the properties. The findings supported the development of anisotropic, stable, monodispersed AgNPs. The presence of AgNPs in the scaffold matrix was revealed by XRD and SEM-EDS. AgNPs were found to modify the crystallinity, roughness, and thermal stability of the scaffold while leaving its chemical and physical characteristics unchanged. Finally, the scaffolds did not show adverse effects on the L929 cells.

2019-n-CoV is the seventh coronavirus known to infect humans and cause serious illness, and due to its lethality there was a worldwide mobilization for the development of new drugs and new vaccines for Covid-19. Therefore, the present work aims to carry out a virtual screening of terpenes with potential anti SARS-CoV-2 activity. To perform the ligand-based virtual, a model was constructed regarding the compounds which already showed inhibitory activity of the SARS-CoV-2. The test series corresponded to terpenes isolated in the Fabaceae Family. The compounds that were most likely to activity were subjected to Molecular Docking and the best poses obtained were subjected to Molecular Dynamics (MD) simulations carried. The molecules under study were submitted to in vitro evaluation to assess inhibitory activity of compounds against SARS-CoV-2 in a phenotypic screening model of the virus. The compounds selected by in silico screening corresponded to triterpenoids from the lupane series. In the in vitro test, both demonstrated activity against the SARS-CoV-2 virus. The virtual screening performed managed to identify the compounds with the highest probability of activity, as well as the most stable compounds, and the method used was validated by the in vitro study carried out.

The main objective of this paper is to find a close link between the adaptive level of significance, presented here, and the sample size. We, statisticians, know of the inconsistency, or paradox, in the current classical tests of significance that are based on p-value statistics that is compared to the canonical significance levels (10%, 5% and 1%): "Raise the sample to reject the null hypothesis" is the recommendation of some ill-advised scientists! This paper will show that it is possible to eliminate this problem of significance tests. The Bayesian Lindley's paradox – "increase the sample to accept the hypothesis" – also disappears. Obviously, we present here only the beginning of a possible prominent research. The intention is to extend its use to more complex applications such as survival analysis, reliability tests and other areas. The main tools used here are the Bayes Factor and the extended Neyman-Pearson Lemma.