The urgent global health challenge posed by methicillin-resistant Staphylococcus aureus (MRSA) infections demands effective solutions. Antimicrobial peptides (AMPs) represent promising tools of research of new antibacterial agents and LyeTx I mn∆K, a short synthetic peptide based on the Lycosa erythrognatha spider venom, is a good representative. This study focused on analyzing some antimicrobial activities of LyeTx I mn∆K, including minimum inhibitory and bactericidal concentrations, synergy and resensitization assays, lysis activity, the effect on biofilm, and the bacterial death curve in MRSA. Additionally, its characterization was conducted through isothermal titration calorimetry, dynamic light scattering, calcein release, and finally, efficacy in a mice wound model. The peptide demonstrating remarkable efficacy against planktonic cells and biofilms of MRSA, outperforms vancomycin in terms of rapid bactericidal action and anti-biofilm effects. The mechanism involves significant membrane damage. Interactions with bacterial model membranes, including those with lysylphosphatidylglycerol (LysylPOPG) modifications, highlight versatility and selectivity of this compound. Also, the peptide has the ability to sensitize resistant bacteria to conventional antibiotics, showing potential for combinatory therapy. Furthermore, using an in vivo model, was showed that a formulated gel containing the peptide proved superior to vancomycin in treating MRSA-induced wound in mice. Together the results highlight LyeTx I mnΔK as a promising prototype for the development of effective therapeutic strategies against superficial MRSA infections.

Machine learning (ML) has a large capacity to learn and analyze a large volume of data. This study aimed to train different algorithms to discriminate between healthy and pathologic corneal images by evaluating digitally processed spectral-domain optical coherence tomography (SD-OCT) corneal images. A set of 22 SD-OCT images belonging to a random set of corneal pathologies was compared to 71 healthy corneas (control group). A binary classification method was applied; three approaches of ML were used. Once all images were analyzed, representative areas from every digital image were also processed and analyzed for a statistical feature comparison between healthy and pathologic corneas. The best performance was obtained from transfer learning - support vector machine (TL-SVM) (AUROC = 0.94, SPE 88%, SEN 100%) and transfer learning – random forest (TL- RF) method (AUROC = 0.92, SPE 84%, SEN 100%), followed by convolutional neural network (CNN) (AUROC = 0.84, SPE 77%, SEN 91%) and random forest (AUROC = 0.77, SPE 60%, SEN 95%). The highest diagnostic accuracy in classifying corneal images was achieved with the TL-SVM and the TL-RF models. In image classification, CNN was a strong predictor. This pilot experimental study developed a systematic mechanized system to discern pathologic from healthy corneas.

Dysregulation of the arsenal of cells, growth factors, cytokines, proteases, and proteins involved in wound healing (WH), could delay the healing process. Plants and plant-derived molecules (PDMs) have been used as medicines for skin wounds. This study aimed to select and evaluate the pro-healing capacity of PMDs. Thirty-three PDMs and 10 therapeutic targets (TTs) were chosen for molecular docking and PDMs: aristolochic acid (AA), α-copaene, selinenes, β-caryophyllene (BC), and BCoxide, and TTs: metalloproteinase (MMP) 3, MMP13, and tumor necrosis factor (TNF α) for molecular dynamics. The bests inhibitor was AA, but because of its toxicity, BC and BCoxide were chosen for evaluation in HaCat cells and BALB/c mice excisional model. Both compounds were not toxic, and higher percentages of lesion area closure (LAC) were induced by BC treatment (p<0.05). All mice healed; however, an initial delay of LAC was induced by 0.05, 0.1% BCoxide, 0.1% BC, and allantoin. At the end of treatment, lower numbers of mast cells, level of cellular infiltrates (except 1% BCoxide and 0.05, 0.5%BC), epidermal thickness tendency (except 0.1, 0.5% BCoxide), and higher values of SC-thickness, and collagen fibers only by 0.5% BC treatment compared with untreated control (p<0.05) were observed. Our results show that BC is a promising multitarget candidate for wound healing treatment and optimization campaigns.

The effects of climate change health impacts on urban health care systems and vulnerable populations are a researched topic with foundations on urban risk management, urban health methodologies, and sustainable urbanization. As climate change is a dynamic and transformative global issue the gap between adaptation and mitigation efforts and urban planning relies, among other things, in the limitations of previous studies of risk management structures tailored to the existing strategy to calculate the uncertainties and predict their influence on urban systems and subsystems. Moreover, as climate and health is a well-researched issue, it is also complex as the methodologies and strategic approach to minimize health risks of climate change is intrinsically contingent to risk methodologies and policy-making processes that are efficient with support of knowledge-based information. This paper emphasis the need for focusing on urban health risk management methods that serves to identify potential opportunities, and then manage and take action to prevent adverse health effects. It also emphasizes the probability of events and their consequences, which are measurable both qualitatively and quantitatively.

Advances in communication technologies have made the interaction of small devices, such as smartphones, wearables, and sensors, scattered on the Internet, bringing a whole new set of complex applications with ever greater task processing needs. These Internet of Things (IoT) devices run on batteries with strict energy restrictions. They tend to offload task processing to remote servers, usually to Cloud Computing (CC) in datacenters geographically located away from the IoT device. In such a context, this work proposes a dynamic cost model to minimize energy consumption and task processing time for IoT scenarios in Mobile Edge Computing environments. Our approach allows for a detailed cost model, with an algorithm called TEMS that considers energy, time consumed during processing, the cost of data transmission, and energy in idle devices. The task scheduling chooses among Cloud or Mobile Edge Computing (MEC) server or local IoT devices to better execution time with lower cost. The simulated environment evaluation saved up to 51.6% energy consumption and improved task completion time up to 86.6%.

Cacao is an understory plant cultivated under full-sun monocultures to multi-strata agroforestry systems, where cocoa trees are planted together with fruit, timber, firewood, and leguminous trees, or grown within thinned native forests. Under agroforestry systems of cultivation, cacao is subjected to excess shade due to high density of shade trees, and overgrown or unmanaged pruning of shade trees. Cacao is tolerant to shade, and the maximum photosynthetic rate occurs around irradiance of 400 μmol m⁻² s⁻¹ but excess shade reduces the irradiance further which is detrimental to photosynthesis and growth functions. Intra-specific variation is known to exist in cacao for the required saturation irradiance. A greenhouse study was implemented with 58 cacao genotypes selected from four geographically diverse groups: (i) wild cacao from river basins of the Peruvian Amazon, (PWC), (ii) Peruvian farmers’ collection (PFC), (iii) Brazilian cacao collection (BCC) and (iv) national and international cacao collections (NIC). All the cacao genotypes were subjected to 50% and 80% shade where photosynthetic photon flux density (PPFD) was 1000 and 400 μmol m^-2 ּs^-1 respectively. Intra-specific variations were observed for growth, physiological and nutritional traits, and tolerance to shade. Cacao genotypes tolerant to shade were: UNG-77 and UGU-130 from PWC; ICT-2173, ICT-2142, ICT-2172, ICT-1506, ICT-1087, and ICT-2171 from the PFC; PH-21, CA-14, PH-990 and PH-144 from BCC; and ICS-1, ICS-39, UF-613 and POUND-12 from NIC. Genotypes that tolerate excess shade might be useful plant types to maintain productivity and sustainability in agroforestry systems of cacao management.

Drowsiness detection is an important task in road safety and other areas that require sustained attention. In this article, an approach to detect drowsiness in drivers is presented, focusing on the eye region, since eye fatigue is one of the first symptoms of drowsiness. The method used for the extraction of the eye region is Mediapipe, chosen for its high accuracy and robustness. Three neural networks were analyzed based on: InceptionV3, VGG16 and ResNet50V2 that implement deep learning. The database used is NITYMED, which contains videos of drivers with different levels of drowsiness. The three networks were evaluated in terms of accuracy, precision and recall in detecting drowsiness in the eye region. The results of the study show that all three convolutional neural networks have high accuracy in detecting drowsiness in the eye region. In particular, the Resnet50V2 network achieved the highest accuracy, with a rate of 99.71% on average. For better visualization of the data, the Grad-CAM technique is used, with which we get a better understanding of the performance of the algorithms in the classification process.

This study addresses the problem of accurately predicting azimuth and elevation angles of signals impinging on an antenna array employing Machine Learning (ML). Using the information obtained at a receiving system when a transmitter’s signal hits it, a Decision Tree (DT) model is trained to estimate azimuth and elevation angles simultaneously. Simulation results demonstrate the robustness of the proposed DT-based method, showcasing its ability to predict the Direction of Arrival (DOA) in diverse conditions beyond the ones present in the training dataset, i.e., the results display the model’s generalization capability. Additionally, the comparative analysis reveals that DT-based DOA estimation outperforms the state-of-the-art MUltiple SIgnal Classification (MUSIC) algorithm, establishing DTs as competitive alternatives for DOA estimation in signal reception systems.

In the age of social media, images come from unreliable sources that may change their content to fit a narrative. Automated detection of forged images is a complex task, especially considering recent technological advances in image manipulation software. However, in the existing literature, it is possible to identify two general approaches adopted by detection methods, active and passive. Active techniques preemptively act on an image by inserting structures before any manipulation is made that can verify its authenticity. In contrast, passive methods analyze the content of an image in search of traces of manipulation. In this way, this research proposes a novel approach to image manipulation detection, combining two passive methods through neural networks, creating a generalist approach capable of detecting with greater accuracy than the methods that compose it. Furthermore, this work used a combination of four datasets available in the literature for training and evaluation. After training, the merged approach obtained an accuracy of 89.59% in the set of validation images, significantly higher than the model trained with only unaltered images, which obtained 78.64%, and the two other models trained using images with a feature selection method applied to enhance inconsistencies that obtained 68.02% for Error-Level Analysis images and 50.70% for the method using Discrete Wavelet Transform. In addition to the performance improvement, the proposed approach’s accuracy variation was lower than the other models.

This work presents an innovative application of optimal control theory to the strategic scheduling of battery storage in the day-ahead electricity market, with a focus on enhancing profitability while factoring in battery degradation. The study incorporates in the optimisation framework the cost of battery capacity degradation, the effects of capacity degradation and internal resistance degradation into dynamics. We employ a continuous-time representation of the dynamics, in contrast with many other studies that use a discrete-time approximation with rather coarse intervals. We adopt an equivalent circuit model coupled with empirical degradation parameters to simulate a battery cell’s behaviour and degradation mechanisms with good support from experimental data. Utilising direct collocation methods with mesh refinement allows for precise numerical solutions to the complex, nonlinear dynamics involved. Through a detailed case study of Belgium’s day-ahead electricity market, we determine the optimal charging and discharging schedules under varying objectives: maximizing net revenues, profits considering capacity degradation, and profits considering both capacity degradation and internal resistance increase due to degradation. The results demonstrate the viability of our approach and underscore the significance of integrating degradation costs into the market strategy for battery operators, alongside its effects on the battery’s dynamic behaviour. Our methodology extends previous work by offering a more comprehensive model that empirically captures the intricacies of battery degradation, including a fine and adaptive time domain representation, focusing on the day-ahead market, and utilising accurate direct methods for optimal control. The paper concludes with insights into the potential of optimal control applications in energy markets and suggestions for future research avenues.

This research program investigated the effects of layer thickness (50 and 100 microns) on the microstructure and mechanical properties of electron beam powder bed fusion (EBPBF) additive manufacturing of Inconel 625 alloy. The as-built 50 and 100 micron layer thickness components were also heat treated at temperatures above 1100 oC, which produced a recrystallized grain structure containing annealing twins in the 50 micron layer thickness components, and a duplex grain structure consisting of islands of very small equiaxed grains dispersed in a recrystallized, large-grain structure containing annealing twins. The heat treated component microstructures and mechanical properties were compared with the as-built components in both the build direction (vertical) and perpendicular (horizontal) to the build direction. Vickers microindentation hardness (HV) values for the vertical and horizontal geometries averaged 227 and 220 for the as-built 50 and 100 micron layer components, and 185 and 282 for the corresponding heat treated components. The yield stress values were 387 MPa and 365 MPa for the as-built layer horizontal and vertical 50 micron layer geometries, and 330 MPa and 340 MPa for the as-built 100 micron layer components. For the heat treated 50 micron components, the yield stress values were 340 and 321 MPa for the horizontal and vertical geometries, and 581 and 489 MPa for the 100 micron layer components, respectively. The elongation for the 100 micron layer as-built horizontal components was 28% in contrast to 65% for the corresponding 100 micron heat treated layer components, an increase of 132% for the duplex grain structure. However, the coarse grains containing annealing twins and the equiaxed small grain islands in the duplex structure for the heat treated components contained continuous carbides in the grain boundaries, and this may indicate sensitization and a reduction in corrosion resistance. These findings point to the potential mechanical property advantage for heat treatment of Inconel 625 alloy 100 micron layer thickness components fabricated by EBPBF.

Primary carcinomas of the lung are vastly represented by the conventional types of adenocarcinomas or squamous cell carcinomas. However, there are other types of non-small cell carcinomas that although uncommon represent a meaningful group that often pose a problem not only in diagnosis but also in classification. Spindle and giant cell carcinomas although uncommon primary lung carcinomas are well known to occur. Important to highlight is that current criteria are rather ambiguous and likely not up to date, which renders the classification of these tumors somewhat more obscure. In addition, with the daily use of immunohistochemical stains, the classification of these tumors may also pose a different problem in the proper allocation of these tumors. Proper classification is highly important in the selection process that takes place using such material for molecular analysis. Current molecular characteristics of these tumors is limited and lacks more in-depth studies and analysis that can provide specific targets for the treatment of patients with these tumors. The current review attempts to highlight the shortcomings in the current classification and definitions of these neoplasms as well as the more current view regarding these tumors when the use of immunohistochemical stains is employed.

Despite the advancements in evidence-based medicine, many hospitals still maintain high rates of patients undergoing prolonged preoperative fasting. The goal of this study is to determine the prevalence of prolonged fasting time among patients undergoing elective surgeries at a Brazilian university hospital and its associations with clinical and sociodemographic variables. This cross-sectional study was conducted between May and November 2019 and included patients of all ages undergoing elective surgeries. Out of the 293 patients analyzed, 64.2% were male, with ages ranging from 1 to 85 years, and 93.9% were classified as ASA I or II. The prevalence of preoperative fasting exceeding 8 hours was 89.4%. An average fasting time exceeding 11 hours was observed across all age groups. Patients who underwent procedures in the afternoon had an average fasting time that was 16% longer than those in the morning period (13.84 vs. 11.92, p<0.001). Surgery time (r=0.134, p<0.03) and anesthesia times (r=0.121, p<0.04) demonstrated a weak correlation with fasting time. Despite the international consensus on preoperative fasting time, our study demonstrated low adherence to current recommendations. Therefore, healthcare professionals should ensure the comprehension of fasting guidelines, and further studies should aim to identify effective solutions to mitigate prolonged fasting.

High-throughput screening technologies continues to produce large amounts of multiomics data from different populations and cell types for various diseases, such as cancer. However, analysis of such data encounters difficulties due to cancer heterogeneity, further exacerbated by human biological complexity and genomic variability. There is a need to redefine the drug discovery development pipeline, bringing an Artificial Intelligence (AI)-powered informational view that integrates relevant biological information and explores new ways to develop effective anticancer approaches. Here, we show SynPred, an interdisciplinary approach that leverages specifically designed ensembles of AI-algorithms, links omics and biophysical traits to predict synergistic anticancer drug synergy. SynPred exhibits state-of-the-art performance metrics: accuracy – 0.85, precision – 0.77, recall – 0.75, AUROC – 0.82, and F1-score - 0.76 in an independent test set. Moreover, data interpretability was achieved by deploying the most current and robust feature importance approaches. A simple web-based application available online at http://www.moreiralab.com/resources/synpred/ was constructed to predict synergistic anticancer drug combinations requiring only the upload of the two drug SMILES to be tested, allowing easy access by non-expert researchers.

The objective of this study was to identify key transcription factors involved in lipid metabolism and immune response related to the differentially expressed genes (DEG) from the liver samples of 35 pig model for metabolic diseases fed diets containing either 1.5 or 3.0% soybean oil (SOY1.5 or SOY3.0). A total of 281 DEG between SOY1.5 and SOY3.0 diets (log2fold-change ≥ 1 or ≤ −1; FDR-corrected p-value &lt; 0.1) were identified, in which 129 were down-regulated and 152 were up-regulated in SOY1.5 group. The functional annotation analysis detected transcription factors linked to lipid homeostasis and immune response, such as RXRA, EGFR, and SREBP2 precursor. These findings demonstrated that key transcription factors related to lipid metabolism could be modulated by dietary inclusion of soybean oil. It could contribute to nutrigenomics research field that aims to elucidate dietary interventions in animal and human health, as well as to drive the food technology and science.

Biologic scaffolds have become an attractive approach for repairing the infarcted myocardium and have been shown to facilitate constructive remodeling in injured tissues. This study aimed to investigate the possible utilization of bacterial cellulose membrane patch containing cocultured cells to limit the myocardium's post-infarction pathology. Myocardial infarction was induced by ligating the left anterior descending coronary artery in 45 Wistar rats, and patches with or without cells were attached to the hearts. After one week, the animals underwent echocardiography for assessing ejection fraction and left ventricular end-diastolic and end-systolic volumes. Following the patch formation, cocultured cells retained viability of >90% over 14 days in culture. The patch was applied to the myocardial surface of the infarcted area after staying 14 days in culture. Interestingly, the bacterial cellulose membrane without cellular treatment showed higher preservation of cardiac dimensions; however, we did not observe improvement in the left ventricular ejection fraction of this group compared to coculture treated membranes. Our results demonstrated an important role for bacterial cellulose in supporting cells known to produce cardioprotective soluble factors and may thus provide effective future therapeutic outcomes for patients suffering from ischemic heart disease.

The aim of this study was to identify the differentially expressed genes (DEG) from the skeletal muscle and liver samples of animal model for metabolic diseases in human. To perform the study, the fatty acid (FA) profile and RNA sequencing (RNA-Seq) data of 35 samples of liver tissue (SOY1.5, n=17 and SOY3.0, n=18) and 36 samples of skeletal muscle (SOY1.5, n=18 and SOY3.0, n=18) of Large White pigs were analyzed. The FA profile of the tissues was modified by the diet, mainly those related to monounsaturated (MUFA) and polyunsaturated (PUFA) FA. The skeletal muscle transcriptome analysis revealed 45 DEG (FDR 10%), and the functional enrichment analysis identified network maps related to inflammation, immune process, and pathways associated with the oxidative stress, type 2 diabetes and metabolic dysfunction. For the liver tissue, the transcriptome profile analysis revealed 281 DEG, which participate in network maps related to neurodegenerative diseases. With this nutrigenomics study, we verified that different levels of soybean oil in the pig diet, an animal model for metabolic diseases in humans, affected the transcriptome profile of skeletal muscle and liver tissue. These findings may help to better understand the biological mechanisms that can be modulated by the diet.

This manuscript presents the result of utilizing cellulose as a template to prepare na-nosized WO3-NiWO4 and its application as co-catalysts in Pt/WO3-C and Pt/WO3-NiWO4-C for ethanol and glycerol electro-oxidation. Microcrystalline cellulose was hydrolyzed with phosphotungstic acid (H3PW12O40) to prepare the nanosized template of crystalline cellulose. Next, the template was impregnated with Ni(NO3)2, rendering a precursor mate-rial that is subsequently air-calcinated, removing the carbon-template material to obtain the nanometric WO3 and NiWO4. Elemental analysis confirmed the coexistence of nickel and tungsten, whereas the thermal analysis evidenced the high thermal stability of these materials. The X-ray diffractograms displayed crystal facets of WO3 and, when added Ni, of NiWO4. The transmission electron micrographs corroborated the formation of na-nosized particles with average particle sizes close to 50 nm. Finally, to apply this material, Pt/WO3-C and Pt/WO3-NiWO4-C were prepared and used in ethanol and glycerol electro-oxidation in alkaline medium, observing a promotional effect of the oxide and tungstate by reducing the onset potential and increasing the current density. These materials show great potential to produce clean electricity or green hydrogen contributing to energetic transition.

We present an open-source Star Tracker (ST) for Attitude Determination. Our implementation makes use of open source software of common usage in astronomy running on a Raspberry Pi 2 platform. The developed platform is open and available for parties interested in further development. Evaluation of the system showed that the ST is suitable for Cubesats of 2U or larger. The ST platform is capable of solving the Lost-In-Space (LIS) problem. Currently, the average accuracy reached of the algorithm is close to 5 seconds of arc with an average processing time of 75 seconds. However, a average accuracy of about 3 minutes of arc can be reached with 35 seconds in average processing time. We also describe the evaluation procedure, the found conclusions of this procedure, in particular the section of the algorithm where most of the processing time is spent and other possible source of errors not included in this study.

Studies on the influence of dietary components and their effects are fundamental for nutrigenomics, or the study of how nutrients can be cellular sensors, how they affect biological processes and gene expression in different tissues. Lipids are an important source of fatty acids (FA) and energy and are fundamental to biological processes and influence the regulation of transcription. Pigs are excellent model to study nutrigenomics, particularly lipid metabolism because the deposition and composition of FA in their tissues reflect the composition of FA in their diet. Recent studies show that FA supplementation is important in production systems, such as growing and finishing pigs, as it can improve the energy value of the feed, help reduce costs, improve animal welfare, and influence the nutritional value of the meat. Studies show that oleic (OA), linoleic (LA), docosahexaenoic (DHA), and eicosapentaenoic (EPA) acids are associated with the regulation of transcription in tissues such as muscle, liver, adipose tissue, and brain. Other studies indicate that EPA and DHA are associated with changes in specific signaling pathways, altering gene expression and biophysical properties of membranes. This review, therefore, focuses on the current knowledge of the effects of dietary FA on production traits and gene expression.

B chromosomes (B) are supernumerary elements found in many taxonomic groups. Most B chromosomes are rich in heterochromatin and composed of abundant repetitive sequences, especially transposable elements (TEs). Bs origin is generally linked to the A chromosome complement (A). The first report of a B chromosome in African cichlids was on Astatotilapia latifasciata, which can harbor 0, 1 or 2 B chromosomes. Classical cytogenetics studies found high TE content on the species B chromosome. In this study, we aim to understand TE composition and expression on A. latifasciata genome and its relation to the B chromosome. We use bioinformatics analysis to explore TEs genome organization and also their composition on the B chromosome. Bioinformatics findings were validated by fluorescent in situ hybridization (FISH) and real-time PCR (qPCR). A. latifasciata has a TE content similar to other cichlid fishes and several expanded elements on its B chromosome. With RNA sequencing data (RNA-seq) we showed that all major TE classes are transcribed in brain, muscle and male/female gonads. The evaluation of TE expression between B- and B+ individuals showed that few elements have differential expression among groups and expanded B elements were not highly transcribed. Putative silencing mechanisms may the acting on the B chromosome of A. latifasciata to prevent adverse consequences of repeat transcription and mobilization in the genome.

In this work, we present some results related with the issue of the Loop Quantum Black Holes (LQBH) thermodynamics by the use of the tunneling radiation formalism. The information loss paradox is also discussed in this context, where we have considered the influence of back reaction effects.

Gadolinium-based contrast agents (GBCA) are complexes, highly stable in vivo, used in Magnetic Resonance Imaging (MRI), administered in patients and then eliminated via renal, passing through wastewater treatment plants (WWTP) before being discarded in the receiving medium, without apparent removal. In this study, it was studied if different exposure periods to several environmental parameters (solar radiation, different salinities, temperatures and pH) will influence the stability of these complexes, namely, the Gd-DOTA. Gd-DOTA solutions were processed in a seaFAST-pico saline matrix pre-concentration and elimination system and Gd concentrations were determined by ICP-MS. Results showed that the complex remained stable in fresh, brackish and saline water environments, even when exposed to extreme temperatures (40ºC) or slightly acidic to basic conditions (6-10), for an exposure period of 96h. A small increase in the free Gd concentration was observed after 18 days when exposed to pH&lt;4, in all tested salinities (0, 18 and 36 PSU), with a degradation increase of up to 29%, after 5 weeks of exposure in freshwater. When exposed to direct solar radiation a low Gd-DOTA degradation (4%) was observed after 24h at salinity 18 PSU and remained constant until the end of the exposure period (96h), while the remaining salinities showed negligible values.

Let $\mathcal{N}$ be an arbitrary class of matroids, closed under isomorphism. For $k$ a positive integer, we say that $M \in \mathcal{N}$ is \emph{$k$-minor-irreducible} if $M$ has no minor $N \in \mathcal{N}$ such that $1\leq\left|E\left(M\right)\right|-\left|E\left(N\right)\right|\leq k $. Tutte's Wheels and Whirls Theorem establish that, up to isomorphism, there are only two families of 1-minor-irreducible matroids in the class of 3-connected matroids. More recently, Lemos classified the 3-minor-irreducibles with at least 14 elements in the class of triangle-free 3-connected matroids. Here we prove a local characterization for the 2-minor-irreducible matroids with at least 11 elements in the class of triangle-free 3-connected matroids. This local characterization is used to establish two new families of 2-minor-irreducible matroids in this class.

The nursing process in clinical practice can be assessed using standardized language systems. The purpose is to find evidence on the effectiveness of the nursing process with standardized terminology using NANDA International, Nursing Interventions Classification, and Nursing Outcome Classification improving diag-nostic accuracy, nursing interventions, health outcomes, and people’s satisfaction. A systematic review was carried out in Medline and PreMedline, Embase, The Cochrane Library, CINAHL, SCI-EXPANDED, SSCI and Scielo and LILACS including randomized clinical trials, quasi-experimental, cohort and case-control studies. Selection and critical appraisal were conducted by two independent reviewers. The certainty of the evidence was assessed with Grading of Recommendations Assessment, Development and Evaluation Methodology. 17 studies were included with variability in the level and certainty of evidence. According to outcomes, 6 evaluated improvements in diagnostic accuracy and 11 evaluated improvements in individual health outcomes. No studies evaluated improvements in intervention efficacy or population satisfaction. There is a need to increase studies with rigorous methodologies that address diagnostic accuracy and indi-viduals’ health outcomes using NANDA International, Nursing Interventions Classification, and Nursing Outcome Classification; as well as implementing studies that evaluate the use of these terminologies for improvements in the efficacy of nurses' interventions and population satisfaction with the nursing process.

Background/Aim: Stool gluten immunogenic peptides (GIP) determination is now considered a valuable tool for detecting dietary lapses in treated celiac disease (CeD) patients. Our study aims to explore the diagnostic performance of a qualitative lateral flow immunoassay point-of-care test (LFIA/PoCT) compared with a qualitative enzyme-linked immunosorbent assay (ELISA) for detection of stool GIP. Methods: The study is a post hoc analysis of stool samples collected in the real-life conditions from a cohort of gluten-free diet-treated CeD patients. Stool GIP was measured in µg/g of stool using an ELISA kit (iVYLISA GIP S®, Biomedal SL). For the qualitative evaluation of stool GIP, a LFIA/PoCT test (GlutenDetect®; Biomedal S.L) was employed, which reported results as positive or negative. The LFIA/PoCT performance was evaluated against ELISA, considered as the gold standard. GIP concentrations

OBJETIVES: During the COVID-19 pandemic, the risk of collapse of the health system created great difficulties. We will demonstrate that Intermediate Respiratory Care Units (IRCU) provide adequate management of patients with non-invasive respiratory support, which is particularly important in patients with SARS-CoV-2 pneumonia. METHODS: A prospective observational study of patients with COVID-19 admitted to the ICU of a tertiary hospital. Sociodemographic data, comorbidities, pharmacological, respiratory support, laboratory and blood gas variables were collected. The overall cost of the unit was subsequently analyzed. RESULTS: 991 patients were admitted, 56 to the IRCU (of the 81 a critical care unit). Mean age was 65 years (SD 12.8), Barthel Index 75 (SD 8.3), Charlson 3.1 (SD 2.2), HTN 27%, COPD 89% and obesity 24%. Significant relationship (p <0.05) with higher mortality of the following: fever greater than or equal to 39oC [OR 5.6; 95% CI (1.2-2.7); p = 0.020], protocolized pharmacological treatment [OR 0.3; 95% CI (0.1-0.9); p = 0.023] and IOI [OR 3.7; 95% CI (1.1-12.3); p = 0.025]. NIMV showed less of a negative impact [OR 1.8; 95% CI (0.4-8.4); p = 0.423] than IOI. The total cost of the IRCUs amounted to €66,233. The cost per day of stay in the IRCU was €164 per patient. The total cost avoided was €214,865. CONCLUSION: The pandemic has highlighted the importance of IRCUs in facilitating the management of a high patient volume. The treatment carried out in IRCUs is effective and efficient, reducing both admissions to and stays in the ICU.

The primary sources of particulate matter are linked to human activity. Certain particulate emissions, particularly those of a finer nature, can significantly impact human health, making them one of the most concerning pollutants. Ultrafine particles (UFP), which have a diameter of less than 100 nm, are of particular concern due to their impact on human health and the difficulty in controlling them. The concentration of ultrafine particles (UFP) in the workplace is a growing concern and is classified as an emerging risk. Workers may be exposed to UFP through inhalation, skin absorption, ingestion, or a combination of these routes. This study aims to determine the levels of UFP exposure among workers in environments with varying direct particle emission patterns. Measurements were conducted to compare the results with the levels recommended by the WHO. The study monitored industrial workplaces with direct particulate matter emissions, such as a carpentry and a bakery, as well as social sector sites without or almost without direct particle emissions, such as a school and a health clinic. One conclusion drawn from this study is that all tasks and occupations are susceptible to high levels of UFP, exceeding WHO recommended values in virtually all monitored environments. Therefore, monitoring and controlling UFP is crucial. Further in-depth studies on this subject are also necessary..

Head injury is among the most devastating types of injury, specifically called Traumatic Brain Injury (TBI). There is need to diminish the morbidity related with TBI and to improve the outcome of patients suffering TBI. Among the improvements on the treatment of TBI, neuroprotection is one of the upcoming improvements. Citicoline has been used in the management of brain ischemia related disorders, such as TBI. Citicoline has biochemical, pharmacological, and pharmacokinetic characteristics that make it a potentially useful neuroprotective drug for the management of TBI. A short review of these characteristics is included in this paper. Also, a narrative review of almost all the published or communicated studies performed with this drug in the management of patients with head injury is included. Based on the results obtained in these clinical studies, it is possible to conclude that citicoline was able to accelerate recovery of consciousness and to improve the outcome of this kind of patients, with an excellent safety profile. Thus, citicoline could have a potential role in the management of TBI.

The main objective of this study was to study the effect of occupational stress on turnover intentions, as well as whether this relationship is mediated by burnout levels and moderated by motivation. The sample of this study consisted of 603 participants, all employees of the Portuguese Tax and Customs Authority, which is part of the Ministry of Finance and belongs to the Direct State Administration. The results indicate that occupational stress (with managers, with career and remuneration and with work overload) has a positive and significant effect on turnover intentions and that this relationship is mediated by burnout. Motivation (intrinsic and identified) has a negative and significant effect on turnover intentions. Intrinsic motivation moderates the rela-tionship between occupational stress (with managers, with colleagues, with career and pay and with family problems) and turnover intentions. These results indicate that among the dimensions of occupational stress, the most critical are stress with managers, work overload and career and pay. These are factors that the Direct State Administration should be concerned about in trying to minimize their causes.

Rhizophora mangle L. is a well-known medicinal plant found in mangroves worldwide used to treatment diabetes. This study evaluated the chemical composition of the acetonic extract from Rhizophora mangle barks (AERM), by HPLC-PDA and FIA-ESI-IT-MS/MS and the effects on high-fat diet induced obesity in mice and its mechanism of action by gene expression of inflammatory markers (Pparg, Ppara, Srebf1, Cd36, Tnf, Ccl2, Lep, Il10, Il6, Fasn, 18s). High-fat diet fed mice during 12 weeks was used as model of obesity and associated alterations. The results were very satisfactory, the extract, rich in polyphenolic compounds, flavonoids and phenolic acids, displayed intense antioxidant activity in vitro (608 µmol Trolox/g), and showed excellent activity against non-alcoholic fatty liver disease (NAFLD) and reverse insulin resistance in a model of diet-induced obesity. We can registered a modulatory effect of AERM in liver PPAR-γ mRNA expression associated to an important inhibition of CD36 mRNA expression suggesting that AERM induces the down regulation of CD36 mRNA via PPAR-gamma inhibition. These results support the traditional knowledge about the use of R. mangle for the treatment of type 2 diabetes and reveal the potential of AERM for the treatment of NAFLD and management of obesity and comorbidities.

The Thermodynamic Formalism provides a rigorous mathematical framework to study quantitative and qualitative aspects of dynamical systems. At its core there is a variational principle and corresponding, in its simplest form, to the Maximum Entropy principle, used as a statistical inference procedure to represent, by specific probability measures (Gibbs measures), the collective behaviour of complex systems. This framework has found applications in different domains of scienThe Thermodynamic Formalism provides a rigorous mathematical framework to study quantitative and qualitative aspects of dynamical systems. At its core there is a variational principle and corresponding, in its simplest form, to the Maximum Entropy principle, used as a statistical inference procedure to represent, by specific probability measures (Gibbs measures), the collective behaviour of complex systems. This framework has found applications in different domains of science, in particular, has been fruitful and influential in neurosciences. In this article, we review how the Thermodynamic Formalism can be exploited in the field of theoretical neuroscience, as a conceptual and operational tool, to link the dynamics of interacting neurons and the statistics of action potentials from either experimental data or mathematical models. We comment on perspectives and open problems in theoretical neuroscience that could be addressed within this formalism.ce, in particular, has been fruitful and influential in neurosciences. In this article, we review how the Thermodynamic Formalism can be exploited in the field of theoretical neuroscience, as a conceptual and operational tool, to link the dynamics of interacting neurons and the statistics of action potentials from either experimental data or mathematical models. We comment on perspectives and open problems in theoretical neuroscience that could be addressed within this formalism.

Aging is a complex process associated with tissue degeneration and an increased risk of age-related diseases. This study aimed to evaluate the impact of Terasen®, a nutraceutical containing standardized extracts of Euterpe oleracea, Myrciaria dubia, and purified oil of Bixa orellana and Astrocaryum aculeatum on the lifespan of Caenorhabditis elegans, a widely used model organism for aging research. The findings demonstrated that Terasen® exhibited significant antioxidant activity and influenced the feeding behavior of C. elegans, leading to a reduced pharyngeal pumping rate and a decreased number of offspring produced by treated individuals. Notably, Terasen® also displayed a remarkable ability to extend the lifespan of C. elegans. These findings suggest that Terasen® may possess promising anti-aging effects in vivo, warranting further investigation.

Experimental recordings of the collective activity of interacting spiking neurons exhibit random behavior and memory effects, thus the stochastic process modeling the spiking activity is expected to show some degree of time irreversibility. We use the thermodynamic formalism to build a framework, in the context of spike train statistics, to quantify the degree of irreversibility of any parametric maximum entropy measure under arbitrary constraints, and provide an explicit formula for the information entropy production of the inferred Markov maximum entropy process. We provide examples to illustrate our results and discuss the importance of time irreversibility for modeling the spike train statistics.

: One of the challenges facing operations management is the design, choice and imple-mentation of action plans adapted to the magnitude of the deviations of the variables of an industrial process. Making conscious and quick decisions is crucial to achieving im-provements in productivity. This will be achieved if the organization's internal and external communication model is strategically designed, considering specific cultural factors and the symmetry or asymmetry required in the communication model. However, how do we organize ourselves and through what channels do we communicate within a production process to generate Big Data that combines data from technologies and the perception, comprehension and projection of experienced humans? Our purpose is to create an operations management model that facilitates the incorporation of technology, allows a prompt response to failures, and promotes the sustainability of processes, without losing sight of its alignment with the organizational strategy. The developed model was implemented in an operations management team, following the guidelines of an action researcher methodology. This resulted in the design of an operations management model and a detailed methodology for its implementation, achieving sig-nificant improvements in the metrics of the current process, making it a success story.

The main challenges in oil platforms are how to define optimal setpoints and decision-making for controlling variables due to many existing dynamical production uncertainties while conceding safe operation and minimizing discharge to sea and atmosphere without killing plantwide inventory. A novel scheduling model to optimize the whole essential units of an oil platform production gathering topside and subsea variables is disclosed. A proper topside and subsea scheduling model enables and creates harmony between optimal production, supply chain, costs, and market dynamics, satisfying demands, environmental and operations constraints leading to stability. The interest of the present research lies in determining the optimal topside and subsea operational settings and decision-making, establishing maximum E&P performance and production control setpoints while predicting and manipulating reservoir lifespan and its revitalization. This objective is attained through a novel multiperiod large-scale model for the planning and operational production scheduling and model predictive control (MPC) in oil platforms complying with sustainability, profitability, platform design capacities, and offloading of oil and gas to supply chains or to pipeline exportation. The present model details heat and mass transfer, PVT, flow profiles along a planning horizon and can be used to any oil platform since comprises all the essential unit operations for oil, gas, CO₂, H₂S and water. The model maximizes the total oil production over any planning horizon. The model is versatile, and decision-making can be either linear or nonlinear but rather a MILP or LP as best choice on optimizing large-scale systems. If the model is applied with auto rescheduling on site within variable hours or minutes, it becomes a real-time optimization schedule approach. Due to its high-velocity performance and robustness, a novel multi-objective function strategy, acting as an LP generic plantwide MPC with industrial scope to maximize production while controlling the process is presented, and as an example is here used to control slug flow to avoid equipment trips and inventory instability, at the same time production is maximized. The output from the decision-making was compared to actual plant data, and the results proved compliance to the design capacity with process safety and sustainability. Comparing to official Brazil's government data for oil, the case study showed superiority to the same size platforms, like FPSOs P-75 and MV32, e.g., more than 101.5% more capacity to produce oil in beginning of campaign after first oil, and 10.5% during campaign. The present work indicates that: 1) the production of millions of barrels is being delayed or left aside; 2) not scheduling production harms the environment and diminish process safety; 3) not scheduling production can create stochastic supply chain deliveries instead of organizing it by deterministic offloading days; 4) scheduling is essential to manipulate, revitalize and monitor reservoir's pressure and content under uncertainty; 5) the oil platform can be automatic optimized by a plantwide MPC reducing human activity/dependency; 6) scheduling gives more transparency to stakeholders and contractors by forecasting business data and capability, and can design, develop or enable new businesses.

Introduction: The HIV/AIDS pandemic in Spanish prison institutions has led to a series of necessary changes to adapt and provide an effective response. Materials and Methods: This research was conducted from an interpretative paradigm with a phenomenological perspective, interpreting the experiences of nursing professionals in Spanish prison institutions. Focus groups were conducted with professionals who worked before and after the emergence of antiretroviral treatments through the Microsoft Teams platform, using the ATLAS Ti v.9 software. The project received approval from the Ethics Committee of the UJI university. Results: Limited dissemination of news in the press regarding HIV/AIDS and Spanish prisons was observed. Changes occurred in organizational, material, and personnel resources, requiring adaptation among nursing professionals. The available resources and difficulties are described, along with patient perspectives, the role of professionals, their environment, and their experiences, both positive and negative. Discussion and Conclusions: There is minimal visibility of the problem, and a description is provided of an adaptation process to the environment compatible with the Callista Roy´s model.

The main objective of this investigation was to study the effect of organizational competencies development practices on turnover intentions and whether affective commitment explains this relationship. Another of the study's objectives was to test whether these relationships vary ac-cording to the generation to which the participant belongs. The study sample consisted of 2123 participants working in Portuguese organizations. The results indicate that organizational com-petencies development practices (training, individualized support, and functional rotation) nega-tively and significantly affect turnover intentions and that affective commitment mediates this re-lationship. However, these relationships vary according to the participant's generation. For Gen-eration Y and Generation X, this mediating effect is found in all dimensions of organizational competencies development practices. For the baby boomer generation, there is only a mediating effect of affective commitment in the relationship between individualized support and turnover intentions. These results indicate that human resources should consider the generation to which the participant belongs when implementing competencies development practices.

We synthesized a small series of five 3-[4-arylmethoxy)phenyl]propanoic acids using an easy and short step synthetic route. All compounds were tested in vitro against a set of four protein targets identified as key elements in diabetes: GPR40, aldose reductase (AKR1B1), PPARγ and GLUT-4. Compound 1 displayed an EC₅₀ value of 0.075 μM against GPR40 and was an AKR1B1 inhibitor, showing IC₅₀ = 7.4 μM. Compounds 2 and 3 behave as AKR1B1 inhibitors, GPR40 agonists and showed an increase of 2 to 4-times in the mRNA expression of PPARγ, as well as the GLUT-4 levels. Docking studies were conducted in order to explain the polypharmacological mode of action and the interaction binding mode of the most active compounds on these targets. Compounds 1-3 were tested in vivo at 100 mg/kg dose, being 2 and 3 orally actives, reducing glucose levels in a non insulin-dependent diabetes mellitus mice model. Compounds 2 and 3 showed robust in vitro and in vivo efficacy, and could be considered as promising multitarget antidiabetic drug candidates. This is the first report of a single molecule with these four polypharmacological target action.

The transcriptional response of human blood leukocytes to SARS-CoV-2 infection was investigated focusing on the differences between mild and severe cases and between age subgroups. Weighted gene co-expression network analysis and comparative gene expression analysis were used. Three transcriptional modules positively associated with the traits of interest and their respective high hierarchy genes were identified. Enrichment analyses showed that the yellow module, associated with severe cases and older patients, had an overrepresentation of genes involved in inflammatory and innate immune responses, and neutrophil activation. The magenta and black modules, associated with disease severity and younger patients, contained genes related to innate immunity and inflammation and genes that regulate those responses. Subnetworks for these modules were constructed using genes enriched for innate immunity, inflammation, immunoregulation and differentially expressed genes (severe vs. mild). Their analysis evidenced that immunoregulatory functions are more activated in the modules associated with younger patients, what may help to explain the better disease course and faster recovery observed in younger COVID-19 patients. Comparative gene expression analysis between severe and mild groups, followed by gene enrichment and normalized gene expression analyses, revelated a set of 23 potential biomarkers for COVID-19 severity, of which 13 are newly described.

Soarinho Alkaline Intrusion, southeastern Brazil, makes part of the Serra do Mar Igneous Province, and it is composed of alkali feldspar syenite, alkali feldspar trachyte, quartz syenite, and mon-zonite. Geochemical and geochronological analysis of the Soarinho were compared with data from its neighbors Rio Bonito and Tanguá. Zircon U-Pb Laser Ablation ages show that Soarinho is youngest than Rio Bonito and Tanguá. Ages obtained from the monzonite (60 ± 2 Ma), alkali feldspar syenite (58 ± 2 Ma), and quartz syenite (58 ± 2 Ma) are indistinguishable within error. Petrographic and geochemical data show a clear contrast among Soarinho, Rio Bonito, Tanguá, and Lu-Hf isotopic data for the three alkaline intrusions (all negative), point to some similarities in their sources. The data suggest an enriched mantle source for Soarinho; however, an older con-tinental crust contribution cannot be discarded.

The main objective of this review is to determine the main risks that agricultural workers are exposed to during pesticide application, which may have a harmful effect on their health and on public health. This systematic review was based on the PRISMA guidelines. A search for articles was conducted in the Medline/PubMed, ScienceDirect, and Web of Science databases. Fifteen articles were selected considering their assessment of agricultural workers' knowledge, perceptions, attitudes, practices, and behaviours, identifying the main risks and risk factors for disease associated with the unsafe handling of pesticides. The main risk factors identified were age, education, pesticide safety training, farming experience, and contact with other farmers/intermediaries resulting in pesticide access. The most frequent risk behaviours were: application of pesticides without personal protective equipment (PPE), incorrect disposal of empty packaging and waste, and undervaluation of label information, as well as other unsafe practices. A multidisciplinary and more effective training must be delivered in order to enhance pesticide safe usage. This will empower workers to adopt more conscious and safer behaviours while using pesticides.

Human keratinocytes and melanoma can stick together to form clusters after eight days in co-culture. As in dynamic system concepts, one can consider cluster formation as the system attractor, cell seeding as the initial condition, and density change over time as a path within the basin of attraction. Herein, Cellular Automata, which is a class of Agent-Based Models, and Boolean Networks are discrete modeling methods used in population dynamics such that running the dynamics of cellular automata backward reveals an underlying network in terms of basin of attraction, also known as global dynamics. Thus, we hypothesize that one can estimate the local dynamic of an agent-based model from the basin of attraction of a boolean network. Here, we propose an approach to estimating these agent-based model rules, which consists of comparing the density states within each state transition and reaching a consensus among state transitions belonging to a basin of attraction of a boolean network. The objectives of this study are: (1) to infer a boolean network from the co-culture growth curve; (2) to estimate the rules of agent-based models; and (3) to implement spatial dynamics simulations. The binarization of the growth curve shows high population density after four days; the estimated agent-based model rules were compatible with cell proliferation and migration in agreement with literature, so we had to propose individual rules for survival and death. Spatial dynamics shows that (1) keratinocytes exhibit a higher density in neighborhoods where melanoma is present; (2) the chance of keratinocyte migration increases until the fourth day, then decreases, and the probability of survival increases substantially after four days; and (3) cells with low proliferation capacity die and free space for those with high ones. Our approach suggests that the attractor state of cell co-culture is induced mainly by an increase in keratinocyte migration and survival. Our approach has the potential to offer valuable clues about microenvironmental interactions or configurations that drive population dynamics.

Agroecology, defined as the ecological science of food production is also as practical approach to design food production systems based on local concerted solutions that aim to promote synergy among the diversity of human and non human food systems elements. These two facets makes agroecology a good candidate for participatory research. Information technology should help using this information for the production of structured scientific knowledge. In this respect, there is a need for information technology that is adaptive to encompass the diversity of within and between systems and that provide benefit to farmers that feed it with data. We present MiCampoApp, a webapp that aims to join participatory research and certification in agroecology, with two roles, the farmer and the administrator. The idea to join participatory research for decision support with certification for market differentiation in single system is that much of the certification data harbors information for scientific research, and this incentivize data collection for the interest of the farmer and the community. The administrator create a model for data collection in order to solve a research question of interest for a communities or to produce traceability information to feed participatory guarantee system in a community. The farmer collects information using simple icons and produces traceability pages for research or certification purposes.

Augmented and Virtual Reality have been experiencing a rapidly growth in recent years, but there is not still a deep knowledge on their capabilities and where they could be explored. In that sense, this paper presents a study on the accuracy and repeatability of the Microsoft's HoloLens 2 (Augmented Reality device) and HTC Vive (Virtual Reality device) using an OptiTrack system as ground truth. For the HoloLens 2, the method used was hand tracking, while in HTC Vive, the object tracked was the system's hand controller. A series of tests in different scenarios and situations were performed to explore what could influence the measures. The HTC Vive obtained results in the millimetre scale, while the HoloLens 2 revealed not so accurate measures (around 2 centimetres). Although the difference can seem to be considerable, the fact that HoloLens 2 was tracking the user's hand and not an inherit controller made a huge impact. The results were considered a significant step for the on going project of developing a human-robot interface to program by demonstration an industrial robot using Extended Reality, which shows great potential to succeed based on this data.

This paper presents the robotic platform, PiBot, that has been developed and that is aimed at improving the teaching of Robotics with vision to secondary students. Its computational core is the Raspberry Pi 3 controller board, and the greatest novelty of this prototype is the support developed for the powerful camera mounted on board, the PiCamera. An open software infrastructure written in Python language was implemented so that the student may use this camera, or even a WebCam, as the main sensor of this robotic platform. Also, higher level commands have been provided to enhance the learning outcome for beginners. In addition, a PiBot 3D printable model and the counterpart for the Gazebo simulator were also developed and fully supported. They are publicly available so that students and educational centers that do not have the physical robot or can not afford the costs of these, can nevertheless practice and learn or teach Robotics using these open platforms: DIY-PiBot and/or simulated-PiBot.

The effective treatment for chronic wounds constitute one of the most common worldwide health care problem due to the presence of high levels of proteases, free radicals and exudates in the wound, which constantly activate the inflammatory system avoiding the tissue regeneration. In this study, we describe a multifunctional bioactive and resorbable membrane with in-built antioxidant agent for the continuous quenching of free radicals as well as to control inflammatory response helping to promote the wound healing process. To reach that goal synthesized statistical copolymers of N-vinylcaprolactam (V) and 2-hydroxyethyl methacrylate (H) have been conjugated with catechol bearing hydrocaffeic acid (HCA) molecules. The natural polyphenol (catechol) is the key molecule responsible for the mechanism of adhesion of mussels, and provides the functionalized polymer conjugate a continuous antioxidant response, antiinflammatory effect, UV screen and bioadhesion in the moist environment of the human body, all of them key features in the wound healing process. Therefore, these novel mussel-inspired materials have an enormous potential of application and can act very positively, favoring and promoting the healing effect in chronic wounds.

Access to health services compromises therapeutic adherence in patients with HTN, which is a risk factor for cardiovascular disease and premature death. The aim of the research is to determine the influence of access to health services on adherence to antihypertensive treatment during the COVID-19 pandemic. We included a cross-sectional analytical study. A survey was applied to 241 hypertensive patients at the Daniel Alcides Carrión Hospital, Callao-Peru. Data were analyzed using SPSS software. Absolute and relative frequencies were reported and the chi-square test was applied with a statistical significance level of p&lt;0.05. In addition, multiple logistic regression analysis was performed using the Stepwise method. An association was found between non-adherence to treatment and health expenses (ORa: 1.9 CI 95% 1.7-2.2), not receiving care due to lack of a doctor (ORa: 2.8 CI 95% 1.5-3.2), having difficulty with schedules (ORa: 3.7 CI 95% 2. 3-5.5), fear of receiving care at the hospital (ORa: 4.5 CI 95 % 2.7-6.8), trust in health personnel (ORa: 7.5 CI 95% 2.3-10.5) and considering that the physician does not have enough knowledge (ORa: 3.1 CI 95% 2.4-7.8). Therapeutic adherence was associated with physician availability for care, difficulty with schedules, fear of being seen in the hospital, trust in health personnel, and waiting time.

The ankle is a complex joint with a high injury incidence. Rehabilitation Robotics applied to the ankle is a very active research field. We present cable-driven reconfigurable robot kinematics and statics. We studied how the tendons pull mid-foot bones around the talocrural and subtalar axes. Likewise, we propose a hybrid serial-parallel mechanism analogous to the ankle. Then, using screw theory, we synthesized a cable-driven robot with the human ankle in the closed-loop kinematics. We incorporate a draw-wire sensor to measure the axes’ pose and compute the product of exponentials. We reconfigure the cables to balance the tension and pressure forces using the axis projection on the base and platform planes. Likewise, we also computed the workspace to show that the reconfigurable design fits several sizes. The data used is from anthropometry and statistics. Finally, we validated the robot’s statics with MuJoCo for various cable length groups corresponding to the axes’ range of motion. We suggested a platform adjusting system and an alignment method. The design is lightweight, and the cable-driven robot has advantages over rigid parallel robots, such as Stewart platforms. We will use compliant actuators.

A Robust Optimization framework with original concepts and fundamentals also admitting a fusion of ideals from relative regret models and static robust optimization, containing conservatism concepts is disclosed. The algorithm uses a fine-tune strategy to tune the model so the robustness and a target ideality can be mutually achieved with a specified risk. The framework comprises original concepts, a mathematical approach and an algorithm. The statistical treatment of the data with the original concepts from the framework make it able to make short, middle or long-term decision-making setting. The framework has high tractability since the algorithm forces the creation of a setting that makes a robust optimization with the specified risk. The framework can be applied in linear and nonlinear mathematical models since that the objective function is monotonic in the domain of the active convex region. Several examples are solved to best understand the framework and all results demonstrated high tractability and performance. There is a wide range of applications. Along all the text, there is a profound discussion about its philosophy, objective, original concepts, fields of application, statistical and probabilistic fundamentals.

We consider the maximum entropy Markov chain inference approach to characterize the collective statistics of neuronal spike trains, focusing on the statistical properties of the inferred model. We review large deviations techniques useful in this context to describe properties of accuracy and convergence in terms of sampling size. We use these results to study the statistical fluctuation of correlations, distinguishability and irreversibility of maximum entropy Markov chains. We illustrate these applications using simple examples where the large deviation rate function is explicitly obtained for maximum entropy models of relevance in this field.

As digitalization expands across all sectors, the economic toll of software defects on the U.S. economy reaches up to $2.41 trillion annually. High-profile incidents like the Boeing 787-Max 8 crash have shown the devastating potential of these defects, highlighting the critical importance of software testing within quality assurance frameworks. However, due to its complexity and resource intensity, the exhaustive nature of comprehensive testing often surpasses budget constraints. This research utilizes a machine learning (ML) model to enhance software testing decisions by pinpointing areas most susceptible to defects and optimizing scarce resource allocation. Previous studies have shown promising results using cost-sensitive training to refine ML models, improving predictive accuracy by reducing false negatives through addressing class imbalances in defect prediction datasets. This approach facilitates more targeted and effective testing efforts. Nevertheless, the generalizability of these models across different projects (cross-project) and programming languages (cross-language) remained untested. This study validates the model's applicability across diverse development environments by integrating various datasets from distinct projects into a unified, using a more interpretable ML approach. The results demonstrate that ML can support software testing decisions, enabling teams to identify up to seven times more defective modules with the same testing effort as a benchmark.

Cancer cells cannot proliferate and survive unless they obtain sufficient levels of the 20 proteinogenic amino acids (AAs). Unlike normal cells, cancer cells have genetic and metabolic alterations that may limit their capacity to obtain adequate levels of the 20 AAs under challenging metabolic environments. However, since normal diets provide all AAs at relatively constant levels and ratios, these potentially lethal genetic and metabolic defects are eventually harmless to cancer cells. If we temporarily replace the normal diet of cancer patients with artificial diets in which the levels of specific AAs are manipulated, cancer cells may be unable to proliferate and survive. This article reviews in vivo studies that have evaluated the antitumor activity of diets restricted or supplemented with the 20 proteinogenic AAs, individually and in combinations. It also reviews our recent studies that show that manipulating the levels of several AAs simultaneously can lead to marked survival improvements in mice with metastatic cancers.

Corynebacterium glutamicum is a Gram-positive bacterium found in soil where the condition changes demand plasticity of the regulatory interactions, which study at the global scale has been challenged by the lack of data integration. Here, we update the manually-curated C. glutamicum transcriptional regulatory network, now including protein-protein interactions having a direct effect on gene transcription. The network model with regulations supported by any experimental evidence increased by 557 interactions regarding the previous (2018) version. 73 interactions supported by directed experiments were also included in a second model. We included 545 sRNA-mediated regulations in a third model with a total of 5164 interactions. We deposited the three network models in Abasy Atlas v2.4. We study the C. glutamicum regulatory structure by comparing it against the networks for more than 40 species, finding it to contrast in several global structural properties. We analyze the system-level components of the networks, finding that the inclusion of the sRNAs regulations changes their proportions, transferring part of the basal machinery to the modular class and increasing the number of modules while decreasing their size. Finally, we use strong networks of three model organisms to provide insights in future directions of the C. glutamicum network characterization.

The content of this paper is a very significant contribution to the heritage regional reconstruction and conservation interventions. The results about the iconographic analysis of the Early-Renaissance frescoes of St. Leocadia Church, in Chaves, in the north-east of Portugal, were presented for the first time. This paper aims to study facial similarity analysis applied to identification of the personages represented in the 1511-1513 mural paintings of the apse of St. Leocadia Church, in Chaves Municipality (North of Portugal) and those ones in the oil paintings by the Proto-Renaissance Portuguese painter Nuno Gonçalves. In this work, it was explored the feasibility of face recognition technologies in answering many ambiguities concerning Manueline stylistic identity and iconography. A proposal was made to identify the characters, fundamental to the meaning of the frescoes. It has been experimentally proved on 7 characters of St. Leocadia Church’s paintings, in comparison with the referred old master portraits. It was used an in-house trained deep face recognition model to extract facial features from images of 15th and 16th century portraits to compare their degree of similarity. It was undertaken facial similarity analysis of the faces in the formidable portrait gallery of the 15th century Portuguese society represented in the Panels of St. Vicent, which has been subject of national and international research for 130 years. On the other, in the oil painting of St. Peter and St. Paul and Infanta St. Joana, of the same old master. The iconographic interpretation of the mural paintings of St. Leocadia, based in the deep facial features of the images, is plausible: a catechetical purpose; the ritual practices of royal ancestor worship in royal portrait apses of the churches; the Portuguese maritime expansion and the macro-imperial ideology of D. Manuel I.

As more end devices are getting connected, the Internet will become more congested. A variety of congestion control techniques have been developed either on transport or network layers. Active Queue Management (AQM) is a paradigm that aims at mitigating the congestion on the network layer by active buffer control to avoid overflow. However, finding the right parameters for an AQM scheme is challenging, due to the complexity and dynamics of the networks. On the other hand, the Explicit Congestion Notification (ECN) mechanism is a solution that makes visible incipient congestion on the network layer to the transport layer. In this work, we propose to exploit the ECN information to improve AQM algorithms by applying Machine Learning techniques. Our intelligent method uses an artificial neural network to predict congestion and an AQM parameter tuner based on reinforcement learning. The evaluation results show that our solution can enhance the performance of deployed AQM, using the existing TCP congestion control mechanisms.

Multicriteria decision aid requires a database as a decision matrix, in which two or more alternatives are evaluated according to two or more variables selected as decision criteria. Several problems of this nature use measures by Likert scales. Depending on the method, parameters from these data (e.g. means, modes or medians) are required for calculations. This parameterization of data in ordinal scales has fueled controversy for decades between authors who favor mathematical/statistical rigor and argue against the procedure, stating that ordinal scales should not be parameterized, and scientists from other areas who have shown gains from the process that compensate for this relaxation. The aim of this article is to demonstrate the advantages of the Composition of Probabilistic Preferences (CPP) method in multicriteria problems with data from Likert scales. The CPP is capable of allaying the protests raised and obtaining more accurate results than descriptive statistics or parametric models can bring. The proposed algorithm in R-code involves the use of CPP with empirical distributions and fitting histograms of data measured by Likert scales. Two case studies with simulated datasets having peculiar characteristics and a real case illustrate the advantages of the CPP.

Introduction of exotic species in new areas through anthropic action is one of the major problems that can affect biodiversity. Branchiomma luctuosum is known for its highly invasive potential and the actual occurrence of species commonly associated with port activity areas is an extra evidence that this anthropogenic activity should not be underestimated. In order to develop suitable molecular markers for future studies on colonization routes and population dynamics of the invading individuals of B. luctuosum, nine highly polymorphic microsatellite loci were isolated and their polymorphism levels were evaluated. These loci showed a range of number of alleles per locus from five to ten and all loci had a high level of genetic diversity, and exhibited significant heterozygote deficiencies probably due to the presence of null alleles. Significant deviations from the Hardy-Weinberg equilibrium were detected at several loci and most of them were related to a heterozygous deficit. Heterozygous deficiency can be expected in this case due to the biology and history of this invasive species, in relation to its recent introduction in Brazilian coast and possible action of multiple introductory events.

In order to fully perform their functions and be durable, mortars for renders and plasters are requested to have a set of characteristics that can vary with the type of exposure to external environmental actions and the type of substrate. Generally, they need moderate strength, high deformability, some water protection capability, good adhesion to the substrate, and compatibility with the pre-existent materials. The presence of water and its movement inside the pore structure of the mortars are among the most significant causes of degradation. Moreover, several authors consider that the main factors for durability and good performance of lime-based mortars are mostly related with the good quality of the binder and the use of adequate aggregates. This paper intends to study the effect of ageing on the properties and durability of air lime mortars, using aggregates of different mineralogy. For this purpose, different mortars compositions are exposed to an accelerated weathering test under defined conditions. The obtained characteristics are discussed and compared with the results obtained with the same mortars tested in laboratory conditions. The effects of the aggregate type on the durability of mortars seem to be linked to their effects on the mortars porous structure.

This research seeks to understand the impact of digital platforms on the governance of smart cities. It uses the Scaffold of Popular Participation to classify digital platforms and better understand participatory governance in cities, its benefits and complications, correlating them with the SDGs of the 2030 Agenda. It was also possible to list points of attention for the development of digitization in the public sector, including in Brazil. It concluded that the digitization of public services is in progress, pressured by the civil body for greater transparency and participation. In addition, the platforms must be guided by civil inclusion in the discussion of public policies, by the training of intelligent citizens and by sustainable guidelines that guide the themes addressed. In contrast, platforms can also facilitate deception and popular manipulation, which represents a high risk if used for this purpose.

(1) Background: The CEECCA questionnaire assesses the ability to communicate among individuals with aphasia. It was designed using the NANDA-I and NOC standardised nursing languages (SNLs), reaching high content validity index and representativeness index values. The questionnaire was pilot-tested, demonstrating its feasibility for use by nurses in any healthcare setting. This study aims to identify the psychometric properties of this instrument. (2) Methods: 47 individuals with aphasia recruited from primary and specialist care facilities. The instrument was tested for construct validity and criterion validity, reliability, internal consistency, and responsiveness. The NANDA-I and NOC SNLs and the Boston test were used for criterion validity testing. (3) Results: 5 language dimensions explain 78.6% of the total variance. Convergent criterion validity tests showed concordances of up to 94% (Cohen’s κ: 0.9; p&lt;0.001) using the Boston test, concordances of up to 81% using DCs of NANDA-I diagnoses (Cohen’s κ: 0.6; p&lt;0.001), and concordances of up to 96% (Cohen’s κ: 0.9; p&lt;0.001) using NOC indicators. Internal consistency (Cronbach’s alpha) was 0.98. Reliability tests revealed test-retest concordances of 76%-100% (p&lt;0,001). (4) Conclusions: The CEECCA is an easy-to-use, valid, reliable instrument to assess the ability to communicate among individuals with aphasia.

Oleogels are of high interest as promising substitutes for trans fats in foods. An emulsion-templated method was used to trap olive oil in the chitosan crosslinked with vanillin matrix. Oil in water emulsions (50:50 w/w) with different chitosan content (0.7 and 0.8% w/w) with constant vanillin/chitosan ratio (1.3) were air-dried at different temperatures (50, 60, 70 and 80ºC) and freeze-dried (-26ºC and 0.1 mbar) to produce oleogels. Only falling-rate periods were determined during air-drying kinetics and were successfully modelled with empirical and diffusional models. At drying temperature of 70ºC the drying kinetics were the fastest. Viscoelasticity of oleogels showed that elastic modulus significantly increased after drying at 60 and 70ºC, and those dried at 50ºC and freeze-dried were weaker. All oleogels showed high oil binding capacity (&gt; 91%), but the highest values (&gt; 97%) were obtained in oleogels with a threshold elastic modulus (50,000 Pa). Oleogels color depended on drying temperature and chitosan content (independent of the drying method). Significant differences were observed between air-dried and freeze-dried oleogels with respect to oxidative stability. Oxidation increased with air drying time regardless of chitosan content. Found results indicated that drying conditions must be carefully selected to produce oleogels with specific features.

Background: Nursing home residents (NHRs) have special needs and may experience reduced functionality, higher sedentary behavior time (SBT) and decreased physical activity (PA). This study aimed to characterize NHRs based on SBT, PA, and functional performance (FP), and to identify associations between these factors. Methods: Cross-sectional study with 65 NHRs aged ≥60, evaluated by accelerometer (SBT, PA) and the following tests: Timed Up and Go (TUG), Short Physical Performance Battery (SPPB), Barthel Index (BI), and Mini-Mental State Examina-tion (MMSE). Health-related variables and anthropometry were assessed. The FP (TUG, SPPB, BI), SBT, PA intensities were used for K-means clustering analysis. Results: The cluster analysis identified: C1 – better FP, shorter SBT, and longer time in PA intensities; C2 - lower FP, longer SBT, and shorter time in PA. In addition, C2 were older, with lower MMSE, lower body mass index, and walking aids use. The SBT showed a negative weak correlation with BI. The moderate PA (MPA) was moderately correlated with the SPPB and strongly correlated with the TUG and BI. Conclusions: MPA is strongly associated with better FP and independence. NHRs have dif-ferent physical and cognitive profiles, which indicates the need for personalized strategies to prevent disability and increase PA.

Gliomas are solid tumors of the Central Nervous System (CNS) that originated from different glial cells. The World Health Organization (WHO) classified these tumors into four groups (I-IV) with increasing malignancy. Glioblastoma (GBM) is the most common and aggressive type of brain tumor classified as a grade IV. GBM are resistant to conventional therapies with poor prognosis after diagnosis even when the Stupp protocol that combines surgery and radiochemotherapy is applied. Nowadays, few novel therapeutic strategies have been used to improve GBM treatment, looking for higher efficiency and lower side effects, but with relatively modest results. The circadian timing system temporally organizes the physiology and behavior of most organisms and daily regulates several cellular processes in organs, tissues, and even in individual cells, including tumor cells. The potentiality of the function of the circadian clock on cancer cells modulation as a new target for novel treatments with a chronobiological basis offers a different challenge that needs to be considered in further detail. The present review will discuss state of the art regarding GBM biology, the role of the circadian clock in tumor progression, and new chrono-chemotherapeutic strategies applied for GBM treatment.

Basketball playing entails the repetitive performance of short intense actions using lower limb explosive power. As such, it is important to measure this capability in basketball players, especially among young players, and to optimize training programs and game plans. After presenting an in-depth understanding of the specific physiological requirements when playing basketball, as well as the type of movements required, The aim of this review is to better understand the importance of the physiological energy systems in basketball, to examine the contribution of each energy system and, accordingly, to heighten awareness of the importance and dominance of the alactic anaerobic physiological system in basketball, for actions requiring high level explosive power. This review of the literature depicts the horizontal and vertical physical movements and physiological requirements entailed in playing basketball, and presents eight standardized anaerobic alactic measurement tools relevant to the game. As some of these tests suit a number of ball games, the findings of this review article are important for making order of the elements unique to basketball as well as additional parameters to consider when testing basketball players. By reliably and validly testing the anaerobic alactic capabilities of basketball players, test results can be used for training purposes and for improving game outcomes. Despite the fact that much of the information in this review is familiar to coaches, highlighting the specific needs of basketball may help them to choose the most suitable tools, and may also shed light on new directions for developing basketball-specific assessment tests.

Research has shown that emotional states may influence the subjective experience of time. The present study involved 111 healthy adult participants and examined the impact of emotional stimuli on time perception, using a time estimation task with four conditions: in one of the conditions, participants estimated the exposure time of a black screen, wherein the duration could vary be-tween 2 to 7 s (condition without emotional interference); in the other conditions, participants es-timated the exposure time (also ranging from 2 to 7 s) of images that would induce pleasant, un-pleasant, or neutral emotions, to which participants were instructed to focus their attention (pleasant, unpleasant, or neutral emotions). The results showed that participants estimated “shorter” time intervals (underestimation) for pleasant and unpleasant images compared to the condition without interference, but no significant differences were found between the neutral condition and the condition without interference. It is suggested that increased attention to an ex-ternal stimuli, regardless of its emotional valence, produces an underestimated perception of time.

Alcohol effects on hepatic lipid metabolism through various mechanisms, leading synergistically to an accumulation of fatty acids (FA) and triglycerides. Obesity, as well as, the dietary fat [saturated fatty acids (FA) versus poly-unsaturated fatty acids (PUFA)] may modulate the hepatic fat. Alcohol inhibits adenosine monophosphate activated kinase (AMPK). AMPK activates peroxisome proliferators activated receptor a (PPARα) and leads to a decreased activation of sterol regulatory element binding protein 1c (SRABP1c). The inhibition of AMPK, and thus of PPARα results in an inhibition of FAs oxidation. This ß-oxidation is further reduced due to mitochondrial damage induced through cytochrome P4502E1 (CYP2E1) driven oxidative stress. Furthermore, the synthesis of FAs is stimulated through an activation of SHREP1. In addition, alcohol consumption leads to a reduced production of adiponectin in adipocytes due to oxidative stress and to an increased mobilization of FAs from adipose tissue and from the gut as chylomicrons. On the other side, the secretion of FAs via very low density lipoproteins (VLDL) from the liver is inhibited by alcohol. Alcohol also affects signal pathways such as early growth response 1 (Egr-1) associated with the expression of tumour necrosis factor  (TNF), and the mammalian target of rapamycin (mTOR) a key regulator of autophagy. Both have influence the pathogenesis of alcoholic fatty liver. Alcohol-induced gut dysbiosis is contributing to the severity of ALD by increasing metabolism of ethanol in the gut and promoting intestinal dysfunction. Moreover, pathogen associated molecular paterns (PAMPS) via specific Toll-like receptors (TLR) bacterial overgrowth is leading to the translocation of bacteria. Endotoxins, and toxic ethanol metabolites enter the enterohepatic circulation reaching the liver, inducing the activation of the nuclear factor kappa-B (NFB) pathway. Pro-inflammatory cytokines released in the process contribute to inflammation and fibrosis. In addition, cellular apoptosis is inhibited in the favor of necrosis.

In this paper we use the conformable fractional derivative to discuss some fractional linear differential equations with constant coefficients. By applying some similar arguments to the theory of ordinary differential equations, we establish a sufficient condition to guarantee the reliability of solving constant coefficient fractional differential equations by the conformable Laplace transform method. Finally, we analyze the analytical solution for a class of fractional models associated with Logistic model, Von Foerster model and Bertalanffy model is presented graphically for various fractional orders and solution of corresponding classical model is recovered as a particular case.

This paper seeks to optimize the mechanical and durability properties of ultra-high performance concrete (UHPC). To meet this objective, concrete specimens were manufactured by using 1,100 kg/m3 of binder, water/binder ratio 0.20, silica sand and last generation of superplasticizer. Silica fume, metakaolin and two types of nano silica were used for improving the performances of the concrete. Additional mixtures included 13mm long OL steel fibers. Compressive strength, electrical resistivity, mercury intrusion porosimetry tests and differential and thermogravimetric thermal analysis were carried out. The binary combination of nano silica and metakaolin, and the ternary combination of nano silica with metakaolin and silica fume, led to the best performances of the UHPC, both mechanical and durable performances.

(1) Background: Nursing homes’ preparedness in managing a public health crisis has been fragile, with effects on safety culture. The objective of this study was to assess nursing homes’ COVID-19 preparedness in Southern Portugal, including personnel’s work experiences during the pandemic. (2) Methods: We used a COVID-19 preparedness checklist to be completed by management teams, followed by follow-up calls to nursing homes. Thereafter, a survey to personnel was applied. Data analysis included descriptive statistics, exploratory factor analysis, and thematic analysis of open-end questions. (3) Results: In total, 71% (138/195) of eligible nursing homes returned the preparedness checklist. We conducted 83 follow-up calls and received 720 replies to the personnel survey. On average, 25% of nursing homes did not have an adequate decision-making structure to respond to the pandemic. Outbreak capacity and training were fragile areas among nursing homes’ contingency plans. We identified compliance with procedures and nonpunitive response to mistakes as fragile areas of safety culture, and teamwork as a strong safety area. (4) Conclusions: To strengthen how nursing homes cope with upcoming phases of the COVID-19 pandemic or future public health emergencies, nursing homes’ preparedness and safety culture should be fostered and closely monitored.

The problem of event detection in general noisy signals arises in many applications; usually, either a functional form for the event is available, or a previous annotated sample with instances of the event that can be used to train a classification algorithm. There are situations, however, where neither functional forms nor annotated samples are available; then it is necessary to apply other strategies to separate and characterize events. In this work, we analyze 15 minute-long samples of an acoustic signal, and are interested in separating sections, or segments, of the signal which are likely to contain significative events. For that, we apply a sequential algorithm with the only assumption that an event alters the energy of the signal. The algorithm is entirely based on Bayesian methods.

Background: During esophagogastroduodenoscopy performed with colonoscopy, gastric and duodenal erythema, erosions, and ulcerations are often observed. This investigation was designed to review the prevalence of gastroduodenal lesions in patients who underwent wireless capsule endoscopy using standard bowel cleansing preparations, but no endoscopy or sedation. Methods: A retrospective analysis was conducted on patients referred for capsule endoscopy. Records and capsule reports were reviewed for patient demographics, preparation prescribed, procedural indications, and gastroduodenal findings. Preparations studied included polyethylene glycol lavage (PEG), PEG plus bisacodyl (PEG+bis), bisacodyl (bis), oral sulfate solution (OSS) and no prep. Results: Among the 1236 records, 498 (40.3%) were men and 738 (59.7%) were women. The mean age was 57 years +/- 17.8 years SD. The percentage of patients with lesions after any bowel preparation was 52.7% for gastric lesions and 23.6% for duodenal lesions. The percentage of patients with gastroduodenal lesions was 58.3% with prep, compared to 38.2% without prep. These findings were statistically significant with RR 1.53 [1.19-1.94] (p-value=0.00004). This difference was more pronounced in the OSS group RR 1.65 [1.29-2.1] and bisacodyl groups RR 1.64 [1.25-2.15] compared to the PEG group RR 0.95 [0.7-1.3]. Conclusion: This study showed that patients undergoing wireless capsule endoscopy who received bowel preparations had a significant increase in gastric and duodenal lesions. Of the preparations studied, OSS was associated with the greater number of gastroduodenal lesions, while PEG was the least associated with lesions with an occurrence similar to the non-prep group. The clinical significance of these lesions remains undetermined.

Cuba is struggling with a growing environmental problem: the uncontrolled spread of the allochthonous weed species marabou (Dichrostachys cinerea) throughout the country. Over the last 70 years, marabou has become a formidable invasive species that poses a threat to Cuban biodiversity and agricultural productivity. In this paper, we present a free and affordable method for regularly mapping the spatial distribution of the marabou based on the Google Earth Engine platform and ecological surveys. To test its accuracy, we develop an 18-year analysis (2000–2018) of marabou dynamics using the Valle de los Ingenios, a Cuban UNESCO World Heritage Site, as an experimental model. Our spatial analysis reveals clear patterns of marabou distribution and highlights areas of concentrated growth. Temporal trends illustrate the dynamic nature of the species, identifying periods of expansion and decline. In addition, our system is able to detect specific, large-scale human interventions against the marabou plague in the area. The results highlight the urgent need for remedial strategies to maintain the fragile balance in the region.

Primary energy consumption is one of the key drivers of global CO₂ emissions that, in turn, heavily depend on the efficiency of involved technologies. Either the improvement in technology efficiency or the expansion of non-fossil fuel consumption require large investments. The planning and financing of such investments, by policy makers or global energy firms, require, in turn, reliable measures of associated global spreads and their evolution in time. In this paper, our main contribution is the introduction of index measures for accessing global spreads (that is, measures of inequality or inhomogeneity in the statistical distribution of a related quantity of interest) of technology efficiency and CO₂ emission in primary energy consumption. These indexes are based on the Gini index, as used in economical sciences, and generalised entropy measures. Regarding primary energy sources, we consider petroleum, coal, natural gas and non-fossil fuels. Between our findings, we attest some stable relations in the evolution of global spreads of technology efficiency and CO₂ emission, and a positive relation between changes in global spreads of technology efficiency and use of non-fossil fuel.

This paper presents the results of aerodynamical performance research focused on maintaining the thermal comfort and increasing the energy efficiency of a typical social housing unit located in a high-density urban area. Bioclimatic design strategies are used to develop a sustainable and economic technology in existing housing clusters in Mexico City. A full-scale prototype, built on campus facilities, was used to study the flow conditions around the design. All scaled prototypes implement similar criterion. Furthermore, a scaled prototype is evaluated within a low speed wind tunnel installation. Additionally, numerical simulations were performed at transient state based on previous physical measurements and historical local climatic conditions to determine preferable modifications.

In Tunisia, olive is the most cultivated fruit crop while in the north where rainfall exceeded 400mm.year-1, the olive growing area is in widely extension in marginal soil with high slope gradient. Thus, the inclusion of cover crops is a sustainable solution to increase the ecosystem productivity, improve the soil fertility and oil yields. But, in Tunisia a few study were investigated the effect of legumes cover crop on the olive productivity. Therefore, the aim of this study was to evaluate the short-term (two cropping seasons s 2021 and 2022) effects of different seeded cover crops and soil management practices on the cover crops and soil characteristics, as well as enzymes activities and related microbial diversity. Six intercropping were tested in rainfed olive orchards (cv.Chétoui): Spontaneous vegetation (Spont), Wheat, Vetch, Oat, Fenugreek, mixture Vetch-Oat and compared to control (3 periodic tillage/year without intercropping). During the first cropping season, cover crops were cut as animal feed and only residues were incorporated into the soil. While, during the second year, all cover crops biomass were incorporated into the soil. Results indicate that the dry biomass and carbon uptake were significantly higher in grasses species (Wheat and Oat). But, highest level of nitrogen was found in Fenugreek cover crops. As compared to control, all cover crops including spontaneous vegetation increased soil organic matter and macronutrient level, mainly phosphorus. The most activity of β-glucosidase, phosphatase and arysulphatase was found in the cover crops plot of wheat and oat. In addition, this study improve that the utilization of the carbon sources was dominated by amides, amine and amino-acids in the fenugreek plot; while it was dominated by polymers and carboxylic acids in the case of wheat and oat.

The aim of this study was to develop and assess the reliability and validity of an innovative field test that measures lower limb explosive power in basketball players (i.e., alactic anaerobic capacity) for the dominant and non-dominant leg. The test examines the performance of vertical, horizontal, and combined movements while holding the ball – similar to penetration of the basket or layup. Such capabilities are required throughout basketball practice and games, combined with upper and lower body coordination. The study included 22 male basketball players, ages 16-18, members of an elite youth league team in Israel. To assess validity, the participants performed the test for each leg, followed by nine standardized tests that were developed for a range of ball games, including basketball. To assess reliability, the participants performed a retest of the unique test 72-hours later. Our findings indicate the validity and reliability of the proposed anaerobic alactic field test for basketball players, for the dominant and non-dominant leg. Moreover, strong correlations were seen between the novel test and the standardized tests, with a high correlation for horizontal explosive power (0.5<r<0.7), a very high correlation for vertical explosive power (0.7<r<0.9), and a nearly perfect correlation for the two combined (r>0.9). In conclusion, this unique field test for basketball players could assist coaches in developing and applying optimal training programs and game plans, for players individually, and for the team as a whole. As the test measures each leg separately, it could also offer an assessment tool following players’ injuries.

One of the areas of research on materials for thin-film solar cells focuses on replacing In and Ga with more earth-abundant elements. In that respect, chalcostibite (CuSbS2) is being considered as a promising environmentally friendly and cost-effective photovoltaic absorber material. In the present work, single CuSbS2 phase have been synthesized directly by a short duration (2 h) mechanochemical synthesis step starting from mixtures of elemental powders. X-ray diffraction analysis of the synthesized CuSbS2 powders revealed a good agreement with the orthorhombic chalcostibite phase, space group Pnma, and a crystallite size of 26 nm. Particle size characterization revealed a multimodal distribution with a median diameter ranging from of 2.93 m to 3.10 m. The thermal stability of the synthesized CuSbS2 powders was evaluated by differential thermal analysis. No phase change was observed by heat treating the mechanochemically synthesized powders at 350 C for 24 h. By UV-VIS-NIR spectroscopy the optical bandgap was determined to be 1.41 eV, suggesting that the mechanochemically synthesized CuSbS2 can be considered suitable to be used as absorber materials. Overall, the results show that the mechanochemical process is a viable route for the synthesis of materials for photovoltaic applications.

One way to increase overall natural gas engine efficiency is to transform exhaust waste heat into useful energy by means of a bottoming cycle. Organic Rankine cycle (ORC) is a promising technology to convert medium and low grade waste heat into mechanical power and electricity. This paper presents an energy and exergy analysis of three ORC-Waste heat recovery configurations by using an intermediate thermal oil circuit: Simple ORC (SORC), ORC with Recuperator (RORC) and ORC with Double Pressure (DORC), and Cyclohexane, Toluene and Acetone have been proposed as working fluids. An energy and exergy thermodynamic model is proposed to evaluate each configuration performance, while available exhaust thermal energy variation under different engine loads was determined through an experimentally validated mathematical model. Additionally, the effect of evaportating pressure on net power output , absolute thermal efficiency increase, absolute specific fuel consumption decrease, overall energy conversion efficiency, and component exergy destruction is also investigated. Results evidence an improvement in operational performance for heat recovery through RORC with Toluene at an evaporation pressure of 3.4 MPa, achieving 146.25 kW of net power output, 11.58% of overall conversion efficiency, 28.4% of ORC thermal efficiency, and an specific fuel consumption reduction of 7.67% at a 1482 rpm engine speed, a 120.2 L/min natural gas Flow, 1.784 lambda, and 1758.77 kW mechanical engine power.

The ironstone outcrops in the rupestrian grasslands, known as cangas, are rich in species of endemic plants. This high endemism and the constant threat because of the area loss and fragmentation make the conservation of the rupestrian grasslands necessary. The rupestrian grasslands that host one of Brazil's largest iron-ore mining areas are Iron Quadrangle. About 89 rare and endangered species of the Iron Quadrangle are exclusive to cangas, including a threatened species Arthrocereus glaziovii. According to the International Union Conservation of Nature (IUCN), this species is considered micro-endemic and endangered and a priority for recovering the Iron Quadrangle's ferruginous rupestrian fields. This work aims to evaluate the potential distribution of A. glaziovii based on abiotic variables and soil elements and characterize the distribution of mining titles that may restrict the areas of occurrence of this species. We used five types of ecological niche model (ENM) algorithms (Bioclim, Domain, MaxEnt, GLM and RandomForest) in two sets of environmental variables for the modeling: 20 climatic variables and 18 edaphic variables. Our results showed that the area of the potential occurrence of A. glaziovii is more extensive and covers areas outside the Iron Quadrangle. However, mining titles currently licensed and in exploration correspond the entire identified area, threatening the species' survival.

In the early 1990s, cyberfeminism emerged as an area of knowledge to discuss the connection between gender and technology. According to UNESCO, women are underrepresented in the field of science, technology, engineering, and mathematics and less than a third of women worldwide work in scientific research and development. However, this number has grown and this reality is constantly changing. In this context, using business intelligence techniques, this study analyzes data from the computer and information and communication technology market to characterize the impact of the performance of women in these areas. It is expected to show that this performance in the highlighted fields is still a challenge in Brazil.

Myelodysplastic syndromes (MDS) are diseases that occur when blood-producing cells in the bone marrow are damaged; such damage can affect one or more types of blood cells. Common types of MDS are refractory anemia with ring sideroblasts and refractory anemia with excess blasts (MDS-RS and MDS-EB, respectively). This work analyzed the proteomics of the medullary plasma of 10 patients with MDS-RS and MDS-EB compared to healthy control people. Overexpressed proteins that may be potential candidates for biological markers for the evaluation, study, and diagnosis of these diseases have been identified. These samples were subjected to immunodepleting, concentrated, and digested for further analysis by mass spectrometry. The ratios between selected groups and healthy people were calculated. Seven overexpressed proteins in both syndromes were identified as potential biomarker candidates: vitronectin (VTN), (2) fibrinogen (FGA), (3) pregnancy zone protein (PZP), (4) kininogen (KNG1), (5) immunoglobulin lambda chain (IGLL1), (6) complement factor C4b, and (7) hemopexin (HPX). A modified affinity chromatographic column with lectin frutalin (FTL) was used for non-depleted samples. Immunoglobulin M (IgM) was expressed in the samples from both syndromes. Surprisingly, IgM from patients with syndromes was over retained on the frutalin (FTL) column when compared with the control group. We further hypothesized that over retention of this protein by the FTL is due to the presence of α-galactosidic residues in the IgM of MDS-RS and MDS-EB patients. Differential recognition of proteins on non-depleted samples from the use of FTL appears to be a powerful tool for proteomic analysis.

This work exclusively focuses on the assessment of the thermal performance of a multifunctional facade panel incorporating PCM in foam layers, recurring to a hot box heat flux meter method to determine the thermal transmittance (U-value). The experimental setup is based on the steady-state approach using climatic chambers, assuring a stable thermal environment. Even small fractions of PCM achieved a small reduction in thermal amplitude. Numerical simulations using Ansys Fluent were developed to evaluate the performance of PCM use over a wide range of temperature boundary conditions and operating modes. These numerical models were calibrated and validated using the results of experimental tests, achieving a correlation factor of 0.9674, thus accurately representing a real-world scenario. The decrement factor (f) was used to analyse the data. It was identified that the efficiency of the panel and size of the optimum region increased with the PCM fraction growth. The simulated behaviour was optimum when the input mean temperature is of 20 °C for a room temperature of between 18-20 °C. The results show the significant potential of the multi-layered panel and the thermal regulator effect of the PCM incorporated on indoor space temperature to reach good thermal comfort levels.

The transport sector is pivotal and indispensable in our daily existence, being the exclusive conduit for the intercontinental conveyance of commodities and individuals. Hence, comprehending the phenomenon of business failure within the transport industry assumes paramount significance in delineating an effective competitive policy for this sector. The primary objective of this research paper is to execute a comparative investigation between statistical models forecasting business failure and models founded on artificial intelligence, within the context of the transport sector. This analysis spans the temporal expanse from 2014 to 2021 and encompasses the nations of Portugal, Spain, France, and Italy, aiming to ascertain superior efficacy among these models. The dataset employed for this endeavor encompassed a final cohort of 4866 companies, comprising 2881 that endured as going concerns and 1985 that succumbed to business failure. The models developed for this study exhibited the capacity to accurately categorize a proportion of companies ranging from 71% to 73%. Nonetheless, upon comparative scrutiny of these outcomes with those derived from the statistical models dedicated to business failure prediction, it becomes evident that the latter demonstrate an enhanced predictive prowess, manifesting fewer errors in the classification of the scrutinized companies.

The human ankle is a complex joint, most commonly represented as talocrural and subtalar axes. It is difficult to locate and take in vivo measurements of the ankle joint. There are no instruments for patients lying on a bed or the floor; that can be used in outdoor or remote sites. We have developed a "Turmell-meter" to address these issues. We started with the study of ankle anatomy and anthropometry, then we used the product of exponentials’ formula to visualize the movements. Furthermore, we built a prototype using human proportions and statistics. For pose estimation, we used a trilateration method by applying tetrahedral geometry. Additionally, we computed the axis direction by fitting 3D circles, plotting the manifold and chart as an ankle joint model. We presented the results of simulations, a prototype comprising 45 parts, specifically designed draw-wire sensors, and electronics. Finally, we tested the device by capturing positions and fitting them into the bi-axial ankle model as a Riemannian manifold. The Turmell-meter is intended to be a hardware platform for human ankle joint axis estimation, it is adjustable and has an easy setup. The proposed model has the properties of a chart in a geometric manifold, we provided the details

In this work a research on pulsed electrochemical micromachining of Stainless Steel is presented. A suitable equipment to study the process is described as well as a fitting procedure to machine and measure the variables involved. A tool of Tungsten with a tip of about 5 mm diameter sunk in an electrolyte of NaNO₃ is used for the process. The pulse on-time must be maintained in the order of ns to achieve a good current confinement, since the tool is active. Some experiments were made to assess the most important variables of the process, as current confinement, surface roughness, material removal rate and efficiency. It is observed that the current confinement get worse when the pulse on-time increases, as well as surface roughness. The material removal rate and the efficiency increase with the voltage amplitude and the pulse on-time. The voltage amplitude must be higher than 12 V so that the phenomenon of passivation disappears. There is a compromise in the choice of the variables, so a suitable combination of parameters is determined so that a good material removal rate with an acceptable result is achieved.

Despite advances in the reliability of sensory devices used by drones, the integrity of information from some devices is still considered an obstacle to ensuring successful flight plans. It is widely known that GNSS can suffer attacks or lose the signal from satellites, which can cause the drone to fail to complete its flight plan. In this context, we propose SiaN-VO, a Siamese network for visual odometry prediction. In our initial studies, this approach proved satisfactory for flights in static conditions (speed and height). Although interesting, these conditions do not reflect real flight conditions. In this sense, we have advanced our studies to propose the SiaN-VO, which fuses data from different sensors to enable displacement predictions to be made in dynamic flight conditions.

Non-typhoid salmonellosis is a common and problematic foodborne zoonotic disease in which pork and pork products can be an important potential source of infection. In order to prevent this disease important efforts to monitor the situation in the main source, livestock, are conducted in most developed countries. In the European Union EFSA and ECDC compile information at the member state level, even though important differences in production systems and surveillance systems exist. Here, Salmonella surveillance systems in one of the main sources of foodborne salmonellosis, swine, and humans in Spain were reviewed to identify potential gaps and discuss potential ways of integration under a One Health approach. Despite the extensive information generated through the surveillance activities source attribution can be only routinely performed through ad-hoc outbreak investigations, and national reports on human outbreaks do not provide sufficiently detailed information to gain a better understanding of the epidemiology of the pathogen. Human and animal monitoring of Salmonella would benefit from a better exchange of information and collaboration. Analysis of spatio-temporal trends in livestock and humans could help to identify likely sources of infection and to target surveillance efforts in areas with higher prevalence or where specific strains are found.

Syphilis continues to be a significant global health concern, and understanding the latest advancements in immunology and pharmacological treatment is crucial for effective disease management. This review article provides an in-depth exploration of these advancements, aiming to contribute to the growing body of knowledge on syphilis research. The epidemiology of syphilis sets the stage for this review, highlighting the persistent burden of the disease worldwide. Current trends and challenges in disease control are discussed, shedding light on the need for comprehensive prevention strategies and improved surveillance systems. The immunological aspects of syphilis are the focus of this review. The intricate interplay between the host immune response and the evasive strategies employed by Treponema pallidum, the causative agent of syphilis, are explored. These include the mechanisms of immune evasion, the role of adaptive and innate immunity, and the development of immune-mediated tissue damage. The article also highlights advancements in diagnostic methods, with emphasis on the importance of accurate and timely detection. From traditional serological tests to the emergence of novel molecular and point-of-care assays, these developments have significantly improved the efficiency and accuracy of syphilis diagnosis. In terms of pharmacological treatment, the review covers the current recommendations and emerging strategies for managing syphilis infections. The challenges posed by antimicrobial resistance are addressed, emphasizing the importance of appropriate treatment regimens and close monitoring of therapeutic efficacy. Looking to the future, this review highlights the potential of vaccine development as a preventive measure against syphilis. Promising vaccine candidates and ongoing research efforts are discussed, offering hope for an effective means of disease prevention. In conclusion, this comprehensive review explores the advancements in syphilis research, from the understanding of immunological complexities to the development of innovative treatment strategies. By collectively advancing our knowledge, we can strive towards better disease management and minimize the impact of syphilis on global public health.

The population growth and its needs, has increasingly demanded water resources, requiring managers to adopt mechanisms to guarantee the availability and quality of water from springs. Among the instruments defined by law n. 9433/1997, water charges stand out. In this sense, the objective was to evaluate the evolution of charging for the use of water resources in Brazil, with emphasis on the channel of the Hydrographic Basin of the Paranaíba River. The methodology used was based on two phases, one of reviewing the articles available in Capes journals and the other, consulting the spreadsheets of the Araguari River Basin Agency with information on charges for the use of water within the competence of the Union in the Hydrographic Basin of the Paranaiba River. The results showed that charging for the use of water resources establish a relevant instrument for disciplining and raising financial resources that will enable improvements in the planning and management of water use. It should be noted that irrigation emerges as the main user of the flow captured from the Paranaíba River. However, the main source of funds for charging comes from the public supply. Among the Federation Units, the Federal District proved to be the largest source of contributions for charging the use of the Union's water resources in the Paranaíba River Basin.

Stroke remains a major cause of death and disability in the United States and around the world. Solid safety and efficacy profiles of novel stroke therapeutics have been generated in the laboratory, but most failed in clinical trials. Investigations into the pathology and treatment of the disease remain a key research endeavor in advancing scientific understanding and clinical applications. In particular, cell-based regenerative medicine, specifically stem cells transplantation, may hold promise as stroke therapy because grafted cells and their components may recapitulate the growth and function of the neurovascular unit, which arguably represents the alpha and omega of stroke brain pathology and recovery. Recent evidence has implicated mitochondria, organelles with a central role in energy metabolism and stress response, in stroke progression. Recognizing that stem cells offer a source of healthy mitochondria, potentially transferrable into ischemic cells, may provide a new therapeutic tool. To this end, deciphering cellular and molecular processes underlying dysfunctional mitochondria may reveal innovative strategies for stroke therapy. Here, we review recent studies capturing the intimate participation of mitochondrial impairment in stroke pathology, and showcase promising methods of healthy mitochondria transfer into ischemic cells, to critically evaluate the potential of mitochondria-based stem cell therapy for stroke.

Any effort to combat corruption can benefit from an examination of past and projected worldwide trends. In this paper, we forecast the level of corruption in countries by integrating an artificial neural network modeling and time series analysis. The data were obtained from 113 countries from 2007 to 2017. The study is carried out at two levels: (a) global level where all countries are considered as a monolithic group; and (b) cluster level, where countries are placed into groups based on their development-related attributes. For each cluster, we use the findings from our previous study on the cluster analysis of global corruption using machine learning methods that identified the four most influential corruption factors, and we use those as independent variables. Then, using the identified influential factors, we forecast the level of corruption in each cluster using a nonlinear autoregressive recurrent neural network with exogenous inputs (NARX), an artificial neural network technique. The NARX models were developed for each cluster, with the objective function in terms of the Corruption Perceptions Index (CPI). For each model, the optimal neural network is determined by finetuning the hyperparameters. The analysis was repeated for all countries as a single group. The accuracy of the models is assessed by comparing the mean square errors (MSE) of the time series models. The results suggest that the NARX artificial neural network technique yields reliable future values of CPI globally or for each cluster of countries. This can assist policymakers and organizations in assessing the expected efficacies of their current or future corruption control policies from a global perspective as well as for groups of countries.

This work studies the discontinuities features of sedimentary flysch materials in a 100 km2 area belonging to the Basque Arc. Such materials are common in this Spanish Alpine region located in the north of the Iberian Peninsula. A total of 33 outcrops are investigated by an intensive geotechnical investigation including geomechanical stations, boreholes and mechanical laboratory tests. Two flysch units are characterized: the Upper Aguinaga Formation or siliciclastic flysch, and the Lower Itziar Formation or calcareous flysch. Differences between both flysch formation are found. Joints in the siliciclastic flysch formation present an undulated roughness, with a spacing narrower and a persistence lower than in the calcareous flysch formation, which exhibits higher friction angles, although roughness is essentially planar. In addition, the potential of using Artificial Intelligence (AI) techniques, particularly Artificial Neural Networks and Support Vector Machine, to estimate the Geological Strength Index (GSI) from the Rock Quality Design (RQD) and some discontinuities features (spacing, persistence, aperture and roughness) is investigated. AI techniques are found to be satisfactory, being the Support Vector Machine with a linear kernel the technique which achieves the best performance.

Metabolically unhealthy obesity (MUO) was associated with increased cardiometabolic risk. However, it is not fully understood which lifestyle factors are associated with MUO in youth. We aimed to investigate the relationship between MUO and lifestyle patterns in youth. 7-17 years old youth with overweight (N=48; 60.4% girls) and obesity (N=71; 56.3% girls) were recruited in the Pediatric Clinic, Luxembourg (cross-sectional study). Eating and sedentary habits, moderate to vigorous physical activity (MVPA) and vigorous physical activity (VPA) were assessed. 72.3% of the participants had MUO. Multivariable logistic regressions showed that MUO is most likely to be associated with moderate to low weekly levels of MVPA [OR: 2.09 (95% CI: 1.07 – 4.09; p = 0.030)] and moderate to high weekly soda and lemonade drinks consumption [OR: 2.92 (95% CI: 1.32 – 6.48; p = 0.008)]. After adjustment for age, gender and Tanner stages, MUO was most likely to be associated with moderate to high soda and lemonade drinks consumption [OR: 2.72 (95% CI: 1.21– 6.12; p = 0.016)] and with Tanner stages [OR: 2.06 (95% CI: 1.08– 3.94; p = 0.029)]. We support the promotion of MVPA and the moderation in the sugar-sweetened beverages consumption to manage cardiometabolic health in youth with obesity.

This study adapted and assessed a shortened version of the IAT (Internet Addiction Test) scale completed by young people aged 12 years and older regarding their online behaviors and risk of online addiction. The psychometric qualities of the reduced version - Screening IAT - youth are presented in order to validate its use in the early detection of online addiction. The total sample is composed of 3021 participants being 55.9% female and 44.1% male, with a mean age of x ̅=15 years (σ=3.028), attending junior high school (56.2%), high school (37.8%) and college (5.9%). The procedure included a factorial analysis, in which the total sample was randomly divided into three samples. An exploratory factor analysis was performed with one part of the sample, and a confirmatory factor analysis was performed with the others parts, assessing internal consistency, construct reliability, and discriminant validity. The results indicate that this reduced version of the IAT for young people has good psychometric qualities and can be applied in research and clinical settings. With this version and the parent-teacher version there is a direct contribution to a tripartite assessment of internet addiction risk.

Amidst the rapid urbanization of cities worldwide, there is a pressing need for practical tools to manage and preserve the invaluable architectural heritage contained within them. This research introduces a systematic methodology for digitalizing and interpreting architectural heritage through augmented Reality (AR). The primary goal is to enhance the documentation, preservation, and accessibility of cultural assets, addressing both educational and touristic needs. Focusing on the historic district of Pelourinho in Salvador, Bahia, Brazil, the study showcases how 3D digitalization combined with AR can provide users with an interactive experience with historical structures, bridging the temporal divide. By integrating the digital replicas of historic buildings into a real-time environment, users gain enriched insights into these structures’ history, architecture, and cultural significance. Though the preliminary results underscore the potential of this approach, comprehensive user testing remains an area for future exploration. This paper thus highlights the potential of AR in historical and cultural preservation, suggesting its broader implications for education, tourism, and heritage management.

This study presents results of the sediment yield Watershed of Ribeirão do Pinhal, in the city of Limeira, São Paulo, conducted under three different scenarios of the land use: 1 – land use in 2008, 2 – with reforested protection areas, 3 – the increase sugarcane's areas over grassland and citrus areas. The Soil and Water Assessment Tool (SWAT) was used as a hydro-sedimentological modeling tool to simulate these scenarios. This watershed was divided into five sub-watersheds according to the prevalent use, and adjustments were made in soils database parameters and cultures that are in SWAT, to adapt it to the Brazilian reality. Was used climatological data of eight years (2007-2014) for this modeling. Different sediment yield could be noted in the different types of land use, sub-watersheds and scenarios. The uses that presented higher sediment yield, in ascending order, were: natural vegetation, sugarcane, citrus, annual crop e grassland. Sub-watershed number 2 had the highest sediment yield (~10Mg.ha^-1), while the sub-watershed 5, the lowest (5.51Mg.ha^-1). This remained in the three scenarios. Overall, scenario 2 had the lowest sediment yield (7.74Mg.ha^-1). Scenario 1 had 8.37 Mg.ha^-1 and scenario 3, 8.58Mg.ha^-1. SWAT was considered efficient to simulate the sediment yield by scenarios and by use, combining different thematic and tabular data when performing the necessary adjustments on their original database.

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.

Over the years, chitosan has been the subject of numerous studies and has gained significant popularity as a biomaterial due to its various characteristics, including biocompatibility, biodegradability, and bioactivity. In this work, chitosan fibres surface was modified with ursolic acid to improve their antibacterial properties by wet impregnation method. Five specimens of chitosan fibres were immersed in ursolic acid (UA) solution for varying immersion times of 1, 2, 4, 6, and 8 hours. Characterization was carried out by means of FTIR, SEM, UV-Vis spectroscopy; the results indicated an ongoing chemical reaction between chitosan and ursolic acid resulting in changes to the chemical structure. After 2 hours, the absorbance ratio remained constant; suggesting that the reaction had reached completion and the chemical structure of the sample remained stable. Antibacterial tests were performed on the resulting chitosan fibres against two bacterial strains. The fibres without ursolic acid did not exhibit any noteworthy antibacterial activity against either strain. However, the chitosan fibres modified with ursolic acid showed significant and almost strong antibacterial activity against the Gram-positive strain, S. aureus. These results suggest that chitosan fibres modified with ursolic acid could have potential applications as antibacterial materials, particularly against Gram-positive bacteria.

GIGANTEA (GI) is a gene involved in multiple biological functions, which were analysed and are partially conserved in a series of mono- and dicotyledonous plant species. The identified biological functions include control over the circadian rhythm, light signalling, cold tolerance, hormone signalling and photoperiodic flowering. The latter function is a central role of GI, as it involves a multitude of pathways, both dependent and independent of the gene CONSTANS(CO) as well as on the basis of interaction with miRNA. The complexity of gene function of GI increases due to the existence of paralogs showing changes in genome structure as well as incidences of sub- and neofunctionalization. We present an updated report of the biological function of GI, integrating late insights into its role in floral initiation, flower development and flower volatile production.