Search Results (267)

Water infiltration into soil is a key process in regulating the hydrological cycle and sustaining ecosystem services in high-Andean environments. However, limited information is available regarding its dynamics in these ecosystems. This study evaluated the influence of three types of vegetation cover and soil properties on water infiltration in a high-Andean environment. A double-ring infiltrometer, the Water Drop Penetration Time (WDPT, s) method, and laboratory physicochemical characterization were employed. Soils under forest cover exhibited significantly higher quasi-steady infiltration rates (i_s, 0.248 ± 0.028 cm·min⁻¹) compared to grazing areas (0.051 ± 0.016 cm·min⁻¹) and agricultural lands (0.032 ± 0.013 cm·min⁻¹). Soil organic matter content was positively correlated with i_s. The modified Kostiakov infiltration model provided the best overall fit, while the Horton model better described infiltration rates approaching i_s. Sand and clay fractions, along with K⁺, Ca²⁺, and Mg²⁺, were particularly significant during the soil’s wet stages. In drier stages, increased Na⁺ concentrations and decreased silt content were associated with higher water repellency. Based on WDPT, agricultural soils exhibited persistent hydrophilic behavior even after drying (median [IQR] from 0.61 [0.38] s to 1.24 [0.46] s), whereas forest (from 2.84 [3.73] s to 3.53 [24.17] s) and grazing soils (from 4.37 [1.95] s to 19.83 [109.33] s) transitioned to weakly or moderately hydrophobic patterns. These findings demonstrate that native Andean forest soils exhibit a higher infiltration capacity than soils under anthropogenic management (agriculture and grazing), highlighting the need to conserve and restore native vegetation cover to strengthen water resilience and mitigate the impacts of land-use change. Full article

Simian foamy virus (SFV) is a retrovirus that infects primates. However, epidemiological studies of SFV are often limited to captive populations. The southeastern Brazilian Atlantic Forest is home to both an endemic, endangered species, Leontopithecus rosalia, and an introduced species, Leontopithecus chrysomelas, to which no data on SFV exist. In this study, we assessed the molecular prevalence of SFV, their viral load, and their phylogenetic relationship in these two species of primates. Genomic DNA was extracted from 48 oral swab samples of L. chrysomelas and 102 of L. rosalia. Quantitative PCR (qPCR) was performed to diagnose SFV infection and quantify viral load. SFV prevalence was found to be 23% in L. chrysomelas and 33% in L. rosalia. No age-related differences in prevalence were observed; however, L. rosalia showed a higher mean viral load (3.27 log10/10⁶ cells) compared to L. chrysomelas (3.03 log10/10⁶ cells). The polymerase gene sequence (213 pb) of L. rosalia (SFVlro) was clustered within a distinct SFV lineage found in L. chrysomelas. The estimated origin of SFVlro dated back approximately 0.0836 million years ago. Our study provides the first molecular prevalence data for SFV in free-living Leontopithecus populations while offering insights into the complex evolutionary history of SFV in American primates. Full article

This study is among the first to characterize the tensile response of composites with quadriaxial glass fiber fabrics designed for marine structural applications. Four composite configurations were fabricated at laboratory scale, combining two matrix types (unsaturated polyester resin and epoxy resin) and the presence or absence of a Coremat Xi3 middle layer. Tensile tests were conducted at four test rates (10 mm/min, 200 mm/min, 500 mm/min, and 1000 mm/min), ranging from quasi-static to moderately dynamic conditions. Tests were conducted using the Instron 5982 universal testing machine (from Laboratory for Advanced Materials and Tribology, INCAS Bucharest, Romania). The specimens have a rectangular cross section, in agreement with SR EN ISO 527-4:2023. For strain measurements, an Instron advanced video extensometer (AVE) was used. Key mechanical parameters, such as maximum force, tensile strength, Young’s modulus, strain at break, and energy absorption, were extracted and analyzed. Results show that the polyester-based composite without a mat interlayer displayed the best overall performance, with the highest ultimate strength (~280 MPa), significant energy absorption (~106 J), and a consistent increase in ductility with increasing test rate. In contrast, the epoxy composite with Coremat Xi3 exhibited lower stiffness and strength, but higher strain and energy absorption at higher test rates, indicating a progressive failure behavior. These findings enhance the understanding of the tensile response of composites made of quadriaxial glass fiber fabric and provide valuable design data for structural components in marine environments, where both strength and energy absorption are essential. These insights support producers and end-users of non-crimp fabrics in making experimentally based selections of a composite, technological strategies, and design optimization. Full article

Native bean genotypes (Phaseolus vulgaris L.) play a crucial role in ensuring food security in the Andean region. However, their cultivation faces challenges, such as low yields and a high dependence on nitrogen fertilizers. Addressing these issues requires the development of sustainable strategies to enhance productivity. This study evaluated the interaction between Rhizobium phaseoli inoculation and three levels of phosphorus (P) and potassium (K) fertilization on the growth, yield, and nutritional profile of the ‘Tiachos bayo’ native bean variety under Andean field conditions. Two R. phaseoli strains (UNC-1 and CIAT-2) were tested in combination with three levels of chemical fertilization (0%, 50%, and 100%) using a factorial design under field conditions. Parameters assessed included nodule number, plant height, phenology, yield, and proximal grain composition. Results indicated that inoculation and fertilization levels significantly influenced nodulation, phenological phases, and crop yield. The highest yield (2172 kg·ha⁻¹) and nodule number (78) were observed with the combined treatment of R. phaseoli CIAT-2 strain with 100% fertilization. It was concluded that R. phaseoli inoculation, when integrated with appropriate fertilization, enhances the productivity of native beans. Full article

This study aimed to identify genetic variants using a customized next-generation sequencing (NGS) panel for pediatric myelodysplastic syndrome (pMDS) and to explore their associations with cytogenetic and clinical characteristics. Cytogenetic analyses were conducted using G-banding and fluorescence in situ hybridization. NGS was performed with the Ion Torrent Personal Genome Machine for the following genes: GATA2, RUNX1, CEBPA, ANKRD26, ETV6, SAMD9, SAMD9L, PTPN11, NRAS, SETBP1, DDX41, TP53, FLT3, SRP72, and JAK3. Analyses were performed with Ion Reporter 5.20.8.0 software. Genetic variants were classified using the dbSNP, 1000 Genomes, COSMIC, and Varsome databases. We analyzed 25 cases of pMDS; 15 presented abnormal karyotypes, and 19 showed genetic variants. Among the 29 variants identified across 12/15 genes, 27% were pathogenic and 14% were likely pathogenic, with NRAS and GATA2 most frequently associated with disease progression. A new somatic variant of uncertain significance in SETBP1 was detected in seven patients showing heterogeneous clinical outcomes. Genetic variants were found in 7/10 patients with normal karyotypes, indicating that submicroscopic alterations can shed light on disease biology. Our results highlight the critical role of a targeted NGS panel in identifying molecular alterations associated with pMDS pathogenesis, thereby enhancing diagnostic precision, prognosis, and aiding in treatment selection. Full article

Air quality forecasts play a crucial role in informing the public about atmospheric pollutant levels that pose risks to human health and the environment. The accuracy of these forecasts strongly depends on the quality and resolution of the input data used in the modelling process. At HungaroMet, the Hungarian Meteorological Service, the CHIMERE chemical transport model is used to provide two-day air quality forecasts for the territory of Hungary. This study compares two configurations of the CHIMERE model: the current operational setup, which uses climatological averages from the LMDz-INCA database for boundary conditions, and a test configuration that incorporates real-time boundary conditions from the CAMS global forecast. The primary objective of this work was to assess how the use of real-time versus climatological boundary conditions affects modelled concentrations of key pollutants, including NO₂, O₃, PM₁₀, and PM_2.5. The model results were evaluated against observational data from the Hungarian Air Quality Monitoring Network using a range of statistical metrics. The results indicate that the use of real-time boundary conditions, particularly for aerosol-type pollutants, improves the accuracy of PM₁₀ forecasts. This improvement is most significant under meteorological conditions that favour the long-range transport of particulate matter, such as during Saharan dust or wildfire episodes. These findings highlight the importance of incorporating dynamic, up-to-date boundary data, especially for particulate matter forecasting—given the increasing frequency of transboundary dust events. Full article

Contextualization: Lifestyle changes, such as smoking cessation, physical activity, and healthy eating, are essential for the treatment and prevention of cardiovascular diseases. The 2021 update of the European Society of Cardiology (ESC) guidelines highlights the need to investigate the adherence to the Mediterranean diet in patients who have suffered acute myocardial infarction (AMI). Objective: The aim of this study was to investigate the adherence to the Mediterranean diet and dietary 2021 ESC guidelines of individuals who have suffered AMI and to evaluate the sociodemographic and lifestyle factors associated with the adherence. Methods: A cross-sectional study was conducted using baseline data from participants prior to enrollment in the DICA-NUTS multicenter clinical trial. The dietary intake was assessed using a food frequency questionnaire and 24 h dietary recall. The nutrient intake was compared with the nutritional recommendations of the 2021 ESC guidelines, and the adherence to the Mediterranean diet was analyzed using a Mediterranean diet score. Furthermore, the analyses of the factors associated with the Mediterranean diet score and 2021 ESC were performed. Analyses were conducted using Stata Data Analysis and Statistical Software version 15.0. Values were considered statistically significant when the p-value < 0.05. Results: Among 488 participants aged ≥ 40 years, moderate adherence to the Mediterranean diet was observed obtaining an average of nine points, with a low intake of vegetables, fish, and cereals. The protein intake was adequate with 18% (interquartile range [IQR] 15.0–23.1) of the total energy value, and the saturated fat intake was high with 9.7% (IQR 7.3–12.7) of the total energy value, while the carbohydrate and total fat intake was adequate. According to the 2021 ESC guidelines, the fiber intake was low with more than 79% of the sample consuming less than 30 g per day. The multivariate analysis using the 2021 ESC dietary recommendations showed that older age (≥60 years) [odds ratio (OR) = 1.63; 95% confidential interval (CI) = 1.44–1.91], never smoking (OR = 1.34; 95% CI = 1.17–1.65), and higher education (OR = 1.37; 95% CI = 1.17–1.77) were correlated with an increased fruit and vegetable intake. Non-white, never-smokers, and former smokers were more likely to consume fish. The alcohol scores were higher in older age participants and women. The dairy scores increased with older age, while the cereal scores decreased. No significant association was found for legumes. Conclusions: According to the scores used, the diet of these individuals moderately reflects the Mediterranean characteristics. Analyzing the 2021 ESC dietary recommendations, the studied population was inadequate. This study found different factors associated with an adequate food intake in post-AMI patients. The highlight of this study was that older age is more likely to increase fruit, vegetable, and dairy intake. Full article

Background: Intestinal metaplasia (IM) is a precancerous gastric condition that requires accurate histopathological diagnosis to enable early intervention and cancer prevention. Traditional evaluation of H&E-stained tissue slides can be labor-intensive and prone to interobserver variability. Recent advances in deep learning, particularly transformer-based models, offer promising tools for improving diagnostic accuracy. Methods: We propose ViSwNeXtNet, a novel patch-wise ensemble framework that integrates three transformer-based architectures—ConvNeXt-Tiny, Swin-Tiny, and ViT-Base—for deep feature extraction. Features from each model (12,288 per model) were concatenated into a 36,864-dimensional vector and refined using iterative neighborhood component analysis (INCA) to select the most discriminative 565 features. A quadratic SVM classifier was trained using these selected features. The model was evaluated on two datasets: (1) a custom-collected dataset consisting of 516 intestinal metaplasia cases and 521 control cases, and (2) the public GasHisSDB dataset, which includes 20,160 normal and 13,124 abnormal H&E-stained image patches of size 160 × 160 pixels. Results: On the collected dataset, the proposed method achieved 94.41% accuracy, 94.63% sensitivity, and 94.40% F1 score. On the GasHisSDB dataset, it reached 99.20% accuracy, 99.39% sensitivity, and 99.16% F1 score, outperforming individual backbone models and demonstrating strong generalizability across datasets. Conclusions: ViSwNeXtNet successfully combines local, regional, and global representations of tissue structure through an ensemble of transformer-based models. The addition of INCA-based feature selection significantly enhances classification performance while reducing dimensionality. These findings suggest the method’s potential for integration into clinical pathology workflows. Future work will focus on multiclass classification, multicenter validation, and integration of explainable AI techniques. Full article

The provision of food in pre-Inca/Inca cultures (1000 BC–≈1532 AD) in environments near Lake Titikaka (approximately 4000 m above sea level) was possible through an agricultural technique called “Waru-Waru”, which consists of filling the space (volume) between rows of land containing plants that are cultivated (a series of earth platforms surrounded by water canals) with water, using water as thermal energy storage to store energy during the day and to regulate the temperature of the soil and crop atmosphere at night. The problem is that these cultures left no evidence in written documents that have been preserved to this day indicating the mathematical models, the physics involved, and the experimental part they performed for the research, development, and innovation of the “Waru-Waru” technique. From a review of the existing literature, there is (1) bibliography that is devoted to descriptive research (about the geometry, dimensions, and shapes of the crop fields (and more based on archaeological remains that have survived to the present day) and (2) studies presenting complex mathematical models with many physical parameters measured only with recently developed instrumentation. The research objectives of this paper are as follows: (1) develop a mathematical model that uses finite differences in fluid mechanics, thermodynamics, and heat transfer to explain the experimental and theory principles of this pre-Inca/Inca technique; (2) the proposed mathematical model must be in accordance with the mathematical calculation tools available in pre-Inca/Inca cultures (yupana and quipu), which are mainly based on arithmetic operations such as addition, subtraction, and multiplication; (3) develop a mathematical model in a sequence of steps aimed at determining the best geometric form for thermal energy storage and plant cultivation and that has a simple design (easy to transmit between farmers); (4) consider the assumptions necessary for the development of the mathematical model from the point of view of research on the geometry of earth platforms and water channels and their implantation in each cultivation area; (5) transmit knowledge of the construction and maintenance of “Waru-Waru” agricultural technology to farmers who have cultivated these fields since pre-Hispanic times. The main conclusion is that, in the mathematical model developed, algebraic mathematical expressions based on addition and multiplication are obtained to predict and explain the evolution of soil and water temperatures in a specific crop field using crop field characterization parameters for which their values are experimentally determined in the crop area where a “Waru-Waru” is to be built. Therefore, the storage of thermal energy in water allows crops to survive nights with low temperatures, and indirectly, it allows the interpretation that the Inca culture possessed knowledge of mathematics (addition, subtraction, multiplication, finite differences, approximation methods, and the like), physics (fluids, thermodynamics, and heat transfer), and experimentation, with priority given to agricultural techniques (and in general, as observed in all archaeological evidence) that are in-depth, exact, practical, lasting, and easy to transmit. Understanding this sustainable energy storage technique can be useful in the current circumstances of global warming and climate change within the same growing areas and/or in similar climatic and environmental scenarios. This technique can help in reducing the use of fossil or traditional fuels and infrastructure (greenhouses) that generate heat, expanding the agricultural frontier. Full article

Background/Objectives: Leadership in nursing plays a pivotal role in the provision of high-quality healthcare. It is, therefore, of paramount importance to understand the challenges encountered by newly qualified nurses when assuming leadership responsibilities. This scoping review protocol aims to identify and map these challenges, thereby facilitating the development of more effective interventions and support programmes. The data collection and analysis were conducted from January 2024 to March 2024. Methods: The review was conducted in accordance with the Joanna Briggs Institute (JBI) guidelines for scoping reviews and the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) recommendations. A comprehensive search was undertaken across MEDLINE, CINAHL, Web of Science, Scopus, LILACS, and SciELO databases, in addition to a search for the grey literature. Study selection was performed by two independent reviewers, applying pre-defined inclusion and exclusion criteria. The data were extracted using a standardised form and analysed descriptively. Results: The review identified several key challenges faced by newly qualified nurses in leadership roles, including conflict management, decision-making under pressure, and effective communication. These findings highlight the complexity of transitioning from academic training to professional practice. The results provide a comprehensive overview of these challenges, enabling the identification of gaps in the existing knowledge base and informing the direction of future research and interventions. Conclusions: The findings of this review will contribute to the enhancement of healthcare quality and the promotion of the professional development of newly qualified nurses. This research underscores the importance of developing targeted interventions and support systems to address the specific challenges identified, thereby influencing nursing practice and policy. Full article

This research examines the link between business models and entrepreneurial capabilities among social assistance program participants who are aging adults in an emerging economic environment. The research targets the insufficient use of entrepreneurial abilities in seniors to advance their active aging potential while enhancing their life quality. This study collected data from selected participants by using Osterwalder and Pigneur’s business model framework as a basis for their structured questionnaire, which followed a quantitative–qualitative method. Researchers applied Spearman’s Rho statistical methods to measure relations between business elements and skills in self-confidence, creativity, initiative, perseverance, and teamwork demonstrated by entrepreneurs. The study results clearly showed that properly executed business models create substantial growth in entrepreneurial abilities among people of advanced age. This study contributes novel empirical evidence from a rural Peruvian context, confirming that structured business model training is positively associated with entrepreneurial outcomes among elderly populations. The findings (r = 0.755, p < 0.001) support the urgency of integrating capability-building into social assistance schemes. These results emphasize how targeted training programs should empower this population since this initiative supports Sustainable Development Goals like “Decent Work and Economic Growth” (SDG 8) and “Reduced Inequalities” (SDG 10). The analysis demonstrates that teaching entrepreneurial abilities to mature individuals leads to better social entrepreneurship sustainability together with superior economic involvement and social connections. Full article

Background: Low birth weight in newborns is of multifactorial origin (fetal, maternal, placental, and environmental factors), and in one-third of cases, the cause is of unknown origin, with high infant morbidity and mortality. The main treatment for regaining weight and height in children with low birth weight is the application of growth hormones. However, their role as a protective factor to prevent an increase in body composition and the development of metabolic diseases is still poorly understood. Methodology: A case–control study was conducted in a cohort of patients consulted at the CES Pediatric Endocrinology Clinic, Medellín, Colombia, between 2008 and 2018. We evaluated sociodemographic and clinical variables. Additionally, the identification of differential patterns of genomic methylation between cases (treated with growth hormone) and controls (without growth hormone treatment) was performed. The groups were compared using Fisher’s exact test for qualitative variables and Student’s t-test for the difference in means in independent samples. The correlation was evaluated with the Pearson coefficient. Results: Regarding clinical manifestations, body mass index (BMI) was higher in children who did not receive growth hormone treatment, higher doses of growth hormone treatment helped reduce body mass index (R: −0.21, and p = 0.067), and the use of growth hormone was related to a decrease in triglyceride blood concentrations (p = 0.06); these results tended towards significance. Regarding genome-wide methylation patterns, the following genes were found to be hypermethylated: MDGA1, HOXA5, LINC01168, ZFYVE19, ASAH1, MYH15, DNAJC17, PAMR1, MROCKI, CNDP2, CBY2, ZADH2, HOOK2, C9orf129, NXPH2, OSCP1, ZMIZ2, RUNX1, PTPRS, TEX26, EIF2A4K, MYO1F, C2orf69, and ZSCAN1. Meanwhile, the following genes were found hypomethylated: C10orf71-AS1, ZDHHC13, RPL17, EMC4, RPRD2, OBSCN-AS1, ZNF714, MUC4, SUGT1P4, TRIM38, C3, SPON1, NGF-AS1, CCSER2, P2RX2, LOC284379, GGTA1, NLRP5, OR51A4, HLA-H, and TTLL8. Conclusions: Using growth hormone as a treatment in SGA newborns helps regain weight and height. Additionally, it could be a protective factor against the increase in adolescent body composition. Full article

Background: Testicular germ cell tumors (GCTs) are highly curable malignancies, particularly when diagnosed early. However, cardiac metastases are exceedingly rare—occurring in less than 1% of cases—and pose significant diagnostic and therapeutic challenges. Intracardiac involvement is exceptionally uncommon and typically necessitates a multidisciplinary approach for optimal management. Objective: To present a rare case of metastatic testicular GCT with intracardiac extension in a young male, underscoring the diagnostic complexity and therapeutic considerations of this unusual clinical scenario. Case Report: A 23-year-old male presented with diffuse abdominal pain, dyspnea, and a palpable right testicular mass. Imaging revealed a testicular tumor with metastases to the lungs, liver, retroperitoneal lymph nodes, and a large intracardiac mass extending from the inferior vena cava into the right atrium. Histopathology confirmed a mixed-germ cell tumor consisting of 75% seminoma, 20% embryonal carcinoma, and 5% teratoma. The patient underwent radical right orchiectomy followed by chemotherapy with the BEP regimen (bleomycin, etoposide, cisplatin). Cardiac magnetic resonance imaging confirmed the intracardiac mass, which significantly decreased in size after treatment. Serum tumor markers (AFP and β-hCG) also showed substantial post-treatment declines, corresponding with clinical improvement. Conclusions: This case highlights a rare presentation of metastatic testicular GCT with intracardiac involvement, emphasizing the importance of recognizing atypical metastases. Despite its complexity, the patient responded well to chemotherapy, reinforcing the effectiveness of current treatments. Long-term follow-up and a multidisciplinary approach are essential for monitoring recurrence and complications, contributing to the understanding of rare metastatic patterns and the need for further research. Full article

Clinopodium bolivianum (Benth.) Kuntze, commonly known as muña, inca muña or koa, has traditionally been used for its medicinal properties in digestive disorders. Some studies have revealed its antioxidant potential and antibacterial activity. This study determined the volatile components, evaluated the antioxidant capacity of C. bolivianum essential oil and its incorporation into three hair cosmetic formulations: shampoo, combing cream, and capillary lotion. Gas Chromatography–Mass Spectrometry (GC–MS) confirmed pulegone as the main component, accounting for 66.85% of the essential oil. The antioxidant activity was assessed using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) assays, with Trolox (6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid) as a reference compound. The essential oil exhibited significant radical scavenging activity, with IC₅₀ values of 1344.0 ± 12.23 µg/mL for DPPH and 40.125 ± 1.25 µg/mL for ABTS. Among the formulated cosmetic products, the combing cream containing 0.5% of the essential oil demonstrated the highest antioxidant activity, with IC₅₀ values of 0.72 µg/mL (DPPH) and 0.068 µg/mL (ABTS). In contrast, the shampoo and capillary lotion showed lower antioxidant potential. The stability evaluation confirmed that all formulations maintained their physicochemical properties under accelerated conditions. These findings highlight the potential application of C. bolivianum essential oil as a natural antioxidant in cosmetic formulations, contributing to its protective and functional properties. Full article

Defect detection is still challenging to apply in reality because the goal of the entire classification assignment is to identify the exact type and location of every problem in an image. Since defect detection is a task that includes location and categorization, it is difficult to take both accuracy factors into account when designing related solutions. Flaw detection deployment requires a unique detection dataset that is accurately annotated. Producing steel free of flaws is crucial, particularly in large production systems. Thus, in this study, we proposed a novel deep learning-based flaw detection system with an industrial focus on automated steel surface defect identification. To create processed images from raw steel surface images, a novel method was applied. A new deep learning model called the Parallel Attention–Residual CNN (PARC) model was constructed to extract deep features concurrently by training residual structures and attention. The Iterative Neighborhood Component Analysis (INCA) technique was chosen for distinguishing features to lower the computational cost. The classification assessed the SVM method using a convincing dataset (Severstal: Steel Defect Detection). The accuracy in both the binary and multi-class classification tests was above 90%. Moreover, using the same dataset, the suggested model was contrasted with pre-existing models. Full article