Sci

This paper proposes an innovative hybrid optimization framework for the optimal installation and operation of thyristor-switched capacitors (TSCs) within medium-voltage distribution networks, targeting both energy losses reduction and cost efficiency. The core of the approach combines the exploratory capabilities of the atan-sinc optimization algorithm (ASOA), a recent metaheuristic inspired by mathematical functions, with the local refinement power of the IPOPT solver within a master–slave architecture. This integrated method addresses the inherent complexity of a multi-objective, mixed-integer nonlinear programming problem that seeks to balance conflicting goals: minimizing annual system losses and investment costs. Extensive testing on IEEE 33- and 69-bus systems under fixed and dynamic reactive power injection scenarios demonstrates that our framework consistently delivers superior solutions when compared to traditional and state-of-the-art algorithms. Notably, the variable operation case yields energy savings of up to 12%, translating into annual monetary gains exceeding USD 1000 in comparison with the fixed support scenario.The solutions produce well-distributed Pareto fronts that illustrate valuable trade-offs, allowing system planners to make informed decisions. The findings confirm that the proposed strategy constitutes a scalable, and robust tool for reactive power planning, supporting the deployment of smarter and more resilient distribution systems. Full article

Football-themed eSports, combining entertainment and learning elements, are booming, offering benefits in terms of cognitive and motor skill development. Despite this, with the increasing use of eSports and their impact on cognitive and motor skills, there is still a paucity of empirical studies that systematically explore how cognitive stimulation from eSports can translate into psychomotor performance on the field, particularly with regard to linear speed. The aim of this study was to investigate the effects of an ecological–dynamic training protocol, integrated with football eSports, on the development of linear sprint speed in young soccer players. Thirty-two male youth football players (age range: 12–16 years) participated in the study. Participants were divided into an experimental group, which followed a combined ecological–dynamic training protocol including football eSports, and a control group, which performed standard training sessions. Pre- and post-intervention assessments of 30 m sprint performance were conducted using electronic timing gates. Statistical analysis using repeated-measures ANOVA indicated a marked improvement in 30 m sprint performance within the experimental group, decreasing from 4.908 s to 4.651 s. A significant time × group interaction was observed (F = 74.076, p < 0.001). Moreover, a robust main effect of time emerged (F = 141.12, p < 0.001), confirming consistent gains in linear sprint speed. Post hoc comparisons revealed significant differences across all assessment points (p < 0.001). The findings suggest that embedding football eSports into an ecologically grounded training framework may enhance the development of linear speed in young soccer players. This integrated approach shows potential as an innovative tool for performance enhancement, although further investigations are needed to confirm long-term efficacy and generalizability to other sporting populations. Full article

Electrical grids are currently facing new demands due to increased power consumption, growing interconnections, and limitations regarding transmission capacity. These factors introduce considerable challenges for the dispatch and operation of large-scale power systems, often resulting in congestion, energy losses, and high operating costs. To address these issues, this study presents a transmission line switching strategy, which is formulated as an optimal power flow problem with binary variables and solved via mixed-integer nonlinear programming. The proposed methodology was tested using MATLAB’s MATPOWER toolbox version 8.1, focusing on power systems with five and 3374 nodes. The results demonstrate that operating costs can be reduced by redistributing power generation while observing the system’s reliability constraints. In particular, disconnecting line 6 in the 5-bus system yielded a 13.61% cost reduction, and removing line 1116 in the 3374-bus system yielded cost savings of 0.0729%. These findings underscore the potential of transmission line switching in enhancing the operational efficiency and sustainability of large-scale power systems. Full article

Water supply networks in both developed and developing major cities worldwide were constructed many years ago. Currently, these systems face numerous challenges, including population growth, climate change, emerging technologies, and the policies implemented by local governments. Such factors can impact the design life of water infrastructure, leading to service pressure deficiencies. Consequently, water infrastructure must be reinforced to ensure an adequate and reliable service. This research presents the development of an analytical formulation for hydraulic installations with a pumping station, enabling the calculation of requirements for a new parallel pipeline within an existing water system without altering the current pipe resistance class. To implement the proposed solution, it is essential to maintain the initial pump head by adjusting the impeller size. A construction cost assessment is also undertaken to identify the most cost-effective reinforcement strategy, acknowledging that pipe costs vary significantly with diameter and material, and are proportional to the square of the diameter. The proposed methodology is applied to a 30 km pipeline with a 10% increase in demand, showing that a new parallel pipe of the same diameter as the existing hydraulic installation must be installed to minimise construction costs. A multi-parametric analysis was conducted employing machine learning presets with 309 dataset points. Full article

This study investigates the solubility correlation of oil extracted from Sabah green Robusta coffee (Coffea canephora) beans through supercritical carbon dioxide (SC-CO₂) extraction. Sabah, recognized as the largest coffee-producing region in Malaysia, serves as a significant source of Robusta beans for this research. The solubility of coffee bean oil was evaluated under varying pressures (10–30 MPa) and temperatures (40–80 °C). The maximum solubility, 2.681 mg/g CO₂, was recorded at 30 MPa and 40 °C, whereas the lowest solubility, approximately 0.440 mg/g CO₂, occurred at 20 MPa and 80 °C. A clear inverse relationship between solubility and temperature was observed, with solubility decreasing as temperature increased to 80 °C. Conversely, elevated pressure, particularly at 30 MPa, enhanced solubility due to the increased density and solvent power of SC-CO₂. Experimental data exhibited strong agreement with Chrastil’s equation, yielding a relatively low percentage error of 3.37%, compared with 14.57% for the del Valle-Aguilera model. These findings demonstrate the reliability of Chrastil’s model in predicting the solubility of Sabah green coffee bean oil in SC-CO₂. Overall, the research highlights the potential of SC-CO₂ extraction as a sustainable, solvent-free approach for obtaining high-quality coffee oil extracts, with promising applications in the food industry and possible extension to the recovery of other bioactive compounds in food processing. Full article

The proliferation of social network data has unlocked unprecedented opportunities for extensive, data-driven exploration of human behavior. The structural intricacies of social networks offer insights into various computational social science issues, particularly concerning social influence and information diffusion. However, modeling large-scale social network data comes with computational challenges. Though large language models make it easier than ever to model textual content, any advanced network representation method struggles with scalability and efficient deployment to out-of-sample users. In response, we introduce a novel approach tailored for modeling social network data in user-detection tasks. This innovative method integrates localized social network interactions with the capabilities of large language models. Operating under the premise of social network homophily, which posits that socially connected users share similarities, our approach is designed with scalability and inductive capabilities in mind, avoiding the need for full-graph training. We conduct a thorough evaluation of our method across seven real-world social network datasets, spanning a diverse range of topics and detection tasks, showcasing its applicability to advance research in computational social science. Full article

Modern military operations place significant physiological and cognitive demands on soldiers, necessitating innovative strategies to monitor and optimize health and performance. This narrative review examines the role of continuous physiological state monitoring and precision health strategies to enhance soldier resilience and operational readiness. Advanced wearable biosensors were analyzed for their ability to measure vital physiological parameters—such as heart-rate variability, core temperature, hydration status, and biochemical markers—in real-time operational scenarios. Emerging technological solutions, including AI-driven analytics and edge computing, facilitate rapid data interpretation and predictive health assessments. Results indicate that real-time physiological feedback significantly enhances early detection and prevention of conditions like exertional heat illness and musculoskeletal injuries, reducing medical attrition and improving combat effectiveness. However, ethical challenges related to data privacy, informed consent, and secure data management highlight the necessity for robust governance frameworks and stringent security protocols. Personalized training regimens and rehabilitation programs informed by monitoring data demonstrate potential for substantial performance optimization and sustained force readiness. In conclusion, integrating precision health strategies into military operations offers clear advantages in soldier health and operational effectiveness, contingent upon careful management of ethical considerations and data security. Full article

Fitting a sinusoidal model to a set of data points is a common practice in engineering, where one wants to estimate some quantities of interest by carrying out a sequence of measurements on a physical phenomenon. Analytical expressions are derived for the statistics of the root mean square value of the residuals from the least-squares sine-fitting procedure, when the data points are affected by phase noise or sampling jitter. The two analytical expressions derived, for the mean and for the variance, are numerically validated using a Monte Carlo-type procedure with simulated data for varying amounts of noise present, a varying number of data points, and varying signal amplitude. It will be shown that there is an excellent agreement between the numerical values obtained and those given by the analytical expressions proposed. These can be of use to engineers who need to compute confidence intervals for their estimations or who need to choose the number of signal data points that should be acquired in a given application. Full article

This study investigated the effects of ultrasonic treatment of olive paste prior to malaxation on oil yield (Y), enzyme activity and virgin olive oil (VOO) quality in four Croatian olive varieties: Istarska Bjelica, Rosulja, Oblica and Levantinka. The oils were extracted using the Abencor system according to a central composite experiment design, with treatment durations of 3–17 min and power levels of 256–640 W. The parameters analyzed included Y, oxidative stability index (OSI), antioxidant capacity (AC), phenolic and α-tocopherol content, volatile compounds, fatty acid profile, and the activity of lipoxygenase, β-glucosidase, polyphenol oxidase, and peroxidase. Olive variety was the most influential factor in all variables. The response surface methodology showed that ultrasonic treatment at low-to-medium intensity improved several quality attributes. For example, Y increased by 4% in Oblica, phenolic content increased by up to 17% in Istarska Bjelica, and OSI and AC increased by 13–15% in Istarska Bjelica and Levantinka. In contrast, longer treatment and higher ultrasound power had a negative effect. No significant differences were found in other parameters examined. Overall, the application of ultrasound led to measurable, though moderate, improvements in Y and VOO quality, with results strongly dependent on olive variety and treatment conditions. These results underline the need for further optimization tailored to each variety. Full article

Food waste from fish processing contributes significantly to environmental pollution, and fish skin is often discarded despite being a rich collagen source. This study evaluated the efficacy and consumer satisfaction of a ready-to-drink collagen supplement made from hydrolyzed collagen derived from seabass skin. The compositional analysis of this study revealed α-amino groups, hydroxyproline, and amino acids essential for skin elasticity, hydration, and tissue repair. A 30-day clinical trial was conducted in 36 Thai volunteers who were aged between 20 to 70 years, and their skin condition was assessed using a facial skin analyzer and a moisture analyzer on days 0, 15, and 30. Participants also completed self-perception and sensory satisfaction questionnaires. The results showed improved skin moisture, reduced pore size, and smoother skin texture. Participants reported high satisfaction, especially regarding increased moisture and skin smoothness. Sensory score evaluation showed favorable scores for color and taste; however, odor was the least preferred attribute with the lowest score. Notably, no adverse effects were reported throughout this study. The findings suggest that fish skin-derived collagen supplements can enhance skin appearance while offering a sustainable approach that converts fish by-products into functional skincare solutions aligned with global sustainability goals. Full article

Eutrophication is a significant issue in aquatic systems that receive wastewater from anthropogenic sources. The reduction of phosphate concentration in wastewater and water bodies is essential to reduce the risk of eutrophication. In this study, biomass obtained from Arthrospira platensis was used to reduce the phosphorus concentration in water. The biomass samples were characterized by spectroscopic and morphological techniques, such as vibrational spectroscopy (FTIR and Raman) and microscopy assay (SEM). Adsorption studies were conducted to evaluate the removal efficacy of the biomass. Phosphate removal capacity was strongly influenced by pH, with the highest effectiveness observed under acidic conditions (88% removal at pH 4.4) and rapid initial adsorption reaching equilibrium. Kinetic modelling showed a maximum removal efficacy (q_e = 2.4 mg g⁻¹ and k₂ = 0.305 min⁻¹). Isothermal adsorption analysis showed that the Langmuir model described properly experimental results showing physical chemical parameters (q_max = 2.8 mg g⁻¹ and K_L = 1.41 L mg⁻¹). Full article

Access to clean and safe drinking water is crucial for global health and well-being, formally recognised as a fundamental human right within the United Nations’ Sustainable Development Goals. However, the integrity of water supply is increasingly threatened by microbial contamination, a risk aggravated by the conditions driven from climate change, which promotes the proliferation, resilience, and facilitation of the dissemination of microorganisms. Pathogens like Legionella, Cryptosporidium, Giardia, Escherichia coli, and Vibrio cholerae can be present in water supplies, developing survival strategies (e.g., biofilm, cysts, inside protozoa). The risk of microorganisms in water requires both effective treatment at drinking water treatment plants and vigilant process control throughout drinking water distribution systems. Globally, a great number of disease outbreaks have been linked to contaminated drinking water. Despite strong regulations in the European Union and the Drinking Water Directive aim to guarantee the safety and quality of potable water, outbreaks persist; recent Legionella cases in Italy in 2024 and Cryptosporidiosis in 2019 linked to rainfalls and insufficient disinfection treatment, respectively, are an example of this. Although cholera is not common in Europe, there is evidence of high incidence of this disease in Africa mainly due to the poor hygienic conditions in the DWTS. In Europe, the data of waterborne diseases and outbreaks are submitted by European Countries to the European Centre for Disease Prevention and Control (ECDC) to give faster and effective response to outbreaks. Determining the origin of the contamination is essential to face the solution of outbreaks and ensure public health safety. Full article

The aim of the present study was to examine the impact of maturation and relative age on the anthropometric variables and physical performance of young elite volleyball players according to sex and playing positions. The sample included 207 girls (13.59 ± 1.74 years) and 59 boys (14.30 ± 1.48 years) who were selected to participate in the 2020–2025 Spanish National Volleyball Programme. Maturity status was estimated using a non-invasive method (percentage of predicted adult height). Relative age was calculated based on date of birth and expressed as decimal age (0–0.99). The physical tests carried out were spike jump reach, vertical jump, 3 × 9, and strength–endurance–agility–coordination (FRAC) tests. The results showed that there was no impact of the interaction between maturity status and relative age on physical performance, except in the 3 × 9 test by boys in the wing-spiker position. Moreover, maturity status had a greater influence on physical test performance than that of relative age. Specifically, maturation served as a statistically significant positive predictor of height in the SJR test for girls who were all-around players, explaining 71.58% of the variance. In addition, an advanced maturity status correlated with better physical performance outcomes, especially in the all-around player and wing-spiker playing positions in boys and the middle-blocker and all-around player playing positions in girls. Coaches and stakeholders should implement strategies to reduce bias, especially regarding maturation, with the aim of retaining the most physically talented late-maturing players, considering differences by playing position and sex. Full article

Large language models (LLMs) have recently demonstrated remarkable capabilities in natural language processing, mathematical reasoning, and code generation. However, their potential for solving differential equations—fundamental to applied mathematics, physics, and engineering—remains insufficiently explored. For the first time, we applied LLMs as translators from the textual form of an equation into the textual representation of its analytical solution for a broad class of equations. More precisely, we introduced a benchmark and fine-tuning protocol for differential equation solving with pre-trained LLMs. We curated a dataset of 300,000 differential equations and corresponding solutions to fine-tune T5-small, Phi-4-mini, DeepSeek-R1-Distill-Qwen, and two Mamba variants (130M and 2.8B parameters). Performance was evaluated using BLEU and TeXBLEU metrics. Phi-4-mini achieved the best results, with average BLEU > 0.9 and TeXBLEU > 0.78 across all considered equation classes, which shows the strong generalization abilities of the model. Therefore, this model should be further investigated on a broader class of differential equations and potentially can be used as a part of mathematical agents for solving more complex particular tasks, for example, from physics or engineering. Based on our results, DeepSeek-R1-Distill-Qwen consistently underperformed, while T5 showed strong results for the most frequent equation type but degraded on less common ones. Mamba models achieved the highest TeXBLEU scores despite relatively low BLEU, attributable to their production of lengthy outputs mixing correct expressions with irrelevant ones. Full article

Legumes contain variable amounts of bioactive substances, including protease inhibitors, which have a protective role against herbivorous insects and bacterial, fungal, and viral pathogens. However, their potential for application in agricultural and medicinal practices requires additional investigation. Bitter vetch (Vicia ervilia (L.) Willd.) is an ancient crop that is now underutilized, and its potential for various applications has recently been reevaluated. In this study, we report the purification, characterization, and bioactive properties of a protease inhibitor against trypsin/chymotrypsin-type proteases (vPI) from bitter vetch seeds. The inhibitor was purified by extraction under acidic conditions, ammonium sulfate fractionation, and size-exclusion chromatography. Its inhibitory specificity, thermostability, pH stability, and antioxidant and antimycotic activity against Alternaria alternata, Alternaria solani, Aspergillus fumigatus, Aspergillus niger, Candida albicans, Fusarium solani, Mucor michei, Penicillium griseofulvum, and Rhizopus oryzae were evaluated. Purified vPI presented superoxide anion scavenging power and antifungal activity in response to all tested strains except M. michei. It had the strongest effect on F.solani and A. solani, and a moderate effect on P. griseofulvum and C. albicans. The treatment of A. alternata, R. oryzae, A. fumigatus, and A. niger demonstrated high efficacy within the initial 24h but declined thereafter. The usefulness and limitations of the vPI application in practice are discussed. Full article

Recent advancements in carbon nanotubes and graphene have driven significant research into other low-dimensional materials, with phosphorus-based materials emerging as a notable area of interest. Phosphorus nanowires and thin sheets show promise for applications in devices such as batteries, photodetectors, and field-effect transistors. However, the presence of multiple allotropes of phosphorus complicates their characterization. Accurate identification of these allotropes is essential for understanding their physical, optical, and electronic properties, which influence their potential applications. Researchers frequently encounter difficulties in consolidating literature for the confirmation of the structure of their materials, a process that can be time-consuming. This minireview addresses this issue by providing a comprehensive, side-by-side comparison of Raman and X-ray diffraction characteristic peaks, as well as electron microscopic images and lattice spacings, for the various phosphorus allotropes. To our knowledge, this is the first compilation to integrate all major structural fingerprints into unified summary tables, enabling rapid cross-referencing. This resource aims to support researchers in accurately identifying phosphorus phases during synthesis and device fabrication workflows. For example, distinguishing between red phosphorus polymorphs is crucial for optimizing anode materials in sodium-ion batteries, where electrochemical performance is phase-dependent. Full article

This study investigates the numerical prediction of the sonic boom phenomenon in supersonic aircraft by evaluating the near-field pressure signatures of three different aeroshapes. Two computational fluid dynamics (CFD) solvers, the open-source SU2 Multiphysics code and ANSYS Fluent, were employed to assess their effectiveness in modeling the aerodynamic flow field. A preliminary validation of numerical methods was conducted against numerical data available from the Sonic Boom Prediction Workshops (SBPW) organized by NASA, ensuring simulation reliability. Particular attention is paid to the topology of the mesh grid, exploring hybrid approaches that combine structured and unstructured grids to optimize the accuracy of pressure wave transmission. In addition, different numerical schemes were analyzed to determine the best practices for sonic boom simulations. The proposed methodology was finally applied to three supersonic aircraft developed within the European project MORE&LESS, demonstrating the capability of the model to estimate shock wave generation, evaluate the aeroacoustic performance of different supersonic aeroshapes from Mach 2 to Mach 5, and provide predictions to support ground-level noise assessment. The findings of this study contribute to the definition of a comprehensive workflow for sonic boom evaluation, providing a reliable methodology for exploring future supersonic aircraft designs. Full article

The growing interest in sustainable materials has encouraged the valorization of agro-industrial byproducts for pharmaceutical, nutraceutical, and food applications. This study evaluated yellow pitaya peel powder, obtained via convective and refractance window drying, as a diluent in immediate-release quercetin tablets. The powders were characterized by physicochemical, granulometric, morphological, and surface properties, and compared with conventional excipients, including partially pregelatinized corn starch and spray-dried lactose monohydrate. Refractance window drying improved solubility, flowability, and structural integrity, while convective drying produced finer, more porous particles with lower water activity. Tablets formulated with both powders showed adequate hardness, low friability, and disintegration times under five minutes. All systems achieved complete quercetin release. Kinetic modeling revealed anomalous, matrix-regulated transport, with Weibull and Modified Hill models providing the best fit. Based on these results, pitaya peel powder could be considered a suitable diluent for the development of immediate-release tablets, offering functional performance aligned with sustainable formulation strategies. Full article

Grape pomace (i.e., the residual skins, seeds, and pulp left after vinification) retains up to 70% of the fruit’s original phenolic compounds and is also rich in dietary fiber. As such, because this by-product is generated in large quantities worldwide and its disposal is both technologically problematic and costly, reusing it as a food ingredient could simultaneously mitigate environmental burdens, lower winery waste-management expenses, and enhance the nutritional profile of fortified foods. In this context, this study investigated the nutritional enrichment of dark chocolate by incorporating flour produced from red (cv. Syrah) and white (cv. Arinto) grape pomace at three levels (5, 10, and 15% w/w). Formulated chocolates and controls were manufactured under industrial tempering conditions and subsequently analyzed for protein, lipids, sugars, dietary fiber, total phenolic content, antioxidant capacity (DPPH and ORAC), color, texture, and consumer perception (hedonic test). All fortified samples showed higher fiber and antioxidant activity than the control, with “White_15” showing higher fiber content (43.1%) and “Red_5” for ORAC (69,483 µmol TE/100 g) and DPPH (6587 µmol TE/100 g). Dietary fiber showed an increase in content with the increase in grape pomace incorporation, regardless of the type (red or white). Texture softening was observed in all fortified chocolates independently of the incorporation level or type (red or white). Principal Component Analysis (PCA) and hierarchical clustering confirmed clear separation between control and fortified chocolates based on the parameters analyzed. Sensory evaluation with untrained panelists revealed good overall acceptability across all formulations. These findings demonstrate that grape pomace flour can be effectively valorized as a functional ingredient in dark chocolates, supporting circular economy practices in the wine and confectionery sectors while delivering products with enhanced health-promoting attributes (nutritional and antioxidant). Full article