Sci, Volume 7, Issue 3 (September 2025) – 49 articles

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

The aviation industry prioritizes safety and has embraced innovative approaches for both reactive and proactive safety measures. Machine learning (ML) has emerged as a useful tool for aviation safety. This systematic literature review explores ML applications for safety within the aviation industry over the past 25 years. Through a comprehensive search on Scopus and backward reference searches via Google Scholar, 87 of the most relevant papers were identified. The investigation focused on the application context, ML techniques employed, data sources, and the implications of contextual nuances for safety analysis outcomes. ML techniques have been effective for post-accident analysis, predictive, and real-time incident detection across diverse aviation scenarios. Supervised, unsupervised, and semi-supervised learning methods, including neural networks, decision trees, support vector machines, and deep learning models, have all been applied for analyzing accidents, identifying patterns, and forecasting potential incidents. Notably, data sources such as the Aviation Safety Reporting System (ASRS) and the National Transportation Safety Board (NTSB) datasets were the most used. Transparency, fairness, and bias mitigation emerge as critical factors that shape the credibility and acceptance of ML-based safety research in aviation. The review revealed seven recommended future research directions: (1) interpretable AI; (2) real-time prediction; (3) hybrid models; (4) handling of unbalanced datasets; (5) privacy and data security; (6) human–machine interface for safety professionals; (7) regulatory implications. These directions provide a blueprint for further ML-based aviation safety research. This review underscores the role of ML applications in shaping aviation safety practices, thereby enhancing safety for all stakeholders. It serves as a constructive and cautionary guide for researchers, practitioners, and decision-makers, emphasizing the value of ML when used appropriately to transform aviation safety to be more data-driven and proactive. Full article

Agricultural markets are increasingly exposed to global risks as climate change intensifies and macro-financial volatility becomes more prevalent. This study examines the dynamic interconnection between major agricultural commodities—soybeans, corn, wheat, rough rice, and sugar—and key uncertainty indicators, including climate policy uncertainty, global economic policy uncertainty, geopolitical risk, financial market volatility, oil price volatility, and the U.S. Dollar Index. Using a Time-Varying Parameter Vector Autoregressive (TVP-VAR) model with monthly data, we assess both internal spillovers within the commodity system and external spillovers from macro-level uncertainties. On average, the external shock from the VIX to corn reaches 12.4%, and the spillover from RGEPU to wheat exceeds 10%, while internal links like corn to wheat remain below 8%. The results show that external uncertainty consistently dominates the connectedness structure, particularly during periods of geopolitical or financial stress, while internal interactions remain relatively subdued. Unexpectedly, recent global disruptions such as the COVID-19 pandemic and the Russia–Ukraine conflict do not exhibit strong or persistent effects on the connectedness patterns, likely due to model smoothing, stockpiling policies, and supply chain adaptations. These findings highlight the importance of strengthening international macro-financial and climate policy coordination to mitigate the propagation of external shocks. By distinguishing between internal and external connectedness under climate stress, this study contributes new insights into how systemic risks affect agri-food systems and offers a methodological framework for future risk monitoring. Full article

Bioactive peptides have significant potential for applications in pharmaceuticals, the food industry, and cosmetics due to their wide spectrum of biological activities. However, their pronounced structural and functional heterogeneity complicates the classification and prediction of biological activity. This study uses data from the PepLab platform, comprising 2748 experimentally confirmed bioactive peptides distributed across 15 functional classes, including ACE inhibitors, antimicrobial, anticancer, antioxidant, toxins, and others. For each peptide, the amino acid sequence and key physicochemical descriptors are provided, calculated via the integrated DMPep module, such as GRAVY index, aliphatic index, isoelectric point, molecular weight, Boman index, and sequence length. The dataset exhibits class imbalance, with class sizes ranging from 14 to 524 peptides. An innovative methodology is proposed, combining descriptive statistical analysis, structural modeling via DEMATEL, and structural equation modeling with neural networks (SEM-NN), where SEM-NN is used to capture complex nonlinear causal relationships between descriptors and functional classes. The results of these dependencies are integrated into a multi-class machine learning model to improve interpretability and predictive performance. Targeted data augmentation was applied to mitigate class imbalance. The developed classifier achieved predictive accuracy of up to 66%, a relatively high value given the complexity of the problem and the limited dataset size. These results confirm that integrating structured dependency modeling with artificial intelligence is an effective approach for functional peptide classification and supports the rational design of novel bioactive molecules. Full article

This study presents a general 3 × 5 × 5 factorial experimental design to maximize the Power Coefficient (Cp) of an H-Darrieus hydrokinetic turbine equipped with external accessories. Five accessory configurations (standard, cycloidal, flat plate, curve, and blocking plate), three solidity levels, and five Tip-Speed Ratio (TSR) levels were evaluated as main factors under the hypothesis that these factors significantly influence Cp. The data analyzed were obtained from numerical simulations, and their processing was conducted using Analysis of Variance (ANOVA), linear regression models, and response surfaces in the software programs Minitab 21 and RStudio V4.4.2. ANOVA makes it possible to determine the statistical significance of the effect of each factor and their interactions on the obtained Cp, identifying the accessories, TSR, and solidity that have the greatest impact on turbine performance. The results indicate that the optimal configuration to maximize Cp includes the flat-plate accessory, a solidity of 1.0, and a TSR of 3.2. From the linear regression models, mathematical relationships describing the system’s behavior were established, while the response surface analysis identified optimal operating conditions. These findings provide an effective tool for optimizing H-Darrieus turbine designs, highlighting the positive impact of accessories on performance improvement. Full article

In Italy, several changes to academic and professional standards and rules in kinesiology and sport have recently occurred. On the university side, no data collection has started regarding these changes and effects on specific scholars. The aim of this study was to evaluate the opinions of Italian university scholars in Exercise and Sport Sciences regarding recent disciplinary reclassifications, the emergence of the kinesiologist as a formal profession, and related curricular updates. Specifically, this study aimed to measure scholars’ views on the usefulness of unification, hybridization with other fields of knowledge, interdisciplinarity with pedagogy, the distinctiveness of undergraduate education in light of the new kinesiologist profile, and the inclusion of Technical and Laboratory Activities (TLA) credited through the European Credit Transfer System (ECTS). These aspects were explored through an eight-question survey offering three multiple-choice answers. An exploratory survey was distributed to a defined population of 261 Italian scholars (48 full professors, 137 associate professors, and 76 researchers). A total of 83 responses were collected: 14 full professors, 45 associate professors, and 24 researchers (response rate: 31.8%). Descriptive statistics and inferential analyses (Chi-Square tests, Cramér’s V, and Pearson/Spearman correlations) were conducted. Results indicated that 72.3% perceived overlap between pedagogical and medical disciplinary groups, and 85.5% considered practical/laboratory activities essential to the kinesiologist’s role. Significant differences in keyword-sharing perceptions across academic ranks emerged (p = 0.012; V = 0.3), and a near-significant trend was found regarding the importance of discipline-aligned research (p = 0.058; V = 0.3). Full agreement was found on the use of updated scientific evidence in lectures (100%), and 81.9% supported standardized education for the kinesiologist profession (Q6). Positive correlations were observed between support for keyword sharing and belief in its usefulness for promoting interdisciplinarity among full professors (r = 0.58, p = 0.02), associate professors (r = 0.68, p < 0.01), and researchers (r = 0.83, p < 0.01). Conversely, negative correlations emerged between the importance placed on practical activities and support for interdisciplinarity among associate professors and researchers, with values ranging from r = −0.31 to −0.46. The results are significant and tended toward autonomy from pedagogy, training aligned with the bachelor’s and master’s degree kinesiologist, and interdisciplinarity inherent in typical Exercise and Sport Sciences (ESS) keywords. This study should be replicated to increase the sample and to expand the ad hoc questionnaire to other issues. These findings highlight the need for greater alignment between academic training, disciplinary definitions, and professional practice through shared epistemological frameworks and updated descriptors that reflect scientific and labor market developments. Full article

Most levees are composed of earthen materials, making their structural stability vulnerable under flood conditions, especially in the case of overtopping. This study aims to analyze the relationship between the channel Froude number and the flow behavior on the landward slope of a levee during overtopping, enabling the prediction of landward slope velocity (LSV) in advance. Accurate estimation of flow velocity on the landward slope is crucial for predicting the occurrence and intensity of erosion during overtopping events, and it serves as a critical criterion for designing protective armoring and assessing levee structural stability. Numerical simulations were conducted under various Froude numbers in the channel to estimate the corresponding LSV. Key variables, including channel discharge, velocity, levee height, and overtopping flow depth, were used to establish quantitative correlations between channel flow characteristics and LSV. The proposed model effectively predicts the LSV for channel Froude numbers approximately between 0.05 and 0.60. The findings allow for a simplified estimation of LSV based on changes in Froude number and overtopping flow depth, providing valuable baseline data for planning levee reinforcement and maintenance strategies. Full article

Perfluorooctane sulfonate (PFOS), a member of the per- and polyfluoroalkyl substance (PFAS) family, has been associated with adverse health effects, including potential links to autism spectrum disorder (ASD). This study investigates the impact of PFOS on metabolic, immunologic and behavioral profiles in BTBR-mt^B6 mice, a mouse strain that models ASD, to provide insights into the role of PFOS in ASD development and related health concerns. Three-month-old male and female BTBR-mt^B6 mice were divided into two groups (n = 6) and received daily administration of either 1 mg/kg PFOS or vehicle over a three-month period by gavage. Metabolic assessments included measurements of body weight and weekly blood glucose levels, glucose and insulin tolerance tests, organ weights, and body compositions (free fluid, fat and lean tissue). Immune profiling was conducted via flow cytometric analysis of splenic leukocytes, while behavioral evaluations included grooming, sniffing, and three-chamber social interaction tests. PFOS exposure disrupted glucose homeostasis, with both sexes exhibiting elevated blood glucose levels. Male mice showed impaired glucose tolerance, delayed glucose level recovery, and increased insulin resistance, while females displayed decreased insulin resistance. Additionally, PFOS exposure led to liver enlargement in both sexes. Behavioral assessments revealed heightened grooming in PFOS-treated males, commonly interpreted as stress- or ASD-related repetitive behaviors, whereas females exhibited reduced grooming, reflecting altered behavioral responses to exposure. Immune alterations were also sex specific. PFOS-treated males exhibited decreased granulocytes, increased macrophages, and enhanced surface expressions of B220 and CD40L. PFOS-treated females showed increased macrophages, B-cells, cytotoxic T-cells and CD25⁺ T-cell subsets, with enhanced surface expression of B220 and CD8, and reduced surface expression of Mac-3. In addition, PFOS exposure reduced spleen weight in females. Taken together, PFOS exposure induced significant physiological and behavioral changes in BTBR-mt^B6 mice, with sex-specific differences observed. These results raise concern that PFASs may contribute to the development or exacerbation of metabolic, immune and neurodevelopmental disorders, highlighting the need for sex-specific human risk assessment in environmental toxicology. Full article

Severe fatigue, difficulty falling asleep, body stiffness, cognitive impairment, and widespread pain are some of the primary symptoms experienced by individuals with fibromyalgia (FM), leading to reduced physical function, increased frailty, and elevated fall risk. The present study aimed to evaluate the effects of the Virtual Square Step Exercise (V-SSE) program on physical function, frailty, FM impact, pain, fear, and risk of falling, and fall incidence in women with FM. A randomized controlled trial was conducted with 61 sedentary Spanish women with FM. Participants were randomly assigned to two groups: V-SSE and the control group. The V-SSE group completed an exercise program based on the V-SSE for 12 weeks (3 sessions/week), while the control group maintained their usual lifestyle and treatment. Physical function was assessed using the Timed Up and Go (TUG), Four-Step Square (FSST), 6-Minute Walking Test (6MWT), and others. Frailty was assessed with the Short Physical Performance Battery (SPPB). FM impact, pain, falls, and fear of falling were evaluated via questionnaires. Significant intergroup differences were only found in the 30 m Walking Test (p = 0.023; E.S. = 0.539), due to worsening in the control group. Although significant improvements were found in other variables in the V-SSE group, Dual Sit to Stand (p = 0.038), FM impact (p = 0.010), pain (p = 0.003) and falls (p = 0.037), these did not remain statistically significant after adjusting for multiple comparisons, nor were they corroborated in the intergroup comparison. A 12-week program based on the V-SSE was not effective in improving physical function, frailty, FM impact, pain, falls, fear, and risk of falling in Spanish women with FM. Full article

(1) Background: Violence against healthcare professionals is becoming a growing concern for healthcare systems and a public health issue, and in Portugal it remains undocumented at a national level, leaving a critical knowledge gap. This scenario compromises the development of effective public policies and evidence-based institutional strategies, which are essential for guiding policymakers in the implementation of preventive measures and appropriate safety protocols to assess the nature, frequency, and key factors contributing to violence against healthcare professionals (doctors and nurses) in clinical settings. (2) Methods: This is a quantitative, descriptive, and cross-sectional study. The sample size was 440 professionals (n = 440). Between January and May 2024, healthcare professionals (physicians and nurses) working in four local health units located in the south of Portugal were invited to participate in this study via institutional e-mail. Data was collected using a structured questionnaire on the healthcare professional’s sociodemographic and work-related characteristics and aspects related to violence towards healthcare professionals in the workplace. Unconditional logistic regression models were fitted to compute crude odds ratios (ORs) and 95% confidence intervals (95%CIs) for the association between sociodemographic and work-related characteristics and violence at work. (3) Results: Nearly 40% of the healthcare professionals sampled reported having been victims of violence in the workplace, and, among these, the majority reported experiencing psychological violence (94.2%), followed by physical violence (46.2%), another type of violence (39.1%), and sexual violence (4.1%). Incidents were mostly occasional (65.5%), occurring during the daytime (51.5%) and on weekdays (84.8%). Healthcare professionals aged between 34 and 55 years old were approximately twice as likely to experience violence compared to those who were 56 years old or older (OR = 2.28; 95%CI 1.33–3.90). Also, those who had been with the organization for more than 4 years (5–7 years: OR = 2.37; 95%CI 1.05–5.37. ≥8 years: OR = 1.87; 95%CI 1.00–3.50), as well as those who worked shifts (OR = 1.84; 95%CI 1.25–2.72), reported incidents of violence more frequently. (4) Conclusions: The low response rate (12.5%) and cross-sectional design limit the generalizability of the results, which should be interpreted considering these methodological limitations. Workplace violence in Portugal is a reality, and it requires solutions. Information related to violent incidents must be comprehensively gathered to understand the full extent of the problem and develop prevention strategies based on potentially changeable risk factors to minimize the negative effects of workplace violence. Full article

Fusarium wilt, caused by Fusarium oxysporum f. sp. cubense tropical race 4 (Foc TR4), threatens banana and plantain production throughout South America. Because Colombian biosafety regulations restrict in vitro work with Foc TR4, we tested the antifungal activity of Nostoc commune against F. oxysporum race 2 isolated from cv. ‘Manzano’ (Musa AAB). An ethanolic extract of the cyanobacterium (EEC) was profiled by gas chromatography and evaluated with a Kirby–Bauer assay (1000–4000 ppm; n = 4). Synthetic Sico^® and botanical Timorex^® served as positive controls, and solvent-free plates were the negative control. Growth reduction (GR) and percentage inhibition of radial growth (PIRG) were analysed with Student’s t-test (α = 0.05). Forty-two compounds—mainly fatty and carboxylic acids associated with antifungal activity—were detected. Sico achieved complete inhibition (100 ± 0%), Timorex suppressed 76 ± 2%, and 4 000 ppm EEC curtailed mycelial expansion by 45 ± 3% (p < 0.01). Although less potent than commercial fungicides, EEC impeded F. oxysporum growth, demonstrating that N. commune synthesises bioactive metabolites. Optimising cyanobacterial cultivation and formulation could yield a sustainable biocontrol alternative for managing Fusarium wilt in the region. Full article

In this work, ZnO nanorods were grown on vertically aligned and randomly aligned silica nanosprings using the hydrothermal method. The initial step was the deposition of a ZnO seed layer by atomic layer deposition to promote nucleation. For hydrothermal growth, equimolar (0.2 M) solutions of Zinc nitrate hexahydrate and hexamethylene tetraamine prepared in DI water were used. The ZnO NR grown on the VANS were flower-like clusters, while for the RANS, the ZnO NR grew radially outward from the individual nanosprings. The lengths and diameters of ZnO NR grown on VANS and RANS were 175 and 650 nm, and 35 and 250 nm, respectively. Scanning electron microscopy confirmed the formation of ZnO nanorods, while X-ray diffraction and Raman spectroscopy verified that they have a hexagonal wurtzite crystal structure with preferential growth along the c-axis. X-ray photoelectron spectroscopy, in conjunction with in vacuo annealing, was used to examine the surface electronic structure of ZnO nanorods and defect healing. Photoluminescence of the ZnO nanorods indicates high crystal quality, as inferred from the weak defect band relative to strong excitonic band edge emission. Full article

Ternary chalcogenide-based sulfide materials with distorted morphologies such as BaZrS₃, CaZrS₃, and SrZrS₃, have recently gained much attention in optoelectronics and photovoltaics due to their high structural and thermal stability and compatibility with low-cost, earth-abundant synthesis routes. However, their relatively large bandgaps often limit their suitability for near-infrared (NIR) photodetectors. Here, we conducted a comprehensive investigation of SrHfSe₃, a ternary chalcogenide with an orthorhombic crystal structure and distinctive needle-like morphology, as a promising candidate for NIR photodetection. SrHfSe₃ exhibits a direct bandgap of 1.02 eV, placing it well within the NIR range. Its robust structure, high temperature stability, phase stability and natural abundance make it a compelling material for next-generation, self-powered NIR photodetectors. An in-depth analysis of the SrHfSe₃-based photodetector was performed using SCAPS-1D simulations, focusing on key performance metrics such as J–V behavior, photoresponsivity, and specific detectivity. Device optimization was achieved by thoroughly altering each layer thickness, doping concentrations, and defect densities. Additionally, the influence of interface defects, absorber bandgap, and operating temperature was assessed to enhance the photoresponse. Under optimal conditions, the device achieved a short-circuit current density (Jsc) of 45.88 mA/cm², an open-circuit voltage (Voc) of 0.7152 V, a peak photoresponsivity of 0.85 AW⁻¹, and a detectivity of 2.26 × 10¹⁴ Jones at 1100 nm. A broad spectral response spanning 700–1200 nm confirms its efficacy in the NIR region. These results position SrHfSe₃ as a strong contender for future NIR photodetectors and provide a foundation for experimental validation in advanced optoelectronic applications. Full article

Today, blockchain technologies are a separate, rapidly developing area. With rapid development, they open up a number of scientific problems. One of these problems is the problem of reliability, which is primarily associated with the use of cryptographic primitives. The threat of the emergence of quantum computers is now widely discussed, in connection with which the direction of post-quantum cryptography is actively developing. Nevertheless, the most popular blockchain platforms (such as Bitcoin and Ethereum) use asymmetric cryptography based on elliptic curves. Here, cryptographic primitives for blockchain systems are divided into four groups according to their functionality: keyless, single-key, dual-key, and hybrid. The main attention in the work is paid to the most significant cryptographic primitives for blockchain systems: keyless and single-key. This manuscript discusses possible scenarios in which, during practical implementation, the mathematical foundations embedded in the algorithms for generating a digital signature and encrypting data using algorithms based on elliptic curves are violated. In this case, vulnerabilities arise that can lead to the compromise of a private key or a substitution of a digital signature. We consider cases of vulnerabilities in a blockchain system due to incorrect use of a cryptographic primitive, describe the problem, formulate the problem statement, and assess its complexity for each case. For each case, strict calculations of the maximum computational costs are given when the conditions of the case under consideration are met. Among other things, we present a new version of the encryption algorithm for data stored in blockchain systems or transmitted between blockchain systems using elliptic curves. This algorithm is not the main blockchain algorithm and is not included in the core of modern blockchain systems. This algorithm allows the use of the same keys that system users have in order to store sensitive user data in an open blockchain database in encrypted form. At the same time, possible vulnerabilities that may arise from incorrect implementation of this algorithm are considered. The scenarios formulated in the article can be used to test the reliability of both newly created blockchain platforms and to study long-existing ones. Full article

Transcription factors play crucial roles in regulating gene expression, and any dysregulation in their levels could be involved in cancer progression. The role of androgen receptors (AR) and zinc finger (ZNF) proteins in tumors, like prostate cancer (PC), remains poorly understood. Moreover, due to the multifaceted transcriptional behavior of ARs and ZNFs, their biological role in cancer progression may also depend on the interplay with micro-RNAs (miRNAs). Based on The Cancer Genome Atlas (TCGA) database, we analyzed the expression levels of zinc finger transcripts and ARs in PC. Specifically, exploring their involvement in cancer progression and regulation by miRNAs. The analysis relied on several tools to create a multivariate combination of the original biomarkers to improve their diagnostic efficacy. Multidimensional Scaling (MDS) identified two new dimensions that were entered into a regression analysis to determine the best predictors of overall survival (OS) and disease-free interval (DFI). A combination of both dimensions predicted almost 50% (R² = 0.46) of the original variance of OS. Kaplan–Meier survival analysis also confirmed the significance of these two dimensions regarding the clinical output. This study showed preliminary evidence that several transcription factor expression levels belonging to the zinc family and related miRNAs can effectively predict patients’ overall PC survivability. Full article

The paper studies the behavior of homogeneous isotropic materials by performing appropriate numerical analyses and utilizing suitable FEMs to reproduce the Brazilian splitting test. Starting with a theoretical approach and adopting suitable numerical simulations, a new formula that is able to characterize the Young’s modulus is presented. To this end, in addition to the analysis of the specimen’s response in terms of stresses and strains, the real displacement field resulting from the real kinematical constraints on the specimen is determined. Therefore, the Brazilian test is taken as a reference test and the specimen’s behavior is derived by taking advantage of both the theoretical approach and numerical simulations developed in the ANSYS 2021 R1 environment. The latter allows us to define a new mathematical relation representing the missing part of the kinematical field. Furthermore, a new formula which explicitly relates the Young’s modulus of the material to the geometrical characteristics of the specimen, to the acting force, and to a measured selected displacement is proposed. Future developments will include adopting the proposed formulas for the identification of other mechanical parameters of the material, e.g., by adopting a full-field contactless approach to displacement measurement and studying the behavior of specimens with different geometrical characteristics. Full article

This narrative review explores the role of additive manufacturing (AM) technologies in the production of dental implants, focusing on materials and key AM methods. The study discusses several materials used in implant fabrication, including porous titanium, trabecular tantalum, zirconium dioxide, polymers, and composite materials. These materials are evaluated for their mechanical properties, biocompatibility, and suitability for AM processes. Additionally, the review examines the main AM technologies used in dental implant production, such as selective laser melting (SLM), electron beam melting (EBM), stereolithography (SLA), selective laser sintering (SLS), and direct metal laser sintering (DMLS). These technologies are compared based on their accuracy, material limitations, customization potential, and applicability in dental practice. The final section presents a data source analysis of the Web of Science and Scopus databases, based on keyword searches. The analysis evaluates the research trends using three criteria: publication category, document type, and year of publication. This provides an insight into the evolution and current trends in the field of additive manufacturing for dental implants. The findings highlight the growing importance of AM technologies in producing customized and efficient dental implants. Full article

Cyanobacteria are a prolific source of bioactive metabolites with expanding applications in sustainable agriculture and biotechnology. This work explores, for the first time in thermotolerant Colombian isolates, the impact of light spectrum, photoperiod, and irradiance on the co-production of exopolysaccharides (EPS) and indole-3-acetic acid (IAA). Six strains from hot-spring environments were screened under varying blue:red (B:R) LED ratios and full-spectrum illumination. Hapalosiphon sp. UFPS_002 outperformed all others, reaching ~290 mg L⁻¹ EPS and 28 µg mL⁻¹ IAA in the initial screen. Response-surface methodology was then used to optimize light intensity and photoperiod. EPS peaked at 281.4 mg L⁻¹ under a B:R ratio of 1:5 LED, 85 µmol m⁻² s⁻¹, and a 14.5 h light cycle, whereas IAA was maximized at 34.4 µg mL⁻¹ under cool-white LEDs at a similar irradiance. The quadratic models exhibited excellent predictive power (R² > 0.98) and a non-significant lack of fit, confirming the light regime as the dominant driver of metabolite yield. These results demonstrate that precise photonic tuning can selectively steer carbon flux toward either EPS or IAA, providing an energy-efficient strategy to upscale thermotolerant cyanobacteria for climate-resilient biofertilizers, bioplastics precursors, and other high-value bioproducts. Full article

This study investigates the use of waste glass powder derived from fluorescent lamps as a partial replacement for cement in mortar production, aiming to valorize this Waste from Electrical and Electronic Equipment (WEEE) and enhance sustainability in the construction sector. Mortars were formulated by substituting 25% of cement by volume with glass powders from fluorescent lamp glass and green bottle glass. The experimental program evaluated mechanical strength, durability parameters and ecotoxicological performance. Results revealed that clean fluorescent lamp mortars showed the most promising mechanical behavior, exceeding the reference in long-term compressive (54.8 MPa) and flexural strength (10.0 MPa). All glass mortars exhibited significantly reduced chloride diffusion coefficients (85–89%) and increased electrical resistivity (almost 4 times higher), indicating improved durability. Leaching tests confirmed that the incorporation of fluorescent lamp waste did not lead to hazardous levels of heavy metals in the cured mortars, suggesting effective encapsulation. By addressing both technical (mechanical and durability) and ecotoxic performance, this research contributes in an original and relevant way to the development of more sustainable building materials. Full article

This study investigates the potential of using downgraded chestnuts, which are unsuitable for commercial sale, from five distinct Greek regions to produce chestnut flour and formulate gluten-free biscuits. Chestnuts were dried and milled into flour, which was then used as the sole flour ingredient in the biscuit formulation, in order to assess its nutritional and functional contribution. The moisture, lipid, protein, and ash contents were analyzed in chestnut flour samples, which showed significant regional differences. Chestnut flour biscuits (CFB) were compared to wheat flour biscuits (WFB). CFB exhibited significantly higher ash content (3.01% compared to 0.94% in WFB) and greater antioxidant capacity, with DPPH scavenging activity reaching 70.83%, as opposed to 61.67% in WFB, while maintaining similar moisture and lipid levels. Although CFB showed slightly lower protein content, the elevated mineral and phenolic compound levels contributed to its functional value. These findings indicate that downgraded chestnuts can be upcycled into gluten-free bakery products with improved functional characteristics. Given their antioxidant activity and mineral content, chestnut flour biscuits may serve as a valuable option for gluten-free diets, supporting circular economy principles and reducing food waste. Full article

Cell culture models are of central importance for the investigation of cellular metabolism, proliferation and stress responses. In this study, the effects of different concentrations of glucose (1 g/L vs. 4.5 g/L) and fetal bovine serum (FBS; 5%, 10%, 15%) on viability, mitochondrial function and autophagy are investigated in four human cell lines: MRC-5, HeLa, Caco-2 and SW-620. Cells were cultured in defined media for 72 h, and viability was assessed by LDH release, mitochondrial membrane potential using Rhodamine 123, ATP content by luminescence and autophagy activity by dual fluorescence staining. The results showed that HeLa and SW-620 cancer cells exhibited increased proliferation and mitochondrial activity under high glucose conditions, while low glucose media resulted in decreased ATP content and increased membrane permeability in HeLa cells. MRC-5 fibroblasts and Caco-2 cells showed greater resilience to nutrient stress, with minimal changes in LDH release and consistent proliferation. Autophagy was activated under all conditions, with a significant increase only in selected cell-medium combinations. These results highlight the importance of medium composition in influencing cellular bioenergetics and stress responses, which has implications for cancer research, metabolic disease modelling and the development of serum-free culture systems for regenerative medicine. Full article

The rise in multidrug-resistant bacterial strains and persistent infections such as Lyme disease caused by Borrelia burgdorferi highlights the need for novel antimicrobial agents. The present study explores the antioxidant, antibacterial, and cytotoxic properties of extracts from submerged mycelial biomass of Fomitopsis pinicola, cultivated in synthetic and lignocellulosic media. Four extracts were obtained using hot water and 80% ethanol. The provided analysis of extracts confirmed the presence of various bioactive compounds, including flavonoids, alkaloids, and polyphenols. All extracts showed dose-dependent antioxidant activity (IC₅₀: 1.9–6.7 mg/mL). Antibacterial tests revealed that Klebsiella pneumoniae was most sensitive, with the L2 extract producing the largest inhibition zone (15.33 ± 0.47 mm), while the strongest bactericidal effect was observed against Acinetobacter baumannii (MBC as low as 0.5 mg/mL for L1). Notably, all extracts significantly reduced the viability of stationary-phase B. burgdorferi cells, with L2 reducing viability to 42 ± 2% at 5 mg/mL, and decreased biofilm mass, especially with S2. Cytotoxicity assays showed minimal effects on NIH 3T3 cells, with slight toxicity in HEK 293 cells for S2 and L1. These results suggest that F. pinicola extracts, particularly ethanolic L2 and S2, may offer promising natural antimicrobial and antioxidant agents for managing resistant infections. Full article

China is one of the countries severely affected by earthquakes, making precise and timely identification of earthquake precursors essential for reducing casualties and property damage. A novel method is proposed that combines a rock acoustic emission (AE) detection technique with deep learning methods to facilitate real-time monitoring and advance earthquake precursor detection. The AE equipment and seismometers were installed in a granite tunnel 150 m deep in the mountains of eastern Guangdong, China, allowing for the collection of experimental data on the correlation between rock AE and seismic activity. The deep learning model uses features from rock AE time series, including AE events, rate, frequency, and amplitude, as inputs, and estimates the likelihood of seismic events as the output. Precursor features are extracted to create the AE and seismic dataset, and three deep learning models are trained using neural networks, with validation and testing. The results show that after 1000 training cycles, the deep learning model achieves an accuracy of 98.7% on the validation set. On the test set, it reaches a recognition accuracy of 97.6%, with a recall rate of 99.6% and an F₁ score of 0.975. Additionally, it successfully identified the two biggest seismic events during the monitoring period, confirming its effectiveness in practical applications. Compared to traditional analysis methods, the deep learning model can automatically process and analyse recorded massive AE data, enabling real-time monitoring of seismic events and timely earthquake warning in the future. This study serves as a valuable reference for earthquake disaster prevention and intelligent early warning. Full article

Hydrogen sulfide (H₂S) can be produced from the metabolism of foods containing sulfur in the gastrointestinal tract (GIT). At low doses, H₂S regulates the gut microbial community and supports GIT health, but depending on dose, age, and individual health conditions, it may also contribute to inflammatory responses and gut barrier dysfunction. Controlling H₂S production in the GIT is important for maintaining a healthy gut microbiome. However, research on this subject is limited due to the gaseous nature of the chemical and the difficulty of accessing the GIT in situ. In the present ex vivo experiment, we used a single-dose sodium sulfide preparation (SSP) as a H₂S precursor to test the effect of H₂S on the human gut microbiome across different age groups, including breastfed infants, toddlers, adults, and older adults. Metagenomic sequencing and metabolite measurements revealed that the development of the gut microbial community and the production of short-chain fatty-acids (SCFAs) were age-dependent; that the infant and the older adult groups were more sensitive to SSP exposure; that exogeneous SSP suppressed SCFA production across all age groups, except for butyrate in the older adult group, suggesting that H₂S selectively favors specific gut microbial processes. Full article

Carbon monoxide (CO) is a major toxic gas emitted from vehicle exhaust, industrial processes, and incomplete fuel combustion, posing serious environmental and health risks. Catalytic oxidation of CO into less harmful CO₂ is an effective strategy to reduce these emissions. In this study, we investigated the catalytic performance of platinum (Pt) single atoms doped on C₃N monolayers with various vacancy defects, including single carbon (C_V) and nitrogen (N_V) vacancies, using density functional theory (DFT) calculations. Our results demonstrate that Pt@N_V-C₃N exhibited the most favorable catalytic properties, with the highest O₂ adsorption energy (−3.07 eV). This performance significantly outperforms Pt atoms doped at other vacancies. It can be attributed to the strong binding between Pt and nitrogen vacancies, which contributes to its excellent resistance to Pt aggregation. CO oxidation on Pt@N_V-C₃N proceeds via the Eley–Rideal (ER2) mechanism with a low activation barrier of 0.41 eV for the rate-determining step, indicating high catalytic efficiency at low temperatures. These findings suggest that Pt@N_V-C₃N is a promising candidate for CO oxidation, contributing to developing cost-effective and environmentally sustainable catalysts. The strong binding of Pt atoms to the nitrogen vacancies prevents aggregation, ensuring the stability and durability of the catalyst. The kinetic modeling further revealed that the ER2 mechanism offers the highest reaction rate constants over a wide temperature range (273–700 K). The low activation energy barrier also facilitates CO oxidation at lower temperatures, addressing critical challenges in automotive and industrial pollution control. This study provides valuable theoretical insights for designing advanced single-atom catalysts for environmental remediation applications. Full article

This research investigates enhancing the performance of an Archimedes screw-type hydrokinetic turbine (ASHT). A 3D transient computational model employing the six degrees of freedom (6-DOF) methodology within the ANSYS Fluent software 2022 R1, was selected for this purpose. A central composite design (CCD) methodology was applied within the response surface methodology (RSM) to enhance the turbine’s power coefficient ($C_p$). Key independent factors, including blade length (L), blade inclination angle ($\gamma$), and external diameter ($D_e$), were systematically varied to determine their optimal values. The optimization process yielded a maximum $C_p$ of 0.337 for L, $\gamma$, and $D_e$ values of 168.921 mm, 51.341°, and 245.645 mm, respectively. Experimental validation was conducted in a hydraulic channel, yielding results that demonstrated a strong correlation with the numerical predictions. This research underscores the importance of geometric design optimization in improving the energy capture efficiency of the ASHT, contributing to its potential viability as a competitive renewable energy solution in the pre-commercial phase of development. Full article

Pangasius (Pangasianodon hypophthalmus) minced muscle with 1 and 2% salt was treated with different high-pressure processing and thermal methods, including conventional heat-induced gels (HIGs), high-pressure processing (HPP) prior to cooking (PC), HPP prior to setting (PS), and setting prior to HPP (SP), to evaluate for their effects on the selected physicochemical properties. The results showed that the PC treatment produced gels with a significantly higher gel strength (496.72–501.26 N·mm), hardness (9.62–10.14 N), and water-holding capacity (87.79–89.74%) compared to the HIG treatment, which showed a gel strength of 391.24 N·mm, a hardness of 7.36 N, and a water-holding capacity of 77.98%. PC gels also exhibited the typical microstructure of pressure-induced gels, with a denser and homogeneous microstructure compared to the rough and loosely connected structure of HIGs. In contrast, SP treatment exhibited the poorest gel quality in all parameters, with gel strength ranging from 319.79 to 338.34 N·mm, hardness from 5.87 to 6.31 N, and WHC from 71.91 to 73.72%. Meanwhile, the PS treatment showed a comparable gel quality to HIGs. SDS-PAGE analysis revealed protein degradation and aggregation in HPP-treated samples, with a decrease in the intensity of myosin heavy chains and actin bands. Fourier-transform infrared spectroscopy (FTIR) analysis showed minor shifts in protein secondary structures, with the PC treatment showing a significant increase in α-helices (28.09 ± 0.51%) and a decrease in random coil content (6.69 ± 0.92%) compared to α-helices (23.61 ± 0.83) and random coil structures (9.47 ± 1.48) in HIGs (p < 0.05). Only the PC treatment resulted in a significant reduction in total plate count (TPC) (1.51–1.58 log CFU/g) compared to 2.33 ± 0.33 log CFU/g in the HIG treatment. These findings suggest that HPP should be applied prior to thermal treatments (cooking or setting) to achieve an improved gel quality in reduced-salt pangasius products. Full article

In this paper, we address the problem of intelligent operation of Distribution Static Synchronous Compensators (D-STATCOMs) in power distribution systems to reduce energy losses and CO₂ emissions while improving system operating conditions. In addition, we consider the entire set of constraints inherent in the operation of such networks in an environment with D-STATCOMs. To solve such a problem, we used three master–slave methodologies based on sequential programming methods. In the proposed methodologies, the master stage solves the problem of intelligent D-STATCOM operation using the continuous versions of the Monte Carlo (MC) method, the population-based genetic algorithm (PGA), and the Particle Swarm Optimizer (PSO). The slave stage, for its part, evaluates the solutions proposed by the algorithms to determine their impact on the objective functions and constraints representing the problem. This is accomplished by running an Hourly Power Flow (HPF) based on the method of successive approximations. As test scenarios, we employed the 33- and 69-node radial test systems, considering data on power demand and CO₂ emissions reported for the city of Medellín in Colombia (as documented in the literature). Furthermore, a test system was adapted in this work to the demand characteristics of a feeder located in the city of Talca in Chile. This adaptation involved adjusting the conductors and voltage limits to include a test system with variations in power demand due to seasonal changes throughout the year (spring, winter, autumn, and summer). Demand curves were obtained by analyzing data reported by the local network operator, i.e., Compañía General de Electricidad. To assess the robustness and performance of the proposed optimization approach, each scenario was simulated 100 times. The evaluation metrics included average solution quality, standard deviation, and repeatability. Across all scenarios, the PGA consistently outperformed the other methods tested. Specifically, in the 33-node system, the PGA achieved a 24.646% reduction in energy losses and a 0.9109% reduction in CO₂ emissions compared to the base case. In the 69-node system, reductions reached 26.0823% in energy losses and 0.9784% in CO₂ emissions compared to the base case. Notably, in the case of the Talca feeder—particularly during summer, the most demanding season—the PGA yielded the most significant improvements, reducing energy losses by 33.4902% and CO₂ emissions by 1.2805%. Additionally, an uncertainty analysis was conducted to validate the effectiveness and robustness of the proposed optimization methodology under realistic operating variability. A total of 100 randomized demand profiles for both active and reactive power were evaluated. The results demonstrated the scalability and consistent performance of the proposed strategy, confirming its effectiveness under diverse and practical operating conditions. Full article

(1) Background: Intrapartum obstetric violence has become increasingly visible and is portrayed as a cross-cutting and complex phenomenon. Despite numerous international debates and extensive reports in the literature, there is limited consensus on its definition, emphasizing the need to clarify the concept. The aim of this article is to analyze the concept of obstetric violence in the care of women in labor in health institutions; (2) Methods: Search and selection of studies using the scoping review methodology, based on the Joanna Briggs Institute guidelines and Rodgers’ conceptual review method for data extraction and analysis; (3) Results: A sample of 49 studies provided a comprehensive understanding of the concept, revealing in its conceptualization attributes of physical, verbal, psychological, sexual, institutional and structural violence. Identification of antecedents of gender inequality and failure of relational, technical and structural standards at the level of health institutions and their professionals, as the main triggers of obstetric violence. Reporting of consequences with a negative impact on maternal and child health; (4) Conclusions: Conceptual analysis with important contributions to the paradigm shift in the work of health professionals. Multiple dimensions, cultural differences and variations in the concept should continue to be examined to improve its research and application. Full article

Surface texture displays are touch panels that provide tactile feedback. Presenting softness sensations on such rigid surfaces remains a challenge, and effective methods are not yet established. This study explores how low-frequency frictional modulation during finger sliding can evoke the perception of softness. We examined multimodal optimization—whether the optimal tactile parameters vary depending on the type of visually presented fabric. Videos of draping cloth were shown beneath the panel, while spatial wavelength of frictional modulation and finger sliding speed were optimized using response surface methodology. The optimal spatial wavelength did not significantly differ across fabric types: towel (16.8 mm), cotton (16.5 mm), leather (17.1 mm), and suede (15.4 mm), with an overall range of 15–18 mm. In contrast, the optimal sliding speed significantly varied by fabric: towel (144 mm/s), cotton (118 mm/s), leather (167 mm/s), and suede (96 mm/s). These results suggest that frictional variation with a fixed spatial wavelength may serve as a general strategy for presenting softness. The findings contribute to advancing tactile rendering techniques for hard touch surfaces. Full article

Infrastructure facility development and modernization highly contribute to national economic growth, but at the same time, such development also causes local negative impacts on the use of specific land plots, creating losses for their right holders. In Russia, some prerequisites have already been laid down on the issue of compensation for the losses associated with restrictions on the rights and prohibitions of economic activity within zones with special territory use conditions (ZSTUCs). However, the impacts of such facilities lead to environmental pollution and land use disadvantages, such as irregular parcels. The aim of this work is to substantiate a set of approaches to compensating for the cumulative negative impact of infrastructure facilities. The factors causing the negative impacts of infrastructure facilities are grouped into three areas: rights restrictions, territorial deficiencies and environmental pollution. This work uses the SWOT analysis method with the possibility of element-by-element analysis, as a result of which the approaches to the compensation for negative impacts under different external and internal conditions are determined. As a result of this study, a justification for a set of approaches to compensating for the negative impacts of infrastructure facilities on land use was executed, and a new algorithm to compensate the right holders of the land, industry sector or state for such negative impacts was developed. The following approaches to compensating for negative impacts were identified: loss assessment; the establishment of environmental payments; cadastral value adjustment; compensation for industry sector losses; and the use of state regulation tools. The first two approaches were identified as the main ones. The proposed algorithm can be realized only with the help of the abovementioned methodological approaches, which form a basis for further research. Full article

Wilson’s disease is a rare autosomal recessive disorder of copper metabolism characterized by excessive copper accumulation in the liver, brain, and other tissues. This paper provides an overview of the primary pharmacological agents used in its treatment, including penicillamine, trientine, tetrathiomolybdate, and zinc. Their mechanisms of action, therapeutic applications, and side-effect profiles are examined, emphasizing how each agent helps reduce copper overload. Additionally, brief information is given on novel therapies such as gene therapy and artificial intelligence applications. Furthermore, information about the structural and chemical properties of these compounds is provided, highlighting the molecular features that enable them to chelate copper or reduce its intestinal absorption. By integrating pathophysiological insights with chemical and mechanistic perspectives, this paper offers a comprehensive review of existing treatment strategies for Wilson’s disease and stresses the importance of careful, patient-specific management to optimize long-term outcomes. Full article

This research represents the first application of the MOLS method to characterize the conformational energy landscape of an antimicrobial peptide within a solvent environment, providing a novel approach to understanding peptide behavior in solution. This method’s exhaustive nature ensures that all minimum-energy conformations for a given amino acid sequence are sampled. In this work, we employed a combination of MOLS and VMD software to generate structural models of a cyclic peptide, both solvated and non-solvated, and then utilized the CHARMM force field to conduct energy calculations throughout the sampling process. In the presence of a solvent, this method predicted a structure close to the experimental crystal structure. A significant reduction was observed in gamma turn motifs in the presence of water. The solvent molecules also favored different hydrogen bonding patterns in the peptide by orchestrating an intermolecular interaction with the peptide atoms. This intermolecular interaction involves an ARG side chain and further stabilizes the backbone. It is evident that solvent interactions are key in designing antimicrobial peptides. This study will help in designing and understanding peptides for use as therapeutic agents like antibacterial or antimicrobial peptides. Each conformer obtained from the MOLS method would be one of the best starting points for molecular dynamic simulation to further explore the landscape. Full article

Drug removal from urban wastewater (UW) is a topic of growing interest. The new European Directive addresses this problem by introducing quaternary treatment by 2045, as part of the “Zero Pollution” plan from a One Health perspective. In this context, the role of microalgae remains very promising in achieving clean and safe effluents, although its cost–benefit ratio needs to be carefully evaluated. The purpose of this review is to disclose the latest approaches to drug removal and energy recovery from UWs adopting different algae (Chlorella spp., Galdieria spp., and Scenedesmus spp.), to provide a detailed background for further research towards the development of new effective strategies on UW remediation while producing clean energy. We examined the most recent studies, considering most drugs found in wastewater, their management, as well as strategies used to recover energy while being mindful of a circular economy. There is growing interest in algae-based systems. The latest findings on algae–bacteria consortia show that it could be a better alternative to suspended biomass and represent a way to manage drug waste. This finding suggests that large-scale experiments should be conducted to confirm the potential benefits of such waste treatments. Full article

Key exchange mechanisms are foundational to secure communication, yet traditional methods face challenges from quantum computing. The Module-Lattice-Based Key-Encapsulation Mechanism (ML-KEM) is a post-quantum cryptographic key exchange protocol with unknown successful quantum vulnerabilities. This study evaluates the ML-KEM using experimental benchmarks. We implement the ML-KEM in Python for clarity and in C++ for performance, demonstrating the latter’s substantial performance improvements. The C++ implementation achieves microsecond-level execution times for key generation, encapsulation, and decapsulation. Python, while slower, provides a user-friendly introduction to the ML-KEM’s operation. Moreover, our Python benchmark confirmed that the ML-KEM consistently outperformed RSA in execution speed across all tested parameters. Beyond benchmarking, the ML-KEM is shown to handle the computational hardness of the Module Learning With Errors (MLWE) problem, ensuring resilience against quantum attacks, classical attacks, and Artificial Intelligence (AI)-based attacks, since the ML-KEM has no pattern that could be detected. To evaluate its practical feasibility on constrained devices, we also tested the C++ implementation on a Raspberry Pi 4B, representing IoT use cases. Additionally, we attempted to run integration and benchmark tests for the ML-KEM on microcontrollers such as the ESP32 DevKit, ESP32 Super Mini, ESP8266, and Raspberry Pi Pico, but these trials were unsuccessful due to memory constraints. The results showed that while the ML-KEM can operate effectively in such environments, only devices with sufficient resources and runtimes can support its computational demands. While resource-intensive, the ML-KEM offers scalable security across diverse domains such as IoT, cloud environments, and financial systems, making it a key solution for future cryptographic standards. Full article

Passiflora caerulea L., commonly known as the blue passionflower, is traditionally grown as an ornamental plant, but has a diverse chemical composition resulting in a wide range of biological activities that determine its pharmacological properties and use in medicine. Traditional propagation methods, including seed germination and vegetative cuttings, are often inefficient due to low germination rates, susceptibility to pathogens, and slow growth. In particular, P. caerulea presents significant challenges in germination due to its slow development. In this context, in vitro cultivation is used to enable rapid, large-scale plant production while maintaining genetic fidelity. The study of Passiflora tissue cultures began in 1966 and has since attracted increasing attention from researchers around the world. However, despite growing interest, studies specifically focused on the in vitro propagation of P. caerulea remain limited. This review aims to summarize existing knowledge on the main techniques used for in vitro culturing and propagation of P. caerulea, including organogenesis, somatic embryogenesis, and callogenesis. Particular attention is paid to the key factors that influence the initiation, growth, and regeneration of cultures, including the type of explant, the composition of the media, and the environmental conditions. Advances in the in vitro cultivation of P. caerulea have greatly improved the understanding and propagation of this species. Although in vitro cultivation offers several advantages, it is crucial to conduct thorough research on the selection of explants, their age, and the appropriate culture media to ensure optimal growth and development. Full article

(1) Eating disorders (EDs), characterized by symptoms such as restrictive eating, binge eating, compensatory behaviors, and emotional dysregulation, are associated with autonomic nervous system dysregulation, which may contribute to cardiovascular complications. This review systematically examines the relationship between heart rate variability (HRV) and core ED symptoms to identify specific autonomic patterns linked to behaviors like fasting, binge eating, and emotional dysregulation. (2) A total of 16 cross-sectional and longitudinal studies were narratively synthesized following PRISMA guidelines. All studies were selected from the Science Direct, PubMed, Web of Science, and Scopus databases. (3) Findings indicate that individuals with anorexia nervosa exhibit blunted sympathetic reactivity and reduced parasympathetic flexibility, particularly during stress or physical activity, with HRV measures normalizing after weight restoration. In contrast, binge eating and loss-of-control eating are associated with lower resting HRV, which correlates with the severity of eating behaviors. Reactive HRV also varies with food cues and emotional states, showing complex autonomic responses in individuals with EDs. Emotional dysregulation, consistently marked by reduced high-frequency HRV, is a key feature across these disorders. (4) These results suggest that HRV patterns may serve as physiological markers of ED symptomatology, offering insights for targeted interventions aimed at improving both emotional regulation and cardiovascular health in affected individuals. Full article

Tomato chlorosis virus (ToCV) is a highly infectious plant virus that poses a significant threat to the Solanaceae family worldwide. Despite its widespread impact, effective control remains challenging due to its vector-borne transmission by whiteflies. To facilitate early detection and potential therapeutic intervention, this study aimed to identify diagnostic epitopes through a comprehensive bioinformatics approach combining comparative genomics and artificial intelligence-based structural modeling. We analyzed forty-four complete ToCV genomes to identify highly conserved regions and uncovered an orphan clade, indicating evolutionary divergence. Subcellular localization and transmembrane domain predictions revealed viral proteins with extracellularly exposed peptide regions. Structural modeling using AlphaFold3 further validated the stability and accessibility of these domains. By integrating these findings with epitope prediction algorithms, this study identified four highly promising epitope candidates, which are suitable for the development of antibody-based diagnostic kits and antiviral therapeutics targeting ToCV. These epitopes provide a strong foundation for the development of antibody-based diagnostic kits or antiviral therapeutics targeting ToCV. Full article

Sheep and goat milk authenticity is of great importance, especially for countries like Greece, where these products are connected to the country’s rural economy and cultural heritage. The aim of the study is to evaluate the effectiveness of Fourier Transform Infrared Attenuated Total Reflectance (ATR-FTIR) spectroscopy in combination with chemometric techniques for the classification of cow, sheep, and goat milk and consequently support fraud identification. A total of 178 cow, sheep and goat milk samples were collected from livestock farms in Thessaly, Greece. Sheep and goat milk samples were confirmed as authentic by applying a validated Enzyme Linked Immunosorbent Assay (ELISA), while all samples were analyzed using ATR-FTIR spectroscopy in both raw and freeze-dried form. Freeze-dried samples exhibited clearer spectral characteristics, particularly enhancing the signals from triglycerides, proteins, and carbohydrates. Partial Least Squares Discriminant Analysis (PLS-DA) delivered robust discrimination. By using the spectral range between 600 and 1800 cm⁻¹, 100% correct classification of all milk types was achieved. These findings highlight the potential of FTIR spectroscopy as a fast, non-destructive, and cost-effective tool for milk identification and species differentiation. This method is particularly suitable for industrial and regulatory applications, offering high efficiency. Full article

In his foundational work on classical and quantum electrodynamics, Stueckelberg introduced an external evolution parameter, $\tau$, in order to overcome difficulties associated with the problem of time in relativity. Stueckelberg particle trajectories are described by the evolution of spacetime events under the monotonic advance of $\tau$, the basis for the Feynman–Stueckelberg interpretation of particle–antiparticle interactions. An event is a solution to $\tau$-parameterized equations of motion, which, under simple conditions, including the elimination of pair processes, can be reparameterized by the proper time of motion. The $4+1$ formalism in general relativity (GR) extends this framework to provide field equations for a $\tau$-dependent local metric ${\gamma }_{\mu \nu }(x,\tau )$ induced by these Stueckelberg trajectories, leading to $\tau$-parameterized geodesic equations in an evolving spacetime. As in standard GR, the linearized theory for weak fields leads to a wave equation for the local metric induced by a given matter source. While previous attempts to solve the wave equation have produced a metric with the expected features, the resulting geodesic equations for a test particle lead to unreasonable trajectories. In this paper, we discuss the difficulties associated with the wave equation and set up the more general ADM-like $4+1$ evolution equations, providing an initial value problem for the metric induced by a given source. As in the familiar $3+1$ formalism, the metric can be found as a perturbation to an exact solution for the metric induced by a known source. Here, we propose a metric, ansatz, with certain expected properties; obtain the source that induces this metric; and use them as the initial conditions in an initial value problem for a general metric posed as a perturbation to the ansatz. We show that the ansatz metric, its associated source, and the geodesic equations for a test particle behave as required for such a model, recovering Newtonian gravitation in the nonrelativistic limit. We then pose the initial value problem to obtain more general solutions as perturbations of the ansatz. Full article

Cement production significantly contributes to global warming, resource depletion, environmental degradation, and environmental pollution. Identifying sustainable alternatives is critical but requires balancing multiple, often conflicting, factors. The objective of this study is to determine the most preferred cement alternative produced in South Africa using an integrated life cycle assessment (LCA) and multi-criteria decision-making (MCDM) framework. The LCA quantified the environmental impacts of seven different cement-type alternatives across 18 midpoint impact categories. The LCA results showed that slag cement-based CEM III/A achieved a 50% reduction in global warming potential (GWP) compared to traditional CEM I (0.57 vs. 0.99 kg CO₂ eq. This study also used the entropy-weighted, COPRAS and ARAS methodologies to evaluate and rank cement types based on their environmental impacts and weighted sustainability criteria and the results showed that fly ash-based CEM II/B-V demonstrated the highest overall sustainability, with utility scores of 100.00 (COPRAS) and 0.7257 (ARAS) in MCDM ranking. These results highlight that fly ash-based cement offers substantial environmental benefits over traditional CEM I, particularly in reducing greenhouse gas emissions and resource consumption. The integrated LCA–MCDM method enables robust prioritization by linking quantitative environmental impacts with objective ranking criteria. Although this analysis focuses on South African cement formulations, the methodology and findings are applicable to other regions with similar production profiles and SCM availability. The framework offers a practical tool for policymakers and industry to support environmentally responsible decision-making in cement production. Full article