Search Results (20,357)

Concrete diagnosis is an important task in making informed decisions about reconstructing or repairing buildings. Among the different approaches for evaluating its characteristics, methods based on electromagnetic waves have been proposed in the literature over the years. In this context, the characterization of concrete complex dielectric permittivity ${ϵ}_r\left(f\right)$ (where f is the frequency) has received considerable attention, taking into account that its values and its frequency behavior are both sensitive to a series of physical parameters, which in turn can significantly influence the mechanical performance of concrete. Recently, data-driven techniques have emerged as alternatives for modeling material properties due to their regression and generalization potential. Following this research line in this work, we investigated the potential of Gaussian Process Regression to model ${ϵ}_r\left(f\right)$ by comparing its performance with that of the model most employed to characterize the concrete dielectric permittivity: the universal Jonscher model. The inherent ability to provide predictions accompanied by confidence intervals, which allows the assessment of the reliability of the permittivity estimate across frequency, and the related error metrics demonstrate that GPR can effectively characterize ${ϵ}_r\left(f\right)$ in an effective manner, outperforming the Jonscher model in terms of accuracy in all the cases considered in our study. Full article

Preschool children develop essential mathematical concepts through play, yet little is known about how traditional board games can support this process. This small-scale microgenetic case study investigates how children unfamiliar with the Ethiopian game Gebeta (a mancala-type game) learn to play the game and what mathematical competencies emerge. Video observations were conducted with 5-year-olds in Norway as they engaged in repeated play sessions. Event logs and transcripts were analysed with a focus on children’s developing strategies and difficulties. The results show that children quickly understood the basic rules but faced challenges with directionality (i.e., maintaining the correct direction of play) and differentiating between different types of game moves. Over time, they demonstrated evident progress in following the rules. They began to treat groups of counters as units, moving from one-by-one counting to bundling and unitising. These developments align with Bishop’s fundamental activities locating and counting. We conclude that Gebeta provides a playful context in which children can practice directionality and bundling, both of which are crucial for avoiding common errors in later school mathematics, such as off-by-one counting errors and misunderstandings of the number system. The study suggests that Gebeta can be introduced in early childhood settings without simplifying the rules, providing an engaging resource for early mathematics education. Full article

As ESG sustainability uncertainty intensifies and globalisation deepens, the energy trilemma—security, equity, and sustainability—emerges as the defining calculus of modern energy policy. Therefore, this investigation explores the influence of ESG sustainability uncertainty intensification and globalisation on the energy trilemma, while controlling education, urbanization and economic growth, using data from 2001 to 2022. The energy trilemma offers an all-inclusive gauge for understanding the effect of ESG sustainability uncertainty on energy trilemma. The study employed Lewbel’s Two Stage Least Squares method to examine the connection. The results disclose that ESG sustainability uncertainty is negatively associated with all three trilemma pillars. Globalisation displays a nonlinear influence: its squared terms are negative and statistically significant, implying diminishing marginal benefits at high levels of openness. This paper’s significance lies in evidence that ESG sustainability uncertainty erodes all three pillars of the energy trilemma, while globalization’s benefits taper at high openness—strengthening the mandate for a clean, just, secure, and sustainable transition. Full article

Textile production contributes significantly to water pollution, making dye removal crucial for protecting water resources from toxic textile waste. The use of nano-adsorbents for water purification has emerged as a promising approach to removing pollutants from wastewater. Nickel Ferrite (NiFe₂O₄), Iron Oxide (Fe₂O₃), and Nickel Oxide (NiO) nanoparticles (NPs) were prepared via an auto-combustion sol–gel technique using chitosan as a capping and stabilizing agent. The prepared nanomaterials were characterized using various techniques such as XRD, UV-Vis DRS, FT-IR, Raman, EDX, SEM, and TEM to confirm their structure, particle size, morphology, functional groups on the surface, and optical properties. Subsequently, the adsorption of the methylene blue (MB) dye using the prepared nanomaterials was studied. NiFe₂O₄ NPs exhibited the best adsorption behavior compared to the mono-metal oxides. Moreover, all prepared nanomaterials were compatible with the pseudo-second-order model. Further investigations were conducted for NiFe₂O₄ NPs, showing that both the Freundlich and Langmuir isotherm models can explain the adsorption of the MB dye on the surface of NiFe₂O₄ NPs. Factors affecting MB dye adsorption were discussed, such as adsorbent dose, concentration of the MB dye, contact time, pH, and temperature. NiFe₂O₄ NPs exhibited a maximum removal efficiency of the MB dye, reaching 96.8% at pH 8. Different water sources were used to evaluate the ability of NiFe₂O₄ NPs to purify a wide range of water types. Full article

Background/Objectives: Psychogenic non-epileptic seizures (PNES) are seizure-like episodes not caused by abnormal brain activity, often linked to emotional dysregulation, dissociation, and altered interoceptive awareness. Standardized treatments are limited. This study aimed to explore the feasibility and preliminary psychological effects of a group-based mindfulness-based intervention (MBI) in individuals with PNES. Methods: This single-arm, pre–post pilot study (no control group) enrolled fifteen participants in two cycles of an 8-week MBI delivered either in-person or online. Twelve participants completed pre/post self-report assessments of depression (BDI-II), anxiety (STAI-Y1), perceived stress (PSS-10), sleep quality (PSQI), dissociation (DES-II), meteoropathy (METEO-Q), mindfulness (FFMQ), and interoceptive awareness (MAIA). Results: The intervention was well tolerated (dropout rate: 20%). Trend-level, non-significant improvements emerged for depressive symptoms (p = 0.092, r = 0.564) and sleep quality (p = 0.078, r = 0.591). A significant reduction was observed in the FFMQ Describing subscale (p = 0.045, r = 0.697). No significant changes were found in anxiety, perceived stress, or interoceptive awareness, although certain MAIA subscales indicated small, non-significant increases. Conclusions: Despite the limited sample size and absence of a control group, these preliminary findings support the feasibility and acceptability of MBIs for PNES, warranting further controlled investigations. Full article

Grounded in a sociocultural theory, this study investigates how distinct interaction scenarios influence Chinese English as a Foreign Language (EFL) learners’ technology acceptance: perceived usefulness (PU) and perceived ease of use (PEU), and their willingness to communicate with AI (AI-WTC). A total of 367 university students completed a scenario-based questionnaire measuring PU, PEU, and AI-WTC across four empirically derived scenarios: advisory interaction, language skills support, academic knowledge inquiry, and factual information retrieval. Repeated-measures ANOVA with Bonferroni tests revealed significant scenario effects on all three constructs, though effect sizes were small to moderate. Factual Information Retrieval Scenario consistently received the highest ratings, whereas Academic Knowledge Inquiry and Language Skills Support Scenario scored lowest. A salient divergence emerged in complex scenarios: Advisory Interaction Scenario was rated more useful than Language Skills Support Scenario, yet both elicited equally low willingness to communicate, indicating that perceived usefulness alone may not sustain engagement under high interactional demands. These findings suggest that the effectiveness of AI as a communicative scaffold is not inherent but co-constructed through scenario-specific affordances and constraints. The study contributes a scenario-sensitive framework to TAM and WTC research, providing pedagogical guidance for designing differentiated AI-mediated language tasks. Full article

Background: Common variable immunodeficiency (CVID), the most prevalent symptomatic inborn error of immunity, involves impaired B-cell differentiation and antibody production, causing recurrent infections and the need for life-long immunoglobulin replacement therapy. Methods: This study evaluated the in vitro differentiation of memory B-cells (MBCs) into antibody-secreting cells (ASCs) in CVID patients. Peripheral blood mononuclear cells from 13 CVID patients and 10 healthy controls were stimulated using two protocols: (I) Staphylococcus aureus Cowan Strain I, Pokeweed mitogen, and CpG, or (II) a T-cell-dependent approach using CD40 ligand, interleukin-21, and CpG. B-cell subpopulations were analyzed by flow cytometry, ASC differentiation using ELISpot, and antibody levels in supernatants by ELISA. Results: Despite severely restricted in vivo antibody production, MBCs from all 13 CVID patients differentiated into IgG and IgM ASCs under adequate in vitro stimulation. Protocol II, mimicking T-cell help, was more effective than protocol I. As expected, the patients exhibited reduced class-switched MBCs ex vivo, but the MBCs differentiated and proliferated to an extent similar to those in healthy controls. IgA secretion remained significantly impaired post-stimulation. Specific IgG antibodies against tetanus toxoid and Streptococcus pneumoniae were detected in the patient supernatants, while no double-stranded DNA autoantibodies emerged after in vitro stimulation. Conclusions: These findings indicate that the MBCs of most patients retain functional B-cell differentiation and antigen-specific IgG secretion under T-cell dependent stimulation, though IgA secretion remains impaired. Tailored stimulation protocols could deepen our understanding of how to restore MBC formation in CVID patients in vivo. This methodology provides a platform to investigate antigen-specific functional memory responses like post-vaccination. Full article

Ticks transmit diseases and harm animals worldwide, and their control primarily relies on pesticides. Resistance to these pesticides has developed consistently over centuries. Arginine Kinase (AK, EC 2.7.3.3) is a conserved, ancestral enzyme that provides reserve energy in emergency situations and a viable target for novel antiparasitic drugs. Our aim was to evaluate six carbamoyl carboxylic acid analogues (CCAs) as potential lead compounds by investigating their interaction with the active site of Rhipicephalus sanguineus AK (RsAK) using a structural modeling approach. The binding was characterized using fluorescence quenching (Stern–Volmer analysis) and molecular dynamics simulations. The simulations, performed with GROMACS using the CHARMM 26 force field over 100 ns, provided atomic-level insight into the ligand–protein interactions and stability. CCA4 exhibited the lowest dissociation constant (K_D~13·10⁻⁶ M) among the analogues, which we attribute to its end moieties (carboxylate and a pyridine on the ends). Purely aromatic ends (CCA1) or those with dual carboxylates (CCA6) showed lower affinity, suggesting that electrostatic complementarity and steric fit are processes involved in the binding. Despite requiring optimization, the CCA scaffold represents a novel strategy for tick control. These compounds provide a foundation for developing synergistic agents to enhance the efficacy of sustainable acaricides. Full article

Artificial intelligence (AI) and machine learning (ML) have become integral to various applications, leveraging vast amounts of heterogeneous, globally distributed Internet of Things (IoT) data to identify patterns and build accurate ML models for predictive tasks. Federated learning (FL) is a distributed ML technique developed to learn from such distributed data while ensuring privacy. Nevertheless, traditional FL requires a central server for aggregation, which can be a central point of failure and raises trust issues. Blockchain-based federated learning (BFL) has emerged as an FL extension that provides guaranteed decentralization alongside other security assurances. However, due to the inherent openness of blockchain, BFL comes with several vulnerabilities that remain unexplored in literature, e.g., a higher possibility of model poisoning attacks. This paper investigates how scaling-based model poisoning attacks are made easier in BFL systems and their effects on model performance. Subsequently, it proposes FedECPA-an extension of FedAvg aggregation algorithm with Efficient Countermeasure against scaling-based model Poisoning Attacks in BFL. FedECPA filters out clients with outlier weights and protects the model against these attacks. Several experiments are conducted with different attack scenarios and settings. We further compared our results to a frequently used defense mechanism, Multikrum. Results show the effectiveness of our defense mechanism in protecting BFL from these attacks. On the MNIST dataset, it maintains an overall accuracy of $98\%$ and $89\%$ and outperforms our baseline with $4\%$ and $38\%$ in both IID and non-IID settings, respectively. Similar results were achieved with the CIFAR-10 dataset. Full article

The ecological restoration process of larch plantations to mixed forests contributes to enhancing the stability and functionality of forest ecosystems, with soil microbes playing a crucial role in this process. To elucidate the changes in soil microbial communities during this transition and their relationships with soil and litter properties, the study used 16S/ITS rRNA high-throughput sequencing to investigate the diversity and composition of soil bacterial and fungal communities at two soil depths across four restoration stages, and further quantified the relative contributions of soil and litter properties to variations in microbial community structure. The results indicated that bacterial and fungal $\mathsf{\alpha }$-diversity remained relatively stable in the topsoil but varied significantly across restoration stages in the subsoil ($p<0.05$), with the highest levels observed during the broadleaf species invasion stage. Fungal community structure demonstrated greater sensitivity to the restoration process, whereas bacterial communities showed stronger spatial dependency. Variance partitioning analysis revealed that soil properties were the main contributors to the variations of bacterial and fungal communities, accounting for 41% and 28% of the total variance, respectively. Fungal communities were more closely associated with litter properties than bacterial communities. Redundancy analysis combined with hierarchical partitioning further revealed that soil available phosphorus (AP) and total nitrogen (TN) were key factors explaining the variation in both bacterial and fungal communities. Additionally, litter total nitrogen (LTN) also emerged as an important factor affecting soil fungal communities. These findings provide critical microbiological evidence for accelerating the forest restoration in Northeast China through soil fertility management and regulation of litter inputs. Full article

Background: The COVID-19 pandemic significantly affected the mental health of frontline healthcare workers. This study investigated the mental health and occupational stressors faced by frontline workers in Selangor during the pandemic. Methods: A cross-sectional study was conducted using secondary data from the Mental Health and Psychosocial Support Services team, collected from March to August 2020. A total of 4593 frontline workers participated in the Depression, Anxiety, and Stress Scale screening. Results: Mental health symptoms were common among frontline workers during the COVID-19 pandemic, with 14.8% reporting stress, 30.7% anxiety, and 20.4% depression. Female workers had significantly higher odds of all three conditions, with adjusted odds ratios (aOR) of 1.35 (95% CI: 1.10–1.66) for stress, 1.25 (95% CI: 1.07–1.47) for anxiety, and 1.23 (95% CI: 1.03–1.47) for depression. Workers aged 18–30 had higher odds of stress (aOR 1.88; 95% CI: 1.42–2.47), anxiety (aOR 1.74; 95% CI: 1.43–2.12), and depression (aOR 1.80; 95% CI: 1.43–2.27) compared with those over 40. Employment in hospitals was associated with increased odds of all three conditions, with aORs ranging from 1.71 to 2.05. Among 711 respondents who reported occupational stressors, lack of mental health support was the strongest predictor (aORs 4.91–5.20), followed by poor work rotation and conflict with supervisors. Conclusions: Women, younger staff, and hospital workers were more vulnerable to mental health symptoms during the pandemic. Organizational factors, especially limited support and poor work arrangements, played a major role. Targeted mental health services and improved working conditions are needed to support healthcare workers in future emergencies. Full article

Background: High-dose cisplatin (≥200 mg/m² cumulative) remains the standard of care in concurrent chemoradiotherapy (CRT) for locally advanced head and neck squamous cell carcinoma (LA-HNSCC). However, its use is frequently limited by nephrotoxicity, including acute kidney disease (AKD). This recently described clinical renal syndrome encompasses functional alterations of the kidney lasting fewer than 3 months post-exposure. Although hydration protocols and antiemetic strategies are routinely applied to avoid reduction in oral liquid intake and to prevent dehydration that could worsen renal function, AKD continues to pose a threat to reach the therapeutic dose, to treatment completion, and long-term outcomes. Recent evidence supports the nephroprotective role of intravenous (IV) magnesium in mitigating cisplatin-induced tubular injury, yet prospective data on its impact in real-world LA-HNSCC settings remain limited. We aimed to prospectively investigate the incidence and characteristics of renal impairment, particularly AKD, in a real-world cohort of LA-HNSCC patients treated with high-dose cisplatin and standardized supportive therapy, including intravenous magnesium. Methods: We conducted a prospective observational study including 207 patients with LA- HNSCC undergoing high-dose cisplatin-based CRT (≥200 mg/m² cumulative dose), within a standardized supportive care protocol incorporating IV magnesium. Renal function was assessed over three cycles via serum creatinine and estimated glomerular filtration rate (eGFR). AKD was defined and staged according to KDIGO criteria. Clinical and biochemical predictors of AKD were explored. Results: AKD occurred in 5.3% of patients (11/207; 95% CI 2.7–9.3), with eight events between C1→C2, 3 between C2→C3, and 0 thereafter; recovery at the next cycle was 9.1% (1/11). Among them, 57.1% were classified as stage 1. A baseline eGFR < 90 mL/min/1.73 m² was associated with a higher AKD incidence (13.3% vs. 5.4%). Body mass index (BMI) was significantly associated with AKD in univariate analysis (p = 0.02), whereas no independent predictor emerged in multivariate analysis. Use of renin–angiotensin–aldosterone system (RAAS) inhibitors was more frequent among patients who developed AKD (p = 0.04). Renal function declined more steeply in AKD patients, with a median eGFR slope of −0.3917 mL/min/1.73 m²/day vs. −0.0483 mL/min/1.73 m²/day in those without AKD (p = 0.0005), irrespective of CKD stage. Conclusions: In a real-world cohort receiving high-dose cisplatin with structured nephroprotection including IV magnesium, AKD developed in approximately 10% of patients. Lower baseline eGFR, elevated BMI, and RAAS inhibitor use emerged as potential risk factors. These findings reinforce the importance of proactive renal monitoring and suggest a role for magnesium supplementation as an accessible strategy to enhance renal safety in curative-intent CRT. Full article

The quality of teacher education represents a fundamental pillar for effective educational systems. European and Czech educational policies emphasise alignment with labour market demands and continuous professional development of teachers. This study examines the motivations of and barriers faced by secondary school teachers enrolled in a pedagogical study programme at the Czech University of Life Sciences Prague, contextualised within broader European and national strategic frameworks. Employing a mixed-methods approach, the research combined document analysis of international and national educational policy reports with a longitudinal questionnaire survey of 404 bachelor’s level teacher education students. Chi-square tests and sign residual analyses investigated relationships between labour market position, study motivation, and perceived obstacles. Findings reveal that employer requirements primarily drive educational professionals to pursue further qualifications, whilst other occupational groups cite personal interest as their main motivator. Time constraints emerge as the predominant barrier across all groups, followed by inadequate employer support. No significant association was identified between motivation and perceived barriers. Comparative analysis demonstrates Czech teachers’ lower remuneration satisfaction relative to other countries examined in this research. The study concludes that enhanced employer support and targeted policy measures addressing time constraints are essential for effective teacher professional development. Full article

Fiber-optic sensing (FOS) technology has emerged as a cutting-edge research focus in the sensor field due to its miniaturized structure, high sensitivity, and remarkable electromagnetic interference immunity. Compared with conventional sensing technologies, FOS demonstrates superior capabilities in distributed detection and multi-parameter multiplexing, thereby accelerating its applications across biomedical, industrial, and aerospace fields. This paper conducts a systematic analysis of the sensing mechanisms in fiber-optic pressure sensors, with a particular focus on the performance optimization effects of fiber structures and materials, while elucidating their application characteristics in different sensing scenarios. This review further examines current manufacturing technologies for fiber-optic pressure sensors, covering key processes including fiber processing and packaging. Regarding practical applications, the multifunctional characteristics of fiber-optic pressure sensors are thoroughly investigated in various fields, including biomedical monitoring, industrial and energy monitoring, and wearable devices, as well as aerospace monitoring. Furthermore, current challenges are discussed regarding performance degradation in extreme environments and multi-parameter cross-sensitivity issues, while future research directions are proposed, encompassing the integration and exploration of novel structures and materials. By synthesizing recent advancements and development trends, this review serves as a critical reference bridging the gap between research and practical applications, accelerating the advancement of fiber-optic pressure sensors. Full article

Slaughterhouses serve as critical surveillance hubs for identifying subclinical and economically important diseases in food-producing animals. Trueperella (Arcanobacterium) pyogenes, an opportunistic pathogen commonly found on the mucous membranes of livestock, is associated with mastitis, abortion, and suppurative infections such as abscesses. In this study, we investigated 30 pig carcasses fully condemned due to vertebral osteomyelitis (VO) at two slaughterhouses in Gwangju, Republic of Korea, between November 2023 and May 2024. From abscess lesions, 11 T. pyogenes strains were isolated and characterized morphologically, biochemically, and genetically. The hemolytic exotoxin pyolysin (plo gene), a major virulence factor, was detected in five isolates (45.46%). Phylogenetic analysis of partial 16S rDNA sequences confirmed close clustering with known T. pyogenes reference strains. All 11 isolates exhibited multidrug resistance, showing resistance to 8–14 antimicrobial agents per strain. Complete resistance (11/11, 100%) was observed against amikacin (AMI), nalidixic acid (NAL), chloramphenicol (CHL), florfenicol (FFN), and trimethoprim/sulfamethoxazole (SXT). High resistance rates were also detected for erythromycin (ERY) and clindamycin (CLI) (10/11, 90.9%), ceftazidime (TAZ), ceftriaxone (AXO), ciprofloxacin (CIP) (7/11, 63.6%), and tetracycline (TET) and streptomycin (STR) (5/11, 45.5%), while gentamicin (GEN) resistance was found in three isolates (27.3%). In contrast, none of the isolates showed resistance to ampicillin, cefoxitin, or cefotaxime. These findings underscore the epidemiological value of abattoir-based monitoring in detecting emerging pathogens and tracking antimicrobial resistance. The results provide important baseline data to inform disease control strategies, guide antimicrobial stewardship, and support One Health approaches, including the development of preventive measures such as vaccines. Full article