Search Results (4,204)

The selection of hazard factors is an important factor affecting the accuracy of landslide susceptibility mapping (LSM). The systematic development of an integrated input framework, incorporating both static and time-varying factors, as well as comparative studies of different input frameworks, remains at a preliminary stage. The degree of fit between each data-driven method and landslide-prone environment cannot be known in advance, so the best modeling method can only be determined through comparative studies. Therefore, the Pearson correlation coefficient method and collinearity diagnostics were used to screen the hazard factors, and three hazard factor combinations, considering both static and time-varying factors, were established. A total of 4498 landslide grids and 4498 non-landslide grids were determined, among which 70% (3149 landslide grids and 3149 non-landslide grids) were training samples, and the remaining 30% (1349 landslide grids and 1349 non-landslide grids) were verification samples. The three combinations were input to five models (Support Vector Machine, Random Forest, Convolutional Neural Network-Random Forest, Convolutional Neural Network-Support Vector Machine and Deep Belief Network-Multilayer Perceptron). The results show that the LSM results of different combinations and models are quite varied, and the combination No.3 and the Deep Belief Network-Multilayer Perceptron are the best. The study area is divided into extremely low susceptible areas, low susceptible areas, medium susceptible areas, high susceptible areas and extremely high susceptible areas, and the extremely high susceptible areas mainly distribute in the northwest, south and east. The other models overestimate the distance from the fault and underestimate the distance from the road. The extreme tendency of LSM results of the combinations No.1 and No.2 are strong, and they are easy to produce error estimation areas, which overestimate the elevation and underestimate the distance from the river. The LSM results of the Convolutional Neural Network-Support Vector Machine are closer to those of the benchmark, which underestimates the distance from the road and overestimates the distance from the fault. This study selected the best combination and model through comparative studies and revealed the degree of influence of each hazard factor on landslide susceptibility, greatly improving LSM accuracy, which can provide a scientific basis for land use planning. Full article

This research focuses on characterizing typical displacement patterns in concentrically braced frame (CBF) systems for use in the direct displacement-based seismic design (DDBD) methodology. Using the finite-element program SeismoStruct, two-dimensional models were developed for nonlinear time–history analysis (NLTHA), employing scaled real accelerograms, conventional gravity loads, and detailed numerical models. Thirty varied CBF configurations with different numbers of storeys, spans, and bracing types were evaluated. It was found that the conventional displacement profiles, commonly used for moment-resisting frames, do not accurately represent the actual behavior of CBFs in the inelastic range. Therefore, fitted equations were developed and validated to accurately represent the actual displacements of CBF systems, accounting for factors such as the fundamental vibration period and equivalent system damping. These improvements enable the seismic design optimization, advanced displacement and drift control, and strengthen structural safety and performance in high-seismicity zones in the region. This contribution is relevant to performance-based engineering, facilitating a plausible update to regulations and best practices for seismic-resistant design. Full article

Soil alkalinization constitutes a significant abiotic stress factor that severely constrains global agricultural productivity. The application of alkali-tolerant endophytes represents a promising strategy for enhancing crop resilience. This study focused on the isolation and characterization of alkali-resistant endophytic fungi derived from wild soybean (Glycine soja), aiming to elucidate their potential in promoting host plant growth and to investigate their molecular responses to alkali stress. From an initial collection of 39 wild soybean endophytic fungal isolates, 12 strains demonstrated significant alkali tolerance, as evidenced by increased mycelial dry weight under both mild and intense alkali stress. Among these, two strains, designated WDR2 and WDR5, demonstrated particularly pronounced biomass enhancement and were taxonomically identified as Fusarium verticillioides through comprehensive morphological and molecular analyses. Subsequent inoculation assays conducted on maize (Zea mays) revealed that both fungal strains significantly alleviated the inhibitory effects of alkali stress on root system architecture. Comparative evaluations in soybean indicated that the growth-promoting effects of these endophytes were host-specific and varied according to fungal strain, stress intensity, and inoculation timing. Transcriptomic profiling via RNA-Seq under mild alkali stress identified 589 and 182 differentially expressed genes (DEGs) in WDR2 and WDR5, respectively, with only 43 DEGs shared between the two strains, indicating largely strain-specific transcriptional adaptations. Functional enrichment analysis revealed several shared mechanisms underlying alkaline adaptation in both fungi species, including the maintenance of ion homeostasis, remodeling of the cell wall, and regulation of protein complex assembly and oxidative stress responses. Moreover, distinct metabolic adaptations were identified: WDR2 exhibited significant enrichment in cellular integrity and modulation of membrane-related processes, as well as amino sugar and nucleotide sugar metabolism pathways. In contrast, WDR5 was enriched in phosphate ion transport and related transporter functions, glycerol kinase activity, and glycerolipid and glutathione metabolism. In summary, this study successfully identified two novel alkali-tolerant wild soybean endophytic fungi, WDR2 and WDR5. The results provide valuable insights into their divergent molecular adaptation strategies and highlight their potential application as bio-inoculants to enhance crop productivity in alkaline soils. Full article

The rapid development of autonomous vehicle technologies represents a major transformation in contemporary transportation systems; however, their successful integration depends not only on technological maturity but also on societal acceptance. This study investigates public attitudes toward autonomous vehicles, with particular emphasis on generational and gender-based differences, aiming to identify key factors influencing acceptance, usage intention, and purchase-related decision-making. A quantitative, cross-sectional research design was applied using an online questionnaire survey conducted between January and September 2025. The final sample consisted of 655 respondents, with a balanced gender distribution and representation across multiple generational cohorts. Statistical analyses included one-way and two-way analysis of variance (ANOVA), complemented by non-parametric tests when distributional assumptions were not fully met. The results indicate significant generational differences across all examined dimensions. Younger generations, particularly Generations Y and Z, exhibit significantly higher willingness to try autonomous vehicles, greater openness to new technologies, and stronger consideration of autonomous functions in vehicle purchasing decisions. Gender-based differences were also identified, with men generally demonstrating higher technological openness than women. Moreover, a significant interaction effect between generation and gender was found, suggesting that gender differences vary across generational groups and are less pronounced among younger cohorts. Despite these contributions, the study has several limitations. Its cross-sectional design captures attitudes at a single point in time and does not allow causal inference or longitudinal analysis of attitude change. The use of self-reported, hypothetical measures may not fully reflect actual behaviour in real-world adoption scenarios. Additionally, online data collection may introduce self-selection bias, favouring respondents with higher digital literacy and technological interest. Overall, the findings highlight the importance of considering demographic heterogeneity when developing, communicating, and regulating autonomous vehicle technologies, while also underscoring the need for longitudinal and behaviour-based research in future studies. Full article

The poor clinical outcomes of pediatric high-grade glioma (pHGG) highlight the urgent need for new therapies. Oligodendrocyte lineage transcription factor 2 (OLIG2) is a pro-mitotic transcription factor highly expressed in glioma stem cells and may represent a novel therapeutic target. To evaluate the therapeutic efficacy of an OLIG2 inhibitor CT-179 in pHGG, we determined the OLIG2 mRNA expression in 10 patient-derived orthotopic xenograft (PDOX) models. In vitro activities of CT-179 were analyzed in monolayer and neurosphere cells (0–10 µM) with and without radiation (XRT) (0–8 Gy), brain penetration was evaluated in tumor-bearing PDOX mice, and in vivo efficacy was determined at 15–240 mg/kg (oral) alone or combined with XRT (2 Gy/day × 5 days). Changes in animal survival times were analyzed using the Kaplan–Meier method, followed by pair-wise comparisons. Increased OLIG2 mRNA expression was detected in seven out of ten PDOX models. CT-179 inhibited cell viability in a time- and dose-dependent manner in all eight pGBM xenograft tumors (IC₅₀ 0.03–10 µM) and was potentiated by XRT (0.03–1 µM). Oral gavage (24 mg/kg) of CT-179 for 5 days led to effective penetration in mouse cerebrum (3232.7 ± 569.2 ng/g), cerebellum (1563.3 ± 269.6 ng/g), brain stem (1685.3 ± 309 ng/g), and PDOX tumors (1814 ± 110.3 ng/g) vs. 361.3 ± 1.5 ng/mL in serum. CT-179 alone was not active at 200 mg/kg in four models, although it was moderately effective at 240 mg/kg in one model. When combined with XRT, a significant extension of animal survival times was observed in two out of four models. Doses needed to eliminate OLIG2 expression in vitro varied from 0.3 to >1 µM in pGBM cells. In summary, our data showed that orally administered CT-179 penetrated the blood–brain barrier (BBB) and exhibited potential for inhibiting pGBM growth when combined with XRT. Full article

Government building projects are particularly complex due to their scale and number of end users, which makes construction prices time-consuming and prone to error. Machine learning is recognized for its ability to process large volumes of complex data quickly with high accuracy, but only a limited number of studies have applied Deep Learning in the early construction stage. Therefore, we aimed to evaluate the potential of Deep Learning to predict construction contract prices for government buildings. Factors were identified through a literature review and interviews with eight experts, and data were collected from 300 government construction projects obtained from Thailand’s Electronic Government Procurement (e-GP) database, the national centralized platform for transparent public bidding. By varying the number of parameters, 80 models were developed and tested. The best-performing model had a three-hidden-layer ratio of 128:64:32 with a Quadratic Loss Function, achieving an R² of 0.918 and an RMSE of 2.022. The results showed 14 significant factors, with the top 5 being (1) usable area, (2) number of sanitary wares, (3) number of rooms, (4) height, and (5) number of elevators. Sensitivity analysis was subsequently conducted to enhance the explainability of the model. The findings demonstrate the potential of Deep Learning to enhance the accuracy of determining construction price and support more effective government budget planning and decision making. Full article

Infrasound, physically defined as sound at frequencies below 20 Hertz, can travel long distances with minimal attenuation and permeate biological tissues due to its marked particle displacement and deep penetration. Generated by both natural phenomena and human-made systems, infrasound has drawn increasing scientific and public attention regarding its potential physiological and psychological effects. Experimental studies demonstrate that infrasound can modulate mechanosensitive structures at the cellular level, particularly pressure-sensitive ion channels such as PIEZO1 and TRPV4, leading to intracellular calcium influx, oxidative stress, altered intercellular communication, and in some settings, apoptosis. These responses vary according to sound pressure levels, frequencies, exposure duration, and tissue type. In the cardiovascular system, higher sound pressures have been associated with mitochondrial injury and fibrosis, whereas low sound pressures may exert context-dependent protective effects. In animal models, prolonged or intense exposure to infrasound has been shown to induce neuroinflammatory responses and memory impairment. Short-term studies in humans at moderate intensities have reported minimal physiological changes, with psychological and contextual factors influencing symptom perception. Occupational environments such as factories and agricultural settings may contain elevated levels of infrasound, underscoring the importance of systematic measurements and exposure assessments. At the same time, controlled infrasound stimulation has shown potential as an adjunct modality in bone repair and tissue regeneration, highlighting its dual capacity as both a biological stressor and a possible therapeutic tool. Overall, existing data indicate that infrasound may be harmful at chronic exposure depending on intensity and frequency, yet beneficial when precisely regulated. Future research should standardize exposure metrics, refine measurement technologies, and clarify dose–response relationships to better define the health risks and therapeutic applications of infrasound. Full article

Background/Objectives: This study aimed to investigate whether therapy with perampanel is associated with the development of psychosis or psychosis-like symptoms in patients with epilepsy. Methods: We conducted systematic electronic searches in PubMed, Google Scholar, ScienceDirect, and Scindex databases. We included articles published as case reports/case series, as well as conference abstracts and letters from the editor, if they contained enough data for analysis and quality assessment. The main inclusion criteria relate to patients who experienced psychosis or psychosis-like symptoms described by the authors during perampanel therapy or during its recent use. Results: Publications (n = 17) describing a total of 33 patients who met the inclusion criteria were included. Patient ages ranged from 11 to 70 years, and the majority of them were female (66.67%). A confirmed personal psychiatric history was identified in 60.61% of patients. The time interval between the initiation of perampanel and the onset of adverse events varied significantly across cases. The most frequently reported symptom was aggression (75.75%), followed by irritability (30.30%), while delusions or hallucinations were observed in 8 patients (24.24%). Conclusions: Clinicians should be aware that psychosis or psychosis-like symptoms may represent dose-dependent adverse effects of perampanel with a satisfactory prognosis. Identified risk factors for these developments were positive personal psychiatric history, antiseizure polytherapy at high doses, women’s gender, and focal epilepsies with secondary generalization, mainly manifested as tonic–clonic seizures. Early recognition of symptoms, followed by drug discontinuation, dose reduction, symptomatic treatment, or a combination of the mentioned strategies, is crucial for achieving better outcomes. Full article

Background/Objectives: In food-producing animal (FPA) environments, healthy animals can act as reservoirs of potentially pathogenic Escherichia coli, which can be transmitted through the food chain to humans. This study aimed to evaluate cloacal E. coli in healthy Sicilian lambs subjected to an experimental feeding regimen by assessing bacterial levels, antimicrobial resistance, virulence traits, and the clonal relationships, as well as the impact of a pistachio skin as an agro-industrial by-product supplement during a 58-day feeding trial. Methods: A total of 295 E. coli isolates from the control (CTRL) and treatment (Treated) groups at initial time (T0) and final time (T1) were phenotypically and genotypically characterized using Kirby–Bauer antimicrobial testing, multiplex PCR for virulence genes, and PFGE for clonal analysis. Results: The feeding regimen did not significantly influence the prevalence, abundance, or virulence of the E. coli isolates. Shiga toxin-producing E. coli (STEC) were the most common pathotype, mainly carrying the stx1 gene, while the Enteroinvasive (EIEC) type was detected only sporadically. Enteropathogenic E. coli (EPEC) predominated at T0, while enteroaggregative E. coli (EAEC) at T1, and enterotoxigenic E. coli (ETEC), initially prevalent in Treated samples, disappeared by T1. Antimicrobial resistance profiles varied among isolates, with the highest resistance observed in the CTRL group. However, both groups exhibited high resistance to streptomycin, and 9% of CTRL isolates were multidrug resistant. A notable reduction in overall resistance rates, especially in the Treated group, was observed, indicating a dietary effect on the E. coli resistome. PFGE genotyping showed high genetic diversity, with resistance traits more frequently detected than virulence factors. Conclusions: This study highlights that healthy lambs serve as reservoirs for potentially human-pathogenic E. coli and suggests that dietary regimes could effectively reduce antibiotic resistance. Full article

This study investigates the influence of reaction conditions on the stereoselective Wittig synthesis of a thienostilbene analogue of trans-resveratrol. Reaction conditions were systematically varied across batch experiments and analysed using Spearman correlation, principal component analysis (PCA), and response surface methodology (RSM) to identify key factors (base type and amount, solvent type and volume, system configuration, and reaction time) affecting conversion and the trans/cis ratio. The base type, solvent type, and system configuration had the strongest impact on stereoselectivity, while solvent volume proved effective in enhancing the trans-isomer. PCA revealed that cyclic ether solvents combined with medium-strong bases provide the best balance between conversion and selectivity. RSM predicted optimal conditions in a two-phase NaOH system via phase transfer catalysis (PTC) with increased organic solvent volume, which experimentally increased conversion from 35% to over 92% and raised the trans/cis ratio to 1.81. Transferring the optimized process to continuous flow dramatically reduced reaction time, achieving 67.5% conversion in 15 min while maintaining stereoselectivity. These results demonstrate how statistical optimization combined with flow processing can significantly accelerate the development of stereoselective Wittig reactions. Full article

The environmental profile of the electricity grid varies throughout the year, especially with the introduction of renewables, given their high level of discontinuity. Additionally, positive energy districts emerged as a solution for decarbonizing the building sector, thanks to high levels of self-consumed electricity and the benefits of exporting electricity to the national grid. Most life cycle assessment studies assume a retrospective and static background system for these evaluations. This study presents a prospective attributional life cycle assessment of the Italian national electricity grid for 2024–2040. Hourly factors were derived from a cost-optimization energy model, plus ecoinvent and PREMISE for background modeling. The model projects a sharp decline in fossil-based generation and a significant expansion of solar photovoltaics and wind, which together exceed half of national production by 2040. A total of 16 impact categories were evaluated, revealing decreasing trends in climate change (255 to 141–100 gCO₂-eq/kWh_e) and others, and rising temporal variability in mineral/metal resource depletion and land use due to renewable intermittency. Applying the method to a positive energy district in Bologna shows that time-resolved factors offer clearer insights than annual averages, especially for season-dependent impacts, and demonstrate substantial reductions in impact by 2040, alongside notable differences between consuming and exporting electricity. Full article

Background/Objectives: Chemsex is defined as the intentional use of psychoactive substances to enhance or prolong sexual activity, predominantly observed among men who have sex with men. It has emerged as a notable behavioral and public health concern due to its association with high-risk sexual practices, psychiatric morbidity, and somatic complications. Despite increasing recognition, global prevalence estimates vary widely (3–52.5%) due to differences in study populations and methodology. Commonly used substances include synthetic cathinones, amphetamines/methamphetamines, MDMA, GHB/GBL, ketamine, alkyl nitrites, and PDE-5 inhibitors. Methods: A narrative review was conducted using PubMed through 11 December 2025. Search terms combined chemsex-related terminology, substance names, and health outcomes. Recent English-language publications (2020–2025) were prioritized. Evidence was synthesized thematically across epidemiology, health complications, motivations, and interventions. Results: Chemsex is strongly associated with unprotected sex, multipartner encounters, and prolonged intercourse, leading to significantly increased rates of HIV, syphilis, gonorrhoea, and chlamydia. Psychiatric complications include depression, anxiety, compulsive sexual behavior, and psychosis, with higher risks in individuals engaging in slamming or polysubstance use. Somatic complications vary by substance and include cardiovascular disease, hyponatremia, rhabdomyolysis, ulcerative cystitis, methemoglobinemia, and overdose. Motivational factors extend beyond sexual enhancement and include minority stress, internalized and externalized stigma, and maladaptive coping mechanisms. Integrated interventions combining harm reduction, cognitive–behavioral therapy, peer-led services, and pharmacotherapy, alongside digital health tools to support PrEP adherence and risk reduction, show promise in mitigating these harms. Conclusions: Chemsex represents a complex interplay of biological, psychological, and sociocultural factors that contribute to elevated STI risk and psychiatric and somatic morbidity. Addressing chemsex requires destigmatized, multidisciplinary approaches that integrate behavioral, pharmacological, and community-based interventions. Digital health innovations can further enhance engagement, risk reduction, and access to timely care. Full article

Fiber-reinforced laminates composed of a thermoset matrix have seen widespread use in industries such as the aerospace, wind power, and automotive industries, due to their strength-to-weight ratios and ease of formability. For optimal performance, the instantaneous cure state must be sufficient such that the component will not deform during or after molding, a state that can vary based on many manufacturing-related factors. Thus, monitoring the cure process non-destructively in situ is key to manufacturing composite laminates to achieve the as-designed properties while balancing the cycle time reduction. The current work presents a pulse-echo ultrasound method to correlate the acoustic waveform to the thermoset resin cure state and the instantaneous structural properties, specifically the resin storage and loss moduli. This latter information provides a fabricator knowledge of when a part can be successfully demolded, allowing for optimizing part cycle times. The present paper provides the results for the neat resin specimen and fiberglass specimen impregnated with the same resin system. The results provide a direct correlation between the acoustic and the viscoelastic properties. Interestingly, it is noted that there is a direct correlation between the peak signal attenuation and the peak gelation of the material, thus providing a means to predictively schedule the demolding time while maintaining proper curing cycles. Full article

In the context of sustainable logistics planning, carbon emission costs have become a critical factor influencing distribution decisions. Meanwhile, the time-dependent characteristics of urban road networks and simultaneous pickup–delivery operations present significant challenges to vehicle routing problems (VRPs). This study addresses a time-dependent vehicle routing problem with simultaneous pickup–delivery and time windows (TDVRPSPDTW). Fuel consumption and carbon emission costs are quantified using a comprehensive emission model, while time-dependent network conditions, simultaneous pickup–delivery demands, and time window constraints are integrated into a unified modeling framework. To solve this NP-hard problem, an improved ant colony optimization (IACO) algorithm is developed by incorporating adaptive large neighborhood search to enhance solution diversity and convergence efficiency. Computational experiments are conducted using internationally recognized VRPSPDTW benchmark datasets and newly constructed TDVRPSPDTW instances, together with sensitivity analyses under varying traffic conditions, time window flexibility, and delivery strategies. The results indicate that the proposed IACO effectively addresses the TDVRPSPDTW. Comparing ant colony optimization with local search (ACO-LS), the IACO achieves a maximum reduction of 11.78% in total distribution cost. Furthermore, relative to the conventional separate pickup–delivery strategy, the simultaneous pickup–delivery mode reduces total distribution cost and carbon emission cost by 49.96% and 53.48%, respectively. Full article

High Mobility Group ^{Box 1} (HMGB1) and S100 proteins are major ligands of Receptor for Advanced Glycation End-products (RAGE) and have causal roles in endometriosis lesions. Yet the AGE–RAGE pathway that unifies Advanced Glycation End-products (AGEs) with these ligands has not been assessed in endometriosis. In diabetes, atherosclerosis, and chronic kidney disease, AGE–RAGE links insulin resistance and oxidative stress to inflammation, fibrosis, and organ harm. Endometriosis shares key drivers of AGE accumulation, including insulin resistance, oxidative stress, and chronic inflammation. Endometriosis is also linked to higher vascular risk and arterial stiffness. We asked whether AGE–RAGE could bridge metabolic stress to pelvic lesions and systemic risk. We did a focused review of mechanisms and an evidence map of studies on AGEs, RAGE, or known RAGE ligands in endometriosis. We grouped findings as most consistent with a driver, amplifier, consequence, or parallel role. We included 29 studies across human samples, cell systems, and animal models. Few studies measured AGE adducts directly. Most work tracked RAGE ligands (mainly HMGB1 and S100 proteins) and downstream immune and angiogenic programs. Across models, this pattern fits best with a self-reinforcing loop after lesions form. RAGE expression often aligned with lesion remodeling, especially fibrosis. Blood and skin readouts of AGE burden were mixed and varied by cohort and sample type. A central gap is receptor proof. Many models point to shared Toll-like receptor 4 (TLR4)/ nuclear factor kappa B (NF-κB) signaling, but few test RAGE dependence. Overall, current evidence supports AGE–RAGE as a disease-amplifying loop involved in chronic inflammation and fibrosis rather than an initiating trigger. Its effects likely vary by stage and site. Priorities now include direct lesion AGE measurement, paired systemic–pelvic sampling over time, receptor-level studies, and trials testing diet or drug interventions against clear endpoints. Outcomes could include fibrosis, angiogenesis, immune state, pain, and oocyte and follicle function. Full article