Search Results (21,716)

This study presents the results of preliminary documentation and radon tracer investigations conducted at the “Aurelia” Mine in Złotoryja. Measurements of ²²²Rn activity concentrations were carried out between 17 March and 26 August 2023, while terrestrial laser scanning (TLS) for mapping purposes was performed on 16 November 2024. The radon data exhibited a consistently right-skewed distribution, with skewness coefficients ranging from 0.9 to 8.2 and substantial standard deviations, indicating significant data dispersion. Outliers and extreme outliers were identified as key factors influencing average radon activity concentrations from April through August, whereas data from March displayed homogeneity, with no detected anomalies. The average ²²²Rn activity concentrations recorded from March to July ranged from 51.4 Bq/m³ to 65.9 Bq/m³. In contrast, July and August showed elevated average values (75.8 Bq/m³ and 5784.8 Bq/m³, respectively) due to the presence of outliers and extreme values. Upon removal of these anomalies, the adjusted means were 73.8 Bq/m³ and 1003.6 Bq/m³, respectively, resulting in reduced skewness and improved representativeness. These findings suggest that the annual average radon concentrations at the “Aurelia” Mine remain compliant with the regulatory threshold of 300 Bq/m³ set by the Atomic Law Act, with exceedances likely related to atypical or rare geophysical phenomena requiring further statistical validation. August exhibited a significant occurrence of outliers and extreme outliers in ²²²Rn activity concentration data, particularly concentrated between the 13th and 17th days of the month. This anomaly is hypothesized to be associated with geological processes, notably mining-induced seismic events within the LGOM (Legnica–Głogów Copper District) region. It is proposed that periodic transitions between tensional and compressional phases within the rock mass, triggered by mining activity, may lead to abrupt increases in radon exhalation, potentially occurring before or after seismic events with a magnitude exceeding 2.5. Although the presented data provide preliminary evidence supporting the influence of tectonic kinematic changes on subsurface radon dynamics, further systematic observations are required to confirm this relationship. At the current stage, the hypothesis remains speculative but may contribute to the broader understanding of radon behavior in geologically active underground environments. Complementing the geochemical analysis, TLS enabled detailed geological mapping and 3D spatial modeling of the mine’s underground tourist infrastructure. The resulting simplified linked data model—integrating radon activity concentrations, geological structures, and spatial parameters—provides a foundational framework for developing a comprehensive GIS database. This integrative approach highlights the feasibility of combining tracer studies with spatial and cartographic data to improve radon risk assessment models and ensure regulatory compliance in underground occupational settings. Full article

3D bioprinting has emerged as a key tool in tissue engineering by facilitating the creation of customized scaffolds with properties tailored to specific needs. Among the design parameters, porosity stands out as a determining factor, as it directly influences critical mechanical and biological properties such as nutrient diffusion, cell adhesion and structural integrity. This review comprehensively analyses the state of the art in scaffold design, emphasizing how porosity-related parameters such as pore size, geometry, distribution and interconnectivity affect cellular behavior and mechanical performance. It also addresses advances in manufacturing methods, such as additive manufacturing and computer-aided design (CAD), which allow the development of scaffolds with hierarchical structures and controlled porosity. In addition, the use of computational modelling, in particular finite element analysis (FEA), as an essential predictive tool to optimize the design of scaffolds under physiological conditions is highlighted. This narrative review analyzed 112 core articles retrieved primarily from Scopus (2014–2025) to provide a comprehensive and up-to-date synthesis. Despite recent progress, significant challenges persist, including the lack of standardized methodologies for characterizing and comparing porosity parameters across different studies. This review identifies these gaps and suggests future research directions, such as the development of unified characterization and classification systems and the enhancement of nanoscale resolution in bioprinting technologies. By integrating structural design with biological functionality, this review underscores the transformative potential of porosity research applied to 3D bioprinting, positioning it as a key strategy to meet current clinical needs in tissue engineering. Full article

CRISPR-Cas9 has emerged as a remarkably powerful gene editing tool and has advanced both research and gene therapy applications. Machine learning models have been developed to predict off-target cleavages. Despite progress, accuracy, stability, and interpretability remain open challenges. Combining predictive modeling with interpretability can provide valuable insights into model behavior and increase its trustworthiness. This study proposes a group-wise L1 regularization method guided by SHAP values. For the implementation of this method, the CRISPR-M model was used, and SHAP-informed regularization strengths were calculated and applied to features grouped by relevance. Models were trained on HEK293T and evaluated on K562. In addition to the CRISPR-M baseline, three variants were developed: L1-Grouped-Epigenetics, L1-Grouped-Complete, and L1-Uniform-Epigenetics (control). L1-Grouped-Epigenetics, using penalties split by on- and off-target epigenetic factors, moderately improved mean precision, AUPRC, and AUROC relative to the baseline, as well as showing reduced variability in precision and AUPRC across seeds, although its mean recall and F-metrics were slightly lower than those of CRISPR-M. L1-Grouped-Complete achieved the highest mean AUROC and Spearman correlation and presented lower variability than CRISPR-M for recall, F1, and F-beta, despite reduced recall and F-metrics relative to CRISPR-M. Overall, this approach required only minor architectural adjustments, making it adaptable to other models and domains. While results demonstrate potential for enhancing interpretability and robustness without sacrificing predictive performance, further validation across additional datasets is required. Full article

Background/Objectives: Head and neck squamous cell carcinoma (NHSCC) is a significant global health burden, with human papillomavirus (HPV) recognized as a major etiological factor in a growing proportion of cases. The interaction between HPV status, tumor characteristics, and other risk factors remains an important focus for both prevention and clinical management. This study aimed to investigate the association between HPV and OPSCC in a Bulgarian cohort, with emphasis on the influence of behavioral and clinical factors, as well as basic tumor features. Methods: Eighty-nine participants were enrolled, including 50 patients with histologically confirmed NHSCC and 39 healthy controls. Clinical examinations and histopathological verification were conducted for all cases. Brush smear and oral rinse samples were collected for HPV testing, in line with molecular detection protocols, specifically PCR-based assays for viral DNA. Demographic data, behavioral risk factors, and information on concomitant diseases were obtained and analyzed in relation to HPV status. Results: Differences were identified between HPV-positive and HPV-negative NHSCC cases in relation to tumor characteristics, including clinical presentation and histological differentiation. Additional analyses demonstrated associations between certain behavioral factors, comorbidities, and the risk of NHSCC. Conclusions: This study provides data on HPV prevalence, related tumor features, and associated risk factors in OPSCC within a Bulgarian population. These findings highlight descriptive trends related to HPV status but indicate no robust statistical associations in this cohort. Full article

As China’s housing market shifts from quantity expansion to quality improvement, consumer expectations for both functionality and aesthetics in residential products are rising. Drawing on the Stimulus–Organism–Response (S-O-R) framework, this study develops a perceptual mechanism model to examine how display design identity and facility service satisfaction influence millennials’ willingness to purchase improved housing, mediated by an elevated sense of style and moderated by upward social comparison. Based on structural equation modeling with 491 valid responses, the findings reveal that facility service satisfaction has a significant direct effect on purchase intention, while display design identity affects behavior indirectly through an elevated sense of style. Moreover, the elevated sense of style serves as a critical mediator in multiple pathways, and its effect is significantly moderated by upward social comparison. This study contributes to the housing consumption literature by clarifying how functional and symbolic factors jointly shape purchase intentions, especially under the influence of social comparison dynamics. It also highlights the role of artistic display design as a symbolic stimulus that enhances style perception and self-identity among younger consumers, offering practical insights for improved housing design and marketing strategies. Full article

Purpose: The Mediterranean diet (MD) is associated with significant health benefits. However, adherence varies considerably, influenced by sociocultural and geographical factors. This review was designed to synthesize existing evidence on the prevalence of MD adherence in different Arab countries and identify sociodemographic, cultural, and behavioral factors associated with adherence. Methodology: Sixteen databases were searched to identify relevant articles, using MeSH search terms related to MD and its applicable terms, adherence, and the names of the 22 Arab countries. Findings: Out of approximately 2400 articles searched, nine articles were selected, investigating adherence to the MD across Arab League countries and exploring the impact of geographic location on dietary practices. Examined Arab populations showed generally moderate adherence to the MD. Wide variability was observed in adherence levels among the different Arab countries. This variability arises from a complex interplay of factors, including access to specific foods, economic considerations, cultural traditions, and the influence of globalization on dietary habits. Our review highlights the role of these factors in contributing to the observed heterogeneity in MD adherence across the Arab League, examining the prevalence of various MD assessment tools and their respective strengths and limitations within this specific context. Conclusions: The findings underscore the need for culturally sensitive and geographically tailored strategies that enhance adherence to the MD’s protective effects across all countries in the Arab League. Full article

Most existing ultra-deep gas wells are characterized by high temperature, high pressure, and high sulfur content. During development, they face serious challenges such as unclear mechanisms of acid gas-induced blowouts and difficulties in wellbore pressure inversion, posing significant challenges to well control operations. To reveal the reasons behind the tendency of acidic gases to trigger blowouts and to clarify the impact of different concentrations of acidic gases on the flow behavior of annular fluids, this study considers the effects of solubility and phase changes on the physical properties of acidic gases. A method replacing critical parameters with pseudo-critical parameters is used to analyze the variation trends of gas density, solubility, and other properties along the well depth. A mathematical model for the annular flow of acidic gas overflow incorporating solubility phase change effects is established. The model is numerically solved using a four-point difference scheme, exploring the essential characteristics of gas flow in the annulus after overflow, and discussing the distribution patterns of physical properties of acidic gases, as well as dynamic parameters such as wellbore pressure and temperature along the well depth. Numerical simulations show that the physical properties of acidic gases change significantly with well depth: the more acidic gas present in the wellbore, the smaller the deviation factor, and the greater the density and viscosity, with parameter changes exceeding 40% near the pseudo-critical point for binary mixtures with 40% H₂S. Compared to pure methane, mixed fluids containing acidic gas experience more than 20% volume expansion near the wellhead for ternary mixtures with 20% CO₂ and 20% H₂S, and the flow velocity increases by more than 10% for mixtures with ≥30% acidic gas content, leading to a higher risk of a sudden pressure drop during well control. This study clarifies the migration patterns of acidic gas overflow in HPHT (high pressure, high temperature) gas wells, providing valuable guidance for optimizing well control design, improving well control emergency plans, and developing well-killing measures. Full article

Children are more vulnerable to the adverse effects of pesticides due to physiological factors and behavioral habits. This study aimed to evaluate the impact of pesticide exposure on telomere length (TL) and the enzymatic activity of acetylcholinesterase (AChE), butyrylcholinesterase (BuChE), and β-glucuronidase (β-Glu) in children ages 6 to 12 from an agricultural area in Mexico. A cross-sectional, descriptive, and analytical study was conducted involving 471 children. Blood samples were collected to assess TL through qPCR and enzymatic activity using established protocols. A pesticide exposure index (PEI) was developed incorporating biomarker levels, urinary dialkylphosphates (DAP), and proximity to farmland. No significant differences were observed in AChE activity across communities; however, BuChE activity was significantly higher in agricultural communities, while β-Glu activity varied among communities. Notably, children aged 6 in agricultural areas showed TL values similar to 12-year-old children in the reference community. Adjusted regression models revealed significantly shorter TL in children from agricultural communities and in children with moderate to high PEI. The findings indicate that chronic pesticide exposure was associated with telomere shortening in children, suggesting accelerated biological aging and potential genomic instability during critical developmental periods. Full article

Background: Indonesia launched a nationwide school-based HPV immunization program in August 2023. Despite this, regional disparities in vaccine uptake persist. Therefore, we undertook a study in North Sumatra Province to assess HPV vaccination coverage and analyze the main factors affecting the uptake of HPV vaccination. Methods: This study employed a mixed-methods approach and was carried out in Medan and Deli Serdang of North Sumatra Province. Quantitative data were used to examine HPV coverage rates among school-aged girls in 2024, while qualitative interviews with parents, teachers, and health officers explored administrative, social, and behavioral barriers and facilitators. Results: In 2024, HPV vaccine coverage in Deli Serdang reached 62.09%, while Kota Medan lagged behind at just 27.20%. High-coverage schools in the Galang subdistrict benefited from proactive engagement between Puskesmas (community health clinics) and parents. In contrast, lower-coverage areas experienced logistical and communication challenges. Parents expressed a preference for face-to-face communication over written consent forms and emphasized the importance of clear, empathetic messaging. Conclusions: The stark contrast in coverage—particularly the low uptake in urban Kota Medan—highlights the need for more responsive and localized implementation strategies. Strengthening direct communication, addressing administrative inefficiencies, and fostering trust through tailored community engagement are critical. These findings suggest a need for targeted improvements in urban settings and further research across diverse regions to inform policy development and strategies for improved coverage of HPV vaccinations. Full article

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by deficits in social communication, repetitive behaviors, and sensory sensitivities. While genetic factors contribute significantly to ASD risk, a growing body of evidence implicates environmental exposures and immune-mediated mechanisms in the etiology and severity of ASD. This review synthesizes peer-reviewed findings on (1) maternal immune activation, (2) environmental toxicant co-exposures, (3) maternal autoimmune disease, and (4) cerebral folate deficiency (via folate receptor alpha autoantibodies), detailing their mechanistic contributions to core and associated ASD symptoms. Collectively, these findings illuminate converging neuroimmune and metabolic pathways that, when disrupted in utero, substantially alter the developmental trajectory of the brain and increase the likelihood of ASD. Such interruptions leading to developmental changes can trigger immune activation from environmental sources of infection and pollution, with these triggers compounded in cases of autoimmune disease or cerebral folate deficiency. Understanding these mechanisms provides a foundation for early identification, stratified risk assessment, and the development of targeted prenatal interventions. Thus, a lesson we learn from autism is that neurodevelopmental disorders should be understood as the product of combined genetic vulnerabilities and modifiable prenatal and postnatal influences. Further exploration of this framework will open paths for precision intervention and prevention. Full article

The confined space of coal mines characterized by curved tunnels with rough surfaces and a variety of deployed production equipment induces severe signal attenuation and interruption, which significantly degrades the accuracy of conventional channel estimation algorithms applied in coal mine wireless communication systems. To address these challenges, we propose a modified Bilinear Generalized Approximate Message Passing (mBiGAMP) algorithm enhanced by intelligent reflecting surface (IRS) technology to improve channel estimation accuracy in coal mine scenarios. Due to the presence of abundant coal-carrying belt conveyors, we establish a hybrid channel model integrating both fast-varying and quasi-static components to accurately model the unique propagation environment in coal mines. Specifically, the fast-varying channel captures the varying signal paths affected by moving conveyors, while the quasi-static channel represents stable direct links. Since this hybrid structure necessitates an augmented factor graph, we introduce two additional factor nodes and variable nodes to characterize the distinct message-passing behaviors and then rigorously derive the mBiGAMP algorithm. Simulation results demonstrate that the proposed mBiGAMP algorithm achieves superior channel estimation accuracy in dynamic conveyor-affected coal mine scenarios compared with other state-of-the-art methods, showing significant improvements in both separated and cascaded channel estimation. Specifically, when the NMSE is ${10}^{-3}$, the SNR of mBiGAMP is improved by approximately 5 dB, 6 dB, and 14 dB compared with the Dual-Structure Orthogonal Matching Pursuit (DS-OMP), Parallel Factor (PARAFAC), and Least Squares (LS) algorithms, respectively. We also verify the convergence behavior of the proposed mBiGAMP algorithm across the operational signal-to-noise ratios range. Furthermore, we investigate the impact of the number of pilots on the channel estimation performance, which reveals that the proposed mBiGAMP algorithm consumes fewer number of pilots to accurately recover channel state information than other methods while preserving estimation fidelity. Full article

Diabetic neuropathy (DN) is one of the most prevalent complications of diabetes mellitus, affecting a substantial proportion of patients and contributing to progressive sensorimotor dysfunction. Despite its clinical significance, available treatments are often insufficient and associated with undesirable effects. This study aims to evaluate the potential of Morus alba (MA), Angelica archangelica (AA), Valeriana officinalis (VO), and Passiflora incarnata (PI) extracts in ameliorating nociceptive alterations and inflammatory markers in the alloxan-induced diabetic rat model. Male Wistar rats with alloxan-induced DN received oral administration of the plant extracts (200 mg/kg/day) or gabapentin (100 mg/kg/day) for 15 days, the dosage regimen being established based on prior efficacy data in preclinical neuropathy models. Behavioral assessments of thermal and mechanical hypersensitivity were conducted using hot plate, tail withdrawal, von Frey, and Randall–Sellito tests. Tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) levels were quantified in brain and liver homogenates to evaluate neuro-inflammatory responses. All plant extracts produced significant improvements in nociceptive thresholds compared to diabetic control, with the most marked effects observed for MA extract. Pro-inflammatory cytokine levels were significantly reduced in all treatment groups, with MA and AA extracts inducing the most significant reductions in TNF-α and IL-6 concentrations. Computational target prediction and molecular docking analyses revealed that key phytochemicals from the plant extracts may exert antihyperalgesic effects through multi-target modulation, notably via interactions with AAK1, a kinase involved in neuropathic pain signaling. The investigated plant extracts displayed significant antihyperalgesic and anti-inflammatory activities in a rat model of DN. Among them, MA extract revealed the most consistent therapeutic profile, supporting its potential role as a strategy for managing DN. Full article

This study investigates the factors that influence household trip generation across the United States using the National Household Travel Survey (NHTS) dataset. Recognizing the limits of a one-size-fits-all modeling approach, we conduct a two-stage analysis to investigate spatial heterogeneity within travel behavior. Stage one creates a benchmark analysis, comparing advanced machine learning models (CatBoost and random forest) to a traditional linear regression model. Contrary to prevailing trends in predictive modeling, the results reveal that linear regression not only delivers competitive overall performance but also emerges as the best performing model in the majority of states. Providing optimal balance between predictive accuracy and interpretability. Building on these findings, the second stage applies state specific linear models to uncover geographic differences in trip generation drivers. The findings highlight extensive spatial heterogeneity: while core demographic variables like household size and the presence of young children show consistent effects across the US, the influence of socio-economic factors such as income and vehicle ownership are highly context-dependent and spatially volatile. These findings highlight the importance of moving beyond black box modeling and instead implementing place based, context sensitive techniques in the promotion of more effective and equitable transportation plans. Full article

This study investigates the dynamic behaviors of the discrete epidemic model influenced by media coverage through integrated analytical and numerical approaches. The primary objective is to quantitatively assess the impact of media coverage on disease outbreak patterns using mathematical modeling. Firstly, the Euler method is used to discretize the model (2), and the periodic solution is strictly analyzed. Secondly, the coefficients and conditions of restricted flip and Neimark–Sacker bifurcation are studied by using the center manifold theorem and bifurcation theory. By calculating the largest Lyapunov exponent near the critical bifurcation point, the occurrence of chaos and limit cycles is proved. On this basis, the chaotic control of the system is carried out by using state feedback and hybrid control. Under certain conditions, the chaos and bifurcation of the system can be stabilized by control strategies. Numerical simulations further reveal bifurcation dynamics, chaotic behaviors, and control technologies. Our results show that media coverage is a key factor in regulating the intensity of disease transmission and chaos. The control technology can effectively prevent the large-scale outbreak of epidemic diseases. Importantly, enhanced media coverage can effectively promote public awareness and defensive behaviors, thereby contributing to the mitigation of disease transmission. Full article

Integration of thermographic imaging with in situ scanning electron microscopy (SEM) analysis may aid in quantifying thermal–mechanical behavior during tensile testing of 3D-printed polymers, which gives information about fracture mechanics, including the associated thermal phenomena. Upon fracture, samples exhibit changes in the thermal field, which is interesting because temperature fluctuations can affect material integrity. The paper introduces printing parameters to demonstrate a thermal measurement system’s sensitivity in detecting variations in mechanical response due to controlled changes in the process. Employing scientific methods, one can extrapolate results to a wider class of materials such as thermoplastics. Analysis of variance (ANOVA) is key in the design of experiments (DOE) if one wants to analyze the effect of factors and interactions. It has been used with the purpose of reducing the risk of type I errors (i.e., false positives). The finite element method (FEM) highlights temperature distribution in the area of interest and confirms recorded data. The particularly developed research experiments are carried out in a laboratory environment. Different samples are subjected to tensile tests under the evaluation of changes in the thermal field. SEM analysis is also widely used in fracture analysis to understand failure modes (ductile vs. brittle, crazing, delamination, and others). Thus, the paper aims to present a custom setup comprised a thermal camera pointed at samples during tensile testing that would serve as a reliable assessment system that accounts for the substitution of a sensor-based environment but is still fully capable of validating the measurement approach. Full article