Search Results (11,937)

Understanding Alzheimer’s Disease (AD) progression using resting-state functional Magnetic Resonance Imaging (rs-fMRI) remains an open challenge. Variational Autoencoders (VAEs) provide compact representations of high-dimensional neuroimaging data but lack mechanisms to highlight disease-relevant features. We propose KS-VAE, a novel framework that integrates the Kolmogorov–Smirnov test into the latent space of VAEs to identify statistically significant variables discriminating healthy from pathological brain states. This integration enables measurement of latent space shifts associated with cognitive decline, offering a quantitative approach to neurodegenerative processes. By modifying the most relevant variables, KS-VAE generates synthetic samples that simulate transitions between clinical conditions while preserving anatomical plausibility. The method enhances the modeling of temporal and distributional dynamics underlying disease progression and provides interpretable analysis of class-relevant features. Applied to rs-fMRI scans of 220 subjects from the ADNI cohort, KS-VAE demonstrated robust class separation between cognitively normal and Alzheimer’s disease subjects, achieving a classification accuracy of 84.5% and an F1-score of 84.5%, and clinically consistent synthetic transitions. KS-VAE thus offers a statistically grounded and clinically interpretable framework for understanding Alzheimer’s disease progression. Full article

We developed a real-time alert and data management framework that integrates programmable logic controllers, RS-485 industrial communication, Structured Query Language Server, Message Queuing Telemetry Transport (MQTT), and the nodemation (n8n) automation platform, using a filling machine production line as a case study. The system collects and analyzes the operational status and production line data of the filling machine in real time, storing all information in a database for preservation. Through MQTT, the data is sent to n8n for automated processing. When equipment anomalies occur or data exceed predefined thresholds, the system automatically notifies maintenance personnel via communication software APIs. Additionally, users can query daily production capacity or related data using n8n’s AI functions. This architecture offers low cost, rapid deployment, cross-platform integration, and high flexibility. It not only improves anomaly handling efficiency but also preserves complete historical records, supporting trend analysis, report generation, and decision optimization, thereby assisting the filling production line in achieving long-term stable and intelligent management. Full article

Groundwater sustains human activity in arid crystalline terrains where surface water is scarce and hydrogeological data are limited. However, most groundwater potential mapping approaches depend on deterministic weighting methods without quantifying model variability. This study describes an uncertainty-aware Remote Sensing and Geographic Information Systems (RS–GIS) framework to delineate groundwater potential zones in the Wadi Arab Watershed, Northeastern Sudan. Nine thematic factors—geology and lithology, rainfall, slope, drainage density, lineament density, soil, land use/land cover, topographic wetness index, and height above nearest drainage—were integrated using the Analytical Hierarchy Process (AHP), with acceptable consistency (Consistency Ratio (CR) < 0.1). To address subjectivity in weights, a Dirichlet-based Monte Carlo simulation (500 iterations) was implemented to perturb AHP weights whilst preserving compositional constraints. The resulting Groundwater Potential Index (GWPI) classified 32.69% of the watershed as high to very high potential, primarily associated with alluvial deposits and fractured crystalline rocks. Model validation using Receiver Operating Characteristic (ROC) analysis yielded an Area Under the Curve (AUC) of 0.704, indicating acceptable predictive performance. Uncertainty assessment showed low spatial variability (mean standard deviation (SD) = 0.215) and stable exceedance probabilities, verifying the robustness of predicted high-potential zones. The proposed probabilistic AHP framework augments decision reliability and provides a transferable, cost-effective tool for groundwater planning in data-limited arid basement environments. Full article

Background: Athletic performance is a multifactorial construct influenced by physiological, biomechanical, and psychological determinants. In recent years, genetic factors have been increasingly recognized as contributors to inter-individual variability in performance. In particular, polymorphisms in genes involved in neurobiological pathways have been associated with cognitive processes relevant to sport performance. However, the distribution of cognition-related genetic variants in elite athletes has not been systematically synthesized. Methods: This meta-analysis aimed to examine the distribution of selected candidate gene polymorphisms previously associated with cognition-related traits in elite athletes compared to control populations. A systematic literature search identified 17 eligible case–control studies investigating allele distributions of COMT rs4680, BDNF rs6265, DRD2 rs1800497, OPRM1 rs1799971, and HTR1A rs6295. Pooled analyses were performed using a fixed-effect model, and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Results: Elite athletes demonstrated a significantly higher frequency of the G allele of COMT rs4680 (OR = 1.11; 95% CI: 1.02–1.21; p = 0.013) and the G allele of BDNF rs6265 (OR = 1.40; 95% CI: 1.10–1.77; p = 0.005) compared to controls. No significant differences were observed for HTR1A rs6295, DRD2 rs1800497, or OPRM1 rs1799971 polymorphisms (p > 0.05). Conclusions: This meta-analysis indicates that certain genetic variants previously associated with cognition-related traits, particularly COMT rs4680 and BDNF rs6265, are more frequently observed in elite athletes. These findings suggest a potential association between cognition-related genetic pathways and elite athletic status. However, as the present analysis is based on genetic distribution rather than direct cognitive assessments, the results should be interpreted within the context of association rather than causation. Full article

Chronic inflammation contributes to bladder cancer (BC) development and progression through dysregulated cytokine signaling and tumor–immune interactions. This case–control study investigated associations between IL6 rs1800795, TNF rs1800629, CCL2 rs1024611, and VEGFA rs699947 polymorphisms, circulating cytokine levels, clinicopathological characteristics, and autonomic nervous system balance assessed by heart rate variability (HRV) in 73 BC patients and 88 controls. Genotyping was performed using PCR–RFLP, serum cytokine levels were measured by ELISA, and associations were evaluated using logistic, linear regression, and survival analyses. No significant associations with BC risk were observed for IL6, TNF, or VEGFA variants. However, the CCL2 rs1024611 GG genotype was associated with increased BC risk (recessive model: OR = 5.82, p = 0.026). Stratified analyses showed a lower frequency of the IL6 rs1800795 C allele and TNF rs1800629 GA genotype in high-grade and muscle-invasive tumors, suggesting potential associations with reduced tumor aggressiveness. No polymorphism was associated with serum cytokine levels or disease-free survival. In BC patients, the TNF rs1800629 A allele was associated with higher parasympathetic-related HRV indices and lower sympathetic parameters, whereas no such associations were observed in controls. These findings indicate that genetic variation within inflammatory pathways may contribute to BC susceptibility and tumor phenotype and may also modulate neuroimmune interactions. Full article

High spatio-temporal resolution satellite imagery has become increasingly accessible thanks to advancements in the aerospace industry which, combined with a growing computational power, has enabled the spring of novel techniques regarding recognition in remote sensing (RS) images. However, there is still a lack of studies around 3D convolutions for spatio-temporal data applied to classification problems in RS. Hence, this study investigates the feasibility of 3D convolutional neural networks (3DCNNs) within a spatio-temporal perspective for scene classification and semantic segmentation in RS images, focusing on the identification of mining sites. We firstly developed a dataset covering several parts of Brazil based on MapBiomas products and Planet imagery, then we evaluated the effectiveness of 3DCNNs in capturing temporal information from a sequence of monthly captured images. Moreover, not only for scene classification but also for semantic segmentation, we compared 3D and 2D approaches. As for scene classification, a 3DCNN was better than the corresponding 2D model, while a 2D U-Net was better than a U-Net3D for semantic segmentation. The main explanation for this lies in the fact that a less costly annotation and training time strategy was adopted, but this may have harmed spatio-temporal approaches for semantic segmentation but not for scene classification. However, U-Net3D presented the highest Precision of all models, meaning that it is highly accurate when it predicts a positive. Moreover, 3DCNN (U-Net3D) presented significantly better performance with respect to semantic segmentation compared to other spatio-temporal approaches like ConvLSTM+U-Net and TempCNN. Sensitivity analysis revealed that the near-infrared (NIR) band played a decisive role in distinguishing mining areas, emphasizing its importance in highlighting subtle spectral variations associated with land-cover disturbances. Full article

As an important part of green manufacturing, remanufacturing has important practical significance for alleviating resource shortage and waste, developing circular economy and promoting sustainable development. In recent years, remanufacturing scheduling (RS), which can achieve high efficiency and green remanufacturing through the reasonable allocation of resources, has become a research hotspot in the field of remanufacturing. To offer a comprehensive evaluation of the research dynamics and development trends of RS, this paper systematically reviews the publications from 2010 to 2025 via Scopus, Web of Science, and the IEEE Xplore database. Firstly, the research background of RS, related remanufacturing policies and the generalized connotation of remanufacturing are introduced. Then, selected and valid publications are analyzed from time aspect, country aspect, and keyword aspect through Citespace software. In addition, based on remanufacturing level, modeling idea, optimization objectives, solution method, production scenarios and practical application, publications are further grouped and reviewed. In addition, according to the research gap existing in recent studies, some future development trends are accordingly pointed out, aiming to provide valuable insights for research related to RS. Finally, meaningful conclusions are drawn and the importance of RS is emphasized once again. Full article

Background: The optimal timing of cranioplasty (CP) after decompressive craniectomy (DC) remains debated. Early reconstruction may enhance neurological recovery through restoration of cerebral perfusion and cerebrospinal fluid dynamics, yet concerns persist regarding postoperative complications. Objective: To evaluate the impact of early versus delayed cranioplasty on neurological outcomes and postoperative complications in adults following decompressive craniectomy. Methods: A systematic review was conducted in accordance with PRISMA guidelines (PROSPERO ID: CRD420251123808). PubMed, OVID, and Web of Science were searched for studies published between January 2017 and December 2025. Eligible studies compared early and delayed CP in adults and reported neurological outcomes and/or complications. Results: Twenty-one retrospective cohort studies including 8462 patients were analyzed. Neurological improvement was observed in both groups across multiple validated scales (GOSE, GOS, GCS, mRS, BI, FIM, NIHSS, MMSE). Early CP was consistently associated with superior recovery, including higher one-year Barthel Index improvement (74.1% vs. 54.8%), greater FIM gains (7.31% vs. 4.66%), and higher composite recovery rates (95.6% vs. 80.0%). No study demonstrated superior recovery with delayed CP. Infection, hydrocephalus, and seizure rates were comparable between groups. However, hematoma (21% vs. 10.4%) and hygroma (7.49% vs. 4.73%) were more frequent after early CP, although hematoma rates were influenced by a large database study. Bone flap resorption was less frequent with early CP (1.44% vs. 6.26%). Conclusions: Early cranioplasty is associated with improved neurological recovery but carries an increased risk of select complications, particularly hematoma and hygroma, representing a clinically relevant trade-off. Delayed CP does not demonstrate overall superior safety due to higher bone flap resorption. Timing should be individualized, and prospective multicenter studies with standardized definitions are needed. Full article

To enhance the utilization rate and mechanical performance of recycled sand (RS) in extrusion-based 3D printing, this study investigates the influence of varying incorporation ratios of RS across two particle size fractions: 0.075–1.18 mm (RS01) and 1.18–2.36 mm (RS12). The RS utilization rate was determined via the material balance method, while microstructural mechanisms were analyzed using scanning electron microscopy and Vickers microhardness testing. The results indicate that: a combination of 75% RS01 and 25% RS12 achieves the maximum RS utilization rate of 84.3%. At an RS12/RS01 ratio of 1:3, the printed specimens exhibit the smallest tilt angles in bidirectional buildability tests, measuring 7.6° and 7.2°, with corresponding tan θ values of 0.066 and 0.063. Compared to mortar with 100% RS01, this optimized mixture yields average increases of 36.5% in compressive strength, 40.7% in flexural strength, and 6.8% in interlayer splitting strength. Analysis of variance indicates that different particle size combinations have a significant effect on the mechanical properties. Microhardness analysis reveals that the combination of 75% RS01 and 25% RS12 achieves a minimum interfacial transition zone width of 46 µm. Utilizing larger-particle-size RS in 3D printing effectively enhances its utilization rate while maintaining satisfactory printability and mechanical properties. Full article

The pathways governing the transformation of crop residues into humic acid (HA) remain incompletely understood because multiple biochemical routes may operate simultaneously during composting-like humification. In this study, a 30-day solid-state humification experiment was conducted by integrating physicochemical pretreatments, including steam explosion (SE) and ammonification coupled with steam explosion (SE-N), with a multi-fungal inoculation strategy involving Aspergillus niger, Candida spp., and Phanerochaete chrysosporium. Across three representative substrate–pretreatment systems and 81 experimental groups, the contents of lignocellulosic fractions, reducing sugars (RS), a UV-280-based soluble nitrogen-containing precursor index (operationally denoted as SNP), fulvic acid (FA), and HA were compared. The results showed that neither physicochemical pretreatment alone nor single-strain inoculation was sufficient to achieve substantial HA formation. SE mainly improved substrate accessibility and promoted carbon release, whereas ammonification provided essential nitrogen preloading for subsequent precursor coupling. In the saccharification-dominant treatment, RS reached 27.5%, but HA remained negligible. In the Candida-only treatment, the soluble nitrogen-containing precursor index increased markedly, yet HA formation was still minimal. By contrast, the highest HA yield (13.7%) was obtained under multi-fungal co-inoculation, particularly when nitrogen preloading by ammonification was combined with concurrent accumulation of carbon and aromatic precursors. The data suggest that lignin-targeting activity by P. chrysosporium was associated with the likely generation of phenolic and quinone-like intermediates that bridged the condensation of sugar- and nitrogen-derived compounds. Overall, the findings support a synergistic humification framework in which polysaccharide depolymerization, microbial nitrogen transformation, and lignin-derived aromatic precursor formation jointly contribute to HA accumulation, rather than a single linear pathway dominating the process. Full article

Digital transformation in the interior design industry has opened new opportunities for innovation; however, many cost-conscious homeowners still face difficulties in selecting and customizing design packages that achieve a balance between overall cost and sustainable quality. Existing interior design platforms lack seamless support and often require homeowners to invest considerable time and effort to tailor services to their needs while staying within budget. To address these challenges, this paper explores the use of machine learning to build a predictive modelling framework that supports personalized and value-driven interior design recommendations. The proposed approach uses a hybrid recommendation system that combines content-based and collaborative filtering. It also incorporates lightweight techniques such as TF–IDF (Term Frequency–Inverse Document Frequency) and logistic regression to more effectively capture user preferences, budget limits, and several interior-design service categories. Primary data was collected from small to medium-sized interior design companies. To demonstrate the proposed approach, a user-friendly web application tool is developed to integrate machine learning-enabled recommendation services. The resulting solution provides access to professional interior design services, enhancing customization and customer satisfaction while reducing the time and effort required from homeowners. To validate and compare the performance of the proposed approach, several machine learning models including Random Forest, XGBoost and KNN (K-Nearest Neighbors) were tested using standard metrics such as accuracy, precision, recall, and ROC-AUC (Receiver Operating Characteristic-Area Under the Curve). The proposed logistic regression hybrid model achieved the strongest overall results, with an accuracy of 83.62%. These findings demonstrate the significant contribution of this work to enhancing personalization and accessibility in the interior design sector via machine learning-enabled recommendation systems. The proposed approach bridges the gap between expert-level services and financial limits, making it a practical choice for cost-conscious homeowners. Full article

Dew constitutes a component of the near-surface water balance, but its large-scale fractal dynamical properties remain poorly documented across Africa. This study estimates dew amounts and investigates their fractal and multifractal behavior under African climatic conditions using gridded ERA5 datasets from 1993 to 2022. The Rescaled-Range (R/S) method, Multifractal Detrended Fluctuation Analysis (MFDFA), and the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) algorithm are used. Hurst exponent (Hu) and the multifractal spectrum width (ω) are evaluated at daily and monthly scales over the full period and two sub-periods (1993–2007 and 2008–2022). The results reveal pronounced spatial heterogeneity in dew distribution. Daily mean amounts range between 0 and 0.18 mm, corresponding to annual accumulations reaching up to ~85 mm·yr⁻¹ in humid coastal, equatorial, and sub-equatorial regions, while remaining below 0.5 mm·yr⁻¹ in hyper-arid deserts. The continental mean annual amount is ~35.5 mm·yr⁻¹. The Hurst exponent exhibits values between zero and one, indicating region-dependent persistent and anti-persistent behaviors. This suggests that prediction schemes based on preceding values may be suitable for dew time series prediction in African regions exhibiting persistent characteristics. The multifractal spectrum width (ω), reaching values of up to 10, highlights strong scaling heterogeneity, particularly at the monthly timescale. These findings indicate that African dew dynamics exhibit significant long-range dependence and multifractal variability, providing new insights into the intrinsic temporal structure of dew and into appropriate approaches for its forecasting. Full article

Coherent Raman scattering (CRS) techniques such as coherent anti-Stokes Raman scattering (CARS) provide chemically specific vibrational contrast with signal levels far exceeding spontaneous Raman scattering (SpRS). Extending these to broadband excitation enables multiplex detection across wide spectral regions, including the fingerprint region, CH-stretch bands and high-frequency vibrational modes. This review provides a structured overview of excitation architecture for broadband CRS, ranging from low-energy oscillator schemes to energy-scalable platforms. The discussion is organized along key design parameters, including spectral bandwidth, excitation intensity, and probe delay, which jointly determine the accessible operating regimes. Rather than representing competing methods, the reviewed architectures are presented as a complementary toolbox for application-driven spectroscopy in chemically reactive environments and complex biological systems. In addition, a representative OPCPA-based implementation is presented as a platform demonstration to illustrate accessible operating regimes, single-shot stability, and multiplex detection capability under realistic experimental conditions. Full article

Recent reports have shown that polymorphisms in the TRPS1 and TRIB1 genes are associated with plasma lipid levels and the risk of cardiovascular disease. This study evaluates the associations of TRPS1 and TRIB1 polymorphisms with subclinical atherosclerosis (SA) and plasma lipid levels in Mexican individuals. This study included 1406 Mexican mestizo individuals (417 individuals with SA and 989 healthy controls). Genotyping of TRPS1 and TRIB1 polymorphisms was performed using TaqMan assays in a real-time PCR system. To analyze whether these polymorphisms are associated with SA and plasma lipid levels, we used logistic regression (OR [95% CI]), adjusted for confounding factors. The AA genotype of the TRPS1 rs2737229 A/C polymorphism showed a significant association with the risk of developing SA under multiple genetic models [codominant: OR = 1.61 (95% CI: 1.10–2.36), p = 0.048; recessive: OR = 1.42 (1.02–1.99), p = 0.039; additive: OR = 1.26 (1.05–1.53), p = 0.015]. Similarly, the TT genotype of the TRIB1 rs2954029 T/A polymorphism was also significantly associated with the risk of developing SA [codominant: OR = 1.63 (1.10–2.43), p = 0.033; recessive: OR = 1.64 (1.13–2.37), p = 0.009]. In a sub-analysis of SA individuals, individuals with homozygous AA for the TRPS1 rs2737229 polymorphism had higher LDL cholesterol levels [135 mg/dL (110–148)] than those with homozygous CC [118 mg/dL (99–139)] (p < 0.003). The analysis of the TRIB1 rs2954029 polymorphism showed that carriers of the TT genotype had increased glucose levels [97 mg/dL (87–118)] compared to carriers of the AA genotype [91 mg/dL (84–99)] (p < 0.002). In summary, our findings showed that, in Mexican Mestizos, the AA genotype of the TRPS1 rs2737229 A/C SNP and the TT genotype of the TRIB1 rs2954029 A/T polymorphism are associated with a higher risk of developing SA and elevated levels of glucose and LDL cholesterol. Full article

Bitter taste receptors (TAS2Rs) are increasingly recognised as extraoral chemosensors that modulate diverse biological processes, including cancer cell behaviour and drug responsiveness. Many TAS2R ligands correspond to therapeutic compounds; however, their contribution to the response of brain tumours to chemotherapy remains unexplored. Here, we investigated whether the bitter taste signalling pathway is modulated by temozolomide (TMZ), the standard chemotherapeutic agent for glioblastoma, with an impact on treatment efficacy in glioblastoma cells. We show that TMZ elicits intracellular Ca²⁺ responses compatible with activation of G-protein-coupled receptor signalling and induces anti-proliferative and pro-apoptotic effects in multiple human glioblastoma cell lines. Pharmacological inhibition of bitter taste receptors, as well as genetic silencing of the taste transduction G protein GNAT3, significantly attenuated TMZ-induced cytotoxicity, suggesting that bitter taste signalling is involved in this process. In silico ligand prediction combined with receptor expression profiling identified TAS2R43 as a candidate modulator of these effects, and TAS2R43 knockdown markedly reduced TMZ-induced loss of cell viability and apoptosis. Moreover, TMZ enhanced intracellular accumulation of the ABC transporter substrate doxorubicin, suggesting modulation of multidrug efflux mechanisms. Collectively, our findings identify TAS2R43 as a potential biomarker that warrants further validation to improve responses to TMZ and other ABC transporter-limited anticancer drugs. Full article