Search Results (6,559)

Phosphorus-based compounds play a crucial role in agricultural productivity. However, excessive phosphorus discharge into water bodies contributes to eutrophication. This study proposes a circular approach for phosphorus recovery and reuse through the thermal valorization of Posidonia oceanica residues, an abundant marine biomass along Mediterranean coasts. After energy recovery from this waste (12.3 MJ kg⁻¹), the resulting ash was assessed as an effective adsorbent for aqueous phosphorus removal. Batch experiments were conducted to evaluate adsorption kinetics and equilibrium, considering the influence of key operational variables, such as temperature, pH, and adsorbent dosage. Under optimal conditions, the material achieved a maximum retention of approximately 55–60 mgP g⁻¹. The Freundlich model successfully describes the equilibrium isotherm data, indicating a heterogeneous adsorbent and an overall endothermic process. Phosphorus removal was favored at basic pH values (9.5–10.5), where the monohydrogen phosphate predominates. Leaching tests further revealed that saturated material releases phosphorus and other minerals in a manner clearly dependent on the final pH, with higher phosphorus release under more acidic conditions. These results suggest that Posidonia ash could serve as a low-cost adsorbent while also acting as a potential phosphorus source in soils. Full article

Autism spectrum disorder (ASD) is a heritable neurodevelopmental condition with a complex genetic architecture. Dissecting the interplay between inherited variants and high-impact de novo variants is critical for understanding its etiology. We conducted a family-based study involving 42 families with ASD (139 individuals). Using a targeted next-generation sequencing (NGS) panel of 236 genes, we identified and characterized rare inherited and de novo variants in affected probands, parents, and unaffected siblings. Our analysis revealed a complex genetic landscape marked by diverse inheritance patterns. De novo variants were predominantly observed in individuals with atypical autism, while biparental (homozygous) inheritance was more common in Asperger syndrome. Maternally inherited variants showed significant enrichment in intronic regions, pointing to a potential regulatory role. We also detected variants in several high-confidence ASD risk genes, including SHANK3, MYT1L, MCPH1, NIPBL, and TSC2, converging on pathways central to synaptic function and neurogenesis. Across the cohort, five variants of uncertain significance (VUS) were identified, comprising two inherited variants in ABCC8 and additional variants in CUL23, TSC2, and MCPH1. Our findings underscore the profound genetic heterogeneity of ASD and suggest that distinct genetic mechanisms and inheritance patterns may contribute to different clinical presentations within the spectrum. This highlights the power of family-based genomic analyses in elucidating the complex interplay of inherited and de novo variants that underlies ASD. Full article

To address the fragmentation and weak correlation of knowledge in the design method domain, this paper proposes a framework for constructing a knowledge graph driven by multi-source heterogeneous data. The process involves collecting multi-source heterogeneous data and subsequently utilizing text mining and natural language processing techniques to extract design themes and method elements. A “theme–stage–attribute” three-dimensional mapping model is established to achieve semantic coupling of knowledge. The BERT-BiLSTM-CRF (Bidirectional Encoder Representations from Transformers-Bidirectional Long Short-Term Memory-Conditional Random Field) model is employed for entity recognition and relation extraction, while the Sentence-BERT (Sentence Bidirectional Encoder Representations from Transformers) model is used to perform multi-source knowledge fusion. The Neo4j graph database facilitates knowledge storage, visualization, and querying, forming the basis for developing a prototype of a design method recommendation system. The framework’s effectiveness was validated through experiments on extraction performance and knowledge graph quality. The results demonstrate that the framework achieves an F1 score of 91.2% for knowledge extraction, and an 8.44% improvement over the baseline. The resulting graph’s node and relation coverage reached 94.1% and 91.2%, respectively. In complex semantic query tasks, the framework shows a significant advantage over traditional classification systems, achieving a maximum F1 score of 0.97. It can effectively integrate dispersed knowledge in the field of design methods and support method matching throughout the entire design process. This research is of significant value for advancing knowledge management and application in innovative product design. Full article

The rise of common institutional ownership has a profound impact on corporate environmental policies, and the business environment in which the enterprises operate can significantly affect the decisions of institutional investors. This study evaluates the effect of common institutional ownership on corporate environmental responsibility disclosure (CERD) practices in Chinese manufacturing firms from the performance feedback perspective. Utilizing a sample period spanning from 2008 to 2021, the study indicates several key findings. Firstly, the presence of common institutional ownership is demonstrated to enhance the level of CERD in these firms, especially soft information on environmental responsibility. Secondly, this positive effect is amplified when positive performance expectation gaps exist. Mechanism tests reveal that under the dual pressures of common institutional investor exit threats and a negative expected performance gap, firms tend to lower their level of CERD. Conversely, synergistic effects effectively promote this disclosure. Furthermore, analysis of the impact pathway demonstrates that under such conditions, common institutional ownership exerts pressure to reduce both monetary and non-monetary private benefits accruing to management, thereby leading to optimized CERD. In addition, heterogeneity analysis indicates a more significant effect of common institutional ownership on CERD enhancement in private enterprises compared to their state-owned counterparts, particularly when positive performance expectation gaps are present. Full article

An ascending aortic aneurysm is a localized dilation of the ascending aorta, which poses a high risk of aortic dissection or rupture, with surgery recommended at diameters > 5.5 cm. However, events also occur at smaller sizes, suggesting additional factors—such as stenosis—may significantly influence aneurysm severity. To investigate this, a computational fluid dynamics (CFD) analysis was conducted using a patient-specific ascending aortic model (aneurysm diameter: 5.28 cm) under three aortic stenosis severities: mild, moderate, and severe. Results showed that the severe stenosis condition led to the formation of prominent recirculation zones and increased peak velocities, 2.36 m·s⁻¹ compared to 1.53 m·s⁻¹ for moderate stenosis and 1.37 m·s⁻¹ for mild stenosis. A significantly increased pressure loss coefficient was observed for the severe case. Additionally, the wall shear stress (WSS) distribution exhibited higher values along the anterior region and lower values along the posterior region. Peak WSS values were recorded at 43.46 Pa in the severe stenosis model, compared to 21.98 Pa and 13.87 Pa for the moderate and mild cases, respectively. Velocity distribution and helicity analyses demonstrate that increasing stenosis severity amplifies jet-induced flow disturbances, contributing to larger recirculation zones and greater helicity heterogeneity in the ascending aorta. Meanwhile, WSS results indicate that greater stenosis severity is also associated with elevated WSS magnitude and heterogeneity in the ascending aorta, with severe cases exhibiting the highest value. These findings highlight the need to incorporate hemodynamic metrics, alongside traditional diameter-based criteria, into rupture risk assessment frameworks. Full article

Head and neck cancer (HNC) is highly heterogeneous and difficult to treat, underscoring the need for rapid, patient-specific models. Standard three-dimensional (3D) cultures often lose stromal partners that influence therapy response. We developed a patient-derived system maintaining tumor cells, cancer-associated fibroblasts (CAFs), and cells undergoing partial epithelial–mesenchymal transition (pEMT) for drug sensitivity testing. Biopsies from four HNC patients were enzymatically dissociated. CAFs were directly cultured, and their conditioned medium (CAF-CM) was collected. Cryopreserved primary tumor cell suspensions were later revived, screened in five different growth media under 2D conditions, and the most heterogeneous cultures were re-embedded in 3D hydrogels with varied gel mixtures, media, and seeding geometries. Tumoroid morphology was quantified using a perimeter-based complexity index. Viability after treatment with cisplatin or Notch modulators (RIN-1, recombination signal-binding protein for immunoglobulin κ J region (RBPJ) inhibitor; FLI-06, inhibitor) was assessed by live imaging and the water-soluble tetrazolium-8 (WST-8) assay. Endothelial Cell Growth Medium 2 (ECM-2) medium alone produced compact CAF-free spheroids, whereas ECM-2 supplemented with CAF-CM generated invasive aggregates that deposited endogenous matrix. Matrigel with this medium and single-point seeding gave the highest complexity scores. Two of the three patient tumoroids were cisplatin-sensitive, and all showed significant growth inhibition with the FLI-06 Notch inhibitor, while the RBPJ inhibitor RIN-1 induced minimal change. The optimized scaffold retains tumor–stroma crosstalk and provides patient-specific drug response data within days after operation, supporting personalized treatment selection in HNC. Full article

Surface irrigation systems are among the most common yet often inefficient methods due to poor design and management. A key factor in optimizing their design is the accurate prediction of the water advance and infiltration relationships’ coefficients. This study introduces a novel model based on the Beta cumulative distribution function for predicting water advance and estimating infiltration coefficients in surface irrigation systems. Traditional methods, such as the two-point approach, rely on limited data from only the midpoint and endpoint of the field, often resulting in insufficient accuracy and non-physical outcomes under heterogeneous soil conditions. The proposed model enhances predictive flexibility by incorporating the entire advance dataset and integrating the midpoint as a constraint during optimization, thereby improving the accuracy of advance curve estimation and subsequent infiltration coefficient determination. Evaluation using field data from three distinct sites (FS, HF, WP) across 10 irrigation events demonstrated the superiority of the proposed model over the conventional power advance method. The new model achieved average RMSE, MAPE, and R² values of 0.790, 0.109, and 0.997, respectively, for advance estimation. For infiltration prediction, it yielded an average error of 12.9% in total infiltrated volume—outperforming the two-point method—and also showed higher accuracy during the advance phase, with average RMSE, MAPE, and R² values of 0.427, 0.075, and 0.990, respectively. These results confirm that the Beta-based model offers a more robust, precise, and reliable tool for optimizing the design and management of surface irrigation systems. Full article

As a key target area in China’s new round of strategic mineral exploration initiatives, Tibet possesses favorable metallogenic conditions shaped by its unique geological evolution and tectonic setting. In this paper, the Saga region of Tibet is the research object, and Level-2A Sentinel-2 imagery is utilized. By applying mixed pixel decomposition, interfering endmembers were identified, and spectral unmixing and reconstruction were performed, effectively avoiding the drawback of traditional methods that tend to remove mineral alteration signals and masking interference. Combined with band ratio analysis and principal component analysis (PCA), various types of remote sensing alteration anomalies in the region were extracted. Furthermore, the fractal box-counting method was employed to quantify the fractal dimensions of the different alteration anomalies, thereby delineating their spatial distribution and fractal structural characteristics. Based on these results, two prospective mineralization zones were identified. The results indicate the following: (1) In areas of Tibet with low vegetation cover, applying spectral mixture analysis (SMA) effectively removes substantial background interference, thereby enabling the extraction of subtle remote sensing alteration anomalies. (2) The fractal dimensions of various remote sensing alteration anomalies were calculated using the fractal box-counting method over a spatial scale range of 0.765 to 6.123 km. These values quantitatively characterize the spatial fractal properties of the anomalies, and the differences in fractal dimensions among alteration types reflect the spatiotemporal heterogeneity of the mineralization system. (3) The high-potential mineralization zones identified in the composite contour map of fractal dimensions of alteration anomalies show strong spatial agreement with known mineralization sites. Additionally, two new prospective mineralization zones were delineated in their periphery, providing theoretical support and exploration targets for future prospecting in the study area. Full article

After the original support system in the auxiliary transportation roadway of the northern wing of the Zhaoxian Mine failed, the extent of damage and deformation varied significantly across different sections of the drift. A single support method could not meet the engineering requirements. Therefore, this paper conducted research on the classification of roadway damage and zoning repair. The overall damage characteristics of the roadway are described by three indicators: roadway deformation, development of rock mass fractures, and water seepage conditions. These are further refined into nine secondary indicators. In summary, a rock mass damage combination weighting evaluation model based on the FAHP–entropy weight TOPSIS method is proposed. According to this model, the degree of damage to the roadway is divided into five grades. After analyzing the damage conditions and support requirements at each grade, corresponding zoning repair plans are formulated by adjusting the parameters of bolts, cables, channel steel beams, and grouting materials. At the same time, the reliability of partition repair is verified using FLAC3D 6.0 numerical simulation software. Field monitoring results demonstrated that this approach not only met the support requirements for the roadway but also improved the utilization rate of support materials. This provides valuable guidance for the design of support systems for roadways with similar heterogeneous damage. Full article

Peritoneal carcinomatosis (PC) and malignant pleural effusions (MPE) are two common complications of cancers metastatic to the respective body cavities. A PC diagnosis indicates metastasis to the tissue lining the abdominal cavity and is most common in patients with gastrointestinal and gynecological cancers. It is often accompanied by ascites, an accumulation of serous fluid in the abdomen. MPE presents as the accumulation of fluid in the space between the lungs and chest wall. It is a common terminal event in patients diagnosed with breast cancer, lung cancer, lymphoma, and mesothelial cancers, and less commonly, in a wide variety of other epithelial cancers. Due to the aggressive nature of cavitary tumors, the outcome of current treatments for both PC and MPE remains bleak. Although PC and MPE are characteristically affected by different sets of primary tumors (lung/breast/mesothelioma for MPE and gynecologic/gastrointestinal for PC), their environments share common cytokines and cellular components. Owing to the unique cytokine and chemokine content, this environment promotes aggressive tumor behavior and paradoxically both recruits and suppresses central memory and effector memory T cells. The cellular and secretomic complexity of the cavitary tumor environment renders most currently available therapeutics ineffective but also invites approaches that leverage the robust T-cell infiltrate while addressing the causes of local suppression of anti-tumor immunity. Interactions between the heterogeneous components of the tumor environment are an area of active research. We highlight the roles of the immune cell infiltrate, stromal cells, and tumor cells, and the soluble products that they secrete into their environment. A more comprehensive understanding of the cavitary tumor environment can be expected to lead to better immunotherapeutic approaches to these devastating conditions. Full article

The production of fuels and materials from residual biomass through sustainable processes is one of the most challenging goals for science and technology. Such development is highly ambitious because of the complex composition of the feedstock (lipidic and lignocellulosic). To succeed, biomass conversion technologies must be able to compete economically with technologies based on fossil carbon. The use of specific and more available catalysts combined with improved reaction conditions can significantly reduce overall industrial costs and maximize efficiency. The synthesis and application of optimized catalytic systems are essential to modulate their activity, ensuring at the same time a high resistance to deactivation. For this reason, the study of multifunctional systems is gaining increasing interest alongside new industrial technologies. Here, we review significant recent advances in sustainable catalytic biomass conversion using emerging heterogeneous catalysts. Full article

In this study, the use of spent coffee waste as a green precursor of polyphenolic compounds, which are subsequently employed as reducing agents for the synthesis of zero-valent iron nanoparticles (nZVI) aimed at the efficient removal of dyes from aqueous systems, has been investigated. The nanoparticles, generated in situ in the presence of controlled amounts of hydrogen peroxide, were applied in the removal of organic dyes—including methylene blue, methyl orange, and orange G—through a heterogeneous Fenton-like catalytic process. The synthesized nZVI were thoroughly characterized by nitrogen adsorption at 77 K, scanning electron microscopy (SEM), transmission electron microscopy (TEM), Fourier-transform infrared spectroscopy (FT-IR), and powder X-ray diffraction (XRD). A statistical design of experiments and response surface methodology were employed to evaluate the effect of polyphenol, Fe(III), and H₂O₂ concentrations on dye removal efficiency. Results showed that under optimized conditions, a 100% removal efficiency could be achieved. This work highlights the potential of nZVI synthesized from agro-industrial waste through sustainable routes as an effective solution for water remediation, contributing to circular economy strategies and environmental protection. Full article

Neurodevelopmental disorders (NDDs), including autism spectrum disorder, intellectual disability, and attention-deficit/hyperactivity disorder, are genetically and phenotypically heterogeneous conditions affecting millions worldwide. High-throughput omics technologies—transcriptomics, proteomics, metabolomics, and epigenomics—offer a unique opportunity to link genetic variation to molecular and cellular mechanisms underlying these disorders. However, the high dimensionality, sparsity, batch effects, and complex covariance structures of omics data present significant statistical challenges, requiring robust normalization, batch correction, imputation, dimensionality reduction, and multivariate modeling approaches. This review provides a comprehensive overview of statistical frameworks for analyzing high-dimensional omics datasets in NDDs, including univariate and multivariate models, penalized regression, sparse canonical correlation analysis, partial least squares, and integrative multi-omics methods such as DIABLO, similarity network fusion, and MOFA. We illustrate how these approaches have revealed convergent molecular signatures—synaptic, mitochondrial, and immune dysregulation—across transcriptomic, proteomic, and metabolomic layers in human cohorts and experimental models. Finally, we discuss emerging strategies, including single-cell and spatially resolved omics, machine learning-driven integration, and longitudinal multi-modal analyses, highlighting their potential to translate complex molecular patterns into mechanistic insights, biomarkers, and therapeutic targets. Integrative multi-omics analyses, grounded in rigorous statistical methodology, are poised to advance mechanistic understanding and precision medicine in NDDs. Full article

Air pollution from fine particulate matter (PM2.5) is a recurring crisis in Northern Thailand, largely driven by seasonal biomass burning. This study investigates how socioeconomic and individual characteristics shape labor allocation during high-exposure periods. Using survey data from 400 individuals across eight provinces in April–May 2024, we applied a logit model to estimate the probability of reducing work hours. Results show heterogeneous and non-linear patterns of avoidance. The probability of work reduction rose across higher income strata but peaked in the third stratum before declining in the fourth, reflecting the trade-off between avoidance and the opportunity cost of foregone earnings. Education exhibited a strong awareness effect, with each additional year increasing avoidance behavior. Outdoor workers and individuals with respiratory conditions were most likely to reduce work, indicating rational prioritization under greater exposure risks. Together, these findings demonstrate environmental inequality: lower-income and less-educated groups remain disproportionately exposed due to limited coping capacity. The regional context of Northern Thailand further amplifies these vulnerabilities. Policy interventions should prioritize protective measures for vulnerable groups while promoting long-term alternatives to biomass burning. By highlighting nuanced behavioral responses, this study extends evidence on environmental inequality in developing-country contexts. Full article

The temperature-based indicators heating and cooling degree days, are frequently utilized to quantitatively link indoor energy demand and outdoor thermal conditions, especially in the context of climate change. We present a comprehensive study of the heating and cooling degree-days and the degree-days categories for the near past (1976–2005), and the AR5 RCP4.5 and RCP8.5 scenario-driven future (2066–2095) over Southeast Europe based on an elaborated methodology and performed using a 19 combinations of driving global and regional climate models from EURO-CORDEX with horizontal resolution of 0.11°. Alongside the explicit focus of the degree-days categories and the finer grid resolution, the study benefits substantially from the consideration of the monthly, rather than annual, time scale, which allows the assessment of the intra-annual variations of all analyzed parameters. We provide evidences that the EURO-CORDEX ensemble is capable of simulating the spatiotemporal patterns of the degree-days and degree-day categories for the near past period. Generally, we demonstrate also a steady growth in cooling and a decrease in heating degree-days, where the change of the former is larger in relative terms. Additionally, we show an overall shift toward warmer degree-day categories as well as prolongation of the cooling season and shortening of the heating season. As a whole, the magnitude of the projected long-term changes is significantly stronger for the ’pessimistic’ scenario RCP8.5 than the ’realistic’ scenario RCP4.5. These outcomes are consistent with the well-documented general temperature trend in the gradually warming climate of Southeast Europe. The patterns of the projected long-term changes, however, exhibit essential heterogeneity, both in time and space, as well as among the analyzed parameters. This finding is manifested, in particular, in the coexistence of opposite tendencies for some degree-day categories over neighboring parts of the domain and non-negligible month-to-month variations. Most importantly, the present study unequivocally affirms the significance of the anticipated long-term changes of the considered parameters over Southeast Europe in the RCP scenario-driven future with all subsequent and far-reaching effects on the heating, cooling, and ventilation industry. Full article