Search Results (101,084)

This study investigates the structural transformation from the γ-phase into the α-phase in bio-based nylon 5,6 fibers during in situ uniaxial stretching, using X-ray diffraction (XRD) and density functional theory (DFT) calculations. Initially, nylon 5,6 films exhibited a well-defined γ-phase crystalline structure, and the as-spun fibers also retained a γ-phase-dominant structure with partial coexistence of α-phase components. Due to the lattice similarity between the γ- and α-phases, phase separation was challenging in the direction perpendicular to the fiber axis (ab-plane). However, the analysis of the (004) diffraction peaks along the fiber axis (c-axis) enabled the quantitative evaluation of each crystalline component. As the stretching progressed, the α(004) peak intensity gradually increased, indicating a continuous γ-to-α structural transition. Furthermore, DFT calculations revealed that the α-phase has lower energy than the γ-phase, supporting the thermodynamic favorability of the phase transition during elongation. These results provide a comprehensive understanding of the crystalline structure and transformation mechanism in environmentally friendly nylon fibers from both experimental and theoretical perspectives, and offer foundational insights for developing nylon materials with desirable properties through the precise control of crystal phase structures. Full article

Background: Trace elements and heavy metals can provide valuable forensic information for individual identification, lifestyle reconstruction, and association with the scene or time of death and may also assist in linking objects to criminal activities. However, the lack of standardized guidelines and post-mortem reference values represents a significant limitation in forensic investigations. Methods: This review was conducted in accordance with the PRISMA statement. We performed a comprehensive literature study over the last ten years focusing on the analysis of trace elements and heavy metals in post-mortem tissues. Results: The search results from the databases yielded 247 records. The screening, according to PRISMA criteria, allowed us to select and include 19 articles. The results showed the need for standardized guidelines and reference values. Although post-mortem trace element analysis shows high potential for forensic applications, substantial methodological heterogeneity persists. Some studies have proposed preliminary reference values for cadmium (Cd) in kidneys and mercury (Hg) in hair but validated post-mortem reference ranges remain largely unavailable. Conclusions: The current literature demonstrates the forensic potential of trace element and heavy metals analysis including Cd, Hg, lead (Pb), Manganese (Mn), Aluminum (Al), Copper (Cu), Zinc (Zn), Iron (Fe), Thallium (Tl), Polonium (²¹⁰Po) but also underlines the urgent need for standardized protocols and validated post-mortem reference values to improve interpretability and reliability in forensic contexts. Full article

This review provides a comprehensive overview of the recent green innovations in high-performance liquid chromatography (HPLC) for sustainable food analysis. It outlines the principles of green analytical chemistry and examines advances such as eco-friendly solvent systems, miniaturized and energy-efficient instrumentation, and greener sample preparation techniques. Key applications include the analysis of bioactive compounds, detection of contaminants and residues, and support for clean-label and sustainability claims. Furthermore, the review discusses relevant regulatory and certification frameworks, including ISO 14001, ISO 22000, and global food safety initiatives aligned with environmental, social, and governance standards. Persistent challenges, such as cost, limitations in analytical performance, and limited instrument availability, are highlighted, along with the need for reliable metrics to assess the environmental impact and effectiveness of green analytical practices. The review concludes by emphasizing the need for interdisciplinary collaboration among scientists, industry stakeholders, and regulatory bodies to support the wider adoption of sustainable HPLC practices in food laboratories. Full article

This article discusses how various factors can affect the accuracy of U, Th, and K elemental content measurements in natural gamma spectroscopy logs. These factors include errors in the measured energy spectrum, degradation of energy resolution, and spectrum drift. Currently, there is limited research on quantifying the individual impact of each factor on measurement accuracy. To address this gap, the study proposes a methodology that combines energy spectrum data sampling and single-factor quantitative analysis. This approach allows for a more precise understanding of how each factor influences the accuracy of the measurements. The results of the study have important implications for improving the accuracy of U, Th, and K content measurements in applications such as the oil and gas industry. Full article

This study presents a comprehensive assessment of long-term nutrient dynamics in the northern South China Sea (NSCS), a region that hosts the world’s largest marine ranching cluster and serves as a cornerstone of China’s “Blue Granary” initiative. By integrating multi-sensor satellite remote sensing data (Landsat and Sentinel-2, 2002–2024) with in situ observations, we developed robust retrieval algorithms for total nitrogen (TN) and total phosphorus (TP), achieving high accuracy (TN: R² = 0.82, RMSE = 0.09 mg/L; TP: R² = 0.94, RMSE = 0.0071 mg/L; n = 63). Results showed that TP concentrations increased significantly faster than TN, leading to a decline in the TN:TP ratio (NP) from 19.2 to 13.2 since 2013. This shift indicates a transition from phosphorus (P) limitation to nitrogen (N) limitation, driven by warming sea surface temperatures (SST) (about 1.16 °C increase) and increased anthropogenic phosphorus inputs (about 27.84% increase). The satellite-based framework offers a scalable, cost-effective solution for monitoring aquaculture water quality. When integrated with artificial intelligence (AI) technologies, these near-real-time nutrient anomaly data can support early warning of harmful algal blooms (HABs), offering key insights for ecosystem-based management and climate adaptation. Overall, our findings highlight the utility of remote sensing in advancing sustainable marine resource governance amid environmental change. Full article

Background/Objectives: Dopamine (DA), a chemical commonly associated with neuroscience and human physiology, has been the subject of growing interest in the field of agriculture due to its potential applications. Methods: This comprehensive review examines the multifaceted role of dopamine in agricultural practices, elucidating its chemical characteristics, biological activities, and diverse applications. The review examines the chemical properties and physiological functions of dopamine in plants, highlighting the unique characteristics that make it suitable for agricultural applications. A significant portion of the review is dedicated to analyzing the biological activities of dopamine, particularly its antioxidant properties, and exploring the underlying mechanisms. The review also delves into the potential of dopamine to enhance crop growth, yield, and quality and investigates the influence of dopamine on plant physiology and metabolism. Results: Furthermore, the review provides a forward-looking perspective on the prospects of dopamine in agriculture, identifying emerging trends and areas of innovation that hold promise for sustainable and resilient farming systems. Conclusions: In summary, this review consolidates the current knowledge surrounding dopamine’s potential in agriculture, underscoring its versatility as a natural tool for growth enhancement and environmental sustainability, and offering valuable insights for researchers, practitioners, and policymakers seeking innovative approaches to address the challenges of modern agriculture. Full article

Background: This study was aimed to comprehensively investigate the clinical and molecular characteristics, treatments, and outcomes of young patients with lung cancer in the new era of cancer treatment. Methods: Clinical data from patients aged 18 to 45 with lung cancer, treated at our hospital from January 2014 through January 2024, were systematically collected and analyzed. Results: This study enrolled a total of 343 patients, with a predominance of females, never-smokers, and those diagnosed at an advanced stage. Adenocarcinoma was the most common histology (72.0%), and rare tumors could also be seen in young patients, such as pulmonary sarcomatoid carcinoma and pulmonary mucoepidermoid carcinoma. The mutation rate of the epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) in NSCLC patients were 35.9% (111/309) and 14.2% (44/309), respectively. PD-L1 expression was assessed in 55 patients, with 14 showing high expression (≥50%) and 24 showing negative expression (<1%). The median overall survival (mOS) for the entire cohort was 80.2 months, with a 5-year survival rate of 55.7%. For patients with stage I, II, and III disease, the mOS had not yet been reached, whereas the mOS for stage IV patients was 39.7 months. Targeted therapy, particularly second-generation ALK tyrosine kinase inhibitors (TKIs), significantly improved the prognosis of patients with driver gene mutations. Chemotherapy combined with immunotherapy was beneficial for patients with progressive disease or driver gene negativity in NSCLC and was associated with improved OS in small cell lung cancer (SCLC). Female, family history of lung cancer, positive driver genes, and first-line use of second-generation ALK-TKIs are independent prognostic factors in young patients with advanced NSCLC. Conclusions: Our findings highlight the importance of early diagnosis, targeted therapy, and immunotherapy in improving outcomes for young patients with lung cancer. Full article

The growing demand for animal products exerts pressure on the livestock sector to increase production while minimizing its impact on the environment. The paper explored the impact of ruminant production systems on the environment and opportunities for enhancing production and environmental conservation. A comprehensive review of literature on livestock production, animal nutrition, and environmental conservation was conducted. The review shows that the challenges of ruminant production on the ecosystem are centered around greenhouse gas emissions, land degradation, and water and feed resources. However, manipulation of animal feeding strategies, rotational grazing, precision farming, and integration of crop-livestock systems have the potential to enhance feed efficiency, reduce waste, improve animal health, and nutrition and reduce nitrogen and methane gas emissions. This will also improve manure management, soil health, and biodiversity, which are essential in climate resilience building and resource management by farmers. Development of effective strategies for enhancing animal nutrition and ruminant production while conserving the ecosystem is important. Full article

This article reconstructs Fakhr al-Dīn al-Rāzī’s (d. 1210) systematic treatment of the jinn in his Great Exegesis (al-Tafsīr al-Kabīr) and his summa The Sublime Objectives in Metaphysics (al-Maṭālib al-ʿĀliya min al-ʿIlm al-Ilāhī). In these works, al-Rāzī treats the jinn not as a marginal curiosity but as a test case for probing core metaphysical categories such as substance, embodiment, and divine action. His analysis unfolds through a sequence of guiding questions. Do the jinn exist at all? If not, we arrive at (1) the Denialist View. If they do exist, they must be either immaterial or material. The first yields (2) the Immaterialist View. The second raises the further question of whether bodies differ in essence or share a single essence. If they differ, we arrive at (3) the Non-Essentialist Corporealist View. Notably, these first three views are associated, in different ways, with various figures in the falsafa tradition. If they share a single essence, this produces the Essentialist Corporealist position, which then divides according to whether bodily structure is metaphysically necessary for life and agency. If not necessary, this produces (4) the Essentialist Corporealist—Structural Independence View, associated with the Ashʿarīs. If necessary, it leads to (5) the Essentialist Corporealist—Structural Dependence View, associated with the Muʿtazilīs. Al-Rāzī rejects (1) and (5), but he leaves (2), (3), and (4) as live possibilities. While he shows greater sympathy for (4), his broader purpose is not to settle the matter but to map the full range of theological and philosophical options. Al-Rāzī’s comprehensive exposition reflects the wider dialectic between falsafa, Ashʿarī theology, and Muʿtazilī theology, showcasing a sophisticated willingness to engage and entertain multiple metaphysical possibilities side by side. The result is an exercise in systematic metaphysics, where the question of the jinn, as liminal beings, becomes a means for interrogating broader ontological commitments in Islamic theology and philosophy. Full article

To address urban flooding challenges exacerbated by climate change and urbanization, this study develops an integrated assessment framework combining the analytic hierarchy process (AHP), entropy weight method, and cloud model to quantify urban flood resilience. Resilience is deconstructed into resistance, adaptability, and recovery and evaluated through 24 indicators spanning water resources, socio-economic systems, and ecological systems. Subjective (AHP) and objective (entropy) weights are optimized via minimum information entropy, with the cloud model enabling qualitative–quantitative resilience mapping. Analyzing 2014–2024 data from 27 Chinese sponge city pilots, the results show resilience improved from “poor to average” to “good to average”, with a 2.89% annual growth rate. Megacities like Beijing and Shanghai excel in resistance and recovery due to infrastructure and economic strengths, while cities like Sanya enhance resilience via ecological restoration. Key drivers include water allocation (27.38%), economic system (18.41%), and social system (17.94%), with critical indicators being population density, secondary industry GDP ratio, and sewage treatment rate. Recommendations emphasize upgrading rainwater storage, intelligent monitoring networks, and resilience-oriented planning. The model offers a scientific foundation for urban disaster risk management, supporting sustainable development. This approach enables systematic improvements in adaptive capacity and recovery potential, providing actionable insights for global flood-resilient urban planning. Full article

Five-axis machining centers are essential for manufacturing complex, high-precision parts. However, their accuracy is significantly affected by thermally induced geometric errors, also known as thermo-elastic errors. This paper presents a comprehensive approach to thermal characterization and its potential application in predictive modeling on a five-axis machine tool demonstrator, showcasing the capabilities of a novel dynamic R-test measurement method. Based on a previously developed and validated dynamic R-test measurement method that enables the rapid, volumetric acquisition of machine deviations during continuous movement, detailed experimental investigations were conducted under various single- and combined-axis loading scenarios. The extensive dataset and detailed error information provided by the dynamic R-test method enabled thorough analysis and correlation of thermo-elastic errors, including translational and rotational errors, with temperature and control-internal axis data. A well-established phenomenological model based on PT1 transfer functions is used, detailing its input variables and parameter determination methods. The model’s predictive capability was rigorously validated against independent datasets, demonstrating significant reductions in primary errors (up to 70% in maximum residual and 80% in RMSE). This study identifies the most influential error types and their correlation with thermal loads. This confirms the feasibility of robustly predicting thermo-elastic behavior and enhancing the volumetric accuracy of five-axis machine tools, particularly by leveraging the detailed error insights enabled by the dynamic R-test. Full article

Glioblastoma multiforme (GBM) remains the most aggressive primary brain tumor with median survival of 14.6 months, necessitating novel therapeutic approaches. Here, we report the biogenic synthesis of zinc oxide nanoparticles (ZnO NPs) using Bacillus licheniformis strain TT14s isolated from mining environments and demonstrate their selective anti-glioma efficacy. ZnO NPs exhibited hexagonal wurtzite structure (crystallite size: 15.48 nm) with spherical morphology (19.37 ± 5.28 nm diameter) as confirmed by XRD, HRTEM, and comprehensive physicochemical characterization. Colloidal stability analysis revealed an isoelectric point at pH 7.46, ensuring optimal dispersion in biological media. Cytotoxicity evaluation revealed remarkable selectivity: at 100 μg/mL, ZnO NPs reduced NG-108 glioblastoma cell viability to 36.07 ± 1.89% within 1 h while maintaining 78.9 ± 0.94% viability in primary retinal cells. The selective cytotoxicity was attributed to the interplay of convergent mechanisms acting under dark conditions, including defect-mediated ROS generation supported by photoluminescence analysis revealing a characteristic oxygen vacancy emission at 550 nm, pH-dependent dissolution enhanced in the acidic tumor microenvironment, and preferential cellular uptake by rapidly proliferating cancer cells with compromised antioxidant defenses. Time-course analysis demonstrated concentration-dependent effects with therapeutic windows favoring normal cell preservation. The intrinsic cytotoxic activity under dark laboratory conditions eliminates the need for external activation, providing practical advantages for therapeutic applications. These findings establish ZnO NPs as promising candidates for targeted glioblastoma therapy, warranting further in vivo validation and mechanistic elucidation for clinical translation. Full article

Water is an essential resource for life and is also a necessary resource for the sustainable economic competitiveness of any country. In recent decades, climate change, economic development, and rising population have led to water scarcity in certain regions. In response, new technologies and water management techniques have been researched and developed, which are now incorporated into the concept of smart cities. These innovations, called smart water systems, aim to enhance water management by monitoring consumption, quality, reservoir levels, leaks, and asset conditions, and optimizing water processes to maximize water system resilience. The first systems were based on smart meters and have advanced to so-called digital twins for water systems. This review aims to present a comprehensive review of smart water system developments, the geographic distribution of the works, their technological readiness level, and their implementation challenges. Full article

Linpan ecosystems, distinct to western Sichuan, China, are integral to regional biodiversity and carbon cycling. However, comprehensive biomass estimation for these systems has not been thoroughly investigated. This study seeks to fill this gap by enhancing the accuracy and precision of biomass estimation in these ecologically vital landscapes through the application of multi-source remote sensing techniques, specifically by integrating the strengths of optical and radar remote sensing data. The focus of this research is on the forest biomass of Linpan, encompassing the tree layer, which includes the trunk, branches, leaves, and underground roots. Specifically, the research focused on the Linpan ecosystems in the Wenjiang District of western Sichuan, utilizing an integration of Sentinel-1 SAR, Sentinel-2 multispectral, and GF-2 high-resolution data for multi-source remote sensing-based biomass estimation. Through the preprocessing of these data, Pearson correlation analysis was conducted to identify variables significantly correlated with the forest biomass as determined by field surveys. Ultimately, 19 key modeling factors were selected, including band information, vegetation indices, texture features, and phenological characteristics. Subsequently, three algorithms—multiple stepwise regression (MSR), support vector machine (SVM), and random forest (RF)—were employed to model biomass across mixed-type, deciduous broadleaved, evergreen broadleaved, and bamboo Linpan. The key findings include the following: (1) Sentinel-2 spectral data and Sentinel-1 VH backscatter coefficients during the summer, combined with vegetation indices and texture features, were critical predictors, while phenological indices exhibited unique correlations with biomass. (2) Biomass displayed a marked north–south gradient, characterized by higher values in the south and lower values in the north, with a mean value of 161.97 t ha⁻¹, driven by dominant tree species distribution and management intensity. (3) The RF model demonstrated optimal performance in mixed-type Linpan (R² = 0.768), whereas the SVM was more suitable for bamboo Linpan (R² = 0.892). The research suggests that integrating multi-source remote sensing data significantly enhances Linpan biomass estimation accuracy, offering a robust framework to improve estimation precision. Full article

The accumulation of plastic waste has intensified the pursuit of biodegradable alternatives, yet standard methods such as CO₂ evolution, oxygen demand, and mass loss fail to fully capture microbial physiological responses during degradation. This study introduces a biochemical assay-based approach to quantify proteins, lipids, and carbohydrates in soil as indicators of microbial activity during polymer biodegradation. For microcrystalline cellulose (MCC), proteins, lipids, and carbohydrates increased by 2.09-, 6.47-, and 11.22-fold, respectively (all p-values < 0.001), closely aligning with CO₂ evolution trends. Non-biodegradable poly(vinyl chloride) (PVC) exhibited no significant changes. Synthesized poly(butylene glutarate) (PBG) also showed significant biomolecule accumulation (up to 2.70-fold) alongside CO₂ production. Biomolecule quantification complements CO₂-based methods by revealing microbial proliferation and metabolic activity that persist beyond the mineralization plateau, offering a more comprehensive assessment of biodegradability. Full article