Search Results (23,612)

Arsenic (As) contamination in paddy soils poses a serious risk to rice safety and human health. To mitigate this issue, we developed a low-temperature, partially pyrolyzed Fe/Mn/Mg-modified biochar (FMM-BC) and evaluated its performance and mechanisms for remediating As-contaminated soil through a pakchoi–rice rotation pot experiment, aiming to reduce As accumulation in rice grains and pakchoi. The results indicated that FMM-BC application altered soil physicochemical properties and As speciation, reducing both water-soluble and bioavailable As and promoting its transformation from exchangeable to more stable organic-bound and residual fractions. Compared with the control, FMM-BC application reduced arsenic content in rice stems, leaves, and brown rice to 1.94 mg∙kg⁻¹, 5.24 mg∙kg⁻¹, and 1.21 mg∙kg⁻¹, respectively. In contrast, unmodified biochar (BC) increased As bioavailability and plant uptake, underscoring the importance of Fe/Mn/Mg modification. FMM-BC also enhanced the translocation of Fe, Mn, and Mg within rice plants, thereby modifying internal As transport dynamics and suppressing its accumulation in aboveground tissues. Under FMM-BC treatment, arsenic content in pakchoi stems and leaves decreased to 1.19 mg∙kg⁻¹ (vs. 1.96 mg∙kg⁻¹ in the control), and brown rice declined to 0.27 mg∙kg⁻¹ (vs. 1.49 mg∙kg⁻¹ in the control)—well below the national food safety threshold (0.35 mg∙kg⁻¹). These findings demonstrate that FMM-BC effectively stabilizes As in contaminated soils and reduces its transfer to edible plant parts, with Fe/Mn/Mg playing a key role in enhancing As immobilization and limiting its mobility within the soil–plant system. Full article

In this work, highly water-soluble silk fibroin (SF) is first prepared by recrystallizing degummed silkworm cocoon fibers in concentrated CaCl₂ solution (replacing the conventional Ajisawa’s reagent), and then used as both stabilizing and reducing agents to synthesize copper nanoclusters (Cu@SF NCs) at pH = 11. Due to the existence of unreacted Cu²⁺ ions, the resulting SF-templated Cu NCs form slight aggregates, yielding a purple-colored solution with blue fluorescence. Interestingly, upon adding the pesticide 2,4-dichlorophenoxyacetic acid (2,4-D), the Cu NCs aggregates disassemble and the fluorescence is significantly enhanced, creating a “fluorescence-on” sensor for 2,4-D with a detection limit of 0.65 μM. In contrast, the pollutant p-nitrophenol (p-NP) quenches the fluorescence of Cu NCs via a fluorescence resonance energy transfer mechanism (with a detection limit as low as 1.35 nM), which is attributed to the large overlap between absorption spectrum of p-NP and excitation spectrum of Cu NCs. Other tested analytes (i.e., pyrifenox, carbofuran and melamine) produce negligible fluorescence changes. The distinct sensing mechanisms are elucidated with experimental evidence and density functional theory (DFT) calculations. The evolutions of fluorescence as a function of incubation time and analyte concentration are systematically investigated, demonstrating a versatile platform for sensitive and selective detection of target analytes. These findings provide an effective strategy for optimizing the optical properties of metal nanoclusters and improving their performance in environmental applications. Full article

This study examines reservoir-triggered seismicity (RTS) in Poland and Vietnam. The current state of individual RTS seismic networks necessitates detecting earthquakes from only a few stations. The number of P waves is often inadequate for phase association and event location, which underscores the importance of identifying S waves. Given that individual RTS cases may consist of only hundreds of events, it is crucial for algorithms to be trained on small datasets or to detect effectively using external, global training data. To evaluate this, we compared the efficiency of a deep learning global detection model, transfer learning to the RTS database, a specialized neural network designed for RTS, and manual detection of seismic signals. Transfer learning efficiency was database dependent. Additional interpretation and parametrization of detection results are assumed. Therefore, the emphasis is on phase detection, rather than phase picking accuracy, and detection sensitivity is more important than its specificity. Phase association plays a vital role in detecting seismic signals, facilitating the elimination of most false picks. As a result, the comparisons of detections were based on parameters related to the location of seismic events. The findings indicate that neither the automatic signal detection methods nor the manual methods alone are sufficient. However, their combination significantly enhances detectability. The final catalogs cover up to 30% more events compared to the previous manual. It fulfills the main aim of applying a neural network detector, which is to increase the number of seismic events in the catalog. It may also be further utilized in the research of the triggering process, such as identifying fluid paths and determining fault geometry. Full article

Accurate segmentation of nuclei and cytoplasm in cervical cytology images plays a pivotal role in characterizing cellular morphology. The primary challenge is to precisely delineate boundaries within densely clustered cells, which is complicated by low-contrast edges and irregular morphologies. This paper introduces a novel framework combining MaskDino architecture with Hausdorff distance loss, enhanced by a two-phase training strategy. The method begins by employing MaskDino for precise nucleus segmentation. Building on this foundation, the framework then enhances cytoplasmic boundary detection in cellular clusters by incorporating a Hausdorff distance loss, with weight transfer initialization ensuring feature consistency across tasks.. The symmetry between the nucleus and cytoplasm servers as a key morphological indicator for cell assessment, and our method provides a reliable basis for such analysis. Extensive experiments demonstrate that our method achieves state-of-the-art cytoplasm segmentation results on the ISBI2014 dataset, with absolute improvements of 2.9% in DSC, 1.6% in TPRp and 2.0% in FNRo. The performance of nucleus segmentation is better than the average level. These results validate the proposed framework’s effectiveness for improving cervical cancer screening through robust cellular segmentation. Full article

This study examines the systemic integration of entrepreneurship education and the culture of self employment within higher education as a component of sustainable institutional reform. Using a comparative analytical approach, it analyzes international practices across five higher education systems. Finland, the United States, Canada, the United Kingdom, and South Korea were selected to represent diverse yet mature models of entrepreneurship education integration. The findings reveal significant variation in the depth and coherence of integration across national contexts. Rather than identifying a single transferable model, the study shows that effective integration depends on the interaction of key institutional dimensions, including policy alignment, curricular embedding, faculty capacity, infrastructure, external partnerships, and impact evaluation. Finland demonstrates the most coherent configuration, while other systems exhibit partial or fragmented integration shaped by contextual factors. The study concludes that entrepreneurship education is most sustainable when embedded as a system-level institutional strategy rather than implemented through isolated initiatives. It offers an analytical framework, supported by an adapted ADKAR change model, to guide context-sensitive reform. For Arab higher education systems, the primary implication is diagnostic, emphasizing contextual adaptation over direct replication. Full article

Volatile organic compounds (VOCs) play a central role in plant communication and ecology, acting as a chemical language that mediates interactions with other organisms and responses to environmental stimuli. Analyzing changes in the plant volatilome enables the effective differentiation between biotic and abiotic stresses. Consequently, monitoring VOC emissions offers valuable insights into plant signaling pathways and health status. These insights position this approach as a promising strategy for improving crop protection. Direct infusion (DI) online analytical techniques, such as proton transfer reaction mass spectrometry (PTR-MS) and adduct ionization mechanism mass spectrometry (AIM-MS), have been developed to detect and characterize VOCs in real time. Here, we evaluated the suitability of PTR-MS and AIM-MS for monitoring VOC emissions in pea plants (Pisum sativum L.). Comparative analysis revealed that AIM-MS, a recently developed technology, detected a higher number of distinct signals than PTR-MS. Annotation of detected and significant AIM-MS signals indicated a predominance toward those that were putative lipids-derived and amino acids-derived, whereas PTR-MS signals were primarily associated with putative phenolic compounds. These findings suggest that the newly developed AIM reactor offers a broader detection range and may enhance our ability to monitor plant VOC emissions. Consequently, AIM-MS emerges as a promising tool for the real-time assessment of pea plant health and stress responses. Further efforts are needed to improve the portability of DI-MS techniques and to integrate them with GC-MS techniques. Overall, these efforts will allow this technology to be exploited for plant protection in compromised environments. Full article

To investigate the complex interaction in multi-structure systems, this study establishes a refined 3D numerical model based on a transportation hub project in Tianjin to analyze the asymmetric coupling deformation mechanism of a deep excavation adjacent to a shared-wall metro station and elevated bridge piles. This study highlights the transition from soil-mediated interaction mechanisms to those dominated by structures under shared-wall constraints. Results show that the existing station acts as a high-stiffness boundary, effectively suppressing lateral-wall deflection and basal heave on the proximal side. A critical finding is the reversal of the station’s deformation mode: while stations with a soil buffer typically tilt toward the excavation, the shared-wall station exhibits a clockwise rotation away from the excavation; this phenomenon is driven by excavation-induced basal rebound directly transferred through the common diaphragm wall. Furthermore, the station exerts a significant “shielding effect” on adjacent bridge piles, shifting their maximum lateral displacement from the pile head to the toe and reducing overall deformation. Parametric analyses reveal that optimizing shared-wall thickness is more effective for controlling lateral deformation, whereas increasing wall depth primarily mediates vertical heave. This study concludes that, for shared-wall systems, design priorities must shift from settlement control to anti-heave measures, and pile monitoring should extend to the deeper critical zones identified in this study. Full article

Hydrometallurgical pretreatment of pyrite-bearing concentrates and tailings by hydrothermal interaction with Cu(II) solutions is a promising route for chemical beneficiation and mitigation of acid mine drainage but is limited by passivation caused by elemental sulfur and secondary copper sulfides. Here, the effect of sodium lignosulfonate (SLS) on the hydrothermal reaction between natural pyrite and CuSO₄ in H₂SO₄ media at 180–220 °C was studied at [H₂SO₄]₀ = 10–30 g/dm³, [Cu]₀ = 6–24 g/dm³, and [SLS]₀ = 0–1.0 g/dm³. Process efficiency was evaluated by Fe extraction into solution and Cu precipitation on the solid phase, and products were characterized by XRD and SEM/EDS. SLS markedly intensified pyrite conversion: at 200 °C and 120 min, Fe extraction increased from 14 to 26% and Cu precipitation from 5 to 23%, while at 220 °C, Fe extraction reached 33.4% and Cu precipitation 26.8%. XRD confirmed the sequential transformation CuS → Cu_1.8S. SEM/EDS showed that SLS converts localized nucleation of Cu_xS on defect sites into the formation of a fine, loosely packed, and well-dispersed copper sulfide phase. The results demonstrate that lignosulfonate surfactants efficiently suppress passivation and enhance mass transfer, providing a basis for intensifying hydrothermal pretreatment of pyrite-bearing industrial materials. Full article

China’s roof-cutting and pressure relief gob-side entry retaining (RCPR-GER) technology provides an efficient non-pillar mining solution that significantly enhances coal recovery. This paper presents a systematic review of the technological progress in Chinese coal mines from 2011 to 2023, based on an analysis of 1038 publications from CNKI, EI, and Web of Science using VOS viewer and Origin software. Four main technical approaches are examined: gob-side entry retaining without roadside filling, with roadside filling, with roof-cutting and pressure relief, and hybrid methods. Five key roof-cutting techniques are evaluated: dense drilling, high-pressure water-jet slotting, hydraulic fracturing, blasting, presplitting, and roof water injection softening. Successful applications have been documented in coal seams with thicknesses of 1.6–6.15 m and burial depths of 92–1037 m, demonstrating wide adaptability. The roof-cutting short-beam theory underpins the mechanism, which reduces roadway deformation, shortens the cantilever beam length, and alters stress transfer paths. Compared to previous reviews on general gob-side entry retaining, this study offers a dedicated synthesis and comparative analysis of RCPR-GER technologies, establishing a selection framework grounded in geological compatibility and engineering practice. Future research should focus on adaptive parameter design for deep hard composite roofs, quantitative modeling of passive roof-cutting effects, optimization of cutting timing and orientation, and floor-heave control technologies to extend applications under complex geological conditions. Full article

Students with learning disabilities (LD) often struggle to develop deep, transferable conceptual understanding in mathematics due to cognitive and processing challenges, underscoring the relevance of instruction grounded in strong teacher pedagogical content knowledge (PCK). This issue is critical given widening post-pandemic achievement gaps and increased expectations for conceptual understanding in inclusive classrooms. Although many studies document effective mathematics interventions for students with LD, relatively few examine how teachers’ PCK functions in these classrooms. In contrast, general education research highlights the importance of PCK for conceptual learning. This manuscript bridges these studies by examining how insights from broader PCK research may inform instruction for students with LD. This manuscript presents a practice-based conceptual synthesis of research on mathematics teachers’ PCK, integrating findings from special education and mathematics intervention literature with classroom vignettes and practitioner examples. The synthesis highlights how core PCK components—content knowledge, understanding of student thinking and misconceptions, and instructional strategies—may support early conceptual understanding in students with LD, emphasizing multiple representations, error analysis, and routines that promote generalization through distributed practice. Implications for practice, professional development, and future research are discussed, offering practice-informed pathways to support inclusive mathematics instruction for students with LD. Full article

A dew-point evaporative air cooler incorporating a novel segmented heat exchange design, demarcated according to the humidity state of moist air, is proposed. The system employs a porous fibrous material to create a wetted evaporative surface, which is continuously maintained in a moistened condition through a self-wicking water supply mechanism to enhance latent heat transfer. Circular fins are installed on the heat exchanger’s partition surface once the moist air reaches saturation, thereby improving sensible heat exchange between the dry and wet channels. The performance of a prototype was evaluated under controlled conditions in a standard enthalpy chamber. Experimental results indicate that, under typical summer conditions (inlet dry-bulb and wet-bulb temperatures of 33.8 °C and 25.4 °C, respectively), with an air mass flow ratio of 0.7 and an air velocity of 1.5 m/s, the wet-bulb effectiveness reaches 114.4% and the dew-point effectiveness achieves 84.8%. The maximum temperature reduction occurs in the sensible heat exchange section, reaching up to 6.1 °C, demonstrating its substantial sensible heat recovery capability. The device exhibits an energy efficiency ratio (EER) ranging from 9.1 to 31.8. The proposed compact configuration not only enhances energy efficiency but also reduces material costs by approximately 15.4%, providing a valuable reference for the future development of dew-point evaporative cooling systems in residential buildings. Full article

Camellia oleifera, a woody oil crop unique to China, plays a crucial role in alleviating the global pressure of edible oil supply and maintaining ecological security. However, it remains challenging to accurately forecast Camellia oleifera yield in complex landscapes using only remote sensing data. The aim of this study is to develop an interpretable deep learning model, namely Shapley Additive Explanations–guided Attention–long short-term memory (SALSTM), for estimating Camellia oleifera yield by integrating an improved spectral bloom index and environmental parameters. The study area is located in Hengyang City in Hunan Province. Sentinel-2 imagery, meteorological observation from 2019 to 2023, and topographic data were collected. First, an improved spectral bloom index (ISBI) was constructed as a proxy for flowering density, while average temperature, precipitation, accumulated temperature, and wind speed were selected to represent environmental regulation variables. Second, a SALSTM model was designed to capture temporal dynamics from multi-source inputs, in which the LSTM module extracts time-dependent information and an attention mechanism assigns time-step-wise weights. Feature-level importance derived from SHAP analysis was incorporated as a guiding prior to inform attention distribution across variable dimensions, thereby enhancing model transparency. Third, model performance was evaluated using root mean square error (RMSE) and coefficient of determination (R²). The result show that the constructed SALSTM model achieved strong predictive performance in predicting Camellia oleifera yield in Hengyang City (RMSE = 0.5738 t/ha, R² = 0.7943). Feature importance analysis results reveal that ISBI weight > 0.26, followed by average temperature and precipitation from flowering to fruit stages, these features are closely associated with C. oleifera yield. Spatially, high-yield zones were mainly concentrated in the central–southern hilly regions throughout 2019–2023, In contrast, low-yield zones were predominantly distributed in the northern and western mountainous areas. Temporally, yield hotspots exhibited a gradual increasing while low-yield zones showed mild fluctuations. This framework provides an effective and transferable approach for remote sensing-based yield estimation of flowering and fruit-bearing crops in complex landscapes. Full article

Background/Objectives: Water pollution caused by human activities disrupts ecosystems and promotes the spread of antimicrobial resistance genes (ARGs), posing a public health threat. This study investigated the presence of resistant Gram-negative bacteria and resistance genes in water from two sites occasionally exposed to domestic and hospital effluents, the Carioca River (CR) and Rodrigo de Freitas Lagoon (RFL), both used for recreation. Methods: Physicochemical parameters and coliform levels were measured. Bacterial isolates were identified by Matrix-Assisted Laser Desorption Ionization–Time-of-Flight Mass Spectrometry (MALDI-TOF MS) and tested for antimicrobial susceptibility using disk diffusion. The Minimum Inhibitory Concentration (MIC) was determined using the E-test^® and broth microdilution methods. PCR was used to detect carbapenem resistance and other ARGs from the DNA of bacterial isolates obtained from water samples. Results: CR presented signs of environmental degradation, with low dissolved oxygen and high coliform counts. One Citrobacter braakii isolate showed resistance to all tested antimicrobials, raising concern for untreatable infections. Carbapenem-resistant isolates accounted for 49.4% of the total, harboring bla_KPC (20%), bla_TEM (5%), bla_VIM (5%), and bla_SPM (5%). The intl1 gene was found in 10% of isolates, indicating potential horizontal gene transfer. Conclusions: The findings from a one-day sampling reveal the presence of multidrug-resistant bacteria that carry antimicrobial resistance genes in polluted aquatic systems. These highlight the connection between water contamination and antimicrobial resistance. The evidence underscores the urgent need for environmental monitoring and effective management strategies to reduce public health risks. Full article

The Mixed-Conduction Model for oxide films is used to quantitatively interpret in situ electrochemical and ex situ surface analytical results on the corrosion of AISI 316L (an internal reactor material) and Alloy 690 (a steam generator tube material) in small modular reactor primary coolant with the addition of soluble Zn. The model parameters of alloy oxidation and corrosion release are estimated with the time of exposure up to 168 h and anodic polarization potential (up to −0.25 V vs. standard hydrogen electrode) using fitting of the transfer function to experimental impedance spectra. Model parameters of individual alloy constituents are estimated by fitting of the model equations to the atomic fraction profiles of respective elements in the formed oxide obtained by Glow-Discharge Optical Emission Spectroscopy (GDOES). Conclusions on the effect of Zn addition on film growth and cation release processes in boron-free SMR coolant are drawn and future research directions are outlined. Full article

In recent years, the energy revolution has driven the rapid development of lithium-ion batteries (LIBs). A fire suppression system capable of rapidly and effectively extinguishing LIB fires constitutes the last line of defense for ensuring the safe operation of the LIB industry. In this study, an experimental platform simulating the storage environment of LIBs in energy-storage stations was constructed, and liquid nitrogen (LN) was employed to conduct fire suppression tests on LIBs. The effective utilization of 17.4 kg of LN during the suppression process inside the battery module was quantified. In addition, fire compartments were established within the battery module, and a strategy for enhancing the LN suppression effectiveness was proposed. The results indicate that, without intervention, the thermal runaway propagation (TRP) rate within the LIB module gradually accelerates. After LN injection, the effective utilization of LN for extinguishing individual LIBs decreases progressively along the sequence of TRP. Creating fire compartments inside the PACK using 6 mm aerogel blankets effectively reduces the transfer of energy from the region undergoing thermal runaway (TR) to other regions, while simultaneously enhancing the extinguishing performance of LN. Under the same LN dosage, the introduction of fire compartments increases the effective utilization from 0.037 to 0.051. However, as the compartment volume decreases, the degree of improvement in LN utilization is reduced. This work is expected to provide guidance for the engineering application of LN-based fire suppression systems to inhibit LIB TR and its propagation. Full article