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most exciting work published in the various research areas of the journal.
Hydraulic conductivity anisotropy critically controls seawater intrusion management in coastal aquifers, and yet its impact on negative hydraulic barriers remains poorly understood. Using three-dimensional density-dependent modeling, this study reveals how varying ratios between horizontal and vertical conductivity influence barrier effectiveness. The results show
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Hydraulic conductivity anisotropy critically controls seawater intrusion management in coastal aquifers, and yet its impact on negative hydraulic barriers remains poorly understood. Using three-dimensional density-dependent modeling, this study reveals how varying ratios between horizontal and vertical conductivity influence barrier effectiveness. The results show that systems where vertical conductivity dominates enhance horizontal flow, but retain more residual salt, while horizontally dominated systems initially accelerate saltwater wedge retreat, but subsequently cause interface destabilization and inland reinvasion. Pumping rate and well depth interact significantly with these anisotropy effects, with higher pumping rates reducing anisotropy-dependent variations and deeper wells activating density-driven convection processes. Optimal barrier design requires careful consideration of competing objectives, as conditions favoring interface stability differ from those maximizing salt removal. These findings establish design principles for hydraulic barriers in anisotropic coastal aquifers, providing critical insights for managing seawater intrusion in increasingly stressed groundwater systems.
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The objective of the study was to develop and validate a ground-based method using a depth image sensor equipped with depth, visible red, green, blue (RGB), and near-infrared bands to measure the leaf area index (LAI) based on the relative illuminance of foliage
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The objective of the study was to develop and validate a ground-based method using a depth image sensor equipped with depth, visible red, green, blue (RGB), and near-infrared bands to measure the leaf area index (LAI) based on the relative illuminance of foliage only. The method was applied in a Itajii chinkapin (Castanopsis sieboldii (Makino) Hatus. ex T.Yamaz. & Mashiba )forest in Aichi Prefecture, Japan, and validated by comparing estimates with conventional methods (LAI-2200 and fisheye photography). To apply the 5-band sensor to actual forests, a methodology is proposed for matching the color camera and near-infrared camera in units of pixels, along with a method for widening the exposure range through multi-step camera exposure. Based on these advancements, the RGB color band, near-infrared band, and depth band are converted into several physical properties. Employing these properties, each pixel of the canopy image is classified into upper foliage, lower foliage, sky, and non-assimilated parts (stems and branches). Subsequently, the LAI is calculated using the gap-fraction method, which is based on the relative illuminance of the foliage. In comparison with existing indirect LAI estimations, this technique enabled the distinction between upper and lower canopy layers and the exclusion of non-assimilated parts. The findings indicate that the plant area index (PAI) ranged from 2.23 to 3.68 m2 m−2, representing an increase from 33% to 34% compared to the LAI calculated after excluding non-assimilating parts. The findings of this study underscore the necessity of distinguishing non-assimilated components in the estimation of LAI. The PAI estimates derived from the depth image sensor exhibited moderate to strong agreement with the LAI-2200, contingent upon canopy rings (R2 = 0.48–0.98), thereby substantiating the reliability of the system’s performance. The developed approaches also permit the evaluation of the distributions of leaves and branches at various heights from the ground surface to the top of the canopy. The novel LAI measurement method developed in this study has the potential to provide precise, reliable foundational data to support research in ecology and hydrology related to complex tree structures.
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Global virtual exchange is a mode of teaching that can reach classrooms beyond national borders and across disciplines. This paper utilizes students’ online conversations and learning projects as primary data to demonstrate experiential learning and critical thinking processes in a global virtual classroom
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Global virtual exchange is a mode of teaching that can reach classrooms beyond national borders and across disciplines. This paper utilizes students’ online conversations and learning projects as primary data to demonstrate experiential learning and critical thinking processes in a global virtual classroom between students in the U.S. and China. Findings reveal that guided weekly online conversations between American and Chinese students provided experiential learning about personal and familial experiences as well as deep insights into healthcare and pension policies affecting individuals and societies. Furthermore, collaborative learning projects on healthcare and pension systems among international students embedded critical thinking in the learning process. These learning projects are comparative and thought-provoking, offering students a chance to apply a critical and global lens to the understanding of social policies and services in different social and cultural contexts. The expansion of global virtual exchange may be a byproduct of COVID-19 distant learning; it may have opened new channels for breaking geographic boundaries of learning sociology in global and critical perspectives.
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Analog computing has re-emerged as a powerful tool for solving complex problems in various domains due to its energy efficiency and inherent parallelism. This paper summarizes recent advancements in analog computing, exploring discrete time and continuous time methods for solving combinatorial optimization problems,
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Analog computing has re-emerged as a powerful tool for solving complex problems in various domains due to its energy efficiency and inherent parallelism. This paper summarizes recent advancements in analog computing, exploring discrete time and continuous time methods for solving combinatorial optimization problems, solving partial differential equations and systems of linear equations, accelerating machine learning (ML) inference, multi-beam beamforming, signal processing, quantum simulation, and statistical inference. We highlight CMOS implementations that leverage switched-capacitor, switched-current, and radio-frequency circuits, as well as non-CMOS implementations that leverage non-volatile memory, wave physics, and stochastic processes. These advancements demonstrate high-speed, energy-efficient computations for computational electromagnetics, finite-difference time-domain (FDTD) solvers, artificial intelligence (AI) inference engines, wireless systems, and related applications. Theoretical foundations, experimental validations, and potential future applications in high-performance computing and signal processing are also discussed.
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Rex Jeya Rajkumar Samdavid Thanapaul, Jishnu K. S. Krishnan, Manoj Y. Govindarajulu, Chetan Y. Pundkar, Gaurav Phuyal, Joseph B. Long and Peethambaran Arun
Traumatic brain injury (TBI) remains a significant public health concern, particularly among military personnel and contact sport athletes who are frequently exposed to repeated blast overpressure waves and mild concussive impacts, respectively. While moderate and severe TBIs have been extensively studied, the long-term
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Traumatic brain injury (TBI) remains a significant public health concern, particularly among military personnel and contact sport athletes who are frequently exposed to repeated blast overpressure waves and mild concussive impacts, respectively. While moderate and severe TBIs have been extensively studied, the long-term neuroendocrine consequences of mild, repetitive brain trauma are poorly understood. In this study, we investigated the temporal dynamics of hypothalamic–pituitary–adrenal (HPA) axis dysregulation following repeated mild concussive head impacts and blast exposures using two clinically relevant rodent models. Male Sprague-Dawley rats were subjected to repeated mild concussive impacts using a modified weight drop model or repeated blast exposures using an advanced blast simulator. Plasma levels of adrenocorticotropic hormone (ACTH) and corticosterone were measured on days 1 and 30 post-injuries. Our findings revealed that repeated blast exposures induced elevation of plasma ACTH and corticosterone on days 1 and 30 post-blasts. After the repeated mild concussive impacts, increased plasma levels of corticosterone were observed on days 1 and 30, but ACTH levels were increased only on day 30. This study is among the first to directly compare neuroendocrine outcomes of repeated mild concussive impacts and blast exposures within a unified experimental framework. Our findings demonstrate distinct temporal trajectories of HPA axis dysregulation depending on injury type and highlight plasma levels of ACTH and corticosterone as potential biomarkers of subclinical brain trauma. These insights may inform early diagnostic approaches and therapeutic strategies aimed at mitigating long-term stress-related complications following mild traumatic brain injuries.
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The disappearance of foreign minors in Italy is a long-standing and critically underexamined social phenomenon. Despite alarming figures, public and institutional attention remains episodic and media-driven, often limited to high-profile or criminal cases. This study offers a socio-forensic analysis of official data from
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The disappearance of foreign minors in Italy is a long-standing and critically underexamined social phenomenon. Despite alarming figures, public and institutional attention remains episodic and media-driven, often limited to high-profile or criminal cases. This study offers a socio-forensic analysis of official data from 2014 to 2023, revealing significant inconsistencies in how these cases are reported, categorized, and followed up by Italian institutions. It highlights how unaccompanied and migrant minors are especially vulnerable within a fragmented and reactive system that lacks transparency and effective preventive measures. Rather than presenting new empirical data, the article reinterprets existing sources to expose systemic gaps, drawing comparisons with the more structured approaches adopted in countries such as the United States, United Kingdom, and Spain. These international examples show how multilingual communication, early warning systems (e.g., AMBER Alert), and public geolocation tools can offer timely, coordinated responses to disappearances—tools that remain largely absent or underused in Italy. The article further argues for the integration of forensic geospatial methods, such as locus operandi analysis, remote sensing, and forensic geoarchaeology, not as experimental techniques, but as practical tools that could strengthen Italy’s institutional capacity to respond. Ultimately, this study seeks to elevate the discussion surrounding missing foreign minors from a marginal social concern to a matter of forensic and public interest, and to encourage interdisciplinary reflection on how such disappearances are framed—and too often dismissed—within the national landscape.
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The overexpression of P-glycoprotein (P-gp) is often directly related to multidrug resistance (MDR), one of the greatest challenges in cancer treatment. This transmembrane efflux pump decreases the intracellular concentrations of chemotherapy drugs, reducing their effectiveness and resulting in treatment failure. This work used
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The overexpression of P-glycoprotein (P-gp) is often directly related to multidrug resistance (MDR), one of the greatest challenges in cancer treatment. This transmembrane efflux pump decreases the intracellular concentrations of chemotherapy drugs, reducing their effectiveness and resulting in treatment failure. This work used in silico methods to assess the potential of bioactive chemicals produced from mushrooms as P-gp modulators. A database comprising 211 bioactive compounds from mushrooms was investigated using molecular docking and virtual screening techniques against the P-gp structure. The compounds ergosta-4,6,8(14),22-tetraen-3-one, lucidumol A, (22E,24S)-ergosta-4,22-dien-3-one, antcin K, 3,11-dioxolanosta-8,24(Z)-diene-26-oic acid, and (22E)-19-norergosta-5,7,9,22-tetraen-3-ol were identified as the six best candidates from our database of mushroom compounds based on their binding affinities, toxicity predictions, and pharmacological properties assessed through ADME analyses (absorption, distributions, metabolism, and excretion). These six compounds exhibited strong binding affinities, with binding energies ranging from −12.31 kcal/mol to −10.93 kcal/mol, all showing higher affinities than the control, tariquidar, which had a binding energy of −10.78 kcal/mol. Toxicity predictions indicated favorable safety profiles for all six, while ADME analyses found that all six compounds had high oral bioavailability and a low probability of acting as P-gp substrates. These results position bioactive mushroom compounds, particularly these six, as promising P-gp modulators, suggesting positive outcomes in cancer treatment.
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Cytokine storm (CS) is associated with poor prognosis in COVID-19 patients. Hypoxic signaling has been proposed to influence proinflammatory pathways and to be involved in the development of CS. Here, for the first time, the role of hypoxia in coronavirus-mediated inflammation has been
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Cytokine storm (CS) is associated with poor prognosis in COVID-19 patients. Hypoxic signaling has been proposed to influence proinflammatory pathways and to be involved in the development of CS. Here, for the first time, the role of hypoxia in coronavirus-mediated inflammation has been investigated, using transcriptomic and proteomic approaches. Analysis of the transcriptome of A549 lung epithelial cells using RNA sequencing revealed 191 mRNAs which were synergistically upregulated and 43 mRNAs which were synergistically downregulated by the combination of human Betacoronavirus OC43 (HCoV-OC43) infection and hypoxia. Synergistically upregulated mRNAs were strongly associated with inflammatory pathway activation. Analysis of the expression of 105 cytokines and immune-related proteins using antibody arrays identified five proteins (IGFBP-3, VEGF, CCL20, CD30, and myeloperoxidase) which were markedly upregulated in HCoV-OC43 infection in hypoxia compared to HCoV-OC43 infection in normal oxygen conditions. Our findings show that COVID-19 patients with lung hypoxia may face increased risk of inflammatory complications. Two of the proteins we have identified as synergistically upregulated, the cytokines VEGF and CCL20, represent potential future therapeutic targets. These could be targeted directly or, based on the novel findings described here by inhibiting hypoxia signaling pathways, to reduce excessive inflammatory cytokine responses in patients with severe infections.
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Mitochondria are central to cellular energy metabolism and play a key role in regulating important physiological processes, including apoptosis and oxidative stress. Mitochondrial quality control has recently garnered significant attention, with the underlying mechanisms traditionally considered to be mitophagy and its dynamics. Various
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Mitochondria are central to cellular energy metabolism and play a key role in regulating important physiological processes, including apoptosis and oxidative stress. Mitochondrial quality control has recently garnered significant attention, with the underlying mechanisms traditionally considered to be mitophagy and its dynamics. Various studies have demonstrated that extracellular vesicles are crucial for the transmission of mitochondria and their components. These vesicles effectively transport mitochondria to target cells, facilitating intercellular material exchange and signal transmission, thereby enhancing cellular function and viability. This review explores the mechanisms of mitochondrial transfer through mitochondrial extracellular vesicles (MitoEVs), analyzes the novel roles of MitoEVs in mitochondrial quality control, and discusses their applications in disease treatment. We aim to provide new perspectives for future research and support the development of relevant therapeutic strategies.
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The purpose of education, viewed as a wicked problem, requires critical examination, particularly in the context of policy that may shape leadership in schools and systems. Given that purpose is a complex and multidimensional construct, it requires multiple frameworks for a comprehensive exploration.
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The purpose of education, viewed as a wicked problem, requires critical examination, particularly in the context of policy that may shape leadership in schools and systems. Given that purpose is a complex and multidimensional construct, it requires multiple frameworks for a comprehensive exploration. We build on Gert Biesta’s three domains of education, qualification, socialisation and subjectification, by developing a novel typology of different perceived benefits of educational purpose and then explore the tensions inherent within these. The benefits typology is derived from the literature specifically exploring educational purpose since 2000, and we employ a tensional analysis framework to untangle competing and interrelated benefit perspectives and identify the paradoxes, dilemmas, dualities and dialectics inherent in purpose statements, which in turn have significant implications for the challenges educational leaders must navigate. We apply this new lens and language for reflection and consideration of purpose by using the framework to examine purpose statements from four international contexts (Australia, Singapore, Finland and Japan), illustrating new ways of conceptualising and analysing the complexity of educational purpose. By extending Biesta’s framework with additional theoretical and practical approaches for educational leaders and researchers seeking to critically examine dominant purpose narratives, this paper makes a small but significant contribution to development of more holistic, sustainable and equitable conceptions of educational purpose in a rapidly changing and increasingly complex global landscape.
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Etching has become a critical step in semiconductor wafer fabrication, and its importance in semiconductor manufacturing highlights the fact that it directly determines the ability of the fab to produce high-process products, as well as the application performance of the chip. While the
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Etching has become a critical step in semiconductor wafer fabrication, and its importance in semiconductor manufacturing highlights the fact that it directly determines the ability of the fab to produce high-process products, as well as the application performance of the chip. While the health of the etcher is a concern, especially for the cooling system, accurately predicting the remaining useful life (RUL) of the etcher cooling system is a critical task. Predictive maintenance (PDM) can be used to monitor the basic condition of the equipment by learning from historical data, and it can help solve the task of RUL prediction. In this paper, we propose the FECAM-WTCN-Informer model, which first obtains a new WTCN structure by inserting wavelet convolution into the TCN, and then combines the discrete cosine transform (DCT) and channel attention mechanism into the temporal neural network (TCN). Multidimensional feature extraction of time series data can be realized, and the processed features are input into the Informer network for prediction. Experimental results show that the method is significantly more accurate in terms of overall prediction performance (MSE, RMSE, and MAE), compared with other state-of-the-art methods, and is suitable for solving the problem of predictive maintenance of etching machine cooling systems.
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Purpose: Our aim was to determine the benefits of serum lactate, albumin, and base excess (BE) values in predicting prognosis and mortality in sepsis when evaluated together. Methods: We performed a prospective observational study. We included 217 patients who were 18 years old
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Purpose: Our aim was to determine the benefits of serum lactate, albumin, and base excess (BE) values in predicting prognosis and mortality in sepsis when evaluated together. Methods: We performed a prospective observational study. We included 217 patients who were 18 years old or older, admitted to the Adult Emergency Department at Hacettepe University Hospital between May 2019 and July 2020, and who had two or more SOFA scores. We evaluated admission hour, 24th hour and 48th hour lactate, albumin, and BE. Results: A decrease in 0, 24th, and 48th hour albumin values increases the mortality of sepsis patients. An increase in the 24th hour lactate value increases hospital mortality. Changes in BE values had no effect on hospital mortality. Hospital mortality increases as 24 h lactate clearance decreases. Alactic base excess has no effect on mortality. The AUC values of lactate and albumin are significant, but their sensitivities are low. The AUC value for 24 h lactate clearance is significant, but the sensitivity of the AUC value is low. Conclusions: Contrary to the literature, lactate, albumin, and BE were found to have low sensitivity in determining prognosis and mortality. When factors that may influence serum lactate, albumin, and base excess (BE) are excluded, the values of these biomarkers decrease when predicting mortality.
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Martín Martínez-Salvador, Alfredo Pinedo-Alvarez, Sandra Rodríguez-Piñeros, Raúl Corrales-Lerma, Ricardo D. Valdez-Cepeda, Fidel Blanco-Macias, Griselda Vazquez-Quintero, David E. Hermosillo-Rojas and Adrián Hernández-Ramos
Forests2025, 16(8), 1295; https://doi.org/10.3390/f16081295 (registering DOI) - 8 Aug 2025
Development of site index models for shrubby species in arid ecosystems remains a challenge, due to the absence of dominant height–age relationships and the complexity of ecological drivers in these environments. In this study, a multivariate approach to classify site quality for Agave [...] Read more.
Development of site index models for shrubby species in arid ecosystems remains a challenge, due to the absence of dominant height–age relationships and the complexity of ecological drivers in these environments. In this study, a multivariate approach to classify site quality for Agave lechuguilla Torr, a wild non-timber species of ecological and economic importance in northern Mexico, was performed. Data were collected from 112 sampling plots where the abundance, height, basal diameter, and crown diameter for the A. lechuguilla plants were measured. Sites were grouped into three site index categories (low, medium, and high) using the Importance Value Index (IVI). Afterward a classical discriminant analysis (CDA) was applied to derive linear functions capable of classifying new sites into these predefined categories. Statistical assumptions of multivariate normality, homogeneity of covariance matrices, and low multicollinearity were met. The discriminant functions showed high classification accuracy (95.54%), with full correct classification of low and high site index categories. Additional validation through MANOVA and principal component analysis (PCA) confirmed the separation of groups and the ecological coherence of the selected variables. This approach provides a simple, practical, and replicable model for assessing shrubland site quality using field measurable features. It also offers a tool for sustainable harvesting and conservation of A. lechuguilla.
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The hydrodynamic resistance experienced by deep-sea mining vehicles (DSMV) during underwater operations and deployment/retrieval processes has a significant impact on maneuverability and operational safety. Therefore, accurate determination of the vehicle’s hydrodynamic coefficients is essential for motion control and system design. In this study,
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The hydrodynamic resistance experienced by deep-sea mining vehicles (DSMV) during underwater operations and deployment/retrieval processes has a significant impact on maneuverability and operational safety. Therefore, accurate determination of the vehicle’s hydrodynamic coefficients is essential for motion control and system design. In this study, computational fluid dynamics (CFD) methods are utilized to calculate the transverse and vertical drag forces acting on the DSMV, as well as the corresponding added mass in both directions. The unsteady Reynolds-averaged Navier–Stokes equations were employed to analyze the vehicle’s dynamic behavior and the development of its wake flow structures. under uniform and accelerated motion conditions is analyzed. The time-averaging technique is applied to extract steady-state drag forces and drag coefficients, while the added mass and added mass coefficients are estimated by isolating viscous and inertial forces during acceleration. To verify the accuracy of the CFD methodology, simulations of regularly shaped bodies are performed, and the results are compared with theoretical solutions. The results show a high degree of agreement, confirming the reliability of the numerical approach used in this study.
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The aim of this study was to analyse the Western Australian (WA) Safety Regulatory System (SRS) database to assess compliance of the WA mining sector regarding workers exposure to welding fumes and to identify trends over time. De-identified data analysed to assess the
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The aim of this study was to analyse the Western Australian (WA) Safety Regulatory System (SRS) database to assess compliance of the WA mining sector regarding workers exposure to welding fumes and to identify trends over time. De-identified data analysed to assess the impact of reducing workplace exposure standards (WES) for general welding fumes on industry compliance. Historical trend analysis shows a shift from 100% compliance to 100% non-compliance, based on mean values and 95% confidence intervals, with exposure levels remaining consistent over time. These findings highlight the need for current, innovative engineering solutions, and raise questions about the validity of current sampling methods. Powered air-purifying respirators (PAPRs) integrated with welding helmets can reduce exposures by up to 99.96%, making their adoption as industry best practice critical, yet current sampling methodologies measure welding fume levels outside PAPRs, thus potentially misclassifying workers who are adequately protected as non-compliant. The sampling method is also influenced by other particulate matter present in the workplace that may be due to grinding or other dust generating activities in the vicinity of the welder. Lower WES values necessitate a review of exposure assessment and reporting methods to accurately reflect worker exposures.
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Julie Mallouhi, Emőke Sikora, Kitti Gráczer, Olivér Bánhidi, Sarra Gaspard, Marckens Francoeur, Yeray Alvarez-Galvan, Francesca Goudou, Béla Viskolcz, Emma Szőri-Dorogházi and Béla Fiser
Int. J. Mol. Sci.2025, 26(16), 7666; https://doi.org/10.3390/ijms26167666 (registering DOI) - 8 Aug 2025
Activated carbon (AC) and biochar (BC) are porous substances derived from any carbonous material known to be highly effective adsorbents, making them valuable for removing pollutants like heavy metals. This study evaluated and compared the potential of AC and BC produced from Sargassum [...] Read more.
Activated carbon (AC) and biochar (BC) are porous substances derived from any carbonous material known to be highly effective adsorbents, making them valuable for removing pollutants like heavy metals. This study evaluated and compared the potential of AC and BC produced from Sargassum sp. by chemical activation and pyrolysis process for heavy metal removal, specifically Co2+ ions, to commercial AC (COMAC). Various techniques were employed to characterize these samples including FTIR, zeta potential, and surface area. Additionally, considering parameters such as pH, initial solution concentration, and the effect of AC/BC dose were investigated. The adsorption isotherm was also assessed. The results showed that a strong dependence of the adsorption capacity on pH was observed with optimal performance at ~6.8. Additionally, the optimal initial solution concentration was determined to be ~2 mmol/L. According to the Langmuir isotherm model, AC derived-Sargassum sp. exhibited maximum uptakes of 468.97 mg/g, higher than COMAC and BC. The experiment at different adsorbent dosages revealed that AC from Sargassum sp. outperformed other samples, with adsorption capacity observed at 94.94% as the dosage increased.
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Background/Objectives: Inflammation plays a key role in acute coronary syndromes (ACS). The systemic immune-inflammation index (SII), which integrates immune and inflammatory markers, may serve as a valuable prognostic tool. This study aimed to evaluate the utility of SII as a short-term predictor of
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Background/Objectives: Inflammation plays a key role in acute coronary syndromes (ACS). The systemic immune-inflammation index (SII), which integrates immune and inflammatory markers, may serve as a valuable prognostic tool. This study aimed to evaluate the utility of SII as a short-term predictor of mortality and major adverse cardiovascular and cerebral events (MACCE) in ACS patients. Methods: A retrospective analysis was conducted on 964 ACS patients admitted in 2023. SII was calculated from admission hematological parameters. Primary and secondary outcomes were 30-day mortality and MACCE, respectively. Results: SII levels differed significantly across ACS subtypes (p < 0.001), highest in ST-segment elevation myocardial infarction (STEMI) and lowest in unstable angina. SII was markedly higher in deceased patients (2003.79 ± 1601.17) vs. survivors (722.04 ± 837.25; p < 0.001) and remained an independent predictor of mortality (OR = 1.038, p < 0.001). Similarly, SII was elevated in MACCE cases (1717 ± 1611.32) vs. non-MACCE (664.68 ± 713.11; p < 0.001) and remained predictive in multivariate analysis (OR = 1.080, p < 0.001). Predictive accuracy for MACCE was moderate (AUC = 0.762), improved when combined with GRACE 2, especially in specificity (p = 0.07). In STEMI, SII had excellent accuracy (AUC = 0.874), outperforming neutrophil–lymphocyte ratio and C-reactive protein. SII rose at 24 h and declined at 48 h in STEMI, with a slower decline in MACCE patients. Conclusions: SII proved to be a cost-effective biomarker reflecting inflammation, immunity, and thrombosis. Elevated SII predicted short-term MACCE and mortality in ACS, with improved prognostic power when combined with GRACE 2. Persistent elevation may signal ongoing inflammation and increased MACCE risk.
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Video anomaly detection has an important application value in the field of intelligent surveillance; however, due to the problems of sparse anomaly events and expensive labeling, it has made weakly supervised methods a research hotspot. Most of the current methods still adopt the
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Video anomaly detection has an important application value in the field of intelligent surveillance; however, due to the problems of sparse anomaly events and expensive labeling, it has made weakly supervised methods a research hotspot. Most of the current methods still adopt the strategy of processing temporal and spatial features independently, which makes it difficult to fully capture their temporal and spatial complex dependencies, affecting the accuracy and robustness of detection. Existing studies predominantly process temporal and spatial information independently, which limits the ability to effectively capture their interdependencies. To address this, we propose the Local Temporal and Global Spatial Network (LTGS) for weakly supervised video anomaly detection. The LTGS architecture incorporates a clip-level temporal feature relation module and a video-level spatial feature module, which collaboratively enhance discriminative representations. Through joint training of these modules, we develop a feature encoder specifically tailored for video anomaly detection. To further refine clip-level annotations and better align them with actual events, we employ a dynamic label updating strategy. These updated labels are utilized to optimize the model and enhance its robustness. Extensive experiments on two widely used public datasets, ShanghaiTech and UCF-Crime, validate the effectiveness of the proposed LTGS method. Experimental results demonstrate that the LTGS achieves an AUC of 96.69% on the ShanghaiTech dataset and 82.33% on the UCF dataset, outperforming various state-of-the-art algorithms in anomaly detection tasks.
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Actinomycosis is an uncommon but significant chronic bacterial infection affecting various parts of the body caused by Actinomyces species. Because of the nonspecific symptoms and rarity of the condition, the diagnosis of head-and-neck or cervicofacial actinomycosis is usually challenging and delayed. A 39-year-old
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Actinomycosis is an uncommon but significant chronic bacterial infection affecting various parts of the body caused by Actinomyces species. Because of the nonspecific symptoms and rarity of the condition, the diagnosis of head-and-neck or cervicofacial actinomycosis is usually challenging and delayed. A 39-year-old woman presented with an enlarging right neck mass and dysphagia after steroid exposure for treatment of De Quervain thyroiditis. MRI showed a large irregular infiltration mass over the right side of her neck, with a multi-loculated rim-enhancing area over the right retropharyngeal space. Excisional biopsy of the lesion only showed evidence of acute on chronic inflammation, and the results of all microbiological testing (including bacterial culture, Gram-staining, and molecular detection) were negative. Metagenomic next-generation sequencing (mNGS) of the formalin-fixed paraffin-embedded (FFPE) tissue from the patient was performed. DNA of Actinomyces israelii and Methylobacterium was detected. The patient was confirmed to have cervical actinomycosis and completely recovered after 6 months of oral amoxicillin. Our patient is the first case utilizing mNGS on FFPE tissue to diagnose cervical actinomycosis. This case shows that mNGS is a promising, unbiased tool for detecting Actinomyces species in FFPE tissues and diagnosing cervical actinomycosis. It also highlights the diagnostic difficulties of cervical actinomycosis.
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The urban heat island (UHI) effect has emerged as a growing ecological challenge in compact urban environments. Although urban vegetation plays a vital role in mitigating thermal extremes, its cooling performance varies depending on vegetation type and urban morphological context. This study explores
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The urban heat island (UHI) effect has emerged as a growing ecological challenge in compact urban environments. Although urban vegetation plays a vital role in mitigating thermal extremes, its cooling performance varies depending on vegetation type and urban morphological context. This study explores the extent to which compact urban development—quantified using the Mixed-use and Intensive Development (MIXD) index—modulates the cooling responses of different vegetation types in Nanjing, China. A combination of landscape metrics, regression-based interaction models, and XGBoost with SHAP analysis is employed to uncover vegetation-specific and structure-sensitive cooling effects. The results indicate that densely planted trees exhibit reduced cooling effectiveness in compact areas, where spatial clustering and fragmentation tend to intensify UHI effects, particularly during nighttime. In contrast, scattered trees are found to maintain more stable cooling performance across varying degrees of urban compactness, while low-lying vegetation demonstrates limited thermal regulation capacity. Critical thresholds of MIXD (approximately 28 for UHI area and 37 for UHI intensity) are identified, indicating a nonlinear modulation of green space performance. These findings underscore the importance of vegetation structure and spatial configuration in shaping urban microclimates and offer mechanistic insights into plant–environment interactions under conditions of increasing urban density.
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This study investigates the association between Low-Carbohydrate Diet (LCD) score and the incidence of hypertension in the Japanese population. This cohort study was conducted in an ongoing longitudinal study, the Toon Health Study. Hypertension was defined by measured blood pressure levels and self-reported
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This study investigates the association between Low-Carbohydrate Diet (LCD) score and the incidence of hypertension in the Japanese population. This cohort study was conducted in an ongoing longitudinal study, the Toon Health Study. Hypertension was defined by measured blood pressure levels and self-reported treatment information, and dietary intake was measured through a validated food frequency questionnaire. Total, animal and plant-based LCD scores were calculated. Participants were divided into sex-specific tertiles of LCD scores. A multivariable-adjusted logistic regression model was used to calculate odds ratio (OR) and 95% confidence interval (95% CI) of incidence of hypertension. Total and plant-based LCD scores showed a borderline negative association with incidence of hypertension. The ORs (95% CI) for the highest versus lowest tertile of the total LCD score were 0.61(0.37–1.03, p for trend = 0.07) and 0.65(0.39–1.10, p for trend = 0.09) for the plant-based LCD score. Stratified analysis by drinking status showed significant negative association among alcohol drinkers, multivariable ORs (95% CI) for the highest versus lowest tertile of total LCD score was 0.38 (0.17–0.83, p for trend = 0.01) and for the plant-based LCD score was 0.39 (0.17–0.90, p for trend = 0.01). No significant association observed in non-drinkers. In conclusion, an increased LCD score was associated with the lower incidence of hypertension, especially in the drinking population.
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With the rapid advancement of the Internet of Things (IoT), artificial intelligence (AI), and blockchain technologies, educational research has increasingly explored smart and personalized learning systems. However, current approaches often suffer from fragmented integration of health monitoring and instructional adaptation, insufficient prediction accuracy
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With the rapid advancement of the Internet of Things (IoT), artificial intelligence (AI), and blockchain technologies, educational research has increasingly explored smart and personalized learning systems. However, current approaches often suffer from fragmented integration of health monitoring and instructional adaptation, insufficient prediction accuracy of physiological states, and unresolved concerns regarding data privacy and security. To address these challenges, this study introduces SHARP, a novel blockchain-enhanced wireless sensor networks (WSNs) framework designed for real-time student health monitoring and personalized learning in smart educational environments. Wearable sensors enable continuous collection of physiological data, including heart rate variability, body temperature, and stress indicators. A deep neural network (DNN) processes these inputs to detect students’ physical and affective states, while a reinforcement learning (RL) algorithm dynamically generates individualised educational recommendations. A Proof-of-Authority (PoA) blockchain ensures secure, immutable, and transparent data management. Preliminary evaluations in simulated smart classrooms demonstrate significant improvements: the DNN achieves a 94.2% F1-score in state recognition, the RL module reduces critical event response latency, and energy efficiency improves by 23.5% compared to conventional baselines. Notably, intervention groups exhibit a 156% improvement in quiz scores over control groups. Compared to existing solutions, SHARP uniquely integrates multi-sensor physiological monitoring, real-time AI-based personalization, and blockchain-secured data governance in a unified framework. This results in superior accuracy, higher energy efficiency, and enhanced data integrity compared to prior IoT-based educational platforms. By combining intelligent sensing, adaptive analytics, and secure storage, SHARP offers a scalable and privacy-preserving solution for next-generation smart education.
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The primary challenge for European society today is to strike a balance between maximizing energy efficiency and environmental care, while also ensuring an accessible and safe living environment. The research presented in this Special Issue addressed various aspects of energy storage methods and
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The primary challenge for European society today is to strike a balance between maximizing energy efficiency and environmental care, while also ensuring an accessible and safe living environment. The research presented in this Special Issue addressed various aspects of energy storage methods and covered advances in the energy efficiency of buildings and cities in light of the climate change awareness and the need to reduce energy consumption and the carbon footprint from the built environment. Results of empirical and modelling research were compared to advanced simulations and measurements rooted in real-world case studies performed with the purpose of extending the knowledge on holistic sustainable design towards efficient energy use. Key aspects enabling improvements in the energy performance of buildings and contributing to the achievement of climate goals cover thermal comfort and overheating in buildings and cities, including district heating, hydrogen energy storage, renewable energy source integration, carbon emissions, and the economic benefits of building deep renovation. The research findings help us to understand the critical importance of transforming the built environment into renewable energy sources while supporting the energy efficiency of buildings, cities, and neighbourhoods.
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With the rapid growth of renewable energy integration, power systems are facing increasing uncertainty and variability in operation. The intermittent and uncontrollable nature of wind and solar generation requires operational decisions to anticipate future fluctuations, creating strong temporal coupling across days. This leads
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With the rapid growth of renewable energy integration, power systems are facing increasing uncertainty and variability in operation. The intermittent and uncontrollable nature of wind and solar generation requires operational decisions to anticipate future fluctuations, creating strong temporal coupling across days. This leads to large-scale mixed-integer linear programming (MILP) with a large number of binary variables, which is computationally intensive—especially in year-long simulations. As a result, there is a growing need for efficient modeling approaches that can reduce complexity while preserving key temporal features. This paper proposes a temporal–spatial acceleration framework for long-term power system operation simulation. In the temporal dimension, a monthly K-means clustering algorithm is applied to reconstruct typical scenario days from 8760 h time series, preserving the characteristics of seasonal and intraday variability. In the spatial dimension, thermal units with similar characteristics are aggregated, and binary decision variables are relaxed into continuous variables, transforming the MILP into a tractable LP model, and thereby reducing computational burden. Case studies are performed based on the six-bus and the IEEE RTS-79 systems to validate the framework, being able to provide a practical solution for renewable-integrated power system planning and dispatch applications.
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Background/Objectives: This study aims to compare the safety of tenecteplase versus alteplase for acute ischemic stroke. Methods: This was a multicenter, retrospective cohort study including 11 Memorial Hermann Health System hospitals in Houston from 7 December 2022 to 7 June 2023. Adults presenting
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Background/Objectives: This study aims to compare the safety of tenecteplase versus alteplase for acute ischemic stroke. Methods: This was a multicenter, retrospective cohort study including 11 Memorial Hermann Health System hospitals in Houston from 7 December 2022 to 7 June 2023. Adults presenting with an acute ischemic stroke who received alteplase or tenecteplase were included in this study. The primary outcome was the incidence of hemorrhagic conversion after 24 h of thrombolytic administration. Secondary outcomes included door-to-needle time, incidence of a major or minor bleed, length of hospital stay, incidence of any adverse effect, modified Rankin score at discharge, patient discharge disposition, medication cost, and mortality. Results: A total of 173 patients were reviewed, with 87 patients in the tenecteplase group and 86 patients in the alteplase group. Gender, actual body weight, and use of aspirin or dual antiplatelet therapy within 24 h of thrombolytic administration were statistically disproportionate between both groups. Hemorrhagic conversion occurred in seven patients in the tenecteplase group and eight patients in the alteplase group (p = 0.79). Medication cost was statistically significant between both groups. All other secondary outcomes were similar between tenecteplase and alteplase. Conclusions: In this underpowered study, we did not observe a statistically significant difference in the rate of 24 h hemorrhagic conversion between the tenecteplase and alteplase groups. Further studies with a large sample size are warranted to assess safety outcomes.
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The escalating demand for sustainable agriculture calls for innovative strategies that enhance crop resilience while minimizing dependence on synthetic fertilizers. This study evaluated the synergistic effects of a microbial consortium (PYS), organic fertilizer (OF), glycine (Gly), and indole-3-acetic acid (IAA) on lettuce under
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The escalating demand for sustainable agriculture calls for innovative strategies that enhance crop resilience while minimizing dependence on synthetic fertilizers. This study evaluated the synergistic effects of a microbial consortium (PYS), organic fertilizer (OF), glycine (Gly), and indole-3-acetic acid (IAA) on lettuce under heat stress. The experiment was conducted in a greenhouse in Bangkok, Thailand, simulating tropical high-temperature conditions. The PYS+OF+Gly treatment significantly improved fresh weight, matching the performance of chemical fertilizer (CF) and indicating a strong growth-promoting synergy. Chlorophyll a, chlorophyll b, and carotenoid contents were higher in PYS or PYS+OF treatment, suggesting enhanced photosynthetic efficiency. At 60 days, PYS-based treatments also led to substantial increases in total phenolics and flavonoids, coupled with reduced lipid peroxidation and elevated antioxidant activities (DPPH, APX, CAT, POD, and SOD). However, vitamin C levels remained highest in the CF and OF controls, indicating a potential metabolic shift toward phenylpropanoid rather than ascorbate biosynthesis. Overall, our results demonstrate that combining microbial consortia with organic and biostimulant inputs could enhance growth, stress tolerance, and the nutritional quality of lettuce. This integrated approach presents a promising strategy for climate-resilient crop production and warrants further validation across different crops, environmental settings, and large-scale agricultural systems.
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