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Significant uncertainties persist across different Leaf Area Index (LAI) products due to multiple factors; therefore, the accuracy assessment of the global LAI products is an indispensable step before their application. In this study, comprehensive validation of multi-scale LAI products including Sentinel-2, Landsat-8/9, and
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Significant uncertainties persist across different Leaf Area Index (LAI) products due to multiple factors; therefore, the accuracy assessment of the global LAI products is an indispensable step before their application. In this study, comprehensive validation of multi-scale LAI products including Sentinel-2, Landsat-8/9, and MCD15A3H was implemented utilizing fine-resolution LAI maps which were based on UAV images and field-measured LAI data. The validation results demonstrated a consistent, systematic underestimation across all the LAI products within the study area, the RMSE of these products ranged from 0.56 to 1.63, and the coarse-resolution MCD15A3H LAI product demonstrated highest accuracy (RMSE = 0.56, R2 = 0.69). The Sentinel-2 products exhibited intermediate accuracy among all those products (RMSE: 1.16–1.36). The Landsat-8/9 LAI product showed markedly lower accuracy relative to Sentinel-2; its RMSE (1.63) exceeded that of Sentinel-2 10 m LAI and 20 m LAI by 40.52% and 21.64%, respectively. In addition, all these LAI products showed consistent seasonal variation patterns with the reference LAI maps. Moreover, Sentinel-2 10 m LAI products showed serious underestimation for all vegetation types, with forests providing the highest RMSE = 0.89. This study serves as a valuable reference for the application of multi-scale LAI products in heterogeneous terrain and provides directions for the improvement of fine-resolution LAI retrieval algorithms.
Full article
The proliferation of renewable energy sources and distributed generation systems interfaced to the grid by power electronics systems is forcing us to better understand the issues arising due to the quality of electrical signals generated through these devices. Understanding and monitoring these harmonics
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The proliferation of renewable energy sources and distributed generation systems interfaced to the grid by power electronics systems is forcing us to better understand the issues arising due to the quality of electrical signals generated through these devices. Understanding and monitoring these harmonics is crucial to ensure the smooth and seamless operation of these networks, as well as to protect and manage the renewable energy sources-based power system. In this paper, we propose an advanced method of dynamic modal decomposition, called Higher-Order Dynamic Mode Decomposition (HODMD), one of the recently proposed data-driven methods used to estimate the frequency/amplitude and phase with high resolution, to identify the harmonic spectrum in power systems dominated by renewable energy generation. In the proposed method, several time-shifted copies of the measured signals are integrated to create the initial data matrices. A hard thresholding technique based on singular value decomposition is applied to eliminate ambiguities in the measured signal. The proposed method is validated and compared to Synchrosqueezing Transform based on Short-Time Fourier Transform (SST-STFT) and the Concentration of Frequency and Time via Short-Time Fourier Transform (ConceFT-STFT) using synthetic signals and real measurements, demonstrating its practical effectiveness in identifying harmonics in emerging power networks. Finally, the effectiveness of the proposed methodology is analyzed on the energy storage-based laboratory-scale microgrid setup using an Opal-RT-based real-time simulator.
Full article
To effectively address the issues of poor ventilation, light deficiency, increased pest and disease pressure, and declining fruit quality in closed-canopy walnut orchards, this study was conducted in a standard, densely planted ‘Xinwen 185’ walnut orchard. Three treatments were established: an unthinned control
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To effectively address the issues of poor ventilation, light deficiency, increased pest and disease pressure, and declining fruit quality in closed-canopy walnut orchards, this study was conducted in a standard, densely planted ‘Xinwen 185’ walnut orchard. Three treatments were established: an unthinned control (CK), a 1-year thinning treatment (T1), and a 2-year thinning treatment (T2). All parameters were uniformly investigated during the 2023 growing season to analyze the effects of thinning on orchard population structure, microenvironment, leaf physiological characteristics, fruit quality, and yield. The results demonstrated that tree thinning significantly optimized the population structure: crown width expanded by 6.22–6.76 m, light transmittance increased to 27.74–33.64%, and orchard coverage decreased from 100% to 75.94–80.51%. The microenvironment was improved: inter-row temperature increased by 2.34–4.08 °C, light intensity increased by 5.38–25.29%, and relative humidity decreased by 2.15–3.30%. Furthermore, leaf physiological functions were activated: in the T2 treatment, the chlorophyll content in outer-canopy leaves increased by 15.23% and 12.45% at the kernel-hardening and maturity stages, respectively; the leaf carbon-to-nitrogen ratio increased by 18.67%; the net photosynthetic rate (Pn) during fruit expansion increased by 34.21–46.10%; and the intercellular CO2 concentration (Ci) decreased by 10.18–10.31%. Fruit quality and yield were synergistically enhanced: single fruit weight increased by 23.39~37.94%, and kernel weight increased by 26.79–41.13%. The total sugar content in inner-canopy fruits increased by 16.50–16.67%, while the protein and fat content in outer-canopy fruits increased by 0.69–12.50% and 0.60–2.18%, respectively. Yield exhibited a “short-term adjustment and long-term gain” pattern: the T2 treatment (after 2 years of thinning) achieved a yield of 5.26 t·ha−1, which was 20.38% higher than the CK. The rates of diseased fruit and empty shells decreased by 65.71% and 93.22%, respectively, and the premium fruit rate reached 90.60%. This study confirms that tree thinning is an effective measure for improving the growing environment and enhancing overall productivity in closed-canopy walnut orchards, providing a scientific basis for sustainable orchard management and increased orchard profitability.
Full article
Type 2 diabetes mellitus (T2DM) is a chronic disease that has become a serious health problem worldwide. Moreover, increased systemic and cerebrovascular inflammation is one of the major pathophysiological features of T2DM, and a growing body of evidence emphasizes T2DM with memory and
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Type 2 diabetes mellitus (T2DM) is a chronic disease that has become a serious health problem worldwide. Moreover, increased systemic and cerebrovascular inflammation is one of the major pathophysiological features of T2DM, and a growing body of evidence emphasizes T2DM with memory and executive function decline. Bioactive sphingolipids regulate a cell’s survival, inflammatory response, as well as glucose and insulin signaling/metabolism. Moreover, current research on the role of sphingosine kinases (SPHKs) and sphingosine-1-phosphate receptors (S1PRs) in T2DM is not fully understood, and the results obtained often differ. The aim of the present study was to evaluate the effect of metformin (anti-diabetic agent, MET) on the brain’s sphingosine-1-phosphate-related signaling and ultrastructure in diabetic mice. Our results revealed elevated mRNA levels of genes encoding sphingosine kinase 2 (SPHK2) and sphingosine-1-phosphate receptor 3 (S1PR3), which was accompanied by downregulation of sphingosine-1-phosphate receptor 1 (S1PR1) in the hippocampus of diabetic mice. Simultaneously, upregulation of genes encoding pro-inflammatory cytokines interleukin 6 (IL-6) and tumor necrosis factor α (TNF-α) was observed. Administration of MET significantly reversed changes in mRNA levels in the hippocampus and reduced Sphk2, Il6, and Tnf, with concomitant upregulation of S1pr1 gene expression. Ultrastructural analysis of diabetic mice hippocampus revealed morphological alterations in neurons, neuropil, and capillaries that were manifested as mitochondria swelling, blurred synaptic structure, and thickened basal membrane of capillaries. The use of MET partially reversed those changes. Our research emphasizes the important role of insulin sensitivity modulation by metformin in the regulation of SPHKs and S1PRs and inflammatory gene expression in a murine model of T2DM.
Full article
Nanomaterials play a beneficial role in regulating the function of cement-based materials. The effects and mechanism of graphene oxide (GO) on foam behavior in solutions and air-entraining behavior of cement mortar were studied, and its effect on the microstructure of cement mortar was
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Nanomaterials play a beneficial role in regulating the function of cement-based materials. The effects and mechanism of graphene oxide (GO) on foam behavior in solutions and air-entraining behavior of cement mortar were studied, and its effect on the microstructure of cement mortar was also investigated. The results show that a synergy between GO’s hydrophobicity and the air-entraining agent’s hydrophobic chains drove more agent molecules to adsorb onto the GO surface, subsequently spreading and aggregating across the bubbles. GO effectively assisted the air entraining agent to refine the bubble size, improved the bubble stability of aqueous solutions, and had excellent air entraining performance in the fresh cement mortar, as well as the optimum air-void adjustment performance of hardened cement mortars. With the addition of 0.4‰ GO, the loss rate of gas content in the GO mixed mortar was 10.3%, which was 55.8% lower than that when only using AEA. The addition of 0.4‰ of GO effectively increased the volume fraction of the cement mortar system. GO reduced the pore volume in the mortar through the filling effect and nucleation effect to reduce the total porosity and refine the microstructure of the mortar.
Full article
The dynamic modulus of asphalt mixtures (|E*|) is a key mechanical parameter in the design of road pavements, yet direct laboratory testing is time- and resource-intensive. This study evaluates two predictive models for estimating |E*| using data from 62 asphalt mixtures containing reclaimed
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The dynamic modulus of asphalt mixtures (|E*|) is a key mechanical parameter in the design of road pavements, yet direct laboratory testing is time- and resource-intensive. This study evaluates two predictive models for estimating |E*| using data from 62 asphalt mixtures containing reclaimed asphalt: a grey relational analysis–multiple linear regression (GRA-MLR) hybrid model and a mechanistic sigmoidal model. The results showed that the GRA-MLR model effectively identifies influential variables but achieved moderate predictive accuracy (R2 values varying from 0.4743 to 0.6547). In contrast, the sigmoidal model outperformed across all temperature conditions (R2 > 0.96) and produced predictions deviating by less than ±20% from measured values. Temperature-dependent shifts in factor influence were observed, with stiffness and gradation dominating at low temperatures and reclaimed asphalt (RA) content becoming more significant at higher temperatures. While the GRA-MLR model is advantageous, offering rapid assessments and early-stage evaluations, the sigmoidal model offers the precision suited for detailed design. Integrating both models can balance computational efficiency and provide a balanced strategy, with strong predictive reliability to advance mechanistic–empirical pavement design.
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This study presents a novel and efficient iterative scheme in the setting of CAT(0) spaces and investigates the convergence properties for a generalized class of mappings satisfying the Garcia–Falset property using the proposed iterative scheme. Strong and weak convergence results are established in
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This study presents a novel and efficient iterative scheme in the setting of CAT(0) spaces and investigates the convergence properties for a generalized class of mappings satisfying the Garcia–Falset property using the proposed iterative scheme. Strong and weak convergence results are established in CAT(0) spaces, generalizing many existing results in the literature. Furthermore, we discuss the stability and data dependence of the new iterative process. Numerical experiments include an analysis of error values, the number of iterations, and computational time, providing a comprehensive assessment of the method’s performance. Moreover, graphical comparisons demonstrate the efficiency and reliability of the approach. The obtained results are utilized in solving integral equations. Additionally, the paper concludes with a polynomiographic study of the newly introduced iterative process, in comparison with standard algorithms, such as Newton, Halley, or Kalantari’s iteration, emphasizing symmetry properties.
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Maritime ship detection faces challenges due to complex object poses, variable target scales, and background interference. This paper introduces YOLO-PFA, a novel SAR ship detection model that integrates multi-scale feature fusion and dynamic alignment. By leveraging the Bidirectional Feature Pyramid Network (BiFPN), YOLO-PFA
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Maritime ship detection faces challenges due to complex object poses, variable target scales, and background interference. This paper introduces YOLO-PFA, a novel SAR ship detection model that integrates multi-scale feature fusion and dynamic alignment. By leveraging the Bidirectional Feature Pyramid Network (BiFPN), YOLO-PFA enhances cross-scale weighted feature fusion, improving detection of objects of varying sizes. The C2f-Partial Feature Aggregation (C2f-PFA) module aggregates raw and processed features, enhancing feature extraction efficiency. Furthermore, the Dynamic Alignment Detection Head (DADH) optimizes classification and regression feature interaction, enabling dynamic collaboration. Experimental results on the iVision-MRSSD dataset demonstrate YOLO-PFA’s superiority, achieving an mAP@0.5 of 95%, outperforming YOLOv11 by 1.2% and YOLOv12 by 2.8%. This paper contributes significantly to automated maritime target detection.
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To address the issue of hysteresis nonlinearity adversely affecting the tracking accuracy of piezoelectric actuators, an improved particle swarm optimization (PSO) algorithm is proposed to improve the accuracy of hysteresis model parameter identification. Additionally, a discrete-time linear quadratic optimal tracking (DLQT) control strategy
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To address the issue of hysteresis nonlinearity adversely affecting the tracking accuracy of piezoelectric actuators, an improved particle swarm optimization (PSO) algorithm is proposed to improve the accuracy of hysteresis model parameter identification. Additionally, a discrete-time linear quadratic optimal tracking (DLQT) control strategy incorporating hysteresis compensation is developed to improve tracking performance. This study employs the Hammerstein model to characterize the nonlinear hysteresis behavior of piezoelectric actuators. Regarding parameter identification, the conventional PSO algorithm tends to suffer from premature convergence and being trapped in local optima. To address this, a cross-variation mechanism is introduced to enhance population diversity and improve global search ability. Furthermore, adaptive and dynamically adjustable inertia weights are designed based on evolutionary factors to balance exploration and exploitation, thereby enhancing convergence and identification accuracy. The inertia weights and learning factors are adaptively adjusted based on the evolutionary factor to balance local and global search capabilities and accelerate convergence. Benchmark function tests and model identification experiments demonstrate the improved algorithm’s superior convergence speed and accuracy. In terms of control strategy, a hysteresis compensator based on an asymmetric hysteresis model is designed to improve system linearity. To address the issues of incomplete hysteresis compensation and low tracking accuracy, a DLQT controller is developed based on hysteresis compensation. Hardware-in-the-loop tracking control experiments using single and composite frequency reference signals show that the relative error is below 3.3% in the no-load case and below 4.5% in the loaded case. Compared with the baseline method, the proposed control strategy achieves lower root-mean-square error and maximum steady-state error, demonstrating its effectiveness.
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This study investigates occupant–seat interaction dynamics in high-speed train frontal collisions. A finite element model of a second-class double seat was developed and simulated using LS-DYNA R12.1 software with a Hybrid III dummy, applying trapezoidal and triangular acceleration pulses per European and American
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This study investigates occupant–seat interaction dynamics in high-speed train frontal collisions. A finite element model of a second-class double seat was developed and simulated using LS-DYNA R12.1 software with a Hybrid III dummy, applying trapezoidal and triangular acceleration pulses per European and American standards. The research analyzes the impact of front-row seatback recline angles (0°, 10°, 20°) and seatback-to-base connection stiffness (1000 N/mm to 0 N/mm) on head, neck, chest, and leg injury severity. Results show that a 10° recline provides optimal protection under fixed stiffness. When optimizing both parameters, a 0° recline with approximately 300 N/mm stiffness minimizes composite injury metrics (HIC15, Nij, CTI). However, reducing stiffness at non-zero recline angles increases neck injury risk due to tray table displacement toward the cervical region. These findings emphasize the critical importance of integrated seat design optimization for rail passenger passive safety and highlight the need to mitigate tray table hazards.
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Total internal reflection fluorescence (TIRF) microscopy excites fluorophores within a few hundred nanometers of the sample–substrate interface, enabling high-contrast imaging near the cell membrane. When cultured cells differentiate, the membrane in contact with the coverslip generally acquires basal characteristics, while the opposite membrane
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Total internal reflection fluorescence (TIRF) microscopy excites fluorophores within a few hundred nanometers of the sample–substrate interface, enabling high-contrast imaging near the cell membrane. When cultured cells differentiate, the membrane in contact with the coverslip generally acquires basal characteristics, while the opposite membrane develops apical features. Consequently, conventional TIRF microscopy is limited to imaging the basal surface. We developed an immersed-prism TIRF (IP-TIRF) microscope, in which a prism immersed in the culture medium generates TIR at the cell/medium–prism interface, illuminating the apical membrane and reducing cytosolic background. In proof-of-principle experiments, we imaged fluorescent beads and 3xmNeonGreen-tagged intraflagellar transport (IFT) particles in cilia, and compared the performance with confocal microscopy. In cellular regions where both methods can be applied (such as the IFT base pool), on average, IP-TIRF achieved approximately 1.8 times the contrast-to-noise ratio (CNR~31) compared to confocal microscopy. Furthermore, IFT-particle motion was detected in IP-TIRF image sequences and Kymographs of cilia, with adequate spatial resolution. Kymograph analysis revealed an average anterograde IFT velocity of 0.156 ± 0.071 µm/s and an average retrograde velocity of 0.020 ± 0.007 µm/s, approximately one-quarter and one-twentieth, respectively, of the values reported for mammalian primary cilia, which we attribute to acquisition at room temperature rather than physiological conditions. Therefore, these velocity measurements should be regarded as proof-of-principle demonstrations obtained at room temperature, not as validated physiological transport rates. Our IP-TIRF method provides a high-resolution, cost-effective, and broadly accessible approach for imaging the apical membrane in live cells.
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Background: The treatment of wounds remains a significant clinical challenge, particularly in chronic and infected wounds, where delayed healing often results in complications. Recent advances in biomaterials have highlighted the potential of polymer-based scaffolds as promising platforms for wound management due to their
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Background: The treatment of wounds remains a significant clinical challenge, particularly in chronic and infected wounds, where delayed healing often results in complications. Recent advances in biomaterials have highlighted the potential of polymer-based scaffolds as promising platforms for wound management due to their ability to mimic the extracellular matrix, support tissue regeneration, and provide a moist environment conducive to healing. Objectives: This review aims to provide a comprehensive overview of the recent progress in the design and application of polymer-based scaffolds loaded with essential oil (EO) components, emphasizing their role in promoting effective wound healing. Methods: Relevant literature on polymeric scaffolds and EO-based bioactive agents was systematically reviewed, focusing on studies that investigated the biological activities, fabrication techniques, and therapeutic performance of EO-loaded scaffolds in wound management. Results: Findings from recent studies indicate that EO components, particularly monoterpenoids such as thymol, carvacrol, and eugenol, exhibit remarkable antimicrobial, anti-inflammatory, antioxidant, and analgesic properties that accelerate wound healing. When incorporated into polymer matrices, these components enhance scaffold biocompatibility, antimicrobial efficacy, and tissue regeneration capacity through synergistic interactions. Conclusion: The integration of essential oil components into polymeric scaffolds represents a promising strategy for developing multifunctional wound dressings. Such systems combine the structural advantages of polymers with the therapeutic benefits of EOs, offering an effective platform for accelerating healing and preventing wound infections.
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Virgínia Rayanne Soares de Souza, Camila Ferreira Alves, Larissa Felix de Lucena, Luana Caroline Costa Silva, Everthon de Albuquerque Xavier, Cláudio José Galdino da Silva Jr., Attilio Converti, Renata Laranjeiras Gouveia and Leonie Asfora Sarubbo
Coatings2025, 15(10), 1185; https://doi.org/10.3390/coatings15101185 (registering DOI) - 9 Oct 2025
Biofouling is the colonization and attachment of sessile organisms on submerged surfaces, whether natural or artificial. The presence of these communities compromises the structural integrity, operational efficiency, and durability of coastal structures, resulting in high economic and environmental costs, especially when conventional removal
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Biofouling is the colonization and attachment of sessile organisms on submerged surfaces, whether natural or artificial. The presence of these communities compromises the structural integrity, operational efficiency, and durability of coastal structures, resulting in high economic and environmental costs, especially when conventional removal methods involve the use of toxic biocides. In this context, this article aimed to evaluate the scientific productivity of the literature related to sustainable antifouling strategies, with an emphasis on technologically and environmentally sustainable solutions, through a bibliometric analysis. We analyzed 160 research articles and 90 patents published between 2004 and 2024. It was observed that, since 2019, there has been an increase in publications about biofouling solutions, with a notable emphasis on China’s leadership in both scientific production and patent filings. This topic has also attracted extensive international collaboration. The most promising strategies for controlling marine biofouling involve a combination of physical, chemical, and biological methods, integrated with sustainable coatings. The growing demand for low-environmental-impact solutions has driven the development of safer, more effective, and economically viable antifouling technologies. Therefore, the integration of traditional techniques with advances in biotechnology represents a strategic path to mitigating the impacts of biofouling in marine environments.
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Marco Pensabene, Benedetto Spataro, Fabio Baldanza, Francesco Grasso, Gregorio Serra, Veronica Notarbartolo, Mario Giuffrè, Giovanni Corsello, Elisa Zambaiti, Maria Rita Di Pace and Maria Sergio
Children2025, 12(10), 1363; https://doi.org/10.3390/children12101363 (registering DOI) - 9 Oct 2025
Background and Objectives: Primary vesicoureteral reflux (VUR) is a common pediatric urological disorder that can lead to significant renal morbidity if undetected or improperly managed. Ultrasound (US) plays a pivotal role in its assessment, providing a radiation-free tool to prenatal assessment, diagnosis, treatment,
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Background and Objectives: Primary vesicoureteral reflux (VUR) is a common pediatric urological disorder that can lead to significant renal morbidity if undetected or improperly managed. Ultrasound (US) plays a pivotal role in its assessment, providing a radiation-free tool to prenatal assessment, diagnosis, treatment, and long-term follow-up. This study aims to systematically review the literature on the use of US in pediatric primary VUR, emphasizing its applications in prenatal and postnatal diagnosis, intraoperative guidance, and follow-up monitoring. Methods: A systematic review of the literature was performed on PubMed in accordance with PRISMA guidelines. The research strategy used the following keywords: Ultrasound Vesicoureteral reflux, VUR Ultrasound, and VUR Sonography. A total of 2222 records were initially identified. After screening titles and abstracts for relevance, 2165 studies were excluded because they did not focus on ultrasound procedures, did not specify age limits, were redundant, involved non-homogeneous populations, or were unavailable in full text. Results: Prenatal US enables early identification of urinary tract anomalies suggestive of VUR, facilitating targeted postnatal evaluation. Postnatally, contrast-enhanced voiding ultrasound (CEVUS) offers a non-ionizing method for VUR confirmation or exclusion. Intraoperatively, US improves the accuracy and efficacy of bulking agent placement, potentially enhancing surgical outcomes. In follow-up, US remains essential for both conservatively managed and surgically treated patients, enabling timely detection of complications or recurrence. Conclusions: Ultrasound represents a useful tool in the management of pediatric primary VUR, applicable across all clinical stages, avoiding radiation exposure, and improving surgical effectiveness and follow-up management.
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With the rapid economic and social development and the increasingly severe water shortage situation, the sustainable utilization of unconventional water resources is of great significance. As one of the “second water sources”, the full utilization of highly mineralized mine water (HMMW) is a
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With the rapid economic and social development and the increasingly severe water shortage situation, the sustainable utilization of unconventional water resources is of great significance. As one of the “second water sources”, the full utilization of highly mineralized mine water (HMMW) is a key strategy for promoting sustainable development in water-scarce regions. It has obvious resource, environmental, and economic benefits that are central to sustainability. However, the mechanism of the impact of HMMW utilization on water utilization, the environment, and the economy is still unclear, making it difficult to evaluate its overall sustainability performance and to provide scientific data support to promote HMMW utilization. Therefore, this paper develops a novel sustainability-oriented accounting framework to assess the environmental–economic sustainability of HMMW utilization. Firstly, this paper proposes the method of calculating the HMMW utilization environmental benefits, proposes a novel integrated environmental–economic input–output accounting framework, which refines the HMMW sector from the traditional water industry and integrates the environmental benefits into a balanced input–output table. Secondly, taking Ningdong Energy Chemical Industry Base (NECI Base) as an example, this paper conducts applied research on the integrated environmental–economic accounting of HMMW utilization: (I) The HMMW environmental benefits of NECI Base are calculated, the utilization of 22.69 million m3 of HMMW generated environmental benefits, valued at 233.69 million CNY, demonstrating its substantial contribution to environmental sustainability. The compiled environmental–economic input–output table passed the balance verification, confirming the robustness and practicality of the accounting method.
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With the global deceleration of urbanization, traditional regeneration strategies centered on demolition and reconstruction have revealed substantial limitations. Against this backdrop, land-use transformation has emerged as a more cost-effective and less disruptive alternative. Focusing on Chengdu, China, this study employs a causal machine
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With the global deceleration of urbanization, traditional regeneration strategies centered on demolition and reconstruction have revealed substantial limitations. Against this backdrop, land-use transformation has emerged as a more cost-effective and less disruptive alternative. Focusing on Chengdu, China, this study employs a causal machine learning framework to rigorously assess the impacts of residential-to-commercial and industrial-to-commercial conversions on urban vitality. The findings demonstrate that population density consistently constitutes the fundamental driver across both transformation pathways. Residential-to-commercial conversion reflects a regeneration trajectory that integrates residential and commercial functions while prioritizing community livability, whereas industrial-to-commercial conversion entails large-scale spatial restructuring and enhanced accessibility. Overall, the study uncovers the heterogeneous causal effects of land-use transformation on urban vitality, thereby providing a theoretical basis to inform differentiated and sustainable urban regeneration policies.
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There has been a recent shift in the global wine market towards reduced-alcohol wines. Muscadine grapes (Vitis rotundifolia) have become a popular choice in many emerging markets; however, their suitability in reduced-alcohol wine production has not been extensively tested. In this
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There has been a recent shift in the global wine market towards reduced-alcohol wines. Muscadine grapes (Vitis rotundifolia) have become a popular choice in many emerging markets; however, their suitability in reduced-alcohol wine production has not been extensively tested. In this study, methods to reduce ethanol in muscadine wine were compared to determine differences in chemical and sensory attributes and consumer preference. The methods evaluated included full fermentation time with Saccharomyces cerevisiae (control), reduced fermentation time with Saccharomyces cerevisiae (stopped fermentation), fermentation with Saccharomycodes ludwigii yeast (instead of Saccharomyces cerevisiae), and vacuum distillation. The control and distilled wines were fermented for 121 h, Saccharomycodes ludwigii for 45 h, and the stopped fermentation wine for 3 h. Yeast and sugar levels were monitored throughout the fermentation processes using brix measurements and yeast counts. After the fermentation, the color, pH, volatiles, and titratable acidity (TA) were measured. The results showed that Saccharomycodes ludwigii fermented more slowly than Saccharomyces cerevisiae, and that both the stopped fermentation and Saccharomycodes ludwigii wines had lower titratable acidity with a more intense color. The total concentration of volatile compounds for the Saccharomycodes ludwigii wine and the stopped wine were lower than for the distilled and control wines. A consumer panel (n = 92) judged the wine samples on chemical qualities and overall preference. The distilled wine was perceived as more alcoholic compared to the other reduced-alcohol wines. The results showed that the stopped fermentation and Saccharomycodes ludwigii wines were preferred by consumers over the control and vacuum-distilled wines.
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Defect detection in textile manufacturing is critically hampered by the inefficiency of manual inspection and the dual constraints of deep learning (DL) approaches. Specifically, DL models suffer from poor generalization, as the rapid iteration of fabric types makes acquiring sufficient training data impractical.
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Defect detection in textile manufacturing is critically hampered by the inefficiency of manual inspection and the dual constraints of deep learning (DL) approaches. Specifically, DL models suffer from poor generalization, as the rapid iteration of fabric types makes acquiring sufficient training data impractical. Furthermore, their high computational costs impede real-time industrial deployment. To address these challenges, this paper proposes a texture-adaptive fabric defect detection method. Our approach begins with a Dynamic Subspace Feature Extraction (DSFE) technique to extract spatial luminance features of the fabric. Subsequently, a Light Field Offset-Aware Reconstruction Model (LFOA) is introduced to reconstruct the luminance distribution, effectively compensating for environmental lighting variations. Finally, we develop a texture-adaptive defect detection system to identify potential defective regions, alongside a probabilistic ‘OutlierIndex’ to quantify their likelihood of being true defects. This system is engineered to rapidly adapt to new fabric types with a small number of labeled samples, demonstrating strong generalization and suitability for dynamic industrial conditions. Experimental validation confirms that our method achieves 70.74% accuracy, decisively outperforming existing models by over 30%.
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Background: Inflammation of unknown origin (IUO) represents a persistent clinical challenge, often requiring extensive diagnostic efforts despite nonspecific inflammatory findings such as elevated C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR). The complexity and heterogeneity of its etiologies—including infections, malignancies, and rheumatologic diseases—make
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Background: Inflammation of unknown origin (IUO) represents a persistent clinical challenge, often requiring extensive diagnostic efforts despite nonspecific inflammatory findings such as elevated C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR). The complexity and heterogeneity of its etiologies—including infections, malignancies, and rheumatologic diseases—make timely and accurate diagnosis essential to avoid unnecessary interventions or treatment delays. Objective: This study aimed to evaluate the potential of machine learning (ML)-based models in distinguishing the major etiologic subgroups of IUO and to explore their value as clinical decision support tools. Methods: We retrospectively analyzed 300 IUO patients hospitalized between January 2023 and December 2024. Four binary one-vs-rest Linear Discriminant Analysis (LDA) models were first developed to independently classify infection, malignancy, rheumatologic disease, and undiagnosed cases using clinical and laboratory parameters. In addition, a multiclass LDA framework was constructed to simultaneously differentiate all four diagnostic groups. Each model was evaluated across 10 independent runs using standard performance metrics, including accuracy, sensitivity, specificity, precision, F1 score, and negative predictive value (NPV). Results: The malignancy model achieved the highest performance, with an accuracy of 91.7% and specificity of 0.96. The infection model demonstrated high specificity (0.88) and NPV (0.86), supporting its role in ruling out infection despite lower sensitivity (0.71). The rheumatologic model showed high sensitivity (0.81) but lower specificity (0.73), reflecting the clinical heterogeneity of autoimmune conditions. The undiagnosed model achieved very high accuracy (96.7%) and specificity (0.98) but limited precision and recall (0.50 each). The multiclass LDA framework reached an overall accuracy of 73.3% (mean 66%) with robust specificity (0.90) and NPV (0.89). Conclusions: ML-based LDA models demonstrated strong potential to support the diagnostic evaluation of IUO. While malignancy and infection could be predicted with high accuracy, rheumatologic diseases required integration of additional serological and clinical data. These models should be viewed not as stand-alone diagnostic tools but as complementary decision-support systems. Prospective multicenter studies are warranted to externally validate and refine these approaches for broader clinical application.
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Pedro Henrique Gomes de Sá Santos, Gabriel da Silva Oliveira, Liz de Albuquerque Cerqueira, José Luiz de Paula Rôlo Jivago, Susana Suely Rodrigues Milhomem Paixão, Márcio Botelho de Castro, Concepta McManus and Vinícius Machado dos Santos
Toxics2025, 13(10), 851; https://doi.org/10.3390/toxics13100851 (registering DOI) - 9 Oct 2025
Previous studies have linked formaldehyde (FA) fumigation to significant risks to animal health, highlighting, among other effects, its cytotoxic and genotoxic potential. Literature includes several studies on the use of FA for fumigating hatching eggs, but studies employing in-depth methodological approaches are scarce.
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Previous studies have linked formaldehyde (FA) fumigation to significant risks to animal health, highlighting, among other effects, its cytotoxic and genotoxic potential. Literature includes several studies on the use of FA for fumigating hatching eggs, but studies employing in-depth methodological approaches are scarce. As a result, the effects of practices involving this chemical remain insufficiently characterized. The present study aimed to investigate the antibacterial effects and potential toxicity resulting from the fumigation of hatching eggs with FA. The three FA concentrations (2.5, 5, and 10 g/m3) exhibit effective antibacterial activity, but this effect does not translate into long-term benefits. FA affected hatchability and demonstrated embryotoxic effects, with repercussions on chicks depending on the concentration used. The overall quality of poultry and the losses from eggs fumigated with FA remain questionable. Despite its efficacy as an egg fumigant, the observed toxicity suggests that its use violates safety standards and should be reconsidered. If its use cannot be avoided, the lowest possible concentrations should be prioritized to minimize toxic effects.
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As the core space for students’ daily living and learning, the quality of the indoor wind environment and air quality in dormitory buildings is particularly critical. However, existing studies often neglect natural ventilation optimization under local climatic conditions and the multidimensional evaluation of
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As the core space for students’ daily living and learning, the quality of the indoor wind environment and air quality in dormitory buildings is particularly critical. However, existing studies often neglect natural ventilation optimization under local climatic conditions and the multidimensional evaluation of health benefits, leaving notable gaps in dormitory design. Under the Healthy China Initiative, the indoor wind environment in university dormitories directly impacts students’ health and learning efficiency. This study selects dormitory buildings in Xuzhou as the research object and employs ANSYS FLUENT 2020 software for computational fluid dynamics (CFD) simulations, combined with orthogonal experimental design methods, to systematically investigate and optimize the indoor wind environment with a focus on healthy ventilation standards. The evaluation focused on three key metrics—comfortable wind speed ratio, air age, and CO2 concentration—considering the effects of building orientation, corridor width, and window geometry, and identifying the optimal parameter combination. After optimization based on the orthogonal experimental design, the proportion of comfortable wind speed zones increased to 44.6%, the mean air age decreased to 258 s, and CO2 concentration stabilized at 613 ppm. These results demonstrate that the proposed optimization framework can effectively enhance indoor air renewal and pollutant removal, thereby improving both air quality and the health-related performance of dormitory spaces. The novelty of this study lies in integrating regional climate conditions with a coordinated CFD–orthogonal design approach. This enables precise optimization of dormitory ventilation performance and provides locally tailored, actionable evidence for advancing healthy campus design.
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Serena Sophia Rudy, Jorge Jimenez-Canale, Jose A. Sarabia-Sainz, Ana María Guzmán Partida, Alexel J. Burgara-Estrella, Erika Silva-Campa, Aracely Angulo Molina, Marcelino Montiel-Herrera, Nelly Flores-Ramírez, Paul Zavala-Rivera and Daniel Fernández-Quiroz
Nanomaterials2025, 15(19), 1538; https://doi.org/10.3390/nano15191538 (registering DOI) - 9 Oct 2025
The development of snake venom-loaded nanobiosystems based on smart biopolymers represents a promising therapeutic approach in several biomedical research fields. Specifically, the western diamondback rattlesnake (Crotalus atrox) contains various bioactive peptides and proteins with reported antitumor activity. This research aimed to
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The development of snake venom-loaded nanobiosystems based on smart biopolymers represents a promising therapeutic approach in several biomedical research fields. Specifically, the western diamondback rattlesnake (Crotalus atrox) contains various bioactive peptides and proteins with reported antitumor activity. This research aimed to establish a simplistic, facile and straightforward protocol for preparing chitosan-g-poly(N-vinylcaprolactam) nanoparticles containing C. atrox venom for potential use as a therapeutic nanocarrier against breast carcinoma cell lines. Herein, the physicochemical properties of venom-loaded nanoparticles were evaluated by FTIR, DLS, and SDS-PAGE. Also, the biological properties of both C. atrox venom and Cs-Venom NPs such as hemagglutination and hemolysis activity were evaluated in vitro. Finally, we evaluated their cytotoxic activity against two breast carcinoma cell lines (T-47D and MDA-MB-231). The most suitable formulation exhibited a hydrodynamic size of 222 nm, a ζ-potential of 42.0 mV and an encapsulation efficiency of 88.6%. C. atrox venom exhibited hemagglutination at concentrations >15 µg/mL but, no hemagglutination or hemolysis was observed for the CS-Venom NPs. Lastly, the IC50 of Cs-Venom NPs was determined for the T-47D and MDA-MB-231 cell lines, at 61.7 and 59.0 µg/mL, respectively. Thus, Cs-Venom NPs exhibit promising properties that can be considered a feasible alternative for developing controlled-release therapeutic systems.
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Monoacylglycerol lipase (MAGL) is a key serine hydrolase involved in lipid metabolism, catalyzing the hydrolysis of monoacylglycerols into free fatty acids and glycerol. MAGL plays a central role in regulating endocannabinoid signaling and lipid homeostasis, processes often dysregulated in cancer and other pathological
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Monoacylglycerol lipase (MAGL) is a key serine hydrolase involved in lipid metabolism, catalyzing the hydrolysis of monoacylglycerols into free fatty acids and glycerol. MAGL plays a central role in regulating endocannabinoid signaling and lipid homeostasis, processes often dysregulated in cancer and other pathological conditions. In recent years, MAGL has emerged as a promising therapeutic target, particularly in oncology, where its inhibition has shown potential to impair tumor growth, metastasis, and inflammation-driven processes. Alongside the development of selective MAGL inhibitors, several biochemical methods have been established to measure MAGL enzymatic activity, providing essential tools for target validation and inhibitor characterization. In this review, we provide a comprehensive and critical overview of the main approaches developed for MAGL activity evaluation, including radiometric, chromatographic, colorimetric, fluorescence-based, bioluminescence-based, and activity-based protein profiling (ABPP) assays. For each method, we discuss principles, advantages, and limitations. This review aims to support researchers in the selection of the most appropriate assay strategy for their experimental needs, ultimately fostering the rapid and accurate development of novel MAGL inhibitors with potential applications in cancer therapy and metabolic disease management.
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Animal-based measures, such as detecting inflammation in areas like the tail, ears, teats, coronary band, heels and claws (Swine Inflammation and Necrosis Syndrome, SINS), are used to monitor animal health and welfare. When parameters deviate from the established range, these measures enable prompt
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Animal-based measures, such as detecting inflammation in areas like the tail, ears, teats, coronary band, heels and claws (Swine Inflammation and Necrosis Syndrome, SINS), are used to monitor animal health and welfare. When parameters deviate from the established range, these measures enable prompt action to adjust husbandry practices, feeding regimens and management strategies. In addition to environmental factors, genetics have been shown to play a key role in inflammation and necrosis processes, and selection can reduce the severity of the disease. This study examined whether different breeds of AI boar exhibit different signs of SINS and how these signs are associated with SINS in their offspring when they are suckling piglets and weaners. Initially, 286 AI boars of 7 breeds from a German artificial insemination center were evaluated for SINS. The following parameters were assessed: tail base, tail tip, ears, skin, scrotum, coronary bands, heels and claws. Subsequently, 23 Pietrain and Duroc boars were used in combination with a Topigs DL sow line. The progeny of the AI boars was evaluated as suckling and weaned piglets, with the assessment framework encompassing SINS traits. The results revealed significant differences between the breeds and lines, as well as a strong correlation between the SINS phenotypes of the AI boars and the SINS scores of their offspring. The offspring of the 25% most extreme boars exhibited a 17% variation in SINS scores. This association was particularly evident when comparing the boars’ tail base. However, the development of the boars’ heels and claws was found to be significantly influenced by mechanical environmental factors and not associated with the piglets’ scores. These findings imply that heritable, endogenous processes, as proposed for SINS, also visibly impact the phenotype of the AI boar. This study’s fundamental premise suggests that pre-selecting AI boars could mitigate the occurrence of SINS and enhance piglet health and welfare.
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High-entropy boride (HEB) ceramics combine ultra-high melting points, superior hardness, and compositional tunability, enabling service in extreme environments; however, difficult densification and limited fracture toughness still constrain their aerospace applications. In this study, metallic Ta was introduced into high-entropy (Ti0.2Zr0.2 [...] Read more.
High-entropy boride (HEB) ceramics combine ultra-high melting points, superior hardness, and compositional tunability, enabling service in extreme environments; however, difficult densification and limited fracture toughness still constrain their aerospace applications. In this study, metallic Ta was introduced into high-entropy (Ti0.2Zr0.2Hf0.2Nb0.2Ta0.2)B2 as both a sintering aid and a toughening phase. Bulk HEB-Ta composites were fabricated by spark plasma sintering to investigate the effect of Ta content on densification behavior, microstructure, mechanical properties, and high-temperature oxidation resistance. The results show that an appropriate amount of Ta markedly promotes densification; at 10 vol% Ta, the open porosity reaches a minimum of 0.15%. Hardness and fracture toughness exhibit an increase-then-decrease trend with Ta content, attaining maxima at 15 vol% Ta (20.79 ± 0.17 GPa and 4.31 ± 0.12 MPa·, respectively). During oxidation at 800–1400 °C, the extent of oxidation increases with temperature, yet the composite with 10 vol% Ta shows the best oxidation resistance. This improvement arises from the formation of a viscous, protective Ta2O5-B2O3 glassy layer that effectively suppresses oxygen diffusion and enhances high-temperature stability. Overall, incorporating metallic Ta is an effective route to improve the manufacturability and service durability of HEB ceramics, providing a composition guideline and a mechanistic basis for simultaneously enhancing densification, toughness, and oxidation resistance.
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Viral metagenomic next-generation sequencing (vmNGS) has transformed our capacity for the untargeted detection and characterisation of (re)emerging zoonotic viruses, surpassing the limitations of traditional targeted diagnostics. In this review, we critically evaluate the current landscape of vmNGS, highlighting its integration within the One
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Viral metagenomic next-generation sequencing (vmNGS) has transformed our capacity for the untargeted detection and characterisation of (re)emerging zoonotic viruses, surpassing the limitations of traditional targeted diagnostics. In this review, we critically evaluate the current landscape of vmNGS, highlighting its integration within the One Health paradigm and its application to the surveillance and discovery of (re)emerging viruses at the human–animal–environment interface. We provide a detailed overview of vmNGS workflows including sample selection, nucleic acid extraction, host depletion, virus enrichment, sequencing platforms, and bioinformatic pipelines, all tailored to maximise sensitivity and specificity for diverse sample types. Through selected case studies, including SARS-CoV-2, mpox, Zika virus, and a novel henipavirus, we illustrate the impact of vmNGS in outbreak detection, genomic surveillance, molecular epidemiology, and the development of diagnostics and vaccines. The review further examines the relative strengths and limitations of vmNGS in both passive and active surveillance, addressing barriers such as cost, infrastructure requirements, and the need for interdisciplinary collaboration. By integrating molecular, ecological, and public health perspectives, vmNGS stands as a central tool for early warning, comprehensive monitoring, and informed intervention against (re)emerging viral threats, underscoring its critical role in global pandemic preparedness and zoonotic disease control.
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Background: The Healthy Japan 21-Phase III dietary recommendations comprise a staple food, main dish, and side dish to maintain nutritional balance and support healthy child growth. The relationship between the frequency of such balanced meals and early adiposity rebound (AR), a predictor of
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Background: The Healthy Japan 21-Phase III dietary recommendations comprise a staple food, main dish, and side dish to maintain nutritional balance and support healthy child growth. The relationship between the frequency of such balanced meals and early adiposity rebound (AR), a predictor of obesity, remains unclear. Objective: This study aimed to examine the association between the frequency of balanced meals (staple food, main dish, and side dish) and early AR in preschool children. Methods: In this cross-sectional secondary analysis of nationwide online survey data of 688 mothers of children aged 3–6 years, dietary habits were assessed using a validated NutriSTEP-based 22-item Japanese Nutrition Screening Questionnaire. AR constituted a body mass index (BMI) increase from the 18- to 36-month health checkups recorded in the Maternal and Child Health Handbook. Risk scores reflecting lower frequency of balanced meals were calculated for staple foods, main dishes, and side dishes. Logistic regression evaluated associations between dietary risk scores and AR, adjusting for the child’s sex, age, gestational age, birth weight, daycare attendance, and parental obesity. Results: Among 688 children, 193 (28.1%) exhibited early AR and had significantly higher BMI at age 3 and the most recent measurement (both p < 0.01). A higher total dietary risk score was independently associated with AR (adjusted odds ratio; 2.58 [95% CI: 1.08–6.16]). In addition, the absolute risk difference between high- and low-risk groups was 8.5% (95% CI: 1.7–15.2%). Conclusions: A lower frequency of balanced meals is associated with early AR. These findings suggest that a simple, meal-balance screening tool could potentially aid in the early identification of the risk of later obesity and timely nutritional guidance.
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