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Fermentation of mulberry juice not only improves its shelf life, but also effectively enhances their flavor and nutritional quality. This study elucidated the phytochemical and flavor characteristics of mulberry juice fermented with Lactiplantibacillus plantarum BXM2, originally isolated from naturally fermented fruit beverage, through widely targeted metabolomics. The fermentation produced the unique flavor of fermented juice and decreased the pH from 4.15 to 3.19. The metabolomic analysis detected 907 non-volatile metabolites, from which 359 significantly different non-volatile metabolites (up 238, down 121) were screened out. Among 731 identified volatile metabolites, 26 flavor substances were the major contributors to the flavor differences between fermented and unfermented mulberry juices. It is hypothesized that lipid metabolism and amino acid catabolism are crucial pathways for the flavor enhancement of mulberry juice fermented with L. plantarum BXM2. Meanwhile, significant increases of the contents of a variety of bioactive substances, such as indole-3-lactic acid, octadeca-9,12,15-trienoic acid, di-/tri-peptides, etc., conferred additional health potential to BXM2-fermented mulberry juice. [ABSTRACT FROM AUTHOR]

Lifts, or elevators, are transportation facilities that are indispensable for countless end users in high-rise buildings. They require proper maintenance to ensure safe operation. In addition to technological applications, effective management and legislative controls play a crucial role in ensuring lift safety. Given the limited understanding of an optimal regulatory model for governing lift maintenance, a cross-discipline comparative study was conducted to examine lift maintenance regulations in regions with different legal systems. Following a systematic and comparative review approach, this study focused on regulatory controls across civil and common law jurisdictions, specifically Beijing, Hong Kong, and London. Relevant statutes and publications were searched from engineering, law and management databases, which included Scopus, JSTOR, Lexis+, Lexis China, Lexis Advance Hong Kong, and Westlaw Asia. Through scrutinizing the retrieved documents, key features of the regulations were identified and compared in terms of lift classifications, types and frequencies of mandatory maintenance works, qualifications for authorized parties, and legal liabilities for non-compliance. Validated by industry experts, the results reveal both similarities and differences in the regulations among the three jurisdictions. While these findings serve as valuable references for policymakers in formulating optimal legislative controls to enhance lift safety in the future, further research could expand the scope of this study to examine the regulations in other regions and investigate the effectiveness of existing statutory controls on lift maintenance. [ABSTRACT FROM AUTHOR]

Zika virus (ZIKV) and Japanese encephalitis virus (JEV) can cause permanent neurological damage and death, yet no approved drugs exist for these infections. Rhodiola crenulate, an herb used in traditional Chinese medicine for its antioxidation and antifatigue properties, was studied for its antiviral activity against ZIKV and JEV in vitro. The cytotoxicity of Rhodiola crenulata extract (RCE) was evaluated using the CCK-8 reagent. Antiviral effects of RCE were assessed in ZIKV-infected or JEV-infected Vero cells via quantitative reverse transcription polymerase chain reaction (qRT-PCR), Western blotting, fluorescent focus assay (FFA), and immunofluorescence assay (IFA). The cell-free antiviral effects of RCE were evaluated using an inactivation assay. To determine the stage of the viral life cycle affected by RCE, time-of-addition, binding, and entry assays were conducted. Three bioactive constituents of RCE (salidroside, tyrosol, and gallic acid) were tested for antiviral activity. RCE exhibited dose-dependent anti-ZIKV and anti-JEV activities at non-cytotoxic concentrations, which were likely achieved by disrupting viral binding and stability. Gallic acid exhibited antiviral activity against ZIKV and JEV. Our findings indicate that RCE disrupts viral binding and stability, presenting a potential strategy to treat ZIKV and JEV infections. [ABSTRACT FROM AUTHOR]

The bioactivity of tea polysaccharides (TPs) has been widely reported, but studies to date have focused on green tea. Some human health investigations have implied that black tea may possess potential antidiabetic effects, but less is known about their potential role and related antidiabetic mechanism. The present study was, therefore, conducted to investigate the chemical properties and antidiabetic activity of TPs from black tea. Monosaccharide composition revealed that Alduronic acid (77.8 mol%) considerably predominated in the fraction. TP conformation analysis indicated that three components in TPs were all typical of high-branching structures. Oral administration of TPs could effectively alleviate fasting blood glucose in type 2 diabetes mellitus (T2D) mice, with the values 23.6 ± 1.42, 19.6 ± 2.25, and 16.4 ± 2.07 mmol/L in the 200, 400, and 800 mg/kg·BW groups, respectively. Among these TPs groups, the 800 mg/kg·BW groups significantly decreased by 37.88% when compared with the T2D+water group (p < 0.05). Further studies demonstrated that TP treatment upregulated the expression of p-Akt/p-PI3K (p < 0.001). Additionally, TP treatment significantly promoted glucose transporter protein 2 (GLUT2) translocation in the liver (p < 0.001). These findings suggest that TPs from black tea protect against T2D by activating PI3K/Akt/GLUT2 signaling and might serve as a novel therapeutic candidate for T2D. [ABSTRACT FROM AUTHOR]

With the increasing number of electric vehicles (EVs), their uncoordinated charging poses a great challenge to the safe operation of the power grid. In addition, traditional individual-EV scheduling models may be difficult to solve due to the increasing number of constraints. Therefore, this paper proposes a cluster-based EV scheduling model. Firstly, electric vehicle clusters (EVCs) are formed based on the charging and discharging preferences of EV users and the expected time for EVs to leave. Secondly, the EVC energy and power boundary aggregation method based on the Minkowski addition algorithm is proposed. Finally, for the sake of reducing user charging cost and distribution network energy loss, and smoothing the daily load curve, an EVC scheduling model for EV participation in grid auxiliary services is proposed. The optimization model includes the reactive-power compensation of EV charging piles. The simulation results show that the proposed EVC scheduling model can greatly reduce the solution time compared to traditional individual-EV scheduling model. The model has high potential to be applied to large-scale EV scheduling. The reactive-power compensation provided by EV charging piles improves the voltage quality of the grid and enables more EVs to be connected to the grid. [ABSTRACT FROM AUTHOR]

Human action recognition (HAR) is a critical area in computer vision with wide-ranging applications, including video surveillance, healthcare monitoring, and abnormal behavior detection. Current HAR methods predominantly rely on full-body data, which can limit their effectiveness in real-world scenarios where occlusion is common. In such situations, the face often remains visible, providing valuable cues for action recognition. This paper introduces Face in Action (FIA), a novel two-stream method that leverages facial action cues for robust action recognition under conditions of significant occlusion. FIA consists of an RGB stream and a landmark stream. The RGB stream processes facial image sequences using a fine-spatio-multitemporal (FSM) 3D convolution module, which employs smaller spatial receptive fields to capture detailed local facial movements and larger temporal receptive fields to model broader temporal dynamics. The landmark stream processes facial landmark sequences using a normalized temporal attention (NTA) module within an NTA-GCN block, enhancing the detection of key facial frames and improving overall recognition accuracy. We validate the effectiveness of FIA using the NTU RGB+D and NTU RGB+D 120 datasets, focusing on action categories related to medical conditions. Our experiments demonstrate that FIA significantly outperforms existing methods in scenarios with extensive occlusion, highlighting its potential for practical applications in surveillance and healthcare settings. [ABSTRACT FROM AUTHOR]

The high prevalence of catheter-associated urinary tract infections (CAUTIs) is causing significant concern in healthcare systems. Antibacterial urinary catheters have been developed to prevent CAUTIs in clinical application. In this work, a copper sulfide nanorod (CuS NR)-embedded urinary catheter (CuS/UC) was designed as an antibacterial urinary catheter with photothermal sterilization. The CuS NRs with low cytotoxicity were synthesized via the hydrothermal method. The CuS NRs were embedded into urinary catheters at different weight percentages. The CuS/UC exhibited homogenous surface roughness, low wettability, hydrophobicity, and low adhesiveness, promoting minimal interaction with bacteria and healthy cells. Under near-infrared (NIR) laser irradiation, the 0.8 weight percentage of CuS NRs in the urinary catheter (0.8CuS/UC) reached a temperature of 67.4 °C, demonstrating its photothermal antibacterial activity and suitability for catheter sterilization. Agar plate test verified that CuS/UCs exhibited a superior photothermal antibacterial activity against both Gram-negative Escherichia coli (E. coli) and Gram-positive Streptococcus aureus (S. aureus). Moreover, the 0.8CuS/UC exhibited excellent biocompatibility and anti-cell adhesion properties. The 0.8CuS/UC with photothermal performance, excellent biocompatibility, and anti-cell adhesion properties demonstrated its potential as a photothermal antibacterial catheter for clinical applications. [ABSTRACT FROM AUTHOR]

Carbon/carbon (C/C) composite materials are widely used in aerospace, the military and nuclear energy. The outstanding mechanical qualities of C/C composites mean that they are difficult to crush and recycle using traditional technology. The current recycling methods primarily involve stacking and landfill disposal. Therefore, achieving efficient and environmentally friendly recycling of carbon/carbon (C/C) composites is an urgent and challenging issue. In this work, we reported a simple high-value recycling approach for carbon–carbon frictional composite material (CFCM). The solid-state shear milling (S3M) technology is employed to achieve ultrafine milling of carbon matrices in carbon/carbon (C/C) composite materials while preserving carbon fibers. By this means, carbon fibers and the carbon matrix were mainly split, and the prepared composite powder had combined functionalities of conductivity, thermal conductivity, reinforcement, and wear resistance. The experimental results showed that the tensile strength of the material increased from 64.35 MPa to 72.79 MPa after being compounded with PA6, and the thermal conductivity increased from 0.211 W/mK to 0.611 W/mK. The friction coefficient was reduced from 0.51 to 0.36, a reduction of 25.4%, and the heat deflection temperature was increased from 47.2 °C to 108.2 °C. The S3M technique proposed in this work is an efficient, high-value, and scalable recycling strategy for CFCM, which can be used to produce value-added products and has great application prospects. [ABSTRACT FROM AUTHOR]

Saccharina japonica is one of the most productive aquatic plants in the world, widely used in food, feed, medicine, and other industries. Predominantly inhabiting temperate marine environments in mid- to high-latitude regions of the Northern Hemisphere, the growth of S. japonica is significantly limited by high-temperature stress. Abscisic acid (ABA) plays an important role in plant growth and development and stress responses. However, the role of ABA on high-temperature stress tolerance in S. japonica still needs to be further elucidated. Here, we found that exogenous ABA significantly alleviated disease and decay in S. japonica under high-temperature stress while also increasing the relative growth rate, chlorophyll fluorescence parameters, photosynthetic pigment, and osmotic substance content. Meanwhile, exogenous ABA enhanced the activity of protective enzymes and up-regulated the transcript levels of antioxidant-related genes, thereby reducing oxidative damage. Most importantly, we observed a significant increase in ABA content and the transcript levels of key genes involved in ABA synthesis in S. japonica under high-temperature stress, which were further amplified by the addition of exogenous ABA. In conclusion, this study provides evidence that ABA can moderate the detrimental effects of high-temperature stress and provides a theoretical basis for the screening of S. japonica germplasm resources and the cultivation of new stress-resistant varieties. [ABSTRACT FROM AUTHOR]

Ion-adsorbing rare earth tailings (IRETs) contain a large amount of clay minerals, which are a potential source of silicon and aluminum for the preparation of zeolite materials. The complexity of the tailings' composition and the impurity composition are the main difficulties in the controllable preparation of zeolite. Herein, IRETs were treated by classification activation technology for the preparation of IRET-ZEO, which was used for the removal of heavy metal Pb2+ in water. A new method of resource utilization of ion-type rare earth tailings is realized by "treating waste with waste". The results showed that the IRETs were classified and then thermally activated, and the optimal activation parameter was calcination at 850 °C for 1 h. The optimal NaOH concentration used in the crystallization process was 5 mol/L, with a crystallization time of 3 h and a crystallization temperature of 85 °C, and the crystallization product was zeolite A. The removal rate of the Pb2+ solution with an initial concentration of 100 mg/L was as high as 96.7% in an acidic solution with a pH value from 2 to 5.5. In particular, when the solution pH was higher than 4.2, the adsorption rate of Pb2+ was close to 100%. The IRET-ZEO showed a fast adsorption rate (5 min to reach adsorption equilibrium), a large adsorption capacity (378.35 mg/g), excellent acid resistance, and selectivity and regenerability for Pb2+. This work provides a new strategy for the green resource utilization of IRETs and the treatment of lead-containing wastewater. [ABSTRACT FROM AUTHOR]

This study explores the water consumption and greenhouse gas (GHG) emissions in the Yarkand River Basin, focusing on their dynamic interactions across industrial sectors. Utilizing environmental input–output analysis (IOA), the CROPWAT model, and life cycle assessment (LCA), we quantified the historical evolution of physical and virtual water cycles in relation to the water–carbon nexus. Our findings reveal that the planting industry, particularly the production of export-oriented, water-intensive crops like cotton, significantly contributes to both blue and green water consumption, exacerbating regional water scarcity. The persistent external market demand drives this over-extraction, further strained by the basin's limited water retention capabilities. Although advancements have been made in reducing the per-unit water footprint of crops, total water consumption continues to rise due to agricultural expansion, intensifying pressure on blue water resources. Additionally, agricultural GHG emissions have surged, driven by increased electricity consumption, heavy fertilizer use, and escalating soil N2O emissions. In light of these challenges, our research underscores the critical need for integrated resource management strategies that align with sustainable development goals. By promoting efficient water allocation within the agricultural sector and diversifying crop structures downstream, we can enhance ecosystem resilience and reduce environmental degradation. Furthermore, the advancement of value-added agricultural processing and the implementation of innovative water conservation technologies are essential for fostering economic sustainability. These strategies not only mitigate the environmental impacts associated with agricultural practices but also strengthen the region's adaptive capacity in the face of climate change and fluctuating market demands. Our findings contribute to the broader discourse on sustainable agricultural practices, emphasizing the interconnectedness of water management, climate resilience, and economic viability in arid regions. [ABSTRACT FROM AUTHOR]

The vehicular trajectory offset represents a critical controlling element in the design of lane width. In light of the paucity of extant research on the lane widths for dedicated autonomous vehicle lanes, this study deployed the PreScan-Simulink co-simulation platform. Based on the established typical lateral and longitudinal control methods for autonomous vehicles, we initially identified the primary factors influencing trajectory offset through multifactorial coupled analysis. Subsequently, we conducted quantitative research on vehicle trajectory offset using S-shaped curves to elucidate the patterns in geometric elements' impact on trajectory offset. Following this, we established a model of the relationship between design speed and trajectory offset under different vehicle types. Ultimately, we calculated the lane width values for scenarios involving varying positions and numbers of dedicated lanes. The results demonstrate that vehicle speed significantly impacts the trajectory offsets of autonomous vehicles. For passenger cars, the mean offset at speeds between 60 and 130 km/h is approximately 10 cm. At higher speeds of 140–150 km/h, the offset is more variable. The range of offset exhibited by trucks at speeds between 60 and 100 km/h is [8 cm, 16 cm]. In the case of a single dedicated lane, the width of the inner lanes intended for passenger cars is [2.60 m, 3.00 m], while the outer lanes designed to accommodate trucks have a width of [3.00 m, 3.20 m]. In scenarios with two dedicated lanes, the width of lanes for passenger cars can be reduced further, whereas the required lane width for trucks remains largely unchanged compared to that for single-lane setups. The conclusions show that the width of lanes adapted to autonomous vehicles could be reduced, which could help to optimize the use of road space, thus potentially reducing the occupation of land resources, reducing the environmental impact of road construction, and contributing to sustainable development. This study also provides valuable insights for the design of lanes dedicated to autonomous vehicles. [ABSTRACT FROM AUTHOR]

Limited data are available on copper (Cu)–pH interaction-responsive genes and/or metabolites in plant roots. Citrus sinensis seedlings were treated with 300 μM (Cu toxicity) or 0.5 μM (control) CuCl2 at pH 3.0 or 4.8 for 17 weeks. Thereafter, gene expression and metabolite profiles were obtained using RNA-Seq and widely targeted metabolome, respectively. Additionally, several related physiological parameters were measured in roots. The results indicated that elevating the pH decreased the toxic effects of Cu on the abundances of secondary metabolites and primary metabolites in roots. This difference was related to the following several factors: (a) elevating the pH increased the capacity of Cu-toxic roots to maintain Cu homeostasis by reducing Cu uptake and Cu translocation to young leaves; (b) elevating the pH alleviated Cu toxicity-triggered oxidative damage by decreasing reactive oxygen species (ROS) formation and free fatty acid abundances and increasing the ability to detoxify ROS and maintain cell redox homeostasis in roots; and (c) increasing the pH prevented root senescence and cell wall (CW) metabolism impairments caused by Cu toxicity by lowering Cu levels in roots and root CWs, thus improving root growth. There were some differences and similarities in Cu–pH interaction-responsive genes and metabolites between leaves and roots. [ABSTRACT FROM AUTHOR]

Oil tea camellia (Camellia spp.) is an important woody oil crop with a high nutritional and economic value. Whole-genome resequencing (WGR) technology can provide an in-depth understanding of the genetic background of this plant as well as a reference for breeding research, germplasm resource conservation, and genetic modification. In this study, we analyzed SNP and InDel variations in 49 individual oil tea camellia germplasm samples collected from five populations located in three provinces of China: Hainan, Guangdong and Guangxi. The samples were analyzed through WGR after the ploidy of the samples was determined through flow cytometry. A total of 239,441,603 high-quality single nucleotide polymorphisms (SNPs) and 23,510,374 high-quality insertion/deletion variation sites (InDels) were obtained. The distribution of SNPs and InDels in different functional regions differed significantly, with a high density of variations in non-coding regions, such as intergenic regions and introns, and a relatively low density of variations in coding regions. Transition was the main type of SNP variation. A population genetic diversity analysis revealed that the sampled oil tea camellia populations exhibited a high genetic diversity and extensive genetic variation. The genetic diversity of the oil tea camellia populations in the Hainan region was higher than inland regions. This study also determined the genetic diversity of and variations between octoploid and decaploid oil tea camellia in the tropics and between Hainan-based and inland oil tea camellia. Such findings provide a reference for the conservation of germplasm resources and the genetic modification of oil tea camellia. [ABSTRACT FROM AUTHOR]

Trophic state index (TSI) is a critical ecological and environmental issue in water resource management that has garnered significant attention. Given the complexity of optical characteristics in aquatic environments, this study employs fuzzy classification methods (FCM) and composite nutrient status indices to meticulously classify in-situ remote sensing reflectance data, aiming to develop evaluation models for different nutrient status categories to facilitate the assessment of the Daihai River in Inner Mongolia, China. Subsequently, we applied this model to MSI data to analyze the nutrient status of Daihai Lake from 2016 to 2021. Furthermore, a structural equation model (SEM) was utilized to explore the primary driving factors influencing nutrient status. The results indicated that the water bodies in Daihai Lake can be broadly classified into three categories, with the nutrient status models demonstrating robust performance for each category (R2 = 0.80, R2 = 0.83, and R2 = 0.74). Comparisons were made between nutrient status accuracies obtained through the NCM and FCM based on measured data, yielding R2 values of 0.74 and 0.85, respectively. Furthermore, the TSI results derived from MSI inversion were validated, with NCM achieving an R2 of 0.49, RMSE of 6.88, and MAPE of 10.36%, while FCM exhibited an R2 of 0.55, RMSE of 8.89, and MAPE of 13.18%. An SEM–based analysis revealed that over the long term, human activities exerted a more substantial impact on eutrophication in Daihai Lake, while climatic factors played an accelerating and reinforcing role. These results are consistent with prior research in the Daihai area, indicating a state of mild eutrophication and the potential of the fuzzy classification method and comprehensive trophic status index method in eutrophication assessment. [ABSTRACT FROM AUTHOR]

Simple Summary: The obesity epidemic in the USA is increasing the risk of aggressive triple-negative breast cancer (TNBC) in obese women. This study investigated the potential impact of obesity on the advancement of TNBC by amplifying leukemia inhibitory factor receptor (LIFR) signaling. We tested the effects of LIFR inhibition using EC359 on TNBC cells in obesity conditions. The obesity environment increased TNBC cell growth and invasion, and treatment with EC359 effectively reduced these effects. Using TNBC cells, patient-derived organoids, and mouse models, we showed that EC359 can inhibit obesity-linked TNBC progression. Collectively, our results suggest targeting LIFR signaling as a potential treatment for obesity-related TNBC. American women with obesity have an increased incidence of triple-negative breast cancer (TNBC). The impact of obesity conditions on the tumor microenvironment is suspected to accelerate TNBC progression; however, the specific mechanism(s) remains elusive. This study explores the hypothesis that obesity upregulates leukemia inhibitory factor receptor (LIFR) oncogenic signaling in TNBC and assesses the efficacy of LIFR inhibition with EC359 in blocking TNBC progression. TNBC cell lines were co-cultured with human primary adipocytes, or adipocyte-conditioned medium, and treated with EC359. The effects of adiposity were measured using cell viability, colony formation, and invasion assays. Mechanistic studies utilized RNA-Seq, Western blotting, RT-qPCR, and reporter gene assays. The therapeutic potential of EC359 was tested using xenograft and patient-derived organoid (PDO) models. The results showed that adipose conditions increased TNBC cell proliferation and invasion, and these effects correlated with enhanced LIFR signaling. Accordingly, EC359 treatment reduced cell viability, colony formation, and invasion under adipose conditions and blocked adipose-mediated organoid growth and TNBC xenograft tumor growth. RNA-Seq analysis identified critical pathways modulated by LIF/LIFR signaling in diet-induced obesity mouse models. These findings suggest that adiposity contributes to TNBC progression via the activation of the LIF/LIFR pathway, and LIFR inhibition with EC359 represents a promising therapeutic approach for obesity-associated TNBC. [ABSTRACT FROM AUTHOR]

This paper addresses the inherent limitations in traditional color modeling techniques for measuring the flame equivalence ratio (Φ), particularly focusing on the subjectivity involved in threshold settings and the challenges posed by uneven 2D color distribution. To overcome these issues, this study introduces an attention-based convolutional neural network (ACN) model, a novel approach that transcends the conventional reliance on B/G color features (Tf). The ACN model leverages adaptive feature extraction, augmented by a spatial attention mechanism, to more effectively analyze flame images. By amplifying key features, autonomously minimizing background noise, and standardizing variations in color distribution, the ACN model in this experiment achieved a prediction accuracy of 99%, with a 76% reduction in error rate compared to the original model, significantly improving the accuracy and objectivity of flame Φ measurement. This method marks a substantial development in the precision and reliability of flame analysis. [ABSTRACT FROM AUTHOR]

As Deep Neural Networks (DNNs) continue to increase in complexity, the computational demands of their training have become a significant bottleneck. Low-precision training has emerged as a crucial strategy, wherein full-precision values are quantized to lower precisions, reducing computational overhead while aiming to maintain model accuracy. While prior research has primarily focused on minimizing quantization noise and optimizing performance for specific models and tasks, a comprehensive understanding of the general principles governing low-precision computations across diverse DNN architectures has been lacking. In this paper, we address this gap by systematically analyzing the factors that influence low-precision matrix computations, which are fundamental to DNN training. We investigate three critical factors—accumulation in matrix calculations, the frequency of element usage, and the depth of matrices within the model—and their impact on low-precision training. Through controlled experiments on standard models, as well as customized experiments designed to isolate individual factors, we derive several key insights: layers with higher accumulation and matrices with lower usage frequencies demonstrate greater tolerance to low-precision noise, without significantly compromising the stability of model training. Additionally, while the depth of matrices influences the stability of matrix operations to some extent, it does not have a noticeable effect on the overall training outcomes. Our findings contribute to the development of generalizable principles for low-precision training, offering a systematic framework applicable across various DNN architectures. We provide empirical evidence supporting the strategic allocation of training bit-widths based on the analyzed factors, thereby enhancing the efficiency and effectiveness of DNN training in resource-constrained environments. [ABSTRACT FROM AUTHOR]

Magnetic resonance (MR) imaging is widely used in the clinical field due to its non-invasiveness, but the long scanning time is still a bottleneck for its popularization. Using the complementary information between multi-modal imaging to accelerate imaging provides a novel and effective MR fast imaging solution. However, previous technologies mostly use simple fusion methods and fail to fully utilize their potential sharable knowledge. In this study, we introduced a novel multi-hierarchical complementary feature interaction network (MHCFIN) to realize joint reconstruction of multi-modal MR images with undersampled data and thus accelerate multi-modal imaging. Firstly, multiple attention mechanisms are integrated with a dual-branch encoder–decoder network to represent shared features and complementary features of different modalities. In the decoding stage, the multi-modal feature interaction module (MMFIM) acts as a bridge between the two branches, realizing complementary knowledge transfer between different modalities through cross-level fusion. The single-modal feature fusion module (SMFFM) carries out multi-scale feature representation and optimization of the single modality, preserving better anatomical details. Extensive experiments are conducted under different sampling patterns and acceleration factors. The results show that this proposed method achieves obvious improvement compared with existing state-of-the-art reconstruction methods in both visual quality and quantity. [ABSTRACT FROM AUTHOR]

Urethane surfactants (REQ) were synthesized with octadecanol ethoxylate (AEO) and isocyanate methacrylate (IEM). Subsequently, reactive-carbamate-surfactant-modified nanomicrospheres (PER) were prepared via two-phase aqueous dispersion polymerization using acrylamide (AM), 2-acrylamido-2-methylpropanesulfonic acid (AMPS) and ethylene glycol dimethacrylate (EGDMA). The microstructures and properties of the nanomicrospheres were characterized and examined via infrared spectroscopy, nano-laser particle size analysis, scanning electron microscopy, and in-house simulated exfoliation experiments. The results showed that the synthesized PER nanomicrospheres had a uniform particle size distribution, with an average size of 336 nm. The thermal decomposition temperature of the nanomicrospheres was 278 °C, and the nanomicrospheres had good thermal stability. At the same time, the nanomicrospheres maintained good swelling properties at mineralization < 10,000 mg/L and temperature < 90 °C. Under the condition of certain permeability, the blocking rate and drag coefficient gradually increased with increasing polymer microsphere concentration. Furthermore, at certain polymer microsphere concentrations, the blocking rate and drag coefficient gradually decreased with increasing core permeability. The experimental results indicate that nanomicrospheres used in the artificial core simulation drive have a better ability to drive oil recovery. Compared with AM microspheres (without REQ modification), nanomicrospheres exert a more considerable effect on recovery improvement. Compared with the water drive stage, the final recovery rate after the drive increases by 23.53%. This improvement is attributed to the unique structural design of the nanorods, which can form a thin film at the oil–water–rock interface and promote oil emulsification and stripping. In conclusion, PER nanomicrospheres can effectively control the fluid dynamics within the reservoir, reduce the loss of oil and gas resources, and improve the economic benefits of oil and gas fields, giving them a good application prospect. [ABSTRACT FROM AUTHOR]

Water scarcity and ecological degradation in arid zones present significant challenges to regional ecological health. Despite this, integrating the water supply–demand balance and water supply security (SEC) into ecological health assessments—particularly through composite indicators—remains underexplored in arid regions. In this study, we assessed the ecological health changes in Xinjiang by utilizing multivariate remote sensing data, focusing on the balance between water supply and demand, the degree of SEC, and ecosystem resilience (ER). Our results indicate that while water supply and demand remained relatively stable in northern Xinjiang between 2000 and 2020, the conflict between supply and demand intensified in the southern and eastern agricultural regions. SEC evaluations revealed that 73.3% of the region experienced varying degrees of decline over the 20-year period. Additionally, ER assessments showed that 7.12% of the region exhibited a significant decline, with 78.6% experiencing overall reductions in ecological health. The indicators' response to drought demonstrated that improvements in ecological health during wet conditions were less pronounced than declines during droughts. This study underscores the necessity of prioritizing areas with lower ecological health in future water allocation strategies to optimize water resource utilization. [ABSTRACT FROM AUTHOR]

The access of a high proportion of photovoltaic (PV) will change the energy structure of the distribution network (DN), resulting in a series of safety operation risks. This paper proposes a two-stage PV hosting capacity (PVHC) calculation model to assess the maximum PVHC, considering the uncertainty and active management (AM). Firstly, we employ a robust optimization model to characterize the uncertainty of sources and loads in DN with PV and analyze the worst-case scenarios for PVHC. Subsequently, we construct a PVHC calculation model that takes into account AM, and convert the model into a mixed-integer second-order cone (MISOC) model using linearization techniques. Finally, we apply "heuristic optimization + CPLEX solver" to solve the model and introduce overvoltage and overcurrent indices to analyze the safety of the DN under PV limit access. Case studies are carried out on the IEEE 33-bus system and a practical case. Results show that (1) only the uncertainty that reduces the load or increases the output efficiency will affect PVHC; (2) for DN limited by overvoltage, AM can better improve PVHC; however, for DN limited by maximum transmission power, the effect of AM is low; (3) for most DN, SVC can improve PVHC, but the effect is modest. And network reconfiguration can significantly increase PVHC on the system with poor branch network, even reaching 150% of the original PVHC. [ABSTRACT FROM AUTHOR]

Papaya leaves have been used as food and traditional herbs for the treatment of cancer, diabetes, asthma, and virus infections, but the active principle has not been understood. We hypothesized that the anti-inflammatory activity could be the predominant underlying principle. To test this, we extracted papaya leaf juice with different organic solvents and found that the ethyl acetate (EA) fraction showed the most outstanding anti-inflammatory activity by suppressing the production of nitric oxide (NO, IC50 = 24.94 ± 2.4 μg/mL) and the expression of pro-inflammatory enzymes, such as inducible nitric oxide synthase (iNOS) and cyclooxygenase (COX-2), and cytokines including interleukins (IL-1β and IL-6), and a tumor necrosis factor (TNF-α) in lipopolysaccharide (LPS)-induced RAW 264.7 cells. Transcriptomic analysis and Western blot results revealed its anti-inflammatory mechanisms were through the MAPK signaling pathway by inhibiting the phosphorylation of ERK1/2, JNKs, and p38 and the prevention of the cell surface expression of TLR4. Furthermore, we discovered that the EA fraction could inhibit the replication of alpha-coronavirus (HCoV-229E) and beta-coronavirus (HCoV-OC43 and SARS-CoV-2) and might be able to prevent cytokine storms caused by the coronavirus infection. From HPLC-QTOF-MS data, we found that the predominant phytochemicals that existed in the EA fraction were quercetin and kaempferol glycosides and carpaine. Counter-intuitively, further fractionation resulted in a loss of activity, suggesting that the synergistic effect of different components in the EA fraction contribute to the overall potent activity. Taken together, our results provide preliminary evidence for papaya leaf as a potential anti-inflammatory and anti-coronavirus agent, warranting further study for its use for human health promotion. [ABSTRACT FROM AUTHOR]

To enhance the efficiency of solving the optimal operation model for cascade reservoirs, this paper first constructed an optimal operation model of cascade reservoirs. The model comprehensively considered the ecological flow, the guaranteed output of hydroelectric power plants, and the relaxation constraints of the water level at the end of water supply and storage period. The relaxation constraints refer to two relaxation variable constraints, which are used to ensure that the water levels decline in the water supply period and rise in the water storage periods. At the same time, to avoid the challenges of "dimension disaster" and susceptibility to local optima commonly encountered in existing optimization algorithms when resolving the above model, a novel optimization algorithm, M-IWO-ODDDP, derived from the optimization principles of the Invasive Weed Optimization (IWO) and Discrete Differential Dynamic Programming (DDDP) algorithms, was proposed in this paper. The 11 cascade hydropower stations in the Wujiang River basin were used as a case study, and the results showed that the water-level dispatching process exhibited a high degree of conformity with the actual dispatching process during both the water supply and storage periods. Furthermore, the output calculation results based on the M-IWO-ODDDP algorithm were 3.94% and 0.30% higher than the actual output and ODDDP calculation results, respectively, while reducing water abandonment by 21.58% and 4.07%. [ABSTRACT FROM AUTHOR]

The rotational mechanism, which plays a critical role in energy supply, payload antenna pointing, and attitude stabilization in satellites is essential for the overall functionality and performance stability of the satellite. This paper takes the space turntable of a specific satellite model as an example, utilizing high-frequency and high-dimensional telemetry data. An improved informer model is used to predict and diagnose features related to the turntable's operational health, including temperature, rotational speed, and current. In this paper, we present a forecasting method for turntable temperature data using a hybrid model that combines singular spectrum analysis with an enhanced informer model (SSA-Informer), comparing the results with threshold limits to determine if faults occur in the satellite's rotational mechanism. First, during telemetry data processing, singular spectrum analysis (SSA) is proposed to retain the long-term and oscillatory trends in the original data while filtering out noise from interference. Next, the improved informer model predicts the turntable temperature based on the mapping relationship between the turntable subsystem's motor current and temperature, with multiple experiments conducted to obtain optimal parameters. Finally, temperature thresholds generated from the prediction results are used to forecast faults in the rotational mechanism over different time periods. The proposed method is compared with current popular time-series prediction models. The experimental results show that the model achieves high prediction accuracy, with reductions of at least 10% in both the MAE and MSE than CNN-LSTM, DA-RNN, TCN-SE and informer, demonstrating the outstanding advantages of the SSA and improved informer-based method in predicting temperature faults in satellite rotational mechanisms. [ABSTRACT FROM AUTHOR]

Integrated circuits (ICs) are critical components in the semiconductor industry, and precise wafer defect inspection is essential for maintaining product quality and yield. This study addresses the challenge of insufficient sample patterns in wafer defect datasets by using the denoising diffusion probabilistic model (DDPM) to produce generated defects that elevate the performance of wafer defect inspection. The quality of the generated defects was evaluated using the Fréchet Inception Distance (FID) score, which was then synthesized with real defect-free backgrounds to create an augmented defect dataset. Experimental results demonstrated that the augmented defect dataset significantly boosted performance, achieving 98.7% accuracy for YOLOv8-cls, 95.8% box mAP for YOLOv8-det, and 95.7% mask mAP for YOLOv8-seg. These results indicate that the generated defects produced by the DDPM can effectively enrich wafer defect datasets and enhance wafer defect inspection performance in real-world applications. [ABSTRACT FROM AUTHOR]

Background: The relationship between mental disorders and oral health is complex, involving behavioral, biological, and psychosocial factors. This review aims to investigate the impact of mental disorders, including autism spectrum disorder (ASD), depression, bipolar disorder, and schizophrenia, on oral health outcomes. Methods: A comprehensive review of existing literature was conducted to analyze the oral health outcomes associated with each mental disorder. The focus was on examining dietary habits, oral hygiene behaviors, physiological changes, and medication side effects that contribute to oral health issues. Results: The findings indicate that individuals with ASD often exhibit unique dietary habits and reduced oral hygiene capabilities due to sensory sensitivities, leading to a higher prevalence of dental caries and periodontal diseases. Depression and bipolar disorder are associated with physiological changes such as reduced saliva production and poor oral hygiene behaviors, increasing the risk of oral health problems. Medications used for these conditions exacerbate issues like xerostomia, further elevating the risk of dental diseases. Schizophrenia poses additional challenges, including cognitive impairments and medication side effects that hinder effective oral care, heightening susceptibility to oral diseases. Conclusions: This review highlights the specific oral health challenges associated with different mental disorders and emphasizes the need for tailored dental care strategies that integrate mental health considerations. The study contributes to the literature by demonstrating the unique oral health impacts of these disorders. However, the findings are limited by the scope of available cross-sectional data and the absence of longitudinal studies. Future research should focus on longitudinal and intervention-based studies to explore causal relationships and develop effective treatments. [ABSTRACT FROM AUTHOR]

Ertan Hydroelectric Power Station was the first large-scale water conservancy facility in western China, and with its completion, the ecological pattern of the reservoir area has changed dramatically; however, the changes in habitat quality before and after the completion of the reservoir have not yet been systematically monitored and evaluated. In this study, we analyzed the spatial and temporal characteristics of the remote sensing ecological index (RSEI), used CA-Markov model and GeoDetector, evaluated the ecological environment of the Ertan Reservoir area in each five-year period from 1995 to 2020, simulated the ecological quality of the Ertan Reservoir area in 2025, and revealed the nine drivers and their interactions affecting ecological quality of the watershed from a geologic point of view, and finally put forward reasonable planning and targeted protection suggestions. Finally, rational planning and targeted protection recommendations were proposed. The main results were as follows: (1) After the completion of the Ertan Hydropower Station, the spatial distribution of the RSEI in the reservoir area varied significantly, with a trend of "rising-declining-rising" in time, and the area share of "good" area increased the most, by 19.83%. (2) The degree of grading of each driving factor had different degrees of influence on the size of the RSEI value, and its interaction enhanced the spatial differentiation of the RSEI. (3) The average value of the RSEI is 0.66 in 2025, and the ecological environment quality will show a steady improvement in five years. The results of the study can provide a reference for constructing RSEI indicators for large hydropower facilities. [ABSTRACT FROM AUTHOR]

Modular design facilitates easy disassembly and reduces the manufacturer's remanufacturing costs. However, the simplicity and modular structure of products can intensify competition between manufacturers and third-party recyclers. To improve recovery efficiency, this study examines the impact of modular design on the manufacturer's selection of recovery strategies, including centralized, cooperation, and competition strategies. We examine the optimal recovery strategy for achieving both economic goals, such as supply chain profit, and environmental goals, such as collection quantity. Our results indicate that the manufacturer should adopt cooperation recovery and invest in higher modularity when faced with strong competition from third-party recyclers. Conversely, when the competitiveness of third-party recovery is relatively low, a competition recovery strategy is more advantageous. Contrary to conventional wisdom, which suggests limiting product disassembly to reduce third-party recovery competitiveness, our results indicate that manufacturers should invest in higher modularity and avoid engaging in price wars to prevent third-party entry. Moreover, competition recovery leads to a higher collection quantity, while cooperation recovery is preferred in terms of supply chain profit. This study provides theoretical guidance for manufacturers in selecting optimal recovery strategies and offers recommendations for governments on regulating product disassembly effectively. [ABSTRACT FROM AUTHOR]

The development of efficient photocatalysts is crucial in addressing water pollution concerns, specifically in the removal of organic dyes from wastewater. In this context, the use of silver nanoparticles (Ag NPs) might represent a method to achieve high dye degradation efficiencies. On the other hand, the classical Ag NP production process involves several reactants and operating conditions, which make it poorly sustainable. In the present work, Ag NPs were synthesized according to a new sustainable process involving the use of natural extracts of Spirulina platensis and milder operating conditions. The material was also calcined to determine the influence of organic content on the properties of Ag NPs. The X-ray diffraction (XRD) analysis displayed the AgCl and Ag phases with a crystalline size of 11.79 nm before calcination. After calcination, only the Ag phase was present with an increased crystalline size of 24.60 nm. Fourier Transform Infrared Spectroscopy (FTIR) confirmed the capping role of the metabolites from the extract. Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM) revealed the spherical or quasi-spherical morphologies with agglomeration due to the calcination. Energy-dispersive X-ray spectroscopy (EDX) and Thermogravimetric (TGA) analyses further confirmed the involvement of metabolites in the synthesis of Ag NPs. The optical changes in the products were observed in a UV-Vis analysis. The Ag NPs were tested for their photocatalytic activity against the laboratory dye brilliant blue r in visible light in various conditions. The highest degradation efficiency of 81.9%, with a kapp value of 0.00595 min−1, was observed in alkaline medium after 90 min of light irradiation. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) arises from aberrant mutations in colorectal cells, frequently linked to chronic inflammation. This study integrated human gut metagenome analysis with an azoxymethane and dextran sulfate sodium-induced CRC mouse model to investigate the dynamics of inflammation, gut microbiota, and metabolomic profiles throughout tumorigenesis. The analysis of stool metagenome data from 30 healthy individuals and 40 CRC patients disclosed a significant escalation in both gut microbiota diversity and abundance in CRC patients compared to healthy individuals (p < 0.05). Marked structural disparities were identified between the gut microbiota of healthy individuals and those with CRC (p < 0.05), characterized by elevated levels of clostridia and diminished bifidobacteria in CRC patients (p < 0.05). In the mouse model, CRC mice exhibited distinct gut microbiota structures and metabolite signatures at early and advanced tumor stages, with subtle variations noted during the intermediate phase. Additionally, inflammatory marker levels increased progressively during tumor development in CRC mice, in contrast to their stable levels in healthy counterparts. These findings suggest that persistent inflammation might precipitate gut dysbiosis and altered microbial metabolism. Collectively, this study provides insights into the interplay between inflammation, gut microbiota, and metabolite changes during CRC progression, offering potential biomarkers for diagnosis. While further validation with larger cohorts is warranted, the data obtained support the development of CRC prevention and diagnosis strategies. [ABSTRACT FROM AUTHOR]

Background: Infant growth trajectories reflect current health status and may predict future obesity and metabolic diseases. Human milk is tailored to support optimal infant growth. However, nutrient intake rather than milk composition more accurately predicts growth outcomes. Although the role of protein leverage in infant growth is unclear, protein intake is important for early infancy growth. Materials and methods: This study of exclusively breastfeeding mothers with allergies (n = 161) from the Infant Fish Oil Supplementation Study assessed relationships between intake of human milk macronutrients and infant growth. Human milk fat, protein and lactose concentrations were measured at 3 months postpartum, and infant daily intakes were estimated using an average milk intake of 800 mL/day. Results: Higher human milk protein:energy ratio was associated with higher weight-for-age z-score at 2.5 years compared to 3 months and higher body mass index-for-age z-score change (6 months to 1 year compared to 3–6 months). Maternal atopy and birth season (summer) were negatively associated with human milk lactose concentration. Passive smoke exposure was associated with reduced energy and fat concentrations and increased lactose:energy ratio. Conclusions: Our results indicate that intake of human milk macronutrients may impact early childhood growth. [ABSTRACT FROM AUTHOR]

Background: Iron deficiency (ID) remains the leading cause of anemia, affects a vast number of persons globally, and continues to be a significant global health burden. Comprehending the patterns of ID burden is essential for developing targeted public health policies. Methods: Using data from the Global Burden of Disease (GBD) 2021 study for the years 1990–2021, the XGBoost model was constructed to predict prevalence and disability-adjusted life years (DALYs) for the period 2022–2050, based on key demographic variables. Shapley Additive exPlanations (SHAP) values were applied to interpret the contributions of each variable to the model's predictions. Additionally, the Age–Period–Cohort (APC) model was used to evaluate the effects of age, period, and birth cohort on both prevalence and DALYs. The relationship between the Socio-Demographic Index (SDI) and ID's age-standardized prevalence rate (ASPR) as well as the age-standardized DALYs rate (ASDR) was also analyzed to assess the influence of socioeconomic development on disease burden. Results: The global prevalent cases of ID grew from 984.61 million in 1990 to 1270.64 million in 2021 and are projected to reach 1439.99 million by 2050. Similarly, global DALYs from ID increased from 28.41 million in 1990 to 32.32 million in 2021, with a projected rise to 36.13 million by 2050. The ASPR declined from 18,204/100,000 in 1990 to 16,433/100,000 in 2021, with an estimated annual percentage change (EAPC) of −0.36% over this period. It is expected to decrease further to 15,922 by 2050, with an EAPC of −0.09% between 2021 and 2050. The ASDR was 518/100,000 in 1990 and 424/100,000 in 2021, with an EAPC of −0.68% from 1990 to 2021. It is expected to remain relatively stable at 419/100,000 by 2050, with an EAPC of −0.02% between 2021 and 2050. In 2021, the highest ASPRs were recorded in Senegal (34,421/100,000), Mali (34,233/100,000), and Pakistan (33,942/100,000). By 2050, Mali (35,070/100,000), Senegal (34,132/100,000), and Zambia (33,149/100,000) are projected to lead. For ASDR, Yemen (1405/100,000), Mozambique (1149/100,000), and Mali (1093/100,000) had the highest rates in 2021. By 2050, Yemen (1388/100,000), Mali (1181/100,000), and Mozambique (1177/100,000) are expected to remain the highest. SHAP values demonstrated that gender was the leading predictor of ID, with age and year showing negative contributions. Females aged 10 to 60 consistently showed higher prevalence and DALYs rates compared to males, with the under-5 age group having the highest rates for both. Additionally, men aged 80 and above exhibited a rapid increase in prevalence. Furthermore, the ASPR and ASDR were significantly higher in regions with a lower SDI, highlighting the greater burden of ID in less developed regions. Conclusions: ID remains a significant global health concern, with its burden projected to persist through 2050, particularly in lower-SDI regions. Despite declines in ASPR and ASDR, total cases and DALYs are expected to rise. SHAP analysis revealed that gender had the greatest influence on the model's predictions, while both age and year showed overall negative contributions to ID risk. Children under 5, women under 60, and elderly men aged 80+ were the most vulnerable groups. These findings underscore the need for targeted interventions, such as improved nutrition, early screening, and addressing socioeconomic drivers through iron supplementation programs in low-SDI regions. [ABSTRACT FROM AUTHOR]

Potato (Solanum tuberosum L.) is sensitive to drought, which severely impacts tuber yield and quality. In this study, we characterized a XERICO gene, encoding a RING-H2 type E3 ubiquitin ligase, StXERICO1, from a diploid potato, investigated its role in enhancing drought resistance and ABA accumulation, and identified its interaction with the miRNA novel-miR1730-3p, as well as its protein interactions with StUBC and StTLP. StXERICO1, with a complete Open Reading Frame (ORF) of 459 bp encoding 152 amino acids, was highly responsive to drought, ABA treatment, and abiotic stresses in potato plants. Overexpression of the StXERICO1 significantly enhanced drought resistance and ABA accumulation in transgenic potato and tobacco plants and exhibited greater sensitivity to ABA treatment, which was associated with the upregulation of expression of ABA biosynthetic genes NCED and CYP707A. Furthermore, our results revealed that StXERICO1 and its encoding protein interacted with miRNAs and other proteins. 5′ RLM-RACE (cDNA terminal rapid amplification) experiment showed that the miRNA novel-miR1730-3p targets 5′ UTR region of the StXERICO1 gene. Dual luciferase assay and virus-based miRNA silencing experiment showed that the novel-miR1730-3p negatively regulates StXERICO1 expression. Moreover, yeast two-hybrid assay indicated that StXERICO1 interacts with StUBC (an E2 ubiquitin ligase) and StTLP (a Tubby-like protein), suggesting that StXERICO1 might function on ABA homeostasis at the post-translational level. These findings elucidate the molecular mechanisms by which StXERICO1, a RING-H2 type E3 ubiquitin ligase, enhances drought resistance through increased ABA accumulation, how its expression is regulated by miRNA, and how it exerts its function through interactions with other proteins. The results also provide a potential candidate gene for subsequent precision molecular breeding aimed at improving crop drought resistance. [ABSTRACT FROM AUTHOR]

Agricultural soil is the main source of greenhouse gas emissions, among which carbon dioxide (CO2) is an important greenhouse gas, impacting the global climate. In China, as a large rice-producing country, carbon sequestration and CO2 mitigation in paddy soil are crucial for the mitigation of global climate change. While biochar has been widely used in the mitigation of soil greenhouse gas emissions, the application site of biochar, i.e., whether or not it is the same as its feedstocks, may generate different effects on soil CO2 emissions due to the differences in the element and nutrient concentrations in its feedstocks, especially when applied in fertilized soil. In order to explore the effects of biochar application with different feedstocks on the mitigation of CO2 emissions from paddy soil, this experiment took paddy soil in a red soil area as the research object, using rice straw and Camellia oleifera fruit shell as raw materials to produce biochar (adding an amount of 40 g kg−1 soil) and urea as an external nitrogen source (adding an amount of 200 mg kg−1 soil). The effects of two different types of biochar derived from feedstocks with different producing origins on the CO2 emissions from paddy soil were studied via laboratory control incubation studies. The results showed that (1) the effects of rice straw biochar addition on the soil pH, NO3−-N and total available nitrogen (AN) content were significantly higher than those of Camellia oleifera fruit shell biochar (the scale of the increase was higher by 6.40%, 579.7% and 180.1%, respectively). (2) The CO2 emission rate and cumulative emissions of soil supplemented with rice straw biochar were significantly lower than in that supplemented with Camellia oleifera fruit shell biochar (decreases of 28.0% and 27.5%, respectively). Our findings suggest that the efficiency of emission mitigation of rice straw biochar is better than that of Camellia oleifera fruit shell applied to paddy soil. While future studies considering more types of greenhouse gases will be necessary to expand these findings, this study indicates that biochar prepared from in situ feedstock can be used to reduce greenhouse gas emissions in rice fields, so as to ensure sustainable development and achieve energy conservation and emission reduction goals. This study will benefit future agricultural practices when choosing biochar as a greenhouse gas mitigation strategy in the context of global warming, as well as other global changes following global warming, caused by elevated atmospheric greenhouse gases. [ABSTRACT FROM AUTHOR]

Aiming at the requirements of the marine work platform for real-time control, time-varying speed and the time-varying torque control of the motor-driven active heave compensation device, this paper introduces a composite control strategy based on the switched reluctance motor (SRM)-driven active heave compensation device. As for the compensation error caused by the time lag in the real-time system, the model prediction trajectory algorithm is used to predict the compensation displacement obtained using the dynamic model. The next time, the control parameters are then provided for the SRM control system in advance to reduce the compensation error. The SRM control strategy selects a double closed-loop compound control strategy of Back Propagation (BP) fuzzy neural network Proportion Integration Differentiation (PID) control. Its outer speed loop uses a fuzzy controller to quickly track a wide range of speed changes. The torque inner loop uses BP neural network adaptive PID control. This helps to reduce torque ripple and to ensure that the electromagnetic torque output of the SRM remains stable. Finally, the system feasibility is verified by setting different wave parameters. The simulation results show that the simulation conditions can reach 97.5% and 96.4% under the 3 and 4 wave levels, respectively. The simulation effect is satisfying, which verifies the feasibility of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, we study the asymptotical stability of the exact solutions of nonlinear impulsive differential equations with the Lipschitz continuous function f (t , x) for the dynamic system and for the impulsive term Lipschitz continuous delayed functions I k . In order to obtain numerical methods with a high order of convergence and that are capable of preserving the asymptotical stability of the exact solutions of these equations, impulsive discrete Runge–Kutta methods and impulsive continuous Runge–Kutta methods are constructed, respectively. For these different types of numerical methods, different convergence results are obtained and the sufficient conditions for asymptotical stability of these numerical methods are also obtained, respectively. Finally, some numerical examples are provided to confirm the theoretical results. [ABSTRACT FROM AUTHOR]

Background/Objectives: The aim of this study was to report the visual and refractive outcomes of nanophthalmic eyes undergoing phacoemulsification at a tertiary cataract center. Methods: This is a prospective consecutive case series. Patients with an axial length of ≤20.5 mm who underwent phacoemulsification at a tertiary cataract center in Hong Kong were included. Eyes undergoing extracapsular cataract extraction or with a previous history of intraocular surgery including trabeculectomy were excluded. The outcome measures were the corrected distance visual acuity (CDVA) and refractive status at four months post-operation. Different intraocular lens formulas were used to compare the refractive outcomes. Results: Out of 22,847 cataract surgeries performed from May 2011 to March 2020, 14 eyes (0.06%) of 10 patients had axial lengths of ≤20.5 mm and underwent phacoemulsification. The mean axial length was 20.13 ± 0.44 mm. Out of these fourteen eyes, three (21%) had postoperative myopic shift with spherical equivalent refraction of more than or equal to 1D compared to the original target. Eleven eyes (79%) had postoperative refraction within 0.5D compared to the original target. Nine out of fourteen eyes (64%) had improvements in postoperative vision. There were no intraoperative complications. When comparing the Hoffer Q, Holladay 1, Holladay 2, Haigis and Hill-RBF 2.0 formulas, there was no significant difference in the absolute errors between the five formulas (p = 0.072). Conclusions: There was no significant difference in the mean absolute errors between the Hoffer Q, Holladay 1, Holladay 2, Haigis and Hill-RBF 2.0 formulas. Myopic shift was not uncommon, and more studies on intraocular lens (IOL) power calculation for short eyes are warranted. [ABSTRACT FROM AUTHOR]

This study aims to investigate the toughening effects of rubber and thermoplastic particles on epoxy resin (EP), and to understand the mechanism underlying their synergistic effect. For this purpose, three EP systems were prepared using diglycidyl ether of bisphenol-A (DGEBA) epoxy resin (E-54) and 4,4-Diamino diphenyl methane (Ag-80) as matrix resin, 4,4-diaminodiphenyl sulfone (DDS) as a curing agent, and phenolphthalein poly (aryl ether ketone) particles (PEK-C) and carboxyl-terminated butyl liquid rubber (CTBN) as toughening agents. These systems are classified as an EP/PEK-C toughening system, EP/CTBN toughening system, and EP/PEK-C/CTBN synergistic toughening system. The curing behavior, thermal properties, mechanical properties, and phase structure of the synergistic-toughened EP systems were comprehensively investigated. The results showed that PEK-C did not react with EP, while CTBN reacted with EP to form a flexible block polymer. The impact toughness of EP toughened by PEK-C/CTBN was improved obviously without significantly increasing viscosity or decreasing thermal stability, flexural strength, and modulus, and the synergistic toughening effect was significantly higher than that of the single toughening system. The notable improvement in toughness is believed to be due to the synergistic energy dissipation effect of PEK-C/CTBN. [ABSTRACT FROM AUTHOR]

In rubber plantations, understory coverage is often disrupted by human activities, which increases the risk of soil erosion under intense rainfall typical of tropical islands. Evaluating the effectiveness of soil and water conservation measures (SWCMs) is crucial for effectively conserving subcanopy resources. This study focused on Hainan Island's rubber plantations, where nine different SWCMs were implemented, and the runoff and sediment yield were monitored during the rainy season using runoff plots. Through correlation analysis, we identified the primary rainfall characteristic factors leading to soil and water loss on rubber plantation slopes. Path analysis was then used to quantify the impacts of these characteristic factors. The results showed that the SWCMs were significantly more effective in erosion reduction (68.55%) than in runoff reduction (58.95%). Of all the measures, comprehensive SWCMs proved most effective in controlling runoff (71.34%), followed by engineering SWCMs (62.03%) and biological SWCMs (43.51%). Comprehensive SWCMs were also found to be effective in erosion reduction, with a rate of 77.84%, surpassing engineering and biological SWCMs by 7.23% and 20.66%, respectively. Notably, the combination of narrow terraces, contour trenches, and grass planting was the most effective, achieving runoff-reduction rates of 80.94% and erosion-reduction rates of 85.27%. This combination is recommended as a primary prevention method. Rainfall and maximum 30-min intensity (I30) were identified as key variables affecting the efficacy of SWCMs, with rainfall positively correlating with runoff yield and I30 being more closely linked to sediment production. This study provides valuable insights for developing erosion control strategies for sloping garden lands in similar regions and lays theoretical foundations for future ecological restoration projects. [ABSTRACT FROM AUTHOR]

The Poyang Lake Wetland, an internationally significant ecosystem, frequently experiences drought during the flood season. However, the total impact of extreme drought on wetland vegetation remains poorly understood. This study determined the standardised precipitation evapotranspiration index (SPEI) and analysed drought trends within the Poyang Lake Basin. Additionally, spatiotemporal variations in wetland vegetation under drought conditions were examined by analysing the mean normalised difference vegetation index (NDVI) values and categorising NDVI classifications. The key factors affecting wetland vegetation and its respective thresholds were determined. The Poyang Lake Basin has experienced increasing aridity over the past 3 years. In response to this trend, the wetland vegetation area in Poyang Lake expanded, whereas vegetation greenness declined. Notably, in the year following an extreme drought, Poyang Lake's vegetation greenness was lower than that during the same period in previous years. Regardless, the correlation analysis showed no significant relationship between the SPEI values and the wetland vegetation greenness; however, water level changes significantly impacted the wetland vegetation, with a correlation coefficient of −0.89 (p < 0.001). A critical water level of 14 m was identified as the threshold at which sudden changes in the mean NDVI were observed. This research offers valuable insights into hydrological management strategies to protect Poyang Lake Wetland's vegetation under drought conditions. Future studies should enhance the differentiation of drought tolerance among different wetland plant species, thereby achieving differentiated hydrological management. [ABSTRACT FROM AUTHOR]

Global change and the intensification of human activities have led to a sharp decline in global biodiversity and other ecological issues. Over the past 30 years, ecologists have increasingly focused on the question of whether and how the ongoing loss of biodiversity affects ecosystem functioning. However, historically, researchers have predominantly concentrated on individual ecosystem functions, neglecting the capacity of ecosystems to provide multiple ecosystem functions simultaneously, known as ecosystem multifunctionality (EMF). As a result, the connection between biodiversity and ecosystem multifunctionality (BEMF) has become the central theme in BEF relationship research. In recent years, the research on the BEMF relationship has developed rapidly, and new progress has been made in different ecosystems, the driving mechanism of the BEMF relationship, and the proposal and application of new quantitative methods. However, there are still shortcomings, such as the lack of uniform standards for the selection of functional indicators in EMF research, insufficient attention to belowground microbial diversity, and less research on biological interactions in addition to biodiversity. In the future, we need to enhance standard research on the selection of functional indicators, thoroughly assess the combined effects of aboveground and belowground biodiversity along with abiotic factors on EMF, and bolster the research and application of ecosystem multiserviceability (EMS) methods. [ABSTRACT FROM AUTHOR]

Every country in the world, except for African nations, faces significant challenges due to the increasing older population, with China being particularly affected. This issue is more pronounced in rural areas compared to urban centers. To better understand consumer attitudes and willingness to pay (WTP) for age-friendly retrofitting and to identify industry development shortcomings, this study designed a retrofitting scenario and organized a questionnaire survey to collect WTP and its influencing factors from respondents in the Wuhu area of Anhui Province, China. This study determined the retrofit cost to be CNY 12,224.4 and found that over 80% of respondents intended to pursue age-friendly retrofitting. The analysis results indicated that respondents' education level, perceived psychological benefits, and perceived social benefits were positively correlated with their WTP. Additionally, education level, monthly personal income, and choice of retirement area positively influenced retrofitting budgets, whereas age bracket, employment status, and perceived situational risk negatively influenced them. The study's findings will assist consumers in making informed retrofitting decisions and support the government in formulating appropriate policies to enhance the quality of rural residential environments and improve the living standards of the elderly. [ABSTRACT FROM AUTHOR]

With the rapid pace of global urbanization, the urbanization of resettlement communities in China has garnered increasing attention from scholars. This study, grounded in experiential value theory, delves into the relationship between public spaces in resettlement communities and their social cohesion. Focusing on resettlement communities in the central urban area of Fuzhou, this study employs a mixed-method approach to analyze the functional characteristics of public spaces using geospatial data, including their green coverage ratio, spatial accessibility, facility configuration, and neighborhood density. A correlation analysis and multiple linear regression were employed to identify the key elements influencing social cohesion. The results indicate significant disparities in the green coverage, accessibility, facility configuration, and neighborhood density of public spaces. These differences are evident in the quantitative metrics used and also reflect imbalances in spatial layout and resource distribution, highlighting potential pathways for optimizing the quality of public spaces. Further data analyses revealed that both emotional value (β = 0.602, p < 0.01) and functional value (β = 0.136, p < 0.01) have significant positive impacts on social cohesion, with emotional value being particularly influential. This study offers insights for urban planners and policymakers by providing scientific evidence for the optimization of public space design in resettlement communities, with implications for community governance and urban sustainability. [ABSTRACT FROM AUTHOR]

In the simulation of foundation pit excavation, the traditional element birth–death method commonly used tends to encounter issues such as uncoordinated deformation and changes in the constitutive model, affecting the accuracy of the prediction results. To address these issues, this study proposes the use of element tracking. By duplicating elements for temporary supports or structures requiring changes in material properties and appropriately activating or deactivating them at the right moments, the simulation of the foundation pit excavation process can be achieved more precisely. Using the construction process of the Tangxi Passenger Transport Station's comprehensive transportation hub foundation pit as an example, this study applied the proposed simulation method and compared the results with actual measurements, demonstrating its effectiveness. This research offers a more accurate approach for simulating foundation pit excavation and provides a reference for similar numerical simulation problems. [ABSTRACT FROM AUTHOR]

Intermetallic compounds (IMCs) growth can simultaneously bring about low-resistance electrical pathways and drastically reduce joint lifetime. Recently, incorporated trace nanoparticles into the free-Pb solder were found to promote the performance of the solder joints. Sn3Ag0.9Zn (SAZ) nano-composite solders were developed by doping 0.5 wt.% Al2O3 nanoparticles into the SAZ solder. The IMCs formation and growth behavior at the interfacial reactions between the SAZ-0.5Al2O3 nano-composite solder and the Cu substrate during soldering at temperatures ranging from 250 to 325 °C for 30 min were investigated. The results showed that after the addition of Al2O3 nanoparticles into the SAZ solder, the elongated-type IMCs layer changed into a prism-type IMCs layer, and Ag3Sn nanoparticles were absorbed on the grain surface of the interfacial Cu6Sn5 phase, effectively suppressing the growth of the IMCs layers. The activation energies (Q) for the IMCs layers (Cu6Sn5 + Cu3Sn) were determined to be 36.4 and 39.1 kJ/mol for the SAZ/Cu and SAZ-Al2O3/Cu solders, respectively. [ABSTRACT FROM AUTHOR]