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Crosshole ground penetrating radar (GPR) is an efficient method for ensuring the quality of retaining structures without the need for excavation. However, interpreting crosshole GPR data is time-consuming and prone to inaccuracies. To address this challenge, we proposed a novel three-dimensional (3D) reconstruction method based on a generative adversarial network (GAN) to recover 3D permittivity distributions from crosshole GPR images. The established framework, named CGPR2VOX, integrates a fully connected layer, a residual network, and a specialized 3D decoder in the generator to effectively translate crosshole GPR data into 3D permittivity voxels. The discriminator was designed to enhance the generator's performance by ensuring the physical plausibility and accuracy of the reconstructed models. This adversarial training mechanism enables the network to learn non-linear relationships between crosshole GPR data and subsurface permittivity distributions. CGPR2VOX was trained using a dataset generated through finite-difference time-domain (FDTD) simulations, achieving precision, recall and F1-score of 91.43%, 96.97% and 94.12%, respectively. Model experiments validate that the relative errors of the estimated positions of the defects were 1.67%, 1.65%, and 1.30% in the X-, Y-, and Z-direction, respectively. Meanwhile, the method exhibits noteworthy generalization capabilities under complex conditions, including condition variations, heterogeneous materials and electromagnetic noise, highlighting its reliability and effectiveness for practical quality assurance of retaining structures. [ABSTRACT FROM AUTHOR]

Nonalcoholic steatohepatitis (NASH) is a form of chronic liver disease that is characterized by liver inflammation and steatosis, with possible progression to fibrosis. Currently, no drugs have been approved for the treatment of NASH. In this study, we isolated a polysaccharide from Atractylodes lancea rhizome (AP) and established a methionine- and choline-deficient (MCD) diet -induced NASH mouse model to investigate the preventive effect and potential mechanism of AP on NASH. The results showed that AP effectively reduced liver lipid accumulation and inflammation and reduced autophagy and ferroptosis in hepatocytes, thereby preventing the development of NASH. These findings suggest that AP may be a promising natural candidate for the treatment of NASH. [ABSTRACT FROM AUTHOR]

Simple Summary: The genetic diversity and phylogenetic relationships among wild boars in major regions of the world were assessed using genome-wide data from the Qinghai–Tibet Plateau (QTP), southern and northern regions of China, Europe, Northeast Asia, and Southeast Asia. We clarified the close phylogenetic relationship of QTP wild boars with those in southern China. In addition, genome-wide selection signal analysis based on cross-population extended haplotype homozygosity, fixation index parameters, and run of homozygosity island recognition technology was performed to obtain a series of candidate genes related to the plateau adaptability of wild boar, such as TSC2, TELO2, VCP, SLC5A1, and SLC5A4. In particular, SLC5A1 and SLC5A4 are involved in glucose homeostasis and may be the key to the plateau adaptability of wild boars. This study enhances our understanding of the genetic mechanism of high-altitude adaptation in wild boars. The Qinghai–Tibet Plateau (QTP) wild boar is an excellent model for investigating high-altitude adaptation. In this study, we analyzed genome-wide data from 93 wild boars compiled from various studies worldwide, including the QTP, southern and northern regions of China, Europe, Northeast Asia, and Southeast Asia, to explore their phylogenetic patterns and high-altitude adaptation based on genome-wide selection signal analysis and run of homozygosity (ROH) estimation. The findings demonstrate the alignment between the phylogenetic associations among wild boars and their geographical location. An ADMIXTURE analysis indicated a relatively close genetic relationship between QTP and southern Chinese wild boars. Analyses of the fixation index and cross-population extended haplotype homozygosity between populations revealed 295 candidate genes (CDGs) associated with high-altitude adaptation, such as TSC2, TELO2, SLC5A1, and SLC5A4. These CDGs were significantly overrepresented in pathways such as the mammalian target of rapamycin signaling and Fanconi anemia pathways. In addition, 39 ROH islands and numerous selective CDGs (e.g., SLC5A1, SLC5A4, and VCP), which are implicated in glucose metabolism and mitochondrial function, were discovered in QTP wild boars. This study not only assessed the phylogenetic history of QTP wild boars but also advanced our comprehension of the genetic mechanisms underlying the adaptation of wild boars to high altitudes. [ABSTRACT FROM AUTHOR]

Axitinib (AXTN) is an oral tyrosine kinase inhibitor for the treatment of early to advanced renal cell carcinoma. In this work, solvates of AXTN were prepared in five solvents and subjected to desolvation treatment. The crystal form A of AXTN can form solvates in acetonitrile, DMF, acetic acid, acetic acid + water, and methanol. Different ratios of AXTN and acetic acid will form different products (solvate or directly crystallized into another crystal form (form IV)). The characterization results of thermal analyses confirmed the types of the five solvates. The obtained solvates were desolvated using methods of solid-phase desolvation (heating, exposure to solvent steam, microwave) and solvent-mediated phase transformation (SMPT). The desolvated solids were characterized by PXRD, TGA, DSC, FT-IR, and SEM, and it was ultimately inferred that a new crystal form (form Z) of AXTN could be formed after desolvation. In addition, the solvates obtained in this work experienced mutual transformation via SMPT, which depends on the type of solvents or mixed solvents. The phase transformations of different solid forms were summarized. This study is instructive for exploring solvates and polymorphs of AXTN and understanding phase transitions under different environments. [ABSTRACT FROM AUTHOR]

Leonurine is a natural product unique to the Lamiaceae plant Leonurus japonicus Houtt., and it has attracted attention due to its anti-oxidative stress, anti-apoptosis, anti-fibrosis, and metabolic regulation properties. Also, it plays an important role in the prevention and treatment of nonalcoholic fatty liver disease (NAFLD) through a variety of biological mechanisms, but its mechanism of action remains to be elucidated. Therefore, this study aims to preliminarily explore the mechanisms of action of leonurine in NAFLD. Mice were randomly divided into four groups: the normal control (NC) group, the Model (M) group, the leonurine treatment (LH) group, and the fenofibrate treatment (FB) group. The NAFLD model was induced by a high-fat high-sugar diet (HFHSD) for 12 weeks, and liver pathological changes and biochemical indices were observed after 12 weeks. Transcriptomic analysis results indicated that leonurine intervention reversed the high-fat high-sugar diet-induced changes in lipid metabolism-related genes such as stearoyl-CoA desaturase 1 (Scd1), Spermine Synthase (Sms), AP-1 Transcription Factor Subunit (Fos), Oxysterol Binding Protein Like 5 (Osbpl5), and FK506 binding protein 5 (Fkbp5) in liver tissues. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis results suggest that leonurine may exert its lipid-lowering effects through the AMP-activated protein kinase (AMPK) signaling pathway. Liver lipidomic analysis showed that leonurine could alter the abundance of lipid molecules related to fatty acyl (FAs) and glycerophospholipids (GPs) such as TxB3, carnitine C12-OH, carnitine C18:1-OH, and LPC (20:3/0:0). Molecular biology experiments and molecular docking techniques verified that leonurine might improve hepatic lipid metabolism through the alpha-1A adrenergic receptor (ADRA1a)/AMPK/SCD1 axis. In summary, the present study explored the mechanism by which leonurine ameliorated NAFLD by inhibiting hepatic lipid synthesis via the ADRA1a/AMPK/SCD1 axis. [ABSTRACT FROM AUTHOR]

The evolutionary development and phylogenetic division between Asian and African cercopithecoids (Cercopithecidae) have attracted significant attention in genetics, molecular biology, behavior, and morphology. However, less emphasis has been placed on how they have evolved morphologically after divergence, approximately 10 million years ago (mya) for Colobinae and 5–7 mya for Cercopithecinae, corresponding to the significant variation and diversity in landscape, climate, habitat, and ecologies between the two continents. This study examines whether such variation and diversity have been reflected in dental morphology. Our findings reveal substantial differences between Hylobatidae and Cercopithecidae, as well as between Colobinae and Cercopithecinae, indicating that size-adjusted dental variation mainly reveals the diversity associated with evolution and phylogenetic inertia. Interestingly, despite the earlier divergence of Afro-Asian colobines, their Euclidean Distance is comparable to that of Afro-Asian cercopithecines. This implies that latecomers (macaques) demonstrate equivalent diversity to colobines due to their extensive dispersion and broader adaptative radiation on the same continent. Colobinae exhibit more developed premolar and molar regions. However, when post-canine teeth are considered alone, Colobinae present a significantly larger molar size than Asian Cercopithecinae but not with the African Cercopihecinae. This contradicts the hypothesis that folivorous primates (Colobinae) have larger post-canine molars than frugivorous ones (Cercopithecinae). The considerable molar size in African Cercopithecinae must be associated with their more protrusive and larger facial structure rather than a specific dietary preference, being less diverse than their Asian counterparts—a trait that has evolved phylogenetically. This study also paves the way for further exploration of facial and cranial differences between the continental groups of Cercopithecinae and Colobinae, delving deeply into diversity variation due to geographical and climatic adaptations. [ABSTRACT FROM AUTHOR]

The speckle noise inherent in synthetic aperture radar (SAR) imaging has long posed a challenge for SAR data processing, significantly affecting image interpretation and recognition. Recently, deep learning-based SAR speckle removal algorithms have shown promising results. However, most existing algorithms rely on convolutional neural networks (CNN), which may struggle to effectively capture global image information and lead to texture loss. Besides, due to the different characteristics of optical images and synthetic aperture radar (SAR) images, the results of training with simulated SAR data may bring instability to the real-world SAR data denoising. To address these limitations, we propose an innovative approach that integrates swin transformer blocks into the prediction noise network of the denoising diffusion probabilistic model (DDPM). By harnessing DDPM's robust generative capabilities and the Swin Transformer's proficiency in extracting global features, our approach aims to suppress speckle while preserving image details and enhancing authenticity. Additionally, we employ a post-processing strategy known as pixel-shuffle down-sampling (PD) refinement to mitigate the adverse effects of training data and the training process, which rely on spatially uncorrelated noise, thereby improving its adaptability to real-world SAR image despeckling scenarios. We conducted experiments using both simulated SAR image datasets and real SAR image datasets, evaluating our algorithm from subjective and objective perspectives. The visual results demonstrate significant improvements in noise suppression and image detail restoration. The objective results demonstrate that our method obtains state-of-the-art performance, which outperforms the second-best method by an average peak signal-to-noise ratio (PSNR) of 0.93 dB and Structural Similarity Index (SSIM) of 0.03, affirming the effectiveness of our approach. [ABSTRACT FROM AUTHOR]

The accurate prediction of the flow field characteristics of complex mountains is of great practical significance for the development and construction of wind farms, but it is not yet fully understood. The main purpose of this study is to propose a method for the study of flow field characteristics under complex mountain conditions, which can optimize the boundary conditions required for numerical simulation through the wind acceleration ratio and, at the same time, couple the numerical simulation and wind measurement data to reflect the real mountain flow field distribution. The results show that the proposed method has good applicability in complex mountain wind farms, can reproduce the real flow field distribution, and has a certain practical value. Wind speed distribution and turbulence intensity are greatly affected by boundary conditions such as wind speed and wind direction and are also affected by the shielding effect brought by terrain changes. The contrast between 120° and 150° wind direction is more obvious. When the incoming wind moves to the top of a mountain or the ridgeline, it will form a low-speed wake area behind it, resulting in reduced wind speed, increased turbulence intensity, and an unstable flow field. [ABSTRACT FROM AUTHOR]

Insufficient milk supply is a widespread issue faced by women globally and associated with a higher risk of health problems in infants and mothers. Hemerocallis citrina Baron, commonly known as daylily, is a perennial edible plant often used in traditional Asian cuisine to promote lactation. However, the active compound(s) and mechanism of its lactation-promoting effect remain unclear. This study aimed to confirm the traditional use of daylily in promoting lactation and investigate its potential active components and underlying molecular mechanisms. Our results showed that the aqueous extracts of H. citrina Baroni (HAE) significantly enhanced milk production, and the serum levels of lactation-related hormones, and promoted mammary gland development in lactating rats, as well as increased the levels of milk components in bovine mammary epithelial cells (BMECs) (p < 0.05). UHPLC-Q-Exactive Orbitrap-MS analysis revealed that hexamethylquercetin (HQ) is the representative flavonoid component in HAE, accounting for 42.66% of the total flavonoids. An integrated network pharmacology and molecular docking analysis suggested that HQ may be the potential active flavonoid in HAE that promotes lactation, possibly supporting lactation by binding to key target proteins such as STAT5A, PIK3CA, IGF1R, TP53, CCND1, BCL2, INS, AR, and DLD. Cell experiments further demonstrated that HQ could promote cell proliferation and the synthesis of milk proteins, lactose, and milk fat in BMECs. Transcriptomic analysis combined with a quantitative reverse transcription polymerase chain reaction (RT-qPCR) revealed that both HAE and HQ exert a lactation-promoting function mainly through regulating the expression of key genes in the PI3K-Akt signaling pathway. [ABSTRACT FROM AUTHOR]

Nonalcoholic steatohepatitis (NASH) is a critical stage in the progression of nonalcoholic fatty liver disease (NAFLD). Tanshinone IIA (TIIA) is a tanshinone extracted from Salvia miltiorrhiza; due to its powerful anti-inflammatory and antioxidant biological activities, it is commonly used for treating cardiovascular and hepatic diseases. A NASH model was established by feeding mice a methionine and choline-deficient (MCD) diet. Liver surface microblood flow scanning, biochemical examination, histopathological examination, cytokine analysis through ELISA, lipidomic analysis, transcriptomic analysis, and Western blot analysis were used to evaluate the therapeutic effect and mechanism of TIIA on NASH. The results showed that TIIA effectively reduced lipid accumulation, fibrosis, and inflammation and alleviated endoplasmic reticulum (ER) stress. Lipidomic analysis revealed that TIIA normalized liver phospholipid metabolism in NASH mice. A KEGG analysis of the transcriptome revealed that TIIA exerted its effect by regulating the PPAR signalling pathway, protein processing in the ER, and the NOD-like receptor signalling pathway. These results suggest that TIIA alleviates NASH by activating the PPARα/FGF21 axis to negatively regulate the ER stress-induced unfolded protein response (UPR). [ABSTRACT FROM AUTHOR]

In the past, conventional Czerny–Turner spectrometers were usually designed to achieve high resolution while often ignoring astigmatism in the sagittal direction. In contrast, by replacing the focusing mirror with a freeform surface in the structure, we can obtain a Czerny–Turner spectrometer with low keystone distortion by controlling the astigmatism. At the same time, the area sensor can receive all of the spectrum from the optical system. In this paper, we briefly describe the formation of keystone distortion and smile in a plane grating. Additionally, the validity of the method is verified through simulation. Finally, we evaluated the smile and keystone distortion of both the initial and final systems. The keystone and smile were reduced to 1.77 μm and 8.3 μm, respectively, over the wavelength range of 535 nm to 630 nm. Concurrently, the resolution achieved was 0.4 nm. [ABSTRACT FROM AUTHOR]

The arid and semi-arid region of Northwest China plays a significant role in potato production, yet yields are often hampered by drought due to limited precipitation and irrigation water. The ridge–furrow rainwater-harvesting technology is an efficient and widely used technique to relieve drought impact and improve crop yield by changing the micro-topography to harvest rainwater to meet the water demand of crops. An analysis of precipitation, water demand, and runoff data spanning 30 years guided the selection of suitable rainwater-harvesting methods tailored to meteorological conditions. The results showed that potato water demand exceeded precipitation in the region. The mulching approach performed best in the western arid region with the most significant increase in yield and water use efficiency (WUE) and was suitable for the western semi-arid region and the agro-pastoral ecotone. In the potato dryland farming areas, the water deficit increased from southeast to northwest. Specifically, northern Gansu, northern Ningxia, and midwestern Inner Mongolia experienced a water deficit of over 200 mm, and rainwater harvesting combined with irrigation was recommended. Conversely, regarding deficits below 200 mm in southern Gansu, Ningxia, and central Inner Mongolia, a 1:1 or 2:1 pattern of ridges could be applied, and mulching was needed only in the necessary areas. For the southern Qinghai, Shaanxi, and eastern Inner Mongolia regions, ridge–furrow rainwater harvesting could be replaced by flat potato cropping. In summary, rainwater harvesting addresses water deficits, aiding climate adaptation in Northwest China's arid and semi-arid regions. The implementation of mulching and ridge–furrow technology must be location-specific. [ABSTRACT FROM AUTHOR]

The performance of corrosion-induced cracking of reinforced concrete members under transverse constraints was studied. Based on the theory of elastic-plastic mechanics and the hypothesis of uniform corrosion of a steel bar, a three-layer hollow cylinder model was established to predict the critical corrosion of the steel bar at the time of the cracking of the concrete cover. Taking the constraint of stirrups on surrounding concrete into consideration, it can be used to predict the corrosion rate of members with stirrups at the time of the cracking of the concrete cover, which further expands the application range of the corrosion-induced cracking models of concrete. On this basis, the critical corrosion rate of concrete under different stirrup ratios at the time of cracking was measured. The calculated results of the model are in accordance with experimental data. For corner steel bars, when the stirrup spacing is less than 100 mm, the existence of stirrups can effectively delay the occurrence of rust expansion cracks and enhance the durability of the structure. On the basis of this study, the problem of corrosion expansion and cracking of the concrete cover caused by non-uniform corrosion of steel bars along longitudinal and radial directions needs to be further studied in the future. [ABSTRACT FROM AUTHOR]

Digital sports, also known as online sports, are a new form of sport that users have tried in recent years. Despite the rapid growth of online sports, the factors influencing users' willingness to sustain their use are currently unknown. Based on the theory of planned behavior (TPB) and expectation-confirmation theory (ECT), this study empirically investigates the factors influencing the persistent use of online sports videos. Questionnaires were administered to participants. A total of 305 participants completed the questionnaire. Structural equation modeling showed that all hypotheses' paths were significant, except for H11 and H12. The results indicated that perceived usefulness, expectation confirmation, and coach social presence had a significant positive effect on users' satisfaction in using online sports videos. Moreover, satisfaction, behavioral attitudes, subjective norms, and perceived behavioral control had a significant positive effect on users' willingness to consistently use online sports videos, with gender moderating the impact of satisfaction and behavioral attitudes on the willingness to consistently use. We discuss the practical implications and recommendations for applying this study's findings. [ABSTRACT FROM AUTHOR]

Electrochemical sensors play a pivotal role in various fields, such as biomedicine and environmental detection, due to their exceptional sensitivity, selectivity, stability, rapid response time, user-friendly operation, and ease of miniaturization and integration. In addition to the research conducted in the application field, significant focus is placed on the selection and optimization of electrode interface materials for electrochemical sensors. The detection performance of these sensors can be significantly enhanced by modifying the interface of either inorganic metal electrodes or printed electrodes. Among numerous available modification materials, conductive polymers (CPs) possess not only excellent conductivity exhibited by inorganic conductors but also unique three-dimensional structural characteristics inherent to polymers. This distinctive combination allows CPs to increase active sites during the detection process while providing channels for rapid ion transmission and facilitating efficient electron transfer during reaction processes. This review article primarily highlights recent research progress concerning CPs as an ideal choice for modifying electrochemical sensors owing to their remarkable features that make them well-suited for biomedical and environmental applications. [ABSTRACT FROM AUTHOR]

Due to the rare earth supply shortage, ThMn12-type RFe12-based (R is the rare earth element) magnets with lean rare earth content are gaining more concern. Most ThMn12-type RFe12 structures are thermodynamically metastable and require doping of the stabilizing element Ti. However, the Ti-doping effects on the hard magnetic properties of RFe11Ti have not been thoroughly investigated. Herein, based on density functional theory calculations, we report the Ti-doping effects on the phase stability, intrinsic hard magnetic properties and electronic structures of RFe11Ti (R = La, Ce, Pr, Nd, Sm, Y, Zr). Our results indicate that Ti-doping not only increases their phase stability, but also enhances the magnetic hardness of ground-state RFe12 phases. Particularly, it leads to the transition of CeFe11Ti and PrFe11Ti from easy-plane to easy-axis anisotropy. Charge density distributions demonstrate that Ti-doping breaks the original symmetry of the R-site crystal field, which alters the magnetic anisotropy of RFe11Ti. Projected densities of states reveal that the addition of Ti results in the shift of occupied and unoccupied f-electron energy levels of rare earth elements, affecting their magnetic exchange. This study provides an insight into regulating the hard magnetic properties of RFe12-based magnets by Ti-doping. [ABSTRACT FROM AUTHOR]

Vibrio parahaemolyticus can cause acute gastroenteritis, wound infections, and septicemia in humans. The overuse of antibiotics in aquaculture may lead to a high incidence of the multidrug-resistant (MDR) pathogen. Nevertheless, the genome evolution of V. parahaemolyticus in aquatic animals and the mechanism of its antibiotic tolerance remain to be further deciphered. Here, we investigated the molecular basis of the antibiotic tolerance of V. parahaemolyticus isolates (n = 3) originated from shellfish and crustaceans using comparative genomic and transcriptomic analyses. The genome sequences of the V. parahaemolyticus isolates were determined (5.0–5.3 Mb), and they contained 4709–5610 predicted protein-encoding genes, of which 823–1099 genes were of unknown functions. Comparative genomic analyses revealed a number of mobile genetic elements (MGEs, n = 69), antibiotic resistance-related genes (n = 7–9), and heavy metal tolerance-related genes (n = 2–4). The V. parahaemolyticus isolates were resistant to sub-lethal concentrations (sub-LCs) of ampicillin (AMP, 512 μg/mL), kanamycin (KAN, 64 μg/mL), and streptomycin (STR, 16 μg/mL) (p < 0.05). Comparative transcriptomic analyses revealed that there were significantly altered metabolic pathways elicited by the sub-LCs of the antibiotics (p < 0.05), suggesting the existence of multiple strategies for antibiotic tolerance in V. parahaemolyticus. The results of this study enriched the V. parahaemolyticus genome database and should be useful for controlling the MDR pathogen worldwide. [ABSTRACT FROM AUTHOR]

Cassava (Manihot esculenta Crantz) is a staple crop in tropical and subtropical regions, valued for its high starch content in roots. Effective genetic transformation and genome editing of cassava require efficient screening methods for transgenic and edited plants. In this study, a visual selection marker system using an R2R3-MYB transcription factor anthocyanin 1 gene (HbAN1, LOC110667474) from a rubber tree (Hevea brasiliensis Müll. Arg.) has been developed to facilitate the identification of transgenic cassava plants. Transgenic cassava lines expressing HbAN1 accumulated anthocyanins in their leaves, allowing for easy visual identification without the need for destructive assays or specialized equipment. Importantly, the accumulation of anthocyanins did not affect the regeneration or transformation efficiency of cassava. Additionally, the AR-CRISPR/Cas9-gRNA system with the HbAN1 gene as a marker produced MeCDD4 gene-edited cassava mutants with purple leaves, demonstrating successful editing. This anthocyanin-based visual reporter (AR) system will provide an effective tool for genetic transformation and genome editing in cassava. [ABSTRACT FROM AUTHOR]

Gastrodia elata rhizomes have been applied as traditional medicinal materials for thousands of years. In China, G. elata f. elata (red flower and stem, Ge), G. elata f. viridis (green, Gv), and G. elata f. glauca (black, Gg) represent the primary cultivars in artificial cultivation. Although the annual output of G. elata amounts to 150,000 tons, only 20% is Gg. The long production period, low yield, and high quality of Gg led to its extremely high market prices. However, an effective method to identify this crude drug based solely on its morphological or chemical characteristics is lacking. In this study, the complete chloroplast genomes of three G. elata variants were sequenced using the Illumina HiSeq 2500 platform. Another 21 chloroplast genomes from Gastrodia species, which have published in previous reports, were combined and analyzed together. Our results showed that larger genomic sizes, fewer long tandem repeats, and more simple sequence repeats were the major features of the Gg chloroplast genomes. Phylogenetic analysis showed that the Gg samples were separately clustered in a subclade. Moreover, an accession-specific marker was successfully developed and validated for distinguishing additional rhizome samples. Our study provides investigations of the taxonomic relationships of Gastrodia species. The molecular marker will be useful for differentiating Gastrodia products on the market. [ABSTRACT FROM AUTHOR]

The Co3O4 nanowire@NiCo2O4 nanosheet hierarchical array was constructed on Ni foam using hydrothermal and annealing approaches in turn, from which a NiCo2O4 nanosheet could self-assemble on the Co3O4 nanowire. The structure and morphology of the Co3O4 nanowire@NiCo2O4 nanosheet hierarchical array were characterized via XRD, EDS, SEM, and FESEM, respectively. The electrochemical performance of the composite array was measured via a cyclic voltammetry curve, galvanostatic current charge–discharge, charge–discharge cycle, and electrochemical impedance and then compared with the Co3O4 nanowire. The results show that the Co3O4 nanowire@NiCo2O4 nanosheet hierarchical array could reach a high value of 2034 F g−1 at a current density of 2.5 A g−1. After 5000 galvanostatic charge–discharge cycles, the specific capacitance of the Co3O4 nanowire@NiCo2O4 nanosheet hierarchical array could still maintain 94.7% of the original value. Therefore, the Co3O4 nanowire@NiCo2O4 nanosheet hierarchical array would be a desirable electrode material for a high-performance supercapacitor. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) drive is one of the effective methods to develop old oil fields with high water content for tertiary oil recovery and to improve the recovery rate. However, due to the low viscosity of pure CO2, it is not conducive to expanding the wave volume of the mixed phase, which leads to difficulty utilizing the residual oil in vertical distribution and a low degree of recovery in the reservoir. By introducing viscosity enhancers, it is possible to reduce the two-phase fluidity ratio, expanding the degree of longitudinal rippling and oil recovery efficiency. It has been proven that the acetate scCO2 tackifier PVE can effectively tackify CO2 systems. However, little research has been reported on the microscopic viscosity enhancement mechanism of scCO2 viscosity enhancers. To investigate the influence of a vinyl acetate (VAc) functional unit on the viscosity enhancement effect of the CO2 system, PVE (Polymer–Viscosity–Enhance, P-3) was used as the parent, the proportion of VAc was changed, and the molecules P-1 and P-2 were designed to establish a molecular dynamics simulation model for the P-n-CO2 system. The molecules in the system under the conditions of 70 °C-10 MPa, 80 °C-10 MPa, and 70 °C-20 MPa were simulated; the viscosity of the system was calculated; and the error between the theoretical and simulated values of the viscosity in the CO2 system was relatively small. The difference between P-n molecular structure and system viscosity was analyzed at multiple scales through polymer molecular dynamics simulations and used the molecular radial distribution function, system density, accessible surface area, radius of gyration, minimum intermolecular distance, and minimum number of intermolecular contacts as indicators. This study aimed to elucidate the viscosity enhancement mechanism, and the results showed that the higher the proportion of VAc introduced into the molecules of P-n-scCO2 viscosities, the larger the molecular amplitude, the larger the effective contact area, and the greater the viscosity of the system. Improvement in the contact efficiency between the ester group on the P-n molecule and CO2 promotes the onset of solvation behavior. This study on the microscopic mechanism of scCO2 tackifiers provides a theoretical approach for the design of new CO2 tackifiers. [ABSTRACT FROM AUTHOR]

In the context of low-carbon energy transformation, fully utilizing the integrated demand response (IDR) resources on the load side can improve the operational flexibility and economy of the integrated energy system (IES). However, establishing a reasonable trading mechanism to enhance users' participation in IDR has become a key issue that IES urgently needs to solve. To this end, this paper first establishes an IES model that includes electricity, heat, and gas. To reduce carbon emissions, a ladder-type carbon trading mechanism is introduced while adding low-carbon technologies such as carbon capture devices and power-to-gas conversion. Secondly, a bilateral IDR mechanism centered on the load aggregator (LA) is proposed, and a multi-agent operation model including IES, LA, and users is established. The IDR subsidy price is dynamically determined through a two-level Stackelberg game model involving IES, LA, and users. Then, through KKT conditions and the Big M method, the two-level game model is turned into an IES-LA game model, which is solved using a combination of the White Shark Optimization method and the Gurobi solver. The final simulation results show that the scheduling model can fully reflect the time value of IDR resources, and the IES cost is decreased by USD 152.22, while LA and user benefits are increased by USD 54.61 and USD 31.85. Meanwhile, the ladder-type carbon trading mechanism and low-carbon technology have effectively achieved low-carbon operation of the system. [ABSTRACT FROM AUTHOR]

This study focuses on formulating a low-surface-energy, water-resistant, and anti-condensation coating utilizing a fluorocarbon and acrylic resins composite (FAC), enhanced by six functional additives: antistatic agents, water-repellent agents, nanofillers, anti-mold and anti-algae agent, leveling agents, and wetting and dispersing agents. An orthogonal experimental design was implemented to systematically investigate the effects of varying concentrations of these additives on the surface tension of the coating. The results show that the optimized combination of fluorocarbon and acrylic resins composite (OFAC)with functional additives significantly reduces the surface tension, thereby improving both water resistance and anti-condensation properties. This research advances the development of more efficient surface treatment technologies, particularly for applications requiring enhanced water resistance and anti-condensation performance. [ABSTRACT FROM AUTHOR]

Hyperspectral image (HSI) and light detection and ranging (LiDAR) data have gained significant attention due to their excellent complementarity, which can be combined to improve the accuracy of land cover classification. However, there are still many challenges, such as unrelated physical characteristics, different data structures, and a lack of labeled samples. Many methods fail to leverage the full potential of multi-source data, particularly hierarchical complementary information. To address these problems, a hierarchical coarse–fine adaptive (HCFA) fusion network with dynamic convolution and a transformer is proposed for multi-source remote sensing land cover classification. Although fusing hierarchical information can improve the classification accuracy of the model, improper hierarchical feature selection and optimization may negatively affect the classification results. Therefore, a coarse–fine mutual learning strategy is proposed to dynamically fuse hierarchical information. Additionally, the disparity between multi-source data continues to prevent the realization of effective fusion. To tackle this challenge, cross-tokenization and cross-token attention are implemented to enhance information interaction. Furthermore, to improve the model representation with limited computational cost, we combine the advantages of dynamic convolution with a transformer. Validation on three standard datasets demonstrates that HCFA achieves high accuracy with just 1% of the training set while maintaining low computational costs. [ABSTRACT FROM AUTHOR]

Balance control, a complex sensorimotor skill, declines with age. Assessing balance is crucial for identifying fall risk and implementing interventions in the older population. This study aimed to measure age-dependent changes in static and dynamic balance using inertial measurement units in a clinical setting. This study included 82 healthy participants aged 20–85 years. For the dynamic balance test, participants stood on a horizontally swaying balance board. For the static balance test, they stood on one leg. Inertial measurement units attached to their bodies recorded kinematic data, with average absolute angular velocities assessing balance capabilities. In the dynamic test, the younger participants had smaller average absolute angular velocities in most body parts than those of the middle-aged and older groups, with no significant differences between the middle-aged and older groups. Conversely, in the single-leg stance tests, the young and middle-aged groups outperformed the older group, with no significant differences between the young and middle-aged groups. Thus, dynamic and static balance decline at different stages with age. These results highlight the complementary role of inertial measurement unit-based evaluation in understanding the effect of age on postural control mechanisms, offering valuable insights for tailoring rehabilitation protocols in clinical settings. [ABSTRACT FROM AUTHOR]

Nanomedicine holds great potential for revolutionizing medical treatment. Ongoing research and advancements in nanotechnology are continuously expanding the possibilities, promising significant advancements in healthcare. To fully harness the potential of nanotechnology in medical applications, it is crucial to conduct safety evaluations for the nanomedicines that offer effective benefits in the preclinical stage. Our recent efficacy studies indicated that rapamycin perfluorocarbon (PFC) nanoparticles showed promise in mitigating cisplatin-induced acute kidney injury (AKI). As cisplatin is routinely administered to ovarian cancer patients as their first-line chemotherapy, in this study, we focused on evaluating the safety of rapamycin PFC nanoparticles in mice bearing ovarian tumor xenografts. Specifically, this study evaluated the effects of repeat-dose rapamycin PFC nanoparticle treatment on vital organs, the immune system, and tumor growth and assessed pharmacokinetics and biodistribution. Our results indicated that rapamycin PFC nanoparticle treatment did not cause any detectable adverse effects on cardiac, renal, or hepatic functions or on splenocyte populations, but it reduced the splenocyte secretion of IL-10, TNFα, and IL12p70 upon IgM stimulation. The pharmacokinetics and biodistribution results revealed a significant enhancement in the delivery of rapamycin to tumors by rapamycin PFC nanoparticles, which, in turn, led to a significant reduction in ovarian tumor growth. Therefore, rapamycin PFC nanoparticles have the potential to be clinically beneficial in cisplatin-treated ovarian cancer patients. [ABSTRACT FROM AUTHOR]

Based on the Bayesian framework, a time domain method is proposed for the uncertain quantification of structural modal identification. First, a theoretical prediction model is constructed from the state space model in modal space and then transformed into physical space using the modal basis. Second, taking into account the uncertainty of the identification results caused by measurement noise and modeling errors, the negative log-likelihood function is constructed using time domain measurement data and a theoretical prediction model based on the Bayesian system identification framework. Finally, an unconstrained quadratic function for the identification parameters is derived through matrix vectorization, and, by mathematically transforming the optimization problem, only the dynamic spectral parameters (the natural frequencies and damping ratios) need to be identified, while the spatial parameters (the mode shapes and modal contribution factors) can be analytically calculated from the spectral parameters, which greatly reduces the dimensionality of the identification parameters. In numerical examples, the identification of the modal parameters for a spring–mass system and high-speed pantograph was studied, and the identified modal parameters based on the simulation response's data were in good agreement with the theoretical values. Moreover, the modal parameters of the actual structure of the pantograph were identified based on the experimental data, and the identifying uncertainties were quantified by the coefficient of variation. [ABSTRACT FROM AUTHOR]

To meet the needs of industrial and environmental monitoring of methane and ethane flammable gases, a low-stress filter device for detecting methane and ethane simultaneously is developed based on the absorption spectra of methane and ethane and the thin-film design theory. In order to improve the sensitivity of the detection system and reduce the influence of environmental noise, the information of methane and ethane gas is extracted simultaneously by using a filter with double bandpass and wide cut-off in the middle-infrared and far-infrared bands. The transmittance of the filter is 91.3%, 93.1%, and 93.02% at the wavelengths of 3.31 μm, 6.71 μm, and 7.67 μm, respectively. The cut-off depth in the cut-off interval is above OD3, which meets the system's requirements. [ABSTRACT FROM AUTHOR]

The stochastic Green's function method has been widely used in the field of ground motion simulation in recent years. It is generally assumed that the rise time of each subfault is the same in this method. Since the rise time significantly influences the amplitude of simulation results in the intermediate frequency band, to improve the accuracy of stochastic Green's function method for near-fault broadband ground motion simulation, referring to the numerical simulation results of Day, the rise time is assumed to be non-uniformly distributed on the fault, and an improved approximate expression of rise time on a rectangular fault considering that the rupture starting point may be at any position and the aspect ratio may be arbitrary is proposed. Additionally, the contributions of P, SV and SH wave are considered, respectively, and an improved stochastic Green's function method is proposed for 3D broadband ground motion simulation. Taking the 1994 Northridge earthquake in America and 2013 Lushan earthquake in China as examples, under different subfault division numbers, the synthesized source spectra are compared with the omega-squared theoretical source spectra of the large earthquake, and the simulated ground motions at observation points are compared with observed records to verify the effectiveness of the improved method. The results show that when the Northridge earthquake fault and Lushan earthquake fault are divided into 9 × 10 subfaults and 11 × 7 subfaults, respectively, the simulation results obtained using the improved method are close to the observed records in the broadband frequency range. Therefore, the improved method can effectively simulate the 3D ground motion in near-fault regions. [ABSTRACT FROM AUTHOR]

With the rapid development of intelligent transportation systems and information technology, the security of road traffic signal systems has increasingly attracted the attention of managers and researchers. This paper proposes a new method for detecting attacks on traffic signal systems based on game theory and Generative Adversarial Networks (GAN). First, a game theory model was used to analyze the strategic game between the attacker and the defender, revealing the diversity and complexity of potential attacks. A Bayesian game model was employed to calculate and analyze the attacker's choice of position. Then, leveraging the advantages of GAN, an adversarial training framework was designed. This framework can effectively generate attack samples and enhance the robustness of the detection model. Using empirical research, we simulated the mapping of real traffic data, road network data, and network attack data into a simulation environment to validate the effectiveness of this method. In a comparative experiment, we contrasted the method proposed in this paper with the traditional Support Vector Machine (SVM) algorithm, demonstrating that the model presented here can achieve efficient detection and recognition across various attack scenarios, with significantly better recall and F1 scores compared to traditional methods. Finally, this paper also discusses the application prospects of this method and its potential value in future intelligent transportation systems. [ABSTRACT FROM AUTHOR]

In order to achieve multi-objective optimization for a permanent magnet water pump motor in heavy commercial vehicles, we propose a strategy based on response-surface methodology and the improved sparrow algorithm (CGE-SSA). Firstly, the output capacity of the pump during actual operation was tested with an experimental bench to determine the design parameters of the motor, and then its modeling was completed using Ansys Maxwell 2022r2 software. Secondly, the response-surface model was established by taking the parameters of permanent magnet width, rib width, and slot width as optimization parameters and the output torque (Ta), torque ripple (Tr), and back electromotive force (EMF) amplitude as optimization objectives. Meanwhile, three methods—namely, circular sinusoidal chaotic mapping, improved golden sinusoidal strategy, and adaptive weight coefficients—were used to improve the convergence speed and accuracy of the sparrow search algorithm (SSA). Finally, the multi-objective optimization of the permanent magnet synchronous motor was completed using the improved sparrow algorithm. A comparative analysis of the motor's output before and after optimization showed that the torque pulsation and reverse electromotive force of the motor were significantly improved after optimization. [ABSTRACT FROM AUTHOR]

To facilitate the maintenance of hidden frame glass curtain walls, it is necessary to identify the damage location of the structural sealant accurately. However, detecting concealed sealant damage directly is challenging. This paper proposes a two-stage damage localization method to pinpoint the center of damaged structural sealants. In the first stage, an assurance criterion of boundary modal curvature (ACBMC) is developed to identify damaged edges. In the second stage, the exact damage location is determined by comparing the differences in boundary modal curvature between the undamaged and damaged edges. Two-panel units are analyzed by numerical and model experiments. The results show that the proposed method can effectively identify the damage location of the structural sealant when the damage severity is higher than 4%. [ABSTRACT FROM AUTHOR]

With the continuous increase in global greenhouse gas emissions, the impacts of climate change are becoming increasingly severe. In this context, geothermal energy has gained significant attention due to its numerous advantages. Alongside advancements in CO2 geological sequestration technology, the use of CO2 as a working fluid in geothermal systems has emerged as a key research focus. Compared to traditional water-based working fluids, CO2 possesses lower viscosity and higher thermal expansivity, enhancing its mobility in geothermal reservoirs and enabling more efficient heat transfer. Using CO2 as a working fluid not only improves geothermal energy extraction efficiency but also facilitates the long-term sequestration of CO2 within reservoirs. This paper reviews recent research progress on the use of CO2 as a working fluid in Enhanced Geothermal Systems (EGS), with a focus on its potential advantages in improving heat exchange efficiency and power generation capacity. Additionally, the study evaluates the mineralization and sequestration effects of CO2 in reservoirs, as well as its impact on reservoir properties. Finally, the paper discusses the technological developments and economic analyses of integrating CO2 as a working fluid with other technologies. By systematically reviewing the research on CO2 in EGS, this study provides a theoretical foundation for the future development of geothermal energy using CO2 as a working fluid. [ABSTRACT FROM AUTHOR]

The influence of carrier mobility on the space charge transport behavior inside the oil-impregnated pressboard insulation of converter transformers cannot be neglected. However, at present, current knowledge is usually derived from empirical or theoretical values, lacks experimental studies, and often ignores the effects of temperature and field strength under actual operating conditions. In this paper, based on the variable-temperature surface potential decay (SPD) method, a carrier mobility measurement platform for oil-impregnated pressboard is established, and the carrier mobility values for different combinations of oil and oil-impregnated pressboard are obtained experimentally to analyze and reveal the influence mechanisms of temperature and field strength on the carrier mobility. The results indicate the following: (1) The positive and negative carrier mobilities of oil-impregnated pressboard are in the range of 10−12–10−13 m2·V−1·s−1, and the negative carrier mobility is always higher than the positive carrier mobility. (2) The carrier mobility is positively correlated with the changes of temperature and field strength, and when the temperature increases from 20 °C to 80 °C, the positive and negative carrier mobilities increase by 4.01 times and 4.72 times, respectively; when the field strength increases from 1 kV/mm to 7 kV/mm, the positive and negative carrier mobility increases by 2.53 and 2.72 times, respectively. (3) The carrier mobility of the pressboard with a higher oil absorption rate changes more significantly with temperature; when the field strength is 7 kV/mm and the temperature increases from 20 °C to 80 °C, the positive polarity carrier mobility increases from 3.96 × 10−13 m2·V−1·s−1 to 2.64 × 10−11 m2·V−1·s−1, an increase of 66.67 times, while the increase in the carrier mobility of the pressboard with a lower oil absorption rate is only 1.59 times. (4) The carrier mobility of the naphthenic transformer oil-impregnated pressboard is higher than that of the paraffin-based transformer oil-impregnated pressboard, and the carrier mobility of two kinds of naphthenic transformer oil-impregnated pressboard is 3.16 times and 2.47 times higher than that of the paraffin-based transformer oil-impregnated pressboard, respectively, under the conditions of 60 °C and 7 kV/mm. (5) Utilizing the Darcy model and microscopic scanning results of the pressboard morphology, it was revealed that permeability and fiber structure are key factors influencing the variation in carrier mobility. The research results of this paper can provide theoretical basis for the calibration and optimization of the oil-pressboard insulation structure of converter transformers. [ABSTRACT FROM AUTHOR]

The large-scale storage and stable supply of oil products are essential for national energy security and economic development. As the economy expands and energy demands rise, centralized storage and supply systems become increasingly vital for ensuring the efficiency and reliability of oil product distribution. However, large oil storage depots present substantial safety risks. In the event of fires, explosions, or other accidents, emergency response efforts face stringent demands and challenges. To enhance the emergency response capabilities of oil storage and transportation bases (OSTBs), this paper proposes an innovative approach that integrates the improved analytic hierarchy process (IAHP) with the Entropy Weight Method (EMW) to determine the combined weights of various indices. This approach reduces the subjective bias associated with the traditional analytic hierarchy process (AHP). The emergency response capabilities of OSTBs are subsequently evaluated through fuzzy comprehensive analysis. An empirical study conducted on an OSTB in the Zhoushan archipelago quantitatively assesses its emergency preparedness. The results show that the base excels in pre-incident prevention, demonstrates robust preparedness and response capabilities, and exhibits moderate recovery abilities after incidents. These findings provide a theoretical foundation for reducing the likelihood of accidents, enhancing emergency response efficiency, and mitigating the severity of consequences. Practical recommendations are also offered based on the results. [ABSTRACT FROM AUTHOR]

Background: Neuronal excitotoxicity and metabolic decline, which begin in the early stages of Alzheimer's disease (AD), pose challenges for effective amelioration. Our previous work suggested that the natural compound xanthohumol, the most abundant prenylated flavonoid in hops, prevents memory deficits in APP/PS1 mice; however, the underlying mechanisms remain unclear. Methods: This study utilized APP/PS1 mice and cutting-edge omics techniques to investigate the effects of xanthohumol on hippocampal proteome, serum metabolome, and microbiome. Results: Our findings revealed that xanthohumol reduces the postsynaptic overexpression of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid, N-methyl-D-aspartate, and metabotropic glutamate receptors, but enhances ATP synthesis and mitophagy in the young AD hippocampus. Further mechanistic analyses suggested systemic regulatory effects, particularly on the decreasing glutamate synthesis in the blood and intestines of AD mice following xanthohumol administration. Conclusions: These results underscore the potential of xanthohumol in mitigating AD pathology through multifaceted mechanisms, sparking interest and curiosity in its preventive and therapeutic potential in AD. [ABSTRACT FROM AUTHOR]

Background: Sodium benzoate (SB) is widely used in food products, cosmetics, and medical solutions due to its antimicrobial properties. While it is generally considered safe and has potential neuroprotective benefits, SB has also been linked to adverse effects, including hepatic oxidative stress and inflammation. However, the potential effects of SB on obesity and lifespan remain poorly understood. Objectives: In this study, we investigated the effects of SB on fat accumulation and lifespan using the nematode Caenorhabditis elegans (C. elegans) as a model system. Methods: Wild-type worms were exposed to various SB concentrations (0%, 0.0004%, 0.0008%, 0.004%, and 0.1%) and 0.016% glucose as a positive control for 72 h in liquid or on NGM agar plates. Result: Fat accumulation was assessed through the Oil Red O staining, which revealed that SB induced more fat accumulation compared to vehicle control, even at low concentrations, including the dosage of 0.0004%. Lifespan analysis also demonstrated that SB significantly reduced lifespan in wild-type worms, even at low concentrations. Further investigations found that SKN-1 (an Nrf2 homolog) is necessary for SB-induced fat accumulation and lifespan reduction. Moreover, SB inhibited the nuclear localization of SKN-1 under oxidative stress conditions. Conclusion: These findings suggest that SB may induce fat accumulation and reduce lifespan by inhibiting the oxidative stress-mediated SKN-1 signaling pathway. [ABSTRACT FROM AUTHOR]

Background: This cross-sectional study aimed to examine the association between dietary diversity and risk of subjective cognitive decline (SCD), a precursor of dementia, in middle-aged and elderly Chinese populations residing in eastern China. Methods: Participants aged ≥ 45 years were recruited from a community in an eastern Chinese city after excluding potential objective cognitive impairment using the Mini-Cognitive Assessment Instrument (Mini-Cog). SCD was assessed using the Subjective Cognitive Decline Questionnaire-9 (SCD-Q9). Dietary data were collected using the Dietary Quality Questionnaire (DQQ), and the Food Group Diversity Score (FGDS) and the Consumed All Five Recommended Food Score (All-5) were calculated as indicators of dietary diversity. Odds ratios (ORs) and 95% confidence intervals (CIs) were computed to evaluate the associations of FGDS and All-5 scores with SCD after adjusting for age, sex, socioeconomic status, lifestyle factors, and health status. Results: Among the 871 participants, 358 (41.1%) were classified as having SCD. Compared with participants with the highest FGDS (≥8) and those with the highest All-5 score (5), those with the lowest FGDS (≤4) and the lowest All-5 score (≤3) exhibited 85% (OR = 1.85; 95% CI: 1.10–3.13; p = 0.02) and 90% (OR = 1.90; 95% CI: 1.21–2.97; p < 0.01) higher risk of SCD, respectively, after adjusting for all covariates. Fruits were the only food group among the All-5 components that demonstrated a significant association with SCD risk. Conclusions: Poor dietary diversity was associated with an elevated risk of SCD in middle-aged and older adults, and fruits were the food group with the most substantial effect. [ABSTRACT FROM AUTHOR]

Topography is one of the dominant factors in regional soil formation and development. Soil distribution has a certain pattern from high to low in space, and this pattern has a high degree of consistency with slope position. Most of the current research on soil mapping uses landscape types generated by existing methods directly as environmental covariates, and there are few landscape classification methods specifically oriented toward soil surveys. There is rarely any research on landform classification using relative slope position (RSP) and elevation. Therefore, we designed a landform classification method based on RSP and elevation, Terrainforms (TF), and combined the landform type with land use type to construct soil–landscape units for soil type and attribute spatial prediction. In this study, two commonly used landform classification methods, Geomorphons and Landforms, were also used to compare with this design method. It was found that the constructed soil–landscape units had a high consistency with the soil spatial distribution. The landform types based on RSP and elevation obtained the second-highest prediction accuracy in both soil type and soil organic carbon (SOC), and the constructed soil–landscape types obtained the highest prediction accuracy. The results show that the landform classification method based on RSP and elevation is not easily limited by the analysis scale, and is an efficient and accurate landform classification method. The TF landform type and its constructed soil–landscape types can be used as an important environmental variable in soil prediction and sampling, which can provide some guidance and reference for landform classification and digital soil mapping. [ABSTRACT FROM AUTHOR]

In recent years, deep learning-based multi-source data fusion, e.g., hyperspectral image (HSI) and light detection and ranging (LiDAR) data fusion, has gained significant attention in the field of remote sensing. However, the traditional convolutional neural network fusion techniques always provide poor extraction of discriminative spatial–spectral features from diversified land covers and overlook the correlation and complementarity between different data sources. Furthermore, the mere act of stacking multi-source feature embeddings fails to represent the deep semantic relationships among them. In this paper, we propose a cross attention-based multi-scale convolutional fusion network for HSI-LiDAR joint classification. It contains three major modules: spatial–elevation–spectral convolutional feature extraction module (SESM), cross attention fusion module (CAFM), and classification module. In the SESM, improved multi-scale convolutional blocks are utilized to extract features from HSI and LiDAR to ensure discriminability and comprehensiveness in diversified land cover conditions. Spatial and spectral pseudo-3D convolutions, pointwise convolutions, residual aggregation, one-shot aggregation, and parameter-sharing techniques are implemented in the module. In the CAFM, a self-designed local-global cross attention block is utilized to collect and integrate relationships of the feature embeddings and generate joint semantic representations. In the classification module, average polling, dropout, and linear layers are used to map the fused semantic representations to the final classification results. The experimental evaluations on three public HSI-LiDAR datasets demonstrate the competitiveness of the proposed network in comparison with state-of-the-art methods. [ABSTRACT FROM AUTHOR]

To control energy consumption, China issued the environmental regulation policy of the Top-1000 Energy-Saving Program in 2006, and it remains to be examined whether this policy will impact enterprises' labor demand while promoting energy conservation and consumption reduction. Based on the panel data of Chinese enterprises (2000–2010), this study employs the difference-in-differences (DID) method to investigate the impact of the Top-1000 Energy-Saving Program on the labor demand of enterprises. It is found that the policy significantly reduces enterprises' labor demand, a finding that passes several robustness tests. Second, the effects of the policy show heterogeneity across enterprises of various sizes, ownership structures, and regions. Finally, the mechanism analysis verifies the existence of an output effect leading to a decline in enterprises' labor demand, while the substitution effect manifests itself in the substitution of enterprises' labor demand with the increase of capital and technological innovation. This study provides important empirical evidence for the improvement of energy efficiency policies. [ABSTRACT FROM AUTHOR]

Damping is a fundamental characteristic of bridge structures, reflecting their ability to dissipate energy during vibration. In the design and maintenance of bridges, the damping ratio has a direct impact on the safety and service life of the structure, thus affecting its sustainability. Currently, there is no suitable theoretical method for estimating structural damping at the design stage. Therefore, the modal damping ratio of a completed or under-construction bridge can only be obtained through field dynamic tests to ensure compliance with design specifications. To summarize the latest research findings on bridge structure damping models and identification methods, and to advance the development of damping identification techniques, this paper provides an in-depth review from several perspectives: Firstly, it offers a comprehensive analysis of the theoretical framework for structural damping. Secondly, it summarizes the damping models proposed by researchers from various countries. Thirdly, it reviews the research progress on identifying the modal damping ratio of bridge structures using time domain, frequency domain, and time-frequency domain methods based on environmental excitation. It also summarizes the methods and current status of identifying the modal damping ratio using artificial excitation. Finally, the future prospects and conclusions are discussed from three aspects: damping theory, test and identification method and data processing. This research and summary provide a solid theoretical foundation for advancing bridge structural damping theory and identification methods and offer valuable references for bridge operation and maintenance, as well as damage identification. From the perspective of modal parameter identification, it provides a theoretical basis for the sustainable development of bridges. [ABSTRACT FROM AUTHOR]

Plastic waste has been gradually accumulating in the environment due to rapid population growth and increasing consumer demand, posing threats to both the environment and human health. In this overview, we provide a comprehensive understanding of the degradation of plastics in real environments, such as soil, aquatic environment, landfill, and compost. Both conventional and biodegradable plastics exhibit limited degradation in real environments, except for biodegradable plastics during industrial composting with high thermophilic temperatures. Meanwhile, we also review techniques for enhanced degradation of plastics such as physical technologies (e.g., photocatalysis, mechanical degradation, and pyrolysis), chemical technologies (e.g., hydrolysis, alcoholysis, ammonia, strong oxidation, and supercritical fluids), and biotechnologies (e.g., microorganisms, microfauna, and microalgae). The future research directions for the enhancement of plastic degradation are also discussed, such as the establishment of equivalency standards, adoption of internal control techniques, the control of precise recycling of plastic products, and the ecotoxicology of their degradation products. Therefore, this review comprehensively summarizes the state of plastic degradation in real environments and proposes methods to improve plastic degradation, providing a theoretical basis for the future control and disposal of plastics. [ABSTRACT FROM AUTHOR]

Since the onset of Supply chain management has gained maximum recognition, with many countries elevating supply chain levels at the strategic level. This article selects AH Company's supply chain network as the research object, analyzes the main challenges faced by the company in the supply chain aspect, and evaluates its original supply chain network. It incorporates sustainable development factors into the current global supply chain management theme, taking into account four aspects: total supply chain cost, service level, corporate sustainable development vision (carbon emissions), and supply chain risks. The "Supply Chain Guru X (2022)" software is applied to propose optimization solutions for existing problems on the basis of the original supply chain network. Based on the existing data, a comprehensive comparison of the advantages and disadvantages of various optimization schemes is implemented to select the current optimal supply chain network optimization scheme. In the process of optimizing the plan, the multi-objective optimization theory and big data processing technology were emphasized, and the corresponding technical theories were integrated into the "Supply Chain Guru X (2022)" software. By optimizing the supply chain network of AH Company, the overall operating costs of the company's supply chain network have been significantly reduced while meeting customer needs. Concurrently, it can provide a good example for optimizing the supply chain network of similar enterprises. [ABSTRACT FROM AUTHOR]