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Long-tailed data distribution (i.e., minority classes occupy most of the data, while most classes have very few samples) is a common problem in image classification. In this paper, we propose a novel multimodal framework for long-tailed data recognition. In the first stage, long-tailed data are used for visual-semantic contrastive learning to obtain good features, while in the second stage, class-balanced data are used for classifier training. The proposed framework leverages the advantages of multimodal models and mitigates the problem of class imbalance in long-tailed data recognition. Experimental results demonstrate that the proposed framework achieves competitive performance on the CIFAR-10-LT, CIFAR-100-LT, ImageNet-LT, and iNaturalist2018 datasets for image classification. [ABSTRACT FROM AUTHOR]

Trehalose is crucial for the stress resistance of Saccharomyces cerevisiae, primarily through its stabilization of proteins and membranes. The Agt1 transporter, a member of the Major Facilitator Superfamily, mediates trehalose uptake, a key process for maintaining cellular integrity under stress. Despite its importance, the molecular mechanisms of Agt1-mediated trehalose transport remain underexplored. In this study, we expressed and purified the trehalase enzyme TreA from E. coli to develop reliable trehalose assays. We screened 257 wild S. cerevisiae isolates, identifying strains with enhanced trehalose transport capacities. Comparative analyses, including structural modeling and molecular docking, revealed that specific Agt1 variants exhibited significantly higher transport efficiency, influenced by key residues in the transporter. Molecular dynamics simulations and steered molecular dynamics provided further insights, particularly into the role of the Agt1 channel head region in substrate recognition and binding. Site-directed mutagenesis validated these findings, showing that mutations at critical residues, such as 156Q, 164L, 256Q, 395E, 396R, and 507Y significantly reduced transport activity, while 137Q, 230T, and 514 N increased efficiency under certain conditions. [ABSTRACT FROM AUTHOR]

Five layers of detrital amphiboles in the CJ08-008 sediment core from the northwest Indian Ocean have been found. To analyze their genetic types and provenance, an electron probe microanalysis of 300 amphibole grains from the core was conducted to calculate the numerical and characteristic values of cations in the crystal structure. The results showed that amphiboles with high Si, Ca, and Mg contents and low Na and K contents exhibit a low degree of weathering and that amphiboles mainly comprise tschermakite (46.43~70.69%), followed by magnesiohornblende, in the calcic amphibole subgroup. The types of sources for these amphiboles are mainly different types of metamorphic and magmatic rock. A large proportion of the detrital amphiboles (>60%) are derived from metamorphic rocks, followed by intermediate acid-intrusive rocks. The genetic analysis of amphiboles showed that most of the medium acid-intrusive amphiboles belong to the crust–mantle type, followed by the mantle type. Most of the amphiboles of metamorphic origin are of the low-pressure type. The amphiboles in the CJ08-008 sediment core exhibit characteristics different from those brought by monsoons from surrounding land masses. The variations in the amphiboles indicate different sources, which may have different origins; these origins could include the Carlsberg Ridge, the Owen Fault Zone, or older submarine sediment sequences eroded by turbidity currents. [ABSTRACT FROM AUTHOR]

This study employed atomic layer deposition (ALD) to fabricate an Al2O3 passivation layer to optimize the performance of ultraviolet (UV) photodetectors with a TiO2-nanorod-(NR)-containing active layer and a solid–liquid heterojunction (SLHJ). To reduce the processing time and enhance light absorption, a hydrothermal method was used to grow a relatively thick TiO2-NR-containng working electrode. Subsequently, a 5-nm-thick Al2O3 passivation layer was deposited on the TiO2 NRs through ALD, which has excellent step coverage, to reduce the surface defects in the TiO2 NRs and improve the carrier transport efficiency. X-ray photoelectron spectroscopy revealed that the aforementioned layer reduced the defects in the TiO2 NRs. Moreover, high-resolution transmission electron microscopy indicated that following the annealing treatment, Al, Ti, and O atoms diffused across the interface between the Al2O3 passivation layer and TiO2 NRs, resulting in the binding of these atoms to form Al–Ti–O bonds. This process effectively filled the oxygen vacancies in TiO2. Examination of the photodetector device revealed that the photocurrent-to-dark current ratio exhibited a difference of four orders of magnitude (10−4 to 10−8 A), with the switch-on and switch-off times being 0.46 and 3.84 s, respectively. These results indicate that the Al2O3 passivation layer deposited through ALD can enhance the photodetection performance of SLHJ UV photodetectors with a TiO2 active layer. [ABSTRACT FROM AUTHOR]

The Apollo basin is a well-preserved double-ringed impact basin located on the northeastern edge of the South Pole–Aitken (SPA) basin. The Apollo basin has been flooded and filled with large volumes of mare lavas, indicating an active volcanism history. Based on orbital data, we reveal that the Apollo basin exhibits an overall asymmetric configuration in the distribution of mare basalts as well as its topography, chemical compositions, and crustal thickness. The Apollo basin is an excellent example for assessing the influences of the above factors on mare basalts petrogenesis and evaluating mare basalt genesis models. It was found that the generation of mare basalt magmas and their emplacement in the Apollo basin seems to be strongly related to local thin crust (<30 km), but the formation of basaltic magmas should be independent of the decompression melting because the mare units (3.34–1.79 Ga) are much younger than the pre-Nectarian Apollo basin. The mare basalts filled in the Apollo basin exhibits a large variation of TiO2 abundances, indicating the heterogeneity of mantle sources, which is possible due to the lunar mantle overturn after the LMO solidification or the impact-induced mantle convection and migration. However, the prolonged mare volcanic history of the Apollo basin is not well explained, especially considering the low Th abundance (<2 ppm) of this region. In addition, the central mare erupted earlier than other mare units within the Apollo basin, which seems to contradict the predictions of the postbasin loading-induced stresses model. Laboratory investigations of the Chang'E-6 mare basalt samples could possibly answer the above questions and provide new insight into the mare volcanic history of the lunar farside and the connections between mare volcanism and impact basin formation/evolution. [ABSTRACT FROM AUTHOR]

To address current product styling design issues, such as ignoring the joint effects of multiple styling elements when constructing perceptual imagery fitting models and thus failing to effectively identify the relationships between styling elements, a product styling design method based on fuzzy set qualitative comparative analysis (fsQCA) is proposed. This method first uses semantic differential and statistical methods to obtain users' evaluative vocabulary for the product's perceptual imagery. Then, morphological analysis and cluster analysis are employed to establish typical product samples and extract styling elements to create a styling feature library. Perceptual imagery ratings of these styling features are obtained through expert evaluation. fsQCA is then used to analyze the different grouping relationships between styling elements and their influence on product styling imagery, aiming to match user intentions through different element combination paths. The results show that this method achieves a consistency value of 0.9 for the most optimal styling configurations, demonstrating that fsQCA can effectively identify the multiple paths of product styling elements that meet users' needs. The contributions of this study to the related fields are: (1) providing a new perspective on the relationship between user perceptual imagery and predicted product styling elements, and (2) advancing the theoretical basis for studying multiple paths of product styling elements. The research results demonstrate that using the fsQCA-based product styling design method can accurately portray the multiple paths of product styling elements that meet users' needs, thereby effectively improving design efficiency. Finally, a teapot styling design study is used as an example to further verify the method's feasibility. [ABSTRACT FROM AUTHOR]

In the traditional decision-making process for product form design, designers and experts often prioritize schemes based on their own knowledge and experience. This approach can lead to an oversight of user preferences, ultimately affecting decision outcomes. In contrast, crowd-intelligence-driven, multi-attribute decision-making for product form design in the cloud environment builds upon traditional approaches by leveraging the vast and diverse expertise of individuals on cloud platforms, engaging participants from various fields and roles in the decision-making process to enhance comprehensiveness and accuracy. To address the issue of a single decision-maker and limited user participation in the decision-making process for product form design schemes in the cloud environment, a multi-attribute decision-making method integrating expert knowledge and user preferences is proposed. This method aims to select a product form design scheme that optimally balances expert and user satisfaction. Initially, the Pythagorean Hesitant Fuzzy Set (PHFS) is used to quantify qualitative product attributes and to establish a comprehensive multi-attribute evaluation system. In the aspect of expert decision-making, a gray correlation coefficient decision matrix based on expert knowledge is established and the overall score of the base alternative is calculated by the ViseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method and the Improved Osculating Value method. In terms of user decision-making, weights are determined by calculating the similarity between user evaluation matrices, and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is used to calculate scores for product form designs based on user preferences. Ultimately, optimal selection is achieved by aggregating the aforementioned expert evaluation values and user preference values. The method's effectiveness and feasibility are confirmed through a case study of coffee machine product form design schemes. [ABSTRACT FROM AUTHOR]

Aquavoltaics is an innovative and beneficial solution that makes dual use of water area for photovoltaic (PV) power generation and aquaculture. Currently, China has made remarkable developments in aquavoltaics. This paper first analyzes the current development status of aquavoltaics in China, then takes the TW "fishery–PV integration" base project in Nanjing, Jiangsu Province, as a case study to analyze its economic and social benefits, and finally puts forward countermeasure suggestions for the development of aquavoltaics in China. It is found that Jiangsu Province is one of the clustering areas for the development of aquavoltaics in China, and the development of aquavoltaics in this province has a high level of specialization. The payback period (PP) of the TW "fishery–PV integration" base project is 10.44 years, the net present value (NPV) is USD 18.5334 million (the discount rate is 5%), and the internal rate of return (IRR) is 8.06%. The social benefits of this project are mainly reflected in the promotion of energy conservation and emission reduction, the alleviation of energy shortages, the optimization of land use, and the development of culture, tourism, science, and education. The development of aquavoltaics should be promoted by strengthening scientific research, paying attention to the impact of PV panel erection on the ecological environment of the waters, emphasizing the fishery farming part of the aquavoltaic project, and improving the commercial operation mode of the aquavoltaic project. [ABSTRACT FROM AUTHOR]

The Discrete Element Method (DEM) is an important tool for investigating the geotechnical properties of lunar regolith. The accuracy of DEM simulations largely depends on precise particle modeling and the appropriate selection of mesoscopic parameters. To enhance the reliability and accuracy of the DEM in lunar regolith studies, this paper utilized the high-fidelity IRSM-1 lunar regolith simulant to construct a DEM model with realistic particle shapes and conducted an angle of repose (AoR) simulation test. The optimal DEM parameters were calibrated using a combination of the Plackett–Burman test, steepest ascent test, and Box–Behnken design. The results indicate that the sliding friction coefficient, rolling friction coefficient, and surface energy significantly influence the simulation AoR. By optimizing against the measured AoR using a second-order regression model, the optimal parameter values were determined to be 0.633, 0.401, and 0.2, respectively. Under these optimal parameters, the error between the simulation and experimental AoR was 2.1%. Finally, the calibrated mesoscopic parameters were validated through a lifting cylinder test, showing an error of 6.3% between the simulation and experimental results. The high similarity in the shape of the AoR further confirms the accuracy and reliability of the parameter calibration method. This study provides a valuable reference for future DEM-based research on the mechanical and engineering properties of lunar regolith. [ABSTRACT FROM AUTHOR]

Background: Minimally invasive plate osteosynthesis (MIPO) for clavicular shaft fracture yields favorable functional outcomes and results in less surgery-related soft tissue injury than other techniques. Anterior chest and shoulder skin numbness, a common complication after open reduction and plate fixation, is related to injury to the supraclavicular nerves. We propose MIPO combined with a mini-open approach without fluoroscopy for nerve preservation to minimize the risk of postoperative numbness compared with traditional open plating without nerve preservation. Methods: A total of 59 patients were retrospectively identified, with a follow-up period of 6 months. Thirty-two patients underwent MIPO with mini-open and nerve preservation technique (MIPO group), and 27 patients underwent traditional open plating without nerve preservation (open group). Constant–Murley shoulder outcome score, operation time, wound length, skin numbness, and number of implant removals were compared between the groups. Results: The MIPO group had significantly lower rates of anterior chest and shoulder skin numbness than the open group (MIPO: 12.5% vs. open: 55.6%; p < 0.001). Operation time was significantly longer in the MIPO group than in the open group (MIPO: 109.38 ± 18.83 vs. open: 81.48 ± 18.85; p < 0.001). Wound length was significantly shorter in the MIPO group than in the open group (MIPO: 4.73 ± 0.79 vs. open: 9.76 ± 1.64; p < 0.001). Both groups had similarly excellent Constant–Murley shoulder scores. There were significantly fewer implant removals in the MIPO group than in the open group (MIPO: 6.3% vs. open: 25.9%; p = 0.036). Neither group experienced any infection, implant failure, or nonunion. Conclusions: Our technique combining MIPO with the mini-open approach and supraclavicular nerve preservation yields a lower incidence of skin numbness than traditional open plating without nerve preservation. [ABSTRACT FROM AUTHOR]

Calcium phosphate bone cement (CPC) is a popular material for bone remodeling, and nanohydroxyapatite (nHA) represents a breakthrough that has a wide range of clinical applications. During the early stages of bone repair, antibacterial and angiogenesis effects are essential to remodel new bone tissues. In this study, an antibacterial effect was achieved by incorporating Cu2+-doped nano-hydroxyapatite (Cu–nHA) synthesized through hydrothermal methods into CPC, and the impact of various amounts of Cu–nHA addition on the antibacterial and mechanical properties of CPC hybridization was evaluated. Moreover, the effects of Cu–nHA/CPC composites on the proliferation and mineralization of mouse progenitor osteoblastic cells (D1 cells) were characterized; the cell migration and angiogenesis ability of vascular endothelial cells (HUVECs) were also studied. Results indicated that incorporating 5 wt.% and 10 wt.% Cu–nHA into CPC led to a practical short-term antibacterial effect on S. aureus but not on E. coli. These Cu–nHA/CPC slurries remained injectable, anti-disintegrative, and non-toxic. Furthermore, compared with pure CPC, these Cu–nHA/CPC slurries demonstrated positive effects on D1 cells, resulting in better proliferation and mineralization. In addition, these Cu–nHA/CPC slurries were more effective in promoting the migration and angiogenesis of HUVECs. These findings indicate that 10 wt.% Cu–nHA/CPC has great application potential in bone regeneration. [ABSTRACT FROM AUTHOR]

Furfural is an essential compound that contributes to the distinctive flavor of sauce-flavored Baijiu. However, traditional detection methods are hindered by lengthy and complex sample preparation procedures, as well as the need for expensive equipment. Therefore, there is an urgent need for a new approach that allows rapid detection. In this study, we developed a novel surface-enhanced Raman spectroscopy (SERS) substrate by constructing MXene (Ti3C2TX) @Ag nanoparticles (Ag NPs) through an electrostatic attraction method. The MXene (Ti3C2TX) @Ag NPs were successfully fabricated, with adsorbed NaCl-treated Ag NPs uniformly absorbed on the surface of MXene (Ti3C2TX), creating high-density distributed SERS "hot spots". The prepared substrate demonstrated excellent sensitivity, uniformity, repeatability, and long-term stability, with a low detectable concentration of 10−9 M for R6G (Rhodamine 6G) and an enhancement factor of up to 7.08 × 105. When applied for the in situ SERS detection of furfural in Baijiu, the detection limit was as low as 0.5 mg/L. Overall, the proposed method offers rapid, low-cost, and sensitive quantitative analysis, which is significant not only for detecting furfural in Baijiu but also for identifying hazardous substances and distinguishing between authentic and counterfeit Baijiu products. [ABSTRACT FROM AUTHOR]

Newcastle disease virus (NDV) is an oncolytic virus whose F protein cleavage activity is associated with viral infectivity. To explore the potential of modifying F protein cleavage activity to enhance antitumor effects, we constructed a recombinant NDV LaSota strain by replacing its F protein cleavage site with that from the mesogenic Beaudette C (BC) strain using reverse genetics techniques. The resulting virus, rLaSota-BC-RFP, demonstrated significantly enhanced infectivity and tumor cell suppression on the murine melanoma B16F10 cell, characterized by higher cytotoxicity and increased apoptosis compared to its parental strain, rLaSota-RFP. In vivo, rLaSota-BC-RFP treatment of B16F10 tumors in C57BL/6 mice resulted in significant tumor growth inhibition, improved survival rate, and induction of tumor-specific apoptosis and necrosis. Additionally, the rLaSota-BC-RFP treatment enhanced immunostimulatory effects within the tumor microenvironment (TME), characterized by increased infiltration of CD4+ and CD8+ T cells and elevated levels of antitumor immune modulator cytokines, including mouse IL-12, IFN-γ, IL-15, and TNF-α, in the rLaSota-BC-RFP-treated tumor tissues. Collectively, these findings demonstrate that the mesogenic F protein cleavage site enhances the oncolytic potential of the NDV LaSota strain, suggesting that rLaSota-BC-RFP is a promising oncolytic viral vector for gene delivery in cancer immunotherapy. [ABSTRACT FROM AUTHOR]

Cross-domain fault diagnosis enhances the generalization capability of diagnostic models across different operating conditions and machines. Current studies tackle the domain shift problem by adapting the model during training with data from the target domain or multiple source domains. However, a more realistic and less explored scenario is automatically adapting a trained (developed) model at test time (deployment period) using limited normal-condition data. To bridge this research gap, we propose a novel test-time adaptation framework to rapidly and effectively adapt the trained model, which only requires mini-batch test data (normal condition). Specifically, we first transform input signals to informative signal embedding and mitigate its noise with a reconstruction loss. Then, we decompose the signal embedding to the domain-related healthy component and the domain-invariant faulty component to better leverage the normal-condition data. Finally, we adapt the model by re-identifying the normal signals of the target domain during the test stage. Extensive experiments verify the effectiveness of our method, demonstrating performance improvements across public and private datasets. [ABSTRACT FROM AUTHOR]

The China Near-Earth Object Survey Telescope (CNEOST) conducted four photometric surveys from 2015 to 2018 using image processing and aperture photometry techniques to obtain extensive light curve data on asteroids. The second-order Fourier series method was selected for its efficiency in determining the rotation periods of the observed asteroids. Our study successfully derived rotation periods for 892 asteroids, with 648 of those matching values recorded in the LCDB (for asteroids with U > 2). To enhance the reliability of the derived spin parameters and shape models, we also amassed a comprehensive collection of published light curve data supplemented by additional photometric observations on a targeted subset of asteroids conducted using multiple telescopes between 2021 and 2022. Through the application of convex inversion techniques, we successfully derived spin parameters and shape models for seven main-belt asteroids (MBAs): (2233) Kuznetsov, (2294) Andronikov, (2253) Espinette, (4796) Lewis, (1563) Noel, (2912) Lapalma, and (5150) Fellini. Our thorough analysis identified two credible orientations for the rotational poles of these MBAs, shedding light on the prevalent issue of "ambiguity in pole direction" that often accompanies photometric inversion processes. CNEOST continues its observational endeavors, and future collected data combined with other independent photometric measurements will facilitate further inversion to better constrain the spin parameters and yield more refined shape models. [ABSTRACT FROM AUTHOR]

The eastern slope of Gongga Mountain is located in the mountainous region of Southwestern China, which has strong geologic tectonics that leads to frequent landslide hazards. A large number of such landslides were induced by the 2022 Luding Ms 6.8 earthquake. Therefore, it is necessary to identify the spatial distribution of landslides in the region. In this paper, the Google Earth platform and GF-1 and GF-6 satellite imagery were used to construct new pre-earthquake and co-seismic landslides. Then, we analyzed the relationship between the conditioning factors of the pre-earthquake and co-seismic landslide inventories and the spatial distribution of landslides, as well as the main controlling factors of landslide development. The main conclusions are as follows: (i) Through remote-sensing interpretation and field investigation, 1198 and 4284 landslides were recognized before and after the earthquake, respectively, and the scale was mainly small- and medium-sized. (ii) In two kinds of inventories, landslides are primarily distributed along the banks of the Dadu River basin, within elevations of 1200–1400 m and slopes of 30–50°. (iii) The distribution of pre-earthquake and co-seismic landslides was influenced by engineering geological layer combinations and earthquake intensity, with these two factors being the most significant. This paper plays an important role in hazard prevention and reconstruction planning in the Gongga Mountains. [ABSTRACT FROM AUTHOR]

To address the challenges posed by the vast and complex knowledge information in cultural heritage design, such as low knowledge retrieval efficiency and limited visualization, this study proposes a method for knowledge extraction and knowledge graph construction based on graph attention neural networks (GAT). Using Tang Dynasty gold and silver artifacts as samples, we establish a joint knowledge extraction model based on GAT. The model employs the BERT pretraining model to encode collected textual knowledge data, conducts sentence dependency analysis, and utilizes GAT to allocate weights among entities, thereby enhancing the identification of target entities and their relationships. Comparative experiments on public datasets demonstrate that this model significantly outperforms baseline models in extraction effectiveness. Finally, the proposed method is applied to the construction of a knowledge graph for Tang Dynasty gold and silver artifacts. Taking the Gilded Musician Pattern Silver Cup as an example, this method provides designers with a visualized and interconnected knowledge collection structure. [ABSTRACT FROM AUTHOR]

This manuscript introduces MPSD (Malicious PowerShell Script Detector), an advanced tool to protect Windows systems from malicious PowerShell commands and scripts commonly used in fileless malware attacks. These scripts are often hidden in Office document macros or downloaded remotely via PowerShell, posing significant threats to corporate networks. A 2018 report revealed that 77% of successful cyberattacks involved fileless malware, with PowerShell being the primary attack method, as highlighted in Red Canary's 2022 report. To counter these threats, MPSD leverages the Antimalware Scan Interface (AMSI) to intercept and analyze real-time PowerShell scripts, preventing their execution. It further utilizes VirusTotal to filter out malicious scripts. Unlike traditional methods that rely on direct access to scripts, MPSD detects them before execution, addressing the challenge of hidden or obfuscated scripts. Experimental results show that MPSD outperforms well-known antivirus engines, with a low false-negative rate of 1.83%. MPSD is highly effective against evasion techniques like concatenation, encoding, and reordering, making it a robust tool in the cybersecurity landscape. [ABSTRACT FROM AUTHOR]

Sn-10Bi low-bismuth-content solder alloy provides a potential alternative to the currently used Sn-Ag-Cu series due to its lower cost, excellent ductility, and strengthening resulting from the Bi solid solution and precipitation. This study primarily investigates the interfacial evolution and shear strength characteristics of Sn-10Bi joints on a Ni/Au surface finish during the as-soldered and subsequent isothermal aging processes. To improve the joint performance, a 0.2 or 0.5 wt.% dopant of Zn was incorporated into Sn-10Bi solder. The findings demonstrated that a 0.2 or 0.5 wt.% Zn dopant altered the composition of the intermetallic compound (IMC) formed at the interface between the solder and Ni/Au surface finish from Ni3Sn4 to Ni3(Sn, Zn)4. The occurrence of this transformation is attributed to the diffusion of Zn atoms into the Ni3Sn4 lattice, resulting in the substitution of a portion of the Sn atoms by Zn atoms, thereby forming the Ni3(Sn, Zn)4 IMC during the soldering process, which was also verified by calculations based on first principles. Furthermore, a 0.2 or 0.5 wt.% Zn dopant in Sn-10Bi significantly inhibited the Ni3(Sn, Zn)4 growth after both the soldering and thermal aging processes. Zn addition can enhance the shear strength of solder joints irrespective of the as-soldered or aging condition. The fracture mode was determined by the aging durations—with the brittle mode occurring for as-soldered joints, the ductile mode occurring for aged joints after 10 days, and again the brittle mode for joints after 40 days of aging. [ABSTRACT FROM AUTHOR]

Background and Objectives: Microvascular invasion (MVI) significantly impacts recurrence and survival rates after liver resection in hepatocellular carcinoma (HCC). Pre-operative prediction of MVI is crucial in determining the treatment strategy. This study aims to develop a nomogram model to predict the probability of MVI based on clinical features in HCC patients. Materials and Methods: A total of 489 patients with a pathological diagnosis of HCC were enrolled from our hospital. Those registered from 2012–2015 formed the derivation cohort, and those from 2016–2019 formed the validation cohort for pre-operative prediction of MVI. A nomogram model for prediction was created using a regression model, with risk factors derived from clinical and tumor-related features before surgery. Results: Using the nomogram model to predict the odds ratio of MVI before hepatectomy, the AFP, platelet count, GOT/GPT ratio, albumin–alkaline phosphatase ratio, ALBI score, and GNRI were identified as significant variables for predicting MVI. The Youden index scores for each risk variable were 0.287, 0.276, 0.196, 0.185, 0.115, and 0.112, respectively, for the AFP, platelet count, GOT/GPT ratio, AAR, ALBI, and GNRI. The maximum value of the total nomogram scores was 220. An increase in the number of nomogram points indicated a higher probability of MVI occurrence. The accuracy rates ranged from 55.9% to 64.4%, and precision rates ranged from 54.3% to 68.2%. Overall survival rates were 97.6%, 83.4%, and 73.9% for MVI(−) and 80.0%, 71.8%, and 41.2% for MVI(+) (p < 0.001). The prognostic effects of MVI(+) on tumor-free survival and overall survival were poor in both the derivation and validation cohorts. Conclusions: Our nomogram model, which integrates clinical factors, showed reliable calibration for predicting MVI and provides a useful tool enabling surgeons to estimate the probability of MVI before resection. Consequently, surgical strategies and post-operative care programs can be adapted to improve the prognosis of HCC patients where possible. [ABSTRACT FROM AUTHOR]

Constipation, a widespread gastrointestinal disorder, often leads to the exploration of natural remedies. This study examines the efficacy of Golden Flower Tibetan Tea Polysaccharides (GFTTPs) in alleviating constipation in mice. Chemical analyses reveal that GFTTPs possess O-H, carboxyl, carboxylic acid (-COOH), and C-O-C groups, alongside a porous crystal structure with thermal stability. In animal experiments, GFTTPs significantly upregulated aquaporin 3 (AQP3) and aquaporin 8 (AQP8) expressions in the colon, enhancing water absorption and reducing fecal water content. At a 400 mg/kg dosage, GFTTPs notably improved colonic tissue alterations and serum levels of excitatory neurotransmitters caused by loperamide hydrochloride. They also beneficially altered gut microbiota, increasing Coprococcus, Lactobacillus, and Pediococcus populations. These changes correlated with improved stool frequency, consistency, and weight in constipated mice. Importantly, GFTTPs at 200 and 400 mg/kg doses exhibited comparable effects to the normal control group in key parameters, such as gastrointestinal transit rate and fecal moisture. These findings suggest that GFTTPs may serve as a potent natural remedy for constipation, offering significant therapeutic potential within the context of gut health and with promising implications for human applications. [ABSTRACT FROM AUTHOR]

The rapid urbanization of urban areas in China has brought about great variation in the layout of cities and serious air pollution. Recently, the focus has been directed toward understanding the role of urban morphology in the generation and spread of atmospheric pollution, particularly in PM2.5 emissions. However, there have been limited investigations into the impact of three-dimensional (3D) features on changes in PM2.5 concentrations. By analyzing a wealth of data on building structures based on a mixed linear model and variance partition analysis in the Yangtze River Delta throughout 2018, this study sought to examine the associations between PM2.5 concentrations and urban building form, and further compared the contributions of two-dimensional (2D) and 3D building features. The findings revealed that both 2D and 3D building forms played an important role in PM2.5 concentrations. Notably, the greater contribution of 3D building forms on PM2.5 concentrations was observed, especially during the summer, where they accounted for 20% compared to 7% for 2D forms. In particular, the building height range emerged as a crucial local factor affecting PM2.5 concentrations, contributing up to 12%. Moreover, taller buildings with more variability in height were found to aid in the dispersion of pollution. These results underscore the substantial contribution of 3D building morphology to PM2.5 pollution, contrasting with previous studies. Furthermore, compact buildings were linked to lower pollution levels, and an urban landscape characterized by polycentric urban structures and lower fragmentation was deemed more favorable for sustainable urban development. This study is significant in investigating the contribution of 3D morphology to PM2.5 and its importance for pollution dispersion mechanisms. It suggests the adoption of a polycentric urban form with a broader range of building heights in urban planning for local governments in the Yangtze River Delta. [ABSTRACT FROM AUTHOR]

In the late 20th century, computer viruses emerged as powerful malware that resides permanently in target hosts. For a virus to function, it must load into memory from persistent storage, such as a file on a hard drive. Due to the significant destructive potential of viruses, numerous defense measures have been developed to protect computer systems. Among these, antivirus software is one of the most recognized and widely used. Typically, antivirus solutions rely on static analysis (signature-based) technologies to detect infections in files stored on permanent storage devices, such as hard drives or USB (Universal Serial Bus) flash drives. However, a new breed of malware, fileless malware, has been designed to evade detection and enhance durability. Fileless malware resides solely in the memory of the target hosts, circumventing traditional antivirus software, which cannot access or analyze processes executed directly from memory. This study proposes the Check-on-Execution (CoE) kernel-based approach to detect fileless malware on Linux systems. CoE intervenes by suspending code execution before a program executes code from a process's writable and executable memory area. To prevent the execution of fileless malware, CoE extracts the code from memory, packages it with an ELF (Executable and Linkable Format) header to create an ELF file, and uses VirusTotal for analysis. Experimental results demonstrate that CoE significantly enhances a Linux system's ability to defend against fileless malware. Additionally, CoE effectively protects against shell code injection attacks, including buffer and memory overflows, and can handle packed malware. However, it is important to note that this study focuses exclusively on fileless malware, and further research is needed to address other types of malware. [ABSTRACT FROM AUTHOR]

WiFi fingerprint-based positioning is a method for indoor localization with the advent of widespread deployment of WiFi and the Internet of Things. However, single WiFi fingerprint positioning has the problems of mismatch, unstable signal strength and limited accuracy. Aiming to address these issues, this paper proposes the fusion algorithm combining WiFi and pedestrian dead reckoning (PDR). Firstly, the particle swarm optimization (PSO) model is utilized to optimize the weighted k-nearest neighbors (WKNN) in the WiFi part. Additionally, the artemisinin optimization (AO) algorithm is used to optimize the particle filter (PF) to improve the fusion effect of the WiFi and PDR. Finally, to thoroughly validate the localization performance of the proposed algorithm, we designed experiments involving two scenarios with four smartphone gestures: calling, dangling, handheld, and pocketed. The experimental results unequivocally indicate that the positioning error of AO-PSO-PF algorithm is lower than that of other algorithms including PDR, WiFi, PF, APF, and FPF. The average positioning errors for the two experiments are 0.95 m and 1.42 m, respectively. [ABSTRACT FROM AUTHOR]

Urban trees are known for their ability to settle fine particulate matter (PM2.5), yet the effects of historical pollution exposure on their dust-retention capacity and stress memory remain underexplored. Therefore, we selected Euonymus japonicus Thunb. var. aurea-marginatus Hort. and Photinia × fraseri Dress, which are two common urban greening tree species in the Yangtze River Delta, a highly urbanized region in China facing severe air pollution challenges, characterized by dense urban forests, and we employed an aerosol generator to perform controlled experiments aiming to simulate PM2.5 pollution exposure in a sealed chamber. The experiments encompassed a first pollution treatment period P1 (15 days), a recovery period R (15 days), and a second pollution treatment period P2 (15 days). The study investigates the historical impacts of pollution exposure by simulating controlled environmental conditions and assessing the morphological and physiological changes in trees. The main results are as follows: Vd of Euonymus japonicus Thunb. var. aurea-marginatus Hort. significantly decreased on the 10th day during P2 compared with that on the same day during P1, whereas Vd of Photinia × fraseri Dress significantly decreased on the 15th day. Compared with those during P1, the specific leaf area of both plants significantly decreased, the specific leaf weight significantly increased, the wax layer significantly thickened, the stomata decreased, and the content of photosynthetic pigments remained stable during P2. Furthermore, the air pollution tolerance index (APTI) generally increased during both P1 and P2. This study contributes to international knowledge by examining stress memory in urban trees and underscores the role of stress memory in enhancing plant resistance to periodic particulate pollution, offering insights into the adaptive mechanisms that can be applied globally, not just regionally. [ABSTRACT FROM AUTHOR]

The actinomycete genus Rhodococcus is known for its diverse biosynthetic enzymes, with potential in pollutant degradation, chemical biocatalysis, and natural product exploration. Comparative genomics have analyzed the distribution patterns of non-ribosomal peptide synthetases (NRPSs) in Rhodococcus. The diversity and specificity of its secondary metabolism offer valuable insights for exploring natural products, yet remain understudied. In the present study, we analyzed the distribution patterns of biosynthetic gene clusters (BGCs) in the most comprehensive Rhodococcus genome data to date. The results show that 86.5% of the gene cluster families (GCFs) are only distributed in a specific phylogenomic-clade of Rhodococcus, with the most predominant types of gene clusters being NRPS and ribosomally synthesized and post-translationally modified peptides (RiPPs). In-depth mining of RiPP gene clusters revealed that Rhodococcus encodes many clade-specific novel RiPPs, with thirteen core peptides showing antibacterial potential. High-throughput elicitor screening (HiTES) and non-targeted metabolomics revealed that a marine-derived Rhodococcus strain produces a large number of new aurachin-like compounds when exposed to specific elicitors. The present study highlights the diversity and specificity of secondary biosynthetic potential in Rhodococcus, and provides valuable information for the targeted exploration of novel natural products from Rhodococcus, especially for phylogenomic-clade-specific metabolites. [ABSTRACT FROM AUTHOR]

To study the effects of fluid compressibility on the dynamics of a cavitating vortex street flow in a regime where the vortex shedding frequency increases as a result of the cavitation increase, the cavitating wake behind a wedge was simulated employing both incompressible and compressible solvers. To do this, a compressible cavitation model was implemented, modifying the Zwart-Gerber-Belamri (ZGB) incompressible solver and including a pressure limit and absorbing boundary conditions to prevent a non-physical pressure field. To validate the performance of the compressible model, preliminary simulations were carried out on a 1D Sod cavitating tube and the cavitating vortex shedding behind a circular body at laminar flow conditions. The results of the cavitating wake behind the wedge with the incompressible and the compressible solvers showed similar predictions in terms of pressure, vortex shedding frequency, and instantaneous and average vapor volume fraction profiles. In spite of this, differences were obtained in the energy content of the fluid force fluctuations on the body at higher frequencies, which appear to be better resolved and amplified when the compressibility model is considered. Overall, both solvers provided comparable results in terms of cavitation phenomena that are well aligned with experimental observations. [ABSTRACT FROM AUTHOR]

The lack of vertical observation of reactive nitrogen oxides in agricultural areas has posed a significant challenge in fully understanding their sources and impacts on atmospheric oxidation. Ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations were conducted in the agricultural regions of the North China Plain (NCP) during the summer of 2019 to measure the vertical distributions of aerosols, nitrogen dioxide (NO2), and nitrous acid (HONO). This study aimed at revealing the spatiotemporal distribution, sources, and environmental effects of reactive nitrogen oxides in the NCP agricultural areas. Our findings indicated that the vertical profiles of aerosols and NO2 exhibited a near-Gaussian distribution, with distinct peak times occurring between 8:00–10:00 and 16:00–18:00. HONO reached its maximum concentration near the surface around 8:00 in the morning and decreased exponentially with altitude. After sunrise, the concentration of HONO rapidly decreased due to photolysis. Additionally, the potential source contribution function (PSCF) was used to evaluate the potential sources of air pollutants. The results indicated that the main potential pollution sources of aerosols were located in the southern part of the Hebei, Shanxi, Shandong, and Jiangsu provinces, while the potential pollution sources of NO2 were concentrated in the Beijing–Tianjin–Hebei region. At altitudes exceeding 500 m, the heterogeneous reactions of NO2 on aerosol surfaces were identified as one of the important contributors to the formation of HONO. Furthermore, we discussed the production rate of hydroxyl radicals (OH) from HONO photolysis. It was found that the production rate of OH from HONO photolysis decreased with altitude, with peaks occurring in the morning and late afternoon. This pattern was consistent with the variations in HONO concentration, indicating that HONO was the main contributor to OH production in the agricultural regions of the NCP. This study provides a new perspective on the sources of active nitrogen in agricultural regions and their contribution to atmospheric oxidation capacity from a vertical perspective. [ABSTRACT FROM AUTHOR]

The development of conductive coatings has significant implications for microelectronics and electrochemistry. However, conductive coatings may exhibit different electrochemical properties when prepared on different substrate materials. This research explores the comparative performance of graphene, graphene oxide (GO), and silver nanoparticle (Ag NP) composites as conductive coatings on diverse substrate materials, including polydimethylsiloxane (PDMS), polymethyl methacrylate (PMMA), and glass. The study employed various preparation methods, such as mixing conductive materials with substrate materials and preparing copolymer composite materials. The conductive coating approach was found to be the most straightforward and convenient, with broader development prospects and fewer restrictive conditions. The results indicate that the distinct surface characteristics of the substrate materials influence the conductive properties of coating materials. Consequently, results show that graphene exhibits the highest conductivity on all three substrates, while GO is more conductive than Ag NPs on PMMA and PDMS but less conductive than Ag NPs on glass. That offers valuable insights into the selection of substrate materials and coating materials for the preparation of conductive materials. [ABSTRACT FROM AUTHOR]

Obstacles on rail transit significantly compromise operational safety, particularly under dense fog conditions. To address missed and false detections in traditional rail transit detection methods, this paper proposes a multi-scale adaptive YOLO (MSA-YOLO) algorithm. The algorithm incorporates six filters: defog, white balance, gamma, contrast, tone, and sharpen, to remove fog and enhance image quality. However, determining the hyperparameters of these filters is challenging. We employ a multi-scale adaptive module to optimize filter hyperparameters, enhancing fog removal and image quality. Subsequently, YOLO is utilized to detect obstacles on rail transit tracks. The experimental results are encouraging, demonstrating the effectiveness of our proposed method in foggy scenarios. [ABSTRACT FROM AUTHOR]

A scientific method for evaluating the design of interfaces is proposed to address the unique characteristics and user needs of infrequent-contact public service interfaces. This method is significant for enhancing service efficiency and promoting the sustainable development of public services. Current interface evaluation methods are limited in scope and often fail to meet actual user needs. To address this, this study focuses on virtual museums, examining users' aesthetic psychology and cognitive behavior in terms of layout aesthetics and visual cognitive characteristics, aiming to explore the relationship between the two. Interface layout aesthetic values and user visual cognitive measurements were obtained by using computational aesthetics methods and eye-tracking experiments. These served as input data for a new model. An improved gray H-convex correlation model utilizing the ICRITIC method is proposed to examine the mapping relationship between interface layout aesthetics and visual cognitive features. The results demonstrate that our new model achieves over 90% accuracy, outperforming existing models. For virtual museum interfaces, symmetry and dominance significantly influence user visual cognition, with the most notable correlations found between density and gaze shift frequency, simplicity and mean pupil diameter, and order and gaze shift frequency. Additionally, fixation duration, fixation count, and mean pupil diameter were inversely correlated with interface layout aesthetics, whereas gaze shift frequency and gaze time percentage were positively correlated. [ABSTRACT FROM AUTHOR]

This work aimed to investigate the feasibility of fabricating Pickering emulsions stabilized by Desmodium intortum protein isolate (DIPI) aggregates. The DIPI aggregates were formed using heat treatment, and the effects of ionic strength and pH on their properties were investigated. The heat-treated protein exposes its hydrophobic groups due to structural damage, resulting in rapid aggregation of the protein into aggregates with a size of 236 nm. The results showed that the aggregates induced by ionic strength had larger particle size and higher surface hydrophobicity and partial wettability. Moreover, this study explored effective strategies for bolstering Pickering emulsion stability through optimized DIPI aggregate concentration (c) and oil fraction (ø). The DIPI Pickering emulsion (DIPIPE) formed at c = 5% and ø = 0.7 was still highly stable after 30 days of storage. As confirmed by laser confocal microscopy, DIPI aggregates could be adsorbed onto the oil–water interface to form a network structure that could trap oil droplets in the network. Collectively, the Pickering emulsion stabilized by DIPI aggregates exhibited excellent stability, which not only deeply utilizes the low-value protein resources in the Desmodium intortum for the first time, but also demonstrates the potential of DIPI for the bio-based field. [ABSTRACT FROM AUTHOR]

Nanotechnology has ushered in significant advancements in drug design, revolutionizing the prevention, diagnosis, and treatment of various diseases. The strategic utilization of nanotechnology to enhance drug loading, delivery, and release has garnered increasing attention, leveraging the enhanced physical and chemical properties offered by these systems. Polyamidoamine (PAMAM) dendrimers have been pivotal in drug delivery, yet there is room for further enhancement. In this study, we conjugated PAMAM dendrimers with chitosan (CS) to augment cellular internalization in tumor cells. Specifically, doxorubicin (DOX) was initially loaded into PAMAM dendrimers to form DOX-loaded PAMAM (DOX@PAMAM) complexes via intermolecular forces. Subsequently, CS was linked onto the DOX-loaded PAMAM dendrimers to yield CS-conjugated PAMAM loaded with DOX (DOX@CS@PAMAM) through glutaraldehyde crosslinking via the Schiff base reaction. The resultant DOX@CS@PAMAM complexes were comprehensively characterized using Fourier-transform infrared (FTIR) spectroscopy, transmission electron microscopy (TEM), and dynamic light scattering (DLS). Notably, while the drug release profile of DOX@CS@PAMAM in acidic environments was inferior to that of DOX@PAMAM, DOX@CS@PAMAM demonstrated effective acid-responsive drug release, with a cumulative release of 70% within 25 h attributed to the imine linkage. Most importantly, DOX@CS@PAMAM exhibited significant selective cellular internalization rates and antitumor efficacy compared to DOX@PAMAM, as validated through cell viability assays, fluorescence imaging, and flow cytometry analysis. In summary, DOX@CS@PAMAM demonstrated superior antitumor effects compared to unconjugated PAMAM dendrimers, thereby broadening the scope of dendrimer-based nanomedicines with enhanced therapeutic efficacy and promising applications in cancer therapy. [ABSTRACT FROM AUTHOR]

The interaction between the leaf and airflow directly influences droplet deposition on the leaf surface. This paper investigates the effect of this interaction on droplet deposition. A bidirectional fluid-structure coupling model was established using computational fluid dynamics (CFD) based on mechanical parameters and surface roughness of tomato leaves to simulate tomato leaf deposition under air-assisted spraying. Utilizing the model and considering air velocity, droplet size, and initial leaf inclination as experimental factors, a three-factor, three-level central composite design simulation and response surface analysis were conducted to examine the influence of each factor on the surface deposition amount of tomato leaves. The order of influence of each factor on the deposition amount is as follows: a quadratic regression model was established with the flow velocity having the greatest influence, followed by initial leaf inclination and then droplet size. The influence of each factor on the deposition distribution of the leaf surface was compared and studied separately. Airflow velocity significantly affected the deposition distribution of the leaf surface. Higher airflow velocities resulted in a lower proportion of deposition at the tip and a higher proportion at the base. The maximum relative errors of leaf deformation and deposition were 8.77% and 17.44%, respectively. The findings of this research can provide valuable insights for optimizing the working parameters of air-assisted atomizers. [ABSTRACT FROM AUTHOR]

We investigated the effects of periarticular multimodal drug injection (PMDI) on postoperative pain control, patients' mobilization, and length of hospital stay in patients undergoing total knee arthroplasty (TKA). We retrospectively enrolled patients who underwent unilateral TKA between 2019 and 2020. The formula for PMDI included 0.5 mL epinephrine (1 mg/mL), 1 mL ketorolac (30 mg/mL), 0.5 mL morphine (10 mg/mL), and 20 mL bupivacaine hydrochloride (5 mg/mL), mixed with 60 mL normal saline. The outcomes of interest included (1) the amount of patient-controlled anesthesia (PCA) consumption in the first 24 h after the surgery, (2) early mobilization within 24 h after the surgery, and (3) the length of hospital stay. A total of 127 patients were analyzed. Compared with patients who did not receive PMDI, those who received PMDI had lower consumption of PCA in the first 24 h (β coefficient −29.9, 95% CI −51.9 to −7.9, p = 0.008), higher odds of early mobilization within 24 h (odds ratio 8.263, 95% CI 3.041 to 22.453, p < 0.001), and shorter length of hospital stay (β coefficient −0.705, 95% CI −1.158 to −0.252, p = 0.003). We suggest that PMDI may be considered for patients undergoing TKA to improve the quality of care and shorten their length of hospital stay. [ABSTRACT FROM AUTHOR]

The mapping relation between the emission angle of the photoelectron and its ionization time (i.e., the angle–time mapping) is important for the attoclock measurement. For a long time, the angle–time mapping was assumed to be angularly uniform. Recent investigations have demonstrated that the angle–time mapping is discontinuous for the low-energy electron at the angle for the minimum yield. However, the previous results were interpreted based on the assumption of s-electron initial states for noble-gas atoms, and the effect of the initial orbital symmetry on the angle–time mapping has been rarely investigated. In this work, we investigate the influence of the initial orbital symmetry on time–energy distribution using F− ions as a specific example. We demonstrate that the initial orbital symmetry significantly impacts the time–energy distribution. This behavior can be well explained by the saddle-point method. More interestingly, it is found that the angle–time mapping is strongly dependent on the initial orbital symmetry in the elliptically polarized laser field, especially for the low-energy electrons. Our work holds great significance for further developing the attoclock scheme. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel equivalent composite control architecture for electro-optical equipment. The improved tracking performance and loss of robustness caused by this structure have a clear relationship with a 2 , the time coefficient of the compensation circuit. The compensation circuit can make the speed quality factor and the acceleration quality factor of the system infinite, and the jerk quality factor can be expanded to 1 / a 2 times the original acceleration quality factor, but it will cause a main zero point of the servo system to be far away from the virtual axis and the main poles to be close to the virtual axis. As the time coefficient of the compensation loop controller decreases, the tracking performance of the system increases, but the robustness decreases, the dynamic response deteriorates, the water bed effect becomes more obvious, and the system is more susceptible to noise and disturbances. Compared to the existing method, our method focuses on system performance and robustness. Experimental results show that our method can achieve target tracking with a peak accuracy of 64 ″ and 22 ″ (RMS), which is superior to the tracking performance without equivalent composite control. [ABSTRACT FROM AUTHOR]

To meet the challenges of renewable energy consumption and improve the efficiency of energy systems, we propose an intelligent distributed energy dispatch strategy for multi-energy systems based on Nash bargaining by utilizing the power dispatch meta-universe platform. First, the operational framework of the multi-energy system, including wind park (WP), photovoltaic power plant (PVPP), and energy storage (ES), is described. Using the power dispatch meta-universe platform, the models of WP, PVPP, and ES are constructed and analyzed. Then, a Nash bargaining model of the multi-energy system is built and transformed into a coalition profit maximization problem, which is solved using the alternating direction multiplier method (ADMM). Finally, the effectiveness of the proposed strategy is verified. The results show that the strategy greatly improves the consumption of renewable energy sources and the profit of the overall system. [ABSTRACT FROM AUTHOR]

Urbanization and industrialization have escalated air pollution into a critical global issue, particularly in urban areas. Urban green infrastructures (GIs), such as parks and street trees, play a vital role in mitigating air pollution through dry deposition, the process by which air pollutants are removed by deposition onto plant surfaces or through plant uptake. However, existing studies on the dry-deposition capacity of urban green spaces are limited in their ability to reflect variations at the tree-species level, hindering comprehensive evaluations and effective management strategies. This study aims to quantitatively assess the dry-deposition capacity of the urban green spaces of Beijing and Shanghai for six major air pollutants in using an improved dry-deposition model and tree-species-specific data. Results showed that Shanghai's urban green spaces had a monthly average dry-deposition rate of 5.5 × 10−6 s m−1, slightly higher than Beijing's rate of 5.3 × 10−6 s m−1. Significant seasonal variations were observed, with summer showing the highest deposition rates due to favorable meteorological conditions. Broad-leaved species such as Zelkova serrata in Beijing and Photinia serratifolia in Shanghai exhibited superior dry-deposition capacities compared to coniferous species. Temperature significantly influenced dry-deposition rates for gaseous pollutants, while particulate-matter deposition was primarily affected by pollutant concentrations. This study provides critical insights into the air = purification functions of urban green spaces and underscores the importance of species selection and strategic green-space planning in urban air-quality management, informing the development of optimized urban-greening strategies for improved air quality and public health. [ABSTRACT FROM AUTHOR]

Porosity assessment is a vital component for reservoir evaluation in the oil and gas sector, and with technological advancement, reliance on conventional methods has decreased. In this regard, this research aims to reduce reliance on well logging, purposing successive machine learning (ML) techniques for precise porosity measurement. So, this research examines the prediction of the porosity curves in the Sui main and Sui upper limestone reservoir, utilizing ML approaches such as an artificial neural networks (ANN) and fuzzy logic (FL). Thus, the input dataset of this research includes gamma ray (GR), neutron porosity (NPHI), density (RHOB), and sonic (DT) logs amongst five drilled wells located in the Qadirpur gas field. The ANN model was trained using the backpropagation algorithm. For the FL model, ten bins were utilized, and Gaussian-shaped membership functions were chosen for ideal correspondence with the geophysical log dataset. The closeness of fit (C-fit) values for the ANN ranged from 91% to 98%, while the FL model exhibited variability from 90% to 95% throughout the wells. In addition, a similar dataset was used to evaluate multiple linear regression (MLR) for comparative analysis. The ANN and FL models achieved robust performance as compared to MLR, with R2 values of 0.955 (FL) and 0.988 (ANN) compared to 0.94 (MLR). The outcomes indicate that FL and ANN exceed MLR in predicting the porosity curve. Moreover, the significant R2 values and lowest root mean square error (RMSE) values support the potency of these advanced approaches. This research emphasizes the authenticity of FL and ANN in predicting the porosity curve. Thus, these techniques not only enhance natural resource exploitation within the region but also hold broader potential for worldwide applications in reservoir assessment. [ABSTRACT FROM AUTHOR]

Simple Summary: Insect-specific negative-sense RNA viruses are widespread, exhibiting a diverse range of characteristics. Leaf beetles within the Chrysomelidae family, known for their chewing mouthparts, are significant agricultural pests. Despite this, reports of negative-sense RNA viruses in leaf beetles are scarce. In this study, we have identified two novel negative-sense RNA viruses in a globally distributed leaf beetle species, Aulacophora indica (Coleoptera, Chrysomelidae). The complete genomes of two insect-infecting viruses (ISVs) were successfully obtained through metatranscriptome analysis and rapid amplification of cDNA ends (RACE), named Aulacophora indica nyami-like virus 1 (AINlV1) and Aulacophora indica chu-like virus 1 (AIClV1). Phylogenetically, AINlV1 falls into an unclassified clade within the Nyamiviridae virus family, while AIClV1 is classified as a member of the Scarabeuvirus genus within the Chuviridae family. Both viruses exhibit typical genome structures associated with their respective families. Additionally, they activate small RNA interference responses, with virus-derived small RNAs (vsiRNAs) from AINlV1 and AIClV1 showing a consistent pattern peaking at 21 nucleotides, biased towards A/U at the 5′-terminal. Our study provides valuable insights into insect-specific viruses (ISVs) affecting leaf beetles. Herbivorous insects harbor a variety of insect-specific viruses (ISVs) some of which are considered to be valuable biological agents for potential applications in biological defense and control strategies. Leaf beetles with chewing mouthparts are particularly known for their capacity to disrupt plant tissue while feeding, often creating openings that can act as entry points for plant pathogens. In this study, we have identified two new negative-sense RNA viruses infecting the leaf beetle Aulacophora indica, an important member of the Chrysomelidae family. These recently discovered viruses belong to the viral families Nyamiviridae and Chuviridae and have been preliminarily named Aulacophora indica nyami-like virus 1 (AINlV1) and Aulacophora indica chu-like virus 1 (AIClV1), respectively. The complete genomic sequences of these viruses were obtained using rapid amplification of cDNA ends (RACE) techniques. Detailed analysis of their genomic structures has confirmed their similarity to other members within their respective families. Furthermore, analysis of virus-derived small interfering RNA (vsiRNA) demonstrated a high abundance and typical vsiRNA pattern of AINlV1 and AIClV1, offering substantial evidence to support their classification as ISVs. This research enhances our understanding of viral diversity within insects. [ABSTRACT FROM AUTHOR]

Simple Summary: Enterococcus faecium, a lactic acid bacterium, is approved for use as a direct-fed microbial by the Ministry of Agriculture (MOA) in China. However, some research reports indicate that certain strains of Enterococcus faecium have developed antibiotic resistance. Moreover, some strains of Enterococcus faecium carry virulence genes and are considered to be conditional pathogens. Therefore, selecting safe and reliable strains of Enterococcus faecium as probiotics for livestock and poultry is particularly important. This experiment used Enterococcus faecium isolated from the intestinal contents of healthy minks to evaluate the effects of Enterococcus faecium on the growth performance, antioxidant capacity, immunity, and gut microbiota composition of growing male minks. The purpose of this experiment was to explore the effects of dietary Enterococcus faecium (EF) on the growth performance, antioxidant capacity, immunity, and intestinal microbiota of growing male minks. A total of 60 male Regal White minks at 12 weeks of age were randomly assigned to two groups, each with 15 replicates of two minks per replicate. The minks in two groups were fed the basal diets and the basal diets with viable Enterococcus faecium (more than 107 cfu/kg of diet), respectively. Compared with the minks in control, Enterococcus faecium minks had heavier body weight (BW) at week 4 and week 8 of the study (p < 0.05), greater average daily gain (ADG), and a lower feed/gain ratio (F/G) of male minks during the initial 4 weeks and the entire 8-week study period (p < 0.05). Furthermore, Enterococcus faecium increased the apparent digestibility of crude protein (CP) and dry matter (DM) compared to the control (p < 0.05). Moreover, Enterococcus faecium enhanced the serum superoxide dismutase (SOD) activity and decreased the malondialdehyde (MDA) contents (p < 0.05). The results also confirmed that Enterococcus faecium increased the levels of serum immunoglobulin A (IgA), immunoglobulin G (IgG), and the concentrations of secretory immunoglobulin A (SIgA) in the jejunal mucosa while decreasing the interleukin-8 (IL-8) and interleukin-1β (IL-1β) levels in the jejunal mucosa (p < 0.05). Intestinal microbiota analysis revealed that Enterococcus faecium increased the species numbers at the OUT level. Compared with the control, Enterococcus faecium had significant effects on the relative abundance of Paraclostridium, Brevinema, and Comamonas (p < 0.05). The results showed that Enterococcus faecium could improve the growth performance, increase the antioxidant capacity, improve the immunity of growing male minks, and also modulate the gut microbiota. [ABSTRACT FROM AUTHOR]

Carbon fiber-reinforced polymer (CFRP) components were extensively used and current studies mainly refer to CFRP laminates. The dynamic performance of the complicated CFRP antenna beams is yet to be explored. Therefore, a sensor layout based on fiber Bragg gratings (FBGs) in series was designed to measure the dynamic response of the CFRP antenna beam, and various vibration tests (sweep frequency test, simulated long-life vibration test, shock vibration test, functional vibration test, and constant frequency vibration test) were conducted. The time and frequency domain analysis on FBG sensing signals was performed to check the vibration performance and assess the health condition of this novel CFRP structure. The results indicate that strain values reach a maximum of only 300 µε under different test conditions. The antenna beam exhibited clear vibration patterns, with the first four intrinsic frequencies identified at 44, 94.87, 107.1, and 193.45 Hz. It shows that strain distribution and vibration modes of the antenna beam can be characterized from the sensing data, and the dynamic feature can be much more accurately assessed. The FBG sensors attached on the surface of CFRP antenna beam can accurately and stably measure the dynamic response, which validates that the interfaces between optical fiber sensing elements and CFRP material have excellent interfacial bonding characteristics. The novel CFRP antenna beam exhibits the excellent dynamic performance and stability, offering the replacement of traditional steel antenna beams. The study can finally instruct the development of self-sensing CFRP antenna beams assembled with FBGs in series. [ABSTRACT FROM AUTHOR]

In the present study, the mitochondrial genomic characteristics of Acanthopsetta nadeshnyi have been reported and have depicted the phylogenetic relationship among Pleuronectidae. Combined with a comparative analysis of 13 PCGs, the TN93 model was used to review the neutral evolution and habitat evolution catalysis of the mitogenome to verify the distancing and purification selectivity of the mitogenome in Pleuronectidae. At the same time, a species differentiation and classification model based on mitogenome analysis data was established. This study is expected to provide a new perspective on the phylogenetic relationship and taxonomic status of A. nadeshnyi and lay a foundation for further exploration of environmental and biological evolutionary mechanisms. [ABSTRACT FROM AUTHOR]

With the abuse of antibiotics, its pollution poses an increasing threat to the environment and human health. Effective degradation of organic pollutants in water bodies is urgent. Compared to traditional treatment methods, advanced oxidation processes that have developed rapidly in recent years are more environmentally friendly, efficient and applicable to a wider range of organic compounds. FeWO4 was used in this study as the iron-based semiconductor material to modify and optimize the material design. Fe3O4/FeWO4 composites were prepared by a two-step hydrothermal method. The crystal structure, surface morphology, electrochemical properties and separability of the composite semiconductor were analyzed by XRD, XPS, UV-vis, SEM, EDS and Mott-Schottky. The results showed that, when the initial contaminant concentration was 30 mg/L, the initial solution pH was 4, the dosage of the catalyst was 25 mg and the dosage of hydrogen peroxide was 30 μL, the degradation efficiency of tetracycline hydrochloride (TCH) could reach 91% within 60 min, which was significantly improved compared to the performance of the single semiconductors Fe3O4 and FeWO4. In addition, the catalyst prepared in this experiment can be easily recovered by magnetic separation technology in practical application, which will not affect the turbidity of water while reducing the cost of catalyst separation and recovery. [ABSTRACT FROM AUTHOR]

Deoxynivalenol (DON) is a global contaminant found in crop residues, grains, feed, and animal and human food. Biodegradation is currently the best solution for addressing DON pollution. However, efficient detoxification bacteria or enzymes that can be applied in complex matrices are lacking. The aim of this study was to isolate a DON-detoxifying probiotic strain with a high degradation rate, a good safety profile, and a clear genetic background. One hundred and eight bacterial strains were isolated from 300 samples collected from a school farm and surrounding livestock farms. A new DON-degrading strain, Lactobacillus rhamnosus MY-1 (L. rhamnosus MY-1), with a degradation rate of 93.34% after 48 h and a comprehensive degradation method, was identified. Then, MY-1 at a concentration of 1 × 108 CFU/mL was administered to mice in a chronic intoxication experiment for 28 days. The experimental group showed significantly higher weight gain and exhibited good production performance compared to the control group. The length of the ileal villi in the experimental group was significantly longer than that in the control group. The expression of pro-inflammatory cytokines decreased, while the expression of anti-inflammatory factors increased in the experimental group. Whole-genome analysis revealed that most of the MY-1 genes were involved in carbohydrate metabolism and membrane transport, with a cluster of secondary metabolite genes encoding antimicrobial properties. In summary, this study successfully identified a Lactobacillus strain with good safety performance, high DON degradation efficiency, and a clear genetic background, providing a new approach for the treatment of DON contamination. [ABSTRACT FROM AUTHOR]

Distributed interrupted sampling repeater jamming (D-ISRJ) is the application of interrupted sampling repeater jamming technology within the framework of distributed jamming systems. It can generate coherent false targets after passing through the target radar's matched filter, but these false targets exhibit strong regularity in range and amplitude. Addressing this issue, a distributed interrupted sampling frequency-shifted repeater jamming method based on the group teaching optimization algorithm (GTOA) is proposed in this paper. By introducing frequency-shifted modulation during the retransmission of the jamming signal, the frequency shift amount of the jamming unit in each round of repeater jamming is used as an optimization variable to construct an optimization model for distributed interrupted sampling frequency-shifted repeater jamming. The parameters are then solved by using GTOA. Simulations are conducted to analyze the jamming effects under different distributed jamming modes, and the proposed optimization algorithm is compared to common swarm intelligence algorithms in the same optimization model. The method proposed in this paper can be used in the field of precision electronic warfare to improve the jamming effect of synthetic aperture radar. Experimental results show that under the given simulation conditions, the jamming signal generated by the proposed method can achieve better jamming effects. [ABSTRACT FROM AUTHOR]

Yeast plays a crucial role in the fermentation industry, particularly in alcoholic beverage production, where robustness and metabolic flexibility are essential. This study aimed to investigate the stress tolerance and metabolic capabilities of seven commercial ale yeast strains under various stress conditions, including temperature, pH, osmotic pressure, glucose starvation, and ethanol concentration. Detailed growth assays and stress tolerance tests were utilized to evaluate fermentation efficiency, carbon source utilization, and stress adaptation. Significant variability was observed among the strains. ACY169 and ACY150 demonstrated high overall stress tolerance, making them suitable for high-gravity brewing and processes involving extreme temperature fluctuations. ACY10 showed robust performance under acid stress, making it ideal for sour beer production. In contrast, ACY5 exhibited limited adaptability under stress, with longer doubling times and reduced metabolic activity. The study also revealed differences in carbon source utilization, with ACY169 displaying exceptional metabolic versatility by efficiently fermenting various sugars, including glucose, fructose, maltose, and raffinose. ACY10 and ACY150 exhibited balanced fermentation profiles with high ethanol production rates, while ACY9 demonstrated the highest glucose consumption rate but lower ethanol yields and significant acidification. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries, as the main energy storage component of electric vehicles (EVs), play a crucial role in ensuring the safe and reliable operation of the battery systems through monitoring their state of health (SOH). However, temperature variations and battery aging have significant impacts on the internal parameters of lithium-ion batteries, and these changes directly correlate with the accuracy of battery SOH estimation. To address these issues, this paper proposes an estimation method for lithium-ion battery SOH that considers the impact of temperature. The method begins with reconstructing a second-order hybrid equivalent circuit model for lithium-ion batteries, through which an adaptive update rate for battery model parameters is designed. On this basis, a nonlinear observer for battery states is introduced by integrating filters to estimate SOH. The proposed method considers the impact of capacity in the design of the parameter adaptive update rate, enabling the capacity to be dynamically adjusted based on the actual state of the batteries. This reduces the cumulative error in the SOC observer and improves the modeling accuracy of battery models. Experimental results demonstrate that the method proposed in this paper exhibits exceptional performance in SOH estimation under different temperature conditions. The mean absolute error for SOH estimation does not exceed 0.5%, and the root mean square error does not exceed 0.2%. This method can significantly improve the estimation accuracy of SOH, providing a more efficient and accurate solution for battery management systems in EVs. [ABSTRACT FROM AUTHOR]