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In this paper, the effects of the SiC phase incorporated in Ni substrate deposits on storage tank steel during electrodeposition at different current densities are explored. The microstructure, phase content, and corrosion resistance of the resulting Ni-SiC composites were investigated by scanning electron microscopy (SEM) matched with energy disperse spectroscopy (EDS), X-ray diffraction (XRD), and an electrochemical workstation, respectively. SEM micrographs and EDS results show that at 2.5 A/dm2, the composites presented a smooth and compact structure with high SiC content, while at 1.8 or 3.2 A/dm2, it became uneven and loose in structure with low SiC content. XRD patterns showed that the nickel grain size of composites firstly increased and then decreased with the growth of the current density. Notably, the Ni-SiC composite produced at 2.5 A/dm2 possessed a higher corrosion potential (−0.507 V) and lower corrosion current density (2.439 μA/cm2), illustrating that its excellent anti-corrosion ability was superior than that of other two composites. Hence, SiC co-deposited at 2.5 A/dm2 conducted as a protective barrier and inhibited the corrosion rate against a corrosion medium of Cl− and SO42− ions. In addition, the corrosion relationship illustrated that the SiC content of Ni-SiC composite firstly increased and then decreased with the growth of the current density, while the corrosion weight loss of Ni-SiC composites firstly decreased and then increased. [ABSTRACT FROM AUTHOR]

The long-term excessive use of chemical fertilizers may result in soil degradation, but manure and straw application is considered to be an effective approach for alleviating this problem. The aim of this study is to examine the long-term impacts of different fertilization patterns on soil quality variables in a wheat–sweet potato rotation system. Four treatments were conducted in a field trial for a duration of twelve years, including (1) no fertilizer (control, CK); (2) application of mineral fertilizers (NPK) alone; (3) NPK with crop straw return (NPKs); (4) combined use of NPK and farmyard manure (NPKm). Thirteen physical, chemical, and biological soil parameters were measured. The results showed that the NPKm and NPKs significantly improved the proportion of macroaggregates (>0.25 mm) by 24.7% and 21.9% compared to the NPK alone, respectively. The proportion of microaggregates (0.053–0.25 mm) under the NPKm was 47.4% significantly higher than the NPKs. Additionally, the NPKm resulted in a 22.2% and 19.6% increase in the SOC content than the NPK and NPKs, respectively. In terms of soil-available K, the NPKs resulted in levels that were 42.1% and 49.6% higher than the NPKm and NPK alone, respectively. Long-term fertilization significantly decreased soil pH by 0.95–1.85 units compared to the control, whereas manure application could alleviate soil acidification, as shown when the pH increased by 10.6–18.7%. The NPKm and NPKs resulted in significantly increased soil pHs by 10.6% and 18.7% compared to the NPK alone, respectively. In addition, the NPKm and NPKs increased N-acetyl-β-D-glucosaminidase activity by 52.6% and 60.3% compared to the NPK alone. Determined by the minimum data set method, the NPKm treatment exhibited the highest soil quality index, followed by the NPKs and NPK. Our findings suggested that the combined use of chemical fertilizers with organic amendments proved beneficial for enhancing soil quality. [ABSTRACT FROM AUTHOR]

Quantum secure direct communication (QSDC) is a quantum communication paradigm that transmits confidential messages directly using quantum states. Measurement-device-independent (MDI) QSDC protocols can eliminate the security loopholes associated with measurement devices. To enhance the practicality and performance of MDI-QSDC protocols, we propose a one-photon-interference MDI QSDC (OPI-QSDC) protocol which transcends the need for quantum memory, ideal single-photon sources, or entangled light sources. The security of our OPI-QSDC protocol has also been analyzed using quantum wiretap channel theory. Furthermore, our protocol could double the distance of usual prepare-and-measure protocols, since quantum states sending from adjacent nodes are connected with single-photon interference, which demonstrates its potential to extend the communication distance for point-to-point QSDC. [ABSTRACT FROM AUTHOR]

The refractive index (RI) of biological tissues is a fundamental material parameter that characterizes how light interacts with tissues, making accurate measurement of RI crucial for biomedical diagnostics and environmental monitoring. A Janus sensor (JBS) is designed in this paper, and the photonic spin Hall effect (PSHE) is used to detect subtle changes in RI in biological tissues. The asymmetric arrangement of the dielectric layers breaks spatial parity symmetry, resulting in significantly different PSHE displacements during the forward and backward propagation of electromagnetic waves, thereby realizing the Janus effect. The designed JBS can detect the RI range of 1.3~1.55 RIU when electromagnetic waves are incident along the +z-axis, with a sensitivity of 96.29°/refractive index unit (RIU). In the reverse direction, blood glucose concentrations are identified by the JBS, achieving a sensitivity of 18.30°/RIU. Detecting different RI range from forward and backward scales not only overcomes the limitation that single-scale sensors can only detect a single RI range, but also provides new insights and applications for optical biological detection through high-sensitivity, label-free and non-contact detection. [ABSTRACT FROM AUTHOR]

Yb:CaF2 transparent ceramics represent a promising laser gain medium for ultra-short lasers due to their characteristics: low phonon energy, relatively high thermal conductivity, negative thermo-optical coefficient, and low refractive index. Compared to single crystals, Yb:CaF2 ceramics offer superior mechanical properties, lower cost, and it is easier to obtain large-sized samples with proper shape and uniform Yb3+ doping at high concentrations. The combination of air pre-sintering and Hot Isostatic Pressing (HIP) emerges as a viable strategy for achieving high optical quality and fine-grained structure of ceramics at lower sintering temperatures. The properties of the powders used in ceramic fabrication critically influence both optical quality and laser performance of Yb:CaF2 ceramics. In this study, the 5 atomic percentage (at.%) Yb:CaF2 transparent ceramics were fabricated by air pre-sintering and hot isostatic pressing (HIP) using nano-powders synthesized through the co-precipitation method. The co-precipitated powders were optimized by studying air calcination temperature (from 350 to 550 °C). The influence of calcination temperature on the microstructure and laser performance of Yb:CaF2 ceramics was studied in detail. The 5 at.% Yb:CaF2 transparent ceramics air pre-sintered at 625 °C from powders air calcined at 400 °C and HIP post-treated at 600 °C exhibited the highest in-line transmittance of 91.5% at 1200 nm (3.0 mm thickness) and the best laser performance. Specifically, a maximum output power of 0.47 W with a maximum slope efficiency of 9.2% at 1029 nm under quasi-CW (QCW) pumping was measured. [ABSTRACT FROM AUTHOR]

Sweet potato (Ipomoea batatas L.) is an important food, feed, and industrial raw material and new energy crop. Its rich nutritional value and health effects are increasingly being recognized by consumers, and the demand is increasing. However, due to the continuous cultivation of sweet potato over many years, the degeneration of seedlings and the accumulation of viral diseases are important factors affecting the yield and quality of sweet potatoes. This article provides an overview and analysis of the types and hazards of sweet potato virus diseases, the advantages of virus-free sweet potatoes, the scale of virus-free sweet potato cultivation, sweet potato stem tip virus-free production technology, its development status, and the existing problems. Combined with the development of the sweet potato industry across China, relevant development suggestions are proposed to provide a reference for promoting the healthy, stable, sustainable, high-quality, and efficient development of the sweet potato industry. [ABSTRACT FROM AUTHOR]

Networks are widely used to represent relationships between objects, including microorganisms within ecosystems, based on high-throughput sequencing data. However, challenges arise with appropriate statistical algorithms, handling of rare taxa, excess zeros in compositional data, and interpretation. This work introduces a novel Slope-Matrix-Graph (SMG) algorithm to identify microbiome correlations primarily based on slope-based distance calculations. SMG effectively handles any proportion of zeros in compositional data and involves: (1) searching for correlated relationships (e.g., positive and negative directions of changes) based on a "target of interest" within a setting, and (2) quantifying graph changes via slope-based distances between objects. Evaluations on simulated datasets demonstrated SMG's ability to accurately cluster microbes into distinct positive/negative correlation groups, outperforming methods like Bray–Curtis and SparCC in both sensitivity and specificity. Moreover, SMG demonstrated superior accuracy in detecting differential abundance (DA) compared to ZicoSeq and ANCOM-BC2, making it a robust tool for microbiome analysis. A key advantage is SMG's natural capacity to analyze zero-inflated compositional data without transformations. Overall, this simple yet powerful algorithm holds promise for diverse microbiome analysis applications. [ABSTRACT FROM AUTHOR]

China boasts the world's largest plantation forest of fast-growing poplar trees. However, the wood from these plantations typically exhibits high moisture content, leading to issues such as cracking and warping upon drying. The primary objective of this study was to evaluate the statistical suitability of Weibull, normal, and log-normal distributions for modeling the modulus of elasticity (MOE) of timber and to classify the strength of fast-growing poplar wood based on its strength characteristics to facilitate standardized utilization. Visual grading was employed to remove wood having apparent defects, thus mitigating the influence of wood defects and drying processes on strength. Subsequently, machine grading was conducted using static bending tests to assess the applicability of normal, log-normal, and Weibull distributions to the modulus of elasticity (MOE) distribution. Additionally, the study utilized a correlation matrix to explore the impact of density and moisture content on MOE. The findings suggest that both normal and Weibull distributions are suitable for characterizing the MOE of Chinese fast-growing poplar wood, while the log-normal distribution is not. The mean characteristic values of the MOE and density were 12.21 GPa and 521 kg/m3, respectively. The sampled poplar wood was categorized as C30 grade. Both density and moisture content were found to exert significant influences on the MOE (p < 0.01). However, density alone is not a reliable predictor for estimating MOE (R2 = 0.511). [ABSTRACT FROM AUTHOR]

In recent years, the problem of ecosystem degradation caused by human activities has become increasingly serious. Vegetation restoration is a key means to solve this problem, which has increased. To address the suitability and structural optimization of vegetation restoration in the Loess Plateau (China), the MaxEnt model was used to quantify the impacts of environmental and human activities on the planting suitability of vegetation restoration species at the raster scale. Three layers of trees, shrubs, and herbs with 12 common vegetation restoration species were selected. The factor index system was constructed by combining climatic, ecological, and socio-economic data, and the MaxEnt model predicted land suitability. It was found that human activities significantly increased the unsuitable planting area. This especially affected Robinia pseudoacacia in the tree layer and Amorpha fruticosa in the shrub layer. High and medium suitable areas were mainly sparsely populated areas with close water sources. Through maximum suitability optimization, it was identified that the overall spatial distribution of the three layers in the study area was relatively consistent, and the structural dominance of trees + shrubs + herbs and single herbs in the vertical structure was obvious; these were concentrated in the southwestern and northeastern parts of the study area, respectively. In addition, organic content (OC) and distance from the road to woodland (RW) were the dominant factors affecting land suitability, with a contribution rate of more than 50% and up to 80%. These results provide a scientific basis for optimizing planting structures. They are of significant theoretical and practical significance in guiding vegetation restoration work. [ABSTRACT FROM AUTHOR]

Accurately quantifying the complexity of nodes in a network is crucial for revealing their roles and network complexity, as well as predicting network emergent phenomena. In this paper, we propose three novel complexity metrics for nodes to reflect the extent to which they participate in organized, structured interactions in higher-order networks. Our higher-order network is built using the BuildHON+ model, where communities are detected using the Infomap algorithm. Since a physical node may contain one or more higher-order nodes in higher-order networks, it may simultaneously exist in one or more communities. The complexity of a physical node is defined by the number and size of the communities to which it belongs, as well as the number of higher-order nodes it contains within the same community. Empirical flow datasets are used to evaluate the effectiveness of the proposed metrics, and the results demonstrate their efficacy in characterizing node complexity in higher-order networks. [ABSTRACT FROM AUTHOR]

The lower course of the Yellow River is a "hanging river" across the hinterland of China, and the safety of its flood control measures/systems is closely tied to the stability of the nation. Ensuring high-quality, sustainable development of the lower Yellow River floodplain while maintaining flood safety is crucial for the entire Yellow River Basin. Previous studies have primarily focused on the overall development of the Yellow River Basin or the economic–ecological coupling development of cities along the river, often neglecting the flood safety development of the floodplain. This study optimizes the socio-economic–flood-safety–ecological (SFE) system of the typical downstream Landong floodplain within the Yellow River Basin. The system dynamics model (SDM) can simulate the dynamic behavior of SFE systems by constructing mathematical models that incorporate feedback loops and time delays. The primary components include causal loop modules and stock-flow modules. Then, a coupling coordination degree model for the Landong floodplain is established using a comprehensive subjective and objective weighting method, assessing the SFE system's coordination under five scenarios: inertial development, economic development, environmental protection, flood safety, and sustainable development. The results of historical and validity tests indicate that the SDM can effectively simulate the coupling coordination degree of the SFE system. The study results suggest that the coupling coordination degree increases the most under the sustainable development scenario, indicating that the development of the Landong floodplain should not only focus on socio-economic growth, but should also consider flood safety and ecological concerns. In addition, comprehensive regulation from socio-economic, flood safety, and ecological environment indicators are necessary to achieve high-quality, coordinated development. This study has significant implications for policy formulation and management to achieve high-quality and sustainable development in the downstream floodplain of the Yellow River. [ABSTRACT FROM AUTHOR]

As CMOS technology continues to scale down, the aging effect—known as negative bias temperature instability (NBTI)—has become increasingly prominent, gradually emerging as a key factor affecting device reliability. Accurate aging-aware static timing analysis (STA) at the early design phase is critical for establishing appropriate timing margins to ensure circuit reliability throughout the chip lifecycle. However, traditional aging-aware timing analysis methods, typically based on Simulation Program with Integrated Circuit Emphasis (SPICE) simulations or aging-aware timing libraries, struggle to balance prediction accuracy with computational cost. In this paper, we propose a multi-view graph learning framework for path-level aging-aware timing prediction, which combines the strengths of the spatial–temporal Transformer network (STTN) and graph attention network (GAT) models to extract the aging timing features of paths from both timing-sensitive and workload-sensitive perspectives. Experimental results demonstrate that our proposed framework achieves an average MAPE score of 3.96% and reduces the average MAPE by 5.8 times compared to FFNN and 2.2 times compared to PNA, while maintaining acceptable increases in processing time. [ABSTRACT FROM AUTHOR]

Simple Summary: High-density intensive farming easily induces stress in largemouth bass, leading to significant impairment of growth performance and intestinal health. Ursolic acid (UA), a naturally abundant pentacyclic triterpenoid, has multifaceted biological activities, encompassing anti-inflammatory, antioxidant, lipid-modulating, and hypoglycemic properties. This study examined the effects of UA on growth performance and intestinal barrier in largemouth bass. Our findings demonstrate that dietary supplementation of UA significantly enhances the growth performance and intestinal antioxidant capacity in largemouth bass, while improving intestinal barrier function through its influence on the abundance of intestinal flora such as Tenericutes, Firmicutes, and Mycoplasma. Optimal dietary UA levels for largemouth bass were determined to be between 498 and 520 mg/kg. These findings serve as a valuable reference for largemouth bass production. This study aimed to investigate the effects of ursolic acid (UA) on the growth performance and intestinal health of largemouth bass (Micropterus salmoides). Four diets were formulated with UA supplementation at 0, 250, 500, and 1000 mg/kg, defined as the control (CON), UA250, UA500, and UA1000, respectively. After an 8-week feeding experiment, the results showed that, in the UA500 group, the final body weight (FBW), weight gain rate (WGR), and specific growth rate (SGR) increased, and the feed conversion ratio (FCR) and hepatosomatic index decreased. Total superoxide dismutase (T-SOD) activity exhibited a significant increase, and malondialdehyde (MDA) content decreased. An intestinal histological analysis revealed an improvement in the intestinal structural integrity of the UA500 group. The mRNA relative expression levels of physical barrier-related genes [occludin, claudin-1, and zonula occluden-1 (zo-1)] were upregulated. The mRNA relative expression of interlenkin 10 (il-10) increased, and the mRNA relative expression of interlenkin 1β (il-1β) and tumor necrosis factor-α (tnf-α) significantly decreased. The abundance of Firmicutes and Proteobacteria decreased, and the abundance of Tenericutes increased. The abundance of Mycoplasma, Cyanobium, and Staphylococcus decreased, while the abundance of Clostridium increased. In conclusion, dietary supplementation of UA significantly enhanced the growth performance and antioxidant capacity of largemouth bass while improving intestinal barrier function through its influence on the abundance of intestinal flora, such as Tenericutes, Firmicutes, and Mycoplasma. Optimal dietary UA levels for largemouth bass were determined to be between 498 and 520 mg/kg based on quadratic regression analyses of WGR, SGR, and FCR or T-SOD and MDA content. [ABSTRACT FROM AUTHOR]

In response to prominent issues in existing wine grape cultivation, such as complex power machinery integration, inconvenient connection operations, and low efficiency of unilateral walking operations, a gantry track-mounted multifunctional operations platform for wine grapes was developed. The platform spans across grape trellises, enabling dual-sided operations in a single pass. Considering the high stability requirements for wine grape operations, the track walking device and hitch-lifting mechanism were developed. To accommodate the varying speed requirements of different operational stages, engine power and gearbox gear selection were calculated and selected. Structural strength analysis, steering performance analysis, and overall stability analysis of the machine were conducted. Field test results indicate a maximum operating speed of 3.85 km/h and a minimum turning radius of 3.95 m, meeting the needs of field operations. The maximum climbing angle is no more than 18°, and the machine experiences no lateral sliding or tipping when the maximum lateral tilt angle is below 28°. The hitch-lifting mechanism showed an average settlement of 1.58 mm when lifting to different heights, with a stability rate of 99.7%. This study demonstrates that the developed multifunctional operations platform can meet the field operation requirements of wine grape cultivation. [ABSTRACT FROM AUTHOR]

Event extraction is a complex and challenging task in the field of information extraction. It aims to identify event types, triggers, and argument information from the text. In recent years, overlapping event extraction has attracted the attention of researchers because of its higher challenge and practicability, and some work has carried out in-depth research on overlapping event extraction and achieved remarkable results. But these works (1) ignore the role of ontology knowledge in event extraction; (2) use the same semantic encoding for multi-stage models, lacking consideration for the independent characteristics of extraction tasks such as event types, triggers, and arguments; and (3) face issues in the training process of multi-stage models, such as error cascading and slow convergence. To address the above issues, we propose an ontology-guided and scheduled-sampling approach for overlapping event extraction, termed as OGSS. First, we design a symmetric matrix for event ontology knowledge representation and integrate it into the semantic encoding process, infusing ontology knowledge into event extraction. Second, for extraction targets such as event types, triggers, and arguments, we process the semantic encoding according to the characteristics of each extraction target, obtaining semantic representations tailored for each subtask. Finally, we view multi-stage predictions as sequential outputs of a joint model, using a scheduled sampling strategy between subtasks to effectively mitigate the cascading propagation of errors during training and accelerate model convergence. We conduct extensive experiments on the FewFc event extraction benchmark dataset. The results show that OGSS achieves significant improvements in overlapping event extraction tasks compared to previous methods. [ABSTRACT FROM AUTHOR]

The effects of the rare earth element La on the microstructure and mechanical properties of cast Al-5.4Cu-0.7Mg-0.6Ag alloys have been investigated through metallographic observation, scanning electron microscopy analysis, transmission electron microscopy, X-ray diffraction, and tensile testing. The present form and action mechanism of La have been analyzed. The findings indicate that the inclusion of trace amounts of La markedly diminishes the grain size in the Al-Cu-Mg-Ag alloy. Furthermore, as the La content increases, the alloy's strength is significantly improved. When the La concentration reaches 0.4 wt.%, the mechanical properties of the alloy, both at room temperature and at 350 °C, surpass those of the alloy lacking rare earth elements. When the added rare earth La content exceeds 0.2 wt.%, the emergence of the Al6Cu6La phase causes the alloy structure to exhibit a skeletal morphology, altering the morphology and distribution of excess second phases along grain boundaries, thereby impacting the alloy's overall performance. Incorporating La leads to a reduction in the size of the strengthening precipitate phase Ω while also enhancing its precipitation density, but an excess of La leads to the emergence of Al6Cu6La, depleting the available Cu and suppressing the precipitation of the Ω phase, ultimately affecting the mechanical properties of the alloy. [ABSTRACT FROM AUTHOR]

This paper studies an LSTM-based adaptive transmission method for a 360-degree video and proposes a non-uniform encoding transmission strategy based on LSTM. Our goal is to maximize the user's video experience by dynamically dividing the 360-degree video into tiles of different numbers and sizes, and selecting different bitrates for each tile. This aims to reduce buffering events and video jitter. To determine the optimal number and size of tiles at the current moment, we constructed a dual-layer stacked LSTM network model. This model predicts, in real-time, the number, size, and bitrate of the tiles needed for the next moment of the 360-degree video based on the distance between the user's eyes and the screen. In our experiments, we used an exhaustive algorithm to calculate the optimal tile division and bitrate selection scheme for a 360-degree video under different network conditions, and used this dataset to train our prediction model. Finally, by comparing with other advanced algorithms, we demonstrated the superiority of our proposed method. [ABSTRACT FROM AUTHOR]

A 360° video offers a more immersive experience, gaining increasing popularity among users. However, enhancing the transmission efficiency of 360° videos under limited bandwidth conditions remains a significant challenge. This paper segments the video into three areas: the attention area, the edge area, and the viewpoint-switching transition area. Based on the segmentation of these three distinct video areas, a novel non-uniform coding transmission method for 360° videos is presented, along with mathematical modeling to define the optimization problem. A heuristic algorithm is subsequently introduced, which adaptively determines the optimal number of tiles and allocates the bitrate for each tile in real time to enhance the user's quality of experience (QoE). Finally, a simulation platform has been developed to validate the efficacy of the proposed algorithm by conducting comparative analyses with existing algorithms. [ABSTRACT FROM AUTHOR]

Carbon neutrality has become a global common goal. CCUS, as one of the technologies to achieve carbon neutrality, has received widespread attention from academia and industry. After CO2 enters the formation, under the conditions of formation temperature and pressure, supercritical CO2, formation water, and rock components interact, which directly affects the oil and gas recovery and carbon sequestration efficiency. In this paper, the recent progress on CO2 water–rock interaction was reviewed from three aspects, including (i) the investigation methods of CO2 water–rock interaction; (ii) the variable changes of key minerals, pore structure, and physical properties; and (iii) the nomination of suitable reservoirs for CO2 geological sequestration. The review obtains the following three understandings: (1) Physical simulation and cross-time scale numerical simulation based on formation temperature and pressure conditions are important research methods for CO2 water–rock interaction. High-precision mineral-pore in situ comparison and physical property evolution evaluation are important development directions. (2) Sensitive minerals in CO2 water–rock interaction mainly include dolomite, calcite, anhydrite, feldspar, kaolinite, and chlorite. Due to the differences in simulated formation conditions or geological backgrounds, these minerals generally show the pattern of dissolution or precipitation or dissolution before precipitation. This differential evolution leads to complex changes in pore structure and physical properties. (3) To select the suitable reservoir for sequestration, it is necessary to confirm the sequestration potential of the reservoir and the later sequestration capacity, and then select the appropriate layer and well location to start CO2 injection. At the same time, these processes can be optimized by CO2 water–rock interaction research. This review aims to provide scientific guidance and technical support for shale oil recovery and carbon sequestration by introducing the mechanism of CO2 water–rock interaction, expounding the changes of key minerals, pore structure, and physical properties, and summarizing the sequestration scheme. [ABSTRACT FROM AUTHOR]

The validation of remotely sensed evapotranspiration (ET) products is important for the development of ET estimation models and the accuracy of the scientific application of the products. In this study, different ET products such as HiTLL, MOD16A2, ETMonitor, and SoGAE were compared using multi-source remote sensing data and ground-based data to evaluate their applicability in the Heihe River Basin (HRB) during 2010–2019. The results of the comparison with the site observations show that ETMonitor provides a more stable and reliable estimation of ET than the other three products. The ET exhibited significant variations over the decade, characterized by a general increase in rates across the HRB. These changes were markedly influenced by variations in land use and topographical features. Specifically, the analysis showed that farmland and forested areas had higher ET rates due to greater vegetation cover and moisture availability, while grasslands and water bodies demonstrated lower ET rates, reflecting their respective land cover characteristics. This study further explored the influence of various factors on ET, including land use changes, NDVI, temperature, and precipitation. It was found that changes in land use, such as increases in agricultural areas or reforestation efforts, directly influenced ET rates. Moreover, meteorological conditions such as temperature and precipitation patterns also played crucial roles, with warmer temperatures and higher precipitation correlating with increased ET. This study highlights the significant impact of land use and climatic factors on spatiotemporal variations in ET within the HRB, underscoring its importance for optimizing water resource management and land use planning in arid regions. [ABSTRACT FROM AUTHOR]

Utilizing observed wind speed and direction data from observation stations near the Taiwan Strait and ocean buoys, along with forecast data from the EC model, GRAPES_GFS model, and PanGu weather prediction model within the same period, RMSE, MAE, CC, and other parameters were calculated. To comparatively evaluate the forecasting performance of the PanGu weather prediction model on the sea surface wind field near the Taiwan Strait from 00:00 on 1 June 2023, to 23:00 on 31 May 2024. The PanGu weather prediction model is further divided into the ERA5 (PanGu) model driven by ERA5 initial fields and the GRAPES_GFS (PanGu) model driven by GRAPES_GFS initial fields. The main conclusions are as follows: (1) over a one-year evaluation period, for wind speed forecasts with lead times of 0 h to 120 h in the Taiwan Strait region, the overall forecasting skill of the PanGu weather prediction model is superior to that of the model forecasts; (2) different initial fields input into the PanGu weather prediction model lead to different final forecast results, with better initial field data corresponding to forecast results closer to observations, thus indicating the operational transferability of the PanGu model in smaller regions; (3) regarding forecasts of wind speed categories, the credibility of the results is high when the wind speed level is ≤7, and the PanGu weather prediction model performs better among similar forecasts; (4) although the EC model's wind direction forecasts are closer to the observation field results, the PanGu weather forecasting model also provides relatively accurate and rapid forecasts of the main wind directions within a shorter time frame. [ABSTRACT FROM AUTHOR]

Liner shipping accounts for over 80 % of the global transportation volume, making substantial contributions to world trade and economic development. To advance global economic integration further, it is essential to link the flows of global liner shipping routes with the complex system of international trade, thereby supporting liner shipping as an effective framework for analyzing international trade and geopolitical trends. Traditional methods based on first-order global liner shipping networks, operating at a single scale, lack sufficient descriptive power for multi-variable sequential interactions and data representation accuracy among nodes. This paper proposes an effective methodology termed "Multi-Scale Higher-Order Dependencies (MSHOD)" that adeptly reveals the complexity of higher-order interactions among multi-scale nodes within the global liner shipping network. The key step of this method is to construct high-order dependency networks through multi-scale attributes. Based on the critical role of high-order interactions, a method for key node identification has been proposed. Experiments demonstrate that, compared to other methods, MSHOD can more effectively identify multi-scale nodes with regional dependencies. These nodes and their generated higher-order interactions could have transformative impacts on the network's flow and stability. Therefore, by integrating multi-scale analysis methods to mine high-order interactions and identify key nodes with regional dependencies, this approach provides robust insights for assessing policy implementation effects, preventing unforeseen incidents, and revealing regional dual-circulation economic models, thereby contributing to strategies for global, stable development. [ABSTRACT FROM AUTHOR]

Rapid urbanization leads to fragmentation and reduced connectivity of urban landscapes, endangering regional biodiversity conservation and sustainable development. Constructing a red, green, and blue spatial ecological network is an effective way to alleviate ecological pressure and promote economic development. Using circuit theory, hydrological analysis, and suitability analysis, this study constructs a composite ecological network under urban–rural integration. The results show the following: (1) A total of 22 ecological corridors with a length of 349.20 km, 22 ecological pinch points, and 22 ecological barrier points are identified in the municipal area, mainly distributed in Haidong Town. There are 504 stormwater corridors, which are more evenly distributed, 502 riverfront landscape corridors, and 130 slow-moving landscape corridors. (2) A total of 20 ecological corridors, with a length of 99.23 km, 19 ecological pinch points, and 25 barrier points were identified in the main urban area, and most of them are located in the ecological corridors. There are 71 stormwater corridors, mainly located in the northwestern forest area, 71 riverfront recreation corridors, and 50 slow-moving recreation corridors. (3) Two scales of superimposed ecological source area of 3.65 km2, and eleven ecological corridors, are primarily distributed between Erhai Lake and Xiaguan Town. There are two superimposed stormwater corridors and fourteen recreational corridors. The eco-nodes are mostly distributed in the east and south of Dali City; wetland nodes are mainly situated in the eighteen streams of Cangshan Mountain; and landscape nodes are more balanced in spatial distribution. The study results can provide a reference for composite ecological network construction. [ABSTRACT FROM AUTHOR]

Biochar is crucial for agricultural output and plays a significant role in effectively eliminating heavy metals (HMs) from the soil, which is essential for maintaining a soil–plant environment. This work aimed to assess machine learning models to analyze the impact of soil parameters on the transformation of HMs in biochar–soil–plant environments, considering the intricate non-linear relationships involved. A total of 211 datasets from pot or field experiments were evaluated. Fourteen factors were taken into account to assess the efficiency and bioavailability of HM–biochar amendment immobilization. Four predictive models, namely linear regression (LR), partial least squares (PLS), support vector regression (SVR), and random forest (RF), were compared to predict the immobilization efficiency of biochar-HM. The findings revealed that the RF model was created using 5-fold cross-validation, which exhibited a more reliable prediction performance. The results indicated that soil features accounted for 79.7% of the absorption of HM by crops, followed by biochar properties at 17.1% and crop properties at 3.2%. The main elements that influenced the result have been determined as the characteristics of the soil (including the presence of different HM species and the amount of clay) and the quantity and attributes of the biochar (such as the temperature at which it was produced by pyrolysis). Furthermore, the RF model was further developed to predict bioaccumulation factors (BAF) and variations in crop uptake (CCU). The R2 values were found to be 0.7338 and 0.6997, respectively. Thus, machine learning (ML) models could be useful in understanding the behavior of HMs in soil–plant ecosystems by employing biochar additions. [ABSTRACT FROM AUTHOR]

Soil pollution with cadmium (Cd) poses serious health and environmental consequences. The study investigated the incubation of several soil samples and conducted quantitative soil characterization to assess the influence of biochar (BC) on Cd adsorption. The aim was to develop predictive models for Cd concentrations using statistical and modeling approaches dependent on soil characteristics. The potential risk linked to the transformation and immobilization of Cd adsorption by BC in the soil could be conservatively assessed by pH, clay, cation exchange capacity, organic carbon, and electrical conductivity. In this study, Long Short-Term Memory (LSTM), Bidirectional Gated Recurrent Unit (BiGRU), and 5-layer CNN Convolutional Neural Networks (CNNs) were applied for risk assessments to establish a framework for evaluating Cd risk in BC amended soils to predict Cd transformation. In the case of control soils (CK), the BiGRU model showed commendable performance, with an R 2 value of 0.85, indicating an approximate 85.37% variance in the actual Cd. The LSTM model, which incorporates sequence data, produced less accurate results ( R 2 = 0.84) , while the 5-layer CNN model had an R2 value of 0.91, indicating that the CNN model could account for over 91% of the variation in actual Cd levels. In the case of BC-applied soils, the BiGRU model demonstrated a strong correlation between predicted and actual values with R 2 (0.93), indicating that the model explained 93.21% of the variance in Cd concentrations. Similarly, the LSTM model showed a notable increase in performance with BC-treated soil data. The R 2 value for this model stands at a robust R 2   (0.94) , reflecting its enhanced ability to predict Cd levels with BC incorporation. Outperforming both recurrent models, the 5-layer CNN model attained the highest precision with an R 2 value of 0.95, suggesting that 95.58% of the variance in the actual Cd data can be explained by the CNN model's predictions in BC-amended soils. Consequently, this study suggests developing ecological soil remediation strategies that can effectively manage heavy metal pollution in soils for environmental sustainability. [ABSTRACT FROM AUTHOR]

Financial fraud is a serious challenge in a rapidly evolving digital economy that places increasing demands on detection systems. However, traditional methods are often limited by the dimensional information of the corporations themselves and are insufficient to deal with the complexity and dynamics of modern financial fraud. This study introduces a novel intelligent financial fraud detection support system, leveraging a three-level relationship penetration (3-LRP) method to decode complex fraudulent networks and enhance prediction accuracy, by integrating the fuzzy rough density-based feature selection (FRDFS) methodology, which optimizes feature screening in noisy financial environments, together with the fuzzy deterministic soft voting (FDSV) method that combines transformer-based deep tabular networks with conventional machine learning classifiers. The integration of FRDFS optimizes feature selection, significantly improving the system's reliability and performance. An empirical analysis, using a real financial dataset from Chinese small and medium-sized enterprises (SMEs), demonstrates the effectiveness of our proposed method. This research enriches the financial fraud detection literature and provides practical insights for risk management professionals, introducing a comprehensive framework for early warning and proactive risk management in digital finance. [ABSTRACT FROM AUTHOR]

Three successive vegetable pot experiments were conducted to assess the effects on the long-term immobilization of heavy metals in soil and crop yield improvement after the addition of peanut shell biochar and an alkaline mineral to an acidic soil contaminated with lead and cadmium. Compared with the CK treatment, the change rates of biomass in the edible parts of the three types of vegetables treated with B0.3, B1, B3, B9, R0.2 and B1R0.2 were −15.43%~123.30%, 35.10%~269.09%, 40.77%~929.31%, −26.08%~711.99%, 44.14%~1067.12% and 53.09%~1139.06%, respectively. The cadmium contents in the edible parts of the three vegetables treated with these six additives reduced by 2.08%~13.21%, 9.56%~24.78%, 9.96%~35.61%, 41.96%~78.42%, −4.19%~57.07% and 12.43%~65.92%, respectively, while the lead contents in the edible parts reduced by −15.70%~59.47%, 6.55%~70.75%, 3.40%~80.10%, 55.26%~89.79%, 11.05%~70.15% and 50.35%~79.25%, respectively. Due to the increases in soil pH, soil cation-exchange capacity and soil organic carbon content, the accumulation of Cd and Pb in the vegetables was most notably reduced with a high dosage of 9% peanut shell biochar alone, followed by the addition of a low dosage of 1% peanut shell biochar blended with 0.2% alkaline mineral. Therefore, the addition of a low dosage of 1% peanut shell biochar blended with 0.2% alkaline mineral was the best additive in increasing the vegetable biomass, whereas the addition of 9% peanut shell biochar alone was the worst. Evidently, the addition of 0.2% alkaline mineral can significantly reduce the amount of peanut shell needed for passivating heavy metals in soil, while it also achieves the effect of increasing the vegetable yield. [ABSTRACT FROM AUTHOR]

Gastrodin (GAS) is the main chemical component of the traditional Chinese herb Gastrodia elata (called "Tianma" in Chinese), which has been used to treat neurological conditions, including headaches, epilepsy, stroke, and memory loss. To our knowledge, it is unclear whether GAS has a therapeutic effect on Huntington's disease (HD). In the present study, we evaluated the effect of GAS on the degradation of mutant huntingtin protein (mHtt) by using PC12 cells transfected with N-terminal mHtt Q74. We found that 0.1–100 μM GAS had no effect on the survival rate of Q23 and Q74 PC12 cells after 24–48 h of incubation. The ubiquitin–proteasome system (UPS) is the main system that clears misfolded proteins in eukaryotic cells. Mutated Htt significantly upregulated total ubiquitinated protein (Ub) expression, decreased chymotrypsin-like, trypsin-like and caspase-like peptidase activity, and reduced the colocalization of the 20S proteasome with mHtt. GAS (25 μM) attenuated all of the abovementioned pathological changes, and the regulatory effect of GAS on mHtt was found to be abolished by MG132, a proteasome inhibitor. The autophagy–lysosome pathway (ALP) is another system for misfolded protein degradation. Although GAS downregulated the expression of autophagy markers (LC3II and P62), it increased the colocalization of LC3II with lysosomal associated membrane protein 1 (LAMP1), which indicates that ALP was activated. Moreover, GAS prevented mHtt-induced neuronal damage in PC12 cells. GAS has a selective effect on mHtt in Q74 PC12 cells and has no effect on Q23 and proteins encoded by other genes containing long CAGs, such as Rbm33 (10 CAG repeats) and Hcn1 (>30 CAG repeats). Furthermore, oral administration of 100 mg/kg GAS increased grip strength and attenuated mHtt aggregates in B6-hHTT130-N transgenic mice. This is a high dose (100 mg/kg GAS) when compared with experiments on HD mice with other small molecules. We will design more doses to evaluate the dose–response relationship of the inhibition effect of GAS on mHtt in our next study. In summary, GAS can promote the degradation of mHtt by activating the UPS and ALP, making it a potential therapeutic agent for HD. [ABSTRACT FROM AUTHOR]

The Bounty Channel is a large-scale submarine channel system located in the eastern continental margin of New Zealand. Extending along the axis of the Bounty Trough, the channel system comprises three main tributaries (C1–C3) at its head, which merge downstream into a trunk channel leading to a terminal submarine fan. In this study, we use high-quality two-dimensional multichannel seismic data to investigate the formation and evolution of tributary channels C1 and C2. Four types of seismic facies are identified in the tributary channels: fill-type, mounded divergent, wavy, and subparallel facies. These seismic facies are correspondingly interpreted as topographic depression or channel fills, levees, sediment waves, and hemipelagic deposits. The Late Miocene tributary channels were developed above a pre-existing NE–SW-oriented depression. The Pliocene to Quaternary tributary channels are characterized by preferential development of higher levees on their left hand, and the presence of sediment waves on the lower levees of their right-hand, signaling an effect of the Coriolis force. The formation and evolution of the tributaries are primarily linked to regional tectonics, including increased convergence rate between the Pacific and Australian plates along the Alpine Fault in the Late Miocene and enhanced uplift and erosion at the Southern Alps during the Pliocene. [ABSTRACT FROM AUTHOR]

Data missing is a ubiquitous problem in real-world systems that adversely affects the performance of machine learning algorithms. Although many useful imputation methods are available to address this issue, they often fail to consider the information provided by both features and labels. As a result, the performance of these methods might be constrained. Furthermore, feature selection as a data quality improvement technique has been widely used and has demonstrated its efficiency. To overcome the limitation of imputation methods, we propose a novel algorithm that combines data imputation and feature selection to tackle classification problems for mixed data. Based on the mean and standard deviation of quantitative features and the selecting probabilities of unique values of categorical features, our algorithm constructs different imputation models for quantitative and categorical features. Particle swarm optimization is used to optimize the parameters of the imputation models and select feature subsets simultaneously. Additionally, we introduce a legacy learning mechanism to enhance the optimization capability of our method. To evaluate the performance of the proposed method, seven algorithms and twelve datasets are used for comparison. The results show that our algorithm outperforms other algorithms in terms of accuracy and F 1 score and has reasonable time overhead. [ABSTRACT FROM AUTHOR]

To enhance the selenium (Se) intake of the general public, the present study implemented biofortification techniques in alfalfa sprouts. Alfalfa sprouts possess unique nutritional value and provide an optimal Se-enriched supplemental Se source. The impact of sodium selenite (Na2SeO3) on alfalfa shoot germination, shoot length, and biomass was assessed experimentally, and changes in the antioxidant capacity of sprouts treated with optimal Se concentrations were investigated. In addition, the transcriptome of alfalfa sprouts treated with the optimal Na2SeO3 concentration was sequenced. Gene co-expression networks, constructed through differential gene analysis and weighted gene co-expression network analysis, were used to identify the core genes responsible for Se enrichment in alfalfa sprouts. The findings of the present study offer novel insights into the effects of Se treatment on the nutrient composition of alfalfa sprouts, in addition to introducing novel methods and references that could facilitate production of Se-enriched alfalfa sprouts and associated products. [ABSTRACT FROM AUTHOR]

Simple Summary: High-density intensive farming easily induces immune stress in broilers, leading to significant impairment of growth performance and intestinal health. Sea-buckthorn flavone (SF), extracted from the fruits, leaves, and branches of sea buckthorn, exhibits anti-oxidative, anti-inflammatory, anti-obesity, liver protective, and lipid metabolism-regulating properties. This study examined the effects of SF on growth performance, serum inflammation, the intestinal barrier, and the microbiota in lipopolysaccharide (LPS)-challenged broilers. Our findings demonstrate that SF alleviates LPS-induced inflammatory responses in broilers while improving intestinal health and enhancing growth performance. These findings serve as a valuable reference for poultry production. The experiment investigated the effects of sea-buckthorn flavonoids (SF) on lipopolysaccharide (LPS)-challenged broilers. A total of 288 one-day-old male broilers were randomly assigned to 4 groups, with 6 replicates of 12 broilers each. The experiment lasted for 20 days. The diet included two levels of SF (0 or 1000 mg/kg) and broilers intraperitoneally injected with 500 μg/kg LPS on 16, 18, and 20 days, or an equal amount of saline. LPS challenge decreased final body weight, average daily gain, and average daily feed intake, increased feed-to-gain ratio, and elevated serum IL-1β, IL-2, TNF-α, D-LA, and endotoxin levels. Moreover, it resulted in a reduction in the IL-10 level. LPS impaired the intestinal morphology of the duodenum, jejunum, and ileum, down-regulated the mRNA relative expression of Occludin, ZO-1, and MUC-2 in the jejunum mucosa, up-regulated the mRNA relative expression of TLR4, MyD88, NF-κB, and IL-1β, and increased the relative abundance of Erysipelatoclostridium in broilers (p < 0.05). However, SF supplementation mitigated the decrease in growth performance, reduced serum IL-1β, IL-2, and D-LA levels, increased IL-10 levels, alleviated intestinal morphological damage, up-regulated mRNA expression of Occludin and ZO-1, down-regulated the mRNA expression of TLR4, NF-κB, and IL-lβ in jejunum mucosal (p < 0.05), and SF supplementation presented a tendency to decrease the relative abundance of proteobacteria (0.05 < p < 0.1). Collectively, incorporating SF can enhance the growth performance, alleviate serum inflammation, and improve the intestinal health of broilers, effectively mitigating the damage triggered by LPS-challenges. [ABSTRACT FROM AUTHOR]

In order to explore the combustion performance of a non-road air-cooled two-cylinder turbocharged diesel engine, an experiment on the effects of engine compression ratio, combustion chamber shape and injection timing were systematically conducted in this study. Moreover, the effects of intake air conditions on combustion performance were numerically investigated using the one-dimensional simulation platform. The findings of this study could help provide new insights for promoting the sustainable development of diesel engines used in generator sets. The results show that the increase in intake air temperature can delay the combustion center of gravity and improve the combustion performance and the sustainability of diesel engines. The decrease in intake air pressure leads to a reduction in oxygen amount during the combustion process, thus causing the deterioration of cylinder pressure and combustion performance. By modifying the combustion chamber, the ignition delay and combustion duration are each extended by 1.6 degrees and 4.2 degrees under 100% engine load. The ignition delay and combustion duration are not obviously affected by modifying the combustion chamber shape under 25% and 50% loads. By increasing the compression ratio from 19.5 to 20.5, the ignition delay and combustion duration are shortened, which could enhance the cylinder pressure and heat release rate. However, reducing the compression ratio from 19.5 to 18.5 could significantly decrease the heat release rate. Under middle and low loads, combustion duration is less affected by injection timing. Under 100% load, the peak cylinder pressure increases to 11.4 MPa, and the ignition delay is shortened by advancing injection timing from −17 °CA to −20 °CA. [ABSTRACT FROM AUTHOR]

To enhance the operational efficiency and fault detection accuracy of hydroelectric units, this paper proposes a parallel convolutional neural network model that integrates the Gramian angular summation field (GASF) with an Improved coati optimization algorithm–parallel convolutional neural network (ICOA-PCNN). Additionally, to further improve the model's accuracy in fault identification, a multi-head self-attention mechanism (MSA) and support vector machine (SVM) are introduced for a secondary optimization of the model. Initially, the GASF technique converts one-dimensional time series signals into two-dimensional images, and a COA-CNN dual-branch model is established for feature extraction. To address the issues of uneven population distribution and susceptibility to local optima in the COA algorithm, various optimization strategies are implemented to improve its global search capability. Experimental results indicate that the accuracy of this model reaches 100%, significantly surpassing other nonoptimized models. This research provides a valuable addition to fault diagnosis technology for modern hydroelectric units. [ABSTRACT FROM AUTHOR]

The effective and comprehensive utilization of forest resources has become the theme of the global "dual-carbon strategy". Forestry restructured wood is a kind of wood-based panel made of wood-based fiber composite material by high-temperature and high-pressure restructuring–molding, and has become an important material in the field of construction, furniture manufacturing, as well as derivative processing for its excellent physical and mechanical properties, decorative properties, and processing performance. Taking Medium Density Fiberboard (MDF) as the recombinant material as the research object, an event-triggered synergetic control mechanism based on interventional three-way decision making is proposed for the viscoelastic multi-field coupling-distributed agile control of the "fixed thickness section" in the MDF continuous flat-pressing process, where some typical quality control problems of complex plate shape deviations including thickness, slope, depression, and bump tend to occur. Firstly, the idea of constructing the industrial event information of continuous hot pressing based on information granulation is proposed, and the information granulation model of the viscoelastic plate shape process mechanism is established by combining the multi-field coupling effect. Secondly, an FMEA-based cyber granular method for diagnosing and controlling the plate thickness diagnosis and control failure information expression of continuous flat pressing is proposed for the problems of plate thickness control failure and plate thickness deviation defect elimination that are prone to occur in the continuous flat-pressing process. The precise control of the plate thickness in the production process is realized based on event-triggered control to achieve the intelligent identification and processing of the various types of faults. The application test is conducted in the international mainstream production line of a certain type of continuous hot-pressing equipment for the production of 18 mm plate thickness; the synergistic effect is basically synchronized after 3 s, the control accuracy reaches 30%, and the average value of the internal bond strength is 1.40, which ensures the integrity of the slab. Practical tests show that the method in the actual production is feasible and effective, with detection and control accuracy of up to ±0.05 mm, indicating that in the production of E0- and E1-level products, the rate of superior products can reach more than 95%. [ABSTRACT FROM AUTHOR]

The main components of sandalwood heartwood essential oil are terpenoids, approximately 80% of which are α-santalol and β-santalol. In the synthesis of the main secondary metabolites of sandalwood heartwood, the key gene, santalene synthase (SaSSY), can produce α-santalene and β-santalene by catalyzed (E, E)-FPP. Furthermore, santalene is catalyzed by the cytochrome monooxygenase SaCYP736A167 to form sandalwood essential oil, which then produces a fragrance. However, the upstream regulatory mechanism of the key gene santalene synthase remains unclear. In this study, SaSSY (Sal3G10690) promoter transcription factors and SaSSY cis-elements were screened. The results showed that the titer of the sandalwood cDNA library was 1.75 × 107 CFU/mL, 80% of the inserted fragments identified by PCR were over 750 bp in length, and the positivity rate of the library was greater than 90%. The promoter region of the SaSSY gene was shown to have the structural basis for potential regulatory factor binding. After sequencing and bioinformatics analysis, we successfully obtained 51 positive clones and identified four potential SaSSY transcriptional regulators. Sal6G03620 was annotated as the transcription factor MYB36-like, and Sal8G07920 was annotated as the small heat shock protein HSP20 in sandalwood. Sal1G00910 was annotated as a hypothetical protein of sandalwood. Sal4G10880 was annotated as a homeobox-leucine zipper protein (ATHB-15) in sandalwood. In this study, a cDNA library of sandalwood was successfully constructed using a yeast one-hybrid technique, and the transcription factors that might interact with SaSSY gene promoters were screened. This study provides a foundation for exploring the molecular regulatory mechanism involved in the formation of sandalwood heartwood. [ABSTRACT FROM AUTHOR]

Conventional stator–magnet moving−iron transverse−flux linear oscillatory machines (CSMTLOMs) are widely applied in directly−drive reciprocating devices due to the merits of easy fabrication and robust mover. However, in order to keep the mover vibrating at a certain resonance frequency to save the energy and enlarge the output power, they still suffer from a higher requirement on spring stiffness due to their thick and heavy mover core, which would also narrow the frequency band with a high power factor due to the large inertial energy storage of the heavy mover. Hence, to reduce the mover core weight to reduce the demand of the spring and improve the operation performance, an improved linear oscillatory machine featured by a spoke−type interior permanent magnet inner stator (ISMTLOM) is proposed. Benefiting from its separated two stators, the tangential flux in the radial plane can return through the inner stator core, so that the yoke of the mover core can be eliminated directly. Then, to analytically investigate the influence of the special axial local saturation effect, the segmental equivalent magnetic circuit (EMC) model of the ISMTLOM is established, wherein a saturation coefficient is introduced to quantitatively consider the local saturation effect on the output force. Consequently, several important size parameters are optimally selected when keeping the same outer diameter and copper loss as that of the CSMTLOM. Afterward, the three−dimension finite element algorithm (3D FEA) is adopted for the electromagnetic performance validation and comparison. Finally, it is found that the nonlinear segmental EMC corrected by the saturation coefficient can quickly predict the output force more accurately within the wide load range, and benefiting from the topology improvement, the ISMTLOM has the merits over the CSMTLOM in its smoother output force, much lighter mover core, and less demand of mechanical spring stiffness, whilst preserving the similar output force density. [ABSTRACT FROM AUTHOR]

The digital model of airborne frequency selective surface radomes (AFSSRs) is the basis of design, simulation analysis, manufacturing, and other related research on AFSSRs. This paper proposes a rapid modeling method for AFSSRs based on dynamic customizable primitives. Firstly, a layered digital model construction scheme for AFSSRs is presented based on the typical radome wall structure. Then, according to the characteristics of various surface configurations and the complex wireframe information of AFSSRs, the dynamic primitives are raised to express the boundary and contour information of all kinds of radomes. Focusing on the undevelopable characteristics of the aerodynamic shape surface of the AFSSR, the arrangement solution and mapping method for frequency-selective elements on undevelopable surfaces are proposed. Furthermore, the implementation logic of this method for the creation of each layer model and the assembly of the whole machine model is introduced. Finally, a rapid modeling system (RMS) is established based on this method, enabling the automated creation of digital models of AFSSRs. Utilizing this system resulted in modeling time savings ranging from 20% to 97.5% compared to traditional methods, which verifies the feasibility and effectiveness of this method. [ABSTRACT FROM AUTHOR]

For the RRT* algorithm, there are problems such as greater randomness, longer time consumption, more redundant nodes, and inability to perform local obstacle avoidance when encountering unknown obstacles in the path planning process of autonomous vehicles. And the artificial potential field method (APF) applied to autonomous vehicles is prone to problems such as local optimality, unreachable targets, and inapplicability to global scenarios. A fusion algorithm combining the improved RRT* algorithm and the improved artificial potential field method is proposed. First of all, for the RRT* algorithm, the concept of the artificial potential field and probability sampling optimization strategy are introduced, and the adaptive step size is designed according to the road curvature. The path post-processing of the planned global path is carried out to reduce the redundant nodes of the generated path, enhance the purpose of sampling, solve the problem where oscillation may occur when expanding near the target point, reduce the randomness of RRT* node sampling, and improve the efficiency of path generation. Secondly, for the artificial potential field method, by designing obstacle avoidance constraints, adding a road boundary repulsion potential field, and optimizing the repulsion function and safety ellipse, the problem of unreachable targets can be solved, unnecessary steering in the path can be reduced, and the safety of the planned path can be improved. In the face of U-shaped obstacles, virtual gravity points are generated to solve the local minimum problem and improve the passing performance of the obstacles. Finally, the fusion algorithm, which combines the improved RRT* algorithm and the improved artificial potential field method, is designed. The former first plans the global path, extracts the path node as the temporary target point of the latter, guides the vehicle to drive, and avoids local obstacles through the improved artificial potential field method when encountered with unknown obstacles, and then smooths the path planned by the fusion algorithm, making the path satisfy the vehicle kinematic constraints. The simulation results in the different road scenes show that the method proposed in this paper can quickly plan a smooth path that is more stable, more accurate, and suitable for vehicle driving. [ABSTRACT FROM AUTHOR]

Accurate estimation of surface evapotranspiration (ET) in the Heihe River Basin using remote sensing data is crucial for understanding water dynamics in arid regions. In this paper, by coupling physical constraints and machine learning for hybrid modeling, we develop a hybrid model based on surface conductance optimization. A hybrid modeling algorithm, two physical process-based ET algorithms (Penman–Monteith-based and Priestley–Taylor-based ET algorithms), and three pure machine learning algorithms (Random Forest, Extreme Gradient Boosting, and K Nearest Neighbors) are comparatively analyzed for estimating the ET. The results showed that, in general, the machine learning model optimized by parameters was able to better predict the surface conductance of the hybrid model. Driver analyses showed that radiation, normalized difference vegetation index (NDVI), and air temperature had high correlations with ET. The hybrid model had a better prediction performance for ET than the other five models, and it improved the R2 of the two physical process-based algorithms to 0.9, reduced the root mean square error (RMSE) to 0.5 mm/day, reduced the BIAS to 0.2 mm/day, and improved the Kling–Gupta efficiency (KGE) to 0.9. The hybrid model outperformed the others across different time scales, displaying lower BIAS, RMSE, and higher KGE. Spatially, its ET patterns aligned with regional vegetation changes, with superior accuracy in annual ET estimation compared to the other models. Comparison with other ET products shows that the estimation results based on the hybrid model have better performance. This approach not only improves the accuracy of ET estimation but also improves the understanding of the physical mechanism of ET estimation by pure machine learning models. This study can provide important support for understanding ET and hydrological processes under different climatic and biotic vegetation in other arid and semi-arid regions. [ABSTRACT FROM AUTHOR]

The effective treatment and recovery of fracturing wastewater has always been one of the difficult problems to be solved in oilfield wastewater treatment. Accordingly, in this paper, photocatalytic-coupled low-temperature plasma technology was used to degrade the simulated wastewater containing hydroxypropyl guar, the main component of fracturing fluid. Results indicated that hydroxypropyl-guar wastewater could be degraded to a certain extent by either photocatalytic technology or plasma technology; the chemical oxygen demand and viscosity of the treated wastewater under two single-technique optimal conditions were 781 mg·L−1, 0.79 mPa·s−1 and 1296 mg·L−1, 1.01 mPa·s−1, respectively. Furthermore, the effective coupling of AgIn5S8/gC3N4 photocatalysis and dielectric-barrier discharge–low-temperature plasma not only enhanced the degradation degree of hydroxypropyl guar but also improved its degradation efficiency. Under the optimal conditions of coupling treatment, the hydroxypropyl-guar wastewater achieved the effect of a single treatment within 6 min, and the chemical oxygen demand and viscosity of the treated wastewater reduced to below 490 mg·L−1 and 0.65 mPa·s−1, respectively. In the process of coupled treatment, the AgIn5S8/gC3N4 could directly absorb the light and strong electric field generated by the system discharge and play an important role in the photocatalytic degradation, thus effectively improving the energy utilization rate of the discharge system and enhancing the degradation efficiency of hydroxypropyl guar. [ABSTRACT FROM AUTHOR]

With the increasing complexity of integrated circuit design, the threat of a hardware Trojan (HT) is becoming more and more prominent. At present, the research mainly focuses on the detection of HTs, but the amount of research on the diagnosis of HTs is very small. The number of existing HT diagnosis methods is generally completed by detecting the HT nodes in the netlist. The main reason is the lack of consideration of the integrity of HTs, so the diagnosis accuracy is low. Based on the above reason, this paper proposes two implanted node search algorithms named layer-by-layer difference search (LDS) and layer-by-layer grouping difference search (LGDS). The LDS algorithm can greatly reduce the search time, and the LGDS algorithm can solve the problem of input node disorder. The two methods greatly reduce the number of nodes sorting and comparing, and therefore the time complexity is lower. Moreover, the relevance between implanted nodes is taken into account to improve the diagnosis rate. We completed experiments on an HT diagnosis; the HT implantation example is from Trust-Hub. The experimental results are shown as follows: (1) The average true positive rate (TPR) of the diagnosis using KNN, RF, or SVM with the LDS or LGDS algorithm is more than 93%, and the average true negative rate (TNR) is 100%. (2) The average proportion of implanted nodes obtained by the LDS or LGDS algorithm is more than 97%. The proposed method has a lower time complexity compared with other existing diagnosis methods, and the diagnosis time is shortened by nearly 75%. [ABSTRACT FROM AUTHOR]

Orange peel biochar (C)-supported cadmium sulfide composites (CdS-C) were prepared by the combination of hydrothermal and calcination methods. The structure and morphology were characterized in detail by X-ray diffraction (XRD) and scanning electron microscopy (SEM), respectively. The CdS-C composite with 60% CdS exhibited the highest photocatalytic hydrogen production rate of 7.8 mmol·g−1·h−1, approximately 3.69 times higher than that of synthesized CdS without biochar. These results indicate that biochar derived from orange peel could be a low-cost, renewable, environmentally friendly, and metal-free co-catalyst for CdS, enhancing its photostability. [ABSTRACT FROM AUTHOR]

Sorption is the most important process influencing the amount of herbicide retained in soils. The special properties of biochar could influence the soil retention of pollutants through adsorption. However, the detailed sorption mechanisms as influenced before and after applying biochar to soils with different properties are unclear. This study examined the sorption characteristics of metolachlor using soil samples collected from South China. Sorption experiments were conducted using a batch equilibration method. After comparing the metolachlor sorption constants observed for all soil samples, our results showed that the application of biochar significantly increased the capacity of metolachlor adsorption. Without biochar, sorption capacity (Kf) was positively related to soil organic matter and to a soil particle size of 0.002–0.02 mm in soils developed from granite, of 0.002–0.02 mm in soils developed from delta shockwaves, and of 0.002–0.02 mm, together with complex iron oxide and total iron content, in soils developed from arenaceous shale. Moreover, sorption capacity (Kf) with biochar was positively related to peroxidase in soils developed from granite and to dissociative iron oxide and total iron content in soils developed from arenaceous shale. Our results show that biochar greatly affects metolachlor sorption behavior, probably because of qualitative differences in the structural characteristics of soils with different developmental parent materials and properties. [ABSTRACT FROM AUTHOR]

Understanding the regulation of autotetraploid sterility is essential for harnessing the strong advantages in genomic buffer capacity, biodiversity, and heterosis of autotetraploid rice. miRNAs play crucial roles in fertility regulation, yet information about their reproductive roles and target genes in tetraploid rice remains limited. Here, we used three tetraploid lines, H1 (fertile), HF (fertile), and LF (sterile), to investigate cytological features and identify factors associated with autotetraploid sterility. LF showed abnormal meiosis, resulting in low pollen fertility and viability, ultimately leading to scarce fertilization and a low-seed setting compared to H1 and HF. RNA-seq revealed 30 miRNA-candidate target pairs related to autotetraploid pollen sterility. These pairs showed opposite expression patterns, with differential expression between fertile lines (H1 and HF) and the sterile line (LF). qRT-PCR confirmed that miR9564, miR528, and miR27874 were highly expressed in the anthers of H1 and HF but not in LF, while opposite results were obtained in their targets (ARPS, M2T, and OsRPC53). Haplotype and expression pattern analyses revealed that ARPS was specifically expressed in lines with the same haplotype of MIR9564 (the precursor of miR9564) as LF. Furthermore, the Dual-GFP assay verified that miR9564 inhibited the fluorescence signal of ARPS-GFP. The over-expression of ARPS significantly decreased the seed setting rate (59.10%) and pollen fertility (50.44%) of neo-tetraploid rice, suggesting that ARPS plays important roles in autotetraploid pollen sterility. This study provides insights into the cytological characteristic and miRNA expression profiles of tetraploid lines with different fertility, shedding light on the role of miRNAs in polyploid rice. [ABSTRACT FROM AUTHOR]

Processing polyethylene terephthalate (PET) into functional materials has both sustainable and economic significance. Therefore, this study aims to prepare functional nanofibers using PET, combining electrospun nanofibers with metal–organic frameworks (MOFs), which is an effective solution to increase the added value of functional nanofiltration membranes (NFMs). The surface morphology of PET fibers is successfully controlled by electrospinning parameters and post-treatment. The formation of a uniform coating of CuBTC crystals on the PET surface is induced by a simple and low-cost in situ growth technique. CuBTC@PET was treated to prepare superhydrophobic CuBTC@PET (SCP), thus improving the stability of CuBTC in water and expanding its potential applications. Through a series of optical and thermal characterizations, the porous morphology formation mechanism and MOF in situ growth mechanism of SCP fibers were discussed. Then, the air filtration performance and bacteriostatic properties of SCP nanofiltration membranes were investigated. The as-prepared SCP showed a high water contact angle (146.4°), low-pressure drop (39.7 Pa), and high filtration efficiency (95.3%, 3 μm NaCl), as well as unique, broad-spectrum antibiosis potency against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli). This study shows that SCP nanofiltration membranes can be practically applied in high-performance antibacterial filtration membranes. [ABSTRACT FROM AUTHOR]

Bisphenol S (BPS), one of the substitutes for bisphenol A (BPA), is widely used in various commodities. The BPS concentrations in surface water have gradually increased in recent years, making it a predominant bisphenol analogue in the aquatic environment and raising concerns about its health and ecological effects on aquatic organisms. For this study, we conducted a 96 h acute toxicity test and a 15-day developmental exposure test to assess the adverse effects of BPS exposure in Chinese medaka (Oryzias sinensis), a new local aquatic animal model. The results indicate that the acute exposure of Chinese medaka embryos to BPS led to relatively low toxicity. However, developmental exposure to BPS was found to cause developmental abnormalities, such as decreased hatching rate and body length, at 15 dpf. A transcriptome analysis showed that exposure to different concentrations of bisphenol S often induced different reactions. In summary, environmental concentrations of BPS can have adverse effects on the hatching and physical development of Chinese medaka, and further attention needs to be paid to the potential toxicity of environmental BPS. [ABSTRACT FROM AUTHOR]

Concrete, as a composite material, is subject to heterogeneity in its mechanical properties and damage characteristics responding to load. In this paper, a numerical approach for analyzing the heterogeneous characteristics and the mechanical behavior of concrete specimens in tensile splitting tests using DIP techniques is introduced. The experiment involves the preparation of three types of concrete specimens with different strengths and performances of the tensile splitting test. The contour and position information of the different components in the split surface of a concrete specimen are reflected in the numerical model using the DIP techniques and the fracture of the split surface is realized by three types of cohesive elements in the finite element software ABAQUS. The results of the proposed numerical model are highly consistent with the experimental results with a maximum error of 4.77%, whereby the evolution of the splitting process is discussed. The simulation shows that the concrete fracture develops from the periphery towards the center of the concrete and the ITZ region splits first at similar strain levels, followed by the mortar region and finally the aggregate region. In addition, a simplified modeling scheme with faster computational efficiency and higher accuracy is proposed, which indicates that the shape of the heterogeneous components in concrete has a low effect on mechanical strength. The proposed model can accurately reflect the splitting fracture process of concrete which is instantaneous in the actual process, contributing to the understanding of the mechanism of the splitting fracture process and proposing a new methodology for simulating the fracture process of heterogeneous materials (e.g., concrete, rock). This work contributes to the understanding of the effect of material heterogeneity on concrete's mechanical behavior and fracturing process and provides valuable hints for the research on the non-destructive prediction of concrete strength. [ABSTRACT FROM AUTHOR]

In the construction process of tunnel inlet sections, the rock mass can sustain unsymmetrical pressure due to asymmetrical terrain on the two sides of the tunnel. The fact that the inlet sections are usually under shallow buried conditions with strongly weathered rock mass exacerbates the issue. This paper discusses optimization strategies of the initial support of a shallow buried tunnel based on the analytical results of asymmetrical loading characteristics. Numerical simulation is performed with particle flow code (PFC) using the Jianshanji tunnel project as an example. The simulation results show that the bench excavation has slightly less total deformation than the full-section excavation but the deformation range is wider, especially in the tunnel arch. Both lining support and slope reduction treatments can effectively improve rock deformation, with lining support demonstrating better performance in controlling deformation and adjusting stress distribution. Based on the simulation results, the bench excavation and lining support are used in the actual project, and the corresponding optimization control measures were adopted to address deformation issues, including crushed-stone backfilling for compression resistance, advanced grouting reinforcement, and grouting. The field data show that the tunnel stability is effectively improved by adopting the optimization schemes, which further validates the effectiveness of the proposed unsymmetrical control method. [ABSTRACT FROM AUTHOR]