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Selenium (Se) is an essential trace element for human health, and dietary Se intake is an effective supplement. Rich in nutrients and functional components with potential for Se enrichment, Tartary buckwheat (Fagopyrum tataricum (L.) Gaertn.) is a Se-biofortified cereal. To determine the optimal Se treatment concentration and fully understand its effects on Tartary buckwheat, sodium selenite (Na2SeO3) in different concentrations was sprayed onto leaves of Tartary buckwheat at the initial flowering stage. Agronomic and yield-related traits and Se enrichment were analyzed between CK and treatments. The results showed that Na2SeO3 concentrations of 3.0 and 6.0 mg/L significantly increased the contents of Se and starch in the grains, the 1000-grain weight, the number of grains per plant, and the yield. The 6.0 mg/L treatment had the best effect. Transcriptome and weighted gene co-expression network analyses showed that selenite promoted chlorophyll synthesis and photoelectron transport by upregulating chlorophyll synthase (CHLG) and protein CURVATURE THYLAKOID 1B (CURT1B) levels, improving photosynthesis, increasing sucrose synthesis and transport in leaves and starch synthesis and accumulation in grains, and promoting grain-filling and yield. These changes were regulated by genes related to photosynthesis, sucrose, and starch metabolism-related genes, including CAB3C, HPR3, SUS5, BAM9, SS3, SWEET1, and SWEET12. Selenite absorption in Tartary buckwheat was regulated by aquaporin genes NIP1-1 and PIP1-5. Selenite transport was regulated by the inorganic phosphate transporter gene PHT1-1, and organic Se transport was controlled by the proton-dependent oligopeptide transporters NPF3.1 and NPF4.6. Methionine gamma-lyase (MGL) was involved in selenocompound metabolism. This study identified the best spraying scheme for enhancing Se content in the grains. It also revealed the regulatory genes responding to selenite absorption, transport, and metabolism and the regulatory pathways promoting yield in Tartary buckwheat. These results provide technical guidance and theoretical support for producing high-yielding and Se-enriched Tartary buckwheat. [ABSTRACT FROM AUTHOR]

With the evolution of consumer purchasing power and consumption concepts, external attributes such as fruit size, color, and peel smoothness have emerged as pivotal determinants influencing purchasing preferences; among these, the background color of the fruit peel exerts a considerable impact on fruit esthetics. The background color of fruit peel is predominantly influenced by the chlorophyll content. Consequently, examining the degradation patterns of chlorophyll in Prunus persica L. peel holds significant importance for cultivating varieties with a cleaner peel background color. In this study, Prunus persica L. CP14 and 20–29 were selected as experimental materials to evaluate the peel color variation and chlorophyll content during fruit development. Samples collected from three developmental stages of CP14 and 20–29 underwent transcriptome sequencing. Kyoto Encyclopedia of Genes and Genomes enrichment analysis identified chlorophyll-degradation-related genes within the purine metabolism pathway. Quantitative polymerase chain reaction analysis of chlorophyll degradation gene expression pinpointed PpPAO and PpSGR as likely key genes involved in chlorophyll degradation in Prunus persica L. Transient transformation assays in Nicotiana benthamiana leaves further substantiated that PpPAO and PpSGR markedly reduce chlorophyll levels. Yeast two-hybrid experiments also demonstrated an interaction between PpPAO and PpSGR. [ABSTRACT FROM AUTHOR]

DNA methylation is an epigenetic modification process that can alter the functionality of a genome. It has been reported to be a key regulator of fruit ripening. In this study, the DNA methylation changes of CpG islands of ethylene signaling genes regulated by 1-methylcyclopropene (1-MCP) during ripening and senescence of tomato fruit were detected. The results showed that the 1-MCP treatment decreased the accumulation of lycopene, maintained the content of vitamin C, and delayed the ripening and senescence of tomato fruit. The quantitative real-time PCR and bisulfite sequencing analysis showed that 1-MCP treatment changed the expression and the DNA methylation level of CpG islands related to the ethylene signaling pathway genes, among which the DNA methylation change of LeEIN3 was the most significant. Compared with the control, 1-MCP treatment increased the DNA methylation level of the CpG island of the LeEIN3 gene, reduced the expression of LeEIN3 in tomato fruit, and was involved in 1-MCP delaying the postharvest senescence of tomato fruit. The results indicated that DNA methylation changes of ethylene signaling genes were involved in ethylene synthesis and signal transduction and played an important role in the regulation of 1-methylcyclopropene, delaying postharvest ripening and senescence of tomato fruit. [ABSTRACT FROM AUTHOR]

In fossil fuel and nuclear power plants, welded joints continuously experience creep-fatigue loading, which can result in premature cracking during the in-service term. To study the creep-fatigue interactive (CFI) behavior, the CFI test of P92 steel was performed with different strain rates at 823 K. Results indicate that the short cycle life is measured with the increasing strain rate. Relying on the scanning electron microscope, the fracture mechanism of P92 steel gradually changes from fatigue-dominating to creep-fatigue interactive damage with the increasing strain rate. The hardness (H), elastic modulus (E) and creep deformation were then measured by nanoindentation, and the strain rate sensitivity (m) was estimated. The relation between the degenerated mechanical properties and microstructural evaluations, i.e., enhanced grain size and nucleation of creep voids, was established, and the damage mechanism was discussed. [ABSTRACT FROM AUTHOR]

An algorithmic model of a neural network with channel attention and spatial attention (CASANet) is proposed to estimate the value of atmospheric coherence length, which in turn provides a quantitative description of atmospheric turbulence intensity. By processing the acquired spot image data, the channel attention and spatial attention mechanisms are utilized, and the convolutional neural network learns the interdependence between the channel and space of the feature image and adaptively recalibrates the feature response in terms of the channel to increase the contribution of the foreground spot and suppress the background features. Based on the experimental data, an analysis of the CASANet model subject to turbulence intensity perturbations, fluctuations in outgoing power, and fluctuations in beam quality at the outlet is carried out. Comparison of the results of the convolutional neural network with those of the inverse method and the differential image motion method shows that the convolutional neural network is optimal in three evaluation indexes, namely, the mean deviation, the root-mean-square error, and the correlation coefficient, which are 2.74, 3.35, and 0.94, respectively. The convolutional neural network exhibits high accuracy under moderate and weak turbulence, and the estimation values under strong turbulence conditions are still mostly within the 95% confidence interval. The above results fully demonstrate that the proposed convolutional neural network method can effectively estimate the atmospheric coherence length, which provides technical support for the inversion of atmospheric turbulence intensity based on images. [ABSTRACT FROM AUTHOR]

Insider threats pose significant risks to organizational security, often leading to severe data breaches and operational disruptions. While foundational, traditional detection methods suffer from limitations such as labor-intensive rule creation, lack of scalability, and vulnerability to evasion by sophisticated attackers. Recent advancements in graph-based approaches have shown promise by leveraging behavior analysis for threat detection. However, existing methods frequently oversimplify session behaviors and fail to extract fine-grained features, which are critical for identifying subtle malicious activities. In this paper, we propose a novel approach that integrates session graphs to capture multi-level fine-grained behavioral features. First, seven heuristic rules are defined to transform user activities across different hosts and sessions into an associated session graph while extracting features at both the activity and session levels. Furthermore, to highlight critical nodes in the associated session graph, we introduce a graph node elimination technique to normalize the graph. Finally, a graph convolutional network is employed to extract features from the normalized graph and generate behavior detection results. Extensive experiments on the CERT insider threat dataset demonstrate the superiority of our approach, achieving an accuracy of 99% and an F1-score of 99%, significantly outperforming state-of-the-art models. The ASG method also reduces false positive rates and enhances the detection of subtle malicious behaviors, addressing key limitations of existing graph-based methods. These findings highlight the potential of ASG for real-world applications such as enterprise network monitoring and anomaly detection, and suggest avenues for future research into adaptive learning mechanisms and real-time detection capabilities. [ABSTRACT FROM AUTHOR]

With the wide deployment of edge devices, distributed network traffic data are rapidly increasing. Traditional detection methods for malicious traffic rely on centralized training, in which a single server is often used to aggregate private traffic data from edge devices, so as to extract and identify features. However, these methods face difficult data collection, heavy computational complexity, and high privacy risks. To address these issues, this paper proposes a federated learning-based distributed malicious traffic detection framework, FL-CNN-Traffic. In this framework, edge devices utilize a convolutional neural network (CNN) to process local detection, data collection, feature extraction, and training. A server aggregates model updates from edge devices using four federated learning algorithms (FedAvg, FedProx, Scaffold, and FedNova) to build a global model. This framework allows multiple devices to collaboratively train a model without sharing private traffic data, addressing the "Data Silo" problem while ensuring privacy. Evaluations on the USTC-TFC2016 dataset show that for independent and identically distributed (IID) data, this framework can reach or exceed the performance of centralized deep learning methods. For Non-IID data, this framework outperforms other neural networks based on federated learning, with accuracy improvements ranging from 2.59% to 4.73%. [ABSTRACT FROM AUTHOR]

The effect of the angular rolling process on the plan view pattern of a plate was studied, and the rectangular influencing factors and improvement methods for this process were proposed in this paper. DEFORM (v11.0) finite element software was used to simulate the processes of conventional rolling and angular rolling, and the degree of rectangularity of plates under different rolling process conditions was compared. A formula to characterize the degree of rectangularity of plates was established; the closer this value is to one, the better the degree of rectangularity. Considering the actual rolling process conditions, the range of theoretically calculated rectangular rotation angles was extended to obtain the optimum rectangular rotation angle using the finite element simulation method. In the two-pass angular rolling process, the optimal rectangular angle of the second pass was 14.275° when the first pass was 15°. The optimal rectangular angle of the plate was 19.008° when the first pass' angle was 20°. Two-pass angular rolling is different to four-pass rolling, and the simulation results showed that J   15 °   4 (1.0012) was less than J   15 °   2 (1.0015) and J   20 °   4 (1.0034) was less than J   20 °   2 (1.0055). The rectangularity degree of the four-pass process was better than the two-pass process. Angular rolling experiments were carried out, and the actual data show that the characteristic rectangular value of the rolled piece was 1.003 during the four-pass process and 1.014 during the two-pass process. This verified that separating the one-group two-pass angular rolling process from the one-group four-pass angular rolling process can improve the rectangular degree of the rolled plate, thereby increasing the yield rate. This provides a theoretical basis for industrial applications. [ABSTRACT FROM AUTHOR]

In recent years, significant breakthroughs have been made in the exploration of deep to ultra-deep oil and gas reserves onshore in China. These conventional deep to ultra-deep reservoirs are typically buried at depths exceeding 4500 m, with bottom-hole temperatures surpassing 150 °C. The high temperatures at the bottom of the well are more likely to cause deterioration in drilling fluid properties, altering its rheological properties and reducing cutting transport efficiency, which can lead to wellbore cleaning issues. In this paper, the numerical simulation method is used to analyze the influence of cutting particle size, drilling fluid flow rate, drill pipe rotation speed, and drill pipe eccentricity on the annular cutting concentration under different wellbore drilling fluid temperature conditions. The results show that at the same cutting particle size, as the drilling fluid temperature increases, the cutting concentration in the annulus increases sharply. The increase is the largest when the particle size is 3 mm, and when the drilling fluid temperature is 220 °C, the cutting concentration increases by 79.7% compared to at 200 °C and by 279% compared to at 180 °C. When the flow rate increases from 0.5 m/s to 1.0 m/s, the annular cutting concentration at drilling fluid temperatures of 220 °C and 200 °C decreases by 70.5% and 50.4%, respectively. The higher the drilling fluid temperature, the better the cutting removal effect when increasing the drill pipe rotation speed. However, when the rotation speed exceeds 120 rpm, the change in cutting concentration with increasing rotation speed becomes insignificant. When the drill pipe eccentricity is small, an increase in drilling fluid temperature leads to a significant rise in annular cutting concentration. However, when the drill pipe eccentricity is large, changes in drilling fluid temperature have a smaller impact on cutting concentration. The research findings can provide engineering guidance and theoretical support for the design of drilling fluid hydraulic parameters for cutting transport and rheological parameters in high-temperature wellbores. [ABSTRACT FROM AUTHOR]

Based on the technical issues encountered during underground pipe jacking construction in the Jining area, a series of ring shear tests were conducted on silty clay below the groundwater level to investigate the interfacial friction characteristics under the lubrication of thixotropic slurry during construction. Seven different slurry formulations were prepared, and ring shear tests were conducted under varying normal stresses, shear rates, and shear displacements. The friction characteristics during the shearing process were analyzed, and the corresponding friction coefficients were determined. The experimental results indicate that shear stress increases with increasing normal stress, but it is not affected by shear rate and shear displacement. As normal stress increases, the friction coefficient also exhibits a slight rise, which may be due to the uneven distribution of the slurry under pressure. Among the seven formulations, Slurry 1 exhibited the best lubricating effect, which reduced the friction coefficient by 64.5%, while Slurry 0 had the poorest effect with a reduction of 42.6% in friction coefficient. Additionally, the excessive addition of bentonite in the slurry reduces its lubricating effect, and the content of fiber has a significant effect on the friction reduction degree by thixotropic slurry. [ABSTRACT FROM AUTHOR]

Phosphorus deficiency critically constrains crop growth. Soil microbial diversity, which is crucial for maintaining terrestrial ecosystem integrity, plays a key role in promoting soil P cycling. Therefore, it is imperative to understand the survival strategies of microorganisms under P-limited conditions and explore their roles in community regulation. We initiated a comprehensive, long-term, in situ wheat field experiment to measure soil physicochemical properties, focusing on the different forms of soil inorganic P. Subsequently, 16S rRNA and ITS marker sequencing was employed to study changes in soil microbial abundance and community structure and predict functional alterations. The results showed that soil water and P deficiencies significantly affected wheat growth and development, soil physicochemical properties, and microbial diversity and function. Prolonged P deficiency lowered soil pH, significantly increasing phosphatase content (58%) under W1 (normal irrigation) conditions. Divalent calcium phosphate decreased significantly under W0 (lack of irrigation) and W1 conditions, and the most stable ten-valent calcium phosphate began to transform under W0 conditions. Soil microbial diversity increased (e.g., Proteobacteria and Vicinamibacterales) and enhanced the transport capacity of bacteria. P deficiency affected the coexistence networks between bacteria and fungi, and SEM (structural equation modeling) analysis revealed a stronger correlation in bacteria (r2 = 0.234) than in fungi (r2 = 0.172). In soils deprived of P for 7 years, the soil P content and forms were coupled with microbial changes. Microorganisms exhibited community and functional changes in response to low-phosphorus soil, concurrently influencing soil P status. This study enhances our understanding of rhizospheric processes in soil P cycling under microbial feedback, particularly the impact of microbial interactions on changes in soil P forms under P-limited conditions. [ABSTRACT FROM AUTHOR]

The section span of the withdrawal space of fully mechanized top coal caving in an extra-thick coal seam is large, and with the gradual withdrawal of the hydraulic support, a series of strong dynamic pressure disasters occur in the withdrawal space, and the difficulty of surrounding rock support control increases sharply. In order to study the control mechanism of surrounding rock in the final mining withdrawal space in detail and put forward a reasonable support technology scheme, taking the large-section withdrawal space of an 8309 fully mechanized caving face in an extra-thick coal seam of a mine as the research object—through the theoretical investigation of whether the key blocks of the main roof are stably hinged under varied stopping coal caving distances and fracture locations of the main roof—the reasonable and optimal stopping coal caving distances and roadway formation time are determined. Using numerical simulation and similar simulation methods, the vertical stress and the maximum shear stress research indicators were introduced to verify the accuracy of the theoretical analysis results. The results show the following: (1) The reasonable stopping coal caving span is 1~2 times the cycle weighting interval, the best stopping coal caving distance in this geological condition is 30 m, and the best fracture position of the main roof is located above the goaf. (2) The migration of overlying strata in the withdrawal space has obvious zoning characteristics, and the zoning is as follows: a stopping coal caving area, support area of the hydraulic support, withdrawal channel area, and stopping coal pillar area. (3) According to the zoning characteristics of overlying strata movement, the asymmetric zoning support control scheme of the withdrawal space is proposed. The field monitoring results show that the maximum roof subsidence in the withdrawal space is 151 mm, the maximum internal squeezing amount of the stopping coal pillar is 82 mm, and the supporting and anchoring effect of each partition in the withdrawal space is good. The set of partition asymmetric support control schemes has been successfully applied to field practice. [ABSTRACT FROM AUTHOR]

In reality, the remaining oil in the ultra-high water cut period is highly dispersed, so a thorough investigation is required to understand the microscopic remaining oil. This will directly influence the technological direction and allow for countermeasures such as enhanced oil recovery (EOR). Therefore, this study aims to investigate the state, classification method and utilization mechanism of the microscopic remaining oil in the late period of the ultra-high water cut. To achieve this, the classification of microscopic remaining oil based on mechanical mechanism was developed using displacement CT scan and micro-scale flow simulation methods. Three carefully selected mechanical characterization parameters were used: oil–water connectivity, oil–mass specific surface and oil–water area ratio. These give five types of microscopic remaining oil, which are as follows: A (capillary and viscous oil cluster type), B (capillary and viscous oil drop type), C (viscous oil film type), D (capillary force control throat type), and E (viscous control blind end type). The state of the microscopic remaining oil in classified oil reservoirs was defined after high-expansion water erosion. Based on micro-flow simulation and analysis of different forces during the displacement process, the main microscopic remaining oil recognized is in class-I, class-II and class-III reservoirs. Within the Eastern sandstone oilfields in China, the ultra-high water-cut stage is a good indicator that the class-I oil layer is dominated by capillary and viscous oil drop types distributed in large connected holes. The class-II oil layer has capillary and viscous force-controlled clusters distributed in small and medium pores with high connectivity. In the case of the class-III oil layer, it enjoys the support of capillary force control throats that are mainly distributed in small holes with high connectivity. Integrating mechanisms of different types of micro-remaining oil indicates that, enhancing utilization conditions requires increasing pressure gradient and shear force while reducing capillary resistance. An effective way to improve the remaining oil utilization is to increase the pressure gradient and change the flow direction during the water-drive development process. Hence, this forms a theoretical basis and a guide for the potential exploitation of remaining oil. Likewise, it provides a strategy for optimizing enhanced oil recovery in the ultra-high water-cut stage of mid-high permeability oil reservoirs worldwide. [ABSTRACT FROM AUTHOR]

Porous Ni-Mn-Ga shape memory alloys (SMAs) were prepared by powder metallurgy using NaCl as a pore-forming agent with an average pore size of 20–30 μm. The microstructure, phase transformation, superelasticity, and elastocaloric properties of the porous alloys were investigated. The prepared porous alloy had a uniform pore distribution and interconnected microchannels were formed. Cu doping can effectively improve the toughness of a porous alloy, thus improving the superelasticity. It was found that porous Ni-Mn-Ga-Cu SMAs have a flat stress plateau, which exhibits a maximum elongation of 5% with partially recoverable strain and a critical stress for martensite transformation as low as about 160 MPa. In addition, an adiabatic temperature change of 0.6 K was obtained for the prepared porous alloy at a strain of 1.2% at about 150 MPa. This work confirms that the introduction of porous structures into polycrystalline Ni-Mn-Ga SMAs is an effective way to reduce costs and improve performance, and provides opportunities for engineering applications. [ABSTRACT FROM AUTHOR]

The rapid increase in electric vehicles (EVs) poses significant impacts on multi-energy system (MES) operation and energy management. Accurately assessing EV charging demand becomes crucial for maintaining MES stability, making it an urgent issue to be studied. Therefore, this paper proposes a novel deep learning-based EV charging load prediction framework to assess the impact of EVs on the MES. First, to model the EV traffic flow, a modified weight fusion spatial–temporal graph convolutional network (WSTGCN) is proposed to capture the inherent spatial–temporal characteristics of traffic flow. Specifically, to enhance the WSTGCN performance, the modified residual modules and weight fusion mechanism are integrated into the WSTGCN. Then, based on the predicted traffic flow, an improved queuing theory model is introduced to predict the charging load. In this improved queuing theory model, special consideration is given to subjective EV user behaviors, such as refusing to join queues and leaving impatiently, making the queuing model more realistic. Additionally, it should be noted that the proposed charging load predicting method relies on traffic flow data rather than historical charging data, which successfully addresses the data insufficiency problem of newly established charging stations, thereby offering significant practical value. Experimental results demonstrate that the proposed WSTGCN model exhibits superior accuracy in predicting traffic flow compared to other benchmark models, and the improved queuing theory model further enhances the accuracy of the results. [ABSTRACT FROM AUTHOR]

The combination support structure of pile-anchor and frame-anchor is widely used in multi-level slope engineering, but the relevant theoretical research lags behind engineering practice. To make up for this deficiency, this paper takes the multi-level slope under combined support of pile-anchor and frame-anchor as the research object, conducts a model test using the geotechnical centrifuge, analyzes the most relevant structural force and slope deformation in engineering, and provides some reinforcement suggestions. The test results show that the combination support structure of pile-anchor and frame-anchor has a good reinforcement effect on multi-level soil slopes, but the deformation range of the slope is greatly affected by the anchoring structure and the anchor rods located within the deformation zone. The structural force condition is significantly different from traditional structures that place the anchor rod anchoring section in a stable soil layer. According to the structural force characteristics, it is recommended that the support design fully consider the positional relationship between the anchor rods and the sliding surface. The design of the frame-anchor support section should strictly control the anchoring depth, so that the potential sliding surface of the slope can be moved backward, thereby increasing the difficulty of sliding. The design of pile-anchor support should ensure that the anchor rods have sufficient length to provide greater anchoring force, thereby improving the bearing capacity of the pile. These research results can enrich and improve the support design theory of multi-level soil slopes, providing guidance for engineering practice. [ABSTRACT FROM AUTHOR]

During the operation of maglev trains, they are subjected to various disturbances. The presence of these disturbances presents a significant challenge for attaining high-performance control and even poses the risk of system instability. To further enhance the anti-disturbance capability of maglev trains, this paper proposes a model information-assisted modified active disturbance rejection control (MADRC) approach. A mathematical model of the single-point suspension system of maglev trains is constructed for the design of the extended state observer (ESO), which is a modified extended state observer (MESO), and a nonlinear mechanism is incorporated to boost the performance of the ESO. Owing to the introduction of model information, the estimated quantity of disturbances by MESO no longer considers the system model deviation as a disturbance. Hence, the linear feedback control law is modified accordingly. The MESO is regarded as an ESO with time-varying gain using the equivalent gain method, and its stability is proven using the Lyapunov method. The tracking and anti-disturbance performances of different controllers are compared via simulation experiments. Suspension and anti-disturbance experiments are conducted on the single-point suspension experimental platform, verifying that the proposed MADRC has a more potent suppression ability for load disturbances in the suspension system. [ABSTRACT FROM AUTHOR]

The rise of antibiotic tolerance in bacteria harboring genetic elements conferring resistance to antibiotics poses an increasing threat to public health. However, the primary factors responsible for the emergence of antibiotic tolerance and the fundamental molecular mechanisms involved remain poorly comprehended. Here, we demonstrate that the commonly utilized food additive Benzaldehyde (BZH) possesses the capacity to induce a significant level of fluoroquinolone tolerance in vitro among resistant Escherichia coli. Our findings from animal models reveal that the pre-administration of BZH results in an ineffective eradication of bacteria through ciprofloxacin treatment, leading to similar survival rates and bacterial loads as observed in the control group. These results strongly indicate that BZH elicits in vivo tolerance. Mechanistic investigations reveal several key factors: BZH inhibits the formation of bacterial flagella and releases proton motive force (PMF), which aids in expelling antibiotics from within cells to reducing their accumulation inside. In addition, BZH suppresses bacterial respiration and inhibits the production of reactive oxygen species (ROS). Moreover, exogenous pyruvate successfully reverses BZH-induced tolerance and restores the effectiveness of antibiotics, highlighting how crucial the pyruvate cycle is in combating antibiotic tolerance. The present findings elucidate the underlying mechanisms of BZH-induced tolerance and highlight potential hazards associated with the utilization of BZH. [ABSTRACT FROM AUTHOR]

Simple Summary: Odorant receptors (ORs) are essential to insects' highly efficient and sensitive olfactory system. ORs' stage-specific expression and precise functionality significantly influence insect behavior exhibited during particular developmental stages. Despite larvae possessing a relatively simplistic olfactory system with fewer expressed ORs than adult moths, larvae effectively employ ORs to navigate larval-specific survival challenges. This study investigated the OR SfruOR40 in newly hatched larvae of Spodoptera frugiperda, an invasive agricultural pest also known as the fall armyworm. Subsequent functional characterization indicated that SfruOR40 facilitates the detection of host plant volatiles. Our findings enhance understanding of the olfactory perception mechanisms in S. frugiperda and underscore the significance of OR expression in newly hatched larvae. In the past decade, Spodoptera frugiperda has emerged as a significant invasive pest globally, posing a serious threat to agriculture due to its broad diet, migratory behavior, and ability to cause extensive plant damage. While extensive research has focused on the olfactory capabilities of adult S. frugiperda, understanding of the olfactory process in larvae remains limited, despite larvae playing a crucial role in crop damage. To address this gap, we identified an odorant receptor (OR), SfruOR40, expressed in the first-instar larvae through phylogenetic analysis. Using quantitative real-time PCR, we compared SfruOR40 expression levels in larvae and adults. We then characterized the function of SfruOR40 against 67 compounds using the Xenopus oocyte expression system and found that SfruOR40 responded to three plant volatiles. Further, behavioral experiments revealed a larval attraction to (−)-trans-Caryophyllene oxide. This study elucidates SfruOR40's role in the olfactory recognition of newly hatched S. frugiperda larvae, expanding our knowledge of such mechanisms in Noctuid moths. Furthermore, it highlights the potential of plant-derived natural products for biological pest control from a behavioral ecology perspective. [ABSTRACT FROM AUTHOR]

Currently, there are limitations in the research on the use of carbon fiber geogrids to prevent low-temperature cracking in asphalt pavements. This study aims to comparatively investigate the effects of carbon fiber-based geogrid type and dense-graded asphalt concrete mixture (AC) surface combined body (SCB) type on the low-temperature cracking resistance of reinforced asphalt pavement through low-temperature bending damage tests. Two geogrid types were prepared: a carbon fiber geogrid (CCF) and a glass/carbon fiber composite qualified geogrid (GCF). Two SCB types were studied: AC-13/AC-20 and AC-20/AC-25. The results show that the improvement in the flexural tensile strength of CCF is similar to that for GCF. Moreover, under reinforced conditions, the improvement in the low-temperature cracking resistance of AC-20/AC-25 is better than that for AC-13/AC-20 by 16.26–24.57%. Based on the analysis, the reasonable ratio range of the aperture sizes to the major particle sizes in the dense gradation can achieve a more effective interlocking effect. This can improve the low-temperature cracking resistance of carbon fiber-based geogrid-reinforced samples. Then, increasing the bending absorption energy is a key way of improving the low-temperature cracking resistance of carbon fiber-based geogrid reinforcements. Eventually, the fracture type of carbon fiber-based geogrid-reinforced samples is a mixed plastic–brittle fracture. These results can provide a reference for the road failure analysis of geogrid-reinforced asphalt pavement. [ABSTRACT FROM AUTHOR]

As new advanced vehicles, the safety and stability of electromagnetic suspension maglev trains have always been a subject of concern. This study introduces the improved R index and τ-distance index into the performance evaluation of the suspension control system, respectively assessing the stability of the suspension gap and the smoothness of train operation, combining them with grey relational analysis to achieve data-driven comprehensive evaluation. Furthermore, feasibility tests on the Fenghuang Maglev Express validate the effectiveness and superiority of the comprehensive evaluation method based on measured data. Experimental results demonstrate that the data-driven comprehensive evaluation method, through designing specialized evaluation metrics and increasing assessment dimensions, effectively evaluates the performance of the suspension system control loop. Compared to a traditional error integral comprehensive performance index, it offers greater comprehensiveness and accuracy, along with real-time state-monitoring capabilities. [ABSTRACT FROM AUTHOR]

In social network applications, competitive influence propagation often exhibits a certain degree of time lag. In the scenario of positive and negative competitive propagation studied in this paper, under the premise that negative nodes are activated first, how to find a set of positive seed nodes to participate in competitive propagation is studied, aiming to minimize the spread of negative influence. In the current study, the time complexity of the improved algorithms based on greedy strategies is high, which limits their scope of application in practical scenarios; some heuristic algorithms achieve better scalability, but there is still much room for improvement. Therefore, this paper proposes a new method to solve the influence propagation problem of delayed competition, also known as a heuristic propagation factor evaluation algorithm (HeuPFE). The main process is as follows: (1) We build a shortest path snapshot for the nearest propagation region of negative nodes and reduce the search space of competing nodes. (2) Then, we construct a node propagation factor evaluation method based on this shortest negative-oriented node path snapshot to reduce computational complexity. Comparing results with those of traditional heuristic algorithms, we carry out experiments on real datasets and verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

As they are the core components of the drive motor in electric vehicles, the accurate fault diagnosis of rolling bearings is the key to ensuring the safe operation of electric vehicles. At present, intelligent diagnostic methods based on current signals (CSs) are widely used owing to the advantages of the easy collection, low cost, and non-invasiveness of CSs. However, in practical applications, the fault characteristics of the CS are weak, resulting in diagnostic performance that fails to meet the expected standards. In this paper, a diagnosis method is proposed to address this problem and enhance the diagnosis accuracy. Firstly, CSs from two phases are processed by periodic resampling to enhance data features, which are then fused through splicing operations. Subsequently, a feature enhancement module is constructed using multi-scale feature fusion for decomposing the input. Finally, a diagnosis model is constructed by using an improved channel attention module (CAM) for enhancing the diagnosis performance. The results from experiments containing two different types of bearing datasets show that the proposed method can extract high-quality fault features and improve the diagnosis accuracy, presenting great potential in intelligent fault diagnosis and the maintenance of electric vehicles. [ABSTRACT FROM AUTHOR]

The South China Block, a region renowned for its extensive granite distribution and rich metal deposits, serves as a natural laboratory for the study of granite-related mineralization. This research focuses on the Tongtianmiao granite pluton, which is located at the intersection of the Qin-Hang and Nanling metallogenic belts and has been confirmed as a significant lithium mineral resource. Despite its discovery and ongoing development, the lithium-rich Tongtianmiao pluton has been understudied, particularly concerning its petrogenesis, which has only recently come to the forefront of scientific inquiry. By integrating an array of petrogeochemical data with geochronological studies derived from zircon and monazite dating, this study provides insights into the magmatic processes related to lithium enrichment in the Tongtianmiao granites. The Tongtianmiao granites are classified as A-type granites characterized by high SiO2 contents (69.18–78.20 wt.%, average = 74.08 wt.%), K2O + Na2O contents (4.59–8.34 wt.%, average = 6.86 wt.%), A/CNK > 1.2, and low concentrations of Ca, Mg, and Fe. These granites are enriched in alkali metals such as Li, Rb, and Cs but are significantly depleted in Ba, Sr, and Eu. They show no significant fractionation of light or heavy rare-earth elements but present characteristic tetrad effects. A finding of this study is the identification of multiple ages from in situ zircon U–Pb dating, which implies a prolonged history of magmatic activity. However, given the high uranium content in zircons, which could render U–Pb ages unreliable, emphasis is placed on the monazite U–Pb ages. These ages cluster at approximately 172.1 ± 1.1 Ma and 167.9 ± 1.6 Ma, indicating a Middle Jurassic period of granite formation. This timing correlates with the retreat of the Pacific subduction plate and the associated NE-trending extensional fault activity, which likely provided favorable conditions for lithium enrichment. The study concluded that the Tongtianmiao granites were formed through partial melting of crustal materials and subsequent underplating by mantle-derived materials, and were contaminated by strata materials. This process resulted in the formation of highly differentiated granite through magmatic differentiation and external forces. These findings have significant implications for understanding the petrogenesis of lithium-rich granites and are expected to inform future exploration endeavors in the Tongtianmiao pluton. [ABSTRACT FROM AUTHOR]

Returning extraterrestrial samples to Earth for analysis is crucial for planetary geological research and resource utilization. However, during their return journey, these samples undergo significant environmental changes, such as varying pressure, temperature, impact, and vibration. Hence, a dependable sealing technique that preserves sample integrity without requiring high-powered tools is necessary. This article aims to develop an automatic sealing system for collecting extraterrestrial samples, conducting parametric design and mechanical analysis on two types of proposed sealing structures with minimal sealing force as the benchmark. Additionally, the system will undergo validation through sealing and leakage detection experiments. An automated sealing system, capable of storing samples in multiple sampling tubes, is assembled for the extraterrestrial sampling device. [ABSTRACT FROM AUTHOR]

Olfaction is critical for guiding the physiological activities of insects, with antennae being the primary olfactory organs. However, recent evidence suggests that other tissues may also participate in olfactory recognition. Among these, the genitalia of moths have received attention due to their roles in mating and oviposition. Sensilla and odorant receptors (ORs) in moth genitalia highlight the potential olfactory function of these structures. In this study, we examined the olfactory sensing capacity of the genitalia in Helicoverpa armigera by analyzing their structure in males and females and characterizing the expressed ORs. Scanning electron microscopy uncovered many sensilla distributed throughout the male and female genitalia. Transcriptome sequencing identified 20 ORs in the genitalia, with HarmOR68 exhibiting significant responses to methyl esters: methyl benzoate and salicylate. Our findings provide theoretical evidence that H. armigera genitalia may have significant olfactory perception functions. [ABSTRACT FROM AUTHOR]

As concerns about indoor air quality increase, air purifiers and fresh air systems are increasingly being used in conjunction with air conditioners in office buildings. To study the synergistic effects of multisystem joint operation on indoor air quality, this study used a combination of experimental and simulation methods to study the indoor particulate matter with a diameter of less than 2.5 µm (PM2.5) and carbon dioxide (CO2) concentrations under different operation conditions. The purification time and the PM2.5 concentration distribution under different conditions were compared with the condition in which the purifier was used alone. The results showed that the purification time required for the condition that the air conditioner runs together with the purifier was shortened by 15.2%. When the fresh air system is running together with the purifier, the purification time can be reduced by 30.4%. It was reduced by 32.6% when the three systems were operating at the same time. The PM2.5 concentration distribution under the joint operating condition was much more even than that under the condition in which the purifier was running alone. To analyze the impact on the CO2 distribution, the CO2 distributions under different joint operations were compared. The results show that the fresh air system can effectively dilute CO2 below 1000 ppm in 30 min. The air conditioner and purifier could help to mix the indoor air to provide a much more uniform indoor CO2 distribution. [ABSTRACT FROM AUTHOR]

Mealy peaches are dry and flavorless, which reduces their consumer acceptance. A deeper understanding of the mechanism underlying mealiness is crucial to enhancing peach fruit quality. In this study, comparative profiling was conducted on CP13, CP14, CM, and RM peaches. Sensory evaluation indicated that CP13 and CM are non-mealy clingstone and freestone peaches, respectively, and CP14 and RM are mealy freestone peaches. Both CP13 and CP14, identified as stony hard (SH) peaches, exhibited minimal ethylene release, whereas CM and RM, identified as melting flesh (MF) peaches, released high amounts of ethylene during the ripening process. Scanning electron microscopy (SEM) microstructure observation indicated that cells in the flesh tissue of mealy peaches, CP14 (SH) and RM (MF), were intact and separated, with large intercellular spaces and irregular arrangements. The main factor that promotes mealiness is differences in pectin metabolism, which impact cell wall composition. The fluctuations in polygalacturonase (PG) and pectin methylesterase (PME) activity between mealy and non-mealy peaches were the main factor contributing to mealiness. However, the changes in cell wall metabolism that caused these fluctuations did not have a clear direction. Using transcriptome analysis and weighted gene co-expression network analysis (WGCNA), we were able to identify forty differentially expressed genes (DEGs) that are associated with mealy patterns. Among these DEGs, genes encoding PG were significantly upregulated in mealy peaches (CP14 and RM) compared to non-mealy peaches (CP13 and CM). PpPG1 was the main effector gene for mealiness, while PpPG2, PpEGase2, PpEXP1, PpEXP3, PpAGP2, PpIAA4, and PpABA2 were identified as candidate genes regulating peach mealiness. These findings provide a solid experimental basis for understanding the textual distinctions between mealy and non-mealy peaches. [ABSTRACT FROM AUTHOR]

In this work, we consider the physical basis of deformation and fracture in layered composite nanocrystalline/amorphous material–low-melting crystalline alloy in a wide temperature range. Deformation and fracture at the crack tip on the boundary of such materials as nanocrystalline alloy of the trademark 5BDSR, amorphous alloy of the trademark 82K3XSR and low-melting crystalline alloy were experimentally investigated. The crack was initiated by uniaxial stretching in a temperature range of 77–293 K. A theoretical description of the processes of deformation and fracture at the crack tip is proposed, with the assumption that these processes lead to local heating and ensure the plastic character of crack growth at liquid nitrogen temperatures. The obtained results improve the theoretical understanding of the physics of fracture at the boundary of nanocrystalline and crystalline alloys in a wide temperature range. The possibility of preserving the plastic nature of fracture in a thin boundary layer of crystalline–nanocrystalline material at cryogenic temperatures has been experimentally shown. [ABSTRACT FROM AUTHOR]

The lattice Boltzmann method is employed in the current study to simulate the heat transfer characteristics of sinusoidal-temperature-distributed heat sources at the bottom of a square cavity under various conditions, including different amplitudes, phase angles, initial positions, and angular velocities. Additionally, a machine learning-based model is developed to accurately predict the Nusselt number in such a sinusoidal temperature distribution of heat source at the bottom of a square cavity. The results indicate that (1) in the phase angle range from 0 to π, Nu basically shows a decreasing trend with an increase in phase angle. The decline in Nu at an accelerated rate is consistently observed when the phase angle reaches 4π/16. The corresponding Nu decreases as the amplitude increases at the same phase angle. (2) The initial position of the sinusoidal-temperature-distributed heat source Lc significantly impacts the convective heat transfer in the cavity. Moreover, the decline in Nu was further exacerbated when Lc reached 7/16. (3) The optimal overall heat transfer effect was achieved when the angular velocity of the non-uniform heat source reached π. As the angular velocity increases, the local Nu in the square cavity exhibits a gradual and oscillatory decline. Notably, it is observed that Nu at odd multiples of π surpasses that at even multiples of π. Furthermore, the current work integrates LBM with machine learning, enabling the development of a precise and efficient prediction model for simulating Nu under specific operational conditions. This research provides valuable insights into the application of machine learning in the field of heat transfer. [ABSTRACT FROM AUTHOR]

Water vapor adsorption on soil, a crucial non-rainfall water resource in arid regions, warrants further experimental investigation, particularly on two typical land surfaces: bare soil and gravel. This study examined the formation characteristics and influencing factors of vapor adsorption in an arid region of Northwestern China. Observations and analyses were conducted on adsorption and evaporation measurements taken by two small weighing lysimeters (SLSs); soil temperature at a depth of 5 cm; surface temperature; relative humidity; and air temperature at a height of 30 cm above the ground from 2019 to 2020. The adsorbed water in this area was more abundant at night and less abundant during the day, with a stable nightly adsorption rate of 0.013 mm/h. Adsorption was more frequent in spring and winter (from January to June and November to December), accounting for about 90% of the total annual adsorption. In 2019 and 2020, the ratio values of adsorption to evaporation were 0.16 and 0.10 for bare soil, and 0.10 and 0.12 for gravel, respectively. Adsorption was more likely to occur when the soil moisture content was less than 13%; the highest adsorption frequency was close to 20% when the RH was between 75 and 95%; low soil temperatures were more conducive to the occurrence of adsorption. The effect of temperature differences (Ta−Ts) on adsorption was stronger than that of relative humidity. The adsorption frequency generally showed a bimodal change with increasing temperature difference, but the effect of temperature differences was less effective for gravel than bare soil. When the relative humidity was high and the temperature difference was weakly positive, the maximum adsorption intensity could reach 0.18 mm/h. [ABSTRACT FROM AUTHOR]

AI-driven mineral prospectivity mapping (MPM) is a valid and increasingly accepted tool for delineating the targets of mineral exploration, but it suffers from noisy and unrepresentative input features. In this study, a set of fractal and multifractal methods, including box-counting calculation, concentration–area fractal modeling, and multifractal analyses, were employed to excavate the underlying nonlinear mineralization-related information from geological features. Based on these methods, multiple feature selection criteria, namely prediction–area plot, K-means clustering, information gain, chi-square, and the Pearson correlation coefficient, were jointly applied to rank the relative importance of ore-related features and their fractal representations, so as to choose the optimal input feature dataset readily used for training predictive AI models. The results indicate that fault density, the multifractal spectrum width (∆α) of the Yanshanian intrusions, information dimension (D1) of magnetic anomalies, correlation dimension (D2) of iron-oxide alteration, and the D2 of argillic alteration serve as the most effective predictor features representative of the corresponding ore-controlling elements. The comparative results of the model assessment suggest that all the AI models trained by the fractal datasets outperform their counterparts trained by raw datasets, demonstrating a significant improvement in the predictive capability of fractal-trained AI models in terms of both classification accuracy and predictive efficiency. A Shapley additive explanation was employed to trace the contributions of these features and to explain the modeling results, which imply that fractal representations provide more discriminative and definitive feature values that enhance the cognitive capability of AI models trained by these data, thereby improving their predictive performance, especially for those indirect predictor features that show subtle correlations with mineralization in the raw dataset. In addition, fractal-trained models can benefit practical mineral exploration by outputting low-risk exploration targets that achieve higher capturing efficiency and by providing new mineralization clues extracted from remote sensing data. This study demonstrates that the fractal representations of geological features filtered by multi-criteria feature selection can provide a feasible and promising means of improving the predictive capability of AI-driven MPM. [ABSTRACT FROM AUTHOR]

Strawberry plants require light for growth, but the frequent occurrence of low-light weather in winter can lead to a decrease in the photosynthetic rate (Pn) of strawberry plants. Light-emitting diode (LED) systems could be used to increase Pn. However, the changes in the phytohormones and transcriptomic reprogramming in strawberry leaves under different light qualities are still unclear. In this study, we treated strawberry plants with sunlight, sunlight covered with a 50% sunshade net, no light, blue light (460 nm), red light (660 nm), and a 50% red/50% blue LED light combination for 3 days and 7 days. Our results revealed that the light quality has an effect on the contents of Chl a and Chl b, the minimal fluorescence (F0), and the Pn of strawberry plants. The light quality also affected the contents of abscisic acid (ABA), auxin (IAA), trans-zeatin-riboside (tZ), jasmonic acid (JA), and salicylic acid (SA). RNA sequencing (RNA-seq) revealed that differentially expressed genes (DEGs) are significantly enriched in photosynthesis antenna proteins, photosynthesis, carbon fixation in photosynthetic organisms, porphyrin and chlorophyll metabolisms, carotenoid biosynthesis, tryptophan metabolism, phenylalanine metabolism, zeatin biosynthesis, and linolenic acid metabolism. We then selected the key DEGs based on the results of a weighted gene co-expression network analysis (WGCNA) and drew nine metabolic heatmaps and protein–protein interaction networks to map light regulation. [ABSTRACT FROM AUTHOR]

A porous Ni50Mn28Ga22 alloy was produced using powder metallurgy, with NaCl serving as the pore-forming agent. The phase structure, mechanical properties, and magnetic properties of annealed bulk alloys and porous alloys with different pore sizes were analyzed. Vacuum sintering for mixed green billets in a tube furnace was employed, which facilitated the direct evaporation of NaCl, resulting in the formation of porous alloys characterized by a complete sinter neck, uniform pore distribution, and consistent pore size. The study found that porous alloys within this size range exhibit a recoverable shape memory performance of 3.5%, as well as a notable decrease in the critical stress required for martensitic twin shear when compared to that of bulk alloys. Additionally, porous alloys demonstrated a 2% superelastic strain when exposed to 353 K. Notably, under a 1.5 T magnetic field, the porous Ni50Mn28Ga22 alloy with a pore size ranging from 20 to 30 μm exhibited a peak saturation magnetization of 62.60 emu/g and a maximum magnetic entropy of 1.93 J/kg·K. [ABSTRACT FROM AUTHOR]

The investigation of the features of laser control over the state of nanoscale objects in solid materials is an urgent task of condensed matter physics. We experimentally established the potential for the simultaneous enhancement of hardness and resistance to surface cracking in a titanium alloy due to selective laser irradiation. The regularities of selective heating near nanopores and the influence of the nanopore system on the features of isotherm propagation have been revealed. A physical model is proposed for the healing of nanopores situated in the surface layer of the sample. According to this model and as a result of laser irradiation and laser plasma, a brief transition of the material surface to extreme conditions is initiated. [ABSTRACT FROM AUTHOR]

Plan view pattern control (PVPC) is a highly effective means to improve the rectangularization of products and increase the yield of plate mills. By optimizing the parameters of PVPC, the effect of PVPC can be further improved. In this paper, a digital model for predicting and controlling crop patterns of plates is proposed based on the radial basis function (RBF) neural network optimized by the dung beetle optimizer (DBO) algorithm. Machine vision technology is used to obtain a digital description of the crop pattern of the rolled plates. An automatic threshold adjustment algorithm is proposed for the image processing of plate pattern photos during the rolling process. The error between the pattern data calculated through machine vision technology and the measured pattern data does not exceed 3 mm. The spread parameters of the RBF are optimized using DBO, and the digital model structure is established. The goodness of fit (R2) and the mean absolute error (MAE) are used as evaluation indicators. The results show that the digital model established based on DBO-RBF has good predictive and control performance, realizing intelligent prediction of the crop pattern of plates and the parameter optimization of PVPC. In practical applications, the crop cutting loss area of irregular deformation at the end of the plate can be reduced by 31%. [ABSTRACT FROM AUTHOR]

The carbonation of industrial calcium-rich byproducts such as steel slag demonstrates significant potential for CO2 sequestration. This technique aids in reducing carbon emissions while also promoting waste recycling. Despite its advantages, gaps remain in the understanding of how steel slag characteristics and operational parameters influence the carbonation process, as well as the underlying mechanism of direct aqueous carbonation. We evaluated the carbonation performance of three types of steel slag at temperatures below 100 °C. The slag with the highest CO2 sequestration capacity was chosen for a systematic evaluation of the effects of operating conditions on carbonation efficiency. Thermodynamic analysis indicated that the reactivity of CaO and Ca(OH)2 with CO2 exceeded that of CaO·SiO2 and 2CaO·SiO2. Under conditions of 85 °C, a particle size less than 75 μm, an initial CO2 pressure of 0.5 MPa, a liquid-to-solid ratio of 5 mL/g, and a stirring speed of 200 rpm, the steel slag achieved a sequestration capacity (K) of 283.5 g(CO2)/kg and a carbonation efficiency (ζCa) of 51.61%. Characterization of the slag before and after carbonation using X-ray diffraction, SEM-EDS, thermogravimetric analysis, and Fourier transform infrared spectrometry confirmed the formation of new carbonates. Mechanistic analysis revealed that the rate-limiting step initially involved the mass transfer of CO2, transitioning to Ca2+ mass transfer as time progressed. Our research provides a viable technique for CO2 capture and a beneficial approach for reutilizing waste steel slag. Furthermore, solid residues after capturing CO2 have the potential for conversion into carbon-negative building materials, offering a sustainable strategy for steel companies and other enterprises with high carbon emissions. [ABSTRACT FROM AUTHOR]

The storage of peach fruits at 4–5 °C can easily lead to chilling injury and greatly reduce the quality and commercial value of peach fruits. In this study, two kinds of peach fruits (CX and CM) were selected to analyze the mechanisms of chilling injury in fruits with different chilling sensitivity by means of their lipidomic, transcriptome, and dynamic changes in plant hormones. We found that the ethylene, abscisic acid (ABA), and lipid contents changed differently between CX and CM. The ABA and dilactosyl diacylglycerol (DGDG) contents significantly increased after refrigeration in CM fruit, leading to strong cold resistance. However, low temperatures induced a greater accumulation of ethylene, phospholipids, and ABA-GE in CX fruit than in CM fruit, eventually leading to more severe CI symptoms in CX fruit. Additionally, a transcriptional regulatory network for CM and CX fruits during cold storage was constructed, providing a new theoretical reference for the cultivation of cold-resistant peach cultivars and the development of postharvest preservation technology. [ABSTRACT FROM AUTHOR]

As the stress of the frame, especially the bottom side rail supports and bottom inclined supports, of a traditional LNG tank container could be significantly greater than its allowable stress, and the container cannot meet the strength requirement of the specification when it is impacted by a transport vehicle during railway transportation, three improved frame structures were suggested, which removed or changed the side rails or bottom inclined supports; the stress and deformation of these improved frames and the tank container were analyzed using the finite element method under the impact test. The results show that all three improved frames can meet the strength requirement, i.e., the maximum Mises stress is less than the allowable stress and the deformation requirement of the diagonal length difference is less than the allowable value, meaning that the tank containers with improved frames can pass the impact test. Moreover, for the FRP support rings and impact side heads, although the maximum values are different, they are still less than the respective allowable stresses. In addition, the maximum value of the middle cross section of the outer vessel in the direction of gravity does not increase with the change in the frame, and the deformation of the outer vessel remains within the elastic range. Therefore, the improvements of the frames have little effect on the stress and deformation of the other components of the tank container, in particular, the inner vessel and outer vessel. Compared to the frame of the traditional tank container, removing the side rails partially or completely can reduce the weight of the frame by 17.99% and 38.34%, respectively, greatly reducing manufacturing and transportation costs. It can also reduce the maximum Mises stress by 38.89% and 39.24% and the maximum diagonal difference by 57.95% and 61.16%. [ABSTRACT FROM AUTHOR]

To investigate the retarding effect of bonding the shape memory alloy (SMA) patches on crack propagation in steel plates, both numerical and experimental analyses were conducted in the present study. A compact tension (CT) model was developed to clarify the feasibility of bonding the SMA patch to the reinforcement of the mode Ⅰ, mode Ⅱ, and mode Ⅲ cracks. On this basis, parametric analysis was conducted to investigate the strengthening parameters, i.e., the bonding area, the thickness, and the strengthening angle of the SMA patch. Subsequently, fatigue tests on the unreinforced steel plate and cracked steel plate strengthened by the SMA patches were conducted. The monitored stress variation, crack propagation behavior, and fatigue fracture surfaces were analyzed. Findings are meaningful to the application of the SMA reinforcement method in practical engineering. [ABSTRACT FROM AUTHOR]

In order to have a better understanding of the shear creep characteristics of muddy interlayer in unstable landslides, we took the more "inferior" clay muddy interlayer as the research object, and shear creep experiments under different normal stress levels were carried out by means of hierarchical loading. This paper focuses on the variation law of creep curve and its long-term strength in the clay-type muddy interlayer under different normal stresses. The results showed that the creep characteristics of clay-type muddy interlayer were obvious: at the same normal stress level, instantaneous deformation, initial creep and stable creep appeared at lower shear stress level; at the level of rupture shear stress, there were two cases: the creep curve included three stages of typical initial creep, stable creep and accelerated creep failure, or directly entered the accelerated creep stage until the specimen's failure. The average shear and stable creep rate of the muddy interlayer specimen increased exponentially with the increase in shear stress. The empirical formula u = u0 + A [1 − e(−Bt)] + Ctn of shear strength could better reflect the creep deformation law of muddy interlayer, and the correlation coefficient R2 varies from 0.90 to 0.99. Based on the definition of long-term ultimate strength, the long-term strength of clay-type muddy interlayer was determined. [ABSTRACT FROM AUTHOR]

Niobium pentoxide (Nb2O5), as an important dielectric and semiconductor material, has numerous crystal polymorphs, higher chemical stability than water and oxygen, and a higher melt point than most metal oxides. Nb2O5 materials have been extensively studied in electrochemistry, lithium batteries, catalysts, ionic liquid gating, and microelectronics. Nb2O5 polymorphs provide a model system for studying structure–property relationships. For example, the T-Nb2O5 polymorph has two-dimensional layers with very low steric hindrance, allowing for rapid Li-ion migration. With the ever-increasing energy crisis, the excellent electrical properties of Nb2O5 polymorphs have made them a research hotspot for potential applications in lithium-ion batteries (LIBs) and supercapacitors (SCs). The basic properties, crystal structures, synthesis methods, and applications of Nb2O5 polymorphs are reviewed in this article. Future research directions related to this material are also briefly discussed. [ABSTRACT FROM AUTHOR]

After entering the ultra-high water cut stage of multilayer oil reservoirs, the remaining oil is highly dispersed. Due to the continuous development of general water injection, the generation of advantageous channels makes interlayer contradictions more prominent, and the differences in the utilization between different layers are even greater. After the water drive development of multilayer oil reservoirs enters the ultra-high water cut stage, the development effect deteriorates year by year. Layer restructuring is an effective method of improving the water injection development effect and increasing the degree of utilization. In essence, its goal is to achieve balanced utilization for multiple development layers to increase the degree of recovery. This article mainly employs physical simulation experiments combined with reservoir numerical simulation technology to jointly study the effects of different equilibrium production strategies in the ultra-high water cut period of multilayer oil reservoirs and their mechanism of action based on the remaining oil distribution field and streamline field. As a specific implementation, we use large-plate physical simulation to demonstrate the effectiveness of the rotational injection and production strategy, and to supplement the physical simulation experiment with a reservoir numerical simulation model, we analyze the mechanism of different balanced production strategies. The research results for the combination of physical simulation experiments and numerical simulation experiments show that the combined strategy of rotary injection and rotary production is the most effective method for use in multilayer and ultra-high water cut oil reservoirs. The displacement effect of the high-permeability layer is better, and the increase in the recovery degree is relatively large, while the displacement effect of the low-permeability layer is relatively weak. After conventional water drive oil recovery, the remaining oil mainly exists in the edge area of the research area. However, the use of three-dimensional well network injection wheel recovery changes the streamline field, produces the effect of fluid flow diversion, expands the water drive sweep coefficient, and improves the recovery rate. Chemical plugging can effectively replace water drive oil recovery and will become the main method for improving the recovery rate of such reservoirs in the lower part. [ABSTRACT FROM AUTHOR]

Effective notch stress (ENS) approaches have many application prospects in fatigue damage assessments; however, an ENS can only be obtained by conducting complex and time-consuming numerical analyses, deterring many engineers from applying such an approach. In terms of the rib–deck weld in orthotropic steel decks (OSDs), predictive formulae for determining the ENS concentration factors (ENS-based SCFs) have been proposed; however, the effect of asphalt surfacing is not involved, which limits their applications in practical engineering. In the present study, refined finite element (FE) models, including asphalt surfacing, were developed to obtain the ENS-based SCFs which could be applied to practical engineering. Parametric analyses were conducted to investigate the effect of the transverse loading position, the combined effect of the transverse loading position and asphalt surfacing, and the effect of the temperature of the asphalt surfacing. The amplification coefficients (kSCF, kSCF1, and kSCF2) were introduced to determine the ENS-based SCFs on the basis of the predictive formulae without considering the effect of asphalt surfacing. Results show that the ENS-based SCFs of the rib–deck weld is considerably affected by the transverse position of wheel loading and the asphalt surfacing. The cubic polynomial function could be employed to fit the numerical results of the ENS-based SCFs and amplification coefficients (kSCF, kSCF1, and kSCF2) with high fitting precision. Predictive formulae for determining the ENS-based SCFs corresponding to arbitrary transverse loading position and temperature of asphalt surfacing are proposed. The validation investigation turns out that the relative error of the proposed formulae is within 10%, indicating the feasibility of using this approach for engineering applications. [ABSTRACT FROM AUTHOR]

Broadband millimeter-wave power amplifiers have attracted much attention and have wide applications for 5G communication, satellite communication, radar, sensing, etc. Yet, it is challenging to design a power amplifier with broadband small-signal gain and power performance simultaneously. In this study, a transformer-based symmetrical magnetically coupled resonator (MCR) matching network for broadband output matching and stagger-tuned MCRs are used to achieve both broadband small- and large-signal performance. Also, to enhance the gain for the power amplifier, a three-stage common-source pseudo-differential structure is adopted to mitigate the low-gain issue due to stagger tuning, and the shunt resistors aimed to decrease the Q factor of the MCRs. We used the in-phase two-way current combined with microstrip transmission lines to increase the output power. Designed in 65 nm bulky CMOS technology, the power amplifier presents a 3 dB small-signal gain bandwidth from 25.8 GHz to 36.9 GHz, indicating a peak gain of 25.87 dB at 30.5 GHz. The power amplifier demonstrates a 17.84 dBm saturated output power ( P s a t ) at 31 GHz and a 24.37% peak power added efficiency ( P A E m a x ) at 28 GHz. The power amplifier achieves a flat P s a t of 17.44 ± 0.4 dBm, a P A E m a x of 22.59 ± 1.78%, and an O P 1 d B of 13.78 ± 0.31 dBm from 26 GHz to 36 GHz. [ABSTRACT FROM AUTHOR]

As virtual reality and 3D-modeling technology continue to advance, the amount of digital geometric media data is growing at an explosive rate. For example, 3D meshes, an important type of digital geometric media, can precisely record geometric information on a model's surface. However, as the complexity and precision of 3D meshes increase, it becomes more challenging to store and transmit them. The traditional method of compressing non-isomorphic 3D-mesh sequences through frame-by-frame compression is inefficient and destroys the inter-frame correlations of the sequences. To tackle these issues, this study investigates the generation of time-dependent geometric image sequences for compressing non-isomorphic 3D-mesh sequences. Two methods are proposed for generating such sequences: one through image registration and the other through parametrization-geometry cooperative registration. Based on the experimental compression results of the video-coding algorithms, it was observed that the proposed geometric image-sequence-generation method offers superior objective and subjective qualities, as compared to the traditional method. [ABSTRACT FROM AUTHOR]

Leaf photosynthetic pigments play a crucial role in evaluating nutritional elements and physiological states. In facility agriculture, it is vital to rapidly and accurately obtain the pigment content and distribution of leaves to ensure precise water and fertilizer management. In our research, we utilized chlorophyll a (Chla), chlorophyll b (Chlb), total chlorophylls (Chls) and total carotenoids (Cars) as indicators to study the variations in the leaf positions of Lycopersicon esculentum Mill. Under 10 nitrogen concentration applications, a total of 2610 leaves (435 samples) were collected using visible-near infrared hyperspectral imaging (VNIR–HSI). In this study, a "coarse–fine" screening strategy was proposed using competitive adaptive reweighted sampling (CARS) and the iteratively retained informative variable (IRIV) algorithm to extract the characteristic wavelengths. Finally, simultaneous and quantitative models were established using partial least squares regression (PLSR). The CARS–IRIV–PLSR was used to create models to achieve a better prediction effect. The coefficient determination (R2), root mean square error (RMSE) and ratio performance deviation (RPD) were predicted to be 0.8240, 1.43 and 2.38 for Chla; 0.8391, 0.53 and 2.49 for Chlb; 0.7899, 2.24 and 2.18 for Chls; and 0.7577, 0.27 and 2.03 for Cars, respectively. The combination of these models with the pseudo-color image allowed for a visual inversion of the content and distribution of the pigment. These findings have important implications for guiding pigment distribution, nutrient diagnosis and fertilization decisions in plant growth management. [ABSTRACT FROM AUTHOR]

Social activities have a significant impact on the rainstorm flood disaster risk. It is crucial to explore the dynamic changes of urban rainstorm flood disaster risk caused by crowd activities. In this study, a risk simulation method of urban rainstorm flood disasters is proposed, composed of an urban rainstorm flood model based on SWMM and LISFLOOD-FP and a crowd activities model based on ABM. Taking the Futian District of Shenzhen as an example, the temporal and spatial changes in rainstorm flood disaster risk for buildings and roads are analyzed under three scenarios: midnight, morning peak, and evening peak. The results show that: (1) Although the overall risk of urban rainstorm flood disasters increases as the inundation area expands, the average risks of roads and buildings increase rapidly and then stabilize during the morning peak due to commuting activities, while the average risk of roads remains high level during the evening peak due to commuting activities, while; (2) The risk of urban rainstorm flood varies significantly at different time periods. The average risk of buildings is the largest during the morning peak, about twice that during the evening peak. The number of high-risk roads during the evening peak is much higher than in the morning peak, and both buildings and roads have the least risk during midnight; (3) The spatial distribution of urban rainstorm flood disaster risk changes with the crowd activities, shifting from residential areas to industrial areas, schools, shopping malls, etc., during the morning peak, while the evening peak shows the reverse. [ABSTRACT FROM AUTHOR]

Heat exchangers (HX) are often utilized in industry, and the optimization of the performance of HX is a key area of research. In this study, EVAP-COND software 4.0 and genetic algorithm (GA) based optimization methods were proposed to optimize the circuitry and fin pitch of a finned tube heat exchanger for an air conditioner. A simulation model for a multi-circuit finned-tube evaporator used in an air conditioning unit was developed using the EVAP-COND software, and further validated based on the experimental data. Considering the refrigerant flow maldistribution of the original HX, four different circuit arrangements, i.e., types A, B, C, and D, were designed and optimized circuitry obtained. Based on both simulation and experimental results, D-type HX with 1.8 mm fin pitch was selected as 10% tubes could be saved with no significant loss of heat transfer capacity. Then the fin pitch was further optimized using the multi-objective GA method, with both Colburn factor j and friction factor f being considered. Optimization results showed that, in Pareto front, points 1 to 4 showed the increase in the Colburn factor j was negative, while the decrease in the friction factor f was positive. The friction factor decreased by 3.5% as one moved from Point 1 to Point 4, but the Colburn factor rose by 1.02%. Points 5 to 10 demonstrated that, while the decrease in the friction factor was negative, the increase in the Colburn factor was positive. The friction factor decreased by 5.31%, but the Colburn factor increased by 1.51% when going from Point 5 to Point 10. The results of optimization demonstrated that the objective function performed at its optimum when the fin pitch was around 1.77 mm. [ABSTRACT FROM AUTHOR]

Detecting foodborne pathogens on-site is crucial for ensuring food safety, necessitating the development of rapid, cost-effective, highly sensitive, and portable devices. This paper presents an integrated microfluidic biosensing system designed for the rapid and sensitive detection of Salmonella typhimurium (S. typhimurium). The biosensing system comprises a microfluidic chip with a versatile valve, a recombinase polymerase amplification (RPA) for nucleic acid detection, and a customized real-time fluorescence detection system. The versatile valve combines the functions of an active valve and a magnetic actuation mixer, enabling on-demand mixing and controlling fluid flow. Quantitative fluorescence is processed and detected through a custom-built smartphone application. The proposed integrated microfluidic biosensing system could detect Salmonella at concentrations as low as 1.0 × 102 copies/µL within 30 min, which was consistent with the results obtained from the real-time quantitative polymerase chain reaction (qPCR) tests. With its versatile valve, this integrated microfluidic biosensing system holds significant potential for on-site detection of foodborne pathogens. [ABSTRACT FROM AUTHOR]