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This research article presents a comprehensive first-principles study on the piezoelectric properties of Wurtzite Aluminum Nitride (AlN) films under in-plane strain conditions. By calculating the piezoelectric tensor coefficients (e33, e31, and e15), we investigate the variation patterns of these constants with respect to in-plane strain. Our results indicate significant changes in the piezoelectric constants within the range of in-plane strain considered, exhibiting a linear trend despite opposite trends for e33 compared to e31 and e15. This study highlights the extreme sensitivity of AlN films' piezoelectric performance to in-plane strain, suggesting its potential as an effective means for tuning and optimizing the piezoelectric properties of AlN-based devices. [ABSTRACT FROM AUTHOR]

Phaeocystis globosa is an important harmful algal species that is globally distributed. Previous studies have indicated that P. globosa preferentially uptake nitrate, but the underlying mechanism is still unclear. To further verify this preference and reveal the underlying mechanism, the assimilation rates of nitrate and ammonium by P. globosa at different concentrations was quantitatively studied by using a nitrogen stable isotope (15N) tracer technique, and the regulatory mechanism was determined from the physiological and biochemical responses. The findings revealed that the preferential assimilation of nitrate by P. globosa was influenced by the ambient ammonium concentration. When the ambient concentration of ammonium was less than approximately 3.5 μmol·L−1, the assimilation rates of nitrate form P. globosa were as high as 1.05 × 10−5 μmol·L−1·h−1·cell−1. Even though the nitrate assimilation in P. globosa was inhibited at ammonium concentrations greater than this threshold, nitrate assimilation could not be completely suppressed. The activity of NR and the expression of related genes in P. globosa were also affected by ammonium. In addition, 15N signals originally labeled nitrate accumulated in ammonium. This indicated that P. globosa was likely to reduce excess nitrate to ammonium and subsequently release it into the substrate, which might be an important energy dissipation mechanism for P. globosa. These results expand the classical understanding of the utilization of nitrogen nutrients by marine phytoplankton, and offer valuable resources for comprehending the mechanism of harmful algal blooms. [ABSTRACT FROM AUTHOR]

Machine Learning (ML) has developed rapidly in recent years, achieving exciting advancements in applications such as data mining, computer vision, natural language processing, data feature extraction, and prediction. ML methods are increasingly being utilized in various aspects of seismic engineering, such as predicting the performance of various construction materials, monitoring the health of building structures or components, forecasting their seismic resistance, predicting potential earthquakes or aftershocks, and evaluating the residual performance of post-earthquake damaged buildings. This study conducts a scientometric-based review on the application of machine learning in seismic engineering. The Scopus database was selected for the data search and retrieval. During the data analysis, the sources of publications relevant to machine learning applications in seismic engineering, relevant keywords, influential authors based on publication count, and significant articles based on citation count were identified. The sources, keywords, and publications in the literature were analyzed and scientifically visualized using the VOSviewer software tool. The analysis results will help researchers understand the trending and latest research topics in the related field, facilitate collaboration among researchers, and promote the exchange of innovative ideas and methods. [ABSTRACT FROM AUTHOR]

Vitamin D3 (VD3) is a steroid hormone that plays pivotal roles in pathophysiology, and 1,25(OH)2D3 is the most active form of VD3. In the current study, the crucial role of VD3 in maintaining energy homeostasis under short-term fasting conditions was investigated. Our results confirmed that glucose-depriving pathways were inhibited while glucose-producing pathways were strengthened in zebrafish after fasting for 24 or 48 h. Moreover, VD3 anabolism in zebrafish was significantly suppressed in a time-dependent manner under short-fasting conditions. After fasting for 24 or 48 h, zebrafish fed with VD3 displayed a higher gluconeogenesis level and lower glycolysis level in the liver, and the serum glucose was maintained at higher levels, compared to those fed without VD3. Additionally, VD3 augmented the expression of fatty acids (FAs) transporter cd36 and lipogenesis in the liver, while enhancing lipolysis in the dorsal muscle. Similar results were obtained in cyp2r1−/− zebrafish, in which VD3 metabolism is obstructed. Importantly, it was observed that VD3 induced the production of gut GLP-1, which is considered to possess a potent gluconeogenic function in zebrafish. Meanwhile, the gene expression of proprotein convertase subtilisin/kexin type 1 (pcsk1), a GLP-1 processing enzyme, was also induced in the intestine of short-term fasted zebrafish. Notably, gut microbiota and its metabolite acetate were involved in VD3-regulated pcsk1 expression and GLP-1 production under short-term fasting conditions. In summary, our study demonstrated that VD3 regulated GLP-1 production in zebrafish by influencing gut microbiota and its metabolite, contributing to energy homeostasis and ameliorating hypoglycemia under short-term fasting conditions. [ABSTRACT FROM AUTHOR]

In order to realize the effective separation of palladium from high-level liquid waste (HLLW), a ligand-supported adsorbent (NTAamide(C8)/SiO2-P) was prepared by the impregnation method in a vacuum. The SiO2-P carrier was synthesized by in situ polymerization of divinylbenzene and styrene monomers on a macroporous silica skeleton. The NTAamide(C8)/SiO2-P adsorbent was fabricated by impregnating an NTAamide(C8) ligand into the pore of a SiO2-P carrier under a vacuum condition. The adsorption performance of NTAamide(C8)/SiO2-P in nitric acid medium has been systematically studied. In a solution of 0.2 M HNO3, the distribution coefficient of Pd on NTAamide(C8)/SiO2-P was 1848 mL/g with an adsorption percentage of 90.24%. With the concentration of nitric acid increasing, the adsorption capacity of NTAamide(C8)/SiO2-P decreases. Compared to the other 10 potential interfering ions in fission products, NTAamide(C8)/SiO2-P exhibited excellent adsorption selectivity for Pd(II). The separation factor (SFPd/other metals > 77.8) is significantly higher than that of similar materials. The interference of NaNO3 had a negligible effect on the adsorption performance of NTAamide(C8)/SiO2-P, which maintained above 90%. The adsorption kinetics of Pd(II) adsorption on NTAamide(C8)/SiO2-P fits well with the pseudo-second order model. The Sips model is more suitable than the Langmuir and Freundlich model for describing the adsorption behavior. Thermodynamic analysis showed that the adsorption of Pd(II) on NTAamide(C8)/SiO2-P was a spontaneous, endothermic, and rapid process. NTAamide(C8)/SiO2-P also demonstrated good reusability and economic feasibility. [ABSTRACT FROM AUTHOR]

Asphalt pavement, which is mainly made up of the asphalt mixture, exhibits complicated mechanical behaviors under the combined effects of moving vehicle loads and external service environments. Multi-scale numerical simulation can well characterize behaviors of asphalt materials and asphalt pavement, and the essential research progress is systematically summarized from an entire view. This paper reviews extensive research works concerning aspects of the design, characterization, and prediction of performance for asphalt materials and asphalt pavement based on multi-scale numerical simulation. Firstly, full-scale performance modeling on asphalt pavement is discussed from aspects of structural dynamic response, structural and material evaluation, and wheel–pavement interaction. The correlation between asphalt material properties and pavement performance is also analyzed, and so is the hydroplaning phenomenon. Macro- and mesoscale simulations on the mechanical property characterization of the asphalt mixture and its components are then investigated, while virtual proportion design for the asphalt mixture is introduced. Features of two-dimensional and three-dimensional microscale modeling on the asphalt mixture are summarized, followed by molecular dynamics simulation on asphalt binders, aggregates, and their interface, while nanoscale behavior modeling on asphalt binders is presented. Finally, aspects that need more attention concerning this study's topic are discussed, and several suggestions for future investigations are also presented. [ABSTRACT FROM AUTHOR]

The prophenoloxidase (PPO) activation and Toll antimicrobial peptide synthesis pathways are two critical immune responses in the insect immune system. The activation of these pathways is mediated by the cascade of serine proteases, which is negatively regulated by serpins. In this study, we identified a typical serpin, BmSerpin-4, in silkworms, whose expression was dramatically up-regulated in the fat body and hemocytes after bacterial infections. The pre-injection of recombinant BmSerpin-4 remarkably decreased the antibacterial activity of the hemolymph and the expression of the antimicrobial peptides (AMPs) gloverin-3, cecropin-D, cecropin-E, and moricin in the fat body under Micrococcus luteus and Yersinia pseudotuberculosis serotype O: 3 (YP III) infection. Meanwhile, the inhibition of systemic melanization, PO activity, and PPO activation by BmSerpin-4 was also observed. Hemolymph proteinase 1 (HP1), serine protease 2 (SP2), HP6, and SP21 were predicted as the candidate target serine proteases for BmSerpin-4 through the analysis of residues adjacent to the scissile bond and comparisons of orthologous genes in Manduca sexta. This suggests that HP1, SP2, HP6, and SP21 might be essential in the activation of the serine protease cascade in both the Toll and PPO pathways in silkworms. Our study provided a comprehensive characterization of BmSerpin-4 and clues for the further dissection of silkworm PPO and Toll activation signaling. [ABSTRACT FROM AUTHOR]

In this study, a novel organic–inorganic hybrid material IIGK@MnO2 (2-naphthalenemethyl-isoleucine-isoleucine-glycine-lysine@manganese dioxide) was designed as a novel adsorbent for the removal of strontium ions (Sr2+). The morphology and structure of IIGK@MnO2 were characterized using TEM, AFM, XRD, and XPS. The results indicate that the large specific surface area and abundant negative surface charges of IIGK@MnO2 make its surface rich in active adsorption sites for Sr2+ adsorption. As expected, IIGK@MnO2 exhibited excellent adsorbing performance for Sr2+. According to the adsorption results, the interaction between Sr2+ and IIGK@MnO2 can be fitted with the Langmuir isotherm and pseudo-second-order equation. Moreover, leaching and desorption experiments were conducted to assess the recycling capacity, demonstrating significant reusability of IIGK@MnO2. [ABSTRACT FROM AUTHOR]

The efficient separation of Zr(IV) ions from strong acidic and radioactive solutions is a significant challenge, especially in the context of the aqueous reprocessing of nuclear fuels. The complexity of such solutions, which are often characterized by high acidity and the presence of radioactive elements, poses formidable challenges for separation processes. Herein, several mesoporous silicas (HMS, MCM-41, KIT-6, and SiO2-70 Å) with excellent acid and radiation resistance properties were employed as sorbents to remove Zr(IV) ions from simulated high-level liquid waste. The batch experiments were designed to investigate the influence of adsorption time, HNO3 concentration, initial Zr(IV) concentration, adsorbent dosage, and temperature on the adsorption behavior of Zr(IV). The results indicate that the adsorption equilibrium time of mesoporous silica materials was approximately 8 h, and all the adsorption processes followed the pseudo-second-order kinetics equation. The isotherms of Zr(IV) adsorption by KIT-6 exhibited good agreement with the Langmuir model, while the Freundlich model could be utilized to fit the adsorption on HMS, MCM-41, and SiO2-70 Å. The adsorption capacity of MCM-41 for Zr(IV) in 3 mol/L HNO3 was 54.91 mg/g, which is three times the adsorption capacity reported for commercial silica gel (17.91 mg/g). The thermodynamic parameters indicate that the adsorption processes for zirconium are endothermic reactions. Furthermore, the mesoporous silicas exhibited a pronounced selectivity in the adsorption of Zr(IV) within a simulated high-level liquid waste containing 10 co-existing cations (3 mol/L HNO3). This suggests that mesoporous silicas have great potential for Zr(IV) removal in actual radioactive liquids with high acidity during spent fuel reprocessing. [ABSTRACT FROM AUTHOR]

To address the issue of the vibration characteristic signals of floodgates being affected by background white noise and low-frequency water flow noise, a noise reduction method combining the improved adaptive singular value decomposition algorithm (ASVD) and the improved complete ensemble EMD with adaptive noise (ICEEMDAN) is proposed. Firstly, a Hankel matrix is constructed based on the collected discrete time signals. After performing SVD on the Hankel matrix, the ASVD algorithm is used to automatically select the effective singular values to filter out most of the background white noise and retain the useful frequency components with similar energy in the signal. Then, ICEEMDAN combined with the Spearman correlation coefficient method is used to further filter out residual white noise and low-frequency water flows. The noise reduction performance of this combined method is verified through simulation experiments. Filtered by the ASVD-ICEEMDAN method, the signal-to-noise ratio of the simulation signal (50% noise level) is increased from 4.417 to 16.237, and the root mean square error is reduced from 2.286 to 0.586. Based on the practically measured vibration signals of a floodgate at a large hydropower station, the result shows that the ASVD-ICEEMDAN method exhibits good noise reduction performance and feature information extraction abilities for floodgate vibration signals, and can provide support for operational mode analysis and damage identification of practical structures under complex interference conditions. [ABSTRACT FROM AUTHOR]

Soil physicochemical properties affect crop growth and yield. The addition of fertilizers can improve the soil quality during crop cultivation, leading to increased agricultural production. Organic fertilizers may be produced by composting straw that would otherwise be discarded as agricultural waste, with potential implications for sustainable agricultural development. However, the mechanism underlying the effects of straw compost on crop growth is unknown. In this study, a microbial agent suitable for straw decomposition in cold regions was used for a large-scale biological fermentation. Organic compost was obtained after the decomposition of straw. The straw compost was mixed with soil in different proportions and then used to cultivate Songjing 2 rice plants. The addition of straw compost significantly increased the growth and yield of the rice plants and enhanced various physiological indices. Moreover, the straw compost treatment significantly improved soil physicochemical properties (e.g., pH, enzyme activity, nutrient composition, and microbial diversity) and optimized the soil conditions for crop growth. In addition, the application of straw compost influenced the expression of genes in rice metabolic pathways as well as pathways mediating secondary metabolite synthesis and plant hormone signal transduction. The study data reflect the potential applicability of low-temperature straw fermentation technology for maximizing crop production. [ABSTRACT FROM AUTHOR]

In the rapidly emerging field of biomedical applications, multifunctional nanoparticles, especially those containing magnetic and plasmonic components, have gained significant attention due to their combined properties. These hybrid systems, often composed of iron oxide and gold, provide both magnetic and optical functionalities and offer promising avenues for applications in multimodal bioimaging, hyperthermal therapies, and magnetically driven selective delivery. This paper focuses on the implementation of advanced characterization methods, comparing statistical analyses of individual multifunctional particle properties with macroscopic properties as a way of fine-tuning synthetic methodologies for their fabrication methods. Special emphasis is placed on the size-dependent properties, biocompatibility, and challenges that can arise from this versatile nanometric system. In order to ensure the quality and applicability of these particles, various novel methods for characterizing the magnetic gold particles, including the analysis of their morphology, optical response, and magnetic response, are also discussed, with the overall goal of optimizing the fabrication of this complex system and thus enhancing its potential as a preferred diagnostic agent. [ABSTRACT FROM AUTHOR]

The feedback spring rod of the armature assembly was eliminated in the double-redundancy electro-hydraulic servo valve (DREHSV), which employed a redundant design in contrast to the typical double-nozzle flapper electro-hydraulic servo valve (DNFEHSV). The pilot stage was mainly composed of four torque motors, and the double-system spool was adopted in the power stage. Consequently, the difficulty of spool displacement control was increased. By artificially changing the structural parameters of the simulation model in accordance with the theoretical analysis through AMESim, this paper aimed to study the dynamics and static characteristics of the DREHSV. The advantage of redundant design was further demonstrated by disconnecting working coils and setting the different worn parts of the spool. On the test bench, the necessary experiments were performed. Through simulation, it was discovered that when the clogged degree of the nozzle is increased, the zero bias value increases, the pressure and flow gain remain unchanged, and the internal leakage decreases. The pressure gain changes very little, the flow gain close to the zero position grows, the zero leakage increases significantly, and the pilot stage leakage changes very little as a result of the wear of the spool throttling edge. The basic consistency between the simulation curves and the experimental findings serve to validate the accuracy of the AMESim model. The findings can serve as a theoretical guide for the design, debugging, and maintenance of the DREHSV. The simulation model is also capable of producing a large amount of sample data for DREHSV fault diagnosis using a neural network. [ABSTRACT FROM AUTHOR]

Cold exposure is an essential factor affecting breeding efforts in cold regions. Muscle, as an important tissue for homeothermic animals, can produce heat through shivering thermogenesis (ST) and non-shivering thermogenesis (NST) under cold exposure. Long non-coding RNAs (lncRNAs) play important roles in regulating gene expression. However, the regulatory mechanisms of lncRNAs and their role in the thermogenesis of pigs are unclear. We examined lncRNAs in the skeletal muscle of an indigenous pig breed, the Enshi black pig, when the pigs were exposed to acute or chronic cold. Three pigs were maintained inside a pig house (control group), three pigs were maintained outside the pig house for 55 d (chronic cold group), and three pigs were suddenly exposed to the conditions outside the pig house for 3 days (acute cold group). After the experiment, the longissimus dorsi of each pig were collected, and their lncRNA profiles were sequenced and analyzed. Each sample obtained nearly 12.56 Gb of clean data. A total of 11,605 non-coding RNAs were obtained, including 10,802 novel lncRNAs. The number of differentially expressed lncRNAs (DElncRNAs) was identified under acute cold (427) and cold acclimation (376), with 215 and 192 upregulated lncRNAs, respectively. However, only 113 lncRNAs were commonly upregulated by acute cold and cold acclimation. In addition, 65% of the target genes were trans-regulated by DElncRNAs. The target genes were enriched in signal transduction, immune system, cell growth and death pathways, and amino acid and carbohydrate metabolism. Compared to cold acclimation, acute cold stress-induced more DElncRNAs and response pathways. In conclusion, low temperatures altered the expression levels of lncRNAs and their target genes in muscle tissue. Some potential mechanisms were revealed, including ion migration and the metabolism of amino acids and carbohydrates. [ABSTRACT FROM AUTHOR]

Lactobacillus casei (L. casei) has four possible mechanisms: antimicrobial antagonism, competitional adhesion, immunoregulation, and the inhibition of bacterial toxins. To delineate the metabolic reactions of nucleotides from L. casei that are associated with mechanisms of inhibiting pathogens and immunoregulation, we report that a PyrR-deficient L. casei strain was constructed using the CRISPR-Cas9D10A tool. Furthermore, there were some changes in its basic biological characterization, such as its growth curve, auxotroph, and morphological damage. The metabolic profiles of the supernatant between the PyrR-deficient and wild strains revealed the regulation of the synthesis of genetic material and of certain targeting pathways and metabolites. In addition, the characteristics of the PyrR-deficient strain were significantly altered as it lost the ability to inhibit the growth of pathogens. Moreover, we identified PyrR-regulating pyrimidine biosynthesis, which further improved its internalization and colocalization with macrophages. Evidence shows that the PyrR gene is a key active component in L. casei supernatants for the regulation of pyrimidine biosynthesis against a wide range of pathogens. [ABSTRACT FROM AUTHOR]

In large-scale public security equipment projects, long-term equipment operation often leads to equipment failures and other problems, so it is particularly important to choose the appropriate operation and maintenance (O&M) scheme based on the content of the equipment work orders. However, there are a variety of equipment models in the work orders; not only is the data complex, but also due to the long project cycle, there are often problems such as loss of content, which bring great challenges to the O&M work. This paper defines these problems as "3-No problems": inconsistency, inaccuracy, and incompleteness. In this paper, an improved DIKWP model is proposed and combined with a random forest classifier to construct data graphs, information graphs, knowledge graphs, and wisdom graphs. Through the above model, the 3-No problem in equipment work orders can be solved, and the importance of each equipment model can be obtained. Eventually, combined with the purpose graph, the selection of models, the bid score calculation, and the selection of O&M schemes are carried out based on the obtained conclusion in a purpose-driven manner to achieve the evaluation of O&M efficiency and safety. Finally, an example is assumed to illustrate the application of the method in actual projects, which provides a certain reference value for the selection of an O&M scheme for large-scale equipment projects. [ABSTRACT FROM AUTHOR]

Peony seeds, an important oil resource, have been attracting much attention because of α-linolenic acid. Oil bodies (OBs), naturally pre-emulsified oils, have great potential applications in the food industry. This study investigated the effects of extraction pH and Quillaja saponin (QS) on the physicochemical properties of peony oil body (POB) emulsions. POBs were extracted from raw peony milk at pH 4.0, 5.0, 6.0, and 7.0 (named pH 4.0-, 5.0-, 6.0-, and 7.0-POBs). All POBs contained extrinsic proteins and oleosins. The extrinsic proteins of pH 4.0- and pH 5.0-POB were 23 kDa and 38 kDa glycoproteins, the unknown proteins were 48 kDa and 60 kDa, while the 48 kDa and 38 kDa proteins were completely removed under the extraction condition of pH 6.0 and 7.0. The percentage of extrinsic proteins gradually decreased from 78.4% at pH 4.0-POB to 33.88% at pH 7.0-POB, while oleosin contents increased. The particle size and zeta potential of the POB emulsions decreased, whereas the oxidative stability, storage stability, and pI increased with the increasing extraction pH. QS (0.05~0.3%) increased the negative charges of all the POB emulsions, and 0.1% QS significantly improved the dispersion, storage, and the oxidative stability of the POB emulsions. This study provides guidance for selecting the proper conditions for the aqueous extraction of POBs and improving the stability of OB emulsions. [ABSTRACT FROM AUTHOR]

Soybean oil body (SOB) emulsions were prepared using OBs extracted at pH 11.0 and pH 7.0. The pH 11.0-SOB comprised oleosins, whereas pH 7.0-SOB comprised extrinsic proteins and oleosins. All SOB emulsions were heated at 60–100 °C for 15 min. Heating may lead to the release of extrinsic proteins from the surface of pH 7.0-SOB due to heat-induced denaturation. The total proportion of α-helix and β-sheets gradually decreased from 77 (unheated) to 36.2% (100 °C). During stomach digestion, the extrinsic protein hydrolysis of heated pH 7.0-SOB emulsions was fast between 60 and 80 °C, and it then slowed between 90 and 100 °C; heating inhibited the oleosin hydrolysis of pH 7.0- and 11.0-SOBs. Heat treatment promoted aggregation and coalescence, and it resulted in increased particle sizes for all emulsions. Larger aggregates were found in heated pH 7.0-SOB emulsions, and larger oil droplets were found in heated pH 11.0-SOB emulsions. After intestinal digestion, the droplets of all SOB emulsions gradually dispersed, and particle sizes decreased. Different heating temperatures had lesser effects on particle sizes and microstructures. Lipolysis was affected by the extraction pH and heating. For pH 11.0-SOB emulsions, the FFA release tendency was greatly affected by the heating temperature, and heating to 80 °C resulted in the highest FFA release (74%). However, all pH 7.0-SOB emulsions had similar total FFA releases. In addition, the droplet charges of heated pH 7.0-SOB emulsions were lower than those of unheated pH 7.0-SOB emulsions in both the intestine and stomach phases; however, the charge changes in different pH 11.0-SOB emulsions showed the opposite tendency. This study will offer guidance regarding the application of SOB emulsions in food. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries have become the primary electrical energy storage device in commercial and industrial applications due to their high energy/power density, high reliability, and long service life. It is essential to estimate the state of health (SOH) of batteries to ensure safety, optimize better energy efficiency and enhance the battery life-cycle management. This paper presents a comprehensive review of SOH estimation methods, including experimental approaches, model-based methods, and machine learning algorithms. A critical and in-depth analysis of the advantages and limitations of each method is presented. The various techniques are systematically classified and compared for the purpose of facilitating understanding and further research. Furthermore, the paper emphasizes the prospect of using a knowledge graph-based framework for battery data management, multi-model fusion, and cooperative edge-cloud platform for intelligent battery management systems (BMS). [ABSTRACT FROM AUTHOR]

Significant circulating currents in the modular multilevel converter (MMC) increase system losses and complicate heat-sink design. Conventional PI and PR controllers can achieve steady-state error adjustment, but are sensitive to parameter changes and model uncertainty, heavily relying on coordinate transformations and careful design of model parameters. Model predictive control (MPC) has the characteristics of simple design, good robustness, and excellent dynamic response; however, it encountered the complexity of adjusting weighting factors. This paper proposed circulating the current model predictive proportional integral control (MPPIC) method in abc reference frame. This hybrid control solution utilized the predictive model and traditional PI algorithm to combine the advantages of nonlinear and linear control. Compared with existing suppression methods, this method avoided complex mathematical operations and a selection of weight coefficients, was easy to implement, and can effectively suppress circulating currents under different modulation ratios. Simulations were conducted on MATLAB/Simulink to verify the effectiveness of the proposed control strategy. MPPIC can not only distinctly suppress the circulating currents, but also reduce the overall voltage fluctuation of sub-modules capacitors under different modulation ratios, and had almost no any adverse effect on the performance of MMC. [ABSTRACT FROM AUTHOR]

Safety issues are one of the main limitations for further application of lithium-ion batteries, and battery degradation is an important causative factor. However, current state-of-health (SOH) estimation methods are mostly developed for a single feature and a single operating condition as well as a single battery material system, which consequently makes it difficult to guarantee robustness and generalization. This paper proposes a data-driven and multi-feature collaborative SOH estimation method based on equal voltage interval discharge time, incremental capacity (IC) and differential thermal voltammetry (DTV) analysis for feature extraction. The deep learning model is constructed based on bi-directional long short-term memory (Bi-LSTM) with the addition of attention mechanism (AM) to focus on the important parts of the features. The proposed method is validated based on a NASA dataset and Oxford University dataset, and the results show that the proposed method has high accuracy and strong robustness. The estimated root mean squared error (RMSE) are below 0.7% and 0.3%, respectively. Compared to single features, the collaboration between multiple features and AM resulted in a 25% error improvement, and the capacity rebound is well captured. The proposed method has the potential to be applied online in an end-cloud collaboration system. [ABSTRACT FROM AUTHOR]

Liquid lead–bismuth eutectic alloy is one of the candidate coolants for fourth-generation nuclear power systems because of its good physical and chemical properties, neutron economic performance, and safety. However, the compatibility between the coolant and structural steel is still the main factor restricting its large-scale industrial application in the nuclear energy field. Structural steel in a liquid lead–bismuth eutectic alloy for a long time would cause severe corrosion. The erosion of structural steel by high-flow-rate liquid lead–bismuth alloy will lead to a more complex corrosion process. This paper mainly reviews the corrosion characteristics of liquid lead–bismuth and the corrosion behavior of structural steel in liquid lead-bismuth eutectic. The main methods of inhibiting liquid lead–bismuth corrosion are summarized, and future research directions are suggested. [ABSTRACT FROM AUTHOR]

Simple Summary: Min pigs living in northeast China have the characteristics of good meat quality, and strong disease- and cold-resistance characters. Min pig is also one of the few pig breeds with villi hair in the world. The study of its villi hair traits is of great significance for the mechanism of cold resistance and animal welfare. In this study, a Large White × Min pigs F2 population was constructed, and a case-control genome-wide association study was performed to investigate the potential copy number variation (CNVs) associated with villi hair appearance. Finally, we found important genes related to villi. This study may also provide a basic reference for the selection and breeding of cold-resistant pigs and outdoor breeding. The Min pig is a famous native pig breed in northeast China, which has the special genetic character of villi hair growth in cold seasons. At present, little research has focused on the genetic mechanism of villi hair growth in Min pigs. Copy number variations (CNVs) are a type of variant that may influence many traits. In this study, we first investigated the phenotype of Large White × Min pigs' F2 pig villi hair in detail and then performed a CNV-based genome-wide association study (GWAS) between CNVs and pig villi hair appearance. Finally, a total number of 15 significant CNVRs were found to be associated with Min pig villi hair. The most significant CNVR was located on chromosome 1. Nearest gene annotation analysis indicated that the pig villi hair traits may be associated with the biological process of the G-protein-coupled receptor signaling pathway. QTL overlapping analysis found that among the CNVRs, 14 CNVRs could be co-located with known QTLs. Some genes such as MCHR2, LTBP2, and GFRA2 may be candidate genes for pig villi traits and are worth further study. Our study may provide a basic reference for the selection and breeding of cold-resistant pigs and outdoor breeding. [ABSTRACT FROM AUTHOR]

Simple Summary: The Min pig is a national-level protected pig that is recognized as a rare animal in China, lives in a constantly cold environment in the north of China, and has excellent characteristics compared with other commercial pigs. The Min pig has the specific character of secondary hair growth in winter and seasonal cycling. International research on hair follicles is mainly focused on human and mice hair, including hair follicle regeneration and hair loss treatment. Research on hair follicles in pigs is limited. The structure and morphology of hair follicles from Min pigs are different from those of lean-type pigs, such as Yorkshire and Berkshire pigs, which do not grow secondary hairs in the adult stage. In this study, there were significant gene expression differences with high-throughput sequencing to determine the primary and secondary hairs. Based on skin blocker experimental results, we can infer that the Wnt and BMP signaling could stimulate follicle stem cells in the Min pig. In China, the national-level protected pig, the Min pig, is characterized by the development of secondary hairs and hair follicles in winter. Factors that dominate the genotype in the growth of secondary hairs are not clear through the concrete cell signaling pathways. This study compared hair phenotypes based on morphological structure, transcriptomics, and potential targeting molecules in the breeds of Min, Berkshire, and Yorkshire pigs. The results indicated that Min pigs have specific characteristics for the growth of secondary hairs compared with the Berkshire and Yorkshire pigs. The transcriptome analyses and quantitative reverse transcription-polymerase chain reaction results revealed that secondary hair growth was activated by follicle stem cells. The specific inhibitors of Wnt and BMP were studied using respective signals. The density of follicles, activity of follicle stem cells, and relative gene expression results have shown that Wnt and BMP stimulate the activity of follicle stem cells, and the Wnt signaling molecule has a significantly better effect than the BMP signaling molecule on stem cells. Wnt and BMP can promote the growth of local secondary hair and gene expression. Therefore, this study was conducted to verify the development mechanisms of secondary hairs, which have potential applications in laboratory animals and comparative medicine. [ABSTRACT FROM AUTHOR]

Simple Summary: Clinically, surgical decisions for HCC resection are difficult and not sufficiently personalized. The aim of this study was to develop a surgical procedure decision-making and effectiveness prediction system for hepatectomy through extensive expert surgical decision-making experience and long-term follow-up, which can assist surgeons. The proposed machine learning models demonstrated their superior performance in surgical decision-making, OS, and RFS prediction tasks. Additionally, a web server that aids physician decision-making was deployed, which is expected to be an effective tool for auxiliary surgeons. Background: Currently, surgical decisions for hepatocellular carcinoma (HCC) resection are difficult and not sufficiently personalized. We aimed to develop and validate data driven prediction models to assist surgeons in selecting the optimal surgical procedure for patients. Methods: Retrospective data from 361 HCC patients who underwent radical resection in two institutions were included. End-to-end deep learning models were built to automatically segment lesions from the arterial phase (AP) of preoperative dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). Clinical baseline characteristics and radiomic features were rigorously screened. The effectiveness of radiomic features and radiomic-clinical features was also compared. Three ensemble learning models were proposed to perform the surgical procedure decision and the overall survival (OS) and recurrence-free survival (RFS) predictions after taking different solutions, respectively. Results: SegFormer performed best in terms of automatic segmentation, achieving a Mean Intersection over Union (mIoU) of 0.8860. The five-fold cross-validation results showed that inputting radiomic-clinical features outperformed using only radiomic features. The proposed models all outperformed the other mainstream ensemble models. On the external test set, the area under the receiver operating characteristic curve (AUC) of the proposed decision model was 0.7731, and the performance of the prognostic prediction models was also relatively excellent. The application web server based on automatic lesion segmentation was deployed and is available online. Conclusions: In this study, we developed and externally validated the surgical decision-making procedures and prognostic prediction models for HCC for the first time, and the results demonstrated relatively accurate predictions and strong generalizations, which are expected to help clinicians optimize surgical procedures. [ABSTRACT FROM AUTHOR]

Simple Summary: Porcine epidemic diarrhea virus (PEDV) is an α coronavirus that causes major disease outbreaks, producing up to 100% mortality rates in piglets during the first 7 days after birth. In this study, we used microcapsules with inactivated PEDV fed to mice by oral administration to improve the effectiveness of the oral delivery method for protection against PEDV infection, and avoided digestive degradation in the acidic environment of the stomach. In addition, the PEDV microcapsules displayed remarkable storage tolerance to maintain the quality of the PEDV antigen. The PEDV microcapsules delivered the inactivated virus into the gut, stimulating the specific mucosal immune response in mice, which could directly neutralize the enterovirus. The porcine epidemic diarrhea virus, PEDV, which causes diarrhea, vomiting and death in piglets, causes huge economic losses. Therefore, understanding how to induce mucosal immune responses in piglets is essential in the mechanism and application against PEDV infection with mucosal immunity. A method of treatment in our research was used to make an oral vaccine that packaged the inactive PEDV with microencapsulation, which consisted of sodium alginate and chitosan, and adapted the condition of the gut in mice. The in vitro release experiment of microcapsules showed that inactive PEDV was not only easily released in saline and acid solutions but also had an excellent storage tolerance, and was suitable for use as an oral vaccine. Interestingly, both experimental groups with different doses of inactive virus enhanced the secretion of specific antibodies in the serum and intestinal mucus, which caused the effective neutralization against PEDV in the Vero cell by both IgG and IgA, respectively. Moreover, the microencapsulation could stimulate the differentiation of CD11b+ and CD11c+ dendritic cells, which means that the microencapsulation was also identified as an oral adjuvant to help phagocytosis of dendritic cells in mice. Flow cytometry revealed that the B220+ and CD23+ of the B cells could significantly increase antibody production with the stimulation from the antigens' PEDV groups, and the microencapsulation could also increase the cell viability of B cells, stimulating the secretion of antibodies such as IgG and IgA in mice. In addition, the microencapsulation promoted the expression of anti-inflammatory cytokines, such as IL-10 and TGF-β. Moreover, proinflammatory cytokines, such as IL-1, TNF-α, and IL-17, were inhibited by alginate and chitosan in the microencapsulation groups compared with the inactivated PEDV group. Taken together, our results demonstrate that the microparticle could play the role of mucosal adjuvant, and release inactivated PEDV in the gut, which can effectively stimulate mucosal and systemic immune responses in mice. [ABSTRACT FROM AUTHOR]

Damage of high-strength bolt (DHSB) is inevitable during long-term use. Such damage is irreversible that may not be replaced in time, and the potential danger is proven by the changes of the mechanical properties of DHSB. To investigate the mechanical properties of DHSB, this paper uses the software ABAQUS to simulate the stress of various types of DHSB under earthquake, and compares with undamaged high-strength bolts (UDHSB). The results show that the most unfavorable position of the crack is at the bottom of the second ring thread. The model with shorter crack length will have greater stress concentration and displacement deformation. The more the number of cracks, the greater the concentrated stress value. The concentrated stress generated by the tooth deformation is at the top of the thread tooth, and the concentrated stress generated by the crack is at the bottom of the thread tooth. Changing the tooth shape in the appropriate position is beneficial to reduce the degree of bolt damage. Bolt damage will double the harm, and timely replacement of damaged bolts is very time-sensitive and necessary. [ABSTRACT FROM AUTHOR]

Evaluation of the residual seismic capacity (RSC) of post-earthquake damaged buildings is instrumental to the formation of reasonable recovery strategies. At present, incremental dynamic analysis (IDA) that considers the mainshock and aftershock is the method most frequently used to evaluate the RSC of damaged structures. However, the mainshock-induced structural damage determined using the IDA method may be inconsistent with the damage observed in actual engineering. This inconsistency could potentially lead to an unreasonable evaluation result. To overcome this drawback, it is necessary to evaluate the RSC of damaged structures according to their observed damage instead of that obtained by the IDA. In this paper, a method of evaluating the RSC of damaged reinforced concrete (RC) columns is proposed. First, the damage degree and distribution of the damaged columns were evaluated via visual inspection after mainshocks. Then, a numerical model was developed to predict the residual behavior of damaged columns subjected to aftershocks. After that, the RSC of damaged columns was estimated based on fragility analysis. The degradation of the collapse capacity of damaged columns was quantified by the collapse fragility index (CFI), and a parameter analysis was conducted to study the effect of structural parameters on the CFI of damaged columns. Lastly, an empirical model for predicting the CFI was proposed, facilitating the application of this study in actual post-earthquake assessments. The parameter analysis indicates that the axial load ratio of the columns and the degree of damage degree accumulated during mainshocks have a significant effect on the CFI. Additionally, the proposed empirical model can effectively predict the degradation of the collapse capacity of RC columns in existing test data, with an accuracy of 0.82. [ABSTRACT FROM AUTHOR]

Hot-pressed peanut meal protein hydrolysates are rich in Arg residue, but there is a lack of research on their α-glucosidase inhibitory activity. In this study, different proteases were used to produce hot-pressed peanut meal protein hydrolysates (PMHs) to evaluate the α-glucosidase inhibitory activity. All PMHs showed good α-glucosidase inhibitory activity with the best inhibition effect coming from the dual enzyme system of Alcalase and Neutrase with an IC50 of 5.63 ± 0.19 mg/mL. The fractions with the highest inhibition effect were separated and purified using ultrafiltration and cation exchange chromatography. Four novel α-glucosidase inhibitory peptides (FYNPAAGR, PGVLPVAS, FFVPPSQQ, and FSYNPQAG) were identified by nano-HPLC-MS/MS and molecular docking. Molecular docking showed that peptides could occupy the active pocket of α-glucosidase through hydrogen bonding, hydrophobic interaction, salt bridges, and π-stacking, thus preventing the formation of complexes between α-glucosidase and the substrate. In addition, the α-glucosidase inhibitory activity of PMHs was stable against hot, pH treatment and in vitro gastrointestinal digestion. The study demonstrated that PMHs might be used as a natural anti-diabetic material with the potential to inhibit α-glucosidase. [ABSTRACT FROM AUTHOR]

The accurate estimation of the battery state of health (SOH) is crucial for the dependability and safety of battery management systems (BMS). The generality of existing SOH estimation methods is limited as they tend to primarily consider information from single-source features. Therefore, a novel method for integrating multi-feature collaborative analysis with deep learning-based approaches is proposed in this research. First, several battery degradation features are obtained through differential thermal voltammetry (DTV) analysis, singular value decomposition (SVD), incremental capacity analysis (ICA), and terminal voltage characteristic (TVC) analysis. The features highly related to SOH are selected as inputs for the deep learning model based on the results of a Pearson correlation analysis. The SOH estimation is achieved by developing a deep learning framework cored by long short-term memory (LSTM) neural network (NN), which integrates multi-source features as an input. A suggested method is validated using NASA and Oxford Battery Degradation datasets. The results demonstrate that the presented model provides great SOH estimation accuracy and generality, where the maximum root mean square error (RMSE) is less than 1%. Based on a cloud computing platform, the proposed method can be applied to provide a real-time prediction of battery health, with the potential to enhance battery full lifespan management. [ABSTRACT FROM AUTHOR]

The accurate estimation of the state of charge (SOC) plays a crucial role in ensuring the range of electric vehicles (EVs) and the reliability of the EVs battery. However, due to the dynamic working conditions in the implementation of EVs and the limitation of the onboard BMS computational force, it is challenging to achieve a reliable, high-accuracy and real-time online battery SOC estimation under diverse working scenarios. Therefore, this study proposes an end-cloud collaboration approach of lithium-ion batteries online estimate SOC. On the cloud-side, a deep learning model constructed based on CNN-LSTM is deployed, and on the end-side, the coulomb counting method and Kalman's filter are deployed. The estimation results at both sides are fused through the Kalman filtering algorithm, realizing high-accuracy and real-time online estimation of SOC. The proposed approach is evaluated with three dynamic driving profiles and the results demonstrate the proposed approach has high accuracy under different temperatures and initial errors, where the root means square error (RMSE) is lower than 1.5% and the maximum error is lower than 5%. Furthermore, this method could achieve high-accuracy and real-time SOC online estimation under the cyber hierarchy and interactional network (CHAIN) framework and can be extended to multi-state collaborative online estimation. [ABSTRACT FROM AUTHOR]

Feature pyramid networks and attention mechanisms are the mainstream methods to improve the detection performance of many current models. However, when they are learned jointly, there is a lack of information association between multi-level features. Therefore, this paper proposes a feature pyramid of the multi-level local attention method, dubbed as MLA-Net (Feature Pyramid Network with Multi-Level Local Attention for Object Detection), which aims to establish a correlation mechanism for multi-level local information. First, the original multi-level features are deformed and rectified using the local pixel-rectification module, and global semantic enhancement is achieved through the multi-level spatial-attention module. After that, the original features are further fused through the residual connection to achieve the fusion of contextual features to enhance the feature representation. Extensive ablation experiments were conducted on the MS COCO (Microsoft Common Objects in Context) dataset, and the results demonstrate the effectiveness of the proposed method with a 0.5% enhancement. An improvement of 1.2% was obtained on the PASCAL VOC (Pattern Analysis Statistical Modelling and Computational Learning, Visual Object Classes) dataset, reaching 81.8%, thereby, indicating that the proposed method is robust and can compete with other advanced detection models. [ABSTRACT FROM AUTHOR]

Scutellaria baicalensis Georgi is an annual herb from the Scutellaria genus that has been extensively used as a traditional medicine for over 2000 years in China. Baicalin and other flavonoids have been identified as the principal bioactive ingredients. The biosynthetic pathway of baicalin in S. baicalensis has been elucidated; however, the specific functions of R2R3-MYB TF, which regulates baicalin synthesis, has not been well characterized in S. baicalensis to date. Here, a S20 R2R3-MYB TF (SbMYB12), which encodes 263 amino acids with a length of 792 bp, was expressed in all tested tissues (mainly in leaves) and responded to exogenous hormone methyl jasmonate (MeJA) treatment. The overexpression of SbMYB12 significantly promoted the accumulation of flavonoids such as baicalin and wogonoside in S. baicalensis hairy roots. Furthermore, biochemical experiments revealed that SbMYB12 is a nuclear-localized transcription activator that binds to the SbCCL7-4, SbCHI-2, and SbF6H-1 promoters to activate their expression. These results illustrate that SbMYB12 positively regulates the generation of baicalin and wogonoside. In summary, this work revealed a novel S20 R2R3-MYB regulator and enhances our understanding of the transcriptional and regulatory mechanisms of baicalin biosynthesis, as well as sheds new light on metabolic engineering in S. baicalensis. [ABSTRACT FROM AUTHOR]

Crystal Structure Algorithm (CryStAl) is a new meta-heuristic algorithm, and it has been studied by many scholars because of its wide adaptability and the fact that there is no need to set parameters in advance. An improved crystal structure algorithm (GLCryStAl) based on golden sine operator and Levy flight is designed in this paper. The algorithm makes good use of the relationship between the golden sine operator and the unit circle to make the algorithm exploration space more comprehensive, and then gradually narrows the search space in the iterative process, which can effectively speed up the convergence rate of the algorithm. At the same time, a Levy operator is introduced to help the algorithm effectively get rid of the attraction of local optimal value. To evaluate the performance of GLCryStAl, 12 classic benchmark functions and eight CEC2017 test functions were selected to design a series of comparative experiments. In addition, the experimental data of these algorithms are analyzed using the Wilcoxon and Friedman tests. Through these two tests, it can be found that GLCryStAl has significant advantages over other algorithms. Finally, this paper further tests the optimization performance of GLCryStAl in engineering design. GLCryStAl was applied to optimize pressure vessel design problems and tension/compression spring design problems. The optimization results show that GLCryStAl is feasible and effective in optimizing engineering design. [ABSTRACT FROM AUTHOR]

Asphalt pavement presents diverse dynamic responses to vehicle loading in dry and saturated conditions, which can be systematically explored by numerical simulation. Building a numerical model based on the actual conditions of asphalt pavement is necessary, and relevant field tests should be subsequently conducted to monitor dynamic responses to calibrate and validate the numerical model. On the basis of strictly controlling the paths of vehicle wheels during field tests, this study numerically analyzed the dynamic responses of asphalt pavement in dry and saturated conditions under full-scale accelerated loading. The trends of the modeling results were consistent with those of field measurements. The increase in vehicle load significantly increased the magnitudes of stress, strain, and pore water pressure, while vehicle speed showed an obvious impact on pore water pressure. The dynamic responses decreased with pavement depths. Water made the dynamic responses more complex, and pore water pressure significantly decreased with depth within the upper layer of saturated asphalt pavement. Transverse distributions of indicators presented obvious compressive states in the regions in direct contact with vehicle wheels, while tensile states were found in the range of the middle vehicle axle. The numerical results provided a basis for field measurements in future studies, especially for the exploration of factors of temperature and layer depth. [ABSTRACT FROM AUTHOR]

Perovskite solar cells (PSCs) have experienced rapid development in the past period of time, and a record efficiency of up to 25.7% has been yielded. At present, the PSCs with the planar structure are the most prevailing, which not only can significantly simplify the device fabrication process but also reduce the processing temperature. Particularly, the electron transport layer (ETL) plays a critical role in boosting the device performance of planar PSCs. ZnO is a promising candidate as the ETL owing to its high transparency, suitable energy band structure, and high electron mobility. Moreover, ZnO is easy to be processed at a low cost and low energy. This review mainly summarized the recent advances in the application and strategic optimization of ZnO ETL for planar PSCs. The basic properties of ZnO, including energy levels, mobility, processability, trap defects, as well as chemical stability, are clearly clarified. The most available deposition means for preparing ZnO ETLs were also described briefly. Finally, we presented the challenges and guidelines for utilizing ZnO as ETL on efficient planar PSCs. [ABSTRACT FROM AUTHOR]

The tuna swarm optimization algorithm (TSO) is a new heuristic algorithm proposed by observing the foraging behavior of tuna populations. The advantages of TSO are a simple structure and fewer parameters. Although TSO converges faster than some classical meta-heuristics algorithms, it can still be further accelerated. When TSO solves complex and challenging problems, it often easily falls into local optima. To overcome the above issue, this article proposed an improved nonlinear tuna swarm optimization algorithm based on Circle chaos map and levy flight operator (CLTSO). In order to compare it with some advanced heuristic algorithms, the performance of CLTSO is tested with unimodal functions, multimodal functions, and some CEC2014 benchmark functions. The test results of these benchmark functions are statistically analyzed using Wilcoxon, Friedman test, and MAE analysis. The experimental results and statistical analysis results indicate that CLTSO is more competitive than other advanced algorithms. Finally, this paper uses CLTSO to optimize a BP neural network in the field of artificial intelligence. A CLTSO-BP neural network model is proposed. Three popular datasets from the UCI Machine Learning and Intelligent System Center are selected to test the classification performance of the new model. The comparison result indicates that the new model has higher classification accuracy than the original BP model. [ABSTRACT FROM AUTHOR]

Asphalt binder plays an important role in the overall resistance of asphalt mixture to the moisture damage induced by a dynamic pore water pressure environment. This study evaluates the moisture sensitivity of asphalt binder from the perspective of rheological behaviors using the dynamic shear rheometer (DSR) and the bending beam rheometer (BBR) methods at high, medium, and low temperatures. The damage mechanism is further discussed quantitatively based on the Fourier transform infrared spectroscopy (FTIR) method. The results indicate that a longer conditioning duration is beneficial for asphalt binder to recover its adhesion at 60 °C in multiple stress creep recover (MSCR) tests, but the increasing pore water pressure magnitude of 60 psi held an opposite effect in this study. The asphalt binder's fatigue life at 20 °C in linear amplitude sweep (LAS) tests decreased obviously with conditioning duration and environmental severity, but the reducing rate gradually slowed down, while the groups of 50 psi—4000 cycles and 60 psi—4000 cycles held a comparable erosion effect. Both the stiffness and relaxation moduli at −12 °C in the BBR tests exhibited an obvious decreasing trend with conditioning duration and environmental severity. The erosion effect on the asphalt binder was gradually enhanced, but it also exhibited a slightly more viscous performance. Water conditioning induced several obvious characteristic peaks in the FTIR absorbance spectra of the asphalt binder. The functional group indexes presented a trend of non-monotonic change with conditioning duration and environmental severity, which made the asphalt binder show complicated rheological behaviors, such as non-monotonic variations in performance and the abnormal improving effect induced by dynamic pore water pressure conditioning. [ABSTRACT FROM AUTHOR]

The quick and precise assessment of rice distribution by remote sensing technology is important for agricultural development. However, mountain rice is limited by the complex terrain, and its distribution is fragmented. Therefore, it is necessary to fully use the abundant spatial, temporal, and spectral information of remote sensing imagery. This study extracted 22 classification features from Sentinel-2 imagery (spectral features, texture features, terrain features, and a custom spectral-spatial feature). A feature selection method based on the optimal extraction period of features (OPFSM) was constructed, and a multitemporal feature combination (MC) was generated based on the separability of different vegetation types in different periods. Finally, the extraction accuracy of MC for mountain rice was explored using Random Forest (RF), CatBoost, and ExtraTrees (ET) machine learning algorithms. The results show that MC improved the overall accuracy (OA) by 3–6% when compared to the feature combinations in each rice growth stage, and by 7–14% when compared to the original images. MC based on the ET classifier (MC-ET) performed the best for rice extraction, with the OA of 86%, Kappa coefficient of 0.81, and F1 score of 0.95 for rice. The study demonstrated that OPFSM could be used as a reference for selecting multitemporal features, and the MC-ET classification scheme has high application potential for mountain rice extraction. [ABSTRACT FROM AUTHOR]

In the process of the rutting test, the air-void characteristics in asphalt mixture specimens are a dynamic change process. It is of great significance to systematically study the correlation between the change of air-void characteristics and the depth of the rutting slab and establish a relationship with damage. In this paper, the air-void information of rutting specimen sections with different loading cycles (500, 1000, 1500, 2000, 2500, and 3000 times) is obtained by two-dimensional image technology. The dynamic change process of the micro characteristics of internal air voids of two graded asphalt mixtures (AC-13 and AC-16) under cyclic wheel load is analyzed, and it is used as an index to characterize the microstructure damage of the asphalt mixture. The results show that the variation of air-void distribution, air-void shape characteristics, and air-void fractal dimension with the loading process can well characterize the permanent deformation law of the rutting slab. The fractal dimension of the air void increases with the increase in load. It is a dynamic process in which the air-void content changes with crack initiation and propagation. After rutting deformation, the total air-void area and average air-void size of the sample increase, and the total air-void number decreases. Because microcracks are formed in the specimen after rutting damage, the aspect ratio of the air void increases, and the roundness value decreases. [ABSTRACT FROM AUTHOR]

With rapid development of clean energy vehicles, the health diagnosis and prognosis of lithium batteries remain challenging for practical applications. Accurate state-of-health (SOH) and remaining useful life (RUL) estimation provides crucial information for improving the safety, reliability and longevity of batteries. In this paper, a fusion of deep-learning model and feature signal analysis methods are proposed to realize accurate and fast estimation of the health conditions for battery cathodes. Specifically, the long short-term memory (LSTM) network and differential thermal voltammetry (DTV) are utilized to verify our fusion method. Firstly, the DTV feature signal analysis is executed based on battery charging and discharging data, based on which useful feature variables are extracted with Pearson correlation analysis. Next, the deep-learning model is constructed and trained with the LSTM as the core based on timeseries datasets constructed with features. Finally, the validation and error analysis of proposed model are provided, showing a max mean absolute error of 0.6%. The proposed method enables highly accurate models for SOH and RUL estimation that can be potentially deployed on cloud-end for offline battery degradation tracking. [ABSTRACT FROM AUTHOR]

Background and Objectives: The quantity, size, and position of implants might affect the fracture healing process of surgically treated displaced pediatric femoral neck fractures (PFNFs). The aim of this retrospective multicenter study was to evaluate the correlation between the time needed to achieve radiological union and the number, size, and location of the partially threaded cannulated screws (PTCSs) in children with displaced PFNFs. Materials and Methods: A retrospective review of 136 children (mean age: 10.6 ± 3.8 years) with displaced PFNFs treated by two (n = 103) or three (n = 33) PTCSs was carried out. Student's t-tests, one-way ANOVA, Cox regression analysis, and multiple linear regression analyses were performed to investigate the variables affecting the time needed to achieve radiological fracture healing according to the number, size, and position of PTCSs, as assessed on plain radiographs. Results: A total of 132 hips achieved union at an average of 3.2 ± 1.6 months after the initial surgery. The time needed to achieve union in the patients treated with two or three PTCSs was comparable (p = 0.36). Among the fractures treated by two PTCSs, the time needed to achieve union did not correlate with the size of the implant (p = 0.122), or with the angulation between the PTCSs on anterior–posterior (p = 0.257) and lateral radiographs (p = 0.547). The time needed to achieve union in the fractures that were fully compressed by the implants was similar to the partially compressed fractures (p = 0.08). Conclusions: The number, size, and position of the PTCSs do not affect the radiological healing in the children with displaced PFNFs treated surgically. [ABSTRACT FROM AUTHOR]

Variable selection has been a hot topic, with various popular methods including lasso, SCAD, and elastic net. These penalized regression algorithms remain sensitive to noisy data. Furthermore, "concept drift" fundamentally distinguishes streaming data learning from batch learning. This article presents a method for noise-resistant regularization and variable selection in noisy data streams with multicollinearity, dubbed canal-adaptive elastic net, which is similar to elastic net and encourages grouping effects. In comparison to lasso, the canal adaptive elastic net is especially advantageous when the number of predictions (p) is significantly larger than the number of observations (n), and the data are multi-collinear. Numerous simulation experiments have confirmed that canal-adaptive elastic net has higher prediction accuracy than lasso, ridge regression, and elastic net in data with multicollinearity and noise. [ABSTRACT FROM AUTHOR]

R2R3-MYB transcription factors participate in multiple critical biological processes, particularly as relates to the regulation of secondary metabolites. The dried root of Scutellaria baicalensis Georgi is a traditional Chinese medicine and possesses various bioactive attributes including anti-inflammation, anti-HIV, and anti-COVID-19 properties due to its flavonoids. In the current study, a total of 95 R2R3-MYB genes were identified in S. baicalensis and classified into 34 subgroups, as supported by similar exon–intron structures and conserved motifs. Among them, 93 R2R3-SbMYBs were mapped onto nine chromosomes. Collinear analysis revealed that segmental duplications were primarily responsible for driving the evolution and expansion of the R2R3-SbMYB gene family. Synteny analyses showed that the ortholog numbers of the R2R3-MYB genes between S. baicalensis and other dicotyledons had a higher proportion compared to that which is found from the monocotyledons. RNA-seq data indicated that the expression patterns of R2R3-SbMYBs in different tissues were different. Quantitative reverse transcriptase-PCR (qRT-PCR) analysis showed that 36 R2R3-SbMYBs from different subgroups exhibited specific expression profiles under various conditions, including hormone stimuli treatments (methyl jasmonate and abscisic acid) and abiotic stresses (drought and cold shock treatments). Further investigation revealed that SbMYB18/32/46/60/70/74 localized in the nucleus, and SbMYB18/32/60/70 possessed transcriptional activation activity, implying their potential roles in the regulatory mechanisms of various biological processes. This study provides a comprehensive understanding of the R2R3-SbMYBs gene family and lays the foundation for further investigation of their biological function. [ABSTRACT FROM AUTHOR]

Compared with state-of-the-art radio frequency accelerators, the gradient of laser wakefield accelerators is 3–4 orders of magnitude higher. This is of great significance in the development of miniaturized particle accelerators and radiation sources. Higher requirements have been proposed for the quality of electron beams, owing to the increasing application requirements of tabletop radiation sources, specifically with the rapid development of free-electron laser devices. This review briefly examines the electron beam quality optimization scheme based on laser wakefield acceleration and presents some representative studies. In addition, manipulation of the electron beam phase space by means of injection, plasma profile distribution, and laser evolution is described. This review of studies is beneficial for further promoting the application of laser wakefield accelerators. [ABSTRACT FROM AUTHOR]

Detection of hidden defects of aircraft long truss structures (aluminum alloy) is a challenging problem. The shape of the aircraft truss structure is complex, and the crack defects are buried in a large depth. Without the restriction of skin effect, remote field eddy current (RFEC) has great advantages in detecting buried depth defects. In this paper, in order to detect the hidden defects of the aluminum alloy aircraft long truss structure, the remote field eddy current probe is improved from two aspects of magnetic field enhancement and near-field signal suppression using the finite element method. The results show that indirect coupling energy is greatly enhanced when the connected magnetic circuit is added to the excitation coil. By adding a composite shielding structure outside the excitation coil and the detection coil, respectively, the direct coupling energy is effectively restrained. As a result, the size of the probe is reduced. By optimizing the coil spacing and probe placement position, the detection sensitivity of the probe is improved. The simulation is verified by experiments, and the experimental results are consistent with the simulation conclusions. [ABSTRACT FROM AUTHOR]