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Homology to E6-AP Carboxy Terminus (HECT) E3 ubiquitin ligases play pivotal roles in plant growth, development, and responses to abiotic stresses. However, the function of HECT genes in Phyllostachys edulis (P. edulis) remains largely uninvestigated. In this study, a comprehensive genome-wide analysis of the HECT E3 ubiquitin ligases gene family in P. edulis was conducted, aiming to elucidate its evolutionary relationships and gene expansion. Analysis of gene structure, conserved motifs and domains, and synteny genome regions were performed. Furthermore, cis-elements in HECT gene promoters that respond to plant hormones and environmental stresses were identified and corroborated by expression data from diverse abiotic stress conditions and hormone treatments. Based on the co-expression network of PeHECTs under cold and dehydration stresses, PeHECT1 was identified as a key candidate gene associated with abiotic stress tolerance. Overexpression of PeHECT1 in tobacco leaves significantly upregulated genes related to reactive oxygen species (ROS) detoxification and polyamine biosynthesis. Yeast one-hybrid (Y1H), electrophoretic mobility shift assay (EMSA), and dual-luciferase (dual-LUC) assays suggested that the transcription factor ETHYLENE RESPONSE FACTOR 3 (PeERF3) bound to the dehydration-responsive element (DRE) of the promoter of PeHECT1 and activated its transcription activity. Phylogenetic analysis indicated that PeHECT1 in P. edulis exhibited a close association with the diploid herbaceous bamboo Olyra latifolia, followed by the divergence of rice and bamboo. In summary, this study enhances our comprehensive understanding of the HECT E3 ubiquitin ligases gene family in P. edulis and highlights the potential role of PeHECT1 in plant abiotic stress response. [ABSTRACT FROM AUTHOR]

Conventional methods for tumor diagnosis suffer from two inherent limitations: they are time-consuming and subjective. Computer-aided diagnosis (CAD) is an important approach for addressing these limitations. Pathology whole-slide images (WSIs) are high-resolution tissue images that have made significant contributions to cancer diagnosis and prognosis assessment. Due to the complexity of WSIs and the availability of only slide-level labels, multiple instance learning (MIL) has become the primary framework for WSI classification. However, most MIL methods fail to capture the interdependence among image patches within a WSI, which is crucial for accurate classification prediction. Moreover, due to the weak supervision of slide-level labels, overfitting may occur during the training process. To address these issues, this paper proposes a dual-attention-based multiple instance learning framework (DAMIL). DAMIL leverages the spatial relationships and channel information between WSI patches for classification prediction, without detailed pixel-level tumor annotations. The output of the model preserves the semantic variations in the latent space, enhances semantic disturbance invariance, and provides reliable class identification for the final slide-level representation. We validate the effectiveness of DAMIL on the most commonly used public dataset, Camelyon16. The results demonstrate that DAMIL outperforms the state-of-the-art methods in terms of classification accuracy (ACC), area under the curve (AUC), and F1-Score. Our model also allows for the examination of its interpretability by visualizing the dual-attention weights. To the best of our knowledge, this is the first attempt to use a dual-attention mechanism, considering both spatial and channel information, for whole-slide image classification. [ABSTRACT FROM AUTHOR]

The surface quality of parts processed by laser additive manufacturing, especially laser-based directed energy deposition (LDED), makes it difficult to meet actual use requirements. In addition, defects generated during the long-term additive manufacturing process need to be removed in time. Therefore, laser additive and subtractive manufacturing is of great significance for additive manufacturing. The main difference between laser additive-subtractive manufacturing and pure subtraction is that a cooling temperature is required due to the laser process. Therefore, this work studies the temperature variation regularity during LDED and the milling processes, as well as the surface roughness, cross-sectional microstructure, and tool wear under different cooling temperatures for milling. The results show that there is a "turning point temperature" in LDED, and the value of the turning point temperature gradually increases with heat accumulation, which affects the initial temperature of the subtractive manufacturing. When subtracting, a high initial temperature improves surface quality and reduces tool wear, but an excessively high temperature will cause the aluminum alloy to adhere to the tool. Then, the smear metal is difficult to effectively remove, deteriorates the milling quality, and aggravates tool wear. It is found that the higher the cooling temperature generated, the wider the thermally insulated shear band. The insulated shear band may affect the quality of the additive and subtractive manufacturing. Finally, it is determined that the milling temperature of aluminum alloy in this work condition is about 100 °C. [ABSTRACT FROM AUTHOR]

β-carotene (BC) has various biological activities, such as anticancer properties, contributing to the prevention of cardiovascular diseases, etc., while the poor solubility and low bioavailability limit its further development in the food industry. Therefore, how to effectively encapsulate this unstable substance has become a hot topic. Here, different concentrations of sodium caseinate and ι-carrageenan (NaCas-CA) complex emulsions were used as wall materials, and the effect of spray-drying (SD) and vacuum freeze-drying (VFD) on the properties of BC powders loaded with NaCas-CA was investigated. The results showed that the characteristic peaks of BC disappeared in all powdered oils, indicating that BC could be effectively encapsulated. As the wall concentration increased, the surface oil of the powders decreased significantly. At the same concentration, the surface oil content of SD (minimum of 8.34%) was lower than that of VFD (minimum of 10.02%). However, the particle size of SD-reconstituted emulsions was larger than that of VFD. Furthermore, the SD-reconstituted emulsions were more stable than the VFD after storage at 25 °C for 3 h. This study reveals the effect of different drying methods on the structure and stability of powdered oils, providing valuable information for the research of functional active-loaded powdered oils and applications in the food industry. [ABSTRACT FROM AUTHOR]

Metabolic reprogramming of immune cells within the tumor microenvironment (TME) plays a pivotal role in shaping tumor progression and responses to therapy. The intricate interplay between tumor cells and immune cells within this ecosystem influences their metabolic landscapes, thereby modulating the immune evasion tactics employed by tumors and the efficacy of immunotherapeutic interventions. This review delves into the metabolic reprogramming that occurs in tumor cells and a spectrum of immune cells, including T cells, macrophages, dendritic cells, and myeloid-derived suppressor cells (MDSCs), within the TME. The metabolic shifts in these cell types span alterations in glucose, lipid, and amino acid metabolism. Such metabolic reconfigurations can profoundly influence immune cell function and the mechanisms by which tumors evade immune surveillance. Gaining a comprehensive understanding of the metabolic reprogramming of immune cells in the TME is essential for devising novel cancer therapeutic strategies. By targeting the metabolic states of immune cells, it is possible to augment their anti-tumor activities, presenting new opportunities for immunotherapeutic approaches. These strategies hold promise for enhancing treatment outcomes and circumventing the emergence of drug resistance. [ABSTRACT FROM AUTHOR]

Hibernation serves as an energy-conserving strategy that enables animals to withstand harsh environments by reducing their metabolic rate significantly. However, the mechanisms underlying energy adaptation in hibernating ectotherms, such as Pelodiscus sinensis, remain contentious. This paper first reports the decrease in lipid levels and the expression of metabolism-related genes in P. sinensis during hibernation. The results of physiological and biochemical analysis showed that adipocyte cell size was reduced and liver lipid droplet (LD) contents were decreased during hibernation in P. sinensis. Concurrently, serum levels of triglycerides (TGs), total cholesterol (TC), non-esterified fatty acids (NEFAs), high-density lipoprotein cholesterol (HDLC), and low-density lipoprotein cholesterol (LDLC) were diminished (n = 8, p < 0.01), while an increase in serum glucose (Glu) (n = 8, p < 0.01) was noted among hibernating P. sinensis. These observations suggest a shift in energy metabolism during hibernation. To gain insights into the molecular mechanisms, we performed integrated transcriptomic and lipidomic analyses of adipose tissue and livers from summer-active versus overwintering P. sinensis, which revealed downregulation of free fatty acids (FFAs), triglycerides (TGs), diglycerides (DGs), and ceramides (Cers) during hibernation. The results of GSEA analysis showed that metabolic pathways associated with lipid metabolism, including glycerolipid metabolism and regulation of lipolysis in adipocytes, were suppressed significantly. Notably, acute cold exposure induced significant downregulation of genes related to lipolysis such as PNPLA2, ABHD5, LPL, CPT1A, and PPARα. The results indicate that lipolysis is suppressed during hibernation in P. sinensis. Collectively, these findings deepen our understanding of survival mechanisms and elucidate the unique energy adaptation strategies employed by hibernating ectotherms. Future research should explore the implications of these findings for the conservation of ectotherms and the applications for artificially inducing hibernation. [ABSTRACT FROM AUTHOR]

Heat shock proteins (Hsps), acting as molecular chaperones, play a pivotal role in plant responses to environmental stress. In this study, we found a total of 192 genes encoding Hsps, which are distributed across all 12 chromosomes, with higher concentrations on chromosomes 1, 2, 3, and 5. These Hsps can be divided into six subfamilies (sHsp, Hsp40, Hsp60, Hsp70, Hsp90, and Hsp100) based on molecular weight and homology. Expression pattern data indicated that these Hsp genes can be categorized into three groups: generally high expression in almost all tissues, high tissue-specific expression, and low expression in all tissues. Further analysis of 15 representative genes found that the expression of 14 Hsp genes was upregulated by high temperatures. Subcellular localization analysis revealed seven proteins localized to the endoplasmic reticulum, while others localized to the mitochondria, chloroplasts, and nucleus. We successfully obtained the knockout mutants of above 15 Hsps by the CRISPR/Cas9 gene editing system. Under natural high-temperature conditions, the mutants of eight Hsps showed reduced yield mainly due to the seed setting rate or grain weight. Moreover, the rice quality of most of these mutants also changed, including increased grain chalkiness, decreased amylose content, and elevated total protein content, and the expressions of starch metabolism-related genes in the endosperm of these mutants were disturbed compared to the wild type under natural high-temperature conditions. In conclusion, our study provided new insights into the HSP gene family and found that it plays an important role in the formation of rice quality and yield. [ABSTRACT FROM AUTHOR]

This study aimed to investigate differences in the leaf biomasses, chemical compositions, and pharmacological activities of Turpinia arguta histocultured seedlings and live seedlings at different harvesting periods (S1, S2, S3, and S4) in order to determine the optimal harvesting period. Eleven indexes, including biomass, key active components, secondary metabolites, nutrient content, and antioxidant activity, were evaluated by high-performance liquid chromatography and colorimetric methods during different harvesting periods. The weights of the 11 indexes were calculated by principal component analysis, and then a comprehensive quality evaluation was performed. The results showed significant differences in leaf biomasses, key active components, secondary metabolites, nutrient contents, and antioxidant activities between the different harvesting periods. The highest quality score was obtained for the S4 period, indicating that the quality of T. arguta was the best at this time and that the S4 period was the most suitable harvesting period. At this period (S4), the medicinal component content, antioxidant activity, and comprehensive quality score of the histocultured seedlings of T. arguta were higher than those of the live seedlings, indicating the importance of tissue culture technology in enhancing the quality of T. arguta. This study provides more novel and abundant information and reference for determining the appropriate harvesting period of T. arguta, with the aim of providing newer scientific guidance for the management of herbs. [ABSTRACT FROM AUTHOR]

Expansins are known as cell wall loosening proteins and are involved in cell expansion and varieties of plant developmental progresses. However, little is known about their biological functions in alfalfa (Medicago sativa L.). In the present study, 30 MsEXP genes were identified in the alfalfa (cultivar "zhongmu-1") genome. Phylogenetic analysis revealed that these MsEXP proteins were divided into four subfamilies, including twenty-one MsEXPAs, six MsEXPBs, one MsEXL1 and two MsEXLBs. MsEXP genes were unevenly distributed on eight chromosomes. The gene structures of the MsEXP genes and the motif composition of the MsEXP proteins were inconsistent with the phylogenetic relationship of MsEXPs. Cis-acting elements analysis indicated that MsEXP genes may respond to diverse hormonal signals involved in the developmental progress of plants. Furthermore, expression analysis suggested that MsEXP genes exhibited distinct expression patterns among different tissues of alfalfa. Overexpression of MsEXPA3 or MsEXPA4 promoted the growth of leaves, stems and roots of Arabidopsis, thereby increasing the biomass of plants. Subsequent cell morphological analysis uncovered that overexpression of MsEXPA3 or MsEXPA4 promoted the expansion of cells. Taken together, these findings illustrate the functions of MsEXP proteins in regulating the development of plants. Our results may provide a strong basis for further elucidating the roles of these EXP genes in alfalfa development and valuable genetic resources for future crop improvement. [ABSTRACT FROM AUTHOR]

Aminolevulinic acid (5-ALA) and dihydroporphyrin iron chelates (DHFe) play roles in plant growth regulation under normal and stressful conditions. However, definitive data on their roles in regulating chlorophyll synthesis in wheat are lacking. In this study, the optimal concentrations for foliar-spray application of 5-ALA and DHFe to promote wheat seedling growth and leaf chlorophyll content were assessed. The optimal concentrations of 5-ALA or DHFe (50 mg/L and 0.01 mg/L, respectively) were applied as foliar sprays to seedlings of wheat 'Bainong 4199' (high light efficient) and 'Zhoumai No. 18' (average light efficient) under different light intensities. Chlorophyll precursor contents and activities of three chlorophyll synthesis-related enzymes were altered, and the combined application of 5-ALA and DHFe more strongly increased the leaf chlorophyll content. 5-ALA significantly increased the contents of the chlorophyll precursors porphobilinogen, uroporphyrinogen III, protoporphyrin IX, and magnesium-protoporphyrin IX, and the activities of 5-amino-ketovalerate dehydratase and uroporphyrinogen III synthase. DHFe resulted in an increase in chlorophyll content but a significant decrease in chlorophyllase activity and protochlorophyllide content. 5-ALA promoted the synthesis of chlorophyll precursors by regulating the activities of 5-amino-ketovalerate dehydratase and uroporphyrinogen III synthase. DHFe decreased chlorophyllase activity, thereby slowing chlorophyll degradation and increasing the chlorophyll content. [ABSTRACT FROM AUTHOR]

A modified loess/chitosan composite (ML@CS) was prepared via solution. The microstructure and physicochemical properties of ML@CS were characterised via scanning electron microscope (SEM), Zeta potential, X-ray diffraction (XRD), Fourier transform infrared spectrum (FT-IR), and thermogravimetric analysis (TGA). An aqueous solution of methyl orange (MO) was used as simulated wastewater from which the influence of the initial concentration and pH of MO, the dosage amount and regeneration performance of ML@CS, adsorption temperature, and time on the adsorption effect of MO were systematically investigated. The adsorption kinetics, isothermal adsorption, and adsorption mechanism were also analysed. The results indicate that ML@CS had a good adsorption effect on MO. When the initial concentration of MO was 200 mg/L, pH was 5.0, and ML@CS dosage was 1.0 g/L, the adsorption equilibrium could be reached within 180 min at room temperature, and the equilibrium adsorption capacity and removal rate reached 199.52 mg/g and 99.75%, respectively. After five adsorption–desorption cycles, the MO removal rate remained above 82%. The adsorption behaviour of ML@CS for MO conforms to the pseudo–second–order kinetic model and the Langmuir isotherm adsorption model. The spontaneous exothermic process was mainly controlled by monolayer chemical adsorption and the physical adsorption only played an auxiliary role. ML@CS efficiently adsorbed MO in water and can be used as a high-efficiency, low-cost adsorbent for printing and dyeing wastewater treatment. [ABSTRACT FROM AUTHOR]

Ship fuel consumption plays a crucial role not only in understanding ships' energy efficiency but also in gaining insights into their emissions. However, enhancing the accuracy of these predictions poses significant challenges due to data limitations and the methods employed. Due to these factors, such as data variability and equipment characteristics, ship fuel consumption exhibits certain fluctuations under specific conditions. Previous fuel consumption prediction methods primarily generate a single specific value, making it difficult to capture the volatility of and variability in fuel consumption. To overcome this limitation, this paper proposes a novel method that integrates Gaussian process prediction with quantile regression theory to perform interval predictions of ship fuel consumption, providing a range of possible outcomes. Through comparative analyses with traditional methods, the possibility of using the method is verified and its results are validated. The results indicate the following: (1) at a 95% confidence level, the proposed method achieves a prediction interval coverage probability of 0.98 and a prediction interval normalized average width of 0.123, which are significantly better than those of the existing backpropagation neural network (BPNN) and gradient boosting decision tree (GBDT) quantile regression models; (2) the prediction accuracy of the proposed method is 92% for point forecasts; and (3) the proposed method is applicable to main datasets, including both noon report and sensor datasets. These findings provide valuable insights into interval predictions of ship fuel consumption and highlight their potential applications in related fields, emphasizing the importance of accurate interval predictions in intelligent energy efficiency optimization. [ABSTRACT FROM AUTHOR]

Simple Summary: Pine woods have suffered major damage from the beetle Monochamus alternatus, which spreads the nematode Bursaphelenchus xylophilus and poses a serious threat to conifers like Pinus massoniana. In order to fill the knowledge gap regarding the phylogeography of M. alternatus, specific simple sequence repeat (SSR) primers were designed as part of this work. To find polymorphic SSRs, researchers sequenced M. alternatus specimens from three different locations using the Red-seq approach. After additional analysis, 95,612 SSR loci were found, most of which were repeats of mononucleotide (51.43%), dinucleotide (28.79%), and trinucleotide (16.74%) repeats. Eighteen pairs of SSR primers were selected for their stability and high polymorphism, with genetic typing showing an average allele count of 3–8, heterozygosity (Ho) from 0.13 to 0.73, PIC values ranging from 0.29 to 0.78, and Shannon's index between 0.59 and 1.80. The study resulted in 16 usable SSR primer pairs, enhancing research capabilities in phylogeography, genetic mapping, and functional genomics of M. alternatus. Monochamus alternatus, a pest posing a serious threat to coniferous species, such as Pinus massoniana, has had devastating effects on pine forests due to its association with Bursaphelenchus xylophilus. The creation of unique simple sequence repeat (SSR) primers for M. alternatus is crucial, as there has been little study of the species' phylogeography. The aim of this study was to identify and create polymorphic SSR primers by sequencing samples of M. alternatus obtained from three different sampling points using the restriction site-associated DNA sequencing (Red-seq) approach. Subsequently, supplementary samples were integrated, and genetic typing was performed utilizing the identified polymorphic primers. Through comprehensive analysis, a total of 95,612 SSR loci were identified. Among these, mononucleotide repeats (51.43%), dinucleotide repeats (28.79%), and trinucleotide repeats (16.74%) predominated among the SSR motif types. Ultimately, 18 pairs of SSR primers were screened out, demonstrating stable amplification and high polymorphism. Genetic typing revealed that the mean number of alleles (Na) for these primer pairs ranged from 3 to 8, observed heterozygosity (Ho) ranged from 0.133 to 0.733, polymorphic information content (PIC) ranged from 0.294 and 0.783, and Shannon's index (I) ranged from 0.590 to 1.802. This study effectively produced 16 pairs of SSR primers that can be applied to different populations of M. alternatus. As a result, important tools for furthering studies on the phylogeography of pine wood nematodes, creating genetic maps, gene mapping, and carrying out in-depth investigations into gene function have been made available. [ABSTRACT FROM AUTHOR]

The rapid reconstruction of the internal flow field within pressure vessel equipment based on features from limited detection points was of significant value for online monitoring and the construction of a digital twin. This paper proposed a surrogate model that combined Proper Orthogonal Decomposition (POD) with deep learning to capture the dynamic mapping relationship between sensor monitoring point information and the global flow field state during equipment operation, enabling rapid reconstruction of the temperature field and velocity field. Using POD, the order of the tested temperature field was reduced by 99.75%, and the order of the velocity field was reduced by 99.13%, effectively decreasing the dimensionality of the flow field. Our analysis revealed that the first modal coefficient of the temperature field snapshot data, after modal decomposition, had a higher energy proportion compared to that of the velocity field snapshot data, along with a more pronounced marginal effect. This indicates that more modes need to be retained for the velocity field to achieve a higher total energy proportion. By constructing a CSSA-BP model to represent the mapping relationship between the modal coefficients of the temperature and velocity fields and the data collected from the detection points, a comparison was made with the BP method in reconstructing the temperature field of a shell-and-tube heat exchanger. The CSSA-BP method yielded a maximum mean squared error (MSE) of 9.84 for the reconstructed temperature field, with a maximum mean absolute error (MAE) of 1.85. For the velocity field, the maximum MSE was 0.0135 and the maximum MAE was 0.0728. The global maximum errors for the reconstructed temperature field were 4.85%, 3.65%, and 4.29%, respectively. The global maximum errors for the reconstructed velocity field were 17.72%, 11.30%, and 16.79%, indicating that the model established in this study has high accuracy. Conventional CFD simulation methods require several hours, whereas the reconstruction model proposed here can rapidly reconstruct the flow field within 1 min after training is completed, significantly reducing reconstruction time. This work provides a new method for quickly obtaining the internal flow field state of pressure vessel equipment under limited detection points, offering a reference for online monitoring and the development of digital twins for pressure vessel equipment. [ABSTRACT FROM AUTHOR]

To overcome the challenges posed by limited garbage datasets and the laborious nature of data labeling in urban garbage object detection, we propose an innovative unsupervised domain adaptation approach to detecting garbage objects in urban aerial images. The proposed method leverages a detector, initially trained on source domain images, to generate pseudo-labels for target domain images. By employing an attention and confidence fusion strategy, images from both source and target domains can be seamlessly integrated, thereby enabling the detector to incrementally adapt to target domain scenarios while preserving its detection efficacy in the source domain. This approach mitigates the performance degradation caused by domain discrepancies, significantly enhancing the model's adaptability. The proposed method was validated on a self-constructed urban garbage dataset. Experimental results demonstrate its superior performance over baseline models. Furthermore, we extended the proposed mixing method to other typical scenarios and conducted comprehensive experiments on four well-known public datasets: Cityscapes, KITTI, Sim10k, and Foggy Cityscapes. The result shows that the proposed method exhibits remarkable effectiveness and adaptability across diverse datasets. [ABSTRACT FROM AUTHOR]

Shi-related sequence (SRS) proteins, which consist of the RING-like zinc finger domain and IGGH domain, are plant-specific transcription factors that have been well-studied in several plant species. However, information about SRS genes and their roles in cucumber (Cucumis sativus L.) is limited. Therefore, we performed detailed bioinformatic analysis of the SRS gene family, including gene numbers and positions, genes structures, conserved motif distribution patterns, phylogenetic analysis, and promoter cis-element analysis. Eight SRS genes were identified in cucumber and distributed on all seven cucumber chromosomes. SRS genes are conserved in plants and divided into two groups in cucumber based on their protein sequence. In silico analysis predicted that most genes may function in response to abiotic stresses and phytohormones. Gene ontology analysis predicted the possible involvement of genes in development and reproduction, and DNA and protein binding on a molecular level. Furthermore, the differential expression pattern of SRS genes in leaf, stem and root under the condition of Zn2+ stress suggested their roles in response to Zn2+ stress. Furthermore, our metal tolerance assay suggested that CsSRS2 and CsSRS5 mediated enhanced tolerance to Zn2+ stress in Escherichia coli cells. Our study provides a foundation for the functional study of SRS genes in cucumber. [ABSTRACT FROM AUTHOR]

This study used hyperspectral remote sensing to rapidly, economically, and non-destructively determine the soil iron oxide content of the Dinosaur Valley annular tectonic region of Lufeng, Yunnan Province. The laboratory determined the iron oxide content and original spectral reflectance (OR) in 138 surface soil samples. We first subjected the OR data to Savizky–Golay smoothing, followed by four spectral transformations—continuum removal reflectance, reciprocal logarithm reflectance, standard normal variate reflectance, and first-order differential reflectance—which improved the signal-to-noise ratio of the spectral curves and highlighted the spectral features. Then, we combined the correlation coefficient method (CC), competitive adaptive reweighting algorithm, and Boruta algorithm to screen out the characteristic wavelength. From this, we constructed the linear partial least squares regression model, nonlinear random forest, and XGBoost machine learning algorithms. The results show that the CC-Boruta method can effectively remove any noise and irrelevant information to improve the model's accuracy and stability. The XGBoost nonlinear machine learning algorithm model better captures the complex nonlinear relationship between the spectra and iron oxide content, thus improving its accuracy. This provides a relevant reference for the rapid and accurate inversion of iron oxide content in soil using hyperspectral data. [ABSTRACT FROM AUTHOR]

The giant magnetoresistance effect in two-dimensional (2D) magnetic materials has sparked substantial interest in various fields; including sensing; data storage; electronics; and spintronics. Their unique 2D layered structures allow for the manifestation of distinctive physical properties and precise performance regulation under different conditions. In this review, we present an overview of this rapidly developing research area. Firstly, these 2D magnetic materials are catalogued according to magnetic coupling types. Then, several vital effects in 2D magnets are highlighted together with theoretical investigation, such as magnetic circular dichroism, magneto-optical Kerr effect, and anomalous Hall effect. After that, we forecast the potential applications of 2D magnetic materials for spintronic devices. Lastly, research advances in the attracting magnons, skyrmions and other spin textures in 2D magnets are discussed. [ABSTRACT FROM AUTHOR]

Depositing a tritium permeation barrier on the surface of materials is a key method for reducing tritium permeability. During actual operational processes, the surface of the tritium permeation barrier may experience mechanical damage, such as spalling and scratches. The hydrogen permeability resistance of the coating will degrade due to such forms of mechanical damage. It is a significant engineering challenge to evaluate the impact of these damages on the coating's tritium resistance. In this experiment, the mechanical damage to the FeAl/Al2O3 tritium permeation barrier on 316L stainless steel was simulated through scratching, debonding, and thermal shock. Subsequently, a hydrogen isotope gas drive permeation (GDP) test was conducted. The influence of the degree of mechanical damage on the coating's tritium permeation behavior was assessed and discussed. The results indicate that, under the same damage mechanism, the coating's tritium permeability resistance is positively correlated with the integrity of the coating. Additionally, the impact of scratches on the coating surface is more severe than that of other damage mechanisms. [ABSTRACT FROM AUTHOR]

The evaluation and prediction of ecological benefits are significant for regional resource development planning and path designing. This study established a novel ecological benefits evaluation system by integrating macro-ecosystem structure, Ecosystem service index (ESI), and ecological quality index (EQI). Based on this system, this study evaluated the spatiotemporal characteristics and changing trend of ecological benefits in Song-Liao River Basin (SRB) from 1990 to 2020. The results show that the macro-ecosystem structure in Song-Liao River Basin remains stable, and the ecosystem service and ecological quality generally show a trend of first decline and then increase. The average growth rates of ESI and EQI were 0.6% and 0.4%, respectively, during 1990–2020. The ecological benefits of natural areas with widely distributed forest areas are higher, while those of areas with frequent human activities are lower. The prediction model based on machine learning has achieved good modeling effect, which shows that the ecological benefits of SRB will be on the rise in the future. Based on the evaluation results, we suggest that more environmental protection policies on the basis of maintaining the existing development plan should be promoted to reduce the contradiction between human and nature in the development process. For the abundant natural forests in this area, reasonable forest management should be carried out to improve the carbon-fixation capacity of vegetation, and a Methodology for managing natural forests should be constructed to make full use of the existing carbon sinks. For the new afforestation project being promoted, carbon-sink afforestation projects of CCER (Chinese Certified Emission Reduction) should be promoted to realize the synergy between economic development and environmental protection. [ABSTRACT FROM AUTHOR]

Three-body recombination reactions, in which two particles form a bound state while a third one bounces off after the collision, play significant roles in many fields, such as cold and ultracold chemistry, astrochemistry, atmospheric physics, and plasma physics. In this work, the dynamics of the recombination reaction for the N3 system over a wide temperature range (5000–20,000 K) are investigated in detail using the quasi-classical trajectory (QCT) method based on recently developed full-dimensional potential energy surfaces. The recombination products are N2(X) + N(4S) in the 14A″ state, N2(A) + N(4S) in the 24A″ state, and N2(X) + N(2D) in both the 12A″ and 22A″ states. A three-body collision recombination model involving two sets of relative translational energies and collision parameters and a time-delay parameter is adopted in the QCT calculations. The recombination process occurs after forming an intermediate with a certain lifetime, which has a great influence on the recombination probability. Recombination processes occurring through a one-step three-body collision mechanism and two distinct two-step binary collision mechanisms are found in each state. And the two-step exchange mechanism is more dominant than the two-step transfer mechanism at higher temperatures. N2(X) formed in all three related states is always the major recombination product in the temperature range from 5000 K to 20,000 K, with the relative abundance of N2(A) increasing as temperature decreases. After hyperthermal collisions, the formed N2(X/A) molecules are distributed in highly excited rotational and vibrational states, with internal energies mainly distributed near the dissociation threshold. Additionally, the rate coefficients for this three-body recombination reaction in each state are determined and exhibit a negative correlation with temperature. The dynamic insights presented in this work might be very useful to further simulate non-equilibrium dynamic processes in plasma physics involving N3 systems. [ABSTRACT FROM AUTHOR]

The access of a high proportion of photovoltaic (PV) will change the energy structure of the distribution network (DN), resulting in a series of safety operation risks. This paper proposes a two-stage PV hosting capacity (PVHC) calculation model to assess the maximum PVHC, considering the uncertainty and active management (AM). Firstly, we employ a robust optimization model to characterize the uncertainty of sources and loads in DN with PV and analyze the worst-case scenarios for PVHC. Subsequently, we construct a PVHC calculation model that takes into account AM, and convert the model into a mixed-integer second-order cone (MISOC) model using linearization techniques. Finally, we apply "heuristic optimization + CPLEX solver" to solve the model and introduce overvoltage and overcurrent indices to analyze the safety of the DN under PV limit access. Case studies are carried out on the IEEE 33-bus system and a practical case. Results show that (1) only the uncertainty that reduces the load or increases the output efficiency will affect PVHC; (2) for DN limited by overvoltage, AM can better improve PVHC; however, for DN limited by maximum transmission power, the effect of AM is low; (3) for most DN, SVC can improve PVHC, but the effect is modest. And network reconfiguration can significantly increase PVHC on the system with poor branch network, even reaching 150% of the original PVHC. [ABSTRACT FROM AUTHOR]

In order to gain an in-depth understanding of the geothermal geological characteristics and heat-forming conditions in the Tangyuan fault-depression area, this paper has carried out a series of detailed geological works, including geological surveys and geophysical explorations. Through these works, combined with the results of systematic drilling, sampling tests, and dynamic monitoring, we have studied, analyzed, and compared the relevant data to achieve a comprehensive understanding of the geological characteristics in the Tangyuan fault-depression area. During the research process, we preliminarily determined the stratigraphic structure and geological structure in this area and clarified the characteristics of the main geothermal reservoir and its burial conditions. These findings provide basic data support for our understanding of the formation and distribution of geothermal resources. At the same time, we have carried out a systematic analysis of the basic geothermal geological parameters, laying the foundation for the future calculation and evaluation of geothermal resource reserves. Through the collation and analysis of these research results, this paper not only provides a scientific basis for the development of geothermal resources in the Tangyuan fault-depression area but also provides specific references for future development prospect plans. This series of work will lay a solid foundation for further development and utilization of geothermal resources and promote the sustainable development of the regional economy. [ABSTRACT FROM AUTHOR]

Ultra-high-pressure tubular reactors are crucial pieces of equipment for polyethylene production. Long-term operation under high temperature, high pressure, and other extremely harsh conditions can lead to various defects, with circumferential cracks posing a major safety risk. Detecting cracks is challenging, particularly when they are under a protective layer of a certain thickness. This study designed a pulsed eddy current differential probe to detect circumferential cracks in ultra-high-pressure tubular reactors, with the lift-off distance acting as a protective layer. Detection models for traditional cylindrical and semi-circular excitation differential probes were established using finite element simulations. Corresponding experiments under different lift-off conditions were carried out, and the model's accuracy was verified by the consistency between the simulation results and experimental data. The distribution of the eddy current field under different conditions and the disturbances caused by cracks at various positions to the detection signal were then calculated in the simulations. The simulation results showed that the cracks significantly disturbed the eddy current field of the semi-circular excitation differential probe compared with that of the traditional cylindrical probe. The designed differential probe effectively detected circumferential cracks of specific lengths and depths using the difference in the voltage signals. The experimental results were in agreement with the simulation results, showing that the designed probe could effectively detect 20 mm-long circumferential cracks at a lift-off of 60 mm. The experimental results also show that the probe's detection coverage area in the axial direction varied with the lift-off height. The probe design and findings are valuable for detecting cracks in ultra-high-pressure tubular reactors with protective layers. [ABSTRACT FROM AUTHOR]

The spatial–temporal sampling errors arising from the differences in geographical locations and measurement times between co-located Global Navigation Satellite System (GNSS) radio occultation (RO) and radiosonde (RS) data represent systematic errors in the three-cornered hat (3CH) method. In this study, we propose a novel spatial–temporal sampling correction method to mitigate the sampling errors associated with both RO–RS and RS–model pairs. We analyze the 3CH processing chain with this new correction method in comparison to traditional approaches, utilizing Fengyun-3E (FY-3E) GNSS Occultation Sounder II (GNOS II) RO data, atmospheric models, and RS datasets from the Hailar and Xisha stations. Overall, the results demonstrate that the improved 3CH method performs better in terms of spatial–temporal sampling errors and the variances of atmospheric parameters, including refractivity, temperature, and specific humidity. Subsequently, we assess the error variances of the FY-3E GNOS II RO, RS and model atmospheric parameters in China, in particular the northern China and southern China regions, based on large ensemble datasets using the improved 3CH data processing chain. The results indicate that the FY-3E GNOS II BeiDou navigation satellite system (BDS) RO and Global Positioning System (GPS) RO show good consistency, with the average error variances of refractivity, temperature, and specific humidity being less than 1.12%2, 0.13%2, and 700%2, respectively. A comparison of the datasets from northern and southern China reveals that the error variances for refractivity are smaller in northern China, while temperature and specific humidity exhibit smaller error variances in southern China, which is attributable to the differing climatic conditions. [ABSTRACT FROM AUTHOR]

Water quality assessment is an important method for understanding the spatial-temporal variation characteristics of water quality. Therefore, the present study has been performed to evaluate the water quality for a typical plain river network area in Changzhou City, Jiangsu, China, where the river system is characterized by reciprocal flow and diverse pollution sources. The water quality samples from 2017 to 2021 were comprehensively assessed using comprehensive methods that combine the single-factor pollution index (SFPI) method with multivariate statistical analysis. Initially, statistical analyses were conducted to evaluate water quality exceedances and correlations and the SFPI method was applied to classify water quality categories. Furthermore, principal component analysis (PCA) and cluster analysis (CA) were employed to reduce the dimensionality of water quality indicators and group monitoring sections with similar characteristics. The results indicate that the overall water quality in Changzhou City is lightly polluted with a trend of improvement. The primary pollutants identified are total phosphorus (TP) and ammonia nitrogen (NH3-N). This study highlights that organic pollution, self-purification capacity, and eutrophication of river water bodies are the most significant factors affecting water quality. The sampling sites were classified into three groups (good, moderate, and poor). The water quality assessment results of this study provide a theoretical reference for water environment management and ecological protection in plain river network areas. [ABSTRACT FROM AUTHOR]

Aiming at the problem of system controller performance failure caused by improperly setting the value of each weighting coefficient of the model predictive control (MPC), a fractional-order MPC strategy with Takagi–Sugeno fuzzy optimization (T–SFO MPC) is proposed for a vehicle active suspension system. Firstly, the fractional-order model predictive control framework for active suspension systems is designed based on a 1/4 vehicle model. Then, we analyze the influence of different weighting coefficients on the suspension performance and introduce the Takagi–Sugeno fuzzy optimization theory to adaptively adjust the weighting coefficients of the fractional-order MPC controller. Finally, the system responses of the T–SFO MPC, traditional MPC, linear quadratic regulator (LQR), and passive suspension control are numerically analyzed under various road conditions. Simulation results show that suspension response with the T–SFO MPC is significantly improved compared with passive suspension control, traditional MPC control, and LQR control, and the weight coefficients of the T–SFO MPC can be adaptively adjusted according to the dynamic changes of suspension response. Compared with passive suspension, the root mean square (RMS) value of the vertical acceleration of the T–SFO MPC under various roads decreased by a maximum of 37.97%, and the RMS value of suspension dynamic deflection and tire dynamic load decreased by a maximum of 32.94% and 37.8%, respectively. These results validate that the proposed control method can achieve coordinated optimization of vehicle comfort and handling stability. [ABSTRACT FROM AUTHOR]

Simple Summary: Cattle behavior recognition is an important field in animal husbandry. It can be used to understand the health status, emotions and needs of cattle. In this paper, an accurate and lightweight behavioral multi-detection model is proposed, which is adapted to real weather conditions. An innovation in the head, neck, detection head and loss function of the model is proposed, which improves the accuracy of behavior detection in cattle, and greatly reduces the number of parameters and calculations. It not only has high accuracy in recognition tasks, but is also very friendly to edge devices. This gives breeders insight into cattle behavior, helping them to better manage their herds, improve breeding efficiency and ensure the health and welfare of their cattle. In modern animal husbandry, intelligent digital farming has become the key to improve production efficiency. This paper introduces a model based on improved YOLOv8, Cattle Behavior Recognition-YOLO (CBR-YOLO), which aims to accurately identify the behavior of cattle. We not only generate a variety of weather conditions, but also introduce multi-target detection technology to achieve comprehensive monitoring of cattle and their status. We introduce Inner-MPDIoU Loss and we have innovatively designed the Multi-Convolutional Focused Pyramid module to explore and learn in depth the detailed features of cattle in different states. Meanwhile, the Lightweight Multi-Scale Feature Fusion Detection Head module is proposed to take advantage of deep convolution, achieving a lightweight network architecture and effectively reducing redundant information. Experimental results prove that our method achieves an average accuracy of 90.2% with a reduction of 3.9 G floating-point numbers, an increase of 7.4%, significantly better than 12 kinds of SOTA object detection models. By deploying our approach on monitoring computers on farms, we expect to advance the development of automated cattle monitoring systems to improve animal welfare and farm management. [ABSTRACT FROM AUTHOR]

Simple Summary: Plant extracts contain a series of bio-active ingredients. Particularly, flavonoids exert efficient bio-activity and excellent microbial modulatory capacities, which are considered to be appropriate feed additives in husbandry production. In this study, flavonoids extracted from kudzu leaf (KL) was chosen to investigate their promotive effects on the productive performance and egg quality of layer hens. The results indicate that the kudzu leaf flavonoid (KLF) supplement significantly proliferated probiotics, such as Bifidobacterium sp. and Lactobacillus sp., which may have further interacted with hypothalamus genes, thus decreasing the deformity rate while increasing eggshell strength in the finishing phase. The findings indicate that KLF could be used as an effective feed additive for prolonging laying rates during the late-laying stage and may further improve feed efficiency, thus lowering costs. (1) Background: Improving feed efficiency and the vitality of the reproductive system in the late stage of the egg-laying period is of great significance for prolonging the egg-laying cycle and improving egg quality. In the present study, a new flavonoid, which was extracted from kudzu leaf, was chosen to investigate its effects on the productive performance and egg quality of late-laying hens. (2) Methods: A total of 360 500-day-old Hy-Line Brown layer hens were randomly divided into a control treatment group (no KLF supplementation), and groups that received 0.2%, 0.4%, 0.6%, 0.8%, and 1.0% KLF supplement treatments. Each treatment contained 6 replicates, with 10 hens in each replicate. Productive performance metrics, including the daily egg production, egg weight, the number of deformed eggs, egg quality, egg density, egg shape index, eggshell strength, yolk color, and the Haugh unit, were meticulously recorded for each replicate. Furthermore, microbial communities and hypothalamus gene expressions were investigated based on the results of the productive performance and egg quality. (3) Results: KLF supplementation significantly decreased the deformity rate while significantly increasing the eggshell strength in the finishing phase afterward (p < 0.05). Specifically, hens supplemented with 0.6% KLF possessed the lowest deformed egg rate. KLF supplementation significantly increased the relative abundances of Bifidobacterium sp., Blautia sp., Lactococcus sp., and Lactobacillus sp., while significantly decreasing Parasutterella sp. and Escherichia-Shigella sp. (p < 0.05). Furthermore, the interactive analysis showed the hypothalamus gene expression mainly interacted with probiotics, such as Bifidobacterium sp. and Lactobacillus sp., through ribosome biogenesis, nucleocytoplasmic transport, and cAMP signaling pathways. (4) Conclusions: The findings of the present study indicate that KLF supplementation significantly proliferated probiotics, such as Bifidobacterium and Lactobacillus, which may have further interacted with hypothalamus genes, thus decreasing the deformity rate while increasing eggshell strength in the finishing phase. [ABSTRACT FROM AUTHOR]

Anti-wear and anti-oxidation abilities are two key properties of lubricants that play a crucial role in ensuring long-term stable equipment operation. In this study, we aimed to develop a base oil with good anti-oxidation and anti-wear properties for use under extreme pressure. The as-prepared metallocene polyalphaolefin (mPAO) was chemically modified using the trifluoromethanesulfonic acid (TfOH) catalysis through an alkylating reaction with triphenyl phosphorothioate (TPPT). During the experiments, when the reaction temperature exceeded 70 °C or the concentration of TfOH exceeded 2.67%, the β -scission reaction in the alkylation process became significantly more pronounced. The physical and chemical properties of TPPT-modified mPAO (T-mPAO) were evaluated by nuclear magnetic resonance spectroscopy, Fourier trans-form infrared spectroscopy, gel–permeation chromatography, and ASTM standards. T-mPAO showed significantly improved antioxidant capacity, with the initial oxidation temperature increasing by 32 °C compared to the base oil, and it exhibited the slowest increase in acid number in the 96-h oven oxidation test. The tribological tests showed that T-mPAO had the lowest friction coefficient, wear track, and wear rate (72.7% lower than that of mPAO) as well as the highest PB (238 kg) and PD (250 kg) among all tested samples. Compared to mPAO, the average friction coefficient of TPPT-modified mPAO in the four-ball friction test was reduced by 30.5%, and by 16.4% in the TE77 reciprocating friction test. Based on the experimental results, T-mPAO had strong anti-oxidation ability and excellent lubricating performance.The successful synthesis of multifunctional mPAO has enabled lubricant base oil additization, making it possible to use it in more demanding work scenarios, greatly broadening its application scope and making lubricant formulation blending more flexible. [ABSTRACT FROM AUTHOR]

In the present work, the Q345B low-alloy steel with different contents and ER309L stainless steel were melted together to obtain new alloys. The aim was to design the composition of weld metal (Q345B low-alloy steel as the base material and ER309L welding wire as the filler material) and improve the corrosion resistance of the weld metal. During the welding process, the composition of the weld metal was controlled to match the new alloys by changing the welding heat input. A relationship curve between fusion ration and welding heat input was obtained. The research focused on analyzing the effect of mixed-smelting ratio between Q345B and ER309L and welding heat input on the microscopic structure and corrosion performance of the prepared samples. The results show that the melted alloys containing 20% to 30% Q345B consist of a ferrite (δ) phase and austenite (A) phase, the samples containing 45% to 50% Q345B consist of a martensite (M) phase and austenite (A) phase, and the sample containing 40% Q345B consists of a martensite (M) phase, ferrite (δ) phase, and austenite (A) phase. As the mixed-smelting ratio of Q345B/ER309L increased, the corrosion resistance of samples decreased gradually. For the weld metal, the fusion ration between Q345B base material and ER309L welding wire increases with the welding heat input. When the heat input changed from 0.645 kJ/mm to 2.860 kJ/mm, the composition of the weld metal was consistent with the melted alloys containing 20–45% Q345B. The microstructure and corrosion resistance of the weld metal could be designed by the melting means, which has important guiding significance for engineering applications. [ABSTRACT FROM AUTHOR]

Carotenoids are tetraterpene compounds acting as precursors to vitamin A, with functions that include protecting eyesight, enhancing immunity, promoting cell growth and differentiation, and providing antioxidative benefits. Lycopene, β-carotene, and astaxanthin are particularly critical for health and have diverse applications in food, health products, and medicine. However, natural carotenoids are encased within cell structures, necessitating mechanical methods to disrupt the cell wall for their extraction and purification—a process often influenced by environmental conditions. Thus, improving the efficiency of carotenoid extraction from natural resources is of great interest. This review delves into the research progress made on the extraction processes, structures, and biological functions of carotenoids, focusing on lycopene, β-carotene, and astaxanthin. Traditional extraction methods primarily involve organic solvent-assisted mechanical crushing. With deeper research and technological advancements, more environmentally friendly solvents, advanced machinery, and suitable methods are being employed to enhance the extraction and purification of carotenoids. These improvements have significantly increased extraction efficiency, reduced preparation time, and lowered production costs, laying the groundwork for new carotenoid product developments. [ABSTRACT FROM AUTHOR]

Treatment of articular cartilage remains a great challenge due to its limited self-repair capability. In tissue engineering, a scaffold with both mechanical strength and regenerative capacity has been highly desired. This study developed a double-network scaffold based on natural biomaterials of silk fibroin (SF) and methacrylated hyaluronic acid (MAHA) using three-dimensional (3D) printing technology. Structural and mechanical characteristics of the scaffold was first investigated. To enhance its ability of recruiting endogenous bone marrow mesenchymal stem cells (BMSCs), the scaffold was conjugated with a proven BMSC-specific-affinity peptide E7, and its biocompatibility and capacity of cell recruitment were assessed in vitro. Animal experiments were conducted to evaluate cartilage regeneration after transplantation of the described scaffolds. The SF/HA scaffolds exhibited a hierarchical macro-microporous structure with ideal mechanical properties, and offered a 3D spatial microenvironment for cell migration and proliferation. In vitro experiments demonstrated excellent biocompatibility of the scaffolds to support BMSCs proliferation, differentiation, and extracellular matrix production. In vivo, superior capacity of cartilage regeneration was displayed by the SF/MAHA + E7 scaffold as compared with microfracture and unconjugated SF/MAHA scaffold based on macroscopic, histologic and imaging evaluation. In conclusion, this structurally and functionally optimized SF/MAHA + E7 scaffold may provide a promising approach to repair articular cartilage lesions in situ. [ABSTRACT FROM AUTHOR]

Potatoes are typically seeded as tubers, and their slow sprouting significantly impacts production. Therefore, the effects of polyacrylamide (20 g·L−1, 30 g·L−1, and 40 g·L−1) as a seed potato dressing on sprouting, seedling growth, and biomass were investigated. The phytohormone content, respiratory intensity, and starch metabolism enzyme activity were analyzed to elucidate the physiological mechanisms involved. The sprouting rate significantly increased after 20 g·L−1 and 30 g·L−1 treatments by 40.63% and 15.63%, respectively. The sprouting energy was the highest (52.0%) at 20 g·L−1, 7.67 times higher than the control. The 20 g·L−1 and 30 g·L−1 treatments also promoted emergence and growth, with the emergence rate increasing by 18.18% and 27.27% and growth increasing by over 8.1% and 11.9%, respectively. These effects were related to changes in phytohormone content and accelerated starch conversion. After treatment, the auxin and cytokinin contents in the apical buds increased significantly at the germination initiation stage, and during the germination and vigorous growth phases, the auxin, cytokinin, and gibberellin contents increased. Polyacrylamide treatment activated α-amylase and promoted starch degradation, increasing soluble sugar content to provide nutrients and energy for sprouting. This study provides a promising approach for promoting potato tuber sprouting and seedling growth. [ABSTRACT FROM AUTHOR]

Biogeochemical redox cycling of iron (Fe) essentially governs various geochemical processes in nature. However, the mechanistic underpinnings of Fe-redox cycling in deep-sea sediments remain poorly understood, due to the limited access to the deep-sea environment. Here, abyssal sediment collected from a depth of 5800 m in the Pacific Ocean was characterized for its elemental, mineralogical, and biological properties. The sedimentary environment was determined to be oligotrophic with limited nutrition, yet contained a considerable amount of trace elements. Fe-redox reactions in sediment progressed through an initial lag phase, followed by a fast Fe(II) reduction and an extended period of Fe(III) oxidation before achieving equilibrium after 58 days. The presence of an external H2 electron donor significantly increased the extent of Fe(III) bio-reduction by 7.73% relative to an amendment-free control under high pressure of 58 MPa. A similar enhancement of 11.20% was observed following lactate amendment under atmospheric pressure. Fe(II) bio-oxidation occurred after 16 days' anaerobic culturing, coupled with nitrate reduction. During Fe bio-redox reactions, microbial community composition was significantly shaped by the presence/absence of an electron donor, while the hydrostatic pressure levels were the controlling factor. Shewanella spp. emerged as the primary Fe(III)-reducing microorganisms, and were stimulated by supplemented lactate. Marinobacter hydrocarbonoclasticus was the predominant Fe(II)-oxidizing microorganism across all conditions. Our findings illustrate continuous Fe-redox reactions occurring in the deep-sea environment, with coexisting Fe-redox microorganisms determining the oscillation of Fe valence states within the abyssal sediment. [ABSTRACT FROM AUTHOR]

In order to provide a convenient and fast calculation method, the equivalent circuit of a novel stacked piezoelectric cymbal vibrator is studied. The equivalent circuit model of the piezoelectric stack is derived by combining the equivalent circuit models of the thin piezoelectric disk and electrode. The equivalent circuit of the cymbal structure is then derived. The equivalent circuit model of the stacked piezoelectric cymbal vibrator is further proposed. The output axial displacements and output forces of the cymbal vibrator under different excitation voltages are investigated using the equivalent circuit model. The effectiveness of the equivalent circuit has been verified by comparing it with the finite element method. Furthermore, the equivalent circuit method has a much faster calculation speed than the finite element method. [ABSTRACT FROM AUTHOR]