In order to reduce the risk of grid transient voltage instability brought about by the new energy and system dynamic loads and the increasing proportion of new energy access, this paper proposes a differentiated dynamic reactive power compensation configuration method for suppressing transient voltage dip instability. The method first establishes a dynamic reactive power device configuration index system based on a multi-binary table, and then establishes a differentiated dynamic reactive power compensation device configuration model based on the node instability risk characteristics by combining with the regional division of system transient voltage instability risk. The model takes the investment cost and suppression effect as the optimization objectives, and realizes differentiated dynamic reactive power compensation by flexibly adjusting the optimization weights of economic benefits and reactive power compensation effects in the configuration process; Compared with the traditional compensation methods, differentiated compensation can significantly improve the economic benefits of reactive power compensation configuration. Finally, taking the IEEE39 node test system as an example, the improved TLBO algorithm is used to solve the model, which verifies the accuracy and effectiveness of the method proposed in this paper.

The epidemic of Coronavirus Disease 2019 (Covid-19) has brought many changes to people's life. This study aims to analysis Chinese people's psychological change and life after quarantining Wuhan and explore the influencing factors. Based on data from a web-survey after quarantining Wuhan (N=3268), the principal-component-analysis (PCA), multiple-linear-regression (MLR), propensity-score-matching (PSM) were used to explore the psychological change of people in China and the influencing factors. 83.3% of the respondents said that the impact of the epidemic on their life had increased after quarantining Wuhan. A considerable proportion of people's anxiety increased, being reflected in negative emotion, behavioral response and physiological response. The proportion of people who said their anxiety had increased in Wuhan was higher than that in other regions (p <0.05). The anxiety of people who were in medical isolation increased less than those who were not (p <0.05). All three aspects of people’s anxiety were positively related with time of medical isolation and degree of the attention on the epidemic (p＜0.05) except the effect of attention degree on the physiological response (p＝0.06). The measure of medical isolation at home should be advocated. Yet people should reduce the concern for the epidemic while paying attention to self-protection.

Existing studies often lack a systematic solution for Unmanned Aerial Vehicles (UAV) inspection system, which hinders their widespread application in crack detection. To enhance its practicality, this study proposes a formal and systematic framework for UAV inspection systems, specifically designed for automatic crack detection and pavement distress evaluation. The framework integrates UAV data acquisition, deep learning based crack identification, and road damage assessment in a comprehensive and orderly manner. Firstly, the flight control strategy is presented, and road crack data is collected using the DJI Mini 2 UAV imagery, establishing a high-quality UAV crack image datasets with ground truth information. Secondly, a validation and comparison study is conducted to enhance the automatic crack detection capability and provide an appropriate deployment scheme for UAV inspection systems. This study develops automatic crack detection models based on mainstream deep learning algorithms(namely, Faster-RCNN, YOLOv5s, YOLOv7-tiny, and YOLOv8s) in urban road scenarios. The results demonstrate that the Faster-RCNN algorithm achieves the highest accuracy and is suitable for online data collection of UAV and offline inspection at work stations. Meanwhile, the YOLO models, while slightly lower in accuracy, are the fastest algorithm and are suitable for lightweight deployment of UAV with online collection and real-time inspection. Quantitative measurement methods for road cracks are presented to assess road damage, which will enhance the application of UAV inspection systems and provide factual evidence for maintenance decisions made by road authorities.

Mulberry is an economically significant crop for the sericulture industry worldwide. Stresses such as drought exposure have a significant influence on plant survival. Metabolome directly reflects plant physiological status; thus, a way to assess this impact is to perform a global metabolomic analysis. This study investigated the effect of drought stress on mulberry Yu-711 metabolic balance using a liquid chromatography-mass spectrometry (LC-MS) based on an untargeted metabolomic approach. For this objective, Yu-711 leaves were subjected to two weeks of drought stress treatment and control without drought stress. Multivariate and univariate statistical analyses highlighted numerous differentially-accumulated metabolic elements as a function of time and treatment. Drought stress led to a more differentiated metabolites response than the control. We found that the levels of total lipids and galactolipids, and phospholipids (PC, PA, PE) were significantly altered, producing 48% of the total differentially expressed metabolites. Fatty acyls were the most abundant lipids expressed and decreased considerably by 73.6%. Prenol lipids class of lipids increased in drought leaves. Other classes of metabolites, including polyphenols( flavonoids and cinnamic acid), organic acid (amino acids), carbohydrates, benzenoids, and organoheterocyclic, all had a dynamic trend in response to the drought stress. However, their levels under drought stress generally decreased significantly compared to the control. These results provide an overview of the metabolic profile of the mulberry plant through differentially-accumulated compounds and provide a better understanding of global plant metabolic changes in defense mechanisms.

Purpose: The purpose of this study is to further explore how e-loyalty and E-marketing influences E-trust and satisfy the demand by offering fresh perspectives based on research as well as emphasis on the factors influencing the E-trust such as culture as a mediator. This study not only contributed theoretically but also presented practical implementations. Design/methodology/approach: Online survey was used to obtain data by focusing the Hospitality sector (Hotel Industry) and verifying the conceptual framework. Data was collected in multiple time lags. Findings: Findings showed that the E-trust influenced by E-loyalty and E-Marketing. E-trust comes from the previous experiences, e-loyalty and e-marketing. Further, some trends such as culture influenced the e-trust. Research limitation/implications: The present study is quite suitable for those Researchers interested in learning more about the effects of E-loyalty and E-marketing on user E-trust and how to mitigate cultural influences can benefit from the current study. This research also has implications for those who wish to improve market allure and survival in digital world. This study focused on the hospitality sector (Hotel Industry) in China; however, the sector and geography could be altered to suit the needs of the study's participants. Practical implications: The present study delivers the practical guidelines which are quiet suitable for understanding the formation of E-loyalty, E-marketing, and E-trust through which specific E-marketing strategy can be designed to deal with the consumer’s E-loyalty and their expectations as per their Cultural perspective. At some particular regions/countries, cultural trends are more important than practical market. This research study practically showed that how culture changed the consumer set of mind. Originality/value: The relationship between E-loyalty, E-marketing, E-trust, specifically with the cultural influence in digital market has been the subject of few research.

(1) Background: AI technology has been deeply applied to online shopping platform to provide more accurate and personalized services for consumers. It is of great significance to study the different functional experience of AI for consumers to improve the current application status of AI technology.(2)Method: Based on the "S-O-R" model, this study divided the AI technology expe-rienced by the consumers of online shopping platform into accuracy, insight and interaction experience. Takes the perceived value as the mediating variable from the prospect of perceived utility value and perceived hedonic value. This article use empirical research method to analyze the effect of three dimensions of online shopping AI experience to research the internal influence mechanism of consumers purchase intention. (3) Results:① The accuracy, insight and interaction experience of AI marketing technology have a significant positive impact on consumers' per-ceived utility value and hedonic value respectively; ②Both of the perceived utility value and perceived hedonic value obtained by AI technology experience can promote the formation of consumers' purchase intention; ③ The perceived hedonic value was better than perceived utility value to promote the consumers' purchase intention; ④The results of multi group analysis show that some younger and less experiences consumers groups prefer the pleasure experience such as shopping desire stimulation, shopping process relaxation and pleasure that AI marketing brought. However, utilitarian value cannot promote this kind of consumers' purchase intention. (4) Con-clusions: Perceived utility value and perceived hedonic value can be the intermediary between AI technology and consumers' purchase intention.

Objective: To visualize and analyze the published literature on diabetes and pyroptosis based on a bibliometric approach, so as to provide a comprehensive picture of the hot research directions and dynamic progress in this field. Methods: This study was based on the web of science core collection database to conduct a comprehensive search of the published literature in the field of diabetes and Pyroptosis from January 1985 to August 2022, including the published research literature in this field, as well as a visual analysis of the number of citations, year of publication, journal, author, research institution, country, and research topic. Results: A total of 139 literature on research related to diabetes and cellular scorch from 2011 to 2022 were retrieved, with a total of 3009 citations and a maximum of 255 citations for a single article, which had a first authorSchmid-Burgk, JL The first author of this article is from Germany; among 20 publishing countries, China leads with 100 articles; among 222 publishing institutions, Harbin Medical University leads with 18 articles and 184 citations; among 980 authors, Chen, X from China tops the list of high-impact authors with 5 articles and 29 citations; Among the 98 journals, "CELL DEATH DISEASE" ranked first in both volume and high impact journals with 4 articles and 29 citations; among 349 keywords, "pyroptosis" ranked first with a cumulative frequency of 65 times. The cluster analysis was divided into three categories, chronic complications of diabetes and pyroptosis (67 articles), diabetes and pyroptosis (60 articles), and diabetes combined with other diseases and pyroptosis (12 articles), and the number of articles related to diabetes and its chronic complications increased rapidly from 2019, among which, diabetic cardiomyopathy (27 articles) had the highest number of articles. Conclusions: Based on a comprehensive analysis of published literature in the field of diabetes and pyroptosis from 2011-2022, this study achieved a visual analysis of studies with significant and outstanding contributions to the field, thus framing a picture showing the development and changes in the field. At the same time, this study provides research information and direction for clinicians and investigators to conduct diabetes and pyroptosis related research in the future.

The circadian clock regulates daily changes in behavioral, endocrine and metabolic activities in mammals. Circadian rhythms in cellular physiology are significantly affected by aging. In particular, we previously found that aging has profound impact on daily rhythms in mitochondrial functions, leading to increased oxidative stress. However, this is unlikely due to malfunction of molecular clocks in the suprachiasmatic nucleus or peripheral tissues, as robust clock oscillations are observed therein in old animals. Nonetheless, aging induces changes in gene expression levels and rhythms in various peripheral and probably central tissues. In this article, we review findings on the roles of the circadian clock and aging in regulating mitochondrial rhythms and redox homeostasis. Chronic sterile inflammation is implicated in mitochondrial dysfunction and increased oxidative stress during aging. In particular, upregulation of CD38 by inflammatory response can disturb mitochondrial functions in multiple ways.

Multidisciplinary Design Optimization (MDO) is the most active field in the design of current complex system engineering, which is possessed with such two difficulties as subsystem information exchange and analytical and computational complexity of systems. Therefore, an improved collaborative optimization algorithm based on ANN (artificial neural network) response surface was proposed dependent on the consistency constraint algorithm and concurrent subspace algorithm. As an optimization method with secondary structure, it satisfied only local constraints in discipline layer, but provided a coordinated mechanism for interdisciplinary conflict in system layer. Finally, it was applied in the multidisciplinary design optimization of autonomous underwater vehicle (AUV). As shown from the result, the MDO convergence stability and reliability of low resistance, low noise and high maneuvering performance of the AUV shape can be ensured by the improved collaborative optimization algorithm, thus verifying the effectiveness of the algorithm.

The complex network is an abstract modeing of complex systems in the real world, which plays an important role in analyzing the function of complex systems. Community detection is an important tool for analyzing network structure. In this paper, we propose a new community detection algorithm (RWBS) based on different seed nodes aims to understand the community structure of the network, which provides a new idea for the allocation of resources in the network. RWBS provides a new centrality metric ($MC$) to calculate node importance, which calculates the ranking of nodes as seed nodes. Furthermore, two algorithms are proposed for determining seed nodes on networks with and without ground-truth, respectively. We set the number of steps for the random walk to 6 according to the six degrees of separation theory to reduce the running time of the algorithm. Since some traditional community detection algorithms may detect smaller communities, e.g., two nodes become one community, this may make the resource allocation unreasonable. Therefore, modularity ($ Q $) is chosen as the optimization function to combine communities, which can improve the quality of detected communities. Final experimental results on real-world and synthetic networks show that the RWBS algorithm can effectively detect communities.

Cell autonomous circadian oscillation is present in central and various peripheral tissues. The intrinsic tissue clock and various extrinsic cues drive gene expression rhythms. Transcription regulation is thought to be the main driving force for gene rhythms. However, how transcription rhythms arise remains to be fully characterized, due to the fact that transcription is regulated at multiple steps. In particular, Pol II recruitment and pause release are two critical regulatory steps that determine the status of Pol II pausing. Recently, we showed that Pol II pausing exhibits genomewide changes during daily transcription in mouse liver. In this article, we review historical as well as recent findings on the regulation of transcription rhythms. We also discuss the possible mechanisms for daily changes in Pol II pausing and the critical involvement of Pol II pausing regulation in generating rhythmic transcription output.

An inverse aeroacoustic problem for a helicopter rotor combined with aerodynamic constraint is proposed based on Ffowcs Williams and Hawkings equation in subsonic. The rotor noise includes thickness noise and loading noise when quadrupole noise is neglected. Thickness noise is related to geometry and motion conditions. Loading noise is related to the pressure on the wall. Therefore, the equation between pressure on the wall and far-field noise can be established, thus the pressure on the wall can be obtained by solving this equation. Since this equation is an ill-posed, the singular value decomposition combined with the regulation method is applied and the aerodynamic constraint is taken into account. The direct noise prediction is verify firstly and then the inverse problem is solved. The reconstruction pressure is compared to the input data. The result is in good agreement with the input value. At the same time, the influence of interference noise is also considered. Under low signal-to-noise ratio, the reconstruction result is also reasonable.

(1) Background: After the discovery and application of Chlamydomonas reinhardtii channelrhodopsins, the optogenetic toolbox has been greatly expanded with engineered and newly discovered natural channelrhodopsins. However, channelrhodopsins of higher Ca2+ conductance or more specific ion permeability are still in demand. (2) Methods: In this study, we mutated the conserved aspartate of the transmembrane helix 4 (TM4) within Chronos (Stigeoclonium helveticum channelrhodopsin = ShChR) and PsChR (Platymonas subcordiformis channelrhodopsin) and compared them with published ChR2 (C. reinhardtii channelrhodopsin-2) aspartate mutants. (3) Results: We found that the ChR2 D156H mutant (XXM) showed enhanced Na+ and Ca2+ conductance, which was not noticed before, while the D156C mutation (XXL) influenced the Na+ and Ca2+ conductance only slightly. Furthermore, the D173H mutant of PsChR showed a much improved photocurrent, compared to wildtype, and even higher Na+ selectivity to H+ than XXM. PsChR D173H also showed a strongly enhanced Ca2+ conductance, more than 2-fold that of the calcium translocating L132C of ChR2 (CatCh). (4) Conclusions: We found that mutating the aspartate of the TM4 to histidine influences the ion selectivity of channelrhodopsins. With the large photocurrent and enhanced Na+ selectivity and Ca2+ conductance, XXM and PsChR D139H are promising powerful optogenetic tools, especially for Ca2+ manipulation.

Influenced by the quasi-stationary Mei-yu front and the development of mesoscale low vortices on the Mei-yu front, a torrential rain event occurred in Suzhou on July 6, 2020. The 24-hour rainfall recorded by the automatic station exceeded 200 millimeters, with the highest hourly intensity surpassing 70 millimeters, accompanied by thunderstorms and strong winds. This heavy precipitation process was characterized by suddenness, extremity, long duration, high precipitation efficiency, and backward propagation. Using various data sources such as the European ERA5 reanalysis data, ground-based automatic stations, sounding, Doppler weather radar, and wind profile radar, this paper analyzed in detail the circulation characteristics and radar echo structures of this torrential rain event, and further studied the triggering, feature evolution, and maintenance mechanisms of the heavy precipitation.The results show: (1) The continuously strengthening low-level jet stream propagates downward forming an ultra-low-level jet stream. Heavy precipitation is located on the left front side of the jet exit area, where strong convergence and lifting in the boundary layer overlap with the ascending branch of the secondary circulation above the shear line, resulting in heavy precipitation. (2) A supercell storm with intense precipitation produced this heavy rainfall event, characterized by a low centroid of strong echo; echo-free vault, bounded weak echo region, and other supercell structural features. During this event, the high reflectivity factor areas corresponded to high KDP value areas, indicating a large amount of liquid water content. Vertically, the KDP column can track the rainwater mixing ratio well, and its location corresponds to the vicinity of the short-term heavy precipitation occurrence. The high KDP value area mainly consists of numerous precipitation particles, and the vertical vortex wind field structure causes rapid growth of precipitation particles through continuous rolling. Furthermore, it can be found through correlation coefficients (CC) that there are always high-value areas for CC since they correspond to areas of intense precipitation. (3) Continuous triggering of mesoscale convective cloud clusters on the east-west ground convergence line leads to new development and forms a "train effect." Strong frontogenesis in both horizontal and vertical directions triggers and sustains this heavy precipitation event. The significant increase in liquid water and water vapor density has indicative significance for the occurrence of heavy precipitation.

In this paper, the methods and their analysis for estimating the location of three dimension (3-D) single source buried in lossy medium are presented with uniform circular array (UCA). The mathematical model of the signal in the lossy medium is proposed. Using location information in the covariance matrix obtained by sensors’ output, the equations of the source location (azimuth angle, elevation angle and range) are obtained. The phase and amplitude of the covariance matrix function are used to process these equations respectively. Then, the phase and amplitude of the covariance matrix function are used to process the source localization in the conductive medium together. By analyzing the characteristics of the proposed methods and MUSIC method, the computational complexity and the valid range of these methods are given. From the results, whether the loss is known, we can choose the appropriate method to process the issues (localization in lossless medium or lossy medium).

Wearable touch sensors, which can convert force or pressure signals into quantitative electronic signals, have emerged as an essential smart sensing devices and played an important role in various cutting-edge fields, including wearable health monitoring, soft robots, electronic skin, artificial prosthetics, AR/VR, and the Internet of Things. Flexible touch sensors have made significant advancements, while construction of novel touch sensors via mimicking the unique properties of biological materials and biogenetic structures always remains a hot research topic and significant technological pathway. This review provides a comprehensive summary of the research status of wearable touch sensors constructed by imitating the material and structural characteristics in nature, and also summarizes the scientific challenges and development tendency of this aspect. Firstly, the research status for constructing flexible touch sensors based on biomimetic materials is summarized, including hydrogel materials, self-healing materials, and other bioinspired or biomimetic materials with extraordinary properties. Then, design and fabrication of flexible touch sensors based on bionic structures for performance enhancement are fully discussed. These bionic structures include special structures in plants, special structures insects/animal, and special structures in human body. Moreover, a summary of the current issues and future prospects for developing wearable sensors based on bioinspired materials and structures is discussed.

Road cracks significantly affect the serviceability and safety of roadways, especially in mountainous terrain. Traditional inspection methods, such as manual detection, are excessively time-consuming, labor-intensive, and inefficient. Additionally, multi-function detection vehicles equipped with various sensors are expensive and not suitable for mountainous roads due to poor conditions. To address these challenges, this study proposes a customized Unmanned Aerial Vehicles (UAV) inspection system designed for automatic crack detection. The system focuses on enhancing autonomous capabilities in mountainous terrains by incorporating embedded algorithms for route planning, autonomous navigation, and automatic crack detection. The slide window method is proposed to enhance the autonomous navigation of UAV flights by generating path planning in mountainous roads. This method compensates for GPS/IMU positioning errors, particularly in GPS-denied or GPS-drift scenarios. Moreover, the YOLOv8 algorithm is introduced to conduct autonomous crack detection from UAV imagery in the offboard module. To validate our UAV inspection system's performance, we conducted several experiments to assess its accuracy, robustness, and efficiency. The experimental results demonstrate that our UAS inspection system accurately estimates the flight trajectory along the mountainous road for autonomous navigation. Furthermore, the experimental detection results also demonstrate that the YOLOv8 algorithm achieves higher recognition accuracy compared to the YOLOv5, and YOLOv7-tiny algorithms, exceeding 3.1%,and 6.8% of mAP, respectively. In summary, the UAV inspection system proposed in this study can provide a useful tool and technological guidance for the regular inspection of mountainous roads.

Although the concept of additive manufacturing has been proposed for several decades, momentum of selective laser melting (SLM) is finally starting to build. In SLM, density and surface roughness, as the important quality indexes of SLMed parts, are dependent on the processing parameters. However, there are few studies on their collaborative optimization in SLM to obtain high relative density and low surface roughness simultaneously in the previous literature. In this work, the response surface method was adopted to study the influences of different processing parameters (laser power, scanning speed and hatch space) on density and surface roughness of 316L stainless steel parts fabricated by SLM. The statistical relationship model between processing parameters and manufacturing quality is established. A multi-objective collaborative optimization strategy considering both density and surface roughness is proposed. The experimental results show that the main effects of processing parameters on the density and surface roughness are similar. It is noted that the effects of the laser power and scanning speed on the above objective quality show highly significant, while hatch space behaves an insignificant impact. Based on the above optimization, 316L stainless steel parts with excellent surface roughness and relative density can be obtained by SLM with optimized processing parameters.

Objective: To investigate the causal relationships between intestinal microbiome biomarkers and colorectal cancer (CRC) and its subtypes. Method: The meta-analysis method was used to integrate the largest genome-wide association study data from the MiBioGen consortium (n=18,340). Single nucleotide polymorphisms (SNPs) significantly associated with intestinal microbial relative abundance were extracted as instrumental variables (IVs). Based on the Finnish database (R9 version) with 326,322 participants, the two-sample Mendelian randomization (MR) analysis was adopted to explore the causal relationships between intestinal microbes and CRC and its specific subtypes, such as colon cancer and rectal cancer. Result: A total of 3,310 SNPs were screened as IVs. The MR analysis revealed significant associations between various microbial traits and CRC, including its subtypes. Specific microbes, such as Erysipelotrichaceae, exhibited protective effects, while others, like Orato, were demonstrated as risk factors. Notably, specific biomarkers (e.g., Streptococcus thermophilus) for CRC were determined. This study provides new insights and potential targets for the pathogenesis, diagnosis, and treatment of CRC. Conclusion: Significant causal relationships exist between intestinal microbes and CRC and its pathological types. Specific microbes, such as Erysipelotrichaceae, play a protective role, whereas others, like Orato, serve as risk factors. These findings offer new insights into the pathogenesis of CRC and provide a foundation for future prevention and treatment strategies.

Doubly-fed induction generators (DFIG) find extensive application in variable-speed wind power plants, providing notable advantages such as cost-effectiveness, operational flexibility across varying speeds, and enhanced power quality. This research focuses on the control of DFIGs employed in variable-speed wind turbine configurations. A suitable mathematical model is chosen for representative systems following a comprehensive review of contemporary research. Subsequent analysis reveals the instability of the open-loop time response of the system. To address this instability, the initial approach involves the implementation of the conventional Model Predictive Controller (MPC). However, the outcomes indicate that this controller falls short of delivering satisfactory performance despite the enhanced stability. In the subsequent phase, efforts are made to mitigate the impact of wind input variability by utilizing the Kalman filter, given its effectiveness in handling high variability. Following this, a novel methodology is introduced, which combines nonlinear MPC with the Lyapunov function. This method is based on the nonlinear model of the system. By using the Lyapunov function in the nonlinear MPC structure, the stability of the designed controller is guaranteed. The simulation results conducted using MATLAB software show that the output variables of the modeled DFIG system achieve stability within a reasonable timeframe applying the input.

The soybean yield per unit area and soybean acreage are increased to boost overall soybean production as two effective solutions. There is a large area of saline soils in northeast China, where if soybeans could be grown with the help of isolated saline-tolerant rhizobia, the cultivation area of soybeans in China can be effectively expanded. Several rhizobia with different salt-, acid- and alkali-resistant characteristics were obtained in this research by isolating, identifying, and analyzing the nitrogen-fixing activities of indigenous rhizobia from different soybean planting soils, and further analyzed the host compliance between rhizobia and different soybean germplasm concerning 30 representative germplasm resources in the northeast region. Collectively, the results of the resistance study of HLNEAU2 isolated from the Shaanxi region are great references for guiding the application of rhizobia on soybeans.

Historical maps possess significant theoretical and practical value in fields such as historical geography and urban planning, making them essential tools for studying urban spatial structure. This study explores the evolution of Xi'an's urban spatial structure from the Five Dynasties (909 CE) to the late PRC period (1949 CE), using historical maps and Historical GIS (HGIS) methodologies. By integrating Space Syntax and Kernel Density Estimation (KDE) with data from The Historical Atlas of Xi'an, this research identifies key trends in the city's spatial transformation. Two distinct phases of development were observed: the simpler, centralized structure during the Five Dynasties, Northern Song, and Yuan periods, and a more complex, decentralized structure during the Ming, Qing, and PRC periods. These changes were influenced by a dynamic interplay of political, economic, cultural, and environmental factors, as well as the city's need to adapt to external military threats and internal socio-economic shifts. The study emphasizes the value of HGIS in analyzing urban historical geography and the potential it offers for both understanding past urban dynamics and informing contemporary urban planning and cultural heritage preservation efforts. The findings demonstrate how Xi'an's spatial evolution reflects broader trends in Chinese history and provides insights for future sustainable development.

Hepatic carboxylesterase 1(CES1) metabolizes many prodrugs into active ingredients or direct-acting drugs into inactive metabolites. We aim to develop a semi-physiologically based pharmacokinetic model(Semi-PBPK model) to simultaneously predict pharmacokinetics of CES1 substrates and their active metabolites in liver cirrhosis(LC) patients. Six prodrugs(enalapril, benazepril, cilazapril, temocapril, perindopril and oseltamivir) and three direct-acting drugs (flumazenil, pethidine and remimazolam) were selected. The parameters including organ blood flows, plasma binding protein concentrations, functional liver volume, hepatic enzymatic activity, glomerular filtration rate(GFR) and gastrointestinal transit rate were introduced into the simulation. Pharmacokinetic profiles of these drugs and their active metabolites were simulated in 100 virtual subjects. The developed semi-PBPK model, following validation in healthy subjects, was extrapolated to LC patients. Most of the observations are within the 5% and 95% quantile of simulations from 100 virtual patients. The estimated AUC and Cmax are within 0.5-2-fold of observation. The sensitivity analysis showed that the decreased plasma exposure of active metabolite due to the decreased CES1 was partly attenuated by the decreased GFR. Conclusion: The developed PBPK model has successfully predicted pharmacokinetics of CES1 substrates and their metabolites in healthy subjects and LC patients, which assists in tailoring dosages of CES1 substrates in LC patients.

China's economic development has shifted from high speed to high quality. This study constructs an evaluation index for China’s high-quality development utilizing a new development concept. The entropy method and cluster analysis were used to assess the level of high-quality development in China between 2015 and 2021. Kernel density estimation method was employed to explore spatiotemporal dynamics. The results reveal significant differences in the level of economic development among provinces in China; the eastern region is significantly better than the central, northeastern, and western regions. From the perspective of the sub-item evaluation, challenges with uneven, uncoordinated, and insufficient economic development exist in various Chinese provinces.

In this work, a novel single crystal (3-(4-chlorophenyl)-4,5-dihydroisoxazol-5-yl)methyl benzenesulfonate has been synthetized via a one-pot sequential strategy under sonication. A single crystal X-ray diffraction analysis was reported. In the crystal, a layer structure is generated by C—H···O and C—H···N hydrogen bonds. A Hirshfeld surface analysis indicates that the most important contributions to the crystal packing are from H···H (28.9%), H···O/O···H (26.7%) and H···C/C···H (15.8%) interactions. The optimized structure calculated using density functional theory at the B3LYP/6–311 G+(d,p) level is compared with the experimentally determined structure in the solid state. The calculated highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy gap is 4.6548 eV.

Abstract: The EMU(electric multiple units) traction motors are powered by converters. The PWM(pulse width modulation) voltage increases the voltage stress borne by the motor insulation system, making the ITSC(inter-turn short-circuit) fault more prominent. An index based on short-circuit thermal power was proposed in the article to evaluate the non-metallic ITSC faults degree. The apFFT(all phase FFT) time-shift phase difference correction with double Hanning-windows is used to calculate the fundamental frequency of the traction motor's ZSVC（zero se-quence voltage component）, the fundamental amplitudes of ZSVC and three-phase current. The five parameters are used as fault features to train the SVM (support vector machine)fault diagnosis model. The SVM hyper-parameters C and g are optimized by K-CV (K fold cross-validation) and grid search methods. The experimental verification was carried out by the EMU electric traction simulation experimental platform. According to the non-metallic degree index proposed in this article, the experimental samples were divided into three categories, normal, incipient and serious fault samples. The ITSC fault diagnosis accuracy was 100% on the training data set and 93.33 % on the test data set. There was no misclassification between normal and serious ITSC fault samples.

To describe the hysteresis nonlinearities in smart actuators, numerous models have been presented in the literature, among which the Preisach operator would be the most effective one due to its capability in capturing multi-loop or sophisticated hysteresis curves. When such an operator is coupled with uncertain nonlinear dynamics, especially in noncanonical form, it is a challenging problem to develop techniques to cancel out the hysteresis effects, and at the same time achieve asymptotic tracking performance. To resolve this problem, in this paper, we investigate the problem of iterative inverse-based adaptive control for an uncertain noncanonical nonlinear systems with unknown input Preiasch hysteresis, and a new adaptive version of the closest match algorithm is proposed to compensate for the Preisach hysteresis. With our scheme, the stability and convergence of the closed-loop system can be established. The effectiveness of the proposed control scheme is illustrated by simulation and experiment results.

Due to the global warming and dynamic changes in pathogenic virulence, leaf rust caused by Puccinia triticina has greatly expanded its epidermic region and become a severe threat to global wheat production. Genetic bases of wheat resistance to leaf rust mainly relies on the leaf rust resistance (Lr) gene or quantitative trait locus (QLr). Although these genetic loci have been insensitively studied during the last two decades, an updated overview of Lr/QLr in a genome-wide level is urgently needed. This review summarized recent progresses in genetic studies of wheat resistance to leaf rust. Wheat germplasms with great potentials in genetic improvement of resistance to leaf rust were highlighted. Key information about the genetic loci carrying Lr/QLr were summarized. A genome-wide chromosome distribution map for all the Lr/QLr was generated based on the released wheat reference genome. In conclusion, this review has provided valuable sources for both wheat breeders and researchers to understand the genetics of resistance to leaf rust in wheat.

In order to make full use of the complementarity of existing navigation systems to improve the navigation and positioning accuracy, this paper investigates the visual/INS integrated navigation system based on the factor graph optimization (FGO) algorithm. In the traditional visual/INS integrated navigation system, there is often the problem of image blurring due to the rapid change of light and shadow captured by the vision sensor and the attitude change of the carrier, which leads to the decrease of the positioning accuracy of the combined navigation system. Therefore, this paper firstly introduces Retinex algorithm and BID algorithm to carry out the design of image de-blurring method; then implements the visual/INS integrated navigation algorithm based on the factor graph optimization method; finally, the experimental scheme is designed, comparative experiments are carried out, and the researched method is verified by using the public dataset. The experimental results show that the combined navigation algorithm realized in this paper has high accuracy, and its positioning accuracy is improved by 40% compared with visual positioning.

Early diagnosis and treatment have always been highly desired in the fight against cancer, and detection of circulating tumor DNA (ctDNA) has recently been touted as highly promising for early cancer screening. Consequently, the detection of ctDNA in liquid biopsy gains much attention in the field of tumor diagnosis and treatment, which has also attracted research interest from the industry. However, traditional gene detection technology is difficult to achieve low cost, real-time and portable measurement of ctDNA. Electroanalytical biosensors have many unique advantages such as high sensitivity, high specificity, low cost and good portability. Therefore, this review aims to discuss the latest development of biosensors for minimal-invasive, rapid, and real-time ctDNA detection. Various ctDNA sensors are reviewed with respect to their choices of receptor probes, detection strategies and figures of merit. Aiming at the portable, real-time and non-destructive characteristics of biosensors, we analyze their development in the Internet of Things, point-of-care testing, big data and big health.

A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article's main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

Biological neural network (BNN) is the core brain for creature to accomplish its intelligent behaviors through unique network structure and mechanisms. It also inspires controlling human-designed autonomous agents including robots to generate more advanced intelligent behaviors by mimicking the neural control mechanism of creatures at a deeper and more interactive level. Here, we constructed a whole-brain neural network model of Caenorhabditis elegans (C. elegans), which characterizes the electrochemical processes at the level of cellular synapse. The neural network simulation integrates computational programming and visualization of neurons and synapse connections of C. elegans, containing the specific controllable circuits summarization with their dynamic characteristics within the whole network. To illustrate its particular intelligent control capability in terms of robotics, we introduce the first innovative methodology for applying the BNN model to a 12-legged robot’s movement control based on the established numerical simulation platforms. We accomplished and designed two methods and corresponding encoding processes, one involving orientation control and the other involving locomotion generation, to demonstrate the intelligent control performance of BNN. Both simulation and experiment results indicate that the robot exhibits stronger autonomy and more intelligent moving performance under the control of BNN. We then summarized the contributions for digitalizing the C. elegans’ whole-brain neural network in real-time and utilizing it to control robot in a closed loop to validate its advanced intelligence control ability in terms of a scientific robot.

Since the electro-hydraulic servo shaking table exists many nonlinear elements, such as, dead zone, friction and blacklash, its acceleration response has higher harmonics which result in acceleration harmonic distortion, when the electro-hydraulic system is excited by sinusoidal signal. For suppressing the harmonic distortion and precisely identify harmonics, a combination of the adaptive linear neural network and least mean M-estimate (ADALINE-LMM), is proposed to identify the amplitude and phase of each harmonic component. Namely, the Hampel’s three-part M-estimator is applied to provide thresholds for detecting and suppressing the error signal. Harmonic generators are used by this harmonic identification scheme to create input vectors and the value of the identified acceleration signal is subtracted from the true value of the system acceleration response to construct the criterion function. The weight vector of the ADALINE is updated iteratively by the LMM algorithm, and the amplitude and phase of each harmonic, even the results of harmonic components, can be computed directly online. The simulation and experiment are performed to validate the performance of the proposed algorithm. According to the experiment result, the above method of harmonic identification possesses great real-time performance and it has not only good convergence performance but also high identification precision.

Polyvinyl alcohol-engineering cementitious composites (PVA-ECC) has been widely applied in bridge deck repairing or widening, the common practice for doing this is that a portion of a bridge is left open to traffic while the closed portion is constructed, which expose the early age PVA-ECC to the vehicle-induced vibrations. However, whether vehicle-induced vibrations affect the tensile performance of early age PVA-ECC remains unknow. The purpose of this study was to conduct laboratory test programs on how much vehicle-induced vibrations during early ages affected the tensile performance of PVA-ECC. A self-improved device was used to simulate the vehicle-induced vibrations, and after vibrating with the designed variables, both a uniaxial tensile test and a grey correlation analysis were performed. The results indicated that: the effects of vehicle-induced vibrations on the tensile performance of early age PVA-ECC were significant, and they generally tended to be negative in this investigation. In particular, for all of the vibrated PVA-ECC specimens, the most negative age when vibrated occurred during the period between the initial set and the final set. We concluded that although vehicle-induced vibrations during the setting periods had no substantial effects on the inherent strain-hardening characteristics of PVA-ECC, the effects should not be ignored.

This review article explores the innovative application of software sensors for monitoring and controlling biosystems, emphasizing their advantage in managing the complexities of various biological processes. Biosystems—from cellular interactions to ecological dynamics—are characterized by intrinsic nonlinearity, temporal variability, and uncertainty, posing significant challenges for traditional monitoring approaches. A critical challenge highlighted is that what is typically measurable may not align with what needs to be monitored. Software sensors bridge this gap by combining hardware sensor data with advanced computational modelling techniques to indirectly infer hard-to-measure target variables, such as stress level, animal and human health indicators, and chemical soil properties. The article outlines advancements in sensor technologies and their integration into model-based monitoring and control systems, leveraging the capabilities of Internet of Things (IoT) devices, wearables, remote sensing, and smart sensors. It provides an overview of common methodologies for designing software sensors, focusing on the modelling process. The discussion contrasts hypothetico-deductive (mechanistic) models with inductive (data-driven) models, illustrating the trade-offs between model accuracy and interpretability. Specific case studies are presented, showcasing software sensor applications such as the use of Kalman filter in greenhouse control, remote detection of soil organic matter, and sound recognition algorithms for early detection of respiratory infections in animals. Key challenges in designing software sensors, including the complexity of biological systems, inherent temporal and individual variabilities, and the trade-offs between model simplicity and predictive performance, are also discussed. This article positions software sensor as remarkable tool for advancing biosystem management, driving forward the potential for sustainable practices in various sectors such as agriculture, healthcare, and environmental monitoring.

This study reports rapid hydrolysis, acylation, and lipolysis with lipase B from Candida antarctica (CalB) and nanofructosome encapsulated CalB (CalB@NF) enzymes immobilized on silica-coated magnetic nanoparticles (Si-MNPs). Enzymatic hydrolysis was confirmed for conversion to p-nitrophenol (p-NP, λex=400 nm) from p-nitrophenyl butyrate (p-NPB, λex=270 nm), and various catalytic parameters such as Km, Vmax, and Kcat were calculated from Michaelis-Menten and Lineweaver-Burk plot. Efficiency of enzymatic hydrolysis was in the order of CalB > Si-MNPs@CalB > CalB@NF > Si-MNPs@CalB@NF, and reusability was much better with the enzyme immobilized on Si-MNPs than with the native enzyme. Enzymatic acylation was confirmed by the formation of benzyl benzoate (λex=229 nm) from benzoic anhydride (λex=240 nm), and efficiency exceeded 99% in all samples. Finally, enzymatic lipolysis was confirmed by the decomposition of olive oil to fatty acid such as oleic acid (λex=230 nm) using thin-layer chromatography (TLC), column chromatography, and proton nuclear magnetic resonance (1H -NMR). The lipases immobilized on Si-MNPs have the advantage of good thermal stability and reusability and are thus applicable to a wide range of industries.

This paper presents a new semi-explicit algorithm for parameters estimation in a time-fractional generalization of dual-phase-lag heat conduction model with the Caputo fractional derivatives. It is shown that this model can be derived from a general linear constitutive relation for the heat transfer by conduction when the heat conduction relaxation kernel contains the Mittag-Leffler function. The model can be used to describe heat conduction phenomena in a material with power-law memory. The proposed algorithm of parameters estimation is based on the time integral characteristics method. The explicit representations of the thermal diffusivity and the fractional analogues of the thermal relaxation time and the thermal retardation are obtained via a Laplace transform of the temperature field and utilized in the algorithm. An implicit relation is derived for the order of fractional differentiation. In the algorithm, this relation is resolved numerically. An example illustrates the proposed technique.

The decreasing width, increasing aspect ratio RDL presents significant challenges to design for reliability (DFR) of advanced package. Therefore, this paper proposes a ML based RDL modeling and simulation method. In the method, RDL is divided into blocks and subdivided into pixels of metal percentage, and the RDL is digitalized as tensors. Then, an ANN-based surrogate model is built and trained by a subset of tensors to predict the equivalent material properties of each block. Lastly, all blocks are transformed into elements for simulations. For validation, line bending simulations were conducted on an RDL, with the reaction force as accuracy indicator. The results show that neglecting layout impact causes critical errors as substrate thins. By the method, the reaction force error is 2.81% and the layout impact can accurately be considered with 200×200 elements. For application, the TCT maximum temperature state simulation was conducted on a CPU chip. The simulation indicates that for advanced package the maximum stress more likely occurs in RDL rather than bumps, both RDL and bumps are critical impacted by layouts, and RDL stress is also impacted by vias/bumps. The proposed method precisely concerns layout impacts with little resources, presents an opportunity of efficiency improvement.

The near-infrared (NIR) organic dyes with strong ultrafast nonlinear optical (NLO) activities are of importance for various applications. However, such kinds of dyes are still scarce. In this work, we have compared the NLO properties of two NIR Aza-BODIPY derivatives, in which the strong electron-donating groups, namely 4-(N, N-dimethylamino) phenyl and 1-ethyl-1,2,3,4-tetrahydroquinoline groups, are connected with the cores of Aza-BODIPY. Z-Scan experimental results show that two Aza-BODIPY derivatives exhibit strong saturation absorption and large modulation depth under the excitation of femtosecond pulses at 800 nm. Under 1300 nm excitation, two derivatives exhibit strong nonlinear refraction. In addition, the Aza-BODIPY derivatives also display effective two-photon excited fluorescence emission in the wavelength range of 1200-1600 nm. Based on the experimental results, it is found that 1-ethyl-1,2,3,4-tetrahydroquinoline group can more effectively enhance the NLO properties of Aza-BODIPY derivatives compared with the 4-(N, N-dimethylamino) phenyl group, thus providing new possibilities for the design and development of NIR NLO materials.

Archie model is the basis of calculating oil saturation, but there are some limitations when using this model to calculate oil saturation in water-flooded layer. The main reason is that the main parameters, such as rock resistivity and formation water resistivity, are constantly changing dynamic parameters in the underground with the influence of injected water. Considering that water-flooded layers changes with injection waters, influence factors of rock resistivity and formation water resistivity of primary parameters are analyzed. Considering the dynamic data of water cut is the most reactive underground fluid characteristics of real information, combined with dynamic and static, and the “double ratio” model of later development by the same sedimentary layer is established, which realizes the inversion of rock resistivity and formation water resistivity, then modified Archie model relating to water-flooded layers of the same sedimentary explaining formation. The explanation of actual data indicates that the “double ratio” model well considers the dynamic variation of production data, which makes the inversion of the flooded rock resistivity relatively accurate, besides, the modified Archie model can accurately calculate the oil saturation of water-flooded layers with a reasonable result, which offers scientific basis for the predicting of remaining oil distribution rules.

Cadmium (Cd) contamination in rice grains is posing a significant threat to global food security. To restrict the transport of Cd in the soil-rice system, an efficient way is to use the ionomics strate-gy. Since calcium (Ca) and Cd have similar ionic radii, their uptake and translocation may be linked in multiple aspects in rice. However, the underlying antagonistic mechanisms are still not fully understood. Therefore, we first summarized the current knowledge on the physiological and molecular footprints of Cd translocation in plants and then explored the potential antagonistic points between Ca and Cd in rice, including exchange adsorption on roots, plant cell wall compo-sition, co-transporter gene expression, and transpiration inhibition. This review provides sugges-tions for the Ca/Cd interacting study in rice and introduces the ionomics research to better control the accumulation of Cd in plants.

Our results demonstrated that SWT stimulates osteoblastogenesis and increase the cell number of osteoblasts, suggesting positive regulatory effects on osteoblast differentiation. However, the effect of SWT on bone formation need further examination, since the expression of alp gene is downregulated. On the other hand, SWT appears to negatively regulate osteoclast differentiation and bone resorption, as number of osteoclasts and the expression of critical bone resorptive genes are all downregulated. Collectively, SWT might change the equilibrium of bone remodeling and increase the bone mass. Our data provided supportive evidences that this medicine formulation can be applied to treat osteoporosis or bone destructive diseases.

With prosperous development and successful application of deep learning technologies in the field of remote sensing, numerous deep-learning based methods have emerged for synthetic aperture radar (SAR) automatic target recognition (ATR) tasks over the past few years. Generally, most deep-learning based methods can achieve outstanding recognition performance in condition that an abundant of labeled samples are available to train the model. However, in real application scenarios, it is difficult and costly to acquire and to annotate abundant SAR images due to the imaging mechanism of SAR, which poses a big challenge to existing SAR ATR methods. Thereby, SAR target recognition under the situation of few-shot, where only a scarcely few of labeled samples are available, is a fundamental problem that needs to be solved. In this paper, we put forward a new method named enhanced prototypical network with customized region-aware convolution (CRCEPN) to specially tackle the few-shot SAR ATR tasks. To be specific, We first develop a feature extraction network based on a customized and region-aware convolution, which can adaptively adjust convolutional kernels and their receptive fields according to each SAR image’s own characteristics as well as the semantical similarity among spatial regions, thus augmenting its capability to extract more informative and discriminative features. To achieve accurate and robust target identity prediction under the few-shot condition, we then propose an enhanced prototypical network which can improve the representation ability of the class prototype by properly making use of training and test samples together, thus effectively raising the classification accuracy. Meanwhile, a new hybrid loss is designed to learn a feature space with both inter-class separability and intra-class tightness as much as possible, which can further upgrade the recognition performance of the proposed method. Experiments performed on the moving and stationary target acquisition and recognition (MSTAR) dataset and the OpenSARShip dataset demonstrate that the proposed method is competitive with some state-of-the-art methods for few-shot SAR ATR tasks.

Smart agriculture is a new way of farming that uses advanced technology. It makes a significant contribution to improving the efficiency and productivity of farming practices. Systems that use drones to monitor pests and spray pesticides greatly reduce the burden on farmers. In addition, remote sensing technology facilitates the monitoring of crop growth conditions and the early detection of diseases and pests. However, the high cost of equipment to communicate sensor data is preventing farmers from adopting sensing systems. As a result, many studies have been conducted to make the sensing system available at a low cost. Nevertheless, many farmers have not yet adopted them. Therefore, this paper proposes an agricultural sensor network system using drones and optical camera communication (OCC). The proposed system aims to achieve high-density farm sensing at low cost. The proposed system uses OCC as the communication method for sensor data. Low cost light sources such as LED panels can be used as transmitters. In addition, existing agricultural drones equipped with cameras can be used as receivers. We also propose a trajectory control algorithm for the receiving drone to efficiently collect the sensor data. The proposed system is suitable for deploying sensor networks in areas with underdeveloped infrastructure and radio silence. In this paper, we conducted a preliminary experiment at a leaf mustard farm in Kamitonda-cho, Wakayama to demonstrate the effectiveness of the proposed system using a Mavic 2 Pro drone, launched by DJI Co., Ltd.

The integrated stress response (ISR) is an adaptational signaling pathway that is induced in response to different stimuli, such as accumulation of unfolded and misfolded protein, hypoxia, amino acid deprivation, viral infection and ultraviolet light. It has been known that viral infection can activate ISR, but the role of ISR during viral infection is still unclear. In some cases, ISR is a protective mechanism of host cell against infection with virus whilst ISR may be hijacked by viruses for facilitating its replication. In this review, we highlighted recent advances on induction of ISR upon viral infection and the downstream responses involved such as autophagy, apoptosis, formation of stress granules and innate immunity response. We then discussed the molecular mechanism of ISR regulating viral replication and how viruses antagonize this cellular stress response resulting from ISR.

Abstract In order to solve the problem that it is difficult to obtain the accurate trigger signal moment when using the time difference of UAV flight acoustic signals collected by acoustic sensors arranged in advance to locate the position of UAVs when they cannot be tracked by radar and are difficult to be observed by the human eye, an acoustic source localisation method with improved empirical modal decomposition (REMD) under an adaptive frequency window is proposed. Firstly, the collected UAV flight signals are smoothed and filtered, then the robust empirical modal decomposition (REMD) is used for IMF modal decomposition and spectral analysis of the collected signals, and a panning frequency window with variable bandwidth is introduced for corresponding frequency locking and extracting the IMFs; the GWO optimisation is used and the sliding metrics are set to determine the position of the panning frequency window automatically; finally, the extracted Finally, the extracted IMF components are reconstructed according to the criterion, and the trigger signal moments in the reconstructed IMF components are resolved and recorded, and the algorithm is used to calculate the difference between the reception moments of different sensors; for the traditional sound source localisation algorithms with a small detection range, which are prone to fall into the no-solution or false-solution, i.e., unable to achieve the localisation, a weighted least-squares-based Chan-Taylor algorithm is proposed for the localisation computation, and a weighted least-squares algorithm is proposed for the localisation computation, through the Inputting the sensor delay parameter and solving the linear equation system to get the target position information; finally, this paper verifies the robustness and performance of the design method with simulated and actual signals. The results show that the maximum positioning error is no more than 5% in an area with a side length of 15m in the measurement area. With the improved accuracy of time delay estimation, the positioning simulation results meet the positioning requirements even though the positioning error is further expanded when the measurement area is further expanded.

Reverse water gas shift reaction (RWGS) is an important process which plays a vital role in many CO2 utilization related reactions. Noble metals are the most active catalysts in RWGS, but the high price and low reserve strangled their applications. In the present work, we reported a non-transition-metal MgAl2O4 catalyst which showed outstanding activity and stability at high temperatures in the RWGS reaction and improved performance after doping of single atomic Nin+. The catalyst can obtain 46% of CO2 conversion in durability test of 75 h at 800 °C under high weight hourly space velocities (225 000 ml g-1 h-1). The adsorption sites, possible reaction route, and effects of Nin+ single atoms on the (111) surface of MgAl2O4 for RWGS were investigated by in situ DRIFTS and DFT calculations. The results indicated that the rate determining reaction step of RWGS on MgAl2O4 and Ni (SA)/MgAl2O4 were both the reaction of OH* + H* → H2O* + *, but the energy barrier was significantly reduced after introducing single atomic Nin+. Nin+ atoms can increase the hydroxyl coverage on the surface of catalyst and Al3+ sites near the Nin+ ion are considered as the predominant active sites for RWGS reactions.

A dynamic impact test was performed on as-rolled AZ31 alloy with gradient microstructure under various strains. The microstructural evolution and mechanical properties were systematically investigated. As the strain rate gradually increases, an increasing number of twins are formed, facilitating dynamic recrystallization (DRX), and the mechanical properties are also gradually improved as well. The microstructure becomes heterogeneous at higher strain rates, but the peak stress decreases. The impact process results in significantly higher performance due to microstructural refinement, work hardening by dislocations and precipitates. In addition, both the adiabatic shear band and the adjacent crack experience a temperature rise that exceeds the recrystallization temperature of the alloy. This observation also explains the presence of ultrafine recrystallized grains within the adiabatic shear band and the appearance of molten metal around the crack.

Objectives: Stress urinary incontinence (SUI) negatively affects the quality of life and sexual function in women. This study aimed to evaluate the efficacy of radiofrequency (RF) therapy in reducing SUI symptoms and its impact on sexual function. Methods: Thirty-four women with SUI were enrolled and underwent a single RF treatment session using the Viveve® System (Viveve Medical Inc., USA) with parameters of 90 J/cm² and 220 pulses per hour. Assessments at baseline and 6 months post-treatment included perineal ultrasound and personal interviews to evaluate lower urinary tract symptoms and sexual function. Urodynamic studies, voiding diaries, and questionnaires such as the Female Sexual Function Index (FSFI), Overactive Bladder Symp-tom Score (OABSS), Urogenital Distress Inventory-6 (UDI-6), Incontinence Impact Question-naire-7 (IIQ-7), and International Consultation on Incontinence Questionnaire-Short Form (ICIQ-SF) measured outcomes. Results: RF therapy significantly improved sexual function, with higher FSFI scores in all domains except pain at 6 months. SUI symptoms were significantly re-duced, as indicated by improved scores on OABSS, UDI-6, IIQ-7, and ICIQ-SF, alongside better voiding diary results. Anatomical changes included reduced bladder neck mobility, decreased vaginal width, and a reduced rotation angle of the proximal urethra. Conclusions: RF therapy is effective and safe for treating mild to moderate SUI and enhances sexual function, potentially due to changes in vaginal topography. These results suggest RF therapy as a viable non-surgical op-tion for managing SUI and improving sexual health.

Vegetation has a significant influence on velocity distribution and turbulent energy in a confluence channel. A laboratory measurement with ADV was used to investigate the flow through a Y-shaped confluence channel partially covered with rigid vegetation on its inner bank. In this study, the flow velocities in cases with and without vegetation were measured by the ADV in a Y-shaped confluence channel. The results clearly show that the existence of non-submerged rigid plants has changed the internal flow structure, that the velocity in the non-vegetated area is greater than in the vegetated area, and that there is a large exchange of mass and momentum between the vegetated and non-vegetated areas. The velocity on both sides is significantly reduced when vegetation is present. In the vicinity of tributaries, due to the presence of vegetation, the high-velocity area moved rapidly to the middle of the non-vegetated area, and the secondary flow phenomenon disappeared. In the mainstream, when vegetation was present, circulation disappeared, and the degree of lateral mixing decreased. The presence of vegetation caused a great change in the internal flow structure and made the flow in non-vegetated areas more intense.

It is meaningful to monitor and identify the concrete cracks as they will seriously reduce the fatigue life of pavement. In this paper a new method based on distributed long-gauge optic fiber sensing is proposed to implement the crack identification. Firstly, the damage indicator, namely strain curve envelope area ratio (SCEAR), is proposed and calculated with the measured strain in time series when the plane goes across the pavement where the sensors are installed. Then the indicators with different sensors are normalization by the value of the indicator from one referenced sensor where damage normally will not happen. If the crack happens within the sensing gauge of the sensor, the value of damage indicator SCEAR from the sensor will increase. Therefore, the crack will be identified with the change of the damage indicator. The effect of the proposed method is first verified by some simulations of prefabricated pavement as the cracks can be accurately identified by the proposed method. Moreover, the influence from the aircraft, such as taxiing position, aircraft load and aircraft type, is not obvious enough to mislead the identification results. Lastly the static loading tests were implemented with one small-scale model of prefabricated concrete pavement in the lab. From the experimental results the prefabricated cracks inside the pavement slab can be identified accurately with the proposes method as the parameter SCEAR is increased by about 100% at the crack position, while it is only changed by about 3% at the undamaged position.

The impact of antecedent soil moisture content on soil erosion is a complicated phenomenon, which is still under argument with contradictions in research results. Hence, the objective of this study is to investigate the impact of antecedent soil moisture content to soil loss on clay soil by conducting two-year field experiments under natural rainfall on runoff plots with length of 10 meters, width of 3 meters, and uniform slope of 9%. Volumetric soil moisture sensors were used to log soil moisture changes, and soil moisture readings were used along with rainfall records to quantify the antecedent soil moisture conditions for each rainfall event. Results of this study show duration of the effective erosion event outranks the antecedent volumetric soil moisture content. Field study also suggests that accumulative rain falling within 48 hours (Pp48) prior to an effective erosion event strongly correlated with soil loss per Rainfall-Runoff Erosivity Index (Soil Loss / EI30), particularly when the duration of an effective erosion event is either between 3 ~ 7 hours or 10~ 30 hours. Hence, Pp48 can be considered as an alternative to replace antecedent soil moisture content in RUSLE 2’s cover and management factor.

Papillary thyroid carcinoma (PTC) accounts for approximately 85%-90% of all thyroid cancers. BRAFV600E mutation is a highly specific target for papillary thyroid carcinoma (PTC) and may have a reciprocal causative relationship with iodide-metabolizing genes. Here, we performed a review of studies published in the past 10 years to determine the relationship between iodine intake and BRAFV600E mutation in patients with PTC. We searched the MEDLINE, PubMed, and EMBASE databases for studies published from 2009 to 2019; seven partially matched the selection criteria and were suitable for review, and five passed all selection criteria. We divided the patients into three groups by iodine intake: low (urinary iodine concentration [UIC] &lt;100 μg/L), adequate (UIC 100–200 μg/L), and high iodine intake groups (UIC ≥200 μg/L). Between-group analysis revealed no significant differences in the odds ratio of the prevalence of BRAFV600E mutation between the high and adequate/low iodine intake groups and between the adequate and low iodine intake groups. To further analyzed the results of studies, they exhibited U-shaped curves in the relation of deficient and excessive dietary iodine intake in BRAFV600E mutation. The results might suggest that iodine intake slightly influences the prevalence of BRAFV600E mutation in patients with PTC despite the heterogeneity of studies. Further research should explore potential mechanisms underlying the associations between iodine intake and BRAF mutation in PTC. The systematic review was registered in PROSPERO (CRD42021279462).

We propose an innovative approach called SMPTC3, designed specifically to enhance security and privacy in cross-chain transaction verification. This approach addresses multi-chain, multi-participant information exchange and large-scale cross-chain transfers, resisting various types of malicious attacks. We leverage the verifiability of cross-chain transactions based on smart contracts and innovatively transform transaction information into confidential sets, organizing them into quadratic secret polynomials. By utilizing secret sharing and random distribution techniques, we construct a secure multiparty computation method, tailored for cross-chain transactions. To enhance the efficiency of cross-chain transactions, we introduce cross-chain batch processing technology, grouping inter-chain transactions into cross-chain transaction sets. Unlike traditional distributed notary technologies, SMPTC3 designates honest participants as a cross-chain notary group, reducing the time required for redundant signature confirmations and significantly lowering the possibility of malicious notaries. Theoretical analysis and empirical experiments demonstrate that SMPTC3 is highly efficient in addressing cross-chain transaction security issues.

The heavy metal lead (Pb) can irreversibly damage the human nervous system. To help understand Pb-induced damage, we applied a genetically encoded Förster resonance energy transfer (FRET)-based Pb biosensor Met-lead 1.44 M1 to two living systems to monitor the concentration of Pb: induced pluripotent stem cell (iPSC)-derived cardiomyocytes as a semi-tissue platform, and Drosophila melanogaster fruit flies as an in vivo animal model. Different FRET imaging modalities were used to obtain FRET signals, which represented the presence of Pb in the tested samples in different spatial dimensions. Using iPSC-derived cardiomyocytes, the relationship between beating activity (20–24 beats per minute, bpm) determined from the fluctuation of fluorescent signals and the concentrations of Pb represented by the FRET emission ratio values of Met-lead 1.44 M1 was revealed from simultaneous measurements. Pb (50 μM) affected the beating activity of cardiomyocytes, whereas two drugs that stop the entry of Pb differentially affected this beating activity: verapamil (2 μM) did not reverse the cessation of beating, whereas 2-APB (50 μM) partially restored this activity (16 bpm). The results clearly demonstrate a potential of this biosensor system as an anti-Pb drug screening application. In the Drosophila model, Pb was detected within the adult brain or larval central nervous system (Cha-gal4>UAS-Met-lead 1.44 M1) using fast epifluorescence and high-resolution two-photon 3D FRET ratio image systems. The tissue-specific expression of Pb biosensors provides an excellent opportunity to explore the possible Pb-specific populations within living organisms. We believe that this integrated Pb biosensor system can be applied to the prevention of Pb poisoning and advanced research on Pb neurotoxicology.

Hang-ju was one of five officinal varieties of Flos chrysanthemum for its edible and potable usage. Besides Flos Chrysanthemum (FL), there were also Bud Chrysanthemum (BC) and Fetal Chrysanthemum (FC) at the early and late stage of buds, respectively, in the consumption market of Hang-ju with higher prices. Whether the quality and efficiency of BC and FC was superior to FL or merely consumption misunderstandings? Three commercial products of Hongxinju, a representive cultivar of Hang-ju were studied with a GC-MS based metabolomics approach, complemented with morphology, contents of moisture and protein and the anti-oxidant activity, to reveal the metabolic alterations of violate components in Hongxinju in different flowering stage and at different processing periods. It revealed that most of the violate components were increased from fresh FC to FL, and the low-boiling fractions, inflammatory methyl arachidonate and air-polluting component of ethylbenzene were declined while the representative components with pungent flavor and cool nature of a-curcumene and (Z,Z,Z)-9,12,15-octadecatrienoic acid, vision improving carotenol of rhodopin and high-boiling fractions were elevated after processed in final FL compared with that in BC and/or FC. Though the content of protein and anti-oxidative capacity of final BC and FC were nearly equal to those of FL, in comprehensive consideration of the representative components related with the efficiency in heat cooling and vision improving, as well as the representative components related with inflammation and air-pollution, final FL was recommended other than BC and FC in the practice of medicine with the yield and quality integrated into account.

This paper aims to develop a hierarchical risk assessment model using the newly-developed evidential reasoning (ER) rule, which constitutes a generic conjunctive probabilistic reasoning process. In this paper, we first provide a brief introduction to the basics of the ER rule and emphasize the strengths for representing and aggregating uncertain information from multiple experts and sources. Further, we discuss the key steps of developing the hierarchical risk assessment framework systematically, including (1) formulation of risk assessment hierarchy, (2) representation of both qualitative and quantitative information, (3) elicitation of attribute weights and information reliabilities, (4) aggregation of assessment information using the ER rule and (5) quantification and ranking of risks using utility-based transformation. The proposed hierarchical risk assessment framework can potentially be implemented to various complex and uncertain systems. A case study on the fire/explosion risk assessment of marine vessels demonstrates the applicability of the proposed risk assessment model.

In this paper, we study the semilinear pseudo-parabolic equations $\displaystyle u_{t} - \triangle_{\mathbb{B}}u - \triangle_{\mathbb{B}}u_{t} = \left|u\right|^{p-1}u$ on a manifold with conical singularity, where $\triangle _{\mathbb{B}}$ is Fuchsian type Laplace operator investigated with totally characteristic degeneracy on the boundary $x_{1} = 0$. Firstly, we discuss the invariant sets and the vacuum isolating behavior of solutions with the help of a family of potential wells. Then, we derive a threshold result of existence and nonexistence of global weak solution: for the low initial energy $J(u_{0})<d$, the solution is global in time with $I(u_{0}) >0$ or $\displaystyle\Vert \nabla_{\mathbb{B}}u_{0}\Vert_{L_{2}^{\frac{n}{2}}(\mathbb{B})} = 0$ and blows up in finite time with $I(u_{0}) < 0$; for the critical initial energy $J(u_{0}) = d$, the solution is global in time with $I(u_{0}) \geq0$ and blows up in finite time with $I(u_{0}) < 0$. The decay estimate of the energy functional for the global solution and the estimates of the lifespan of local solution are also given.

In response to the fairness issue arising from the unequal delay of vehicles in different phases at intersections, considering the actual situation of small and variable delays for vehicles in low-saturation intersection phases, this paper proposes the concept of "sacrificing efficiency for fairness." Firstly, the universality of unfair delay phenomena at intersection phases is explained, especially at low-saturation intersections where the fluctuation in phase delays is 1.87 times higher than at other intersections. Then, a fairness evaluation index is constructed using information entropy, and the feasibility of the proposed approach is demonstrated. Subsequently, a signal optimization model that balances efficiency and fairness is proposed. Finally, the proposed model is validated through case studies, showing that it not only simultaneously considers efficiency and fairness but also has minimal impact on efficiency. Moreover, the changes to timing schemes in the efficiency model are much smaller compared to the model that only considers fairness. Sensitivity analysis reveals that the model performs better under low-saturation intersection conditions.

In recent years, the AHRS has become an important research area. In order to improve the orientation measurement accuracy of AHRS, this paper first expounds the algorithm principle of the AHRS. Then, aiming at the problem of poor stability of the traditional gradient descent method under high dynamics or large magnetic field interference, a gain-scheduled anti-interference AHRS orientation algorithm is designed. By using the switching architecture designed with this algorithm for gain scheduling, it can ensure stable performance while being subjected to apparent acceleration and ferromagnetic interference. Finally, experimental verification is conducted, and the experimental results show that: in the presence of interference, the roll angle error is 0.0350°, the pitch angle error is 0.0277°, and the yaw angle error is 0.9611°, thereby verifying the strong anti-interference performance of the gain-scheduled AHRS orientation algorithm proposed in this paper.

The existences of the N→C dative bonds in the complexes between N-containing molecules and fullerenes have been verified both theoretically and experimentally. However, finding stable N→C dative bonds is still a highly challenging task. In this work, we investigated computationally the N→C dative bonds in the complexes formed by fullerene C60 with 1,2,5-chalcogenadiazoles, 2,1,3-benzochalcogenadiazoles and 1,2,4,5-chalcogenatriazoles, respectively. It was found that the N→C dative bonds are formed along with the formation of the N–Ch···C (Ch = S, Se, Te) chalcogen bonds. In the gas phase, from S-containing complexes through Se-containing complexes to Te-containing complexes, the intrinsic interaction energies become more and more negative, which indicates that the N–Ch···C chalcogen bonds can facilitate the formation of the N→C dative bonds. The intrinsic interaction energies are compensated by the large deformation energy of fullerene C60. The total interaction energies of Te-containing complexes are negative, while both of the total interaction energies of S-containing complexes and Se-containing complexes are positive. This means that the N→C dative bonds in the Te-containing complexes are more easily observed in experiments in comparison with those in the S-containing complexes and Se-containing complexes. This study provides a new theoretical perspective on the experimental observation of the N→C dative bonds in the complexes involving fullerenes. Further, the formation of stable N→C dative bonds in the complexes involving fullerenes can significantly change the properties of fullerenes, which will greatly simulate and expand the application range of fullerenes.

This study investigates the effects of Zinc (4wt.%) and severe plastic deformation on the mechanical properties of AZ61 magnesium alloy through the stir-casting process. The severe plastic deformation (equal channel angular pressing (ECAP)) has been done followed by T4 heat treatment. The microstructural examinations revealed that the addition of 4wt.%Zn enhances the uniform distribution of β-phase, contributing to a more uniformly corroded surface in corrosive environments. Additionally, dynamic recrystallization (DRX) significantly reduces the grain size of as-cast alloys after undergoing ECAP. The attained mechanical properties demonstrate that after a single ECAP pass, AZ61 + 4wt.%Zn alloy exhibits optimal yield strength (YS), ultimate compression strength (UCS), and hardness. This research highlights the promising potential of AZ61 + 4wt.%Zn alloy for enhanced mechanical and corrosion-resistant properties, offering valuable insights for applications in diverse engineering fields.

Due to the non-degradability of petroleum-based packaging materials, serious environmental pollution and the depletion of non-renewable resources have become pressing issues. In order to actively promote green production and address these concerns, there is an urgent need for new packaging materials to replace traditional plastic products. Starch-based packaging materials, composed of starch, fiber, and plasticizers, offer a degradable and environmentally friendly alternative. Starch alone cannot undergo thermoplastic processing due to its inherent structural characteristics. Therefore, researchers have explored modifications by incorporating plasticizers to create processable thermoplastic starch (TPS). However, there are challenges related to the high crystallinity and poor compatibility between TPS and fibers, resulting in decreased mechanical properties. To address these challenges, a novel approach combining plasticizer optimization and response surface method (RSM) optimization has been proposed to enhance the mechanical properties of starch-based packaging materials. This method leverages the advantages of composite plasticizers and process parameters. The findings demonstrate that the composite plasticizer effectively disrupt the hydrogen bonding and granule morphology of starch, leading to a significant reduction in crystallinity. Based on these findings, the optimal process parameters are determined using the RSM, resulting in a forming temperature of 198 °C, forming time of 5.4 minutes, and AC content of 0.84 grams. Compared with the non-optimized values, the tensile strength increases by 12.2% and the rebound rate increases by 8.1%.

Spacecraft recovery technology is crucial in the field of aerospace, in which the parachute plays a key role in slowing down the descent speed of the spacecraft and realizing a smooth landing. In order to construct a dynamically adjustable parachute deployment strategy, it is necessary to measure the parachute dynamic load accurately in real time. However, the existing sensor measurement scheme is difficult to meet the measurement requirements due to its large structure and complex wiring. In order to meet the current demand for real-time measurement of parachute cords dynamic load, a miniature measuring instrument is designed.According to the function and technical requirements of the miniature measuring instrument, the hardware modules of the acquisition system are selected and designed, and the integration debugging and performance optimization of the microcontroller module, A/D sampling module, signal acquisition circuit and power supply module are carried out. The software of the parachute cords tension acquisition system based on the miniature measuring instrument is developed. The elastomer is modeled by using SolidWorks and statically analyzed by using AnsysWorkbench finite element analysis software. Then the final structure of the elastomer and the pasting position of the strain gage are determined through the results analysis as well as experimental verification. The hardware module of the signal acquisition system for the miniature measuring instrument is then encapsulated. The force value of the miniature measuring instrument is calibrated and tested many times by using the microcomputer-controlled electronic universal testing machine. The experimental results show that the designed miniature measuring instrument has accurate data, strong stability and good real-time performance, which meets the demand for real-time accurate measurement of miniature measuring instrument, and can provide reliable data for parachute cords parameter validation and stepless unfolding design.

The state of the grinding wheel in the grinding process directly affects the surface quality of the workpiece. The monitoring of the wear state of the grinding wheel can effectively identify the wear information of the grinding wheel and timely and effectively repair the grinding wheel. In this paper, a multi-sensor fusion precision grinding wheel wear intelligent monitoring system is established for typical difficult-to-machine aerospace material titanium alloy, and a multi-eigenvalue fusion algorithm based on improved support vector machine (SVM) is proposed. The extracted sound emission signal wavelet packet decomposition coefficient mean square value, force signal grinding force ratio, and vibration signal effective value are used as the input of the improved support vector machine, and the identification strategy is adjusted by the entropy weight evaluation method. The results show that the monitoring system established in this paper can effectively identify the wear state of the grinding wheel, and the monitoring accuracy can reach more than 92%.

The intestinal microbiota, comprised of bacteria, archaea, and phages, inhabits the gastrointestinal tract of the organism. Male reproductive sterility is currently a prominent topic in medical research. Increasing research suggests that gut microbiota dysbiosis can result in various reproductive health problems. This article specifically investigates the impact of gut microbiota dysbiosis on male reproductive infertility development. Gut microbiota imbalances can disrupt the immune system and immune cell metabolism, affecting testicular growth and sperm production. This dysfunction can compromise the levels of hormones produced and secreted by the endocrine glands, affecting male reproductive health. Furthermore, imbalance of the gut microbiota can disrupt the gut-brain-reproductive axis, resulting in male reproductive infertility. This article will explore how the imbalance of the gut microbiota impacts male reproductive infertility through immune regulation, endocrine regulation, and interactions of the gut-brain-reproductive axis, concluding with recommendations for prevention and treatment.

The Pingbei area is the main accumulation area of oil and gas in the Xihu Sag. The phase characteristics of oil and gas in this area are complex, and the understanding of their genesis is still unclear. In this paper, based upon discussions of crude oil and natural gas geochemical data, integrated with local geological features, we discuss the sources, migration, and phase state characteristics of oil and gas in the Pingbei area of the Xihu Sag. The study results showed that the crude oil and natural gas in the Pingbei area are coal-derived and the oil and gas produced by the humic organic matter during the maturity stage. The oil and gas source correlation showed that crude oil and natural gas have good affinity with the Eocene Pinghu Formation (PF) coal-bearing source rocks. Crude oil has the characteristics of near-source accumulation and short-distance migration while natural gas is supplied from a dual source: the coal-derived hydrocarbon rocks of PH in the deep part of the study area, supplemented by the coal-derived hydrocarbon rocks of PH on the bottom of the slope, and adjacent hydrocarbon-bearing sub sag. The distribution characteristics and geochemical migration indices of hydrocarbon showed that the oil generated from the hydrocarbon source rocks of PH in the deep Pingbei area mainly migrates vertically along the fault connecting the reservoir and the source rocks to the trap, where it accumulates, while the natural gas exhibits deep and large faults that mainly migrate vertically, supplemented by its lateral migration along the composite transport system composed of faults and sandstone layers in the slope zone. The mechanisms of produced, exhausted, and geochromatographic effects (PGE), as well as evaporative fractionation (EF) and phase-controlled migration fractionation (PMF), result in the obvious discrepancy of hydrocarbon’s properties on the vertical profiles.

This study investigated the mechanical properties and fatigue behavior of FH36 steel plate rolled in different directions. By adopting a sequential rolling process in the rolling direction (RD) and transverse direction (TD), the differences in properties between RD and TD were eliminated, resulting in nearly identical tensile properties. The steel plate exhibited a yield strength of approximately 420 MPa, a tensile strength of approximately 506 MPa, and an elongation of approximately 25%. Fatigue tests conducted at room temperature and -60℃ showed a fatigue limit of the maximum stress of 488 MPa at room temperature and 500 MPa at -60℃, indicating improved low-temperature fatigue performance. The fracture surfaces displayed distinct characteristics, such as oblique shearing fractures for high-cycle fatigue and cup-cone shape fractures for low-cycle fatigue. The fatigue source zone were both on the surface of the specimens. As the maximum stress increased, the area of the crack propagation zone for high-cycle fatigue decreased, while the area of the final fracture zone, the number of dimples and the proportion of the LAGBs increased.

The key links of face recognition are digital image preprocessing, facial feature extraction and pattern recognition, this article aimed at the current problem of slow speed and low recognition accuracy of face recognition , from the above three key links, on the basic of analyzing the therories of Fractional Differential Masks Operator (FDMO), Principal Component Analysis (PCA) and Support Vector Machine (SVM), design a kind of FDMO+PVA+SVM coupling algorithm that applies to face recognition to improve the speed and accuracy of it. To realize FDMO+PCA+SVM coupling algorithm, first, we should apply FDMO to face image processing binary marginalization, the purpose is getting face contour; Then, we apply PCA to get the feature of face image which is disposed by binary marainalization. At last, we can apply One-Against All of the SVM classifier and LibSVM software package to realize face recognition. Beside, the article with nine different coupling algorithm design four groups of experimental reaults on the ORL face database verified by comparative analysic FDMO+PCA+SVM coupling algorithm in the superiority of face recognition accuracy and speed.

In 2020 the world experienced the threat of the COVID-19 epidemic, as seniors and chronic disease patients typically try to reduce their exercise and social activities to avoid increasing the risk of infection, which could lead to increased loneliness and even many diseases. This research combining golf croquet games with AIoT companion robots constructs a home-based intelligent exercise system thus uses the Technology Acceptance Model (TAM), deduces users’ intention to use this system based on perceived usefulness and perceived ease of use, and adds the needs of love and belonging, esteem, cognitive, aesthetic, and self-actualization in Maslow’s needs theory to conduct system needs analysis. The analysis results show that participants have a high level of acceptance of this system, believing that it is easy to learn and operate, can increase interaction with others, also found that this system can improve self-confirmation, satisfying the third for knowledge, feeling happy, and self-actualization needs are easier to fulfill. In the future, we shall collect and record the seniors in the process of use, so as to find out their health problems as soon as possible, expand their daily life through this exercise, and achieve the goal of happy living and health care.

ESG (Environmental, Social, and Governance) responsibility fulfillment increasingly affects enterprise valuation. Although researchers debate about the precise effects, the prevailing view suggests a linear relationship between ESG performance and enterprise value. This study introduces a novel ESG responsibility performance metric through the Regulated Intermediary Model to delve into this relationship within the Chinese context. Our findings reveal an inverted U-shaped relationship between ESG performance and enterprise value, with financing constraints having a significant moderating effect. These findings remain robust after employing instrumental variables to mitigate potential endogeneity. Heterogeneity analysis demonstrates that this inverted U-shaped relationship is particularly pronounced in non-polluting and non-state-owned enterprises. Moreover, a comparison between equity and debt financing mechanisms underscores that improved ESG performance is associated with lower cost of equity financing, thereby enhancing enterprise value. Financial institutions are encouraged to leverage innovative financial instruments to diversify enterprise financing channels and alleviate financing constraints of enterprises that fulfill their ESG responsibilities.

Recent researches indicated that metal nanoparticles which have the unique optical properties can be used to enhance the spectral response of the photovoltaic modules. Since most of the nanoparticles have enhancement effects in a specific wavelength range, improving the spectral response of the photovoltaic modules in a broadband range is crucial for their applications in imaging, energy harvesting, and optical communication. In this study, flower-like silver particles are applied to achieve the enhancement effects in a broadband range. The optical absorption of photovoltaic modules is improved in a broad wavelength range of 400~2000 nm by immobilizing flower-like silver particles onto an amorphous Si p-i-n structure, and the peak responsivity of the spectral response is enhanced by about 10 times. Theoretical investigation further elaborates that the enhancement originates from the near-field effects of silver particles due to the interaction of different parts of the flower-like silver particles. Through these studies, we demonstrate that, utilizing the subwavelength silver particles with roughness surface can achieve the spectral response of the photovoltaic modules enhanced in broadband range, which can improve the utilization efficiency of optical energy for the applications of sensing, imaging, optical communication, and energy harvesting.

The COVID-19 pandemic has now become very severe as never before due to the overwhelming spread of Omicron. We found that Omicron outbreak can be effectively prevented by inactivated vaccines, which averted an outbreak of more than 1.6 million people in Hangzhou, China. The 36 mutations in the target spike protein of Omicron neutralizing antibody enable it to evade the immune protection afforded by vaccines. This is because that mRNA and adenovirus-vector vaccines are designed to recognize the spike (S) glycoprotein of the SARS-CoV-2 wild-type (WT) strain. However, Inactivated vaccines contain the whole viral antigens and remain stable in their recognition of newly emerging variants of SARS-CoV-2. Our study confirmed the advantage of inactivated vaccines in the face of highly mutated Omicron variant and provided a basis for the development of effective vaccines to prevent future long-term transmission, mutation and recurrence of SARS-CoV-2.

Introduction: Spinal epidural arteriovenous fistulas (SEDAVFs) are extremely rare and the pathological process still remains unclear. Nevertheless, neurofibromatosis, surgery, as well as trauma have been implicated as causes. Nevertheless, long standing chronic vertebral compression fractures (VCFs) as a cause of SEDAVFs has not been reported in literature. Case Presentation: Our cases comprised of a male and female with ages 67 and 62 year respectively. They presented with weakness of bilateral lower extremities and back pain. Their symptoms deteriorated into mild recto-bladder dysfunction as well as hypoesthesia of lower limbs. They both had history of road traffic accidents (RTAs) prior to their symptomatology. In both cases, Magnetic resonance imaging (MRI) revealed VCFs prior to the above symptomatology. Spinal digital subtraction angiography (DSA) was used to confirm SEDAVFs in both cases. We utilized the trans-arterial route with Onyx embolization agent to obliterate both fistulae and their symptom resolved after the embolization. Two-years follow-ups revealed no recurrence of their fistulae. Conclusion: The initial long standing VCFs caused by trauma resulted in perforation of the dorsal somatic branches of the radicular artery leading to the occurrences of SEDAVFs in our cases.

The spread of 2019 novel coronavirus disease (COVID-19) throughout the world has been a severe challenge for public health. The human angiotensin-converting enzyme 2 (ACE2) has a remarkably high affinity binding to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). By the search for network database and re-analysis of pubic data, we found the level of ACE2 expression in adipose tissue was higher than that in lung tissue, which indicated the adipose tissue might be vulnerable to SARS-CoV-2 as well; the levels of ACE2 expressed by adipocytes and adipose progenitor cells were similar between non-obese individuals and obese individuals, but obese individuals have more adiposes so as to increase the number of ACE2-expressing cells; the expression of ACE2 in tumor tissues posed by five different types of cancers increased significantly compared with that in adjacent tissues. Thus, we suggest that more attentions might be given to obese individuals and the five types of cancer patients during the outbreak of COVID-19.

In this work, we designed a MEMS device which allows simultaneous direct measurement of mechanical properties during deformation under external stress and characterization of the evolution of microstructure of nanomaterials within a transmission electron microscope. This MEMS device makes it easy to establish the correlation between microstructure and mechanical properties of nanomaterials. The device uses piezoresistive sensors to qualitatively measure the force and displacement of nanomaterials, e.g., in wire and thin plate forms. The device has a theoretical displacement resolution of 0.19 nm and a force resolution of 2.1 μN. The device has a theoretical displacement range limit of 2.74 μm and a load range limit of 27.75 mN.

The effect of H2S with high concentrations on catalytic dry reforming of methane (DRM) process has seldom been focused on previously. Herein, a thermodynamic analysis of the DRM reactions in the presence of H2S with the concentration varying in 0-20 vol% was conducted firstly. Several typical types of catalysts including MgO, NiO/MgO and LaNiO3 in different states were prepared for executing DRM at 800 C, 0.1 MPa in the feed of 20 vol% CO2 and 20 vol% CH4 balanced with N2. The catalytic performance of each catalyst for DRM process under conditions of absence and presence of H2S was compared. A promotion effect of increasing H2S concentration on both the conversions of CO2 and CH4 and the molar yields of CO and H2 was observed on all the catalysts especially the MgO and the pristine NiO/MgO. While a significant decline in catalytic activity of either the reduced NiO/MgO or the reduced LaNiO3 catalyst after adding H2S, moderate reactant conversions still sustained. The results of process analysis and catalyst structure characterization suggest that H2S participation can contribute to the increment in CO2 and CH4 conversion, and active S-adsorbed species may play the key role of catalysis in the reactions involving H2S.

Plant cells' ability to withstand abiotic stress is strongly linked to modifications in their mechanical characteristics. Nevertheless, the lack of a workable method for consistently tracking plant cell mechanical properties severely restricts our comprehension of the mechanical alterations in plant cells under stress. With Polyethylene Glycol (PEG6000), we created a drought-like environment, and we used the Double Resonator Piezoelectric Cytometry (DRPC) method to dynamically and non-invasively track changes in the stress (ΔS) created and viscoelasticity (storage modulus G' and loss modulus G") of protoplasts and suspension cells of rice during drought stress. The findings demonstrate that, rice suspension cells and protoplasts react mechanically differently to 5%–15% PEG6000 stress, implying distinct resistance mechanisms. However, neither of them can withstand 25% PEG6000 stress, they respond mechanically similarly to 25% PEG6000 stress. The results of DRPC are further corroborated by the morphological alterations of rice cells and protoplasts observed under an optical microscope. To sum up, the DRPC technique functions as a precise cellular mechanical sensor and offers novel research tools for the evaluation of plant cell adversity and differentiating between the mechanical reactions of cells and protoplasts under abiotic stress.

Abstract: Transcription factors are crucial pre-transcriptional regulatory mechanisms that can modulate the expression of downstream genes by binding to their promoter regions. DOF (DNA binding with One Finger) proteins are a unique class of transcription factors with extensive roles in plant growth and development. Our previous research indicated a decrease in iron content in chlorotic bamboo leaves. However, to our knowledge, genes related to iron metabolism pathways in bamboo species have not yet been studied. Therefore, in the current study, we identified iron metabolism-related (IMR) genes in bamboo and determined the transcription factors that significantly influence them. Among these, DOFs were found to have widespread effects and potentially significant impacts on their expression. We identified specific DOF members in Dendrocalamus latiflorus with binding abilities through homology with Arabidopsis DOF proteins, and established connections between some of these members and IMR genes using RNA-seq data. Additionally, molecular docking confirmed the binding interactions between these DlDOFs and the DOF binding sites in the promoter regions of IMR genes. The co-expression relationship between the two gene sets was further validated using q-PCR experiments. This study paves the way for research into iron metabolism pathways in bamboo and lays the foundation for understanding the role of DOF transcription factors in D. latiflorus.

Glass has emerged as a highly versatile substrate for various sensor and MEMS packaging applications, including electromechanical, thermal, optical, biomedical, and RF devices, due to its exceptional properties such as high geometrical tolerances, outstanding heat and chemical resistance, excellent high-frequency electrical properties, and the ability to be hermetically sealed. In these applications, Through-Glass-Via (TGV) plays a vital role in manufacturing and packaging by creating electrical interconnections through glass substrates. This paper provides a comprehensive summary of the research progress in TGV fabrication along with their integrations, including through-via formation and metallization. The paper also reviews the significant qualification and reliability achievements obtained by the scientific community for TGV. Additionally, the paper summarizes the application of TGV technology in various sensors.

Session-based recommendations which aim to predict subsequent user-item interaction based on historical user behavior during anonymous sessions can be challenging tasks. Two main challenges need to be addressed and improved: (1) How to analyze these sessions to accurately and completely capture users’ preferences, and (2) how to identify and eliminate any interference caused by noisy behavior. Existing methods have not adequately addressed these issues since they either neglected the valuable insight that can be gained from analyzing consecutive groups of items or failed to take these noisy data in sessions seriously and handled them properly, which can jointly impede recommendation systems from capturing users’ real intentions. To address these two problems, we designed a multi-order semantic denoising (MSD) model for session-based recommendations. Specifically, we grouped items of different lengths as varying multi-order semantic units to mine the user’s primary intention from multiple dimensions. Meanwhile, a novel denoising network was designed to alleviate the interference of noisy behavior and provide a more precise session representation. The result of extensive experiments on three real-world datasets demonstrated that the proposed MSD model exhibited improved performance compared with existing state-of-the-art methods in session-based recommendation.

Cancer is a devastating disease with female breast cancer becoming the leading cause of global cancer morbidity. Herein we report the design and synthesis of a sorafenib analog 1A and its base-promoted arranged compound 1A2. Their in vitro cytotoxicity and potencies in EFGR inhibition study revealed that compound 1A displayed good antiproliferative activity in MDA-MB-231 (breast) cells with an IC50 value of 16.18±1.42 μM. Crystallization 1A2 affored 1A2a as a solvate with dichloromethane which was explicitly confirmed by the single crystal X-ray diffraction analysis.

Celtis sinensis is an adaptable species that is widely grown in southern China. In June 2022, a leaf blotch disease of C. sinensis was observed in Nanjing, Jiangsu, China. Based on morphological characterization, three isolates were identified as Alternaria species. Phylogenetic analysis of combined ITS, GAPDH, TEF1-α, RPB2 and Alt a 1 sequences identified the three isolates we obtained as Alternaria alternata and Alternaria koreana. Koch’s postulates were fulfilled in the greenhouse, and the pathogenicity of A. alternata and A. koreana was determined by leaf inoculation tests on C. sinensis seedlings. The symptoms of indoor inoculation were consistent with those in the field. A. alternata and A. koreana can grow at 15-35 °C, with an optimal growth temperature of 25 °C. The results of fungicide sensitivity experiments indicated that A. alternata and A. koreana were the most sensitive to prochloraz, which may be a useful strategy for the future prevention and control management of A. alternata and A. koreana. This study provides the first step for further research on A. alternata and A. koreana as pathogens of C. sinensis and provides a theoretical basis for future control strategies.

The movement of liquid droplets on the energy gradient surface has attracted extensive attention. Inspired by biological features in nature, such as the periodic spindle-shaped nodes in spider silks and conical-like barbs of cacti, the structure-property-function relationship of multifunctional gradient surfaces. In this study, a series of specific patterns are fabricated by 3D printing technology, followed by modification via the atmospheric pressure plasma treatment and liquid phase chemical deposition, resulting in enhancing the ability of water droplets of 5μL to travel 18.47mm on a horizontal plane and 22.75mm against gravity up to 20° tilting angle. Additionally, analysis techniques have been employed including contact angle analyzer, ESCA and laser confocal microscope to evaluate the sample performance. This work could further be applied to many applications related to microfluidic devices, drug delivery and water/fog collection.

The synchronization of complex networks is believed to be closely related to network topology. How to study synchronization of real network without clear topology and parameters? In this Letter, a synchronized stability boundary equation is derived that is system- and disturbance-independent and applicable to arbitrarily coupled grids. The results imply that spontaneous synchronization in a network may be network independent. These conclusions provide new research paths for network synchronization and analyze the synchronization stability of grids in a unified way.

Earth observation satellites can capture images of specific areas in Earth's orbit based on user requirements. Despite the high demand for satellite imagery, satellites remain a scarce resource. When there are many observation tasks that are large and dense, they may interfere with each other due to satellite mobility. To address this issue, a multi-satellite scheduling algorithm based on a task merging mechanism has been proposed. This paper proposes a two-stage approach to the problem: task merging phase and merging task scheduling phase. The task merging phase introduces two methods based on Mean Shift and Complete Graph to generate the merging task set. In the merging task scheduling phase, a multi-satellite scheduling algorithm based on merging tasks is employed to solve the problem. Finally, certain measurement experiments suggest the effectiveness of the algorithm.

The sexual reproduction of ascomycetes is controlled by the mating-type(MAT) locus. (Pseudo)homothallic reproduction has been hypothesized based on genetic data from Hirsutella sinensis (Genotype #1 of Ophiocordyceps sinensis). In this study, the differential occurrence of the mating-type genes in the MAT1-1 and MAT1-2 idiomorphs, which constitute the genetic control of O. sinensis reproduction, was analyzed in 237 strains and 5 genomes of H. sinensis. The mating-type genes were differentially transcribed in H. sinensis Strain L0106, and the MAT1-2-1 transcript in H. sinensis Strain 1229 was alternatively spliced, with an unspliced intron I containing stop codons; these findings constitute O. sinensis reproduction controls at the transcriptional and coupled transcriptional-translational levels. The occurrence of the mating-type genes and a-/α-pheromone receptor genes differed among the 5 H. sinensis genomes. The differential occurrence and transcription of these genes are inconsistent with self-fertilization under (pseudo)homothallism but suggest self-sterility of H. sinensis, which therefore needs a mating partner to achieve sexual outcrossing under heterothallism or hybridization. Consistent occurrence and transcription of the mating-type genes of both the MAT1-1 and MAT1-2 idiomorphs have been reported in natural and cultivated Cordyceps sinensis, but these findings are insufficient to determine the reproduction mode(s) because of the co-occurrence of >90 fungal species and multiple genomically independent genotypes of O. sinensis. The mutant MAT1-1-1 and α-pheromone receptor transcripts in natural C. sinensis result in the N-terminus or middle-truncated proteins, with changes in hydrophobicity and secondary structures of the proteins, suggesting heterogeneous fungal source(s) of the proteins and hybridization reproduction.

A method is proposed for describing the dynamics of systems of interacting particles in terms of an auxiliary field, which in the static mode is equivalent to given interatomic potentials, and in the dynamic mode is a classical relativistic composite field. It is established that for interatomic potentials, the Fourier transform of which is a rational algebraic function of the wave vector, the auxiliary field is a composition of elementary fields that satisfy the Klein-Gordon equation with complex masses. The interaction between particles carried by the auxiliary field is nonlocal both in space variables and in time. The temporal non-locality is due to the dynamic nature of the auxiliary field and can be described in terms of functional-differential equations of retarded type. Due to the finiteness mass of the auxiliary field, the delay in interactions between particles can be arbitrarily large. A qualitative analysis of the dynamics of few-body and many-body systems with retarded interactions has been carried out, and a non-statistical mechanisms for both the thermodynamic behavior of systems and synergistic effects has been established.

In recent years, electroencephalogram (EEG) emotion recognition has emerged as a research hotspot in the field of artificial intelligence (AI). Despite advancements in EEG-based emotion recognition, room for enhancing performance persists due to EEG signal redundancy and limitations in feature extraction, leading to inefficient models and emotional information loss. To fully utilize EEG's emotional information and improve recognition accuracy while reducing computational costs, this paper proposes a Convolutional-Recurrent Hybrid Network with a dual-stream adaptive approach and an attention mechanism (CSA-SA-CRTNN). Firstly, the model utilizes a CSAM module to assign corresponding weights to EEG channels. Then, an adaptive dual-stream convolutional-recurrent network (SA-CRNN and MHSA-CRNN) is applied to extract local spatial-temporal features. After that, the extracted local features are concatenated and fed into a temporal convolutional network with a multi-head self-attention mechanism (MHSA-TCN) to capture global information. Finally, the extracted EEG information is used for emotion classification. We conducted binary and ternary classification experiments on the DEAP dataset, achieving 99.26% and 99.15% accuracy for arousal and valence in binary classification, and 97.69% and 98.05% in ternary classification, surpassing relevant algorithms. Additionally, the model's efficiency is significantly higher than other models, achieving better accuracy with lower resource consumption.

Background: People with Down syndrome (DS) have a trisomy of chromosome 21 and marked deficits in verbal memory but relatively preserved visuospatial perception. Verbal memories are related to semantic knowledge. Little is known about the organization of semantic knowledge in people with DS, which was the aim of this study. Aims: The extent of false memory in people with DS was examined. Possible differences in the number of false memories induced by nominal and verbal themes were examined. Methods and Procedures: In the study phase, ten word lists with semantically related associates were presented. In the recognition phase, participants made judgments on whether each word had been represented previously as semantically related lures, old words, and semantically unrelated new words. Outcomes and Results: Differences in the processing of nominal and verbal theme-related lures were observed among people with DS. When processing nominal theme-related lures, people with DS showed delayed false positives. When processing verbal theme-related lures, people with DS showed no differences compared to controls. Similar patterns have been observed in people with DS when processing nominal theme-related associates and verbal theme-related associates. People with DS have delayed recognition of associates. When processing unrelated words, they showed significantly higher false positives than controls for both nominal and verbal eliciting themes. Further analyses of the themes revealed differences in false positives across syntactic categories among groups. Conclusions and Implications: People with DS showed a delayed recognition of associates and deviance in recognizing unrelated words in the nominal and verbal theme categories. People with DS were delayed in terms of nouns, but deviated with verbs in associated and unrelated words. Additionally, people with DS showed distinct patterns in processing five nominal lures and three verbal lures, suggesting that they formed false memories differently based on distinct syntactic categories. Thus, it was concluded that people with DS develop a deviant semantic structure. Category-based interventions for people with DS should be implemented in order to improve their semantic knowledge through lexical connections.

Agrivoltaic agrotunnels are currently designed for high density grow walls that are not amenable to bush berries or root crops. Commercial grow bins provide deeper substrates for produce with more root systems but have high costs per unit growing area. To overcome the economic limitations of grow bins, this study applies the distributed manufacturing open-source design paradigm to develop four designs for low-cost open source structures. The designs target root vegetables and bush fruit specifically to be adopted by remote communities with limited or no outdoor growing environment to offset the market price for imported fresh produce. The indoor growing designs provide the necessary structure for supporting grow light and grow bins and enabled the transplanted berry plants to flower and produced fruits. They provide a comparable amount (110L) or more of grow volume from 106 to 192 L. The water reservoir volume for the commercial system (62 L) and grow area (0.5 m³) is surpassed by all new designs that range from 64 to 192 L and 0.51 to 0.76 m³, respectively. These superior properties are possible with material costs for all four designs that save more than 90% of the economic cost of the commercial systems.

The motor protein Prestin found in the outer hair cells (OHCs) of the inner ear is responsible for producing high sensitivity and sharp frequency selectivity for mammalian hearing. Some studies have suggested that Prestin could serve as a serological biomarker for cochlear damage since OHCs are highly vulnerable to damage from various sources of insults. However, the reported data are inconsistent and lack appropriate negative controls. To investigate this further, we measured Prestin quantities in the bloodstream using ELISA kits from different companies. Wildtype (WT) mice were exposed to different ototoxic treatments, including noise exposure and ototoxic reagents that kill OHCs rapidly. Prestin-knockout (KO) mice were used as a negative control. Our data show that some ELISA kits were not able to detect Prestin specifically. The ELISA kit that could detect Prestin protein from cochlear homogenates failed to detect Prestin in the bloodstream despite significant damage to OHCs in cochleae. Furthermore, the optical densities of samples, which correlate to Prestin quantities, were significantly influenced by hemolysis in the samples. In conclusion, Prestin from OHCs is not a sensitive and reliable serological biomarker for detecting cochlear damage in mice.

The study of trophic relationships among closely related species plays an important role in deepening our understanding of the resource utilization characteristics, differentiation patterns, and population dynamics of co-occurring species in the same habitat. This research uses two congeneric fish species, Pennahia pawak and Pennahia anea, as examples. Based on stomach content analysis and carbon-nitrogen stable isotope analysis, a comparative analysis of their feeding habits and trophic niches is conducted. Additionally, spatial niche analysis is employed to explore the coexistence and competitive mechanisms between these two closely related fish species. The results showed that both P. pawak and P. anea had similar feeding habits, mainly feeding on Pisces and Macrura, but there were some feeding preferences between the two species. Interspecific prey overlap was meaningful but not significant, with an overlap coefficient of 0.56. There were significant differences in feeding habits between the two species during different seasons. Based on stable isotope analyses, body length of both species had a significant positive correlation with δ15N (Pearson r=0.65, P&lt;0.01; Pearson r=0.44, P&lt;0.01), but not with δ13C (P&gt;0.05). Standard ellipse corrected area (SEAc) of P. pawak and P. anea were 0.65 and 1.16, while the trophic niche overlap was only 0.29, which was not significant; the spatial niche width of the two was 1.19 and 0.58, respectively, and the spatial niche overlap was only 0.20, which was not significant. Intra-species competition was intense in P. pawak and P. anea, but reduced feeding specialization had a mitigating effect on intra-species competition. Interspecific competition was present but not significant, and was mitigated by trophic and spatial niche differentiation.

This paper aims to study the surface homogenization and integrity of Ti-6Al-4V alloy by longitudinal-torsional coupled ultrasonic vibration assisted ball-end milling. A method of continuous processing between the flat surface and freeform surface connection is proposed by using ultrasonic vibration assisted ball-end precision milling, during this process, it is not necessary to exchange the cutting tool. The way has been explored for changing the homogenization of surface on Ti-6Al-4V by ultrasonic vibration-assisted milling (UVAM). Cutting experiments employing three parameters, cutting speed, feed rate and depth of cut and two types of machining forms using ball-end milling with UVAM and conventional milling (CM) respectively. The high frequency cutting force, finished surface roughness, topography and residual stresses on the surface and tool wear have been measured by advanced instruments. Particularly, adopting the high frequency cutting force measurement system, it is concluded cutting force in ball-end milling decreased significantly using UVAM as against CM. Moreover, the surface roughness by UVAM with ball-end milling is much better than the CM at a high cutting speed. However, an opposite trend is observed at a low cutting speed. Especially, there is a steep decrease from Ra 0.828 μm average value at 4000 rpm to Ra 0.129 μm average value at 5000 rpm. At the same time, the homogenization of surface roughness and residual stresses decrease significantly in UVAM as compared to which in CM when taking the transversal-longitudinal ratio into consideration. Cutting experiments and measuring results are demonstrated the validity and feasibility of UVAM with ball-end milling, and this method enjoys significant advantages compared to CM process.

With the development of organizational biology and forced from the EU Cosmetic Regulation (EU/1223/2009) with the complete ban of animal testing for cosmetic purposes, 3D skin models have been widely developed due to their similar physiological structure and metabolic function to native human tissue. 3D skin models for in vitro cosmetic evaluation are still promising alternative methods for evaluating phototoxicity, corrosivity and irritation. These models have been used for early screening and later validation of toxicity and efficacy evaluation by many well-known cosmetic companies. 3D skin models have become an important tool in cosmetic evaluation research. This article reviews the development of 3D skin models and their application in cosmetic evaluation. An outlook on the current application and future technological development directions in the cosmetic field is also presented.

(1) Background: In most cases, passive isolation control methods are commonly used for the seismic isolation design of bridge engineering. However, for passive seismic isolation devices, due to their non-adjustable performance parameters, it is challenging to achieve a good seismic isolation effect for structures under random and variable seismic loads in the wide frequency range of 0 Hz to 20 Hz; (2) Methods: the sensitivity of the design parameters of the seismic isolation bearing was analyzed using the optimization center gradient method, and an improved genetic algorithm was employed to quickly optimize and obtain the optimal design parameters; (3) Results: the effectiveness of the three-dimensional seismic isolation bearing was validated through experiments. (4) Conclusions: The multi-factor sensitivity analysis approach used in this study for designing novel isolation bearings is applicable not only to seismic design in bridges but also serves as a reference for parameter design in isolation bearings requiring medium to high precision in seismic performance.

This study primarily investigates the effect of fly ash (FA) content on the mechanical properties and hydration performance of alkali-activated ground granulated blast furnace slag cements (AAGC), and compares the related properties with ordinary Portland cement (OPC). Additionally, the study examined the hydration products, thermal analysis, MIP, SEM, chemically bound water, and pH values of AAGC. The compressive strength of AAGC showed a retrogression phenomenon from 3 to 28 days, with the 14-day and 28-day compressive strengths of AAGC being higher than those of OPC. The AAGC with 20% FA content exhibits the highest 28-day compressive strength (75 MPa). The hydration heat release rate curved of OPC and AAGC can be divided into the initial induction period, induction period, acceleration period, deceleration period and steady period. As FA content increases, the 28-day pore volume of AAGC increased while pH values and chemically bound water decrease. SEM images of AAGC with low FA content showed more microcracks.

This study evaluated the mechanical strengths of three types of orthodontic micro-implants by analyzing their structural configurations. Thirty micro-implants of three types (diameter 1.5 mm, Types A, B, C) were assessed. All micro-implants were manually driven into artificial bones at an 8-mm depth. The insertion torque (IT), pullout strength (PS), and gripping volume (GV) of each type were measured. Intergroup comparisons and intragroup correlation were investigated by statistical analysis. Type B had the greatest inner–outer diameter ratio (0.67), and Type A had the smallest (0.53). The IT of Type A (5.26 Ncm) was significantly (p = 0.038) lower than that of Type C (8.8 Ncm). There was no significant difference in the pullout strength (p = 0.868). The GV of Type A (9.7 mm3) was significant (p < 0.01) greater than Type C (8.4 mm3). Type C was significant (p < 0.01) greater than Type B (7.2 mm3). Spearman’s rho rank correlation test showed that PS of Type B was correlated significantly with GV. In conclusion, the design of thread and its GV were the important factors on the mechanical strengths of micro-implant.

Soft materials bearing rigid, lightweight, and vibration-dampening properties offer distinct advantages over traditional wooden and metal-based fillings for spent fuel transport casks, due to their low density, tunable structure, excellent mechanical properties, and ease of processing. In this study, a novel type of rigid polyurethane foams is prepared using a conventional polycondensation reaction between isocyanate and hydroxy groups. Moreover, the density and size of the pore in these foams are precisely controlled through simultaneous gas generation. The as-prepared polyurethane exhibits high thermal stability exceeding 185 °C. Lifetime predictions based on thermal testing indicate that these polyurethane foams could last up to over 60 years, which is double lifetime of conventional materials of about 30 years. Due to their occlusive structure, the mechanical properties of these polymeric materials meet the design standards for spent fuel transport casks, with maximum compression and tensile stresses of 6.89 and 1.37 MPa, respectively, at a testing temperature of -40 °C. In addition, these polymers exhibit effective flame retardancy; combustion ceased within 2 s after removal of the ignition source. All in all, this study provides a simple strategy for preparing rigid polymeric foams, presenting them as promising prospects for application in spent fuel transport casks.

The astro-structures with the shape of comet and semi-circle, are found in the electronegative inductively coupled plasmas (ICPs), e.g., Ar/O2 and Ar/SF6. They are formed by means of the self-coagulation theory. This theory is built and based on two-dimensional fluid model simulation dynamic data of the above ICP sources. Concretely, quasi-Helmholtz equation is constructed through the free diffusion transport component and a novel negative chemical source term. The absolute value of recombination rate is higher than the attachment rate and so the net source of simulated anion is negative. This is quite a new chemical phenomenon in the electronegative and gaseous discharging plasmas when compared to the previously reported normal positive chemical source that will generate ambi-polar diffusion potential. In electronegative plasma, the self-coagulation is ambi-polar to sustain the electrical neutrality. Besides, when the anions are accelerated by ambi-polar potential before self-coagulated, the self-coagulation is again advective which leads to the formation of blue sheath. At the ambi-polar self-coagulation of high electronegativity, the electrons dynamics are relatively decoupled from ions and meanwhile they have their own relatively weak, spontaneous, and monopolar self-coagulation in the periphery of astro-structure. At the ambi-polar self-coagulation, both the anion and cation are individually treated as mass point models that carry charge (point charge models, more precisely). When the charge amounts of two individual astr-structures, e.g., semi-circle SF3+ and Ar+, are equal, the coagulated profile of heavy species SF3+ collapses by the expelling effect of Coulomb force that exists between the two point-charges. This is an anti-collective behavior of astro-structure, instead of the collective interaction of plasma, since the collapse of coagulated heavy species creates spatially dispersed charge density that cannot be shielded. The simulation shows that the lighter the species, the easier it self-coagulates, determined by the inertial effect of density quantity. The discharge picture of electronegative plasma is combined by a dynamic continuum transport (e.g., forming the ellipse background) and the mechanical balance contained in the static self-coagulation process (proven by dimensional analysis of continuity equation). The popular astro-structure of electronegative ICP source awaits urgently for the validation of experiment.