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Larimichthys crocea is an important economic fish of East Asia, and numerous studies have been conducted on its breeding, aquaculture, preservation and processing; however, there is no systematic review of the literature on the research of Larimichthys crocea. Derwent Data Analyzer (DDA) was used to analyze 1192 Larimichthys crocea research papers indexed by SCI-E, CSCD and KCI from 2001 to 2023. The number of research publications on Larimichthys crocea has rapidly increased, and institutions and scholars from China, the United States, South Korea, Japan, and Norway have conducted the majority of Larimichthys crocea research. The immune response, Pseudomonas plecoglossicida, gene expression, lipid immune response, transcriptomics and other areas have attracted the most attention. To increase the immunity and disease resistance of Larimichthys crocea and improve its survival, growth, storage and transport, researchers have carried out a large amount of research, which has promoted not only the culture of Larimichthys crocea but also the restoration of wild Larimichthys crocea and the rehabilitation of the ecological environment.

AIM: To assess the accuracy of predicting intraocular lens(IOL)power after myopic refractive surgery using the Pentacam system's true net power(TNP)in the 3 mm zone combined with the SRK/T formula [i.e. TNP 3 mm(SRK/T)].METHODS: Retrospective study. This study enrolled 35 cases(50 eyes)of patients undergoing cataract surgery after laser assisted in situ keratomileusis(LASIK)or photorefractive keratectomy(PRK)from July 2019 to December 2021. Preoperatively, IOL power of 50 eyes, 34 eyes and 41 eyes was calculated by TNP 3 mm(SRK/T), Barrett True-K and Olsen 2 formulas, respectively, with at least 2 formulas used to calculate IOL power for each patient. The actual diopter was recorded 3 mo postoperatively. Prediction errors(PE)of IOL power were compared among the three calculation methods, and the proportion of eyes with PE within ±0.5 D and ±1.0 D was analyzed.RESULTS: The PE at 3 mo postoperatively for TNP 3 mm(SRK/T), Barrett True-K, and Olsen 2 was -0.02±0.63, -0.54±0.80, and 0.25±0.80 D, respectively(P0.05).CONCLUSION: The Pentacam TNP 3 mm(SRK/T)method is simple to operate and provides accurate calculation of IOL power after corneal refractive surgery.

Membrane separation technology with the ability to regulate gas/liquid transport and separation is critical for environmental fields, such as sewerage treatment, multiphase separation, and desalination. Although numerous membranes can dynamically control liquid-phase fluids transport via external stimuli, the transport and separation of gas-phase fluids remains a challenge. Here, we show a temperature-regulation liquid gating membrane that allows in-situ dynamically controllable gas/liquid transfer and multiphase separation by integrating a thermo-wettability responsive porous membrane with functional gating liquid. Experiments and theoretical analysis have demonstrated the temperature-regulation mechanism of this liquid gating system, which is based on thermo-responsive changes of porous membrane surface polarity, leading to changes in affinity between the porous membrane and the gating liquid. In addition, the sandwich configuration with dense Au-coated surfaces and heterogeneous internal components by a bistable interface design enables the liquid gating system to enhance response sensitivity and maintain working stability. This temperature-regulation gas/liquid transfer strategy expands the application range of liquid gating membranes, which are promising in environmental governance, water treatment and multiphase separation.

Suspension bridges are the most common type of bridge used to cross the ocean. The cable clamps in suspension bridges clamp the main cables by bolt preload, but the elastic interaction of the bolts reduces the preload, which is detrimental to the force in suspension bridges. However, research on the factors influencing the elastic interaction of cable clamp bolts in suspension bridges is currently limited. This paper aims to explore the law of influence of external factors on the elastic interaction of bolts through a combined approach of theoretical analysis, full-scale experiment, and finite element simulation. The results indicate that the average preload loss was reduced by about 27% when the elastic modulus was increased by about 110%. The average preload loss was reduced by about 45% when the bolt center distance was increased by 75%. The number of bolts has a small effect on the elastic interaction, which can be ignored. When the preload of bolt installation was increased by 133%, the average preload loss was reduced by approximately 125%, which was almost a linear relationship. Tightening the bolt from the center bolt creates greater elastic interaction. The conclusions can provide suggestions for reducing the elastic interaction of bolts in the design and construction of suspension bridge cable clamps.

In order to investigate the effects of thermal processing methods on the quality and oxidation characteristics of pork, boiled, microwaved, roasted, or deep-fried pork loin was evaluated for quality indicators such as cooking loss, color, shear force, texture, basic chemical composition, odor and taste and oxidation indicators such as protein carbonyl content and thiobarbituric acid reactive substance (TBARS) value. The results showed that compared with the control group (raw pork), the quality and oxidation characteristics of cooked pork samples were significantly different. The decreasing order of cooking loss rate during different thermal treatments was roasting > microwave > deep-frying > boiling; protein and ash contents were positively correlated with cooking loss, while water content was negatively correlated with cooking loss. The most significant color changes were found in deep-fried pork, whose elasticity, cohesiveness and shear force were significantly different compared with the other treated groups. Protein carbonyl content was significantly higher in microwaved pork than the other treated groups (P < 0.05). Roasted pork exhibited the highest TBARS value. Electronic nose results showed an increase in the content of volatile flavor substances after thermal processing, and electronic tongue results indicated that the umami intensity of deep-fried pork was the highest. The results of this study can provide reference for the selection of pork thermal processing methods.

Immunotherapy has become a common means of cancer treatment. In immunotherapy, PD-1/PD-L1 inhibitors have significant efficacy. Cancer and various opportunistic infections are common complications in patients with AIDS. Owing to the special immune situation of these patients, AIDS is regarded as an exclusion standard in most clinical trials for cancer immunotherapy, conferring immunotherapy difficulty in treating patients with AIDS. The popularity of effective antiretroviral drugs has prolonged the lifetime of people with AIDS. Therefore, exploiting the opportunity of using immunotherapy in AIDS with cancer is urgent.

Abstract Designing novel catalysts is key to solving many energy and environmental challenges. Despite the promise that data science approaches, including machine learning (ML), can accelerate the development of catalysts, truly novel catalysts have rarely been discovered through ML approaches because of one of its most common limitations and criticisms—the assumed inability to extrapolate and identify extraordinary materials. Herein, we demonstrate an extrapolative ML approach to develop new multi-elemental reverse water-gas shift catalysts. Using 45 catalysts as the initial data points and performing 44 cycles of the closed loop discovery system (ML prediction + experiment), we experimentally tested a total of 300 catalysts and identified more than 100 catalysts with superior activity compared to those of the previously reported high-performance catalysts. The composition of the optimal catalyst discovered was Pt(3)/Rb(1)-Ba(1)-Mo(0.6)-Nb(0.2)/TiO2. Notably, niobium (Nb) was not included in the original dataset, and the catalyst composition identified was not predictable even by human experts.

This paper innovatively proposes a method of 180 °C high-temperature stirring pretreatment for waste rubber particles and compares this method with untreated, NaOH-treated, and silane coupling agent KH570-treated waste rubber particles. Fourier-transform infrared spectroscopy, X-ray diffraction analysis, water contact angle measurement, scanning electron microscopy, and energy-dispersive X-ray study are used to investigate the effects and mechanisms of different pretreatment methods on waste rubber particles. The results indicate that compared to NaOH-treated and KH570-treated waste rubber particles, the 180 °C high-temperature-stirred pretreated waste rubber particles show significantly improved cleanliness and form a hard oxide film. The study also investigates the effects of different pretreatment methods on the mechanical properties and interface binding performance of rubber concrete made from pretreated waste rubber particles. The results demonstrate that rubber concrete prepared using 180 °C high-temperature-stirred pretreated waste rubber particles substituting 20% fine aggregate exhibits the best mechanical properties and interface bonding performance. The compressive strength recovery rates after 7 and 28 days are 41.6% and 37.3%, respectively; the split tensile strength recovery rates are 47.3% and 60.6%; the axial compressive strength recovery rates are 34.1% and 18.8%; and the static compression moduli of elasticity recovery rates are 46.8% and 26.3%. High-temperature stirring pretreatment of waste rubber particles is simple to operate and suitable for scaled production. Its pretreatment effect is superior to those of the KH570 and NaOH methods, providing a reference value for the scalable application of waste rubber particles as a substitute for fine aggregate in rubber concrete.

The micro-cracks in a material lead to a reduction in its overall strength and service life. The emerging capsule-based self-healing system provides a new strategy for repairing the cracks, effectively delaying the potential damage of the matrix, and prolonging the service life of composite materials. Determining the optimal size and dosage of microcapsules required to repair cracks in the matrix is essential for the development and design of capsule-based self-healing materials. This paper presents a novel two-dimensional capsule-based self-healing model composite material whose surface is paved by reproducible and random cells and some microcapsules are randomly dispersed in those cells to investigate the rupture behavior of microcapsules forced by growing cracks. An analytical model is proposed from the viewpoint of geometrical probability to express the probability characteristics of the embedded microcapsules stimulated by linear cracks in a two-dimensional capsule-based self-healing model composite. Additionally, the effect of the size and dosage of the embedded microcapsules on the intersection probability is analyzed, and the maximal probability is also found to improve the self-healing efficiency. Finally, the accuracies of these probability values and theoretical solutions are verified via computer simulation, and the results show that the developed model of the geometrical probability of the crack intersection with microcapsules randomly distributed in the cells of the matrix will help to provide a theoretical basis for the quantitative design of capsule-based self-healing materials.

In order to solve the problem of locomotive failure caused by the fault of grid-side grounding due to misinformation of grid-side current signal in the application of AC locomotive, a real-time diagnosis method for grid-side current signal anomalies based on multi-operating condition nonlinear model is proposed in this paper. Firstly, based on the system mechanism and engineering design experience, the variables strongly related to grid-side current are extracted, and a multi-operating condition nonlinear estimation model of grid-side current is established. Secondly, based on the two redundant grid-side current signals of the traction drive system and the estimated value of the grid-side current, residual and detection statistics were designed, and the effective fault detection and decision-making of the two grid-side current signal anomalies are achieved by combining the CUSUM algorithm. Finally, different fault-tolerant control strategies are adopted according to the fault decision-making results to ensure the normal control and protection functions of the system. Field data tests show that the proposed diagnostic method achieves timely detection and precise positioning of grid-side anomalies 0.3 s after the occurrence of anomalies, avoiding the impact of on-site faults caused by grid-side signal anomalies.

Objective To investigate the effects and mechanisms of monoacylglycerol lipase (MGLL) in tumor-associated macrophages (TAMs) for the progression of colorectal cancer peritoneal metastases (CRC-PM). Methods After macrophage MGLL conditional knockout (cKO) mice was constructed, a CRC-PM model was established in these cKO mice. The effects and mechanism of MGLL deficiency on TAMs were studies with cell biological and RNA-Seq assays. Results Compared with the control mice, macrophage MGLL deficiency significantly shortened the survival time of CRC-PC mice (P < 0.05), increased the weight of peritoneal tumor masses (P < 0.05), diminished the percentage of T cells in the tumor microenvironment (P < 0.01), while elevated the percentage of M2 macrophages in cKO mice (P < 0.05). And the results of RNA-seq showed that TRLs, PD-1/PDL-1, and HIF-1 signal pathways were significantly changed in MGLL deficiency macrophages. Conclusion In the process of CRC-PC, MGLL deficiency leads to macrophage activation towards an M2-type phenotype and further destroys T cell-based anti-tumor immunity capacity, and ultimately promotes the progression of CRC-PC. The mechanisms may be due to the changes in TRLs, PD-1/PDL-1, and HIF-1 signal pathways.

The pull-out method is a simple and effective method for detecting the preload of suspension bridge cable clamp bolts. However, research on the pull-out method is currently limited. The force principles governing the bolt during the pulling process are unclear, and the relationship between tension force and the desired preload remains uncertain. This paper aims to explore the force principles of bolts during the pull-out method detection process through a combined approach of theoretical analysis, full-scale test, and finite element simulation. The results indicate that the bolt preload increases during the pulling process. The preload detected by the pull-out method is not the initial preload of the bolt, but rather it exceeds the initial preload. The force relationships among various components are determined as follows: the preload subtracts the change value of the force exerted by the nut at the tension end, which equals the change value of tension force. Additionally, an analysis of the impact of the length of the bolt clamping section and the bolt area on the preload was conducted. Under the same bolt area, a shorter clamping section length corresponds to a greater increase in preload. With the same clamping section length, the increment of preload increases with the bolt area. These findings can serve as references for detecting and specifying the preload of the bolts.

The quality of crops is closely associated with their geographical location and yield, which is reflected in the composition of their metabolites. Hence, we employed GC–MS pseudotargeted metabolomics to investigate the metabolic characteristics of high-, medium-, and low-yield Nicotiana tabacum (tobacco) leaves from the Bozhou (sweet honey flavour) and Shuicheng (light flavour) regions of Guizhou Province. A total of 124 metabolites were identified and classified into 22 chemical categories. Principal component analysis revealed that the geographical location exerted a greater influence on the metabolic profiling than the yield. Light-flavoured tobacco exhibited increased levels of sugar metabolism- and glycolysis-related intermediate products (trehalose, glucose-6-phosphate, and fructose-6-phosphate) and a few amino acids (proline and leucine), while sweet honey-flavoured tobacco exhibited increases in the tricarboxylic acid cycle (TCA cycle) and the phenylpropane metabolic pathway (p-hydroxybenzoic acid, caffeic acid, and maleic acid). Additionally, metabolite pathway enrichment analysis conducted at different yields and showed that both Shuicheng and Bozhou exhibited changes in six pathways and four of them were the same, mainly C/N metabolism. Metabolic pathway analysis revealed higher levels of intermediates related to glycolysis and sugar, amino acid, and alkaloid metabolism in the high-yield samples, while higher levels of phenylpropane in the low-yield samples. This study demonstrated that GC–MS pseudotargeted metabolomics-based metabolic profiling can be used to effectively discriminate tobacco leaves from different geographical locations and yields, thus facilitating a better understanding of the relationship between metabolites, yield, and geographical location. Consequently, metabolic profiles can serve as valuable indicators for characterizing tobacco yield and geographical location.

Procrastination is considered a result of failed self-regulation. However, could experiencing a sense of successful self-discipline help to boost motivation and reduce procrastination? To explore this question, two studies were conducted to investigate the relationship between the sense of self-discipline, autonomous motivation, and procrastination. Results showed that trait sense of self-discipline negatively predicted general procrastination (Study 1); self-discipline primed participants procrastinated less than the control group (Study 2); autonomous motivation mediated the relationship between sense of self-discipline and procrastination (Study 1 and Study 2). These findings suggest that cultivating a sense of self-discipline can have positive effects on both autonomous motivation and procrastination, and provide useful guidance for interventions aimed at reducing procrastination.

Objective To investigate the plateaued count of CD4+ T cells in human immunodeficiency virus (HIV)-infected patients after long-term antiretroviral therapy (ART) and its influencing factors. Methods All HIV-infected patients receiving continuous ART for >8 years till December 2021 and with HIV RNA < 200 copies/mL in the Infection Department of Chongqing Public Health Medical Treatment Center were recruited and subjected as research object. Their age, ART scheme and CD4+ T count at each time point were collected retrospectively, the growth of CD4+ T count was counted, and the factors affecting CD4+ T count in the plateau stage were analyzed. Results A total of 766 patients who receiving ART for longer than 8 years were included in this study. The median plateaued count of CD4+ T cells was 394.0 (292.0, 507.0)/μL. There were 66 (8.6%) patients of suboptimal immune responders (SIR) with CD4+ T count < 200/μL, 458 (59.8%) with the count ≥350/μL, and 198 (25.8%) ≥500/μL. Based on baseline CD4+ T count (< 200, 200~349, 350~499, and ≥500/μL), the patients were divided into 4 groups and significant differences were seen in CD4+ T count and its increase from baseline in each group (P < 0.05). The teenager group had obviously higher plateaued count of CD4+T cells [403 (306, 519)/μL] than the middle-aged and elderly group (P < 0.05). Univariate analysis showed that the proportion of patients older than 44 years was notably larger (P < 0.01), and that of patients with baseline CD4+ T count < 100/μL was also higher (54.5% vs 17.6%, P < 0.05) in the severe SIR group than the non-severe SIR group. Multivariate analysis indicated that age over 44 years old (OR=2.061, 95%CI: 1.157~3.672) and baseline CD4+ T count < 100/μL (OR=4.803, 95%CI: 2.767~8.340) were associated with severe SIR in plateau stage (P < 0.05). Conclusion The plateaued count of CD4+ T cells in HIV-infected patients is generally low in plateau stage. In middle-aged and elderly patients, those with baseline CD4+ T count < 100/μL at initiation of ART is at higher risk for severe SIR in plateau stage. Early screening and early treatment are the key points to prevent and control the occurrence of severe SIR.

Background: E-skin (electronic skin) is an active research area in human-computer interaction and artificial intelligence.Methods: A bibliometric analysis was performed to evaluate publications in the E-skin field between 2000 and 2021 based on the Web of Science (WoS) databases.Results: A total of 4,954 documents were identified. A detailed overview of E-skin research was presented from aspects of productive countries/regions, institutions, journals, citations, highly cited papers, keywords, and emerging topics. With the emergence of new functional materials, structural design, 3D printing, and nanofabrication techniques, E-skin research has achieved dramatic progress after 2013. Scholars and institutions in China, the United States and South Korea are leading the way in E-skin research. Pressure sensor, strain sensor, and flexible electronics are the most focused directions at present and Internet of things is the most emerging topic.Conclusion: E-skin research has achieved dramatic progress but there is still quite a challenging task in practical applications. Manufacturing process simplification, cost reduction, functional integration, energy supply, and biocompatibility are vital for the future development of E-skin.

Abstract To explore the differentially expressed genes (DEGs) and potential therapeutic targets of skin aging in GEO database by bioinformatics methods. Dermal fibroblasts and skin aging related data sets GSE110978 and GSE117763 were downloaded from GEO database, and epidermal stem cells and skin aging related data sets GSE137176 were downloaded. GEO2R was used to screen DEGs of candidate samples from the three microarrays, GO function analysis and KEGG pathway analysis were performed. Protein interaction network was constructed using String database, and hub gene was obtained by Cytoscape. NetworkAnalys was used to analyze the coregulatory network of DEGs and MicroRNA (miRNA), interaction with TF, and protein-chemical interactions of DEGs. Finally, DSigDB was used to determine candidate drugs for DEGs. Six DEGs were obtained. It mainly involves the cytological processes such as response to metal ion, and is enriched in mineral absorption and other signal pathways. Ten genes were screened by PPI analysis. Gene-miRNA coregulatory network found that Peg3 and mmu-miR-1931 in DEGs were related to each other, and Cybrd1 was related to mmu-miR-290a-5p and mmu-miR-3082-5p. TF-gene interactions found that the transcription factor UBTF co-regulated two genes, Arhgap24 and Mpzl1. Protein-chemical Interactions analysis and identification of candidate drugs show results for candidate drugs. Try to explore the mechanism of hub gene action in skin aging progression, and to discover the key signaling pathways leading to skin aging, which may be a high risk of skin aging.

Objective To explore whether cognitive frailty increases the risk of falls 5 years later in elderly Chinese population. Methods The data were collected from the Rugao Aging Cohort. Fried frailty phenotype was used to evaluate frailty. Those who met ≥3 of the five criteria were defined as frailty, those who met 1-2 criteria were defined as pre-frailty, and those who did not meet any criteria were considered to be robust. The revised Hasegawa Dementia Scale(HDS-R) was used to evaluate cognitive function. Excluding severe cognitive impairment (HDS-R≤10), the lowest quartile of scores was cognitive impairment. Those with both frailty and cognitive impairment were defined as cognitive frailty. Binary logistic regression was used to analyze frailty and falls risk at 5-year follow-up, and explore the effect of cognitive frailty (frailty plus cognitive function assessment) on falls risk. Results This study included 962 subjects with a mean age of 74.7±3.7 years at baseline, including 526 females. After 5 years of follow-up, 134 people experienced falls in the last year of following up . The incidence of falls was higher in female, illiterate and unmarried subgroups. Logistic regression analysis showed that the frail subjects at baseline were more likely to fall(OR=4.360,95% CI=1.955-9.722), and those with cognitive frailty had a higher risk of fall than those robust without cognitive impairment (OR=6.000,95% CI=1.935-18.603). After adjusting for covariates, the higher five-year falls risk for cognitive frailty remained statistically significant (OR=6.736,95% CI=1.897-23.922, P＜0.05). Conclusions Cognitive frailty is significantly correlated with a higher risk of falls after 5 years. The assessment of cognitive frailty is important for assessing the risk of falls in older adults.

Abstract There has been a growing interest in oil–water separation due to the massive economic and energy loss caused by world-wide oil spill. In the past decades, a new type of superhydrophobic surface has been developed for the efficient oil–water separation, but its large-scale use is significantly limited by its expensive, sophisticated, and fragile roughness structure. Meanwhile, to handle complex operating conditions, the transparency of the superhydrophobic surface has been more attractive due to its potential visual oil–water separation and optical application scenarios. Herein, we showed a simple and versatile strategy to fabricate superhydrophobic coating with robustness and high transparency. Subsequently, this multifunctional superhydrophobic coating was utilized for oil–water separation and indicated excellent separation efficiency. In this strategy, candle soot composed of carbon nanoparticles was deposited onto the substrate and used as a rough surface template. Then, a filmy and hard silica shell was modified onto this template via chemical vapor deposition to reinforce the roughness structure. Following, this soot-silica coated substrate was calcined in air to remove the candle soot template. Finally, based on a rational surface design, this robust silica coating achieved excellent superhydrophobicity thereby showing inherently oil–water separation benefits. This reinforced superhydrophobic coating presented robust superhydrophobicity even after 410 s sand impacting with the height of 40 cm and 20 cycles of sandpaper abrasion. Also, it retained excellent oil–water separation efficiency even after reuses.

Abstract Background Automated ICD coding on medical texts via machine learning has been a hot topic. Related studies from medical field heavily relies on conventional bag-of-words (BoW) as the feature extraction method, and do not commonly use more complicated methods, such as word2vec (W2V) and large pretrained models like BERT. This study aimed at uncovering the most effective feature extraction methods for coding models by comparing BoW, W2V and BERT variants. Methods We experimented with a Chinese dataset from Fuwai Hospital, which contains 6947 records and 1532 unique ICD codes, and a public Spanish dataset, which contains 1000 records and 2557 unique ICD codes. We designed coding tasks with different code frequency thresholds (denoted as $$f_s$$ f s ), with a lower threshold indicating a more complex task. Using traditional classifiers, we compared BoW, W2V and BERT variants on accomplishing these coding tasks. Results When $$f_s$$ f s was equal to or greater than 140 for Fuwai dataset, and 60 for the Spanish dataset, the BERT variants with the whole network fine-tuned was the best method, leading to a Micro-F1 of 93.9% for Fuwai data when $$f_s=200$$ f s = 200 , and a Micro-F1 of 85.41% for the Spanish dataset when $$f_s=180$$ f s = 180 . When $$f_s$$ f s fell below 140 for Fuwai dataset, and 60 for the Spanish dataset, BoW turned out to be the best, leading to a Micro-F1 of 83% for Fuwai dataset when $$f_s=20$$ f s = 20 , and a Micro-F1 of 39.1% for the Spanish dataset when $$f_s=20$$ f s = 20 . Our experiments also showed that both the BERT variants and BoW possessed good interpretability, which is important for medical applications of coding models. Conclusions This study shed light on building promising machine learning models for automated ICD coding by revealing the most effective feature extraction methods. Concretely, our results indicated that fine-tuning the whole network of the BERT variants was the optimal method for tasks covering only frequent codes, especially codes that represented unspecified diseases, while BoW was the best for tasks involving both frequent and infrequent codes. The frequency threshold where the best-performing method varied differed between different datasets due to factors like language and codeset.

Social network has become an integral part of our daily life.Sentiment analysis of social media information is helpful to understand people's views,attitudes and emotions on social networking sites.Traditional sentiment analysis mainly relies on text.With the rise of smart phones,information on the network is gradually diversified,including not only text,but also images.It is found that,in many cases,images can enhance the text rather than express emotions independently.We propose a novel image text sentiment analysis model (LSTM-VistaNet).Specifically,this model does not take the picture information as the direct input,but uses the VGG16 network to extract the image features,and then generates the visual aspect attention,and gives the core sentences in the document a higher weight,and get a document representation based on the visual aspect attention.In addition,we use the LSTM network to extract the text sentiment and get the document representation based on text only.Finally,we fuse the two groups of classification results to obtain the final classification label.On the Yelp restaurant reviews data set,our model achieves an accuracy of 62.08%,which is 18.92% higher than BiGRU-mVGG,which verifies the effectiveness of using visual information as aspect attention assisted text for emotion classification;It is 0.32% higher than VistaNet model,which proves that LSTM model can effectively make up for the defect that images in VistaNet model cannot completely cover text.

Abstract A smart liquid gating membrane is a responsive structural material as a pressure‐driven system that consists of solid membrane and dynamic liquid, responding to the external field. An accurate prediction of rheological and mechanical properties is important for the designs of liquid gating membranes for various applications. However, high predicted accuracy by the traditional sequential method requires a large amount of experimental data, which is not practical in some situations. To conquer these problems, artificial intelligence has promoted the rapid development of material science in recent years, bringing hope to solve these challenges. Here we propose a Kriging machine learning model with an active candidate region, which can be smartly updated by an expected improvement probability method to increase the local accuracy near the most sensitive search region, to predict the mechanical and rheological performance of liquid gating system with an active minimal size of experimental data. Besides this, this new machine learning model can instruct our experiments with optimal size. The methods are then verified by liquid gating membrane with magnetorheological fluids, which would be of wide interest for the design of potential liquid gating applications in drug release, microfluidic logic, dynamic fluid control, and beyond.

Background: Artificial muscles are an active research area now.Methods: A bibliometric analysis was performed to evaluate the development of artificial muscles based on research papers and patents. A detailed overview of artificial muscles’ scientific and technological innovation was presented from aspects of productive countries/regions, institutions, journals, researchers, highly cited papers, and emerging topics.Results: 1,743 papers and 1,925 patents were identified after retrieval in Science Citation Index-Expanded (SCI-E) and Derwent Innovations Index (DII). The results show that China, the United States, and Japan are leading in the scientific and technological innovation of artificial muscles. The University of Wollongong has the most publications and Spinks is the most productive author in artificial muscle research. Smart Materials and Structures is the journal most productive in this field. Materials science, mechanical and automation, and robotics are the three fields related to artificial muscles most. Types of artificial muscles like pneumatic artificial muscles (PAMs) and dielectric elastomer actuator (DEA) are maturing. Shape memory alloy (SMA), carbon nanotubes (CNTs), graphene, and other novel materials have shown promising applications in this field.Conclusion: Along with the development of new materials and processes, researchers are paying more attention to the performance improvement and cost reduction of artificial muscles.

Bladder paraganglioma (BPG) is a rare extra-adrenal pheochromocytoma with variable symptoms and easy to be misdiagnosed and mishandled. The aim of the study was to document the imaging features of BPG using computed tomography (CT) and magnetic resonance imaging (MRI).

In the present scenario of development in technology, the applications of stretchable conductive elastomers in modern electronic equipments have aroused great interest. Non-covalent bonding modification of carbon nanotubes (CNTs) using dopamine has improved the dispersion of CNT@PDA and interfacial interaction with the rubber matrix. The SiO2@Ag core-shell particles were prepared by coated with silver nanoparticles (AgNPs) on the surface of SiO2 using dopamine oxidation self-polymerization and electroless plating process. ESBR composites were prepared by latex co-coagulation method, where CNT@PDA and SiO2@Ag were used to develop an 1D-3D synergistic conductive network in ESBR composites. One-dimensional (1D) CNT@PDA were incorporated in three-dimensional (3D) spherical SiO2@Ag core-shell particles, which effectively prevented the agglomeration of SiO2@Ag and CNT@PDA. Again, 1D CNT@PDA could also be used as bridges to interact with 3D SiO2@Ag to develop the charge transfer more effectively in ESBR composites. The optimum electrical conductivity of the ESBR/CNT@PDA/SiO2@Ag composites was 0.2 S/cm, which was found to be higher than that of single filler. Moreover, the high electrical conductivity can be controlled at low tensile strain. The mechanical property of ESBR/CNT@PDA/SiO2@Ag composite was also improved by 105.4% as compared by ESBR/CNTs. This work provides a new idea for the fabrication of stretchable conductive elastomer composites with high performance.

The accuracy of uncertainty analysis in suspension systems is closely tied to the precision of the probability distribution of sprung mass. Consequently, traditional assumptions regarding the probability distribution fail to guarantee the accuracy of uncertainty analyses results. To achieve more precise uncertainty analysis outcomes, this paper proposes a data-driven approach for analyzing the uncertainties in bus air suspension systems. Firstly, a bus vehicle dynamics model is established to investigate the influence of sprung mass on suspension system performance. Subsequently, a deep neural network model is trained using road test data, for the accurate identification of the sprung mass. The historical mass of the bus is then computed using vehicle network data to obtain the true probability density of the sprung mass. Lastly, the real probability distribution of the sprung mass is utilized to perform uncertainty analysis on the bus suspension system, and the results are compared with those obtained by assuming a probability distribution. Comparative analysis reveals substantial disparities in uncertainty response, with a maximum relative error of 9% observed for wheel dynamic loads, thus emphasizing the significance of precise probability distribution information concerning the sprung mass.

Objective To explore the epidemiological characteristics of motoric cognitive risk syndrome (MCR) in Chinese elderly and its relationship with hospitalization. Methods Data were collected from a subcohort of the rugao longevity and aging study. Subjective memory complaints were assessed by the geriatric depression scale (GDS-15), and slow gait was assessed by the time up and go test (TUGT). MCR was determined by the presence of both. The incidence of hospitalization was recorded from the baseline survey in 2014 to the second 3-year follow-up in 2017, and the incidence of MCR in the hospitalized and non-hospitalized groups was compared to analyze the association between MCR and hospitalization. Results In this study, 1 076 subjects were enrolled, with an average age of 75.0±3.8 years old; The prevalence of MCR was 3.3%. During the 3-year follow-up period, 61.1% of the MCR group had records of hospitalization, while only 41.9% of the non-MCR group had the record of hospitalization (P＜0.05). The hospitalized group had a higher average age, and a higher proportion of men, non-illiterates, and those with hypertension, diabetes, and cerebrovascular disease. Hospital combination and the proportion of MCR is 4.8%, the hospital group was 2.3% (P＜0.05). After adjusting for age, sex, occupation, level of education, marital status, smoking status, BMI, blood pressure, diabetes and coronary heart disease, cerebrovascular disease, and other confounding factors, MCR is associated with increased risk of hospitalization in the elderly (P＜0.05). Conclusions The incidence of hospitalization was higher in the population of male especiall those with hypertension, diabetes and cerebrovascular history, MCR is significantly associated with hospitalization.

Hyperhomocysteinemia (HHcy) plays an important role in the progression of many kidney diseases; however, the relationship between HHcy and ischemia-reperfusion injury (IRI)-induced acute kidney injury (IRI-induced AKI) is far from clear. In this study, we try to investigate the effect and possible mechanisms of HHcy on IRI-induced AKI.

ObjectiveTo analyze the mental health status and the influencing factors among the residents taking standardized residency training during the outbreak and stable period of COVID-19， so as to provide theoretical basis for their mental health education.MethodsOn February 8 to February 10 and April 11 to April 13， 2020， Symptom Checklist 90 （SCL-90）， Beck Srivastava Stress Inventory （BSSI） and Simplified Coping Style Questionnaire （SCSQ） were distributed in online chat groups involving all grades of residents taking standardized residency training in the Second Affiliated Hospital of Kunming Medical University. Through two rounds of questionnaire survey， non-probability sampling method was used to obtain survey samples， and their mental status were analyzed.ResultsA total of 159 valid questionnaires were collected in the first round， and 99 valid questionnaires in the second round. The first survey showed that the total score of SCL-90 was （117.69±37.74） and the detection rate of positive symptoms in SCL-90 was 25.8%， and mainly dominated by obsession， fear and interpersonal sensitivity. In the second survey， the results showed that the total score of SCL-90 was （127.19±51.44）， and the main positive symptoms included obsession， depression and interpersonal sensitivity， with a positive detection rate of 30.3 %. The first survey found that the mental health status had significant differences among residents of different grades （χ2=7.46， P

Cerebral small-vessel disease (CSVD) is the main cause of vascular cognitive impairment (VCI), and the accumulation of amyloid β-protein (Aβ) may be significantly involved in CSVD-induced VCI. The imbalance between Aβ production and clearance is believed to be an important pathological mechanism of Aβ deposition in Alzheimer disease. In this study, we aimed to disclose the roles of aquaporin 4 (AQP4) and neuroinflammation in CSVD, which were the key factors for Aβ clearance and production, respectively, and the effect of mesenchymal stem cells (MSCs) on Aβ deposition and these two factors. The stroke-prone renovascular hypertensive (RHRSP) rats were grouped and received MSC and MSC + AS1517499 (an inhibitor of pSTAT6). The latter was used to explore the underlying mechanism. The cognitive function, white matter lesions, Aβ expression, expression, and polarity of AQP4, neuroinflammation and the STAT6 pathway were investigated. Compared with sham-operated rats, RHRSP rats showed spatial cognitive impairment, white matter lesions and Aβ deposition. Moreover, AQP4 polarity disorder and neuroinflammatory activation were found, which were linked to Aβ deposition. Treatment with MSCs markedly improved cognitive tasks and reduced Aβ deposition but failed to reduce white-matter lesions. Furthermore, MSCs not only promoted AQP4 polarity but also alleviated neuroinflammation probably through the STAT6 pathway. The present study demonstrated that Aβ deposition, AQP4 polarity disorder and neuroinflammation might be involved in CSVD and the regulatory effects of MSCs on them suggested potential therapeutic value for CSVD.

BACKGROUND The quantification of trace elements in geological samples depends largely on the analytical methods that require complex chemical pretreatment. High-energy polarized energy-dispersive X-ray fluorescence spectrometry (HE-P-EDXRF) has a considerable advantage for the determination of trace elements with large atomic numbers, due to its high-energy properties, which can effectively excite the Kα line of heavy elements. OBJECTIVES To establish a HE-P-EDXRF method for quantitative analysis of major and trace elements in geological samples. METHODS HE-P-EDXRF was used to establish an analysis method for major and trace elements in soil, rock and water system sediments. The selection of analysis lines, line overlap interference correction and matrix correction modes were discussed. Uncertainty was used to evaluate the method. RESULTS The Kα line was selected as the analysis line for trace elements with a larger atomic number due to less interference from the spectral line overlap, which is beneficial to obtaining the net peak intensity. Rare earth elements such as La, Ce and Nd can be accurately measured. Detection limits of the trace element Ba and rare earth elements such as La, Ce determined by EDXRF were greater than those determined by WDXRF, but lesser for light elements. For all the major and trace elements, the average of relative error of test training data was less than 15% except for Na2O, MgO, P and Sm. The average relative error of trace elements was between 2.40% and 16.3%. The accuracy of trace elements (except Cu and Yb) was significantly better than that of WDXRF. According to the evaluation method of the Europe Union, no significant difference existed between the trace elements results (except V and Th) and the recommended value of certified reference materials. CONCLUSIONS HE-P-EDXRF is a simple, fast and environmentally-friendly method that can simultaneously analyze multiple elements in geological samples. This method is suitable for quantification of the trace and rare earth elements in rock, soil and sediment, which overcomes the dependence of quantitative analysis of rare earth and trace elements in geological samples on the need for methods requiring complex chemical pretreatment.

The dynamic response of a prestressed concrete box girder bridge under the impact of an over-height vehicle is studied using the numerical simulation method. The finite element analysis software LS-DYNA is used to simulate the collision between the bridge superstructure and an over-height truck. Further, a parametric analysis is carried out to investigate the influence of six factors, i.e., girder configuration, vehicle speed, vehicle mass, impact angle, concrete strength and strand prestress, on both local damage and overall performance of the bridge. The numerical analysis results show that the girder configuration, vehicle speed, vehicle mass and impact angle have obvious effects on both local damage and the overall behavior of the PC box girder bridge. Whereas, the concrete strength and strand prestress only have a certain effect on the local damage at the impact area with very limited influence on the overall behavior of the bridge. In addition, based on the results obtained from the numerical simulation and parametric analysis, a formula for predicting the peak and average impact force of the prestressed concrete box girder bridge under the over-height vehicle impact is developed. The proposed impact force formula comprehensively accounts for the influence of the vehicle speed, vehicle mass and impact angle and can accurately predict the impact force generated under different working conditions, which confirms the promising prospect of the proposed formula in practical applications.

Taking a commercial building in Shanghai as an example, a list of cooling and heating systems are established and operation strategies are formulated. Based on the precondition that the excess electricity can be sold to the grid, the primary energy utilization rate and economices of the energy supply schemes are analyzed. The results show that compared with the traditional heating and cooling supply method, the combined cooling, heating, and power systems have better energy-saving and economic benefits. Additionally, the inclusion of the thermal energy storage yields additional economic benefits (up to 36% reduction in the CO2eq emissions and up to the 21% reduction in the total annual cost). Under the following-electric-load operation mode, the role of the thermal energy storage is to alleviate the temporal mismatch between the electric demand and the heating or cooling demand. To be specific, in the combined cooling, heating, and power systems, the total annual cost is reduced by up to 5.8% and the annual carbon dioxide equivalent emissions are reduced by up to 2.4% when the thermal energy storage is used. While under the following-electric-price operation mode, the performance of the CCHP system is largely subject to the natural gas price. Last, although heat pump systems are often regarded as efficient systems owing to the relatively high coefficient of performance of the heat pump, the energy supply through the heat pump systems may be carbon-emission-intensive currently.

A new fracture model is developed to predict the ductile fracture of structural steel under multiaxial stress states. First, the Lee–Mear void growth theory is used to establish the quantitative relationship between the stress triaxiality and material’s ductility. A stress triaxiality dependence function, which accounts for the material’s strain hardening, is derived from modifying the dilatation rate of a spherical void in a typical unit cell. Subsequently, the Tresca failure model is used in conjunction with the Swift hardening law to establish a Lode dependence of fracture strain. Then, the theoretical formula of the new fracture model is obtained by combining both stress triaxiality and Lode angle dependence functions. The proposed fracture model has a unique advantage: i.e., this model has only two material parameters. These two parameters can be easily calibrated through a simple standard coupon test, which significantly reduces the difficulty of model calibration work and facilitates its application in practical engineering. In order to verify the new fracture model, the test results of five types of Q460 steel specimens were used to calibrate the model parameters. The prediction accuracy of the new model is then checked by calculating the average error between the test results and the predicted fracture strain envelope. Finally, the new fracture model was applied in the numerical analysis of two types of steel connections. The validation of the proposed fracture model is verified by comparing the load–displacement curve and failure modes of the steel connections obtained from both test and numerical analysis.

In the previous studies on the microstructure and orientation of titanium alloys, the microstructural and orientational evolution of typical titanium alloys during thermal compression have been studied in depth. However, studies of the correlation between hot compression and heat treatment processes on microstructural and orientational changes have been few. It is of great significance to further study this correlation during hot treatment. For this study, during hot compression deformation and subsequent hot treatment of TC17 titanium alloy on a thermal simulator using cylindrical specimens, the microstructure, grain size change, and orientation evolution of TC17 were studied using optical microscopy and backscattered electron diffraction analysis. Grain size, texture distribution, pole figure, and reverse polarity were analyzed. Law and the relation between structure and orientation results show that the primary α-content decreases dramatically and size decreases in tandem with deformation temperature. Most of the α phase grains are dispersed and located on the trigeminal grain boundaries of the high temperature β phase grains. After heat treatment, the α phase and β phase had a clear structure and distinct boundary. The primary α phase still exists and tends to be equiaxed, and the metastable β phase changes formed a lamellar β-transformed structure. The hot deformation reduces the density of the α phase texture. Additionally, with increasing temperature, the density value of the α phase texture also becomes small. The α phase is no longer strongly textured after thermal deformation, and the orientation of the α phase grains is considerably influenced by thermal deformation, which clearly improves the uniformity of orientation. The thermal deformation also reduces the texture polar density value of the β phase, but the effect is not obvious. However, there is still a density of orientation, and the uniformity of the orientation is relatively poor.

Recently, the research of WiFi-based indoor localization combing with deep-learning techniques has earned wide attention due to its potential applications in smart cities. In this paper, a novel fingerprinting system is proposed to achieve indoor localization via learning spatiotemporal features from channel state information (CSI) of multiple-input multiple-output wireless channels (CSI-MIMO) by a dual-stream three-dimensional (3D) convolutional neural network (DS-3DCNN). In the proposed system, the gathered raw CSI-MIMO data are firstly preprocessed through amplitude outliers elimination and phase sanitization for constructing a pair of 3D CSI-MIMO matrices including a 3D amplitude matrix and a 3D phase matrix. Next, the 3D matrices will be input to the DS-3DCNN deep neural network which consists of two parallel subnetworks with specific architecture of several convolution, batch normalization, max-pooling, and fully connected layers. Through this DS-3DCNN network, learning spatiotemporal features of CSI-MIMO is carried out simultaneously from 3D amplitude and phase matrices. And then, probabilistic classification results of two subnetworks are fused in the final output layer of the proposed DS-3DCNN based on Bayes' theorem. Moreover, in the offline training stage, a dual-stream joint optimization method is presented for efficiently optimizing network parameters. After offline training of the DS-3DCNN, in the online locating stage, current CSI-MIMO data are firstly collected from the mobile device to be located. Then probabilistic classification results are obtained from the output layer of the DS-3DCNN, and further used to approximate the posterior distribution of the mobile device's location with a Gaussian mixture model. Finally, a novel location estimation algorithm is deduced based on the minimum mean square error (MMSE) criterion. Since unique features of wireless MIMO channels are jointly learnt in spatial, temporal, and frequency domains, the proposed DS-3DCNN based fingerprinting system is reasonable to provide accurate localization results in indoor environments, which is verified in corresponding experiments.

Crop genetics: novel gene involved in tomato ripening Chinese researchers have identified a new gene which regulates the ripening of tomatoes. Several genes known to control tomato ripening are members of the NAC family of regulators. To identify others, a team led by Daqi Fu of China Agricultural University blocked the expression of candidate NAC genes. The discovered that silencing NOR-like1 repressed ripening, leaving the tomatoes partially green. The team also engineered plants with defective copies of NOR-like1 and found that this delayed ripening and eventually resulted in partially ripe fruit and impaired seed development. RNA sequencing of these lines revealed that NOR-like1 directly regulates genes involved in ethylene synthesis, carotenoid accumluation, chlorophyll metabolism, and cell wall breakdown. These findings clearly demonstrate a key role for NOR-like1 as a positive regulator of tomato ripening and a potential tool for controlling this important process.