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This study aims to explore the problem of $ H_{\infty} $ fuzzy control with an adjustable convergence rate for switched nonlinear systems with time-varying delays under the persistent dwell time (PDT) switching. Compared to the widely studied dwell time (DT) switching or average dwell time (ADT) switching in existing literature, PDT switching provides a more comprehensive consideration of the switching frequency and has a broader range of applicability. Subsequently, by combining the interval stability definition, T-S fuzzy model, PDT technique, and Lyapunov-Krasovskii (L-K) functional, a new $ H_{\infty} $ fuzzy control criterion for adjusting the convergence rate of switched nonlinear systems with time-varying delays is proposed. This criterion enables the development of a novel method for constructing $ H_{\infty} $ fuzzy controllers, which can regulate the system's convergence rate and achieve the specified $ H_{\infty} $ performance. Combining the above methods, an algorithm is introduced to precisely control the convergence rate of the target system. Finally, the effectiveness of this method is validated through a control example of a single-link robot arm.

Adult mammals, unlike some lower organisms, lack the ability to regenerate damaged hearts through cardiomyocytes (CMs) dedifferentiation into cells with regenerative capacity. Developing conditions to induce such naturally unavailable cells with potential to proliferate and differentiate into CMs, that is, regenerative cardiac cells (RCCs), in mammals will provide new insights and tools for heart regeneration research. In this study, we demonstrate that a two-compound combination, CHIR99021 and A-485 (2C), effectively induces RCCs from human embryonic stem cell-derived TNNT2+ CMs in vitro, as evidenced by lineage tracing experiments. Functional analysis shows that these RCCs express a broad spectrum of cardiogenesis genes and have the potential to differentiate into functional CMs, endothelial cells, and smooth muscle cells. Importantly, similar results were observed in neonatal rat CMs both in vitro and in vivo. Remarkably, administering 2C in adult mouse hearts significantly enhances survival and improves heart function post-myocardial infarction. Mechanistically, CHIR99021 is crucial for the transcriptional and epigenetic activation of genes essential for RCC development, while A-485 primarily suppresses H3K27Ac and particularly H3K9Ac in CMs. Their synergistic effect enhances these modifications on RCC genes, facilitating the transition from CMs to RCCs. Therefore, our findings demonstrate the feasibility and reveal the mechanisms of pharmacological induction of RCCs from endogenous CMs, which could offer a promising regenerative strategy to repair injured hearts.

Abstract Objective Gastric cancer (GC) stands as a prevalent and deadly global malignancy. Despite its role as a preoperative neoadjuvant therapy, Apatinib’s effectiveness is curtailed among GC patients exhibiting elevated YY1 expression. YY1’s connection to adverse prognosis, drug resistance, and GC metastasis is established, yet the precise underlying mechanisms remain elusive. This study aims to unravel potential pathogenic pathways attributed to YY1. Design Utilizing bioinformatics analysis, we conducted differentially expressed genes, functional annotation, and pathway enrichment analyses, and further validation through cellular and animal experiments. Results Higher YY1 expression correlated with diminished postoperative progression-free survival (PFS) and disease-specific survival (DSS) rates in TCGA analysis, identifying YY1 as an independent DSS indicator in gastric cancer (GC) patients. Notably, YY1 exhibited significantly elevated expression in tumor tissues compared to adjacent normal tissues. Bioinformatics analysis revealed noteworthy differentially expressed genes (DEGs), transcriptional targets, factors, and co-expressed genes associated with YY1. LASSO Cox analysis unveiled Transferrin as a prospective pivotal protein regulated by YY1, with heightened expression linked to adverse DSS and PFS outcomes. YY1’s role in governing the p53 signaling pathway and ferroptosis in GC cells was further elucidated. Moreover, YY1 overexpression dampened immune cell infiltration within GC tumors. Additionally, YY1 overexpression hindered GC cell ferroptosis and mediated Apatinib resistance via the p53 pathway. Remarkably, IFN-a demonstrated efficacy in reversing Apatinib resistance and immune suppression in GC tissues. Conclusions Our findings underscore the pivotal role of YY1 in driving GC progression and influencing prognosis, thus pinpointing it as a promising therapeutic target to enhance patient outcomes.

Biomass heavy oil, a renewable green energy source, has been extensively explored for its preparation process and material properties. This study examined the applicability of biomass heavy oil integrated into matrix asphalt. Bio-asphalt samples were prepared using polymer-modified asphalt I-C as the matrix asphalt, blended with straw liquid oil, straw solid oil, and castor liquid oil. The low-temperature performances of these samples were assessed. First, the effects of bio-oil on the fundamental performance of asphalt were analyzed through three-component tests, encompassing a short-term aging test and a temperature scanning test based on dynamic shear rheometry. Subsequently, the effects of the chemical composition of bio-asphalt on its fundamental performance were examined through four-component tests, including SARA, gel-permeation chromatography (GPC), and gray entropy correlation. The glass transition temperature (Tg) was considered a parameter for evaluating the low-temperature properties of the bio-asphalt binders. The bending-beam rheometry (BBR) low-temperature creep test and the binder fracture energy (BFE) full-section fracture energy test revealed that adding bio-oil reduces Tg of the matrix asphalt. The integrated creep flexural parameter Jc and the BFE fracture energy density values indicated that the low-temperature fracture-resistant properties of bio-asphalt surpass those of the matrix asphalt. Furthermore, the low-temperature cracking resistance of the bio-asphalt samples was determined through the BFE test. Gray entropy correlation analysis of the low-temperature performance indicators of bio-asphalt revealed that the BBR test is suitable for evaluating low-temperature performance only up to − 12 °C. In summary, the bio-asphalt mixtures demonstrate exceptional fatigue resistance under low-temperature service conditions. Therefore, bio-oil emerges as an effective candidate for enhancing the low-temperature performance characteristics of matrix asphalt.

Background and aims: Non-tunneling and submucosal tunneling endoscopic resection (STER) techniques are the most frequent treatments for cardial submucosal tumor (SMT). Here, we analyzed common machine learning (ML) algorithms and compared them with traditional regression models in surgical decision-making for cardial SMTs. Methods: Using key baseline predictive factors, ML algorithms and logistic regression (LR) were conducted in 246 patients. For the ML algorithms, gradient boosting machines (GBM), artificial neural networks (ANN), random forests (RF), and support vector machines (SVM), were included. For small sample-sized data, a technique for k-fold cross-validation was exploited to avoid over-fitting. Meanwhile, we tuned the parameters through several replications. Then, we quantified the discrimination (area under the curve, AUC) and predictive ability (Brier score, F1 score, specificity, sensitivity, and accuracy) of models. We divided patients (n ​= ​246) into STER-treated (n ​= ​97) and non-tunneling endoscopic resection (NTER)-treated (n ​= ​149) groups. Results: LR outperformed among all groups (Brier score ​= ​0.1398, F1 score ​= ​0.7391, AUC ​= ​0.8729, and predictive accuracy ​= ​80.65 ​%). In comparison to ML algorithms, an outperformance of the traditional regression approach was also found in a low-dimensional setting for surgical decision prediction of cardial SMTs. Conclusions: The traditional regression approach outperformed ML algorithms for the prediction of the best surgical method in patients with SMTs.

Pavement structures experience stresses due to temperature changes, and these stresses gradually dissipate, similar to the rheological phenomenon of stress relaxation. In this study, we conducted various tests, including low-temperature stress relaxation, low-temperature bending beam rheology test, glass transition temperature test, and asphalt single-edge-notch bending test, to compare and analyze the relaxation performance and low-temperature crack resistance of asphalt mastics. Using the SPSS method, we investigated the correlation between the relaxation performance and low-temperature crack resistance of asphalt mastics. The results revealed that the relaxation time and rate obtained in the small beam bending test were reliable indicators for evaluating the relaxation performance of asphalt mastics. Moreover, the relaxation performance of asphalt mastics exhibited a strong linear relationship with low-temperature crack resistance, as evidenced by the asphalt performance ranking. Through multiple linear regression analysis of relaxation properties, we derived a prediction equation for the low-temperature cracking resistance of asphalt mastics.

Abstract Optimal bowel preparation is a prerequisite for a successful colonoscopy; however, the rate of inadequate bowel preparation remains relatively high. In this study, we establish a smartphone app that assesses patient bowel preparation using an artificial intelligence (AI)-based prediction system trained on labeled photographs of feces in the toilet and evaluate its impact on bowel preparation quality in colonoscopy outpatients. We conduct a prospective, single-masked, multicenter randomized clinical trial, enrolling outpatients who own a smartphone and are scheduled for a colonoscopy. We screen 578 eligible patients and randomize 524 in a 1:1 ratio to the control or AI-driven app group for bowel preparation. The study endpoints are the percentage of patients with adequate bowel preparation and the total BBPS score, compliance with dietary restrictions and purgative instructions, polyp detection rate, and adenoma detection rate (secondary). The prediction system has an accuracy of 95.15%, a specificity of 97.25%, and an area under the curve of 0.98 in the test dataset. In the full analysis set (n = 500), adequate preparation is significantly higher in the AI-driven app group (88.54 vs. 65.59%; P

Background and Aims: Accurate recognition of endoscopic instruments facilitates quantitative evaluation and quality control of endoscopic procedures. However, no relevant research has been reported. In this study, we aimed to develop a computer-assisted system, EndoAdd, for automated endoscopic surgical video analysis based on our dataset of endoscopic instrument images. Methods: Large training and validation datasets containing 45,143 images of 10 different endoscopic instruments and a test dataset of 18,375 images collected from several medical centers were used in this research. Annotated image frames were used to train the state-of-the-art object detection model, YOLO-v5, to identify the instruments. Based on the frame-level prediction results, we further developed a hidden Markov model to perform video analysis and generate heatmaps to summarize the videos. Results: EndoAdd achieved high accuracy (>97%) on the test dataset for all 10 endoscopic instrument types. The mean average accuracy, precision, recall, and F1-score were 99.1%, 92.0%, 88.8%, and 89.3%, respectively. The area under the curve values exceeded 0.94 for all instrument types. Heatmaps of endoscopic procedures were generated for both retrospective and real-time analyses. Conclusions: We successfully developed an automated endoscopic video analysis system, EndoAdd, which supports retrospective assessment and real-time monitoring. It can be used for data analysis and quality control of endoscopic procedures in clinical practice.

This study aims to explore the problem of H∞ fuzzy control with an adjustable convergence rate for switched nonlinear systems with time-varying delays under the persistent dwell time (PDT) switching. Compared to the widely studied dwell time (DT) switching or average dwell time (ADT) switching in existing literature, PDT switching provides a more comprehensive consideration of the switching frequency and has a broader range of applicability. Subsequently, by combining the interval stability definition, T-S fuzzy model, PDT technique, and Lyapunov-Krasovskii (L-K) functional, a new H∞ fuzzy control criterion for adjusting the convergence rate of switched nonlinear systems with time-varying delays is proposed. This criterion enables the development of a novel method for constructing H∞ fuzzy controllers, which can regulate the system’s convergence rate and achieve the specified H∞ performance. Combining the above methods, an algorithm is introduced to precisely control the convergence rate of the target system. Finally, the effectiveness of this method is validated through a control example of a single-link robot arm. [ABSTRACT FROM AUTHOR]

IntroductionThe highly conserved tubby-like proteins (TLPs) play key roles in animal neuronal development and plant growth. The abiotic stress tolerance function of TLPs has been widely explored in plants, however, little is known about comparative studies of TLPs within crops.MethodsBioinformatic identification, phylogenetic analysis, Cis-element analysis, expression analysis, Cis-element analysis, expression analysis and so on were explored to analysis the TLP gene family of multiple crops.ResultsIn this study, a comprehensive analysis of TLP genes were carried out in seven crops to explore whether similar function of TLPs in rice could be achieved in other crops. We identified 20, 9, 14, 11, 12, 35, 14 and 13 TLP genes in Glycine max, Hordeum vulgare, Sorghum bicolor, Arabidopsis thaliana, Oryza sativa Japonica, Triticum aestivum, Setaria italic and Zea mays, respectively. All of them were divided into two groups and ten orthogroups (Ors) based on amino acids. A majority of TLP genes had two domains, tubby-like domain and F-box domain, while members of Or5 only had tubby-like domain. In addition, Or5 had more exons and shorter DNA sequences, showing that characteristics of different Ors reflected the differentiated function and feature of TLP genes in evolutionary process, and Or5 was the most different from the other Ors. Besides, we recognized 25 cis-elements in the promoter of TLP genes and explored multiple new regulation pathway of TLPs including light and hormone response. The bioinformatic and transcriptomic analysis implied the stresses induced expression and possible functional redundancy of TLP genes. We detected the expression level of 6 OsTLP genes at 1 to 6 days after seed germination in rice, and the most obvious changes in these days were appeared in OsTLP10 and OsTLP12.DiscussionCombined yeast two-hybrid system and pull down assay, we suggested that the TLP genes of Or1 may have similar function during seed germination in different species. In general, the results of comprehensive analysis of TLP gene family in multiple species provide valuable evolutionary and functional information of TLP gene family which are useful for further application and study of TLP genes.

BackgroundEndoscopic biopsy is the pivotal procedure for the diagnosis of gastric cancer. In this study, we applied whole-slide images (WSIs) of endoscopic gastric biopsy specimens to develop an endoscopic gastric biopsy assistant system (EGBAS).MethodsThe EGBAS was trained using 2373 WSIs expertly annotated and internally validated on 245 WSIs. A large-scale, multicenter test dataset of 2003 WSIs was used to externally evaluate EGBAS. Eight pathologists were compared with the EGBAS using a man-machine comparison test dataset. The fully manual performance of the pathologists was also compared with semi-manual performance using EGBAS assistance.ResultsThe average area under the curve of the EGBAS was 0·979 (0·958-0·990). For the diagnosis of all four categories, the overall accuracy of EGBAS was 86·95%, which was significantly higher than pathologists (P< 0·05). The EGBAS achieved a higher κ score (0·880, very good κ) than junior and senior pathologists (0·641 ± 0·088 and 0·729 ± 0·056). With EGBAS assistance, the overall accuracy (four-tier classification) of the pathologists increased from 66·49 ± 7·73% to 73·83 ± 5·73% (P< 0·05). The length of time for pathologists to manually complete the dataset was 461·44 ± 117·96 minutes; this time was reduced to 305·71 ± 82·43 minutes with EGBAS assistance (P = 0·00).ConclusionsThe EGBAS is a promising system for improving the diagnosis ability and reducing the workload of pathologists.

Background and study aims Submucosal tunneling endoscopic resection (STER) and non-tunneling techniques are two alternative options for the treatment of cardial submucosal tumors (SMTs). We aimed to establish a regression model and develop a simple scoring system (Zhongshan Tunnel Score) to help clinicians make surgical decisions for cardial submucosal tumors. Patients and methods A total of 246 patients who suffered cardial SMTs and received endoscopic resection were included in this study. All of them were randomized into either the training cohort (n = 147) or the internal validation cohort (n = 99). Then, the scoring system was proposed based on multivariate logistic regression analysis in the training cohort and assessed in the validation cohort. Results Of 246 patients, 97 were treated with STER and the others with non-tunneling endoscopic resection. In the training stage, four factors were weighted with points based on the β coefficient from the regression model, including irregular morphology (–2 points), ulcer (2 points), the direction of the gastroscope (–2 points for forward direction and 1 point for reverse direction), and originating from the muscularis propria (–2 points). The patients were categorized into low-score ( –3) groups, and those with low scores were more likely to be treated with STER. Our score model performed satisfying discriminatory power in internal validation (Area under the receiver-operator characteristic curve, 0.829; 95 % confidence interval, 0.694–0.964) and goodness-of-fit in the Hosmer-Lemeshow test (P = .4721). Conclusions This scoring system could provide clinicians the references for making decisions about the treatment of cardial submucosal tumors.

The gastrointestinal (GI) tract plays an essential role in food digestion, absorption, and the mucosal immune system; it is also inhabited by a huge range of microbes. The GI tract is densely innervated by a network of 200–600 million neurons that comprise the enteric nervous system (ENS). This system cooperates with intestinal microbes, the intestinal immune system, and endocrine systems; it forms a complex network that is required to maintain a stable intestinal microenvironment. Understanding how gut microbes influence the ENS and central nervous system (CNS) has been a significant research subject over the past decade. Moreover, accumulating evidence from animal and clinical studies has revealed that gut microbiota play important roles in various neurological diseases. However, the causal relationship between microbial changes and neurological disorders currently remains unproven. This review aims to summarize the possible contributions of GI microbiota to the ENS and CNS. It also provides new insights into furthering our current understanding of neurological disorders.

Based on ensuring the steady-state performance of the system, some dynamic performance indicators that have not yet been realized in linear stochastic systems with time-delay are discussed in this paper. First, in view of the relationship between system eigenvalues and system performances, the region stability is provided, which can reflect the dynamic performance of the systems. Second, the design scheme of the region stabilization controller is given based on the region stability, so that the closed-loop system has the corresponding dynamic performance. Third, this paper also designs an algorithm to deal with the situation in which the eigenvalues are located in the non-connected region in order to obtain more accurate control system dynamic performance. Finally, an example shows how the precise control method dominates the dynamic performance of the system.

As a special class of rice germplasm, wide-compatibility varieties (WCVs) guarantee the fertility of hybrids when there is cross-fertilization between two subspecies. In this study, Chenghui9348 was identified as a new member of the WCV family that improves pollen fertility in an inter-subspecific hybrid. Cytological analysis showed that the abnormal mitosis of microspores resulted in the sterility of pollens at the early bicellular stage in the inter-subspecific hybrid. Furthermore, the new F12 locus, corresponding to improvements in fertility of the indica-japonica hybrid, was found to co-segregate with the RM1047 marker and associated with a region of approximately 630 kb flanked by the D1101 and D1164 markers on chromosome 12. In this region, two putative genes were predicted as the candidates for wide-compatibility genes (WCGs). Sequence analysis revealed that, compared with indica/japonica alleles, deletion/insertion occurred within exons of both putative genes. Together, the present study identified another new WC locus, F12, and offers more opportunities for further exploitation of inter-subspecific hybrids in rice.

Background: The influenza A virus is the primary cause of respiratory infections and poses a global health risk. Pudilan Xiaoyan oral liquid (PDL) exhibits anti-inflammatory and immunomodulatory properties. PDL is commonly employed in clinical practice to manage upper respiratory tract infections. However, there is still much to uncover regarding its potential therapeutic mechanism. Methods: Institute of cancer research mice were infected with influenza A virus via nasal drip. The general state of the mice, lung index, and lung index inhibition rate were used to evaluate the efficacy of PDL. Enzyme-linked immunosorbent assay, western blotting, and immunohistochemistry were used to observe the presence of proteins and cytokines in the lung tissue. Apoptosis was evaluated using the TUNEL assay. Results: PDL improved the mental state of influenza A virus-infected mice, reduced the lung index, and inhibited viral replication. The expression of interleukin-1β and tumor necrosis factor-α were decreased, whereas the expression of interleukin-10 in the lung tissue was increased due to PDL treatment. In addition, PDL treatment modulated Toll-like receptor 4 and MyD88 expressions in the lung tissues. PDL significantly reduced apoptosis and decreased cleaved caspase-3 and PARP levels, whereas increased B-cell lymphoma-2 expression in the lung tissue. Notably, the moderate-dose group of PDL exhibited a more pronounced effect. These findings indicate that PDL exerts a protective effect against pneumonia injury in influenza A virus-infected mice. Conclusion: PDL inhibited the inflammatory response and regulated apoptosis by regulating Toll-like receptor 4 and MyD88 protein expressions, thereby protecting the lung tissue from viral infection-induced lung tissue injury. [ABSTRACT FROM AUTHOR]

The micro-physical characteristics of a typical sea of clouds process in Jiuxian Mountain are investigated by comprehensively analyzing parameters that delineate the micro-physical characteristics of clouds and atmospheric stratification based on data from a cloud radar, wind profiler, meteorological gradient observation in high mountains, and other observations. The results show that water vapor condenses into cloud particles via an entrained and mixing process accompanied by an updraft originating from orographic uplift. During the thickening stage of the sea of clouds, atmospheric motion within the clouds is featured as "downdraft on the top—updraft on the bottom". The zero vertical velocity area is located closely to the maximum of liquid water content. The thermal inversion layer is formed during the maintenance stage; however, the enhancement of inversion on the cloud top could suppress updraft in areas with a high liquid water content. The values mainly concentrate on the cloud top, and repetitively lifting and falling processes caused by the atmospheric upward and downward motion are in favor of the coalescence growth of cloud particles, which result in the persistence of strong radar echo. At the dissipation stage, warming on the cloud top is greater than that on the cloud bottom due to the short-wave absorption of clouds as the solar radiation enhances. As a result, the inversion layer thickens and elevates, evaporation caused by heating outweighs the condensation caused by cooling, a strong radar echo band descends from the top to the middle part of clouds, a sea of clouds dissipates gradually as cloud particles evaporates, and the particle size and concentration number of cloud particles decrease simultaneously. [ABSTRACT FROM AUTHOR]

In this paper, a longitudinal compression experiment of composites was conducted and the macroscopic failure mode was obtained. Also, the microscopic failure morphologies of longitudinal compression and kink band were observed by using scanning electron microscopy. It can be seen that, under compression, fibers bend and form a kink band, which is the most typical failure mode. Then a micromechanical model of fiber random distribution based on the random collision algorithm, which can reveal the progressive failure mechanism of longitudinal compression considering the kink-band deformation, was established, with two dominant damage mechanisms – plastic deformation and ductile damage initiation of the polymer matrix and interfacial debonding included in the simulation by the extended Drucker-Prager model and cohesive zone model, respectively. Through numerical simulation, the loading and failure procedures were divided into three stages: elastic domain, softening domain and fiber failure domain. It can be concluded that the kink band was a result of fiber instability (micro-bulking), which is caused by the elastic bending of fibers. The fibers rotate and break into two places, forming a kink band. Then the fibers rotate further until the matrix between the fibers fails and the kink-band breaks and, hence, the composite loses its load-bearing capability.

To improve the efficiency of solving vehicle collision velocity and provide sufficient evidence for the identification of accident responsibility, we proposed a method combining the momentum equation and finite element simulation. We built a finite element simulation model of a vehicle where multiple collision simulation experiments were carried out, and studied the calculation method of collision deformation. After fitting and analyzing the simulated deformation data of an accident vehicle under different velocities through collision simulation experiments, a relationship model between collision velocity and deformation was established, and a method to solve the collision velocity was proposed by combing the existing two-dimensional collision momentum equation of the vehicle. For actual collision cases, the proposed velocity solution method and the simulation software were used for reconstruction analyses, respectively, and the results of the instantaneous contact velocity of vehicle collision were compared. It was found that the velocity calculation results obtained using the two methods above were in good agreement; the shape and depth of the simulated deformation were consistent with the actual deformation of the vehicle. [ABSTRACT FROM AUTHOR]

With increasingly serious environmental pressure, carbon emission and the development of logistics industry are constrained by each other. The chief objective of this study is to reveal the relationship between input--output activities in logistics and carbon emissions, to evaluate the carbon emission performance in logistics in the Yellow River Basin based on DEA--Tobit model, and to analyze the factors affecting the environmental performance. The results indicate the following: (1) Ningxia, Inner Mongolia, Henan, Qinghai, Shandong achieved good carbon emission performance in logistics, while the logistics environmental performance of Shanxi, Gansu, Shaanxi and Sichuan is bad, which needs to be adjusted in time to avoid further aggravating unreasonable carbon emissions. (2) The intensity of environmental regulation and energy consumption have a positive and negative correlation, respectively, with the carbon emission performance in logistics, and the industrial aggregation and the government intervention have no significant impact on the carbon emission performance in logistics in the Yellow River Basin. Based on the research results, this paper discusses some principles applicable to improve the logistics environmental performance, which can provide reference for logistics enterprises in the micro-scale and logistics departments in the macro-scale to reduce energy consumption and to eliminate unreasonable pollution factors in the Yellow River Basin. [ABSTRACT FROM AUTHOR]