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Abstract Aims The endoscopic treatment of esophagogastric varices is challenging, and the nationwide application of endoscopic therapies for various types of esophagogastric varices and different clinical scenarios remains unclear. This study investigated the use of endoscopic therapy for portal hypertension in China. Methods This study used a questionnaire survey initiated by the Liver Health Consortium in China to investigate the use of endoscopic therapies for portal hypertension. Questionnaires were released online from January 30, 2023 to February 28, 2023 and filled out by chief physicians or senior instructors responsible for endoscopic therapies in participating hospitals across 31 provinces (autonomous regions and municipalities) in China. Comparisons of guideline adherence between primary and referral medical centers were performed using the chi‐square test or Fisher's exact test. Results In total, 836 hospitals participated in the survey. For primary and secondary prophylaxis of esophagogastric variceal bleeding (EGVB), adherence to the national guidelines was 72.5% (606/836) and 39.2% (328/836), respectively. Significant differences were observed in the rate of adherence between the primary and referral centers for primary (79.9% [111/139] vs. 71.0% [495/697], p = 0.033) and secondary prophylaxis (27.3% [38/139] vs. 41.6% [290/697], p = 0.002). Of the hospitals, 78.2% (654/836) preferred endoscopic therapies for acute EGVB, and the timing of endoscopy was usually within 12 h (48.5%, 317/654) and 12–24 h (36.9%, 241/654) after bleeding. Endoscopic therapy was more likely to be the first choice of treatment for acute EGVB in referral centers than in primary centers (82.6% [576/697] vs. 56.1% [78/139], p

Introduction: The association between elevated lactate levels and the development of disseminated intravascular coagulation (DIC) in patients with severe trauma remains unclear. Hence, this study aimed to explore the association between lactate and the development of DIC in patients with severe trauma. Methods: This prospective cohort study was conducted on consecutive patients with severe trauma who were hospitalized in the intensive care unit from January 2020 to January 2023. The primary outcome measured was the occurrence of DIC in patients in the emergency department or posthospitalization. Logistic regression analysis evaluating the risk values for lactate and DIC, the receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) examinations studying the predictive efficiency of lactate for DIC. The Kaplan–Meier survival curve was used to assess patient survival. Sensitivity robustness analysis included modified Poisson regression, E-value, subgroup analysis, and numerical variable transformation analysis. Results: Logistic regression analysis corrected for confounding factors showed that lactate was a risk factor for DIC in patients with severe trauma (adjusted odds ratio [OR]: 1.374, 95% confidence interval [CI]: 1.206–1.566). Lactate predicted DIC risk with a 0.8513 area under the ROC curve (95% CI: 0.7827–0.9199), 4.8 cutoff value, 0.8333 sensitivity, and 0.8014 specificity. DCA showed the correlation between lactate and DIC. The mortality rate of patients with a high risk of DIC was significantly higher than that of patients with a low risk (log-rank test, P < 0.001). The modified Poisson regression showed that lactate was a risk factor for DIC (risk ratio: 1.188, 95% CI: 1.140–1.237). E-value was 1.645, and the lower limit of 95% CI was 1.495. The logistic regression analysis after subgroup analysis and transformation of numerical variables showed that lactate remained a risk factor for DIC. Conclusions: Elevated lactate is closely associated with the occurrence of DIC in patients with severe trauma. Lactate seems to be a good predictive factor for DIC manifestation in patients with severe trauma.

As a precise and versatile tool for genome manipulation, the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) platform holds promise for modifying fish traits of interest. With the aim of reducing transgene introgression and controlling reproduction, upscaled disease resistance and reproductive intervention in catfish species have been studied to lower the potential environmental risks of the introgression of escapees as transgenic animals. Taking advantage of the CRISPR/Cas9-mediated system, we succeeded in integrating the cathelicidin gene (As-Cath) from an alligator (Alligator sinensis) into the target luteinizing hormone (lh) locus of channel catfish (Ictalurus punctatus) using two delivery systems assisted by double-stranded DNA (dsDNA) and single-stranded oligodeoxynucleotides (ssODNs), respectively. In this study, high knock in (KI) efficiency (22.38%, 64/286) but low on-target events was achieved using the ssODN strategy, whereas adopting a dsDNA as the donor template led to an efficient on-target KI (10.80%, 23/213). The on-target KI of As-Cath was instrumental in establishing the lh knockout (LH–_As-Cath+) catfish line, which displayed heightened disease resistance and reduced fecundity compared with the wild-type (WT) sibling fish. Furthermore, administration of human chorionic gonadotropin (HCG) and luteinizing hormone-releasing hormone analogue (LHRHa) can restore the reproduction of the transgenic fish line. Overall, we replaced the lh gene with an alligator cathelicidin transgene and then administered hormone therapy to move towards complete reproductive control of disease-resistant transgenic catfish in an environmentally responsible manner. This strategy not only effectively improves consumer-valued traits but also guards against unwanted introgression, providing a breakthrough in aquaculture genetics to confine fish reproduction and prevent the establishment of transgenic or domestic genotypes in the natural environment.

Abstract Muscle quality index (MQI) is a novel indicator reflecting the quality of skeletal muscles. The association between MQI and the development of advanced fibrosis in patients with nonalcoholic fatty liver disease (NAFLD) is unknown. We investigated the association of low MQI with advanced fibrosis among adults with NAFLD using a nationally representative sample of the US population. Adults with NAFLD who participated in the National Health and Nutrition Examination Survey (NHANES) 2011–2014 were included. Sex-specific standard was used to define low and extremely low MQI. Univariate and multivariate logistic regressions were used to assess the association between MQI level and advanced fibrosis. In the study, 3758 participants with NAFLD were included. The prevalence of low and extremely low MQI was 11.7% (95% CI 10.4–13.0%) and 2.2% (95% CI 1.6–2.8%), respectively. Among these participants, 96 were assessed to have advanced fibrosis. Individuals with low [(odds ratio (OR) 2.45, 95% confidence interval (CI) 1.22–4.91)] and extremely low MQI (OR 10.48, 95% CI 3.20–34.27) were associated with advanced fibrosis in multivariable analysis. A linear trend relationship was also observed between MQI level and the risk of advanced fibrosis (P trend = 0.001). Subgroup and sensitivity analyses yielded similar results to the main analyses. Decreased MQI is highly prevalent, and is associated with an increased risk of advanced fibrosis in adult US population with NAFLD.

Abstract Background At present, conventional endoscopy and chromoendoscopy using indigo carmine (IC) is a very useful method to determine the demarcation line (DL) of early gastric cancer lesions, but it is not suitable for all lesions. Aims This study aimed to determine the applicable conditions for IC chromoendoscopy. Methods We retrospectively evaluated 187 lesions in 181 patients who had an endoscopic diagnosis of EGC and were treated with endoscopic submucosal dissection (ESD). According to the existence of the DL between the lesion mucosa and normal mucosa with IC chromoendoscopy, the lesions were divided into two groups: clear group and unclear group. Clinicopathological characteristics were evaluated in each group. From January 2022 to March 2023, the postoperative pathological sections of 19 lesions (81 slices) in the clear group and 19 lesions (80 slices) in unclear group were scanned with high definition, and the crypt structure between the two groups was evaluated. Results There was no significant difference in clinical factors between the clear group and unclear group. There were significant differences in crypt area, crypt length, and crypt opening diameter between the two groups. In the clear group, there were significant differences in crypt area, crypt length, and crypt opening diameter between the normal area and cancer area, but there was no significant difference in the unclear group. Conclusions The margins of lesions with fused or absent crypt structures, a small crypt area, a short crypt length, and a short crypt opening diameter can be easily determined with IC chromoendoscopy.

In unstructured environments, dense grape fruit growth and the presence of occlusion cause difficult recognition problems, which will seriously affect the performance of grape picking robots. To address these problems, this study improves the YOLOX-Tiny model and proposes a new grape detection model, YOLOX-RA, which can quickly and accurately identify densely growing and occluded grape bunches. The proposed YOLOX-RA model uses a 3 × 3 convolutional layer with a step size of 2 to replace the focal layer to reduce the computational burden. The CBS layer in the ResBlock_Body module of the second, third, and fourth layers of the backbone layer is removed, and the CSPLayer module is replaced by the ResBlock-M module to speed up the detection. An auxiliary network (AlNet) with the remaining network blocks was added after the ResBlock-M module to improve the detection accuracy. Two depth-separable convolutions (DSC) are used in the neck module layer to replace the normal convolution to reduce the computational cost. We evaluated the detection performance of SSD, YOLOv4 SSD, YOLOv4-Tiny, YOLO-Grape, YOLOv5-X, YOLOX-Tiny, and YOLOX-RA on a grape test set. The results show that the YOLOX-RA model has the best detection performance, achieving 88.75 % mAP, a recognition speed of 84.88 FPS, and model size of 17.53 MB. It can accurately detect densely grown and shaded grape bunches, which can effectively improve the performance of the grape picking robot.

Abstract Angiogenesis plays an essential role in the microenvironment of hepatocellular carcinoma (HCC). HOXD3 is involved in the metastasis and invasion of HCC cells; Whereas the underlying molecular mechanisms in the microenvironment of HCC remain unknown. Wound healing, transwell invasion, tube formation and spheroid sprouting assays were carried out to identify the effects of HCC-HOXD3-exosomes and genes on the migration of HCC cells. ChIP–PCR was applied to test the binding region of HOXD3 on CCR6, Med15, and CREBBP promoter. Exosome isolation and mRNA-seq were applied to examine the morphological characteristics of exosomes and the contained mRNA in exosomes. Co-IP and Immunofluorescence assays were used to demonstrate the role of CREBBP in the chromatin conformation of CCL20. The nude mice were used to identify the function of genes in regulating migration of HCC in vivo. In this study, integrated cellular and bioinformatic analyses revealed that HOXD3 targeted the promoter region of CCR6 and induced its transcription. CCR6 was delivered by exosomes to endothelial cells and promoted tumour migration. Overexpression of CCR6 promoted metastasis, invasion in HCCs and angiogenesis in endothelial cells (ECs), whereas its downregulation suppressed these functions. The role of HOXD3 in the metastasis and invasion of HCC cells was reversed after the suppression of CCR6. Furthermore, CCL20 was demonstrated as the ligand of CCR6, and its high expression was found in HCC tissues and cells, which was clinically associated with the poor prognosis of HCC. Mechanistically, HOXD3 targets the promoter regions of CREBBP and Med15, which affect CCL20 chromatin conformation by regulating histone acetylation and expression of Pol II to enhance the migration of HCCs. This study demonstrated the function of the HOXD3–CREBBP/Med15–CCL20–CCR6 axis in regulating invasion and migration in HCC, thus providing new therapeutic targets for HCC.

Antimicrobial peptides (AMPs) show promise in enhancing resistance against pathogens. Previously, we integrated two AMP genes, cathelicidin (Cath) from alligator (Alligator mississippiensis or Alligator sinensis) and cecropin (Cec) from moth (Hyalophora cecropia), into the channel catfish (Ictalurus punctatus) genome. This study examines the efficacy of exogenous AMP gene integration in improving bacterial resistance in transgenic channel catfish and assesses the direct and pleiotropic effects of gene replacement/knockout on survival and growth based on insertion site. Transgenic Cath- and Cec-expressing fish exhibited similar or higher survival rates (P ​> ​0.05) compared to controls during the initial culture. Integration of the Cec transgene doubled the survival rate when challenged with Edwardsiella ictaluri, with knock-in (KI) of Cath further increasing bacterial resistance. Coupling Cec KI with mstn knockout (KO) increased survival 3-fold after E. ictaluri infection and growth by 50% at 4 months post-fertilization (mpf). However, random integration of Cec had a minimal effect on disease resistance and did not enhance growth. Random integration of Cath increased survival 2.5-fold and 4-fold against E. ictaluri and Flavobacterium covae, respectively, without affecting growth. Cath KI at the lh locus increased survival 4-fold when challenged with F. covae and reduced growth by 10% (P ​> ​0.05) at 24 mpf, whereas Cath KI coupled with mc4r KO resulted in a 2.5-fold increase in survival following F. covae infection compared with controls, and increased growth by 80% at 3 mpf. Simultaneous KI of Cath and Cec, along with KO of mc4r and mstn, increased survival 4-fold against E. ictaluri, while increasing growth by 50% at 3 mpf. Dual insertion of AMP genes yielded the greatest resistance to disease. These direct and pleiotropic effects may increase comprehension and societal acceptance of genetic engineering in aquaculture.

ObjectiveThe presence of mental fatigue seriously affects daily life and working conditions. Non-invasive transcranial electrical stimulation has become an increasingly popular tool for relieving mental fatigue. We investigated whether transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS) could be used to alleviate the state of mental fatigue in a population of healthy young adults and compared their effects.MethodsWe recruited 10 participants for a blank control, repeated measures study. Each participant received 15 min of anodal tDCS, α-tACS, and blank stimulation. Participants were required to fill in the scale, perform the test task and collect ECG signals in the baseline, fatigue and post-stimulus states. We then assessed participants’ subjective fatigue scale scores, test task accuracy and HRV characteristics of ECG signals separately.ResultsWe found that both anodal tDCS and α-tACS significantly (P < 0.05) reduced subjective fatigue and improved accuracy on the test task compared to the blank group, and the extent of change was greater with tACS. For the HRV features extracted from ECG signals. After tACS intervention, SDNN (t = −3.241, P = 0.002), LF (t = −3.511, P = 0.001), LFn (t = −3.122, P = 0.002), LFn/HFn (−2.928, P = 0.005), TP (t = −2.706, P = 0.008), VLF (t = −3.002, P = 0.004), SD2 (t = −3.594, P = 0.001) and VLI (t = −3.564, P = 0.001) showed a significant increasing trend, and HFn (t = 3.122, P = 0.002), SD1/SD2 (t = 3.158, P = 0.002) and CCM_1 (t = 3.106, P = 0.003) showed a significant decreasing trend. After tDCS intervention, only one feature, TINN, showed a significant upward trend (P < 0.05). The other features showed non-significant changes but roughly the same trend as the tACS group.ConclusionBoth tDCS and α-tACS can be effective in relieving mental fatigue, and α-tACS is more effective than tDCS. This study provides theoretical support for tDCS with α-tACS having a alleviating effect on mental fatigue and the use of ECG as a valid objective assessment tool.

Abstract The HOXA genes, belonging to the HOX family, encompass 11 members (HOXA1-11) and exert critical functions in early embryonic development, as well as various adult processes. Furthermore, dysregulation of HOXA genes is implicated in genetic diseases, heart disease, and various cancers. In this comprehensive overview, we primarily focused on the HOXA1-4 genes and their associated functions and diseases. Emphasis was placed on elucidating the impact of abnormal expression of these genes and highlighting their significance in maintaining optimal health and their involvement in the development of genetic and malignant diseases. Furthermore, we delved into their regulatory mechanisms, functional roles, and underlying biology and explored the therapeutic potential of targeting HOXA1-4 genes for the treatment of malignancies. Additionally, we explored the utility of HOXA1-4 genes as biomarkers for monitoring cancer recurrence and metastasis.

Abstract Background There is no study evaluating the association between exercise and functional dyspepsia (FD) based on the Rome IV criteria. We aimed to investigate the prevalence of FD and evaluate the association between exercise and FD based on Rome IV criteria among a sample of Chinese armed police recruits. Methods An on-site questionnaire survey on FD among a sample of Chinese armed police recruits was conducted based on the Rome IV criteria in 2021. Potential confounders included age, body mass index (BMI), race, marriage, education, smoking, and drinking variables were adjusted. Results A total of 2594 recruits were enrolled, including 46 FD participants and 2548 non-FD participants. In the model adjusted for all demographic variables among participants excluding irritable bowel syndrome (IBS) and functional constipation (FC), compared with no exercise participants, 1 h

The Proton Exchange Membrane Fuel Cell (PEMFC) is a fast-developing battery technology, and the key to its reliability and lifespan improvement lies in the accurate assessment of durability. However, the degradation mechanism of the PEMFC is hard to determine and its internal parameters are highly coupled. Thus, the development of a more accurate life prediction model that meets the actual scenarios is to be investigated urgently. To solve this problem, a multi-feature fusion life prediction method based on the Temporal Convolutional Network-Gated Recurrent Unit (TCN-GRU) is proposed. A TCN algorithm is used as the prediction base model, and two GRU modules are included with the model to strengthen the model’s expression ability and improve its predictive accuracy. Two widely recognized datasets and two operating conditions are utilized for model training and prediction, respectively. Comparisons are made with single-feature parameter models in terms of Root Mean Square Error (RMSE) and the Determination Coefficient (R2). The results show that the prediction accuracy of the TCN-GRU multi-feature fusion model is higher than that of the single-feature models in terms of stability and anti-interference under both operating conditions. The accuracy of the TCN-GRU (three-feature) model is the most optimal in a steady-state condition at 80% of the training set ratio (RMSE = 3.27 × 10−3, R2 = 0.965). Furthermore, with the increase in the input feature parameter, the TCN-GRU model is closer to the real value, which proves once again that the proposed model can meet the accuracy requirements of the life prediction of the PEMFC.

Channel catfish (Ictalurus punctatus) and blue catfish (Ictalurus furcatus) are two economically important freshwater aquaculture species in the United States, with channel catfish contributing to nearly half of the country’s aquaculture production. While differences in economic traits such as growth rate and disease resistance have been noted, the extent of transcriptomic variance across various tissues between these species remains largely unexplored. The hybridization of female channel catfish with male blue catfish has led to the development of superior hybrid catfish breeds that exhibit enhanced growth rates and improved disease resistance, which dominate more than half of the total US catfish production. While hybrid catfish have significant growth advantages in earthen ponds, channel catfish were reported to grow faster in tank culture environments. In this study, we confirmed channel fish’s superiority in growth over blue catfish in 60-L tanks at 10.8 months of age (30.3 g and 11.6 g in this study, respectively; p < 0.001). In addition, we conducted RNA sequencing experiments and established transcriptomic resources for the heart, liver, intestine, mucus, and muscle of both species. The number of expressed genes varied across tissues, ranging from 5,036 in the muscle to over 20,000 in the mucus. Gene Ontology analysis has revealed the functional specificity of differentially expressed genes within their respective tissues, with significant pathway enrichment in metabolic pathways, immune activity, and stress responses. Noteworthy tissue-specific marker genes, including lrrc10, fabp2, myog, pth1a, hspa9, cyp21a2, agt, and ngtb, have been identified. This transcriptome resource is poised to support future investigations into the molecular mechanisms underlying environment-dependent heterosis and advance genetic breeding efforts of hybrid catfish.

To improve the accuracy and robustness of autonomous vehicle localization in a complex environment, this paper proposes a multi-source fusion localization method that integrates GPS, laser SLAM, and an odometer model. Firstly, fuzzy rules are constructed to accurately analyze the in-vehicle localization deviation and confidence factor to improve the initial fusion localization accuracy. Then, an odometer model for obtaining the projected localization trajectory is constructed. Considering the high accuracy of the odometer’s projected trajectory within a short distance, we used the shape of the projected localization trajectory to inhibit the initial fusion localization noise and used trajectory matching to obtain an accurate localization. Finally, the Dual-LSTM network is constructed to predict the localization and build an electronic fence to guarantee the safety of the vehicle while also guaranteeing the updating of short-distance localization information of the vehicle when the above-mentioned fusion localization is unreliable. Under the limited arithmetic condition of the vehicle platform, accurate and reliable localization is realized in a complex environment. The proposed method was verified by long-time operation on the real vehicle platform, and compared with the EKF fusion localization method, the average root mean square error of localization was reduced by 66%, reaching centimeter-level localization accuracy.

Background/Aims The aim of this study was to analyze the chronological changes in postoperative complications in surgical ulcerative colitis patients over the past decade in China and to investigate the potential parameters that contributed to the changes. Methods Ulcerative colitis patients who underwent surgery during 2008–2017 were retrospectively enrolled from 13 hospitals in China. Postoperative complications were compared among different operation years. Risk factors for complications were identified by logistic regression analysis. Results A total of 446 surgical ulcerative colitis patients were analyzed. Fewer short-term complications (24.8% vs. 41.0%, P=0.001) and more laparoscopic surgeries (66.4% vs. 25.0%, P

Effects of antimicrobial peptides (AMP) added to diets on aquatic animal health and body function are influenced by multiple factors such as animal species, initial body weight, the dosage of AMP and feeding duration. However, there is limited knowledge on the relationship between these factors and the body function of aquatic animals. Here, we aimed to perform multiple meta-analyses to investigate the effects of dietary AMP on growth performance (feed conversion ratio [FCR], specific growth rate [SGR]), enzyme activity (superoxide dismutase activity [SOD], lysozyme activity [LSA]), disease resistance (cumulative survival rate [CSR], the expression of immune-related genes [GENE]) and the abundance of gut microbiota (MICRO) from a pool of empirical studies. Additionally, the dose-effect model was applied to determine the optimal AMP dose, initial body weight and feeding duration to maximize body function. To conduct the meta-analyses, we included 34 publications that estimated 705 effect sizes across 21 fish, 2 shrimp and 2 shellfish species. The results confirmed that the inclusion of AMP in the diet can significantly improve SGR, SOD, LSA, CSR and GENE and decrease FCR for aquatic animals. Interestingly, our findings implied a slight positive effect of AMP on MICRO albeit with a limited number of studies available on fish gut microbial communities. Although no significant linear or quadratic relationship was predicted by meta-regression, the dose-effect indicated that the optimal AMP doses for FCR, SGR, SOD and LSA were 707.5, 750.0, 1,050.0 and 937.5 mg/kg, respectively. Taken together, fish with an initial body weight of 30 g could be fed with a dose of 600 to 800 mg/kg for 2 mo when AMP-supplemented diets were applied in aquaculture, which can effectively improve body function and health while lowering aquafeed costs. In addition, more studies should address fish gut microbiota to delimitate the influence of dietary AMP on MICRO in the future.

Non-invasive neuromodulation techniques are widely utilized to study and improve cognitive function, with the aim of modulating different cognitive processes. For workers performing high-intensity mental and physical tasks, extreme fatigue may not only affect their working efficiency but may also lead to cognitive decline or cognitive impairment, which, in turn, poses a serious threat to their physical health. The use of non-invasive neuromodulation techniques has important research value for improving and enhancing cognitive function. In this paper, we review the research status, existing problems, and future prospects of transcranial direct current stimulation (tDCS), transcranial alternating current stimulation (tACS), transcranial magnetic stimulation (TMS), and transcutaneous acupoint stimulation (TAS), which are the most studied physical methods in non-invasive neuromodulation techniques to improve and enhance cognition. The findings presented in this paper will be of great reference value for the in-depth study of non-invasive neuromodulation techniques in the field of cognition.

Fatty infiltration of the pancreas (FIP) has been recognized for nearly a century, yet many aspects of this condition remain unclear. Regular literature reviews on the diagnosis, consequences, and management of FIP are crucial. This review article highlights the various disorders for which FIP has been established as a risk factor, including type 2 diabetes mellitus (T2DM), pancreatitis, pancreatic fistula (PF), metabolic syndrome (MS), polycystic ovary syndrome (PCOS), and pancreatic duct adenocarcinoma (PDAC), as well as the new investigation tools. Given the interdisciplinary nature of FIP research, a broad range of healthcare specialists are involved. This review article covers key aspects of FIP, including nomenclature and definition of pancreatic fat infiltration, history and epidemiology, etiology and pathophysiology, clinical presentation and diagnosis, clinical consequences, and treatment. This review is presented in a detailed narrative format for accessibility to clinicians and medical students.

Exogenous oestrogen 17β-oestradiol (E2) has been shown to effectively induce feminization in teleosts. However, the molecular mechanisms underlying the process remain unclear. Here, we determined global DNA methylation and gene expression profiles of channel catfish (Ictalurus punctatus) during early sex differentiation after E2 treatment. Overall, the levels of global DNA methylation after E2 treatment were not significantly different from those of controls. However, a specific set of genes were differentially methylated, which included many sex differentiation-related pathways, such as MARK signalling, adrenergic signalling, Wnt signalling, GnRH signalling, ErbB signalling, and ECM–receptor interactions. Many genes involved in these pathways were also differentially expressed after E2 treatment. Specifically, E2 treatments resulted in upregulation of female-related genes and downregulation of male-related genes in genetic males during sex reversal. However, E2-induced sex reversal did not cause sex-specific changes in methylation profiles or gene expression within the sex determination region (SDR) on chromosome 4, suggesting that E2-induced sex reversal was a downstream process independent of the sex determination process that was regulated by sex-specific methylation within the SDR.

The Non-Synchronizer Automated Mechanical Transmission (NSAMT) demonstrates a straightforward structure and cost-effectiveness; however, the primary obstacle to its widespread application lies in NSAMT shift control. The implementation of active angle alignment effectively addresses the issue of shifting quality, but achieving active angle alignment necessitates precise tracking of the planned shifting curve by the gear-shifting actuator. To tackle the control problem of accurate tracking for NSAMT shift actuators, this paper initially analyzes the structure and shift characteristics of the NSAMT. Based on this analysis, a physical model is established using Amesim, incorporating a drive motor, two-gear NSAMT, shift actuator, sleeve, and DC motor model. An extended state observer (ESO) is designed to mitigate unknown interference within the system. Furthermore, an active angle alignment control algorithm based on “zero speed difference” and “zero angle difference” for double target tracking is constructed while planning the axial motion trajectory of the sleeve. The Backstepping algorithm is employed to successfully track and regulate this planned trajectory. Finally, through Hardware-in-the-Loop testing, we validate our proposed control strategy, which demonstrates consistent results with simulation outcomes, thereby affirming its effectiveness.

Abstract Background Recent studies have shown that chronic kidney disease (CKD) prevalence is significantly higher in patients with hepatic steatosis (HS); however, it remains unclear whether HS is associated with serum creatinine (SCr). We aimed to explore the association between SCr levels and HS in a Chinese population. Methods We performed a cross-sectional study among 56,569 Chinese individuals. SCr level, other clinical and laboratory parameters, abdominal ultrasound and noninvasive fibrosis scores were extracted, and the fibrosis 4 score (FIB-4) was calculated. Results A total of 27.1% of the subjects had HS. After 1:1 propensity score matching (PSM) according to sex and age, we included 13,301 subjects with HS and 13,301 subjects without HS. SCr levels were significantly higher in the HS group than in the non-HS group [73.19 ± 15.14(μmoI/L) vs. 71.75 ± 17.49(μmoI/L), p

H2S is a well-known relaxant regulator in muscle contraction but little attention has been paid to its excitatory effect on colonic motility. To investigate the excitation of H2S on rat colonic contraction and the underlying mechanism, the muscle contractile activity was assessed by an organ bath system, the level of substance P (SP) in the colon was detected using enzyme immunoassay kits, L-type Ca2+ channel currents (ICa,L) and large conductance Ca2+-activated K+ channel currents (IBK) in smooth muscle cells (SMCs) were measured by patch-clamp electrophysiology. The results show that the H2S donor NaHS (100 μM) reversed the relaxation of the NO donor SNP on colonic muscle contraction. Pretreatment with the TRPV1 antagonist and the neurokinin receptor antagonists attenuated the NaHS-induced excitation. Incubation of colon with NaHS increased the SP level. In freshly isolated SMCs, NaHS exerted a biphasic effect on ICa,L and concentration-dependently inhibited the IBK. And 100 μM NaHS partially reversed the SNP-induced changes in ICa,L and IBK. We concluded that exogenous H2S exerts a potential excitatory effect on colonic motility, which may be achieved by activating SP release from afferent nerves in combination with a direct activation of ICa,L and suppression of IBK in SMCs.

Abstract The rapid dissemination of antibiotic resistance accelerates the desire for new antibacterial agents. Here, a class of antimicrobial peptides (AMPs) is designed by modifying the structural parameters of a natural chickpea‐derived AMP–Leg2, termed “functionalized chickpea‐derived Leg2 antimicrobial peptides” (FCLAPs). Among the FCLAPs, KTA and KTR show superior antibacterial efficacy against the foodborne pathogen Escherichia coli (E. coli) O157:H7 (with MICs in the range of 2.5–4.7 µmol L−1) and demonstrate satisfactory feasibility in alleviating E. coli O157:H7‐induced intestinal infection. Additionally, the low cytotoxicity along with insusceptibility to antimicrobial resistance increases the potential of FCLAPs as appealing antimicrobials. Combining the multi‐omics profiling andpeptide‐membrane interaction assays, a unique dual‐targeting mode of action is characterized. To specify the antibacterial mechanism, microscopical observations, membrane‐related physicochemical properties studies, and mass spectrometry assays are further performed. Data indicate that KTA and KTR induce membrane damage by initially targeting the lipopolysaccharide (LPS), thus promoting the peptides to traverse the outer membrane. Subsequently, the peptides intercalate into the peptidoglycan (PGN) layer, blocking its synthesis, and causing a collapse of membrane structure. These findings altogether imply the great potential of KTA and KTR as promising antibacterial candidates in combating the growing threat of E. coli O157:H7.

ObjectiveTo analyze the prevalence, associated comorbidities, influencing factors, and identifying factors of non-obese fatty liver disease and to provide a reference for its prevention and treatment.Materials and methodsFirstly, to screen data obtained from the physical examinations of individuals conducted in the Second Affiliated Hospital of Xi’an Jiaotong University in 2021, subjects with complete data of abdominal ultrasonography, body mass index, age and sex were selected to analyze the prevalence of fatty liver disease and non-obese fatty liver disease. Secondly, to screen non-obese subjects who had data for triglycerides, fasting blood glucose, and so on, to analyze the complications, influencing factors, and identifying factors of non-obese fatty liver disease.ResultsThe prevalence of fatty liver disease was 27.8% (18,416/66,221), including 33.9% (11,921/35,131) in males and 20.9% (6,495/31,090) in females, revealing that the prevalence was significantly higher in males than in females (P < 0.001). There were 40,673 non-obese subjects screened in total, and the prevalence of non-obese fatty liver disease was 13.0% (5,307/40,673). The prevalence of non-obese fatty liver disease was 13.3% (2,208/16,572) in males and 12.9% (3,099/24,101) in females; the difference was not statistically significant (P = 0.17). The serum triglycerides level was elevated in 54.2% of subjects with non-obese fatty liver disease, and this was the most common abnormal metabolic index accompanying the disease. Logistic regression analysis showed that gender, age, body mass index, blood pressure, alanine aminotransferase, aspartate aminotransferase, fasting blood glucose, triglycerides, total cholesterol, and serum uric acid were independent risk factors for non-obese fatty liver disease (P < 0.001). For triglycerides, the area under the receiver operating characteristic curve in predicting non-obese fatty liver disease was the greatest (0.806).ConclusionThe prevalence of fatty liver disease and non-obese fatty liver disease determined by the physical examination of individuals was high, and the triglycerides is likely to be useful for the extensive screening of non-obese fatty liver disease.

Introduction: The prevalence of metabolic dysfunction-associated fatty liver disease (MAFLD) with renal insufficiency in recent years and the association between MAFLD and renal insufficiency is not entirely clear especially in overweight/obesity. The aim of this study was to analyze the prevalence and risk factors of MAFLD with renal insufficiency in overweight/obese adults. Methods: Individuals who attended check-up at the Second Affiliated Hospital of Xi'an Jiaotong University from 2016 to 2021 were included. The prevalence of MAFLD with renal insufficiency [estimate glomerular filtration rate (eGFR)≤90 ml/min/1.73 m2] in overweight/obesity was estimated. Propensity score-matched (PSM) analysis, univariate and multivariate analysis were used to determine the risk factors for MAFLD with renal insufficiency. Results: From 2016 to 2021, the prevalence of MAFLD in overweight/obesity reached its highest of 44.7% in 2017 and its lowest of 36.9% in 2018；and 33.9% in 2021 and 21.8% in 2019 is the highest and lowest prevalence of MAFLD with renal insufficiency, respectively. MAFLD was more common in men, old individuals, and persons with a higher BMI, and was characterized by significant renal insufficiency. MAFLD with renal insufficiency was more common in women, old individuals, and persons with a higher BMI, and was characterized by significant metabolic dysfunction and liver fibrosis. Multivariable analysis showed BMI, uric acid and fibrosis (evaluated with non-invasive liver fibrosis score FIB-4) were independent risk factors for MAFLD with renal insufficiency. Conclusion: The prevalence of MAFLD with renal insufficiency in overweight/obese adults is quite high in the last 5 years. BMI, uric acid and fibrosis are independent risk factors for MAFLD with renal insufficiency.

The rapid development of cities in recent years has increased the operational pressure of rail vehicles, and due to the characteristics of rail vehicles, including harsh operating environment, frequent starting and braking, resulting in rails and wheels being prone to rail corrugation, polygons, flat scars and other faults. These faults are coupled in actual operation, leading to the deterioration of the wheel–rail contact relationship and causing harm to driving safety. Hence, the accurate detection of wheel–rail coupled faults will improve the safety of rail vehicles’ operation. The dynamic modeling of rail vehicles is carried out to establish the character models of wheel–rail faults including rail corrugation, polygonization and flat scars to explore the coupling relationship and characteristics under variable speed conditions and to obtain the vertical acceleration of the axle box. An APDM time–frequency analysis method is proposed in this paper based on the PDMF adopting Rényi entropy as the evaluation index and employing a WOA to optimize the parameter set. The number of iterations of the WOA adopted in this paper is decreased by 26% and 23%, respectively, compared with PSO and SSA, which means that the WOA performs at faster convergence speed and with a more accurate Rényi entropy value. Additionally, TFR obtained using APDM realizes the localization and extraction of the coupled fault characteristics under rail vehicles’ variable speed working conditions with higher energy concentration and stronger noise resistance corresponding to prominent ability of fault diagnosis. Finally, the effectiveness of the proposed method is verified using simulation and experimental results that prove the engineering application value of the proposed method.

Abstract Background Gastrointestinal stromal tumor (GIST) is a common tumor that originates from the alimentary system mesenchyme. Compared to typical gastrointestinal carcinomas, GISTs exhibit unique malignant behaviors. Bioinformatic tools and subsequent experiments were applied to investigate novel targets involved in GIST progression and imatinib resistance. Methods Differences in gene expression profiles between advanced and nonadvanced GISTs were comprehensively analyzed based on the Gene Expression Omnibus (GEO) dataset GSE136755. A protein–protein interaction (PPI) network was constructed to identify the potential target gene. Gene set enrichment analysis (GSEA) was used to elucidate relevant biological events related to the target gene based on the GSE47911 dataset. Subsequently, immunohistochemistry and Kaplan–Meier analysis were performed to validate the prognostic value of the target gene in GISTs. Overexpression of the target gene was conducted to analyze its function in the proliferation, apoptosis, and imatinib resistance of GIST/T1 cells. Results In the current study, a total of 606 differentially expressed genes (DEGs) were screened based on the GSE136755 dataset, and the upregulated DEGs in advanced GISTs were mainly involved in cell division through functional annotations. The intersecting hub gene, Aurora kinase A (AURKA), was identified by degree and bottleneck algorithms. GSEA revealed that AURKA was involved in cell cycle-related biological processes. Analysis of the Oncomine and GEPIA databases revealed a pattern of elevated AURKA expression in most human malignances. Clinical assays demonstrated that AURKA could be an independent prognostic factor for GISTs. Additionally, overexpression of AURKA was experimentally demonstrated to promote cell proliferation, inhibit cell apoptosis, and enhance imatinib resistance in GIST/T1 cells. Conclusions These findings indicated that overexpression of AURKA promoted GIST progression and enhanced imatinib resistance, implying that AURKA is a potential therapeutic target for GISTs.

To improve the diagnosis and classification of Alzheimer’s disease (AD), a modeling method is proposed based on the combining magnetic resonance images (MRI) brain structural data with metabolite levels of the frontal and parietal regions. First, multi-atlas brain segmentation technology based on T1-weighted images and edited magnetic resonance spectroscopy (MRS) were used to extract data of 279 brain regions and levels of 12 metabolites from regions of interest (ROIs) in the frontal and parietal regions. The t-test combined with false discovery rate (FDR) correction was used to reduce the dimensionality in the data, and MRI structural data of 54 brain regions and levels of 4 metabolites that obviously correlated with AD were screened out. Lastly, the stacked auto-encoder neural network (SAE) was used to classify AD and healthy controls (HCs), which judged the effect of classification method by fivefold cross validation. The results indicated that the mean accuracy of the five experimental model increased from 96 to 100%, the AUC value increased from 0.97 to 1, specificity increased from 90 to 100%, and F1 value increased from 0.97 to 1. Comparing the effect of each metabolite on model performance revealed that the gamma-aminobutyric acid (GABA) + levels in the parietal region resulted in the most significant improvement in model performance, with the accuracy rate increasing from 96 to 98%, the AUC value increased from 0.97 to 0.99 and the specificity increasing from 90 to 95%. Moreover, the GABA + levels in the parietal region was significantly correlated with Mini Mental State Examination (MMSE) scores of patients with AD (r = 0.627), and the F statistics were largest (F = 25.538), which supports the hypothesis that dysfunctional GABAergic system play an important role in the pathogenesis of AD. Overall, our findings support that a comprehensive method that combines MRI structural and metabolic data of brain regions can improve model classification efficiency of AD.

Abstract Background There is no study assessing the risk factors associated with functional dyspepsia (FD) in Chinese children based on the Rome IV criteria. Methods In this cross-sectional study, we analyzed data from eight representative primary and secondary schools to assess the risk factors associated with FD in Chinese children based on the Rome IV criteria. Results A total of 6976 Chinese children were enrolled. The mean age was 14.3 ± 2.5 years, with a range from 7 to 17 years, and 3497 (50.1%) participants were female. FD was prevalent in 209 (3.0%) of the Chinese child population studied. Age (OR = 1.112, P = 0.006), living independent of parents (OR = 1.677, P

Abstract Sleep apnea syndrome (SAS) is a disorder in which respiratory airflow frequently stops during sleep. Alterations in electroencephalogram (EEG) signal are one of the physiological changes that occur during apnea, and can be used to diagnose and monitor sleep apnea events. Herein, we proposed a method to automatically distinguish sleep apnea events using characteristics of EEG signals in order to categorize obstructive sleep apnea (OSA) events, central sleep apnea (CSA) events and normal breathing events. Through the use of an Infinite Impulse Response Butterworth Band pass filter, we divided the EEG signals of C3-A2 and C4-A1 into five sub-bands. Next, we extracted sample entropy and variance of each sub-band. The neighbor composition analysis (NCA) method was utilized for feature selection, and the results are used as input coefficients for classification using random forest, K-nearest neighbor, and support vector machine classifiers. After a 10-fold cross-validation, we found that the average accuracy rate was 88.99%. Specifically, the accuracy of each category, including OSA, CSA and normal breathing were 80.43%, 84.85%, and 95.24%, respectively. The proposed method has great potential in the automatic classification of patients' respiratory events during clinical examinations, and provides a novel idea for the development of an automatic classification system for sleep apnea and normal events without the need for expert intervention.

Gear tooth spalling is one of the inevitable fault modes in the long-term service of the traction transmission system of railway vehicles, which can worsen the dynamic load of the rotating mechanical system and reduce the operating quality. Therefore, it is necessary to study its fault mechanism to guide fault diagnosis scientifically. This paper established a planar railway vehicle model with a traction transmission system and an analytical time-varying meshing stiffness (TVMS) model of the spalling spur gear. Then, it analyzed the dynamic characteristics under traction conditions. The research found that the spalling length and depth affect the amplitude of the TVMS at the defect, while the width affects the range of the TVMS loss. The crest factor is the best evaluation indicator in ideal low-noise environments due to its sensitivity and linearity, but it is not good in strong-noise environments. Similarly, a time–frequency analysis tool cannot significantly detect the sideband characteristics that are excited by spalling. After high-pass filtering, the root mean square and variance exhibit excellent classification and vehicle speed independence in strong-noise environments. This research achievement can provide adequate theoretical support for feature selection and making strategies for fault diagnosis of railway vehicle gear systems.

BackgroundThe effects of psychological interventions on symptoms and psychology of functional dyspepsia (FD) remain unclear. We aimed to comprehensively evaluate the effects of psychological interventions on symptoms and psychology of FD.MethodsWe searched the PubMed, Cochrane Library, and Embase electronic databases for randomized controlled trials (RCTs) evaluating the role of psychological interventions in FD patients published before July 2021. Standardized mean differences (SMDs), risk ratios (RRs) and 95% confidence intervals (CIs) were calculated by a random effects model. Subgroup analyses and sensitivity analyses were also performed.ResultsFourteen RCTs with a total of 1,434 FD patients were included. Compared with the control group, psychological interventions were significantly more likely to symptom improvement [RR = 1.74, 95% CI (1.12, 2.72), p = 0.01], relieve gastrointestinal symptoms scores at follow up [SMD = −1.06, 95% CI (−1.55, −0.57), p < 0.0001], relieve gastrointestinal symptoms scores at end of treatment [SMD = −0.98, 95% CI (−1.29, −0.67), p < 0.001], decrease anxiety [SMD = −0.8, 95% CI (−1.38, −0.22), p = 0.006] and depression levels [SMD = −1.11, 95% CI (−1.62, −0.61), p < 0.001]. The results of the subgroup analysis showed that psychotherapy was more likely to symptom improvement, relieve gastrointestinal symptoms scores and decreased depression levels compared to the control.ConclusionsPsychological interventions may be effective in alleviating the symptoms and psychology of FD, but the effect appears to be limited to psychotherapy with fewer trials for other psychological interventions. More data from high-quality RCTs are needed to confirm their use in the treatment of FD.

Abstract TOB1 participates in various kinds of cancers. However, its role in pancreatic cancer has rarely been reported. In this study, we explored the expression and mechanisms of TOB1 in regulating the malignant phenotype of pancreatic cancer cells. TOB1 expression was determined by data mining and immunohistochemistry (IHC), and its localization was observed by immunofluorescence. CCK‐8 cell proliferation, colony formation, flow cytometric, transwell migration, and Western blot (WB) assays were used to examine how it impacts the malignant phenotype of pancreatic cancer. Furthermore, Foxa2 binding to TOB1 was tested by dual‐luciferase reporter assays, and RNA‐Seq was performed to identify signaling pathways. We found TOB1 was downregulated in pancreatic cancer tissues and was mainly located in the cytoplasm. TOB1 overexpression reduced the proliferation of K‐Ras wild‐type pancreatic cancer cells but made no difference to cell migration and invasion. Foxa2 overexpression significantly enhanced TOB1 promoter activity. Moreover, overexpressing TOB1 substantially enriched the calcium pathway in K‐Ras wild‐type pancreatic cancer cells. In conclusion, TOB1 may suppress the proliferation of K‐Ras wild‐type pancreatic cancer cells by regulating calcium pathway genes.

Blockchain, a type of a decentralized network system that allows mutually distrustful parties to transact securely without involving third parties, has recently been attracting increasing attention. Hence, there must be a consensus mechanism to ensure a distributed consensus among all participants. Such a consensus mechanism may also be used to guarantee fairness, correctness and security of such decentralized systems. Thus, in this paper we propose a novel consensus mechanism named GSCS that is an improved version of PoW. Compared with existing consensus mechanisms (such as PoW, PoS and so on), GSCS provides strong resistance to resource centralization, the quantum attack and other malicious attacks. In this work, we first present the serial mining puzzle to resist collusive mining and the quantum attack. It guarantees that participants can only obtain a negligible advantage by solving the relevant problem in parallel. Second, GSCS considers the influence of participant credibility. The credibility is reflected by the mining behavior of each participant and directly influence to the mining difficulty of participant. Thus, credible participants enjoy a higher probability of winning the mining competition than do participants who are not credible. Finally, performance of GSCS is analyzed in terms of the common prefix, chain quality, chain growth, and power cost. The results indicate that GSCS is security- and incentive-compatible with suitable security parameter settings. In brief, GSCS has the potential to ensure a more secure and robust environment for decentralized blockchain systems.

Magnetic detection electrical impedance tomography (MDEIT) is a novel imaging technique that aims to reconstruct the conductivity distribution with electrical current injection and the external magnetic flux density measurement by magnetic sensors. Aiming at improving the resolution and accuracy of MDEIT and providing an efficient imaging method for breast cancer diagnosis, a new algorithm based on stacked auto-encoder (SAE) neural network is proposed. Both numerical simulation and phantom experiments are done to verify its feasibility. In the numerical simulation, an amount of sample data with different conductivity distribution are calculated. Then a neural network model is established and trained by training these samples. Finally, the conductivity distribution of an imaging target with the anomaly location can be reconstructed by the network model. The reconstruction result of the SAE algorithm is compared with the reconstruction results of the traditional sensitivity matrix (SM) algorithm and the back propagation (BP) neural network algorithm. Under the noise of 30dB, the relative errors of BP algorithm, SM algorithm and SAE algorithm are 137.19%, 24.90% and 15.28% respectively. Result shows by the SAE algorithm, the location of anomalies is reconstructed more accurately, the conductivity value is more closely to the real one and the anti-noise performance is more robust. At last, a breast phantom experiment by self-made platforms is completed to verify the application feasibility of the new algorithm. The relative reconstruction error of conductivity by proposed SAE algorithm can be reduced to 14.56%. The results show that by SAE algorithm, MDEIT can be a promising approach in clinical diagnosis of breast cancer, and it also provide more potential application prospect for the extensive application of MDEIT.

As a noninvasive and quantitative method, fluorescence molecular tomography (FMT) has many potential applications in biomedical field. It has the power to resolve in three-dimension (3D), the molecular processes in small animal in-vivo in both theory and practice. This paper proposes to solve the problem of reconstruction error and speed by using stacked auto-encoders (SAE). A finite element method (FEM) solution to the Laplace transformed time-domain coupled diffusion equations is employed as the forward model. The reconstruction model is formulated under the framework of SAE. Numerical simulation experiments were conducted to compare the reconstruction results of SAE and algebraic reconstruction technique (ART). We demonstrated that the proposed reconstruction algorithm can retrieve the positions and shapes of the targets more accurately than ART. This advantage of SAE is especially reflected in the reconstruction for small targets with a radius of 2 mm and 3 mm.

The intelligent diagnosis of wheel flat based on vibration image classification is a promising research subject for performance maintenance of railway vehicles. However, the image representation method of vibration signal and classification network construction under small samples have become two obstacles to intelligent diagnosis of wheel flat. This paper presents a novel frequency-domain Gramian angular field (FDGAF) algorithm to encode the vibration signal of wheel flat to featured images. Furthermore, a modified transfer learning network is introduced to classify these featured images under small samples without any involvement of prior knowledge. The proposed FDGAF can calculate the Gramian angular matrix of axle box acceleration signal in frequency domain and assign frequency position dependence to the featured images to preserve original characteristic information. Then, these featured images can be intelligent classified by a transfer learning network under the condition of 30 sample without require of prior knowledge. To verify the efficiency of this proposed method, 12 cases of artificial wheel flats are processed on a scaled railway test rig, and their axle box acceleration signals are collected to obtain visual diagnosis results. The verfication proves that FDGAF is able to obtain accurate diagnostic results with high separability, for separability indexes of FDGAF reaches 10.8, 8.7, 14.9, and 5.8. We anticipate that this method will find use in the performance maintenance of railway vehicles and the improvement of industrial condition monitoring.

In recent years, urban rail transportation has rapidly developed in China and become one of the most important modes of travel. Most existing studies on the dynamic characteristics of urban rail trains have been based on single-section trains, and there have been fewer studies on marshaling urban rail trains that incorporate traction transmission systems. The dynamic performance of each carriage directly affects the operational reliability and even the running safety of urban rail trains. For this reason, in this paper, a marshaling urban rail train model with a traction transmission system was established and its accuracy was validated by field tests. This dynamics model enables the consideration of the coupling interactions between the gear transmission motion, the vertical, the lateral and the longitudinal motions of the vehicle. First, the model accuracy was validated by field tests. Then, the relationship between the motor torque and the running time of the urban rail train under traction conditions was calculated. Finally, the dynamic performance of each car of the marshaling train was studied. The research results show that there is a clear difference between the dynamics of the motor car and the trailer, and that the motor car is significantly inferior to the trailer. Among the four motor cars, the dynamic performances of the first and last moving cars were worse than those of the other motor cars. Among the two trailers, the trailer at the back was worse than the trailer at the front. The traction transmission system has a greater impact on the vertical and lateral vibration of the train bogie frame and wheelset, but the impact on the vibration of the car body is negligible. This paper provides theoretical support for the research one train dynamic performance optimization and operation safety.

The energy management system (EMS) of hybridization and electrification plays a pivotal role in improving the stability and cost-effectiveness of future vehicles. Existing efforts mainly concentrate on specific optimization targets, like fuel consumption, without sufficiently taking into account the degradation of on-board power sources. In this context, a novel multi-objective energy management strategy based on deep reinforcement learning is proposed for a hybrid electric vehicle (HEV), explicitly conscious of lithium-ion battery (LIB) wear. To be specific, this paper mainly contributes to three points. Firstly, a non-parametric reward function is introduced, for the first time, into the twin-delayed deep deterministic policy gradient (TD3) strategy, to facilitate the optimality and adaptability of the proposed energy management strategy and to mitigate the effort of parameter tuning. Then, to cope with the problem of state redundancy, state space refinement techniques are included in the proposed strategy. Finally, battery health is incorporated into this multi-objective energy management strategy. The efficacy of this framework is validated, in terms of training efficiency, optimality and adaptability, under various standard driving tests.

The nickel-based superalloys processed by additive manufacturing are very promising structural materials in aircraft engines as high-pressure turbine discs. In this work, a nickel-based superalloy with good mechanical performance and few defects was manufactured by optimized selective laser melting (SLM) processing. We then investigated the influences of post heat treatments on its microstructural characteristics and mechanical performance. The results indicated that a fine grain size with uniform grain orientation was presented in the as-printed nickel-based superalloy sample. After heat treatments, the grains were slightly grown and grain orientation was also changed. Under transmission electron microscopy, fine subgrains with an approximate size of 0.5 μm were found in the as-printed sample which accompanied massive dislocations and discontinuous Laves phases. After the post heat treatments, fine subgrains and less dislocations were retained. On the other hand, massive γ′ and γ″ precipitates with an orientation relationship of (001)[100]γ′//(100)[001]γ or (001)[100]γ″//(100)[001]γ were formed. As a result, the yield stress and tensile strength increased to 1362 and 1410 MPa, respectively, in a heat-treated sample, which retained the identical elongation of the as-printed specimen.

During the movement of rail trains, trains are often subjected to harsh operating conditions such as variable speed and heavy loads. It is therefore vital to find a solution for the issue of rolling bearing malfunction diagnostics in such circumstances. This study proposes an adaptive technique for defect identification based on multipoint optimal minimum entropy deconvolution adjusted (MOMEDA) and Ramanujan subspace decomposition. MOMEDA optimally filters the signal and enhances the shock component corresponding to the defect, after which the signal is automatically decomposed into a sequence of signal components using Ramanujan subspace decomposition. The method’s benefit stems from the flawless integration of the two methods and the addition of the adaptable module. It addresses the issues that the conventional signal decomposition and subspace decomposition methods have with redundant parts and significant inaccuracies in fault feature extraction for the vibration signals under loud noise. Finally, it is evaluated through simulation and experimentation in comparison to the current widely used signal decomposition techniques. According to the findings of the envelope spectrum analysis, the novel technique can precisely extract the composite flaws that are present in the bearing, even when there is significant noise interference. Additionally, the signal-to-noise ratio (SNR) and fault defect index were introduced to quantitatively demonstrate the novel method’s denoising and potent fault extraction capabilities, respectively. The approach works well for identifying bearing faults in train wheelsets.

Magnetic induction tomography (MIT) is a non-invasive and non-contact imaging method that uses an excitation coil to generate time-varying magnetic fields in space and reconstruct the internal conductivity distribution based on the phase difference. In this study, a new MIT reconstruction algorithm was proposed for non-contact measurement and monitoring of the location of the anomaly in the biomedical object of interest. To reconstruct the distribution of electrical characteristics inside the biological tissue, this technique uses a stacked auto-encoder (SAE) neural network composed of a multi-layer automatic encoder. The location and reconstruction accuracy of the anomaly based on SAE and back-projection were compared, and a hemorrhagic stroke was simulated to verify the practicability of the proposed algorithm. The results showed that the relative error of reconstruction based on the SAE network algorithm reached 0.29%, which improved anomaly reconstruction accuracy and reduced the prediction time to 0.02 s. At the same time, the network was used for the reconstruction of hemorrhagic stroke in different locations, amounts, and shapes. Accordingly, the SAE neural network reconstruction algorithm proposed in this study, which can autonomously learn the non-linear relationship between input and output, can solve the defects of the traditional reconstruction algorithm, such as serious artifacts and complex calculations.

In recent years, the Internet of Things (IoT) has allowed the easy, intelligent, and efficient connection of many devices used in daily life by means of numerous smart sensors which communicate with each other using wireless signals. The rapid development of the IoT has been a result of recent advances in sensing technology. This paper proposes a three-phase methodology to improve the quality of experience for IoT system technologies. The proposed method employs the concepts of simple routing and two well-known multi-criteria decision-making method (MCDM) techniques: The Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). First, all simple routings are obtained using the proposed depth-first search technology (DFS). AHP is applied to analyze the structure of the problem and to obtain weights for various selected criteria in the second phase. In the third phase, TOPSIS is utilized to rank the simple routings, which are simple paths. A case study example is provided to demonstrate the proposed three-phase methodology. The results from the numerical experiments show that the proposed methodology can successfully achieve the aim of this paper.

The diffuse optical tomography (DOT) technique which uses the traditional linear iterative algorithm has the problems of slow calculation speed and low reconstruction imaging accuracy in the inverse problem reconstruction, which limits its clinical application and development. This paper proposes an inverse-problem solving technology based on a stacked auto-encoder (SAE) network to improve the reconstruction accuracy of anomaly position, size and absorption coefficient in tissues. The reconstruction accuracy of anomaly position, size and absorption coefficient obtained by the traditional algebraic reconstruction technique (ART) method and the SAE based method are experimentally compared. The experimental results show that the SAE based method achieves the prediction accuracy of anomaly position of 96.25%, thus improving the accuracy and shortening the reconstruction time compared with the traditional ART method. Accordingly, the proposed method provides a better solution to the problem of the inaccurate reconstruction of the position and size of the rapid DOT based positioning of anomalies.

In this paper, the signal-to-noise ratios (SNR) of two image channels were enhanced with the fast digital lock-in algorithm. In order to simultaneously improve the quality of white and fluorescence images obtained by fluorescence endoscope, and improve the SNR to achieve a better image processing effect, two sources of white light and near-infrared light of a fluorescence endoscope were modulated, then the acquired images were demodulated into white and fluorescence images. A fluorescent endoscope experimental platform was setup to acquire endoscopic images of a target dyed by indocyanine green. The experimental results showed that the SNR of white and fluorescent images without the lock-in algorithm were 36.56 dB and 33.47 dB, respectively. However, with the lock-in algorithm, the SNR of white and fluorescent images were 39.54 dB and 35.70 dB, respectively. The SNR of white and fluorescent images was increased by 8.2% and 6.7%, respectively, by appling the digital lock-in algorithm. Therefore, this novel fluorescence endoscope based on the fast digital lock-in algorithm can rapidly and simultaneously obtain two-channel images of white light and fluorescence, effectively enhance the SNR of white and fluorescent images, and improve the imaging quality.

The swing behaviour of tower cranes under compound working conditions is closely related to construction safety and structural health. This paper presents dynamic models and simulated them for parameter analysis to understand tower cranes’ dynamic characteristics and vibration features under compound working conditions. The parameters contain payload mass, rope length, lifting acceleration, slewing acceleration, luffing acceleration, and initial angle. For the lifting-luffing coupling motion (LLCM) and lifting-slewing coupling motion (LSCM) of the tower crane, the D’Alembert principle provides a theoretical basis for the derivation of system dynamics equations. The spatial swing angle description of the crane payload includes the time-domain response and frequency-domain response, which uses a dynamic model. The result shows that the mass has little effect on the spatial swing angle. The value of the lifting acceleration is stable at 0.004 m/s2 to 0.01 m/s2. Peak value (PV), root mean square value (RMS), root mean square frequency (RMSF), and frequency standard deviation (RVF) present the best sensitivity to changes in the spatial swing angle response. When PV of angles θ and β increases by tens of thousands of times in the LLCM, PV can reflect the phenomenon of angle divergence. The skewness value (SV) increases by 3422% at the severe swing angle performance in the LSCM. The swing angle regularity with the compound working conditions can provide theoretical guidance for eliminating structural vibration.

Brain-controlled wheelchair (BCW) has the potential to improve the quality of life for people with motor disabilities. A lot of training is necessary for users to learn and improve BCW control ability and the performances of BCW control are crucial for patients in daily use. In consideration of safety and efficiency, an indoor simulated training environment is built up in this paper to improve the performance of BCW control. The indoor simulated environment mainly realizes BCW implementation, simulated training scenario setup, path planning and recommendation, simulated operation, and scoring. And the BCW is based on steady-state visual evoked potentials (SSVEP) and the filter bank canonical correlation analysis (FBCCA) is used to analyze the electroencephalography (EEG). Five tasks include individual accuracy, simple linear path, obstacles avoidance, comprehensive steering scenarios, and evaluation task are designed, 10 healthy subjects were recruited and carried out the 7-days training experiment to assess the performance of the training environment. Scoring and command-consuming are conducted to evaluate the improvement before and after training. The results indicate that the average accuracy is 93.55% and improves from 91.05% in the first stage to 96.05% in the second stage (p = 0.001). Meanwhile, the average score increases from 79.88 in the first session to 96.66 in the last session and tend to be stable (p < 0.001). The average number of commands and collisions to complete the tasks decreases significantly with or without the approximate shortest path (p < 0.001). These results show that the performance of subjects in BCW control achieves improvement and verify the feasibility and effectiveness of the proposed simulated training environment.