An observer-based type-3 fuzzy control for non-holonomic wheeled robots

Non-holonomic wheeled robots (NWR) comprise a type of robotic system; they use wheels for movement and offer several advantages over other types. They are efficient, highly, and maneuverable, making them ideal for factory automation, logistics, transportation, and healthcare. The control of this type of robot is complicated, due to the complexity of modeling, asymmetrical non-holonomic constraints, and unknown perturbations in various applications. Therefore, in this study, a novel type-3 (T3) fuzzy logic system (FLS)-based controller is developed for NWRs. T3-FLSs are employed for modeling, and the modeling errors are considered in stability analysis based on the symmetric Lyapunov function. An observer is designed to detect the error, and its effect is eliminated by a developed terminal sliding mode controller (SMC). The designed technique is used to control a case-study NWR, and the results demonstrate the good accuracy of the developed scheme under non-holonomic constraints, unknown dynamics, and nonlinear disturbances

Farnesoid X Receptor (FXR) Aggravates Amyloid-β-Triggered Apoptosis by Modulating the cAMP-Response Element-Binding Protein (CREB)/Brain-Derived Neurotrophic Factor (BDNF) Pathway In Vitro

BACKGROUND: Alzheimer’s disease (AD), which results in cognitive deficits, usually occurs in older people and is mainly caused by amyloid beta (Aß) deposits and neurofibrillary tangles. The bile acid receptor, farnesoid X receptor (FXR), has been extensively studied in cardiovascular diseases and digestive diseases. However, the role of FXR in AD is not yet understood. The purpose of the present study was to investigate the mechanism of FXR function in AD. MATERIAL AND METHODS: Lentivirus infection, flow cytometry, real-time PCR, and western blotting were used to detect the gain or loss of FXR in cell apoptosis induced by Aß. Co-immunoprecipitation was used to analyze the molecular partners involved in Aß-induced apoptosis. RESULTS: We found that the mRNA and protein expression of FXR was enhanced in Ab-triggered neuronal apoptosis in differentiated SH-SY5Y cells and in mouse hippocampal neurons. Overexpression of FXR aggravated Aß-triggered neuronal apoptosis in differentiated SH-SY5Y cells, and this effect was further increased by treatment with the FXR agonist 6ECDCA. Molecular mechanism analysis by co-immunoprecipitation and immunoblotting revealed that FXR interacted with the cAMP-response element-binding protein (CREB), leading to decreased CREB and brain-derived neurotrophic factor (BDNF) protein levels. Low expression of FXR mostly reversed the Aß-triggered neuronal apoptosis effect and prevented the reduction in CREB and BDNF. CONCLUSIONS: These data suggest that FXR regulates Aß-induced neuronal apoptosis, which may be dependent on the CREB/BDNF signaling pathway in vitro

Deformation rule of bored pile & steel support for deep foundation pit in sandy pebble geology

Regarding the whole excavation process of the support system of the Southwest Jiaotong University Station of Chengdu Metro Line 6 (the deep foundation pit bored pile + steel support and support system) as the engineering background, this paper studies the deformation rule of the deep foundation pit bored pile + steel support of the sandy pebble foundation. The deformation rule of this support system, the settlement rule of the ground surface outside the pit, and the rule of the uplift of the loose at the bottom of the pit are studied. A key analysis of the positive corner of the foundation pit is conducted, and the rationality of the optimization of the support scheme is evaluated. This paper provides effective guidance for the subsequent deep foundation pit construction and provides a reference for deep foundation pit construction

Investigation and analysis of a Salmonella Enteritis food poisoning caused by sandwiches in Zhoushan

Objective To investigate a food poisoning events occurred in multiple schools at the same time, and analyze pathogenic factor, contaminated food and source, in order to guide clinical treatment and preventive measures. Methods Based on the investigation of clinical characteristics and epidemiological distribution of patients, homology analysis of Salmonella from different sources was carried out with the combination of pulsed field gel electrophoresis (PFGE) in the laboratory. Results Totally 37 suspected cases were found from 4 school in different districts, 19 cases were diagnosed. The main clinical features of the patients were diarrhea (70.27%, 26/37), fever (54.05%, 20/37), abdominal pain (51.35%,19/37) and vomiting (37.84%, 17/37). A total of 24 strains of Salmonella Enteritidis were isolated in the laboratory, of which 19 strains were from cases and 5 strains were from sandwiches and their dried meat floss. According to PFGE, 24 strains of Salmonella Enteritidis were clustered to 100.00%. The drug resistance rate of 19 cases was 100.00% to nalidixic acid and 5.26% (1/19) to cefoxitin and imipenem. Conclusion Combined with the clinical feature, epidemiological investigation and laboratory test results, it was confirmed that the main cause of the incident was the raw material of the sandwich which was contaminated by Salmonella Enteritidis. It is suggested that the regulatory department should strengthen the supervision of the school catering company, improve the food safety awareness and prevent the foodborne disease

A Phenomenological Thermal-Mechanical Viscoelastic Constitutive Modeling for Polypropylene Wood Composites

This paper presents a phenomenological thermal-mechanical viscoelastic constitutive modeling for polypropylene wood composites. Polypropylene (PP) wood composite specimens are compressed at strain rates from 10−4 to 10−2 s−1 and at temperature of , , and , respectively. The mechanical responses are shown to be sensitive both to strain rate and to temperature. Based on the Maxwell viscoelastic model, a nonlinear thermal-mechanical viscoelastic constitutive model is developed for the PP wood composite by decoupling the effect of temperature with that of the strain rate. Corresponding viscoelastic parameters are obtained through curve fitting with experimental data. Then the model is used to simulate thermal compression of the PP wood composite. The predicted theoretical results coincide quite well with experimental data. The proposed constitutive model is then applied to the thermoforming simulation of an automobile interior part with the PP wood composites

Sentinel lymph node biopsy in oral cavity cancer using indocyanine green: A systematic review and meta-analysis

This meta-analysis was conducted to evaluate the value of indocyanine green (ICG) in guiding sentinel lymph node biopsy (SLNB) for patients with oral cavity cancer. An electronic database search (PubMed, MEDLINE, Cochrane Library, Embase, and Web of Science) was performed from their inception to June 2020 to retrieve clinical studies of ICG applied to SLNB for oral cavity cancer. Data were extracted from 14 relevant articles (226 patients), and 9 studies (134 patients) were finally included in the meta-analysis according to the inclusion and exclusion criteria. The pooled sentinel lymph node (SLN) sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 88.0% (95% confidence interval [CI], 74.0-96.0), 64.0% (95% CI, 61.0-66.0), 2.45 (95% CI, 1.31-4.60), 0.40 (95% CI, 0.17-0.90), and 7.30 (95% CI, 1.74-30.68), respectively. The area under the summary receiver operating characteristic curve was 0.8805. In conclusion, ICG applied to SLNB can effectively predict the status of regional lymph nodes in oral cavity cancer

A Continuum Description of Rarefied Gas Dynamics (I)--- Derivation From Kinetic Theory

We describe an asymptotic procedure for deriving continuum equations from the kinetic theory of a simple gas. As in the works of Hilbert, of Chapman and of Enskog, we expand in the mean flight time of the constituent particles of the gas, but we do not adopt the Chapman-Enskog device of simplifying the formulae at each order by using results from previous orders. In this way, we are able to derive a new set of fluid dynamical equations from kinetic theory, as we illustrate here for the relaxation model for monatomic gases. We obtain a stress tensor that contains a dynamical pressure term (or bulk viscosity) that is process-dependent and our heat current depends on the gradients of both temperature and density. On account of these features, the equations apply to a greater range of Knudsen number (the ratio of mean free path to macroscopic scale) than do the Navier-Stokes equations, as we see in the accompanying paper. In the limit of vanishing Knudsen number, our equations reduce to the usual Navier-Stokes equations with no bulk viscosity.Comment: 16 page

Machine learning in the prediction of post-stroke cognitive impairment: a systematic review and meta-analysis

ObjectiveCognitive impairment is a detrimental complication of stroke that compromises the quality of life of the patients and poses a huge burden on society. Due to the lack of effective early prediction tools in clinical practice, many researchers have introduced machine learning (ML) into the prediction of post-stroke cognitive impairment (PSCI). However, the mathematical models for ML are diverse, and their accuracy remains highly contentious. Therefore, this study aimed to examine the efficiency of ML in the prediction of PSCI.MethodsRelevant articles were retrieved from Cochrane, Embase, PubMed, and Web of Science from the inception of each database to 5 December 2022. Study quality was evaluated by PROBAST, and c-index, sensitivity, specificity, and overall accuracy of the prediction models were meta-analyzed.ResultsA total of 21 articles involving 7,822 stroke patients (2,876 with PSCI) were included. The main modeling variables comprised age, gender, education level, stroke history, stroke severity, lesion volume, lesion site, stroke subtype, white matter hyperintensity (WMH), and vascular risk factors. The prediction models used were prediction nomograms constructed based on logistic regression. The pooled c-index, sensitivity, and specificity were 0.82 (95% CI 0.77–0.87), 0.77 (95% CI 0.72–0.80), and 0.80 (95% CI 0.71–0.86) in the training set, and 0.82 (95% CI 0.77–0.87), 0.82 (95% CI 0.70–0.90), and 0.80 (95% CI 0.68–0.82) in the validation set, respectively.ConclusionML is a potential tool for predicting PSCI and may be used to develop simple clinical scoring scales for subsequent clinical use.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=383476