A5086326544- Reliability and Maintenance Optimization
- Statistical Distribution Estimation and Applications
- Machine Fault Diagnosis Techniques
- Machine Learning in Healthcare
- Gut microbiota and health
- Inflammatory Bowel Disease
- Artificial Intelligence in Healthcare
- Healthcare Operations and Scheduling Optimization
- Energy Load and Power Forecasting
- Non-Destructive Testing Techniques
- COVID-19 diagnosis using AI
- Diabetic Foot Ulcer Assessment and Management
- Photovoltaic System Optimization Techniques
- Intensive Care Unit Cognitive Disorders
- Cerebral Palsy and Movement Disorders
- Software Reliability and Analysis Research
- Fluid Dynamics and Heat Transfer
- Radiomics and Machine Learning in Medical Imaging
- Solar Radiation and Photovoltaics
- Risk and Safety Analysis
- Sepsis Diagnosis and Treatment
- Fault Detection and Control Systems
- Electrohydrodynamics and Fluid Dynamics
- Plant Stress Responses and Tolerance
- Infrastructure Maintenance and Monitoring
Qiqihar Medical University
2025
Hubei University of Chinese Medicine
2024
Chapman University
2021-2024
Hangzhou First People's Hospital
2023-2024
Westlake University
2024
Guangzhou University
2023-2024
Shenzhen Second People's Hospital
2024
Southern University of Science and Technology
2024
Jinan University
2024
Zhejiang University
2013-2024
Objective To observe and evaluate the effect of a single intravenous injection low-dose esketamine on post-operative pain post-partum depression (PPD) in cesarean delivery patients. Methods A total 210 patients undergoing elective under combined spinal-epidural anesthesia were divided into an group (Group S, n = 105) normal saline L, by random number table. At 5 min after childbirth, S given 0.25 mg/kg esketamine, whereas L received equal volume saline. The primary outcomes included control...
This paper presents two probabilistic approaches based on bootstrap method and quantile regression (QR) to estimate the uncertainty associated with solar photovoltaic (PV) power point forecasts. Solar PV output forecasts are obtained using a hybrid intelligent model, which is composed of data filtering technique wavelet transform (WT) soft computing model (SCM) radial basis function neural network (RBFNN) that optimized by particle swarm optimization (PSO) algorithm. The forecast capability...
Deep generative networks in recent years have reinforced the need for caution while consuming various modalities of digital information. One avenue deepfake creation is aligned with injection and removal tumors from medical scans. Failure to detect deepfakes can lead large setbacks on hospital resources or even loss life. This paper attempts address detection such attacks a structured case study. Specifically, we evaluate eight different machine learning algorithms, which include three...
Pavement defects such as cracks, net and pit slots can cause potential traffic safety problems. The timely detection identification play a key role in reducing the harm of various pavement defects. Particularly, recent development deep learning-based CNNs has shown competitive performance image classification. To detect automatically improve effects, multi-scale mobile attention-based network, which we termed MANet, is proposed to perform architecture encoder-decoder used where encoder...
Abstract Postoperative depression (POD) and postoperative cognitive dysfunction (POCD) have placed heavy burden on patients’ physical mental health in recent years. Sleep disturbance before surgery is a common phenomenon that has been increasingly believed to affect recovery, especially aged patients, while little attention paid sleep disruption the potential mechanism remains ambiguous. Ketamine reported attenuate POCD after cardiac elicit rapid-acting sustained antidepressant actions. The...
Postoperative cognitive dysfunction (POCD) is a common postoperative complication in elderly patients, and neuroinflammation key hallmark. Recent studies suggest that the NOD-like receptor family, pyrin domain containing 3 (NLRP3) inflammasome-mediated astrocytes pyroptosis involved regulation of many neurocognitive diseases, while its role POCD remains obscure. Carnosine natural endogenous dipeptide with anti-inflammatory neuroprotective effects. To explore effect carnosine on mechanism, we...
With the rapid development of sensor and information technology, now multisensor data relating to system degradation process are readily available for condition monitoring remaining useful life (RUL) prediction. The traditional fusion RUL prediction methods either not flexible enough capture highly nonlinear relationship between health or have fully utilized past observations trajectory. In this article, we propose a joint prognostic model (JPM), where Bayesian linear models developed data,...
Bone marrow mesenchymal stem cells (BMSCs) have demonstrated potential in the treatment of radiation-induced brain injury (RIBI); however, presence blood-brain barrier (BBB) limits their therapeutic efficacy. Additionally, precise mechanisms behind use BMSCs treating RIBI are still not well understood. This study aimed to investigate efficacy mannitol and on neuronal autophagy RIBI. In study, models were first established male Sprague-Dawley (SD) rats. Evans blue staining was performed...
Remaining useful life prediction plays an important role in ensuring the safety, availability, and efficiency of various engineering systems. In this paper, we propose a flexible Bayesian multiple-phase modeling approach to characterize degradation signals for prognosis. The priors are specified with novel stochastic process model is formulated state-space facilitate online monitoring prediction. A particle filtering algorithm stratified sampling partial Gibbs resample-move strategy...
Abstract Trichosanthes kirilowii – Allium macrostemon (Chinese name Gualou and Xiebai, GLXB), a classical herb pair, has significant clinical efficacy in the treatment of myocardial ischemia (MI). In this study, network pharmacology combined with RNA‐seq strategy was employed to predict targets pathways GLXB for MI. significantly modulated signaling related pathology MI, such as anti‐inflammatory anti‐apoptotic WNT, PI3K/AKT, AMPK. GSEA showed that administration downregulated these key...
Prognostics play an increasingly important role in modern engineering systems for smart maintenance decision-making. In parametric regression-based approaches, the models are often too rigid to model degradation signals many applications. this paper, we propose a Bayesian multiple-change-point (CP) modeling framework better capture path and improve prognostics. At offline stage, novel stochastic process is proposed joint prior of CPs positions. All hyperparameters estimated through empirical...
Providing timely patient care while maintaining optimal resource utilization is one of the central operational challenges hospitals have been facing throughout pandemic. Hospital length stay (LOS) an important indicator hospital efficiency, quality care, and resilience. Numerous researchers developed regression or classification models to predict LOS. However, conventional suffer from lack capability make use typically censored clinical data. We propose time-to-event modeling techniques,...
Idiopathic toe walking (ITW) is a gait abnormality in which children touch at initial contact and demonstrate limited or no heel throughout the cycle. Toe results poor balance, increased risk of falling, developmental delays among children. Identifying steps during can facilitate targeted intervention diagnosed with ITW. With recent advances wearable sensing, communication technologies, machine learning, new avenues managing behavior are feasible. In this study, we investigate capabilities...
The subsea control system, a pivotal element of the production plays an essential role in collecting data and real-time operational monitoring, crucial for consistent stable output offshore oil gas fields. increasing demand secure extraction underscores necessity advanced reliability modeling effective maintenance strategies systems. Given enhanced equipment due to technological advancements, resulting scarce failure data, traditional methods reliant on historical are becoming inadequate....