A graph self-supervised residual learning framework for domain identification and data integration of spatial transcriptomics.

Spatial transcriptomics (ST) technologies allow for comprehensive characterization of gene expression patterns in the context of tissue microenvironment. However, accurately identifying domains with spatial coherence in both gene expression and histology in situ and effectively integrating data from multi-sample remains challenging. Here, we propose ResST, a graph self-supervised residual learning model based on graph neural network and Margin Disparity Discrepancy (MDD) theory.

Prediction of adsorption performance of ZIF-67 for malachite green based on artificial neural network using L-BFGS algorithm.

Given the necessity and urgency in removing organic pollutants such as malachite green (MG) from the environment, it is vital to screen high-capacity adsorbents using artificial neural network (ANN) methods quickly and accurately. In this study, a series of ZIF-67 were synthesized, which adsorption properties for organic pollutants, especially MG, were systematically evaluated and determined as 241.720 mg g (25 ℃, 2 h).

Optimizing Temperature Setting for Decomposition Furnace Based on Attention Mechanism and Neural Networks.

The temperature setting for a decomposition furnace is of great importance for maintaining the normal operation of the furnace and other equipment in a cement plant and ensuring the output of high-quality cement products. Based on the principles of deep convolutional neural networks (CNNs), long short-term memory networks (LSTMs), and attention mechanisms, we propose a CNN-LSTM-A model to optimize the temperature settings for a decomposition furnace. The proposed model combines the features selected by Least Absolute Shrinkage and Selection Operator (Lasso) with others suggested by domain experts as inputs, and uses CNN to mine spatial features, LSTM to extract time series information, and an attention mechanism to optimize weights.

CLIP-Driven Prototype Network for Few-Shot Semantic Segmentation.

Recent research has shown that visual-text pretrained models perform well in traditional vision tasks. CLIP, as the most influential work, has garnered significant attention from researchers. Thanks to its excellent visual representation capabilities, many recent studies have used CLIP for pixel-level tasks.

Incidence and Outcome of Reintubation in the Postanesthesia Care Unit: A Single-Center, Retrospective, Observational Matched Cohort Study in China.

Purpose: To investigate the incidence and outcome of reintubation after planned extubation (RAP) in the postanesthesia care unit (PACU) in China.

Design: A single-center, retrospective, 1:2 matched cohort study following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement.

Methods: Among 121,965 patients in the PACU, 14 patients with RAP were included in this study from January 1, 2017 to December 31, 2019.

Neural-Network-Based Adaptive Fault-Tolerant Cooperative Control of Heterogeneous Multiagent Systems With Multiple Faults and DoS Attacks.

In this article, the issue of adaptive fault-tolerant cooperative control is addressed for heterogeneous multiple unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) with actuator faults and sensor faults under denial-of-service (DoS) attacks. First, a unified control model with actuator faults and sensor faults is developed based on the dynamic models of the UAVs and UGVs. To handle the difficulty introduced by the nonlinear term, a neural-network-based switching-type observer is established to obtain the unmeasured state variables when DoS attacks are active.

Automatic Analysis of Transverse Musculoskeletal Ultrasound Images Based on the Multi-Task Learning Model.

Musculoskeletal ultrasound imaging is an important basis for the early screening and accurate treatment of muscle disorders. It allows the observation of muscle status to screen for underlying neuromuscular diseases including myasthenia gravis, myotonic dystrophy, and ankylosing muscular dystrophy. Due to the complexity of skeletal muscle ultrasound image noise, it is a tedious and time-consuming process to analyze.

Secondary preventing effect of lung cancer in non-high-risk population: A retrospective investigation of opportunistic screening with low-dose computed tomography in Wuhan.

Background: Given the mortality benefit of low-dose computed tomography (LDCT) screening on high-risk populations, the retrospective investigation intended to identify the benefits of LDCT on lung cancer screening among the general demographic cohorts.

Methods: We used an opportunistic screening with LDCT implemented during the pandemic in Wuhan to study the impact on subsequent thoracic surgeries, especially surgeries for lung cancer. Patients who received LDCT from October 1, 2019, to July 31, 2020, in three Triple-A accredited hospitals in Wuhan were included in the study.

Distributed Event-Triggered Quantized Fault-Tolerant Control of Linear Multiagent Systems With External Disturbances and Parameter Uncertainties.

In this article, the issue of fault-tolerant leader-following consensus under a distributed dynamic event-triggered mechanism is addressed for linear multiagent systems (MASs) in the presence of unknown parameter uncertainties, external disturbances, and actuator faults, including loss of effectiveness and bias, in which the mechanism is with quantized state measurements. Due to the fact that information is transmitted via a bandwidth-limited communication network, a quantized control scheme with a uniform quantizer is introduced for leader-following consensus. In order to decrease the communication load and save the limited communication network resources, a distributed event-triggered mechanism is studied for leader-following consensus problem of linear MASs with quantized state measurements.

Adaptive Fault-Tolerant Formation Control of Heterogeneous Multi-Agent Systems under Directed Communication Topology.

This paper investigates the adaptive fault-tolerant formation control scheme for heterogeneous multi-agent systems consisting of unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs) with actuator faults, parameter uncertainties and external disturbances under directed communication topology. Firstly, the dynamic models of UAVs and USVs are introduced, and a unified heterogeneous multi-agent system model with actuator faults is established. Then, a distributed fault-tolerant formation controller is proposed for the unified model of UAVs and USVs in the XY plane by using adaptive updating laws and radial basis function neural network.

Gaussian-Based Adaptive Fish Migration Optimization Applied to Optimization Localization Error of Mobile Sensor Networks.

Location information is the primary feature of wireless sensor networks, and it is more critical for Mobile Wireless Sensor Networks (MWSN) to monitor specific targets. How to improve the localization accuracy is a challenging problem for researchers. In this paper, the Gaussian probability distribution model is applied to randomize the individual during the migration of the Adaptive Fish Migration Optimization (AFMO) algorithm.

Automatic Measurement of Pennation Angle from Ultrasound Images using Resnets.

In this study, an automatic pennation angle measuring approach based on deep learning is proposed. Firstly, the Local Radon Transform (LRT) is used to detect the superficial and deep aponeuroses on the ultrasound image. Secondly, a reference line are introduced between the deep and superficial aponeuroses to assist the detection of the orientation of muscle fibers.

Perioperative risk factors for recovery room delirium after elective non-cardiovascular surgery under general anaesthesia.

Background: Although postoperative delirium is a frequent complication of surgery, little is known about risk factors for delirium occurring in the post-anaesthesia care unit (PACU). The aim of this study was to determine pre- and intraoperative risk factors for the development of recovery room delirium (RRD) in patients undergoing elective non-cardiovascular surgery.

Methods: RRD was diagnosed according to the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU).

COVID-19: a risk factor for fatal outcomes in patients with comorbid cardiovascular disease.

Objectives: To evaluate the fatal impact of COVID-19 on patients with comorbid cardiovascular disease (CVD).

Results: Overall, the 28-day mortality of patients with comorbid CVD was 3.25 times of that of patients without comorbid CVD (40.

Continuous Analysis of Critical Incidents for 92,136 Postanesthesia Care Unit Patients of a Chinese University Hospital.

Purpose: To determine the spectrum of critical incidents in postanesthesia care unit (PACU) and the possible prediction and prevention of the worse scenario-associated critical incidents.

Design: A retrospective observational study.

Methods: The critical incidents in PACU comprising 92,136 patients were recorded.

Monitoring and Management of Home-Quarantined Patients With COVID-19 Using a WeChat-Based Telemedicine System: Retrospective Cohort Study.

Background: Most patients with coronavirus disease (COVID-19) who show mild symptoms are sent home by physicians to recover. However, the condition of some of these patients becomes severe or critical as the disease progresses.

Objective: The aim of this study was to evaluate a telemedicine model that was developed to address the challenges of treating patients with progressive COVID-19 who are home-quarantined and shortages in the medical workforce.

Adverse Respiratory Events Increase Post-anesthesia Care Unit Stay in China: A 2-year Retrospective Matched Cohort Study.

Despite growing attention to patients' safety worldwide, no data were available on the impact of adverse respiratory events (AREs) on post-anesthesia care and post-operation care in China. This study evaluated the occurrence of AREs, the impact of AREs on length of stay (LOS) in post-anesthesia care unit (PACU) and postoperative time in hospital, and PACU cost and inpatient healthcare costs. A retrospective, matched-cohort study was conducted by prospectively collecting the data of 159 AREs in PACU during 2016-2017 in an university hospital in China.

Arsenic trioxide and angiotensin II have inhibitory effects on HERG protein expression: Evidence for the role of PML SUMOylation.

The human ether-a-go-go-related gene (HERG) channel is a novel target for the treatment of drug-induced long QT syndrome, which causes lethal cardiotoxicity. This study is designed to explore the possible role of PML SUMOylation and its associated nuclear bodies (NBs) in the regulation of HERG protein expression. Both arsenic trioxide (ATO) and angiotensin II (Ang II) were able to significantly reduce HERG protein expression, while also increasing PML SUMOylation and accelerating the formation of PML-NBs.

Manipulating PML SUMOylation via Silencing UBC9 and RNF4 Regulates Cardiac Fibrosis.

The promyelocytic leukemia protein (PML) is essential in the assembly of dynamic subnuclear structures called PML nuclear bodies (PML-NBs), which are involved in regulating diverse cellular functions. However, the possibility of PML being involved in cardiac disease has not been examined. In mice undergoing transverse aortic constriction (TAC) and arsenic trioxide (ATO) injection, transforming growth factor β1 (TGF-β1) was upregulated along with dynamic alteration of PML SUMOylation.

Enhanced dewaterability of sewage sludge with zero-valent iron-activated persulfate oxidation system.

The potential benefits of zero-valent iron-activated persulfate (Na2S2O8) oxidation in enhanced dewaterability of sludge, along with the associated mechanisms were investigated in this study. The sludge dewaterability was evaluated in terms of specific resistance to filtration (SRF) and water content. Based on these indexes, it was observed that ZVI-S2O8(2) oxidation effectively improved sludge dewaterability.

Downregulation of miR-21 is involved in direct actions of ursolic acid on the heart: implications for cardiac fibrosis and hypertrophy.

Purpose: Myocardial fibrosis contributes to cardiac remodeling and loss of cardiac function in myocardial infarction and heart failure. This study used in vitro and in vivo models to examine the effects of ursolic acid (UA) on myocardial fibrosis and to explore its potential mechanism.

Methods: Transverse aortic constriction (TAC) surgery was performed in mice to induce cardiac hypertrophy and fibrosis.