Adaptive Optimal Surrounding Control of Multiple Unmanned Surface Vessels via Actor-Critic Reinforcement Learning.

In this article, an optimal surrounding control algorithm is proposed for multiple unmanned surface vessels (USVs), in which actor-critic reinforcement learning (RL) is utilized to optimize the merging process. Specifically, the multiple-USV optimal surrounding control problem is first transformed into the Hamilton-Jacobi-Bellman (HJB) equation, which is difficult to solve due to its nonlinearity. An adaptive actor-critic RL control paradigm is then proposed to obtain the optimal surround strategy, wherein the Bellman residual error is utilized to construct the network update laws.

Expression pattern and functional analysis of kinesin-14 KIFC1 in spermatogenesis of Macaca mulatta.

C-terminal kinesin motor KIFC1 is increasingly concerned with an essential role in germ cell development. During the spermatogenesis of mice, rats, and crustaceans, KIFC1 functions in regulating meiotic chromosome separation, acrosome vesicle transportation, and nuclear morphology maintenance. The expression pattern of KIFC1 is conservatively concentrated at the acrosome and nucleus of haploid sperm cells.

Sparse Bayesian Learning for Switching Network Identification.

Learning dynamical networks based on time series of nodal states is of significant interest in systems science, computer science, and control engineering. Despite recent progress in network identification, most research focuses on static structures rather than switching ones. Therefore, this article develops a method for identifying the structures of switching networks by exploring and leveraging both temporal and spatial structural information that characterizes the switching process.

A Small "Tent" in the Esophagus.

Cite this article as: Zong Z, Xu J, Zhang H, Xu H, Tang X, Shi L. A small "tent" in the esophagus. Turk J Gastroenterol.

Early warning of atrial fibrillation using deep learning.

Atrial fibrillation (AF), the most prevalent cardiac rhythm disorder, significantly increases hospitalization and health risks. Reverting from AF to sinus rhythm (SR) often requires intensive interventions. This study presents a deep-learning model capable of predicting the transition from SR to AF on average 30.

Identifying Community-Bridge Network Structures via Bayesian Learning With Mixed Sparsity Mode.

Identifying structures of complex networks based on time series of nodal data is of considerable interest and significance in many fields of science and engineering. This article presents a sparse Bayesian learning (SBL) method for identifying structures of community-bridge networks, where nodes are grouped to form communities connected via bridges. Using the structural information of such networks with unknown nodal dynamics and community formations, network structure identification is tackled similar to sparse signal reconstruction with mixed sparsity mode.

A nomogram predicting pneumonia after cardiac surgery: a retrospective modeling study.

Background: Postoperative pneumonia (POP) is the most prevalent of all nosocomial infections in patients who underwent cardiac surgery. The aim of this study was to identify independent risk factors for pneumonia after cardiac surgery, from which we constructed a nomogram for prediction.

Methods: The clinical data of patients admitted to the Department of Cardiothoracic Surgery of Nanjing Drum Tower Hospital from October 2020 to September 2021 who underwent cardiac surgery were retrospectively analyzed, and the patients were divided into two groups according to whether they had POP: POP group (n=105) and non-POP group (n=1083).

Postoperative hyper-inflammation as a predictor of poor outcomes in patients with acute type A aortic dissection (ATAAD) undergoing surgical repair.

Background: Postoperative hyper-inflammation is a frequent event in patients with acute Stanford type A aortic dissection (ATAAD) after surgical repair. This study's objective was to determine which inflammatory biomarkers could be used to make a better formula for identifying postoperative hyper-inflammation, and which risk factors were associated with hyper-inflammation.

Methods: A total of 405 patients were enrolled in this study from October 1, 2020 to April 1, 2023.

Multi-modal molecular determinants of clinically relevant osteoporosis subtypes.

Due to a rapidly aging global population, osteoporosis and the associated risk of bone fractures have become a wide-spread public health problem. However, osteoporosis is very heterogeneous, and the existing standard diagnostic measure is not sufficient to accurately identify all patients at risk of osteoporotic fractures and to guide therapy. Here, we constructed the first prospective multi-omics atlas of the largest osteoporosis cohort to date (longitudinal data from 366 participants at three time points), and also implemented an explainable data-intensive analysis framework (DLSF: Deep Latent Space Fusion) for an omnigenic model based on a multi-modal approach that can capture the multi-modal molecular signatures (M3S) as explicit functional representations of hidden genotypes.

Sivelestat in Patients at a High Risk of Postoperative Acute Lung Injury After Scheduled Cardiac Surgery: A Prospective Cohort Study.

Background: Sivelestat, a neutrophil elastase inhibitor, is specifically developed to mitigate the occurrence of acute lung injury (ALI) in individuals who are undergoing cardiovascular surgery. However, its impact on patients who are at a heightened risk of developing ALI after scheduled cardiac surgery has yet to be determined. In order to address this knowledge gap, we undertook a study to assess the efficacy of sivelestat in protecting the lungs of these patients.

Effects of water fluoridation on early embryonic development of zebrafish.

Fluoride has strong electronegativity and exposes diversely in nature. Water fluoridation is the most pervasive form of occurrence, representing a significant threat to human health. In this study, we investigate the morphometric and physiological alterations triggered by fluoride stimulation during the embryogenesis of zebrafish and reveal its putative effects of stage- and/or dose-dependent.

Sperm retrieval outcomes of contralateral testis in men with nonobstructive azoospermia and unsuccessful unilateral microdissection testicular sperm extraction.

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Resilience of hybrid herbivore-plant-pollinator networks.

The concept of network resilience has gained increasing attention in the last few decades owing to its great potential in strengthening and maintaining complex systems. From network-based approaches, researchers have explored resilience of real ecological systems comprising diverse types of interactions, such as mutualism, antagonist, and predation, or mixtures of them. In this paper, we propose a dimension-reduction method for analyzing the resilience of hybrid herbivore-plant-pollinator networks.

Diagnosis of Early Bacterial Pneumonia and Sepsis After Cardiovascular Surgery: A Diagnostic Prediction Model Based on LASSO Logistic Regression.

Background: Early postoperative bacterial pneumonia and sepsis (ePOPS), which occurs within the first 48 hours after cardiovascular surgery, is a serious life-threatening complication. Diagnosis of ePOPS is extremely challenging, and the existing diagnostic tools are insufficient. The purpose of this study was to construct a novel diagnostic prediction model for ePOPS.

Dexmedetomidine as an anesthetic adjunct is associated with reduced complications and cardiac intensive care unit length of stay after heart valve surgery.

Background: We sought to explore the relationship between dexmedetomidine as an anesthetic adjuvant in cardiac surgery and postoperative complications and length of stay (LOS) in the cardiac intensive care unit (CICU).

Methods: We conducted a retrospective study of patients aged 18 years and older who underwent heart valve surgery between October 2020 and June 2022. The primary endpoint of the study was major postoperative complications (cardiac arrest, atrial fibrillation, myocardial injury/infarction, heart failure) and the secondary endpoint was prolonged CICU LOS (defined as LOS > 90th percentile).

Dual-radical-based molecular anisotropy and synergy effect of semi-conductivity and valence tautomerization in a photoswitchable coordination polymer.

Organic radicals are widely used as linkers or ligands to synthesize molecular magnetic materials. However, studies regarding the molecular anisotropies of radical-based magnetic materials and their multifunctionalities are rare. Herein, a photoisomerizable diarylethene ligand was used to form {[Co(3,5-DTSQ)(3,5-DTCat)](6F-DAE-py)}·3CHCN·HO (·3CHCN·HO, 6F-DAE-py = 1,2-bis(2-methyl-5-(4-pyridyl)-3-thienyl)perfluorocyclopentene), a valence-tautomeric (VT) coordination polymer.

Risk factors for postoperative myocardial injury-related cardiogenic shock in patients undergoing cardiac surgery.

Background: Myocardial injury-related cardiogenic shock (MICS) is significantly associated with poor outcomes in patients after cardiac surgery. Herein, we aimed to investigate the risk factor for postoperative MICS.

Methods: We performed a case-control study on 792 patients undergoing cardiac surgery from 2016 to 2019, including 172 patients with postoperative MICS and 620 age- and sex-matched controls.

A Data-Driven Bayesian Koopman Learning Method for Modeling Hysteresis Dynamics.

Exploring the mechanism of hysteresis dynamics may facilitate the analysis and controller design to alleviate detrimental effects. Conventional models, such as the Bouc-Wen and Preisach models consist of complicated nonlinear structures, limiting the applications of hysteresis systems for high-speed and high-precision positioning, detection, execution, and other operations. In this article, a Bayesian Koopman (B-Koopman) learning algorithm is therefore developed to characterize hysteresis dynamics.