THE CORRELATION BETWEEN PSYCHIATRIC DISORDERS AND COVID-19: A NARRATIVE REVIEW

Since December 2019, the havoc caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has increased exponentially in a short period of time. As the COVID-19 pandemic is raging around the world, scientists are trying to reveal its mysteriousness. Although COVID-19 is predominantly a respiratory disease, the most common symptoms are fever, dry cough, and fatigue, but extrapulmonary manifestations are increasingly recognized. Recent studies have shown that there is a strong genetic correlation between one or more psychiatric disorders and the occurrence of SARS-CoV-2 infection. Historical epidemiological perspectives and recent neurobiological evidence link infection and psychosis. What is the relationship between COVID-19 and psychiatric disorders? In this article, we will review the correlation between COVID-19 and psychoses, the possible reasons, and the possible pathophysiological mechanisms. The purpose of this review is to provide a reference for clinicians to make correct judgment and treatment when facing patients with COVID-19 and/or psychiatric disorders

Motion Control of Two Mobile Robots under Allowable Collisions

This letter investigates the motion control problem of two mobile robots under allowable collisions. Here, the allowable collisions mean that the collisions do not damage the mobile robots. The occurrence of the collisions is discussed and the effects of the collisions on the mobile robots are analyzed to develop a hybrid model of each mobile robot under allowable collisions. Based on the effects of the collisions, we show the necessity of redesigning the motion control strategy for mobile robots. Furthermore, impulsive control techniques are applied to redesign the motion control strategy to guarantee the task accomplishment for each mobile robot. Finally, an example is used to illustrate the redesigned motion control strategy.Comment: 8 pages, 5 figure

An invasive species erodes the performance of coastal wetland protected areas

The world has increasingly relied on protected areas (PAs) to rescue highly valued ecosystems from human activities, but whether PAs will fare well with bioinvasions remains unknown. By analyzing three decades of seven of the largest coastal PAs in China, including World Natural Heritage and/or Wetlands of International Importance sites, we show that, although PAs are achieving success in rescuing iconic wetlands and critical shorebird habitats from once widespread reclamation, this success is counteracted by escalating plant invasions. Plant invasions were not only more extensive in PAs than non-PA controls but also undermined PA performance by, without human intervention, irreversibly replacing expansive native wetlands (primarily mudflats) and precluding successional formation of new native marshes. Exotic species are invading PAs globally. This study across large spatiotemporal scales highlights that the consequences of bioinvasions for humanity’s major conservation tool may be more profound, far reaching, and critical for management than currently recognized

Predicting Microsatellite Instability Status in Colorectal Cancer Based on Triphasic Enhanced Computed Tomography Radiomics Signatures: A Multicenter Study

BackgroundThis study aimed to develop and validate a computed tomography (CT)-based radiomics model to predict microsatellite instability (MSI) status in colorectal cancer patients and to identify the radiomics signature with the most robust and high performance from one of the three phases of triphasic enhanced CT.MethodsIn total, 502 colorectal cancer patients with preoperative contrast-enhanced CT images and available MSI status (441 in the training cohort and 61 in the external validation cohort) were enrolled from two centers in our retrospective study. Radiomics features of the entire primary tumor were extracted from arterial-, delayed-, and venous-phase CT images. The least absolute shrinkage and selection operator method was used to retain the features closely associated with MSI status. Radiomics, clinical, and combined Clinical Radiomics models were built to predict MSI status. Model performance was evaluated by receiver operating characteristic curve analysis.ResultsThirty-two radiomics features showed significant correlation with MSI status. Delayed-phase models showed superior predictive performance compared to arterial- or venous-phase models. Additionally, age, location, and carcinoembryonic antigen were considered useful predictors of MSI status. The Clinical Radiomics nomogram that incorporated both clinical risk factors and radiomics parameters showed excellent performance, with an AUC, accuracy, and sensitivity of 0.898, 0.837, and 0.821 in the training cohort and 0.964, 0.918, and 1.000 in the validation cohort, respectively.ConclusionsThe proposed CT-based radiomics signature has excellent performance in predicting MSI status and could potentially guide individualized therapy

Robust Filtering for 2-D Discrete-Time Switched Systems

In this article, we study the robust filtering problem for 2-D switched systems with convex-bounded uncertainties. The studied switched system is formulated by Fornasini–Marchesini local state-space model, and system matrices depend affinely on convex-bounded uncertain parameters. We first derive synthesis results for 2-D switched systems, which extends the existing results and lays a foundation for the robust filter design. To design the robust filter, we transform the 2-D switched system into an equivalent difference-algebraic representation form. Using the equivalent representation and the parameter-dependent Lyapunov function approach, sufficient conditions are established for system stability, and 2-D stationary discrete-time linear filters are designed to ensure the prescribed H∞ or H2 performance for all admissible uncertain parameters. Finally, a numerical example is presented to illustrate the obtained results