An adaptive, real-time, traffic monitoring system

In this paper we describe a computer vision-based traffic monitoring system able to detect individual vehicles in real-time. Our fully integrated system first obtains the main traffic variables: counting, speed and category; and then computes a complete set of statistical variables. The objective is to investigate some of the difficulties impeding existing traffic systems to achieve balanced accuracy in every condition; i.e. day and night transitions, shadows, heavy vehicles, occlusions, slow traffic and congestions. The system we present is autonomous, works for long periods of time without human intervention and adapts automatically to the changing environmental conditions. Several innovations, designed to deal with the above circumstances, are proposed in the paper: an integrated calibration and image rectification step, differentiated methods for day and night, an adaptive segmentation algorithm, a multistage shadow detection method and special considerations for heavy vehicle identification and treatment of slow traffic. A specific methodology has been developed to benchmark the accuracy of the different methods proposed.     

Adapting plans in progress in distributed supervisory work: aspects of complexity, coupling, and control

Distributed supervisory control systems often rely on complex and centralized plans to cope with a variety of unanticipated situations. Replanning requires practitioners to forgo standard procedures in favor of making simple plans without simplifying, managing task coupling, and anticipating team needs to provide decentralized and elaborate plans. This article proposes a plan classification scheme to study what features of plans facilitate or hinder adaptation and a framework to examine how features of plans influence the cognitive processes of replanning. The plan features have been assigned to the categories of plan complexity, coupling, and control. Plans are task networks sharing similar features of complexity and coupling to technical systems. The proposed framework sets out to explore how plan features influence the processes of recognizing plan disruptions, reviewing challenges and different team stances, repairing plans to resolve new risks, and reacting by coordinating team efforts to execute plans. The framework draws on the Extended Control Model (ECOM) to integrate the four processes of replanning into a set of control loops. The benefits of this framework are illustrated in the context of operator training and decision support.     

Suppressing intersample behavior in iterative learning control

Iterative Learning Control (ILC) is a control strategy to improve the performance of digital batch repetitive processes. Due to its digital implementation, discrete time ILC approaches do not guarantee good intersample behavior. In fact, common discrete time ILC approaches may deteriorate the intersample behavior, thereby reducing the performance of the sampled-data system. In this paper, a generally applicable multirate ILC approach is presented that enables to balance the at-sample performance and the intersample behavior. Furthermore, key theoretical issues regarding multirate systems are addressed, including the time-varying nature of the multirate ILC setup. The proposed multirate ILC approach is shown to outperform discrete time ILC in realistic simulation examples.     

设计与制造之间的界面优化

分辨率增强技术（RET）设计流程中聚集了各式各样的点工具和方法。当前对深亚波长可制造性（DFM）设计的要求迫使设计与制造行业必须建立十分密切的合作关系。同时也促使EDA行业提供一种平台，以促进这些行业间的密切交流。合理利用这一平台将会对产能和品质产生直接的影响。     

SARS-CoV-2 Infection Dysregulates Cilia and Basal Cell Homeostasis in the Respiratory Epithelium of Hamsters

Similar to many other respiratory viruses, SARS-CoV-2 targets the ciliated cells of the respiratory epithelium and compromises mucociliary clearance, thereby facilitating spread to the lungs and paving the way for secondary infections. A detailed understanding of mechanism involved in ciliary loss and subsequent regeneration is crucial to assess the possible long-term consequences of COVID-19. The aim of this study was to characterize the sequence of histological and ultrastructural changes observed in the ciliated epithelium during and after SARS-CoV-2 infection in the golden Syrian hamster model. We show that acute infection induces a severe, transient loss of cilia, which is, at least in part, caused by cilia internalization. Internalized cilia colocalize with membrane invaginations, facilitating virus entry into the cell. Infection also results in a progressive decline in cells expressing the regulator of ciliogenesis FOXJ1, which persists beyond virus clearance and the termination of inflammatory changes. Ciliary loss triggers the mobilization of p73⁺ and CK14⁺ basal cells, which ceases after regeneration of the cilia. Although ciliation is restored after two weeks despite the lack of FOXJ1, an increased frequency of cilia with ultrastructural alterations indicative of secondary ciliary dyskinesia is observed. In summary, the work provides new insights into SARS-CoV-2 pathogenesis and expands our understanding of virally induced damage to defense mechanisms in the conducting airways.