In addition, we introduce a receptive field adaption model to enhance the adaptive perception ability at the neuron-level, which adjusts the RF by adaptively integrating the features with different RFs. Extensive experimental results on the VOT2018, VOT2016, UAV123, LaSOT, and TC128 datasets demonstrate that the proposed algorithm performs favorably against the state-of-the-art methods in terms of accuracy and speed.The cascade approach to Speech Translation (ST) is based on a pipeline that concatenates an Automatic Speech Recognition (ASR) system followed by a Machine Translation (MT) system. Nowadays, state-of-the-art ST systems are populated with deep neural networks that are conceived to work in an offline setup in which the audio input to be translated is fully available in advance. However, a streaming setup defines a completely different picture, in which an unbounded audio input gradually becomes available and at the same time the translation needs to be generated under real-time constraints. In this work, we present a state-of-the-art streaming ST system in which neural-based models integrated in the ASR and MT components are carefully adapted in terms of their training and decoding procedures in order to run under a streaming setup. In addition, a direct segmentation model that adapts the continuous ASR output to the capacity of simultaneous MT systems trained at the sentence level is introduced to guarantee low latency while preserving the translation quality of the complete ST system. The resulting ST system is thoroughly evaluated on the real-life streaming Europarl-ST benchmark to gauge the trade-off between quality and latency for each component individually as well as for the complete ST system.The event-triggered adaptive neural networks control is investigated in this paper for a class of fractional-order systems (FOSs) with unmodeled dynamics and input saturation. Firstly, in order to obtain an auxiliary signal and then avoid the state variables of unmodeled dynamics directly appearing in the designed controller, the notion of exponential input-to-state practical stability (ISpS) and some related lemmas for integer-order systems are extended to the ones for FOSs. Then, based on the traditional event-triggered mechanism, we propose a novel adaptive event-triggered mechanism (AETM) in this paper, in which the threshold parameters can be adjusted dynamically according to the tracking performance. Besides, different from the previous works where the derivative of hyperbolic tangent function tanh(⋅) needs to have positive lower bound, a new type of auxiliary signal is introduced in this paper to handle the effect of input saturation and thus this limitation is released. Finally, two numerical examples and some comparisons are provided to illustrate our proposed controllers.
  Depression and anxiety are the most prevalent mental health difficulties in the workplace, costing the global economy $1 trillion each year.  https://www.selleckchem.com/products/MG132.html  Evidence indicates that symptoms may be reduced by interventions in the workplace. This paper is the first to systematically review psychosocial interventions for depression, anxiety, and suicidal ideation and behaviours in small-to medium-size enterprises (SMEs).
 
  A systematic search following PRISMA guidelines, registered in PROSPERO (CRD42020156275), was conducted for psychosocial interventions targeting depression, anxiety, and suicidal ideation/behaviour in SMEs. The PubMed, PsycINFO, Scopus, and two specific occupational health databases were searched, as well as four databases for grey literature, without time limit until 2nd December 2019.
 
  In total, 1283 records were identified, 70 were retained for full-text screening, and seven met the inclusion criteria three randomised controlled trials (RCTs), three before and after designs and one non-randomised trial, comprising 5111 participants. Study quality was low to moderate according to the Quality Assessment Tool for Quantitative Studies. Five studies showed a reduction in depression and anxiety symptoms using techniques based on cognitive behavioural therapy (CBT), two reported no significant change.
 
  Low number and high heterogeneity of interventions and outcomes, high attrition and lack of rigorous RCTs.
 
  Preliminary evidence indicates CBT-based interventions can be effective in targeting symptoms of depression and anxiety in SME employees. There may be unique challenges to implementing programmes in SMEs. Further research is needed in this important area.
 Preliminary evidence indicates CBT-based interventions can be effective in targeting symptoms of depression and anxiety in SME employees. There may be unique challenges to implementing programmes in SMEs. Further research is needed in this important area.Recent studies have revealed that fatty tissue, so far considered an energy storage organ, is also the source of many substances called adipokines, including chemerin which plays many important functions in the body. Chemerin stimulates adipocytes maturation and differentiation, as well as acts as a chemoattractant, which stimulates innate and acquired immunity. This adipokine participates in the early stages of acute inflammation as well as its suppression by reacting with the CMKLR1 receptor. In various diseases associated with inflammatory processes, the level of chemerin in the serum increases. It is also considered a marker for benign and malignant tumors. Explanation of the pathomechanisms involving this adipokine is of a high importance and may contribute to the development of new possibilities in the treatment of many diseases. The article presents the latest information on the role of chemerin in various pathological states, particularly in psoriasis.The advancement of technology remained an immersive interest for humankind throughout the past decades. Tech enterprises offered a stream of innovation to address the universal healthcare concerns. The novel coronavirus holds a substantial foothold of planet earth which is combatted by digital interventions across afflicted geographical boundaries and territories. This study aims to explore the trends of modern healthcare technologies and Artificial Intelligence (AI) during COVID-19 crisis, define the concepts and clinical role of AI in the mitigation of COVID-19, investigate and correlate the efficacy of AI-enabled technology in medical imaging during COVID-19 and determine advantages, drawbacks, and challenges of artificial intelligence during COVID-19 pandemic. The paper applied systematic review approach using a deliberated research protocol and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow chart. Digital technologies can coordinate COVID-19 responses in a cascade fashion that extends from the clinical care facility to the exterior of the pending viral epicenter.