Clinical Characteristics and Outcomes of Type 2 Diabetes Patients Infected with COVID-19: A Retrospective Study

Diabetes and its related metabolic disorders have been reported as the leading comorbidities in patients with coronavirus disease 2019 (COVID-19). This clinical study aims to investigate the clinical features, radiographic and laboratory tests, complications, treatments, and clinical outcomes in COVID-19 patients with or without diabetes. This retrospective study included 208 hospitalized patients (≥ 45 years old) with laboratory-confirmed COVID-19 during the period between 12 January and 25 March 2020. Information from the medical record, including clinical features, radiographic and laboratory tests, complications, treatments, and clinical outcomes, were extracted for the analysis. 96 (46.2%) patients had comorbidity with type 2 diabetes. In COVID-19 patients with type 2 diabetes, the coexistence of hypertension (58.3% vs 31.2%), coronary heart disease (17.1% vs 8.0%), and chronic kidney diseases (6.2% vs 0%) was significantly higher than in COVID-19 patients without type 2 diabetes. The frequency and degree of abnormalities in computed tomography (CT) chest scans in COVID-19 patients with type 2 diabetes were markedly increased, including ground-glass opacity (85.6% vs 64.9%, P < 0.001) and bilateral patchy shadowing (76.7% vs 37.8%, P < 0.001). In addition, the levels of blood glucose (7.23 mmol·L⁻¹ (interquartile range (IQR): 5.80–9.29) vs 5.46 mmol·L⁻¹ (IQR: 5.00–6.46)), blood low-density lipoprotein cholesterol (LDL-C) (2.21 mmol·L⁻¹ (IQR: 1.67–2.76) vs 1.75 mmol·L⁻¹ (IQR: 1.27–2.01)), and systolic pressure (130 mmHg (IQR: 120–142) vs 122 mmHg (IQR: 110–137)) (1 mmHg = 133.3 Pa) in COVID-19 patients with diabetes were significantly higher than in patients without diabetes (P < 0.001). The coexistence of type 2 diabetes and other metabolic disorders is common in patients with COVID-19, which may potentiate the morbidity and aggravate COVID-19 progression. Optimal management of the metabolic hemostasis of glucose and lipids is the key to ensuring better clinical outcomes. Increased clinical vigilance is warranted for COVID-19 patients with diabetes and other metabolic diseases that are fundamental and chronic conditions.     

Ergonomics interventions to reduce musculoskeletal risk factors in a truck manufacturing plant

Ergonomic interventions may potentially reduce MSDs, but the context of industries (barriers, ever-changing situations, dialogue processes) might play a significant role in the success of interventions. This study evaluates the effectiveness of ergonomic interventions including engineering/technical and organizational interventions, and the involvement of the stakeholders in reducing musculoskeletal risk factors/symptoms. A pre-post-test experimental study in non-randomized groups was performed over three years in a sector of a truck assembly plant. The mean age of the operators in the sector for the initial and second assessment time was 42.0 (±7.6) years and 39.0 (±8.7), respectively. The mean length of work experience in the current job was 15.2 (±7.2) years and 13.9 (±7.3) for the initial and second assessment times, respectively. Five engineering ergonomic solutions and organizational interventions were implemented after a comprehensive ergonomic analysis. The organizational interventions consisted mostly of transferring and redistributing the tasks, i.e., ergonomically balancing and redesigning of the workstations. Before performing the interventions, the findings of the ergonomic study were presented at several meetings to encourage the involvement of the stakeholders (including managers, engineers, and operators) in the interventions. This study showed that a combination of ergonomic measures—engineering and organizational interventions—could reduce physical workloads. Musculoskeletal symptoms decreased after interventions although the difference was not significant.     

Exploring design trade-offs for achieving social inclusion in multi-tiered design problems

ABSTRACT

The digital age of the future is ‘not out there to be discovered’, but it needs to be ‘designed’. The design challenge has to address questions about how we want to live, work, and learn (as individuals and as communities) and what we value and appreciate, e.g.: reflecting on quality of life and creating inclusive societies. An overriding design trade-off for the digital age is whether new developments will increase the digital divide or will create more inclusive societies. Sustaining inclusive societies means allowing people of all ages and all abilities to exploit information technologies for personally meaningful activities. Meta-design fosters the design of socio-technical environments that end-user developers can modify and evolve at use time to improve their quality of life and favour their inclusion in the society. This paper describes three case studies in the domain of assistive technologies in which end users themselves cannot act as end-user developers, but someone else (e.g.: a caregiver or a clinician) must accept this role requiring multi-tiered architectures. The design trade-offs and requirements for meta-design identified in the context of the case studies and other researchers’ projects are described to inform the development of future socio-technical environments focused on social inclusion.     

Etching characteristics of thin SiON films using a liquefied perfluorocarbon precursor of C6F12O with a low global warming potential

Perfluorocarbon gas is widely used in the semiconductor industry. However, perfluorocarbon has a negative effect on the global environment owing to its high global warming potential (GWP) value. An alternative solution is essential. Therefore, we evaluated the possibility of replacing conventional perfluorocarbon etching gases such as CHF₃ with C₆F₁₂O, which has a low GWP and is in a liquid state at room temperature. In this study, silicon oxynitride (SiON) films were plasma-etched using inductively coupled CF₄ +C₆F₁₂O+O₂ mixed plasmas. Subsequently, the etching characteristics of the film, such as etching rate, etching profile, selectivity over Si, and photoresist, were investigated. A double Langmuir probe was used and optical emission spectroscopy was performed for plasma diagnostics. In addition, a contact angle goniometer and x-ray photoelectron spectroscope were used to confirm the change in the surface properties of the etched SiON film surface. Consequently, the etching characteristics of the C₆F₁₂O mixed plasma exhibited a lower etching rate, higher SiON/Si selectivity, lower plasma damage, and more vertical etched profiles than the conventional CHF₃ mixed plasma. In addition, the C₆F₁₂O gas can be recovered in the liquid state, thereby decreasing global warming. These results confirmed that the C₆F₁₂O precursor can sufficiently replace the conventional etching gas.     

Off‐grid DoA estimation method of wideband signals

In this paper, an off‐grid direction of arrival (DoA) estimation method is proposed for wideband signals. This method is based on the sparse representation (SR) of the array covariance matrix. Similar to the time domain DoA estimation methods, the correlation function of the sources was assumed to be the same and known. A new measurement vector is obtained using the lower‐left triangular elements of the covariance matrix. The DoAs are estimated by quantizing the entire range of continuous angle space into discrete grid points. However, the exact DoAs may be located between two grid points; therefore, this estimation has errors. The accuracy of DoA estimation is improved by the minimization of the difference between the new measurement vector and its estimated values. Simulation results revealed that the proposed method can enhance the DoA estimation accuracy of wideband signals.     

基于物联网的智慧林业可持续发展策略研究

随着我国科技的不断进步,在“互联网+”大数据的背景下,林业的智慧化发展是必经之路。虽然我国智慧林业的发展已经取得了一定的突破,但是仍然存在着许多问题。基于此,文章在物联网技术的基础上,对智慧林业的可持续发展策略进行探讨。     

基于学科竞赛的中医药类院校程序设计课程教学模式的探索

高素质人才培养是我国可持续发展战略、科教兴国战略以及人才强国战略等多项发展战略的一项基础性工程。本文针对中医药类院校程序设计类课程实践教学模式单一等教学实际，以“学科竞赛”为平台，“赛教结合”为理念，以《C语言程序设计》为例，从现存问题、赛教结合模式的引入、建立实施及其评价机制4个方面展开阐述，旨在提高学生学习积极性和能力。     

一种新的多渐消因子容积卡尔曼滤波

将强跟踪思想引入容积卡尔曼滤波（cubature Kalman filter，CKF），建立强跟踪CKF能有效克服CKF在模型不确定、状态突变等情况下，滤波性能下降的问题。通过分析现有多渐消因子计算方法，发现它们均只利用了协方差矩阵的对角线元素，并没有考虑各个状态之间的相关性，不能充分发挥多渐消因子的优势。为此，本文提出渐消因子矩阵，基于正交原理推导渐消因子矩阵的求解方法，提出多渐消因子强跟踪CKF算法。多渐消因子强跟踪CKF算法突破了传统多渐消因子为向量的限制，也不再要求渐消因子取值要大于1。仿真验证了算法具有更好的滤波精度何鲁棒性，能更好的满足工程应用的要求。     

Output feedback controller for polytopic systems exploiting the direct searching of the design space

This paper deals with the problem of designing a robust static output feedback controller for polytopic systems. The current research that tackled this problem is mainly based on LMI method, which is conservative by nature. In this paper, a novel approach is proposed, which considers the design space of the controller parameters and iteratively partitions the space to small simplexes. Then, by assessing the stability in each simplex, the solution space for design parameters is directly determined. It has been theoretically proved that, if there exists a feasible solution in the design space, the algorithm can find it. To validate the result of the proposed approach, comparative simulation examples are given to illustrate the performance of the design methodology as compared to those of previous approaches.     

Deep reinforcement learning-based cooperative interactions among heterogeneous vehicular networks

Most real-world vehicle nodes can be structured into an interconnected network of vehicles. Through structuring these services and vehicle device interactions into multiple types, such internet of vehicles becomes multidimensional heterogeneous overlay networks. The heterogeneousness of the overlays makes it difficult for the overlay networks to coordinate with each other to improve their performance. Therefore, it poses an interesting but critical challenge to the effective analysis of heterogeneous virtual vehicular networks. A variety of virtual vehicular networks can be easily deployed onto the native network by applying the concept of SDN (Software Defined Networking). These virtual networks reflect their heterogeneousness due to their different performance goals, and they compete for the same physical resources of the underlying network, so that a sub-optimal performance of the virtual networks may be achieved. Therefore, we propose a Deep Reinforcement Learning (DRL) approach to make the virtual networks cooperate with each other through the SDN controller. A cooperative solution based on the asymmetric Nash bargaining is proposed for co-existing virtual networks to improve their performance. Moreover, the Markov Chain model and DRL resolution are introduced to leverage the heterogeneous performance goals of virtual networks. The implementation of the approach is introduced, and simulation results confirm the performance improvement of the latency sensitive, loss-rate sensitive and throughput sensitive heterogeneous vehicular networks using our cooperative solution.