A rapid detection method for the surface defects of mosaic ceramic tiles

Due to its unique artistic value, mosaic ceramics are widely used in construction-related fields. To meet the artist's demand for high-quality mosaic ceramic to create artistic works, it is necessary to meet the needs for efficient screening of mosaic ceramic tiles. Different from the ordinary large-target ceramics, mosaic ceramics exhibit characteristics of small tile sizes, a variety of colors, large demand for quantities, and easy reflection on the surface. Common manual detection methods show problems of low efficiency or accuracy, easy to fatigue, and many others. To solve these problems, this paper proposes a new detection method to identify surface defects of mosaic ceramic tiles and designs a detection system platform to achieve rapid detection. The experiment proves that the detection system has a detection rate of 93.99% for small defects on the surface of mosaic ceramic tiles, and the detection time of a single mosaic ceramic tile is less than 0.06 s. The detection method can quickly and accurately screen out high-quality, defect-free mosaic ceramic tiles, which can effectively improve the quality and artistic value of mosaic ceramic art creation.     

Aligned Co3O4–CoOOH heterostructure nanosheet arrays grown on carbon paper with oxygen vacancies for enhanced and robust oxygen evolution

Developing efficient and stable non-noble metal oxygen evolution reaction (OER) electrocatalysts for sustainable overall water-splitting is extremely desirable but still a great challenge. Herein, we developed a facile strategy to fabricate Co₃O₄–CoOOH heterostructure nanosheet arrays with oxygen vacancies grown on carbon paper (Co₃O₄–CoOOH/CP). Benefiting from the unique 3D architecture, large surface area, synergistic effects between Co₃O₄, CoOOH and oxygen vacancies, the obtained self-supporting Co₃O₄–CoOOH/CP presents excellent electrocatalytic OER activity (low overpotentials of 245 and 390 mV at 10 and 100 mA cm⁻²) and robust long-term stability in alkaline condition. The present strategy provides the opportunities for the future rational design and discovery of high-performance non-noble metal based electrocatalysts for advanced water oxidation and beyond.     

高稳高效海上风电安装平台关键制造技术研究

海上风电作为可再生清洁能源之一,受到世界各国的高度重视与大力发展。我国将海上风电提升至解决能源危机、减缓气候变化、调整能源结构的国家战略高度,到2030年我国单位国内生产总值二氧化碳排放将比2005年下降65%以上,非化石能源占一次能源消费比重将达到25%左右。安装平台不足将是我国海上风电场无法如期建成投产的主要障碍。对自升自航式海上风电安装平台系列高端装备及其设计制造的三大技术难题——腿站立作业易“失稳”、大平台大跨距大倾覆力矩自升易“失控”、高空吊装巨型叶片逾百螺栓精准定位易“失准”,以及焊缝缺陷修复和局部裂纹损伤的激光锻造修复再制造进行了介绍,研制的具有不同规格的系列装备在中国、英国、丹麦、德国等国家的著名海上风电场建设应用情况良好。     

高性能硅和铌酸锂异质集成薄膜电光调制器 （特邀）

硅基光子集成平台因其高集成度、CMOS工艺兼容性等特点在光通信领域受到了广泛的关注，而电光调制器作为光通信系统中最为重要的器件之一，承担着将电信号加载至光信号上的关键作用，为打破硅基调制器的性能限制，可利用硅和铌酸锂的大面积键合技术以及铌酸锂低损耗波导刻蚀技术实现高性能硅和铌酸锂异质集成薄膜电光调制器，目前该类调制器的性能可达半波电压3 V，3 dB电光带宽超过70 GHz，插入损耗小于1.8 dB, 消光比大于40 dB。文中对比了硅和铌酸锂异质集成调制器的研究现状并介绍了该异质集成薄膜调制器的结构设计与工艺实现方法。     

智能建造技术协同创新主体互动关系研究

文章分析智能建造技术创新主体的特点，界定并划分智能建造技术协同创新主体互动关系的范畴和类别，建立智能建造协同创新的多方演化博弈模型，揭示智能建造技术协同创新主体互动关系。主要结论为：①智能建造技术协同创新呈现级联性、函数性、动态平衡性、不确定性和指数性特征；②智能建造技术协同创新主体互动关系分为同质性的内部主体互动和异质性的内部主体与外部主体互动，表现出利益共生、成长进化和共享协同的特征；③创新主体之间的互动行为有利于对创新资源进行有效配置，推动智能建造技术的应用。     

Enhancement in the osteogenesis and angiogenesis of calcium phosphate cement by incorporating magnesium-containing silicates

Based on the good osteogenic and angiogenic effects of silicon and magnesium elements, three types of micro-nano magnesium-containing silicates (MS), including akermanite (Ake, Ca₂MgSi₂O₇), diopside (Dio, CaMgSi₂O₆) and forsterite (For, Mg₂SiO₄), were incorporated into calcium phosphate cement (CPC) to improve its osteogenic and angiogenic performances for clinical application. In this present work, the physicochemical properties, osteogenesis and angiogenesis of MS/CPCs (Ake/CPCs, Dio/CPCs and For/CPCs) were investigated systematically and comparatively. The results showed that all MS/CPCs had good biomineralization and significantly stimulated the osteogenic differentiation of mBMSCs and angiogenic differentiation of HUVECs, respectively. Besides, the stimulating effects were related to not only the category of MS, but also the content of MS. The For/CPCs had a good angiogenic property but their initial setting times were beyond 60 min. The Dio/CPCs showed the lowest biological performance among the three groups of MS/CPCs due to the lower ion release (Si and Mg). The Ake was the ideal modifier that could provide CPC with appropriate physicochemical properties, better osteogenesis and angiogenesis. Simultaneously, a higher addition (10 wt%) of akermanite resulted in the best potential to bone regeneration. Taken together, this research provides an effective approach to improve the overall performance of CPC, and 10Ake/CPC is of great promising prospect in bone repair.     

Looking ahead: Joint small group detection and tracking in crowd scenes

Small group detection and tracking in crowd scenes are basis for high level crowd analysis tasks. However, it suffers from the ambiguities in generating proper groups and in handling dynamic changes of group configurations. In this paper, we propose a novel delay decision-making based method for addressing the above problems, motivated by the idea that these ambiguities can be solved using rich temporal context. Specifically, given individual detections, small group hypotheses are generated. Then candidate group hypotheses across consecutive frames and their potential associations are built in a tree. By seeking for the best non-conflicting subset from the hypothesis tree, small groups are determined and simultaneously their trajectories are got. So this framework is called joint detection and tracking. This joint framework reduces the ambiguities in small group decision and tracking by looking ahead for several frames. However, it results in the unmanageable solution space because the number of track hypotheses grows exponentially over time. To solve this problem, effective pruning strategies are developed, which can keep the solution space manageable and also improve the credibility of small groups. Experiments on public datasets demonstrate the effectiveness of our method. The method achieves the state-of-the-art performance even in noisy crowd scenes.     

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.     

Soft sensor for real-time cement fineness estimation

This paper describes the design and implementation of soft sensors to estimate cement fineness. Soft sensors are mathematical models that use available data to provide real-time information on process variables when the information, for whatever reason, is not available by direct measurement. In this application, soft sensors are used to provide information on process variable normally provided by off-line laboratory tests performed at large time intervals. Cement fineness is one of the crucial parameters that define the quality of produced cement. Providing real-time information on cement fineness using soft sensors can overcome limitations and problems that originate from a lack of information between two laboratory tests. The model inputs were selected from candidate process variables using an information theoretic approach. Models based on multi-layer perceptrons were developed, and their ability to estimate cement fineness of laboratory samples was analyzed. Models that had the best performance, and capacity to adopt changes in the cement grinding circuit were selected to implement soft sensors. Soft sensors were tested using data from a continuous cement production to demonstrate their use in real-time fineness estimation. Their performance was highly satisfactory, and the sensors proved to be capable of providing valuable information on cement grinding circuit performance. After successful off-line tests, soft sensors were implemented and installed in the control room of a cement factory. Results on the site confirm results obtained by tests conducted during soft sensor development.