以用户为中心的可见光通信协作传输中训练资源分配算法

以用户为中心的可见光通信协作传输是近年来出现的新架构,这导致虚拟小区之间出现重叠。为避免导频污染问题,每个虚拟小区中的光接入点(AP)或者虚拟小区中选择相同AP的用户发送的训练序列应该是正交的。针对可见光通信中以用户为中心的协作网络,研究训练资源的正交分配问题,提出了一种新的导频分配算法,联合导频分配和用户选择问题,以期最大限度地增加虚拟小区内可被接入的用户数。分析和仿真结果表明,该导频分配方案可以有效改善导频污染问题,提高训练资源利用率,并且相比已有的导频分配方案,性能有所改进。     

Identification of Host Cellular Protein Substrates of SARS-COV-2 Main Protease

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease-19 (COVID-19) being associated with severe pneumonia. Like with other viruses, the interaction of SARS-CoV-2 with host cell proteins is necessary for successful replication, and cleavage of cellular targets by the viral protease also may contribute to the pathogenesis, but knowledge about the human proteins that are processed by the main protease (3CLpro) of SARS-CoV-2 is still limited. We tested the prediction potentials of two different in silico methods for the identification of SARS-CoV-2 3CLpro cleavage sites in human proteins. Short stretches of homologous host-pathogen protein sequences (SSHHPS) that are present in SARS-CoV-2 polyprotein and human proteins were identified using BLAST analysis, and the NetCorona 1.0 webserver was used to successfully predict cleavage sites, although this method was primarily developed for SARS-CoV. Human C-terminal-binding protein 1 (CTBP1) was found to be cleaved in vitro by SARS-CoV-2 3CLpro, the existence of the cleavage site was proved experimentally by using a His₆-MBP-mEYFP recombinant substrate containing the predicted target sequence. Our results highlight both potentials and limitations of the tested algorithms. The identification of candidate host substrates of 3CLpro may help better develop an understanding of the molecular mechanisms behind the replication and pathogenesis of SARS-CoV-2.     

External validity and factor structure of individual and group workload ratings

Work teams experience workload from the group dynamics in addition to the usual sources of individual workload. This study had three objectives: to assess the responsiveness of new rating scales for group workload (GWL), investigate their component structure, and determine if changes in workload occur as the team matures. Participants (360 individuals, 44 groups) engaged in an emergency response (ER) simulation in the form of a board game; team size, game difficulty (one versus two opponents), and time constraints were varied. ER teams rated workload after each of two sessions using the NASA Task Load Index (TLX) and GWL. GWL was most responsive to larger task demands and reflected changes in coordination demand over time. Components reflected mixtures of TLX and GWL scales and suggested that self-organising processes were operating.     

汽车涂装废水处理技术的研究进展

汽车涂装中产生大量的工业废水，主要包括脱脂废水、磷化废水、电泳废水和喷漆废水等,其典型污染物为重金属离子、表面活性剂、油漆颗粒、磷酸盐等，是一类复杂及难处理的高浓度工业废水。依据废水中所含污染物的不同，对涂装各工序废水进行分质预处理可有效地去除磷酸盐、重金属离子、悬浮固体、油类物质等污染物，有利于减轻后续生物或高级处理单元的负荷，提高整个处理系统的效率。本文综述近年来汽车涂装废水处理方面的研究成果或实践，旨在总结预处理工艺及主体处理工艺的优点及存在的不足，希望为汽车涂装废水处理达标排放及循环回用提供一些借鉴。     

重庆主城区城市空间结构演变与优化——基于公共服务功能组织视角

城市空间结构与城市公共服务功能组织密切相关。重庆主城区作为典型的"多中心、组团式"城市,在城市公共服务功能的就近组织、公共服务需求的均衡化方面具有先天的优势。本文梳理重庆主城区空间结构的演进历程以及与公共服务需求变化的互动关系,辨识随着城市功能由生产向消费转型,空间面临的结构问题及其内在动因,借鉴马斯洛理论,提出顺应当前及未来公共服务需求层次的分异,城市空间结构应从"多中心、组团式"进一步向"分层多中心、组团式"优化,引导形成相对集中、功能综合的基层"小、微中心"体系,以有序组织公共服务功能,最大限度地减少非必要交通出行,降低居民出行的时耗,提升城市效率,并借鉴恩格尔系数构建衡量城市效率的评价框架,为破解山地城市空间结构问题,推动城市空间转型提供新的思考视角。     

人工监督神经网络在煤层裂缝发育区识别中的应用

针对在地震属性应用中难以精细识别煤层裂缝发育区边界的难题,开展了基于人工监督神经网络技术的煤层裂缝发育区应用研究。从地震资料中获取倾角导向体以提取高质量的地震属性,以多属性为指导进行人工拾取样点,并基于多层感知器进行神经网络机器训练学习,建立裂缝的最优属性集,拓展整体数据后获得裂缝概率体,从而识别划分出煤层裂缝发育区。该技术在山西阳泉新元矿区进行了应用,煤层裂缝发育区的识别结果明显优于属性直接识别,但勘探区内暂无钻井资料,预测效果还有待进一步验证。     

正压给水的主排水泵启动特性仿真分析研究

峰峰集团某矿排水系统在采用正压给水方式后主排水泵泵效明显提高,为了研究排水系统的启动特性,利用Flowmaster软件建立了离心泵串联系统模型。根据水力机械试验室的设备参数进行了仿真,分析了正压给水条件下主泵定量启动前由单泵和双泵组成的排水系统特性。在此基础上,得到了离心泵瞬时启动转速和功率的特性曲线。结果表明,在正压给水条件下,主泵启动功率的影响基本消除,主泵功率达到稳定值的时间缩短。提高了主排水泵的效率,提高了排水系统的综合效率。     

An immersive virtual reality serious game to enhance earthquake behavioral responses and post-earthquake evacuation preparedness in buildings

Enhancing the earthquake behavioral responses and post-earthquake evacuation preparedness of building occupants is beneficial to increasing their chances of survival and reducing casualties after the mainshock of an earthquake. Traditionally, training approaches such as seminars, posters, videos or drills are applied to enhance preparedness. However, they are not highly engaging and have limited sensory capabilities to mimic life-threatening scenarios for the purpose of training potential participants. Immersive Virtual Reality (IVR) and Serious Games (SG) as innovative digital technologies can be used to create training tools to overcome these limitations. In this study, we propose an IVR SG-based training system to improve earthquake behavioral responses and post-earthquake evacuation preparedness. Auckland City Hospital was chosen as a case study to test our IVR SG training system. A set of training objectives based on best evacuation practice has been identified and embedded into several training scenarios of the IVR SG. Hospital staff (healthcare and administrative professionals) and visitors were recruited as participants to be exposed to these training scenarios. Participants’ preparedness has been measured along two dimensions: 1) Knowledge about best evacuation practice; 2) Self-efficacy in dealing with earthquake emergencies. Assessment results showed that there was a significant knowledge and self-efficacy increase after the training. In addition, participants acknowledged that it was easy, helpful, and engaging to learn best evacuation practice knowledge through the IVR SG training system.     

浅谈船用主机使用低硫燃油面临的挑战与应对措施

介绍了低硫燃油和传统的船用高硫燃油在化学成分和物理特性方面存在的诸多不同;指出:IMO2020限硫令对船舶运营带来了很大的挑战。基于两大主机制造商的相关文件和实际服务经验，归纳总结了船用主机使用低硫燃油运营时应注意的事项及应对措施，为船舶安全稳定运营提供参考。