减水剂类型对赤泥—矿渣基地聚物注浆材料性能的影响及机理研究

针对赤泥等固体废弃物对环境危害性大且利用率低等问题,以碱激发赤泥-矿渣基地聚物注浆材料为 研究对象,研究了不同掺量的聚羧酸(PA)减水剂、醛酮缩合物(AKC)减水剂和萘系(N)减水剂对材料凝结时间、流动 性及强度等的影响,并通过 XRD、傅里叶红外光谱及 SEM 等设备对减水剂的作用机理进行研究。 结果表明:减水剂增 强了材料的流动性但降低了材料的剪切应力;N 和 PA 减水剂能缩短材料的凝结时间,但 AKC 减水剂会延长材料的凝 结时间;N 和 AKC 减水剂能提高材料的强度,但 PA 减水剂会降低材料的强度;N 减水剂对材料的综合性能提升效果 更加明显,其最优掺量为 0. 7%;减水剂对赤泥-矿渣基地聚物性能提升的作用机理主要是促进地聚合物凝胶的形成。 研究成果为拓展赤泥在工程上的使用途径和效率提供了理论指导。     

Application of artificial neural network method to predict the breakage properties of PGE bearing chromite ore

In the present investigation, systematic grinding experiments were conducted in a laboratory ball mill to determine the breakage properties of low-grade PGE bearing chromite ore. The population balance modeling technique was used to study the breakage parameters such as primary breakage distribution (B_{i, j}) and the specific rates of breakage (S_i). The breakage and selection function values were determined for six feed sizes. The results stated that the breakage follows the first-order grinding kinetics for all the feed sizes. It was observed that the coarser feed sizes exhibit higher selection function values than the finer feed size. Further, an artificial neural network was used to predict breakage characteristics of low-grade PGE bearing chromite ore. The predicted results obtained from the neural network modeling were close to the experimental results with a correlation of determination R² = 0.99 for both product size and selection function.     

基于现代审美下的赣傩艺术元素分析与设计应用

目的 赣傩艺术元素内容丰富并保存完整,是研究我国古代赣傩地区文化与艺术的珍贵史料.研究赣傩艺术元素的提取及衍生图案的设计方法,在设计应用中表达赣傩傩面具、选取傩舞形和构筑傩庙魂,能给当代赣傩艺术元素的产品设计以指引.方法 通过直接引用、形意结合和局部强化的设计方法,增厚其丰富内涵、设计个性和主题意蕴.通过现代化审美中"绿色化、感性化、地域化"的要求,遵循"以退为进,化繁为简""多元并存,个性体现"的原则,强化赣傩艺术元素的独特风格.结论 用现代的手法,将特色的赣傩艺术元素植入到理性的产品设计中去,使赣傩艺术元素与现代设计思想有机结合.在继承传统文化与现代流行中找到契合点,深入挖掘赣傩艺术元素蕴含的文化精神、文化胸怀和文化自信,使中华传统文化在现代审美下进行创新再现.     

Cognitive and affective processes for learning science in immersive virtual reality

As immersive virtual reality (IVR) systems proliferate in classrooms, it is important to understand how they affect learning outcomes and the underlying affective and cognitive processes that may cause these outcomes. Proponents argue that IVR could improve learning by increasing positive affective and cognitive processing, thereby supporting improved performance on tests of learning outcome, whereas opponents of IVR contend that it could hurt learning by increasing distraction, thereby disrupting cognitive learning processes and leading to poorer learning outcomes. In a media comparison study, students viewed a biology lesson either as an interactive animated journey in IVR or as a slideshow on a desktop monitor. Those who viewed the IVR lesson performed significantly worse on transfer tests, reported higher emotional arousal, reported more extraneous cognitive load and showed less engagement based on EEG measures than those who viewed the slideshow lesson, with or without practice questions added to the lessons. Mediational analyses showed that the lower retention scores for the IVR lesson were related to an increase in self-reported extraneous cognitive load and emotional arousal. These results support the notion that immersive environments create high affective and cognitive distraction, which leads to poorer learning outcomes than desktop environments.     

论携号转网行为的私法规制

以电信用户入网协议为切入点,电信用户的携号转网行为应受到《合同法》《消费者权益保护法》等私法规范的保护与限制。该行为引起的格式条款解释、合同终止、违约责任、损失赔偿等问题,不能仅靠《电信条例》等公法规范来调整。应当积极引导广大消费者用户以私法领域相关规定为依据,转变争议解决思维,拓宽纠纷处理途径,合理选择维权手段,以保护自身合法民事权益,与行业监管部门共同推动电信行业有序发展。     

高排放标准下道路燃油车处境分析

针对国六排放标准实施后道路燃油车竞争和生存压力加大的问题,调查统计近5 a汽车及新能源汽车的保有量,汽车保有量以年均12%的比例增长,新能源汽车保有量以每年约50%的比例增长;研究和对比近年来机动车排放标准,分析道路燃油车节能减排存在的问题,从政策引导制约、供油企业升级改造、燃油车本身的改进优化等几方面提出时效性方案与建议。     

管状带式输送机在线纠扭托辊的研究与应用

管状带式输送机是一种新型环保的散状物料连续输送设备,在运行过程中受各种因素影响,头、尾过渡段经常会跑偏,管状段经常会扭转,常规停机调偏纠扭方法已不能胜任复杂路线长距离管带机稳定运行的要求。为适应市场发展趋势,设计人员分析了管带机扭转原因,结合纠扭基本原理及常规纠扭方法,新开发出一种在线(不停机)纠扭托辊并投入项目应用。     

Applied data science in patient-centric healthcare: Adaptive analytic systems for empowering physicians and patients

We define the emerging research field of applied data science as the knowledge discovery process in which analytic systems are designed and evaluated to improve the daily practices of domain experts. We investigate adaptive analytic systems as a novel research perspective of the three intertwining aspects within the knowledge discovery process in healthcare: domain and data understanding for physician- and patient-centric healthcare, data preprocessing and modelling using natural language processing and (big) data analytic techniques, and model evaluation and knowledge deployment through information infrastructures. We align these knowledge discovery aspects with the design science research steps of problem investigation, treatment design, and treatment validation, respectively. We note that the adaptive component in healthcare system prototypes may translate to data-driven personalisation aspects including personalised medicine. We explore how applied data science for patient-centric healthcare can thus empower physicians and patients to more effectively and efficiently improve healthcare. We propose meta-algorithmic modelling as a solution-oriented design science research framework in alignment with the knowledge discovery process to address the three key dilemmas in the emerging “post-algorithmic era” of data science: depth versus breadth, selection versus configuration, and accuracy versus transparency.