高校涉化类专业安全教育实效及提升策略研究——以天津理工大学为例

为考察高校涉化类专业安全教育实效,对天津理工大学化学化工学院670名学生进行问卷调查。问卷内容包括学生对化学专业的态度、兴趣、安全意识、安全经验、安全行为等。调查结果表明:安全意识方面,不同年级差异显著;化学恐惧和安全行为方面,不同性别差异显著;回归分析表明,安全意识/能力及化学兴趣与安全行为显著正相关。根据统计分析,提出以下提升策略:注重安全教育的持续性;关注学生心理安全;注意发挥学生的主观能动性。     

How to Utilize my App Reviews? A Novel Topics Extraction Machine Learning Schema for Strategic Business Purposes

Acquiring knowledge about users’ opinion and what they say regarding specific features within an app, constitutes a solid steppingstone for understanding their needs and concerns. App review utilization helps project management teams to identify threads and opportunities for app software maintenance, optimization and strategic marketing purposes. Nevertheless, app user review classification for identifying valuable gems of information for app software improvement, is a complex and multidimensional issue. It requires foresight and multiple combinations of sophisticated text pre-processing, feature extraction and machine learning methods to efficiently classify app reviews into specific topics. Against this backdrop, we propose a novel feature engineering classification schema that is capable to identify more efficiently and earlier terms-words within reviews that could be classified into specific topics. For this reason, we present a novel feature extraction method, the DEVMAX.DF combined with different machine learning algorithms to propose a solution in app review classification problems. One step further, a simulation of a real case scenario takes place to validate the effectiveness of the proposed classification schema into different apps. After multiple experiments, results indicate that the proposed schema outperforms other term extraction methods such as TF.IDF and χ² to classify app reviews into topics. To this end, the paper contributes to the knowledge expansion of research and practitioners with the purpose to reinforce their decision-making process within the realm of app reviews utilization.     

Near-Infrared Electroluminescence beyond 800 nm with High Efficiency and Radiance from Anthracene Cored Emitters

Derivatives based on anthryleno[1,2-b]pyrazine-2,3-dicarbonitrile (DCPA) are used as luminescent materials, to realize near-infrared (NIR) electroluminescence. By functionalizing DCPA with aromatic amine donors, two emitters named DCPA-TPA and DCPA-BBPA are designed and synthesized. Both molecules have large dipole moments owing to the strong intramolecular charge transfer interactions between the amine donors and the DCPA acceptor. Thus, compared with doped films, the emission of neat films of DCPA-TPA and DCPA-BBPA can fully fall into the NIR region (>700 nm) with increasing surrounding polarity by increasing doping ratio. Moreover, the non-doped devices based on DCPA-TPA and DCPA-BBPA provide NIR emission with peaks at 838 and 916 nm, respectively. A maximum radiance of 20707 mW Sr⁻¹ m⁻² was realized for the further optimized device based on DCPA-TPA. This work provides a simple and efficient strategy of molecular design for developing NIR emitting materials.     

化学教学中的理性思维:内涵分析、实践缺失与设计策略*

理性思维是中国学生发展核心素养的要点之一,是化学课程落实核心素养的重要内容。理性思维的精神实质在于追求本原,是一种与直觉经验相对应的高阶认知技能,是理科教学的目标和手段。化学教学实践中理性思维的缺失集中表现在教学活动缺乏理性思维的引导,具体在教学问题、教学方式、教学方法上表现突出。为此,课堂教学活动设计中可以从认知顺序、思维方式、思维方法的运用上落实理性思维的培养。     

Overcoming the Biological Contamination in Microalgae and Cyanobacteria Mass Cultivations for Photosynthetic Biofuel Production

Microalgae and cyanobacteria have shown significant potential for the development of the next biofuels innovation because of their own characteristics as photosynthetic microorganisms. However, it is confronted with a lot of severe challenges on the economic scaling-up of the microalgae- and cyanobacteria-based biofuels production. One of these major challenges is the lack of a reliable preventing and controlling culture system of biological contamination, which can attack the cell growth or product accumulation causing crashing effects. To increase the commercial viability of microalgae- and cyanobacteria-based biofuels production, overcoming the biological contaminations should be at the top of the priority list. Here, we highlight the importance of two categories of biological contaminations and their controlling strategies in the mass cultivations of microalgae and cyanobacteria, and outline the directions that should be exploited in the future.     

Structuring Metal–Organic Framework Materials into Hierarchically Porous Composites through One-Pot Fabrication Strategy

Controlled synthesis of metal–organic framework (MOF)-based materials with multiple levels of porous structures across different length scales is of great interest in various applications but it still remains challenging. Most of the current strategies are time consuming and labor intensive, and not readily scaled-up. In this work, we introduce a straightforward one-pot fabrication strategy to prepare a robust and flexible hierarchically macro-meso-micro porous HKUST-1/polyvinylidene fluoride (PVDF) composite through solvent evaporation, in which MOF crystallization and polymer precipitation are combined together. The effect of the MOF precursor and the polymer initial amount on the morphology of the final composite was thoroughly studied. The interaction between the MOF and the polymer during the evaporation process is the key factor, which would limit the mobility of the polymer chains and cause instability in the MOF growth, thus endowing the composite with a hierarchically macro-meso-micro porous structure. This “all-in-one” porous structure could enhance the mass transport property of molecules within the composite. The obtained HKUST-1/PVDF composite showed an enhanced CO₂ adsorption rate constant of 0.821 min⁻¹ (298 K, 1 bar), which was 3.5 times higher than that of the pristine MOF. In addition, the composite showed an equivalent gas adsorption capacity under all tested pressures and greatly improved water stability.     

可拓学的应用研究、普及与推广(综述)

可拓学研究的核心是如何通过变换处理矛盾问题.介绍了近年在计算机、设计、管理、控制、检测和中医药等领域利用可拓论和可拓方法的应用研究情况,提出今后可拓学普及与推广的方向.     

一类随机模型的最优捕获问题研究

在Volterra两种群竞争模型的基础上,构造了随机的具有捕获的两种群竞争模型,研究讨论了捕获对种群生长过程的影响和如何实现最优捕获等问题.从确定性模型入手,深入讨论随机竞争模型的收获最优问题.通过对捕获强度E和贴现率等的估计与讨论,计算出了最优捕获强度最优捕获量最优经济收益.     

截断策略下求解第一类积分方程离散的DSM方法

本文用多尺度投影方法求解离散的DSM问题,与传统全投影方法相比, 减少了内积计算个数, 保持了最优收敛率.最后, 算例说明了算法的有效性.     

基于Stackelberg博弈策略下的多渠道供应链决策研究

构建了基于价格竞争的多渠道供应链模型,模型中两个不同的制造商分别通过单渠道、双渠道销售具有一定替代性的产品,考虑到制造商在市场上的领导地位,制造商与零售商之间采用stackclberg博弈竞争策略.探讨了拥有双渠道的制造商采取分散和集中利润决策时供应链各竞争者的价格策略,分析了需求函数参数变化对供应链竞争者价格决策的影响,借助算例分析表明,拥有双渠道营销方式的制造商采取决策1有利于提高其所在供应链的利润,采用决策2能够激励零售商维持原有的分销渠道.