From the margin to the center: A framework for rehumanizing mathematics education for students with dis/abilities

Mathematics education for students with dis/abilities has a legacy of exclusion; its scholarship has been dominated by ableist perspective: a focus on rote mathematics facts, procedural instruction, and a narrow range of mathematics content. Grounded in critical pedagogy and critical disabilities studies, we argue for a shift in the focus away from the student as the site of defect and intervention to recognize the complex embodiment of dis/ability as a process produced within historical, political, social, and material contexts. The theoretical assumptions and guiding principles for a framework of culturally responsive and relational understanding of dis/ability will be shared together with a case of such an approach in classroom practice. The paper advances efforts to support all learners in robust mathematics learning communities and to situate research from perspectives that acknowledge the situated, interactional nature of ability, identity, and achievement.     

基于深度学习的ELM实时识别研究

基于深度学习的方法，在HL-2A装置上开发出了一套边缘局域模(ELM)实时识别算法。算法使用5200次放电数据(约24.19万数据切片)进行学习，得到一个深度为22层的卷积神经网络。为衡量算法的识别能力，识别了HL-2A装置自2009年实现稳定ELMy H模放电以来所有历史数据(约26000次放电数据)，共识别出1665次H模放电，其中误识别35次，误报率为2.10%。在实际的1634次H模放电中，漏识别4次，漏识别率为0.24%。该误报率和漏报率可以满足ELM实时识别的精度要求。识别算法在实时控制环境下，对单个时间点的平均计算时间为0.46ms，可以满足实时控制的计算速度要求。     

基于SVM的固化土无侧限抗压强度模型

为实现较少试验次数下固化土无侧限抗压强度(qu)的准确预测, 提出了基于支持向量机(SVM)的固化土qu的预测模型. 以固化剂各组分掺入比、龄期、初始含水量、固化剂掺量等因素为输入量, 固化土的qu作为输出量, 以径向基为核函数, 采用网格搜索法和交叉验证法进行参数优化, 建立了基于SVM的固化土qu的预测模型. 算例分析表明: 该模型适用于任意条件下固化土qu的精确预测, 且在较小试验成本下实现与响应面法相当的预测精度.     

Tandem Use of Optical Sensing and Machine Learning for the Determination of Absolute Configuration,Enantiomeric and Diastereomeric Ratios,and Concentration of Chiral Samples

We have developed an optical method for accurate concentration, er, and dr analysis of amino alcohols based on a simple mix‐and‐measure workflow that is fully adaptable to multiwell plate technology and microscale analysis. The conversion of the four aminoindanol stereoisomers with salicylaldehyde to the corresponding Schiff base allows analysis of the dr based on a change in the UV maximum at 420 nm that is very different for the homo‐ and heterochiral diastereomers and of the concentration of the sample using a hypsochromic shift of another absorption band around 340 nm that is independent of the analyte stereochemistry. Subsequent in situ formation of Cu^II assemblies in the absence and presence of base enables quantification of the er values for each diastereomeric pair by CD analysis. Applying a linear programming method and a parameter sweep algorithm, we determined the concentration and relative amounts of each of the four stereoisomers in 20 samples of vastly different stereoisomeric compositions with an averaged absolute percent error of 1.7 %.     

Existence of solutions for a higher-order semilinear parabolic equation with singular initial data

We establish the existence of solutions of the Cauchy problem for a higher-order semilinear parabolic equation by introducing a new majorizing kernel. We also study necessary conditions on the initial data for the existence of local-in-time solutions and identify the strongest singularity of the initial data for the solvability of the Cauchy problem.     

师范专业认证背景下有机化学“三段式”教学法的构建与实践*

针对应用型本科院校化学专业的培养目标和师范专业认证标准,以“发现学习”和“建构主义学习”理论为依据,结合课程内容特点提出了基于学生为中心和产出导向的有机化学“三段式”教学法,并在糖类化合物、蛋白质和核酸章节中进行了具体的教学实施,对实施效果进行了问卷调查和分析。“三段式”教学法对有机化学教学模式的改革提供了一定的借鉴作用。     

Change in motor cortex activation for muscle release by motor learning

For central nervous system disorders'' rehabilitation, it is important to accurately understand motor control and implement an appropriate motor learning process to induce neuroplastic changes. The neurophysiological studies have revealed that neural control mechanisms are crucial during both the onset of muscular activities and muscle release after contraction. When performing various movements during daily activities, muscle relaxation control enables precise force output and timing control. Moreover, surround inhibition is a functional mechanism in the motor system. Surround inhibition of the motor system may be involved in the selective execution of desired movements. This review demonstrates cortical excitability resulting from motor learning, movement control mechanisms including muscle relaxation and the suppression of nontarget muscle groups, and the voluntary drive''s importance that is required for movement.     

Hierarchically Structured Allotropes of Phosphorus from Data-Driven Exploration

The discovery of materials is increasingly guided by quantum-mechanical crystal-structure prediction, but the structural complexity in bulk and nanoscale materials remains a bottleneck. Here we demonstrate how data-driven approaches can vastly accelerate the search for complex structures, combining a machine-learning (ML) model for the potential-energy surface with efficient, fragment-based searching. We use the characteristic building units observed in Hittorf's and fibrous phosphorus to seed stochastic (“random”) structure searches over hundreds of thousands of runs. Our study identifies a family of hierarchically structured allotropes based on a P8 cage as principal building unit, including one-dimensional (1D) single and double helix structures, nanowires, and two-dimensional (2D) phosphorene allotropes with square-lattice and kagome topologies. These findings yield new insight into the intriguingly diverse structural chemistry of phosphorus, and they provide an example for how ML methods may, in the long run, be expected to accelerate the discovery of hierarchical nanostructures.     

有机化学实验混合教学模式的设计与实践

通过介绍混合教学模式在有机化学实验课程教学中的设计、实施情况及效果评价与反馈等内容,与大家分享混合教学模式在有机化学实验课程教学中的应用经验与思考。     

基于GA_XGBoost模型的大学生科研能力预测问题研究

科学评价大学生科研创新能力对我国科研水平的提高具有重要意义.采用机器学习模型来预测大学生科研能力可以起到良好的效果,提出一种GAXGBoost模型来实现对大学生的科研能力预测.此模型是以Xgboost算法为基础,然后充分利用遗传算法的全局搜索能力自动搜索Xgboost最优超参数,避免了人为经验调参不准确的缺陷,最后采用精英选择策略以此确保每一轮都是最佳的进化结果.通过分析表明,所采用的GAXGBoost模型在大学生科研能力预测的结果中具有很高的精度,将此模型与Logistic Regression、Random Forest、SVM等模型进行对比,GAXGBoost模型的预测精度最高.