Convergent genomic signatures of high-altitude adaptation among domestic mammals

Abundant and diverse domestic mammals living on the Tibetan Plateau provide useful materials for investigating adaptive evolution and genetic convergence. Here, we used 327 genomes from horses, sheep, goats, cattle, pigs and dogs living at both high and low altitudes, including 73 genomes generated for this study, to disentangle the genetic mechanisms underlying local adaptation of domestic mammals. Although molecular convergence is comparatively rare at the DNA sequence level, we found convergent signature of positive selection at the gene level, particularly the EPAS1 gene in these Tibetan domestic mammals. We also reported a potential function in response to hypoxia for the gene C10orf67, which underwent positive selection in three of the domestic mammals. Our data provide an insight into adaptive evolution of high-altitude domestic mammals, and should facilitate the search for additional novel genes involved in the hypoxia response pathway.     

Predicting future dynamics from short-term time series using an Anticipated Learning Machine

Predicting time series has significant practical applications over different disciplines. Here, we propose an Anticipated Learning Machine (ALM) to achieve precise future-state predictions based on short-term but high-dimensional data. From non-linear dynamical systems theory, we show that ALM can transform recent correlation/spatial information of high-dimensional variables into future dynamical/temporal information of any target variable, thereby overcoming the small-sample problem and achieving multistep-ahead predictions. Since the training samples generated from high-dimensional data also include information of the unknown future values of the target variable, it is called anticipated learning. Extensive experiments on real-world data demonstrate significantly superior performances of ALM over all of the existing 12 methods. In contrast to traditional statistics-based machine learning, ALM is based on non-linear dynamics, thus opening a new way for dynamics-based machine learning.     

Programmable deformation of patterned bimorph actuator swarm

Graphene-based actuators featuring fast and reversible deformation under various external stimuli are promising for soft robotics. However, these bimorph actuators are incapable of complex and programmable 3D deformation, which limits their practical application. Here, inspired from the collective coupling and coordination of living cells, we fabricated a moisture-responsive graphene actuator swarm that has programmable shape-changing capability by programming the SU-8 patterns underneath. To get better control over the deformation, we fabricated SU-8 micropattern arrays with specific geometries and orientations on a continuous graphene oxide film, forming a swarm of bimorph actuators. In this way, predictable and complex deformations, including bending, twisting, coiling, asymmetric bending, 3D folding, and combinations of these, have been achieved due to the collective coupling and coordination of the actuator swarm. This work proposes a new way to program the deformation of bilayer actuators, expanding the capabilities of existing bimorph actuators for applications in various smart devices.     

高校网球教学中学生网球兴趣的培养和提高

网球是一项非常有益身心健康的运动,可以帮助人们提高自身的运动能力、增强体质,很多高校开设了网球课程。如何提高学生对网球的兴趣,使其积极参与到网球课程中来成为了高校网球教学面临的主要难题。对此,笔者从高校当前的网球教学现状出发,为提高学生网球兴趣提出相应的建议。     

课堂巧问五式

著名教育家陶行知先生曾经说过:“发明千千万万,起点是一问。智者问得巧,愚者问得笨。”那么,在教学实践中,教师应该如何设置科学而又艺术的提问语,引导教学走向成功呢?一、悬念式问语案例:在教学“能被3整除的数”时,有位教师在黑板上写出:6、8、12、17、24、26、39、42、53、66。问:“谁能很快判断出哪个数能被3整除?”,当学生很快判断出来后。教师又写上:456、3250、5277。问:“谁能很快判断出哪个数能被3整除?”由于数目较大,学生陷入沉思。教师紧接着又说:“你们可以考考我,随便说一个数,我都能很快地判断出能否被3整除。”学生一听,急…     

教育的终极目的——关注人的生存状态

通过对教育终极目的的认识,分析了多种关于教育终极目的的论点.揭示了这些论点具有共同的基础,即教育是一门生存的艺术,它的终极目的应为关注人的生存状态.     

物理核心素养评价与学业质量检测的研究

物理是初中阶段的重要课程,也是学生对世界进行基本科学认知的引导课程.在学生系统学习了近两年的物理后,学校和教师应对学生进行物理核心素养评价和学业质量检测.在物理核心素质评价与学业质量检测中,只有从物理观念、科学探究、科学思维、科学态度与责任入手,才能让评价与检测全面、丰富和多元.     

美国情报搜集中个人数据隐私权状况及对我国的启示 ——以FISA第702条为研究样本

[目的/意义]大数据时代,美国情报机构监视恐怖嫌疑分子数据作为维护美国国家安全的重要方面,效果显著。然而,实践中出现"国家安全"和"个人数据安全""个人隐私权"相冲突的问题,对之研究具有重要的镜鉴价值。[方法/过程]以美国《涉外情报监控法》第702条为研究样本,实证分析了个人隐私被侵犯的原因,如即情报搜集工作监督不严、问责不力等。规范分析了平衡"国家安全"和"个人数据安全""个人隐私权"之间的法律对策。[结果/结论]研究认为,设立情报监督机构,规制数据使用目的和范围,加大问责力度是平衡国家安全和公民个人数据隐私权的积极面向。     

递归算法的非递规实现

本文详细阐明递规算法的实质,给出一种递归算法向非递归算法转化的基本思路。     

学区教研活动:问题与对策

近年来,为了弥补大范围活动的不便,出现了一种新的校际科研层次:学区教研组。由此形成了县教研室——学区教研组——校教研组的三级联动教研体系。县教育局根据学校的地域位置、教育发展状况、经济文化基础,同时考虑到优质资源的辐