安康体育旅游开发的SWOT分析及对策研究

运用SWOT分析方法,对安康体育旅游的优势、劣势、机遇和挑战进行分析后认为,安康在区位、资源方面具有优势,在人才、品牌及文化内涵建设方面处于劣势,在体育旅游需求和政策方面具有较好机遏,在资源与环境保护、市场竞争方面存在威胁。因此,安康体育旅游开发应加强各级各部门合作,加快体育旅游人才培养,积极开发精品体育旅游线路,注重挖掘体育旅游项目的文化内涵。     

在音乐教学中培养学生的自主探索能力

我国的教育模式正处于"应试教育"到"素质教育"的转型期,很多教师的教育方法还很落后,音乐教学也不例外.目前中小学音乐教学现状大致可归纳为两种:其一,从教学内容上主要为单一的教唱歌及为教唱而进行识谱教学.     

网络教学环境下自主学习能力的培养

利用校园网和现有教育资源构建适合自主学习的平台与环境,结合实践,对如何依托此平台培养学习者良好的自主学习能力进行分析和探讨。     

计算机组成原理课程导入教学的探讨

从课堂教学设计的各大因素讨论计算机组成原理第一节课"计算机系统概述"的具体设计,采用新颖有效的教学方法,探讨这些方法对知识传授、激发学生学习兴趣、发挥教师主导性和学生主体性产生的积极作用。     

新课程背景下提高高中数学课堂教学有效性的方法探究

随着教育改革的推进,对于高中数学教学的要求也在不断提高。高中数学内容复杂,学习难度大,知识点多,教学效果堪忧。为了有效提高高中数学的教学效率,教师要善于采用科学合理的教学方法。本文简要阐述了高中数学课堂教学的现状,从五个方面探讨如何最大限度地提高高中数学课堂教学的有效性。     

环境工程专业“环境化学”课程双语教学改革的实践与思考

双语教学是我国高校建设双一流大学的重要途径。本文结合环境工程专业的特点和人才培养需求,分析了环境化学课程双语教学的必要性和存在的问题,提出了启发-递进式教学模式、优选英文教材、优化教学内容、构建网络平台和建立多元化考核制等多种方法相结合的教学改革措施。     

“互联网+”时代背景下“科研思路与方法”教学模式探讨

当前,国家对大学本科的教育愈发重视,提出了多种教改方案。面对“互联网+”快速发展的形势,文章分析了“互联网+”时代背景下“科研思路与方法”新型教学模式的优势以及如何高效率地构建。通过教师、学生、互联网三者协调配合以及师生的线上互动交流和讨论,可以充分调动学生独立思考、自主学习的积极性,同时增加了教学趣味性,提高了教学质量。     

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.     

Diagnosis of CO2 dynamics and fluxes in global coastal oceans

Global coastal oceans as a whole represent an important carbon sink but, due to high spatial–temporal variability, a mechanistic conceptualization of the coastal carbon cycle is still under development, hindering the modelling and inclusion of coastal carbon in Earth System Models. Although temperature is considered an important control of sea surface pCO₂, we show that the latitudinal distribution of global coastal surface pCO₂ does not match that of temperature, and its inter-seasonal changes are substantially regulated by non-thermal factors such as water mass mixing and net primary production. These processes operate in both ocean-dominated and river-dominated margins, with carbon and nutrients sourced from the open ocean and land, respectively. These can be conceptualized by a semi-analytical framework that assesses the consumption of dissolved inorganic carbon relative to nutrients, to determine how a coastal system is a CO₂ source or sink. The framework also finds utility in accounting for additional nutrients in organic forms and testing hypotheses such as using Redfield stoichiometry, and is therefore an essential step toward comprehensively understanding and modelling the role of the coastal ocean in the global carbon cycle.     

Understanding divergent domestication traits from the whole-genome sequencing of swamp- and river-buffalo populations

Domesticated buffaloes have been integral to rice-paddy agro-ecosystems for millennia, yet relatively little is known about the buffalo genomics. Here, we sequenced and assembled reference genomes for both swamp and river buffaloes and we re-sequenced 230 individuals (132 swamp buffaloes and 98 river buffaloes) sampled from across Asia and Europe. Beyond the many actionable insights that our study revealed about the domestication, basic physiology and breeding of buffalo, we made the striking discovery that the divergent domestication traits between swamp and river buffaloes can be explained with recent selections of genes on social behavior, digestion metabolism, strengths and milk production.