农房确权的制度设计与政策建议

农民住房财产权的确认(简称农房确权)有助于维护农民财产权利,为下一步农村改革创造 前置条件和法律依据。然而,实践中农房确权面临着甄别、处置、配合和实施等各种难题。建议在制度 设计上按照“房地一体,先地后房”的原则,对农房进行分类处理,通过收取宅基地有偿使用费、明确确权 操作流程等措施予以完善。在此基础上,地方政府利用农房确权契机鼓励农村集约节约用地,通过规划 指导和建房监管确保新建农房达到确权要求,中央政府推进宅基地流转和农房财产权抵押担保制度改 革,使农房确权更具实质意义。     

技术设计：技术认识的形象化

技术设计是运用设计理论和方法，在创制和改造技术人工物的过程中，把思维中的技术构思规范化、定量化，把它们以标准的图纸或说明书的形式展现出来的创造性活动。技术设计是解决技术问题的关键，通过分析问题、综合取舍、实践评估等环节使得抽象的技术认识得以形象化、具体化，从而形成切实的技术问题解决方案。在不同的认识情形下，技术设计或者被当作一个黑箱，或者被当作一个白箱，或者被当作一个系统，这三种不同的设计方式分别反映出技术设计的创造性、合理性和过程控制。     

A Shiny Update to an Old Experiment Game

ABSTRACT

Games can be a powerful tool for learning about statistical methodology. Effective game design involves a fine balance between caricature and realism, to simultaneously illustrate salient concepts in a controlled setting and serve as a testament to real-world applicability. Striking that balance is particularly challenging in response surface and design domains, where real-world scenarios often play out over long time scales, during which theories are revised, model and inferential techniques are improved, and knowledge is updated. Here, I present a game, borrowing liberally from one first played over 40 years ago, which attempts to achieve that balance while reinforcing a cascade of topics in modern nonparametric response surfaces, sequential design, and optimization. The game embeds a blackbox simulation within a shiny app whose interface is designed to simulate a realistic information–availability setting, while offering a stimulating, competitive environment wherein students can try out new methodology, and ultimately appreciate its power and limitations. Interface, rules, timing with course material, and evaluation are described, along with a “case study” involving a cohort of students at Virginia Tech. Supplementary materials for this article are available online.     

Revisiting Nested Group Testing Procedures: New Results,Comparisons, and Robustness

Group testing has its origin in the identification of syphilis in the U.S. army during World War II. Much of the theoretical framework of group testing was developed starting in the late 1950s, with continued work into the 1990s. Recently, with the advent of new laboratory and genetic technologies, there has been an increasing interest in group testing designs for cost saving purposes. In this article, we compare different nested designs, including Dorfman, Sterrett and an optimal nested procedure obtained through dynamic programming. To elucidate these comparisons, we develop closed-form expressions for the optimal Sterrett procedure and provide a concise review of the prior literature for other commonly used procedures. We consider designs where the prevalence of disease is known as well as investigate the robustness of these procedures, when it is incorrectly assumed. This article provides a technical presentation that will be of interest to researchers as well as from a pedagogical perspective. Supplementary material for this article is available online.     

学习分析视域下S-ISAL在大学英语混合式教学中的构建与评估

学习分析技术在教育教学中的应用，其根本目的是为了构建新的教学法，更新教学与管理的方式。针对高校大学英语线上、线下混合教学无法有机融合的现状，S-ISAL（Space-based Information search and Analysis Learning）应运而生，它是基于网络学习空间的信息搜集与分析的教学模式，将学习分析技术引入大学英语混合式课程中。探究该教学模式在大学英语教学中的适切性和实效性是文章的研究重点，目的是为了实现大学英语线上、线下教学优势互补，为大学生在线英语学习提供更具个性化的学习内容和路径，并提升大学生自适应学习能力和在线学习绩效。     

儿童社会情绪学习：Strong Kids系列课程介绍及启示

Strong Kids系列课程是儿童社会情绪学习的经典课程之一，包括5个相对独立的版本，具有扎实的理论基础，是一项方便、经济且见效快的短期预防干预项目，能有效地预防和减少儿童的情绪行为障碍，提升儿童的社会情绪能力。该课程的设计、内容及形式等都值得为他人所借鉴。为此，笔者通过对Strong Kids系列课程的理论基础、主要内容及应用的阐述，探讨该课程的优势及对我国儿童社会情绪学习课程开发与实施的启示。     

Machine Learning for Drug Overdose Surveillance

ABSTRACT

We describe two recently proposed machine learning approaches for discovering emerging trends in fatal accidental drug overdoses. The Gaussian Process Subset Scan (Herlands, McFowland, Wilson, & Neill, 2017 Neill, D. B. (2017). Multidimensional tensor scan for drug overdose surveillance. Journal of Public Health Informatics, 9(1), e20. doi:10.5210/ojphi.v9i1.7598[Crossref] , [Google Scholar]) enables early detection of emerging patterns in spatio-temporal data, accounting for both the complex, correlated nature of the data and the fact that detecting subtle patterns requires integration of information across multiple spatial areas and multiple time steps. We apply this approach to 17 years of county-aggregated data for monthly opioid overdose deaths in the New York City metropolitan area, showing clear advantages in the utility of discovered patterns as compared to typical anomaly detection approaches. To detect and characterize emerging overdose patterns that differentially affect a subpopulation of the data, including geographic, demographic, and behavioral patterns (e.g., which combinations of drugs are involved), we apply the Multidimensional Tensor Scan (Neill, 2017 Neill, D. B. (2017). Multidimensional tensor scan for drug overdose surveillance. Journal of Public Health Informatics, 9(1), e20. doi:10.5210/ojphi.v9i1.7598[Crossref] , [Google Scholar]) to 8 years of case-level overdose data from Allegheny County, Pennsylvania. We discover previously unidentified overdose patterns which reveal unusual demographic clusters, show impacts of drug legislation, and demonstrate potential for early detection and targeted intervention. These approaches to early detection of overdose patterns can inform prevention and response efforts, as well as understanding the effects of policy changes.     

A dynamic business modelling approach to design and experiment new business venture strategies

Business Modelling has evolved as a key activity to reflect new business venture strategy by framing the way a firm will operate and how it will function in achieving its goals (e.g., profitability, growth, innovation, social impact). However, scholars and practitioners have criticized the adoption of a too static perspective in the design and use of conventional Business Model representations. Such a static perspective prevents nascent entrepreneurs experimenting with their Business Models and, as a result, identifying the most effective strategies, especially in terms of business sustainability and profitability. In this paper, we argue that combining conventional Business Model schemas with System Dynamics modelling results in a strategy design tool that may overcome several limitations related to a static view of Business Model representation. Mapping the different key elements underlying value creation processes into a system of causal interdependencies – through the use of simulation – allows strategy analysts and entrepreneurs to experiment and learn how the business reacts to strategic and organizational changes in terms of performance, innovation and value creation. As such, Dynamic Business Models provide useful insights to strategy formulation and business venturing by capturing how critical Business Model elements interact to produce enduring competitive advantages over time.