Literature-related discovery (LRD): Methodology

Literature-related discovery (LRD) is linking two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge. LRD has two components: Literature-based discovery (LBD) generates potential discovery through literature analysis alone, whereas literature-assisted discovery (LAD) generates potential discovery through a combination of literature analysis and interactions among selected literature authors. In turn, there are two types of LBD and LAD: open discovery systems (ODS), where one starts with a problem and arrives at a solution, and closed discovery systems (CDS), where one starts with a problem and a solution, then determines the mechanism(s) that links them.The generic methodology for identifying potential discovery candidates through ODS LRD, focusing mainly on its ODS LBD component, is described in this paper. A comprehensive flow chart showing the details of our systematic potential discovery generation process, including the evolution of the flow chart steps through each of the studies performed, is presented. Also shown is a vetting procedure that insures potential discoveries claimed are potential discoveries realized. The semantic filters that replace the numerical filters of other ODS LBD approaches are overviewed. The rationale for addressing the five topics studied (Raynaud's Phenomenon (RP), Cataracts, Parkinson's Disease (PD), Multiple Sclerosis (MS), and Water Purification (WP)) is summarized.     

听力元认知策略指导和发现式听力教学法比较研究

运用实证研究,比较听力元认知策略指导和发现式听力教学法对大学新生复合式听写能力的影响。实验表明,两种教学法均有利于提高学生复合式听写能力,但发现式听力教学法体现了一定的优势。     

Toxicogenomic predictive modeling: Emerging opportunities for more efficient drug discovery and development

Drug discovery companies are coming under increasing pressure to prove the long-term safety of their products more precisely, and to provide more data on them. As highlighted by Vioxx, for many drugs, the existence of adverse drug reactions (ADRs) becomes apparent once the compound has been extensively prescribed and a population base of considerable size has been exposed to the therapeutic agent. The ability to make decisions regarding termination of clinical development of a non-viable drug candidate as early as possible will have a large financial impact for a pharmaceutical company. Knowledge regarding the interactions of chemicals, genes, and cell function can improve chemical risk analyses. These efforts will be aided by continued improvement and expansion of predictive toxicology in combination with a range of mutually supportive technologies to develop strategies to facilitate better and more focused decision-making throughout the drug discovery process. Failure to implement such an approach causes companies to withdraw drugs from development or the market. This not only presents human health consequences but also has a negative economic impact on the industry. As such, one of the major challenges in drug discovery is to accurately predict which new drugs will be associated with a significant incidence of ADRs. The ability to produce information on potential toxicity early in the discovery phase will become the basis for judging whether a drug candidate merits further development.     

基于Morlet小波时频互相关的股指期货价格发现效率研究

本文采用Morlet小波时频互相关分析方法,从"时域"和"频域"两个维度检验了我国以及国际主要市场股指期货和现货价格序列的动态关联性,研究了股指期货价格发现效率的问题。研究表明,沪深300指数和股指期货在低频长周期范围内,呈现长时间高度相关、协同波动的特征;在高频短周期范围内,两者整体仍然具有协同波动特征,但时常出现短暂紊乱的情况,即期货与现货的交错引导现象。我国股指期货市场的价格发现效率较美国、英国成熟市场仍有较大差距,但强于日本。     

政府投资基金融资网络特征：城市分布、网络关系与社区发现

近年来,我国政府投资基金呈现井喷式发展态势,基金数量和总体规模在风险投资市场中占据较大比重。运用爬虫技术获取政府投资基金大样本微观数据,并用复杂网络法从市级层面考察我国政府投资基金资本集聚情况。研究发现：我国政府投资基金在融资网络层面呈现显著“极点效应”,北京、深圳、上海、苏州等城市为主要集聚区,西部、东北地区未能形成集聚;政府投资基金具有显著“邻近效应”,本地机构更愿意参与本地基金的设立,省域内城市形成明显的族群结构。此外,深圳、苏州政府投资基金相比于北京、上海等城市更具有市场属性。据此,提出如下建议：我国政府投资基金应加强对社会资本的引导,更加注重市场导向;适当降低中西部和东北地区政府投资基金杠杆率,通过政府投资基金吸引东部优势产业向中西部地区转移,进而促进当地政府投资基金落地和资本集聚,并助推区域产业升级与创新发展。     

Literature-Related Discovery (LRD): Potential treatments for Parkinson's Disease

Literature-Related Discovery (LRD) is the linking of two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge (i.e., potential discovery). The open discovery systems (ODS) component of LRD starts with a problem to be solved, and generates solutions to that problem through potential discovery. We have been using ODS LRD to identify potential treatments or preventative actions for challenging medical problems, among myriad other applications. The previous two papers in this Special Issue describe the application of ODS LRD to Raynaud's Phenomenon (RP) and to cataracts.Parkinson's Disease (PD) is a progressive neurodegenerative disorder, affecting approximately 1% of individuals older than 60 years, and is characterized by resting tremor, rigidity, bradykinesia, and postural instability. We selected the subject of PD because of its global prevalence, and its apparent intractability to all treatments except for palliative remediation mainly through drugs or surgery.Our first goal was to identify non-drug non-surgical treatments that would 1) prevent the occurrence, or 2) reduce the progression rate, or 3) stop the progression, or 4) maybe even reverse the progression, of PD. Our second goal was to demonstrate that we could again solve an ODS problem (using LRD) with no prior knowledge of any results or prior work (unlike the case of the RP problem). As in the ‘cataract’ example, we used the MeSH taxonomy of MEDLINE to restrict potential discoveries to selected semantic classes, and to identify potential discoveries efficiently. Our third goal was to generate large amounts of potential discovery in more than an order of magnitude less time than required for the RP study. The discovery generation methodology has been developed to the point where ODS LRD problems can be solved with no results or knowledge of any prior work.     

数据挖掘的商务应用前景

数据挖掘已经成为许多商业领域的一个热门话题。数据挖掘已经成为许多企业在国际市场上赢 得竞争优势的重要的竞争工具之一。国内外早期的研究集中在算法的研究上。其实很多时候技术不是主要 的问题。如何实现从技术到商业的应用才是困扰业界的主要难题。本文试图在这方面有所贡献。本文试图 分别从实践和理论两个角度来阐释数据挖掘的现实的实用性和战略的重要性。本文以一个零售行业的数据 挖掘案例探讨了数据挖掘的商务应用;从技术和商业需求两个方面分别研究了数据挖掘商务应用的可行 性,并指出因竞争战略的细化导致了对数据挖掘的商业需求;最后根据实践经验讨论了数据挖掘在几个典型 行业的应用,希望能拓展我们对数据挖掘的理论和实践的认识。     

Thinking inside the box: A participatory, computer-assisted approach to scenario discovery

Scenarios provide a commonly used and intuitively appealing means to communicate and characterize uncertainty in many decision support applications, but can fall short of their potential especially when used in broad public debates among participants with diverse interests and values. This paper describes a new approach to participatory, computer-assisted scenario development that we call scenario discovery, which aims to address these challenges. The approach defines scenarios as a set of plausible future states of the world that represent vulnerabilities of proposed policies, that is, cases where a policy fails to meet its performance goals. Scenario discovery characterizes such sets by helping users to apply statistical or data-mining algorithms to databases of simulation-model-generated results in order to identify easy-to-interpret combinations of uncertain model input parameters that are highly predictive of these policy-relevant cases. The approach has already proved successful in several high impact policy studies. This paper systematically describes the scenario discovery concept and its implementation, presents statistical tests to evaluate the resulting scenarios, and demonstrates the approach on an example policy problem involving the efficacy of a proposed U.S. renewable energy standard. The paper also describes how scenario discovery appears to address several outstanding challenges faced when applying traditional scenario approaches in contentious public debates.     

科学发现优先权视角下的"网红科学家"现象研究

在后学院科学背景下，科学发现优先权可以带来更多的社会资源与经济利益。有学者甚至认为，科学已经从学院科学时代下“为了公众利益的科学”演变成“为了私人利益的科学”。当前，由于移动互联网等媒介技术的发达，借助于新媒介的广泛传播作用，出现了一些因为科学发现优先权而受媒体和公众异常关注的“网红科学家”，这是一个值得关注的新现象。案例研究发现，部分“网红科学家”及其背后组织，重视了科学发现优先权中独创性所表征出的时效性，但忽视了科学共同体的承认与检验。“网红科学家”主张的科学发现优先权，如果通不过科学共同体的检验与承认，其自身以及背后支持组织也会受到“网红”这把“双刃剑”的损害。     

浅析同化理论指导下发现学习在英语口语教学中的运用

英语口语教学在很大程度上受到同化理论的指导,本文通过探索同化理论在英语口语教学中的实践,提出发现学习的应用弥补了理论的不足。