Literature based discovery: Techniques and tools

Literature Based Discovery (LBD) was initially proposed by Don R. Swanson in 1980 as a method to establish relationships between disease and remedy from disjoint science literature. Consequently, he established a link between magnesium and migraines. Since then literature based discovery has been a subject of research and development for discovery in online medical publications. It has further been investigated in both chemistry and mathematics; In this thesis, we give an overview of LBD and the software tools necessary to automate this technique. We further provide an implementation of this technique that is intended to be used for computer science subject matter

Collaborative development of the Arrowsmith two node search interface designed for laboratory investigators.

Arrowsmith is a unique computer-assisted strategy designed to assist investigators in detecting biologically-relevant connections between two disparate sets of articles in Medline. This paper describes how an inter-institutional consortium of neuroscientists used the UIC Arrowsmith web interface http://arrowsmith.psych.uic.edu in their daily work and guided the development, refinement and expansion of the system into a suite of tools intended for use by the wider scientific community

EpiphaNet: An Interactive Tool to Support Biomedical Discoveries

Background. EpiphaNet (http://epiphanet.uth.tmc.edu) is an interactive knowledge discovery system, which enables researchers to explore visually sets of relations extracted from MEDLINE using a combination of language processing techniques. In this paper, we discuss the theoretical and methodological foundations of the system, and evaluate the utility of the models that underlie it for literature‐based discovery. In addition, we present a summary of results drawn from a qualitative analysis of over six hours of interaction with the system by basic medical scientists. Results: The system is able to simulate open and closed discovery, and is shown to generate associations that are both surprising and interesting within the area of expertise of the researchers concerned. Conclusions: EpiphaNet provides an interactive visual representation of associations between concepts, which is derived from distributional statistics drawn from across the spectrum of biomedical citations in MEDLINE. This tool is available online, providing biomedical scientists with the opportunity to identify and explore associations of interest to them

Using latent semantic indexing for literature based discovery

Latent semantic indexing (LSI) is a statistical technique for improving information retrieval effectiveness. Here, we use LSI to assist in literature-based discoveries. The idea behind literature-based discoveries is that different authors have already published certain underlying scientific ideas that, when taken together, can be connected to hypothesize a new discovery, and that these connections can be made by exploring the scientific literature. We explore latent semantic indexing's effectiveness on two discovery processes: uncovering “nearby” relationships that are necessary to initiate the literature based discovery process; and discovering more distant relationships that may genuinely generate new discovery hypotheses. © 1998 John Wiley & Sons, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/34255/1/2_ftp.pd

Knowledge synthesis in the biomedical literature: Nordihydroguaiaretic acid and breast cancer.

This dissertation refines knowledge synthesis from publicly accessible databases, based on the model of D.R. Swanson. Knowledge synthesis endeavors bring together two or more non-interactive literatures to create combinatorial research data on a specific topic. In this endeavor the biomedical literature was searched on the anti-neoplastic agent nordihydroguaiaretic acid (NDGA) for its potential role as a functional food in the chemoprevention of breast cancer. Bibliometric cocitation was utilized to identify complementary but non-interactive literatures in the disciplines of biomedicine and dietary science. The continuing specialization and fragmentation of the cancer literature degenerates the potential usefulness of cross-disciplinary research and information. As the biomedical sciences become more specialized the potential increases for isolation of discoveries and for failures to connect science to the needs of the people. Within the information science discipline several techniques are available to bridge the isolation between discoveries recorded in different sets of literatures. Electronic database searching with combinatorial keyword entries, syllogistic modeling and bibliometric author cocitation analysis are the principle techniques applied in this endeavor. The research questions are addressed to the absence or presence of human in vivo research on breast cancer with the potentially chemopreventative functional food NDGA. Utilizing a syllogistic model the literatures of functional foods, nordihydroguaiaretic acid and breast cancer were searched with designated combinatorial keywords. The documents retrieved were subjected to author cocitation analysis to demonstrate disjointness or connectivity of the two complementary literatures. The results demonstrated a possible preventative relationship between breast cancer in women and nordihydroguaiaretic acid, a phytochemical antioxidant and potential functional food. The results of this study are consistent with D.R. Swanson's pioneering work in knowledge synthesis. Swanson's methods can be used to identify non-interactive, disjoint literatures. Continuing support for his techniques has been demonstrated

Religion and Growth

We use the elements of a macroeconomic production function—physical capital, human capital, labor, and technology—together with standard growth models to frame the role of religion in economic growth. Unifying a growing literature, we argue that religion can enhance or impinge upon economic growth through all four elements because it shapes individual preferences, societal norms, and institutions. Religion affects physical capital accumulation by influencing thrift and financial development. It affects human capital through both religious and secular education. It affects population and labor by influencing work effort, fertility, and the demographic transition. And it affects total factor productivity by constraining or unleashing technological change and through rituals, legal institutions, political economy, and conflict. Synthesizing a disjoint literature in this way opens many interesting directions for future research

Stochastic models for quality of service of component connectors

The intensifying need for scalable software has motivated modular development and using systems distributed over networks to implement large-scale applications. In Service-oriented Computing, distributed services are composed to provide large-scale services with a specific functionality. In this way, reusability of existing services can be increased. However, due to the heterogeneity of distributed software systems, software composition is not easy and requires additional mechanisms to impose some form of a coordination on a distributed software system. Besides functional correctness, a composed service must satisfy various quantitative requirements for its clients, which are generically called its quality of service (QoS). Particularly, it is tricky to obtain the overall QoS of a composed service even if the QoS information of its constituent distributed services is given. In this thesis, we propose Stochastic Reo to specify software composition with QoS aspects and its compositional semantic models. They are also used as intermediate models to generate their corresponding stochastic models for practical analysis. Based on this, we have implemented the tool Reo2MC. Using Reo2MC, we have modeled and analyzed an industrial software, the ASK system. Its analysis results provided the best cost-effective resource utilization and some suggestions to improve the performance of the system.UBL - phd migration 201

The implicitome: A resource for rationalizing gene-disease associations

High-throughput experimental methods such as medical sequencing and genome-wide association studies (GWAS) identify increasingly large numbers of potential relations between genetic variants and diseases. Both biological complexity (millions of potential gene-disease associations) and the accelerating rate of data production necessitate computational approaches to prioritize and rationalize potential gene-disease relations. Here, we use concept profile technology to expose from the biomedical literature both explicitly stated gene-disease relations (the explicitome) and a much larger set of implied gene-disease associations (the implicitome). Implicit relations are largely unknown to, or are even unintended by the original authors, but they vastly extend the reach of existing

Intelligent Low Voltage Series Arc Detection System

Protection from electric power hazardous has been used ever since applications of electricity were discovered. Hazards in the electric system can be in the form of over voltage or over current leading to catastrophic system and equipment failure, resulting in physical damage or even to human fatalities. Electrical protection is achieved by installing protection devices throughout distribution system to isolate faulty branches and mitigate fault development. Fire is a principal cause of buildings damages and related personal injuries. A major contributor to buildings’ fire originates from electrical arc faults caused by electric distribution equipment and appliances failures. To remedy this problem, regulatory bodies required electric arc faults protection. Over the years this requirement was enforced by different electric codes and expanded to cover most of residential building areas and all living spaces. Arc fault circuit interrupters (AFCI) are devised to complement existing protection methodologies and devices, focusing on electric arc detection and preventions of subsequent risks, mainly fire ignition. Circuit interruption occurs whenever characteristics of arc failure is detected, either from current, voltage or electromagnetic radiation. Detecting the arc faults, and hence increasing the reliability of interruption, is a challenge, given that some household appliances produce arc-like behaviors in normal operating conditions, like electronic light dimmers and solid state controlled variable speed drives. This research focuses on developing an intelligent low voltage series arcing detection scheme based on pattern recognition, with immunity to false tripping. This point is the main drawback of most published work and issued patents on arc detection to date, mainly due to the difficulty of modelling such a transient behavior, especially on low current arc cases. Real data is generated in lab simulating series arc conditions at different combinations of linear and non-linear loads. Appliances current are recorded as well. Two disjoint datasets are used for training and testing of the proposed system with no components shared between the two datasets to verify classifier generality. The proposed pattern recognition method proved to be highly immune to false tripping in line with benchmark regulatory standard, and can be adapted to similar hard to model non-stationary problems

Contesting The Generic Refugee: SIV Identity, Community, And Agency During Resettlement

This thesis examines the complexity of identity and community formation by Special Immigrant Visa (SIV) holders during resettlement in Columbia, South Carolina. It explores the ways in which identities coalesce around various themes, such as religion, gender, and military service, how these identities serve to create, expand, and claim membership in communities, and how SIVs exercise agency throughout these processes. Through semi-structured interviews with 9 SIVs in Columbia, SC, this qualitative study highlights the unique, highly individualized ways in which a select group of refugees experience resettlement, how they negotiate their placement within socio-economic hierarchies, and exercise agency to obtain access to employment, housing, vehicles, and information. This contests the form of the ‘generic’ refugee, adds to existing literatures that address the complexity of refugee resettlement, and suggests the need for a reorientation of resettlement policies