Bioinspired Materials Design: An Assessment of Methods to Improve a Text Mining Algorithm for Identifying Biological Material Structural Design Principles

2016 ◽  
Author(s):  
Joanna Tsenn ◽  
Julie S. Linsey ◽  
Daniel A. McAdams
Keyword(s):  
Text Mining ◽  
Structural Design ◽  
Design Principles ◽  
Biological Materials ◽  
Journal Articles ◽  
Part Of Speech ◽  
Mining Algorithm ◽  
Wide Range ◽  
Bioinspired Materials ◽  
Future Work

Natural materials are able to achieve a wide range and combination of properties through the arrangement of the material’s components. These biological materials are often more effective and better suited to their function than engineered materials, even with the use of a limited set of components. By mimicking a biological material’s component arrangement, or structure, man-made bioinspired materials can achieve improved properties as well. While considerable research has been conducted on biological materials, identifying the beneficial structural design principles can be time-intensive for a materials designer. Previously, a text mining algorithm and tool were developed to quickly extract passages describing property-specific structural design principles from a corpus of materials journals. Although the tool identified over 90% of the principles (recall), many irrelevant passages were returned as well with approximately 32% of the passages being useful (precision). This paper discusses approaches to refine the program in order to improve precision. The text classification techniques of machine learning classifiers, statistical features, and part-of-speech analyses, are evaluated for effectiveness in sorting passages into relevant and irrelevant classes. Manual identification of patterns in the returned passages is also employed to create a rule-based method, resulting in an updated algorithm. An evaluation comparing the revised algorithm to the previously developed algorithm is completed using a new set of journal articles. Although the revised algorithm’s recall was reduced to 80%, the precision increased to 45% and the number of returned passages was reduced by 22%, allowing a materials designer to more quickly identify potentially useful structures. The paper concludes with suggestions to improve the program’s usefulness and scope for future work.

Development of a Search Tool to Identify Structural Design Principles for Bioinspired Materials Design

2014 ◽  
Author(s):  
Joanna Tsenn ◽  
Julie S. Linsey ◽  
Daniel A. McAdams
Keyword(s):  
Material Properties ◽  
Structural Design ◽  
Design Principles ◽  
Biological Materials ◽  
Search Term ◽  
Manual Search ◽  
Bioinspired Materials ◽  
Search Tool ◽  
Engineered Materials ◽  
Key Terms

Natural materials are often more efficient and tend to have a wider range and combination of properties than do present-day engineered materials. Biological materials are composed from a limited set of components, but are able to achieve great diversity in their properties. The variation in properties is largely due to the different arrangements of the materials components, which form unique structures. We believe that there are underlying structural design principles, relating material structure to material properties, that commonly appear in biological materials. Because nature itself achieves highly effective design solutions, the utilization of these natural design principles could similarly improve the effectiveness of engineered materials. Materials scientists need a way to abstract relevant structural design principles from the myriad of biological materials articles for the development of bioinspired materials. This research involves the development of a data mining tool that will quickly identify potential structural design principles of biological materials with respect to a chosen material property or combination of properties. This paper presents the first stage of this process: information retrieval. An algorithm is developed to extract structural design principles’ key terms and relevant passages for specified material properties from a corpus of materials journal articles. The development of this search tool is explained beginning with the determination of search term categories and appropriate search terms and continuing to the refinement of the program algorithm. An evaluation of the tool is also described comparing the program’s results to those of a manual search for the structure-property relationships. The program identified 98% of the manually found structural design principle key terms, although many unanticipated passages were returned as well. Finally, the future work needed to improve the program is presented.

Positive Emotion in Generalized Anxiety Disorder

2019 ◽  
pp. 297-311
Author(s):  
Ilana Seager ◽  
Douglas S. Mennin ◽  
Amelia Aldao
Keyword(s):  
Anxiety Disorder ◽  
Positive Affect ◽  
Generalized Anxiety Disorder ◽  
Positive Emotion ◽  
Behavioral Therapy ◽  
Generalized Anxiety ◽  
Emotional Dysfunction ◽  
Wide Range ◽  
Future Work

Generalized anxiety disorder (GAD) is a debilitating condition characterized by excessive, pervasive, uncontrollable, and paralyzing worries about a wide range of future situations. Individuals with this condition frequently find themselves stuck in worry and tension cycles in futile attempts at reducing uncertainty and increasing control. GAD has been associated with substantial impairments in functioning and reduced quality of life. GAD remains poorly understood, and the long-term efficacy and end-state functioning resulting from treatment are weaker compared to other anxiety disorders. Some treatments (e.g., emotion regulation therapy, acceptance-based behavioral therapy) have improved efficacy, partly by targeting emotional dysfunction. Basic psychopathology research has focused on identifying the role of negative affect in GAD, so little is known about how positive affect is experienced and regulated in this disorder. This is particularly important in light of the overlap of this condition with major depressive disorder, which is characterized by low or suppressed positive emotion. Developing such an understanding is essential to further improve the efficacy of emotion-based treatments. This chapter reviews current and future directions in the study of positive affect in GAD. The chapter reviews the nascent research on positive affect and GAD, then illustrates dimensions of future work.

scholarly journals TREASURE: Text Mining Algorithm Based On Affinity Analysis and Set Intersection to Find the Action of Tuberculosis Drugs against Other Pathogens

2021 ◽  
Vol 11 (15) ◽  
pp. 6834
Author(s):  
Pradeepa Sampath ◽  
Nithya Shree Sridhar ◽  
Vimal Shanmuganathan ◽  
Yangsun Lee
Keyword(s):  
Text Mining ◽  
Causes Of Death ◽  
Intersection Property ◽  
Research Papers ◽  
Bacterial Diseases ◽  
Mining Algorithm ◽  
Set Intersection ◽  
The World ◽  
Medical Researchers

Tuberculosis (TB) is one of the top causes of death in the world. Though TB is known as the world’s most infectious killer, it can be treated with a combination of TB drugs. Some of these drugs can be active against other infective agents, in addition to TB. We propose a framework called TREASURE (Text mining algoRithm basEd on Affinity analysis and Set intersection to find the action of tUberculosis dRugs against other pathogEns), which particularly focuses on the extraction of various drug–pathogen relationships in eight different TB drugs, namely pyrazinamide, moxifloxacin, ethambutol, isoniazid, rifampicin, linezolid, streptomycin and amikacin. More than 1500 research papers from PubMed are collected for each drug. The data collected for this purpose are first preprocessed, and various relation records are generated for each drug using affinity analysis. These records are then filtered based on the maximum co-occurrence value and set intersection property to obtain the required inferences. The inferences produced by this framework can help the medical researchers in finding cures for other bacterial diseases. Additionally, the analysis presented in this model can be utilized by the medical experts in their disease and drug experiments.

scholarly journals Perceptions and Attitudes towards Mules in a Group of Sodiers

Animals ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 1009
Author(s):  
Javiera Lagos ◽  
Manuel Rojas ◽  
Joao B. Rodrigues ◽  
Tamara Tadich
Keyword(s):  
Text Mining ◽  
Pain Perception ◽  
Health Needs ◽  
Emotional Needs ◽  
Mountainous Areas ◽  
Working Capacity ◽  
Perceptions And Attitudes ◽  
Wide Range ◽  
Positive Correlations ◽  
Word Attention

Mules are essential for pack work in mountainous areas, but there is a lack of research on this species. This study intends to assess the perceptions, attitudes, empathy and pain perception of soldiers about mules, to understand the type of human–mule relationship. For this, a survey was applied with closed-ended questions where the empathy and pain perception tools were included and later analyzed through correlations. Open-ended questions were analyzed through text mining. A total of 73 soldiers were surveyed. They had a wide range of ages and years of experience working with equids. Significant positive correlations were found between human empathy, animal empathy and pain perception. Soldiers show a preference for working with mules over donkeys and horses. Text mining analysis shows three clusters associated with the mules’ nutritional, environmental and health needs. In the same line, relevant relations were found for the word “attention” with “load”, “food”, and “harness”. When asked what mules signify for them, two clusters were found, associated with mules’ working capacity and their role in the army. Relevant relations were found between the terms “mountain”, “support”, and “logistics”, and also between “intelligent” and “noble”. To secure mules’ behavioral and emotional needs, future training strategies should include behavior and welfare concepts.

George Washington: a revolutionary approach to leadership

2018 ◽  
Vol 39 (8) ◽  
pp. 995-1009
Author(s):  
Todd C. Harris
Keyword(s):  
Leadership Competencies ◽  
Theory And Practice ◽  
Academic Disciplines ◽  
Leadership Traits ◽  
Journal Articles ◽  
George Washington ◽  
Leadership Theories ◽  
Content Type ◽  
Wide Range ◽  
Tools And Techniques

PurposeThe purpose of this paper is twofold: first, to examine George Washington’s approach to leadership through the lens of contemporary leadership theory and practice; and second, to help modern managers further reflect upon and develop their own leadership capabilities through a historiographic examination of Washington’s leadership traits and skills.Design/methodology/approachCombining three different academic disciplines, management, psychology and history, the author utilized a historiographic and interdisciplinary research methodology, conducting a detailed exploration of the life of George Washington through an examination of a wide range of original archival materials, books, journal articles and other sources.FindingsThe present analysis reveals that Washington demonstrated a variety of well-validated leadership competencies (e.g. emotional intelligence, resilience, integrity, etc.) that are largely consistent with leader-centered theoretical conceptions of leadership.Originality/valueThis is the first historiographic study of George Washington’s approach to leadership within the management literature. Additionally, through the development of a competency model, the study demonstrates how Washington employed tools and techniques from a host of modern leadership theories to achieve critically important results.

scholarly journals New Talent Signals: Shiny New Objects or a Brave New World?

2016 ◽  
Vol 9 (3) ◽  
pp. 621-640 ◽  
Author(s):  
Tomas Chamorro-Premuzic ◽  
Dave Winsborough ◽  
Ryne A. Sherman ◽  
Robert Hogan
Keyword(s):  
Work Performance ◽  
New World ◽  
Assessment Methods ◽  
Human Potential ◽  
Talent Identification ◽  
Digital Revolution ◽  
Wide Range ◽  
Brave New World ◽  
Future Work ◽  
Workplace Assessment

Almost 20 years after McKinsey introduced the idea of a war for talent, technology is disrupting the talent identification industry. From smartphone profiling apps to workplace big data, the digital revolution has produced a wide range of new tools for making quick and cheap inferences about human potential and predicting future work performance. However, academic industrial–organizational (I-O) psychologists appear to be mostly spectators. Indeed, there is little scientific research on innovative assessment methods, leaving human resources (HR) practitioners with no credible evidence to evaluate the utility of such tools. To this end, this article provides an overview of new talent identification tools, using traditional workplace assessment methods as the organizing framework for classifying and evaluating new tools, which are largely technologically enhanced versions of traditional methods. We highlight some opportunities and challenges for I-O psychology practitioners interested in exploring and improving these innovations.

Structural design principles for low hole effective mass s-orbital-based p-type oxides

2017 ◽  
Vol 5 (23) ◽  
pp. 5772-5779 ◽  
Author(s):  
Viet-Anh Ha ◽  
Francesco Ricci ◽  
Gian-Marco Rignanese ◽  
Geoffroy Hautier
Keyword(s):  
Effective Mass ◽  
First Principles ◽  
Structural Design ◽  
Carrier Mobility ◽  
Design Principles ◽  
Hole Effective Mass ◽  
P Type

We demonstrate through first principles computations how the metal–oxygen–metal angle directly drives the hole effective mass (thus the carrier mobility) in p-type s-orbital-based oxides.

Sign in / Sign up

Export Citation Format

Share Document