University of Memphis

About: University of Memphis is a education organization based out in Memphis, Tennessee, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 7710 authors who have published 20082 publications receiving 611618 citations. The organization is also known as: U of M.

Artificial immune systems in industrial applications

Abstract: Artificial immune system (AIS) is a new intelligent problem-solving technique that is being used in some industrial applications. This paper presents an immunity-based algorithm for tool breakage detection. The method is inspired by the negative-selection mechanism of the immune system, which is able to discriminate between the self (body elements) and the nonself (foreign pathogens). However, in our industrial application, the self is defined to be normal cutting operations and the nonself is any deviation beyond allowable variations of the cutting force. The proposed algorithm is illustrated with a simulation study of milling operations. The performance of the algorithm in detecting the occurrence of tool breakage is reported. The results show that the negative-selection algorithm detected tool breakage in all test cases.

Overcoming the loss of blue sensitivity through opsin duplication in the largest animal group, beetles.

Abstract: Opsin proteins are fundamental components of animal vision whose structure largely determines the sensitivity of visual pigments to different wavelengths of light. Surprisingly little is known about opsin evolution in beetles, even though they are the most species rich animal group on Earth and exhibit considerable variation in visual system sensitivities. We reveal the patterns of opsin evolution across 62 beetle species and relatives. Our results show that the major insect opsin class (SW) that typically confers sensitivity to “blue” wavelengths was lost ~300 million years ago, before the origin of modern beetles. We propose that UV and LW opsin gene duplications have restored the potential for trichromacy (three separate channels for colour vision) in beetles up to 12 times and more specifically, duplications within the UV opsin class have likely led to the restoration of “blue” sensitivity up to 10 times. This finding reveals unexpected plasticity within the insect visual system and highlights its remarkable ability to evolve and adapt to the available light and visual cues present in the environment.

Symbols and Embodiment: Debates on Meaning and Cognition

Abstract: 1. Framing the debate 2. The limits of covariation 3. Body and symbol in AutoTutor: conversations that are responsive to the learners' cognitive and emotional states 4. Symbolism, embodied cognition and the broader debate 5. What brain imaging can tell us about embodied meaning 6. Grounding language in the brain 7. Symbols and embodiment from the perspective of a neural modeler 8. Symbol systems and perceptual representations 9. Experiential traces and mental simulations in language comprehension 10. Defining embodiment in understanding 11. A mechanistic model of three facets of meaning 12. The symbol grounding problem has been solved. So what's next? 13. Language and simulation in conceptual processing 14. Levels of embodied meaning: from pointing to counterfactuals 15. Language comprehension is both embodied and symbolic! 16. A well-grounded education: the role of perception in science and mathematics 17. Mending or abandoning cognitivism 18. An embodied cognition perspective on symbols, gesture and grounding instruction 19. Reflecting on the debate

High-throughput behavioral phenotyping in the expanded panel of BXD recombinant inbred strains

Abstract: Genetic reference populations, particularly the BXD recombinant inbred (BXD RI) strains derived from C57BL/6J and DBA/2J mice, are a valuable resource for the discovery of the bio-molecular substrates and genetic drivers responsible for trait variation and covariation. This approach can be profitably applied in the analysis of susceptibility and mechanisms of drug and alcohol use disorders for which many predisposing behaviors may predict the occurrence and manifestation of increased preference for these substances. Many of these traits are modeled by common mouse behavioral assays, facilitating the detection of patterns and sources of genetic coregulation of predisposing phenotypes and substance consumption. Members of the Tennessee Mouse Genome Consortium (TMGC) have obtained phenotype data from over 250 measures related to multiple behavioral assays across several batteries: response to, and withdrawal from cocaine, 3,4-methylenedioxymethamphetamine; “ecstasy” (MDMA), morphine and alcohol; novelty seeking; behavioral despair and related neurological phenomena; pain sensitivity; stress sensitivity; anxiety; hyperactivity and sleep/wake cycles. All traits have been measured in both sexes in approximately 70 strains of the recently expanded panel of BXD RI strains. Sex differences and heritability estimates were obtained for each trait, and a comparison of early (N = 32) and recent (N = 37) BXD RI lines was performed. Primary data are publicly available for heritability, sex difference and genetic analyses using the MouseTrack database, and are also available in GeneNetwork.org for quantitative trait locus (QTL) detection and genetic analysis of gene expression. Together with the results of related studies, these data form a public resource for integrative systems genetic analysis of neurobehavioral traits.

Self-regulated Learning with MetaTutor: Advancing the Science of Learning with MetaCognitive Tools

Abstract: The key to understanding complex learning with advanced learning technologies (e.g., hypermedia) lies in our ability to comprehend the temporal deployment of students’ cognitive, metacognitive, motivational, and affective processes. Our chapter will focus on critically analyzing the use of mixed-method approaches to analyze the complex nature of self-regulated learning (SRL) during hypermedia learning. We will use examples from our own research (e.g., Azevedo 2008, Recent innovations in educational technology that facilitate student learning (pp. 127–156); Azevedo & Witherspoon, in press, Handbook of metacognition in education) and that of others (e.g., Biswas et al., 2005; Schwartz et al., in press; Winne & Nesbitt, in press, Handbook of metacognition in education) to present and discuss the strengths and weaknesses in using mixed methods to capture, model, trace, and infer the unfolding SRL processes during learning with nonlinear, multirepresentational computerized environments. The chapter will focus on the methods, and quantitative and qualitative analyses used to converge product data (e.g., learning outcomes), process data (e.g., think-aloud data), and log-file data collected during learning, develop coding schemes to categorize and infer the deployment of SRL processes, and the use of computational tools to examine learners’ behaviors and navigation paths. Lastly, we will present a theoretical model that integrates the various topics presented in this chapter that will guide future research and educational practices for fostering students’ SRL with hypermedia environments.