Clemson University

About: Clemson University is a education organization based out in Clemson, South Carolina, United States. It is known for research contribution in the topics: Population & Control theory. The organization has 20556 authors who have published 42518 publications receiving 1170779 citations. The organization is also known as: Clemson Agricultural College of South Carolina.

A mathematical model for the continuous culture of microorganisms utilizing inhibitory substrates

Abstract: A mathematical model is presented for both batch and continuous cultures of microorganisms utilizing inhibitory substrates. The key feature of the model is the use of a inhibition function to relate substrate concentration and specific growth rate. Simulation studies show that the primary result of inhibition by substrate in a batch culture is an increase in the lag time whereas in continuous culture inhibition by substrate may result in process instability. The model should be of value in investigations of the stability of biological processes used for the treatment of certain industrial wastes such as those containing phenols, thiocyanates, nitrates, ammonia, volatile acids, etc., which are known to be inhibitory to many of the organisms metabolizing them.

How Important are Job Attitudes? Meta-Analytic Comparisons of Integrative Behavioral Outcomes and Time Sequences

Abstract: Drawing on the compatibility principle in attitude theory, we propose that overall job attitude (job satisfaction and organizational commitment) provides increasingly powerful prediction of more integrative behavioral criteria (focal performance, contextual performance, lateness, absence, and turnover combined). The principle was sustained by a combination of meta-analysis and structural equations showing better fit of unified versus diversified models of meta-analytic correlations between those criteria. Overall job attitude strongly predicted a higher-order behavioral construct, defined as desirable contributions made to one’s work role (r .59). Time-lagged data also supported this unified, attitude-engagement model.

Design for additive manufacturing: trends, opportunities, considerations, and constraints

Abstract: The past few decades have seen substantial growth in Additive Manufacturing (AM) technologies. However, this growth has mainly been process-driven. The evolution of engineering design to take advantage of the possibilities afforded by AM and to manage the constraints associated with the technology has lagged behind. This paper presents the major opportunities, constraints, and economic considerations for Design for Additive Manufacturing. It explores issues related to design and redesign for direct and indirect AM production. It also highlights key industrial applications, outlines future challenges, and identifies promising directions for research and the exploitation of AM's full potential in industry.

A new method to measure the semantic similarity of GO terms

Abstract: Motivation: Although controlled biochemical or biological vocabularies, such as Gene Ontology (GO) ( http://www.geneontology.org), address the need for consistent descriptions of genes in different data sources, there is still no effective method to determine the functional similarities of genes based on gene annotation information from heterogeneous data sources. Results: To address this critical need, we proposed a novel method to encode a GO term's semantics (biological meanings) into a numeric value by aggregating the semantic contributions of their ancestor terms (including this specific term) in the GO graph and, in turn, designed an algorithm to measure the semantic similarity of GO terms. Based on the semantic similarities of GO terms used for gene annotation, we designed a new algorithm to measure the functional similarity of genes. The results of using our algorithm to measure the functional similarities of genes in pathways retrieved from the saccharomyces genome database (SGD), and the outcomes of clustering these genes based on the similarity values obtained by our algorithm are shown to be consistent with human perspectives. Furthermore, we developed a set of online tools for gene similarity measurement and knowledge discovery. Availability: The online tools are available at: http://bioinformatics.clemson.edu/G-SESAME Contact: jzwang@cs.clemson.edu Supplementary information: http://bioinformatics.clemson.edu/Publication/Supplement/gsp.htm

Self-healing polymeric materials

Abstract: Inspired by nature, self-healing materials represent the forefront of recent developments in materials chemistry and engineering. This review outlines the recent advances in the field of self-healing polymers. The first part discusses thermodynamic requirements for self-healing networks in the context of conformation changes that contribute to the Gibbs free energy. The chain flexibility significantly contributes to the entropy changes, whereas the heat of reaction and the external energy input are the main contributors to enthalpy changes. The second part focuses on chemical reactions that lead to self-healing, and the primary classes are the covalent bonding, supramolecular assemblies, ionic interactions, chemo-mechanical self-healing, and shape memory polymers. The third part outlines recent advances using encapsulation, remote self-healing and the role of shape memory polymers. Recent developments in the field of self-healing polymers undeniably indicate that the main challenge will be the designing of high glass transition (Tg) functional materials, which also exhibit stimuli-responsive attributes. Build-in controllable hierarchical heterogeneousness at various length scales capable of remote self-healing by physical and chemical responses will be essential in designing future materials of the 21st century.