Whence chemistry?

Along with exploring some of the necessary conditions for the chemistry of our world given what we know about quantum mechanics, I will also discuss a different reductionist challenge than is usually considered in debates on the relationship of chemistry to physics. Contrary to popular belief, classical physics does not have a reductive relationship to quantum mechanics and some of the reasons why reduction fails between classical and quantum physics are the same as for why reduction fails between chemistry and quantum physics. However, a neoreductionist can accept that classical physics has some amount of autonomy from quantum mechanics, but still try to maintain that classical+quantum physics taken as a whole reduces chemistry to physics. I will explore some of the obstacles lying in the neoreductionist's path with respect to quantum chemistry and thereby hope to shed more light on the conditions necessary for the chemistry of our world.     

Lucifensin, the long-sought antimicrobial factor of medicinal maggots of the blowfly Lucilia sericata

A novel homologue of insect defensin designated lucifensin (Lucilia defensin) was purified from the extracts of various tissues (gut, salivary glands, fat body, haemolymph) of green bottle fly (Lucilia sericata) larvae and from their excretions/secretions. The primary sequence of this peptide of 40 residues and three intramolecular disulfide bridges was determined by ESI-QTOF mass spectrometry and Edman degradation and is very similar to that of sapecin and other dipteran defensins. We assume that lucifensin is the key antimicrobial component that protects the maggots when they are exposed to the highly infectious environment of a wound during the medicinal process known as maggot therapy. We also believe that lucifensin is that long-sought larger molecular weight antimicrobial factor of the Lucilia sericata excretions/secretions believed to be effective against pathogenic elements of the wound microbial flora.     

Use of Geochemical and Geophysical Techniques to Characterize and Prospect for Geothermal Resources and Hydrothermal Ore Deposits

Fluid-rock interactions alter the geochemical, isotopic, petrographic and physical character of host rocks, producing a permanent record of hydrothermal activity. Maps of altered rock properties show r...     

Species of Eimeria from the thirteen-lined ground squirrel, Spermophilus tridecemlineatus , from Wyoming

Five species of the coccidian genus Eimeria ( E. beecheyi [prevalence = 17.9%], E. callospermophili-morainensis [28.6%], E. larimerensis [16.1%], and E. bilamellata [3.6%]) were recovered from 56, 13-lined ground squirrels ( Spermophilus tridicemlineatus ) collected from two sites in eastern Wyoming. Two squirrels from one site were also passing an unidentified polysporocystic coccidian. Infected squirrels were found to harbor from one to three species simultaneously. Previously these same eimerian species were found infecting sympatric populations of Wyoming ground squirrels. ( Spermophilus elegans ) and white-tailed prairie dogs ( Cynomys leacurus ) at one of the sites; it is suggested that the exchange of these generalist parasite species among co-occurring sciurid hosts contributes to the consistent prevalence levels reported in Wyoming ground squirrels.     

Being Post-Positivist . . . or Just Talking About it?

Hans Ruin and Patrick Heelan join me in celebrating the rise of post-positivist and phenomenological approaches to scientific and technological practice. Yet as they both know, I am also concerned that the very presence of all the new accounts which give voice to this trend may tempt us into concluding prematurely that the traditional understanding of science and technology has already been displaced. With especially Ruin’s encouragement, I expand my original discussion of this concern by explaining why I agree with him about the ontologically mistaken suppositions that one might become post-positivistic by doing philosophy “meta-philosophically,” or become phenomenological by making “life” more basic that “nature.”     

A NESTED PARTITIONS FRAMEWORK FOR SOLVING LARGE-SCALE MULTICOMMODITY FACILITY LOCATION PROBLEMS

Large-scale multicommodity facility location problems are generally intractable with respect to standard mixed-integer programming (MIP) tools such as the direct application of general-purpose Branch & Cut (BC) commercial solvers i.e. CPLEX. In this paper, the authors investigate a nested partitions (NP) framework that combines meta-heuristics with MIP tools (including branch-and-cut). We also consider a variety of alternative formulations and decomposition methods for this problem class. Our results show that our NP framework is capable of efficiently producing very high quality solutions to multicommodity facility location problems. For large-scale problems in this class, this approach is significantly faster and generates better feasible solutions than either CPLEX (applied directly to the given MIP) or the iterative Lagrangian-based methods that have generally been regarded as the most effective structure-based techniques for optimization of these problems. We also briefly discuss some other large-scale MIP problem classes for which this approach is expected to be very effective. This work is supported partly by the National Science Foundation under grant DMI-0100220, DMI-0217924, by the Air Force of Scientific Research under grant F49620-01-1-0222, by Rockwell Automation, and by John Deere Horicon Works. Leyuan Shi is a Professor of the Department of Industrial Engineering at University of Wisconsin-Madison. She received her Ph.D. in Applied Mathematics from Harvard University in 1992, her M.S. in Engineering from Harvard University in 1990, her M.S. in Applied Mathematics from Tsinghua University in 1985, and her B.S. in Mathematics from Nanjing Normal University in 1982. Dr. Shi has been involved in undergraduate and graduate teaching, as well as research and professional service. Dr. Shi’s research is devoted to the theory and applications of large-scale optimization algorithms, discrete event simulation and modeling and analysis of discrete dynamic systems. She has published many papers in these areas. Her work has appeared in Discrete Event Dynamic Systems, Operations Research, Management Science, IEEE Trans., and, IIE Trans. She is currently a member of the editorial board for Journal of Manufacturing & Service Operations Management, is an Associate Editor of Journal of Discrete Event Dynamic Systems, and an Associate Editor of INFORMS Journal on Computing. Dr. Shi is a member of IEEE and INFORMS. Robert R. Meyer received a B.S. in Mathematics from Caltech and an M.S. and a Ph.D. in Computer Sciences from the University of Wisconsin-Madison. He is currently Professor of Computer Sciences at the University of Wisconsin-Madison, where he has been on the faculty since 1973. He has co-edited six volumes of optimization conference proceedings and written more than 80 articles focusing on areas such as nonlinear network optimization, parallel decomposition algorithms for large-scale optimization, genetic algorithms, and theory and applications of discrete optimization. Mehmet Bozbay is a research assistant in the Department of Industrial Engineering at University of Wisconsin-Madison. He is currently working towards his Ph.D. degree in Industrial Engineering. He received M.S. degrees in Industrial Engineering and Computer Sciences from University of Wisconsin-Madison, and a B.S. degree in Mathematics from Beloit College. He has been dealing with real-life supply chain optimization problems for the last 4 years. He is a member of INFORMS. Andrew J. Miller is an Assistant Professor of the Department of Industrial Engineering at the University of Wisconsin—Madison. He received his Ph.D. in Industrial Engineering from the Georgia Institute of Technology in 1999, his M.S. in Operations Research from the Georgia Institute of Technology in 1996, and his B.S. in Mathematics from Furman University in 1994. Dr. Miller has been involved in research, undergraduate and graduate teaching, and professional service, as well as in some software prototyping and development. Dr. Miller’s research focuses on theoretical and computational aspects of mixed integer programming, and on its application to areas in production planning, supply chain design, and other fields. He has published several papers in these areas, including articles in Mathematical Programming, Operations Research, and European Journal of Operations Research. He has refereed numerous articles for the journals mentioned above, as well as for Management Science, Annals of Operations Research, and others. Dr. Miller is a member of INFORMS and of the Mathematical Programming Society.