Success In Technology Organizations

In today’s economic environment, it is advantageous for technology organizations to be cognizant of prevalent influences on success and failure and to incorporate this knowledge into their business and innovation strategies. Technology organizations were defined within this research as those in the business of created competence which is expressed in terms of entities consisting of devices, procedures, and acquired human skills (Clarke, 2005). Although, no organization contains the ideal mix of culture and ideological emphases, some have amassed impressive track records of great success. A literature review was used to identify factors relevant within similar contexts such as influences on creativity, innovation, Research and Development (R&D), etcetera. The salient factors identified within the literature review were hypothesized as being very important to great success within technology organizations. A conceptual model was created that visually illustrated the interactions of those factors and their influence on technology organization success which was defined as average annual revenue growth and direct new job creation. An internet questionnaire was utilized to test the hypotheses among 15 very successful technology organizations according to their respective Chief Technology Officers (CTOs) or equivalents. These companies were randomly chosen from a population of the technology organizations included in Inc. Magazine’s Inc. 5000, a list of the 5000 fastest growing companies in America. The questionnaire primarily consisted of Likert questions designed to test the hypotheses. The dependent variable in the statistical analyses, technology organization success, iv was ranked according to average annual revenue growth and direct new job creation relative to the other organizations within the sample set. The top category in typical questionnaire Likert questions included the adjective “very” that was interpreted to imply that the particular factor was exactly or precisely essential to affect that level of success, this in the collective opinion of the CTOs. Not meeting the threshold of exactly or precisely was interpreted that the factor may not be essential to that level of success. Rejection of the respective null hypotheses and subsequent acceptance of the alternative hypotheses were interpreted as evidence that particular factors were essential to great levels of technology organization success. And, the conceptual model was updated accordingly. Acceptance of null hypotheses demonstrated that the factors may not be essential; therefore, they were excluded from further discussion and the model. Seventeen key factors and/or categories were identified according to the Chief Technology Officers within the population of very successful technology organizations as having substantial influence on the success of those organizations. Recommendations were made to technology organizations aspiring towards prolific levels of success. As a check, three open-ended questions were included and used to verify that no consensus crucial elements were omitted within the Likert question section of the questionnaire. There were no consensus factors identified within those open-ended questions

Nonholonomic Hamiltonian method for reacting molecular dynamics

Macroscale, mesoscale, and ab initio models of reacting shock physics are based, in their most general forms, on rate law descriptions of the chemical processes of interest. Reacting molecular dynamics simulations, by contrast, typically employ potential functions (holonomic Hamiltonian methods) to model chemical reactions. An alternative approach to reacting molecular dynamics models the bonding-debonding process using a rate law, resulting in a nonholonomic Hamiltonian formulation. In previous work at macro and meso scales, discrete nonholonomic Hamiltonian methods have been applied to develop very general models of shock impact and fragmentation process. In this dissertation a similar nonholonomic modeling methodology is used, at the molecular scale, to explicitly model transient chemical processes. Note that the chemistry problem is much more difficult, since both dissociation (fragmentation) and the formation of new molecules must be modeled. The result is the first general reacting molecular dynamics formulation which explicitly models chemical kinetics. Simulation results using this method show good agreement with experiment, for energy release and detonation products in two widely used explosives (HMX and RDX). The reacting molecular dynamics simulation results are used to propose reaction mechanisms and species concentration based kinetics models suitable for use in meso and macro scale shock to detonation simulations. Computational modeling of energetic materials is capable of estimating molecular behavior under conditions not amenable to direct experimental measurement. Further development of RMD methods may help to provide a better understanding of energetic material behavior. This in turn may help to develop improved insensitive high energy density materials.Mechanical Engineerin

Circadian Disruption and Metabolic Disease: Findings from Animal Models

Social opportunities and work demands have caused humans to become increasingly active during the late evening hours, leading to a shift from the predominantly diurnal lifestyle of our ancestors to a more nocturnal one. This voluntarily decision to stay awake long into the evening hours leads to circadian disruption at the system, tissue, and cellular levels. These derangements are in turn associated with clinical impairments in metabolic processes and physiology. The use of animal models for circadian disruption provides an important opportunity to determine mechanisms by which disorganization in the circadian system can lead to metabolic dysfunction in response to genetic, environmental, and behavioral perturbations. Here we review recent key animal studies involving circadian disruption and discuss the possible translational implications of these studies for human health and particularly for the development of metabolic disease

The Meter of Metabolism

The circadian system orchestrates the temporal organization of many aspects of physiology, including metabolism, in synchrony with the 24 hr rotation of the Earth. Like the metabolic system, the circadian system is a complex feedback network that involves interactions between the central nervous system and peripheral tissues. Emerging evidence suggests that circadian regulation is intimately linked to metabolic homeostasis and that dysregulation of circadian rhythms can contribute to disease. Conversely, metabolic signals also feed back into the circadian system, modulating circadian gene expression and behavior. Here, we review the relationship between the circadian and metabolic systems and the implications for cardiovascular disease, obesity, and diabetes

Knockdown of the C. elegans kinome identifies kinases required for normal protein homeostasis, mitochondrial network structure, and sarcomere structure in muscle

Kinases are important signalling molecules for modulating cellular processes and major targets of drug discovery programs. However, functional information for roughly half the human kinome is lacking. We conducted three kinome wide, >90%, RNAi screens and epistasis testing of some identified kinases against known intramuscular signalling systems to increase the functional annotation of the C. elegans kinome and expand our understanding of kinome influence upon muscle protein degradation

Bremsstrahlung from a microscopic model of relativistic heavy ion collisions

We compute bremsstrahlung arising from the acceleration of individual charged baryons and mesons during the time evolution of high-energy Au+Au collisions at the Relativistic Heavy Ion Collider using a microscopic transport model. We elucidate the connection between bremsstrahlung and charge stop- ping by colliding artificial pure proton on pure neutron nuclei. From the inten- sity of low energy bremsstrahlung, the time scale and the degree of stopping could be accurately extracted without measuring any hadronic observables. PACS: 25.75.-q, 13.85.Q

Mycielski-Regular Measures

Let μ be a Radon probability measure on M, the d-dimensional Real Euclidean space (where d is a positive integer), and f a measurable function. Let P be the space of sequences whose coordinates are elements in M. Then, for any point x in M, define a function ƒn on M and P that looks at the first n terms of an element of P and evaluates f at the first of those n terms that minimizes the distance to x in M. The measures for which such sequences converge in measure to f for almost every sequence are called Mycielski-regular. We show that the self-similar measure generated by a finite family of contracting similitudes and which up to a constant is the Hausdorff measure in its dimension on an invariant set C is Mycielski-regular