United We Stand - Divided We Fall : A Standard Model of Unit Cohesion

Research on unit cohesion has shown positive correlations between cohesion and valued outcomes such as strong performance, reduced stress, less indiscipline, and high re-enlistment intentions. However, the correlations have varied in strength and significance. The purpose of this study is to show that taking into consideration the multi-component nature of cohesion and relating the most applicable components to specific outcomes could resolve much of the inconsistency. Unit cohesion is understood as a process of social integration among members of a primary group with its leaders, and with the larger secondary groups of which they are a part. Correspondingly, included in the framework are four bonding components: horizontal (peer) and vertical (subordinate and leader) and organizational and institutional, respectively. The data were collected as part of a larger research project on cohesion, leadership, and personal adjustment to the military. In all, 1,534 conscripts responded to four questionnaires during their service in 2001-2002. In addition, sociometric questionnaires were given to 537 group members in 47 squads toward the end of their service. The results showed that platoons with strong primary-group cohesion differed from other platoons in terms of performance, training quality, secondary-group experiences, and attitudes toward refresher training. On the sociometric level it was found that soldiers who were chosen as friends by others were more likely to have higher expected performance, better performance ratings, more positive attitudes toward military service, higher levels of well-being during conscript service, and fewer exemptions from duty during it. On the group level, the selection of the respondents own group leader rather than naming a leader from outside (i.e., leader bonding) had a bearing not only on cohesion and performance, but also on the social, attitudinal, and behavioral criteria. Overall, the aim of the study was to contribute to the research on cohesion by introducing a model that takes into account the primary foci of bonding and their impact. The results imply that primary-group and secondary-group bonding processes are equally influential in explaining individual and group performance, whereas the secondary-group bonding components are far superior in explaining career intentions, personal growth, avoidance of duty, and attitudes toward refresher training and national defense. This should be considered in the planning and conducting of training. The main conclusion is that the different types of cohesion components have a unique, positive, significant, but varying impact on a wide range of criteria, confirming the need to match the components with the specific criteria.

Standard Gibbs' energies of formation of BaCuO2, Y2Cu2O5 and Y2BaCuO5

The Gibbs' energies of formation of BaCuO2, Y2Cu2O5 and Y2BaCuO5 from component oxides have been measured using solid state galvanic cells incorporating CaF2 as the solid electrolyte under pure oxygen at a pressure of 1.01 x 10(5) Pa Because the superconducting compound YBa2Cu3O7-delta coexists with any two of the phases CuO, BaCuO2 and Y2BaCuO5, the data on BaCuO2 and Y2BaCuO5 obtained in this study provide the basis for the evaluation of the Gibbs' energy of formation of the 1-2-3 compound at high temperatures.

A standard reference frame for the description of Nucleic Acid Base-Pair Geometry

A common point of reference is needed to describe the three-dimensional arrangements of bases and base-pairs in nucleic acid structures. The different standards used in computer programs created for this purpose give rise to con¯icting interpretations of the same structure.1 For example, parts of a structure that appear ``normal'' according to one computational scheme may be highly unusual according to another and vice versa. It is thus dif®cult to carry out comprehensive comparisons of nucleic acid structures and to pinpoint unique conformational features in individual structures

Algorithms for Exact Structure Discovery in Bayesian Networks

Bayesian networks are compact, flexible, and interpretable representations of a joint distribution. When the network structure is unknown but there are observational data at hand, one can try to learn the network structure. This is called structure discovery. This thesis contributes to two areas of structure discovery in Bayesian networks: space--time tradeoffs and learning ancestor relations. The fastest exact algorithms for structure discovery in Bayesian networks are based on dynamic programming and use excessive amounts of space. Motivated by the space usage, several schemes for trading space against time are presented. These schemes are presented in a general setting for a class of computational problems called permutation problems; structure discovery in Bayesian networks is seen as a challenging variant of the permutation problems. The main contribution in the area of the space--time tradeoffs is the partial order approach, in which the standard dynamic programming algorithm is extended to run over partial orders. In particular, a certain family of partial orders called parallel bucket orders is considered. A partial order scheme that provably yields an optimal space--time tradeoff within parallel bucket orders is presented. Also practical issues concerning parallel bucket orders are discussed. Learning ancestor relations, that is, directed paths between nodes, is motivated by the need for robust summaries of the network structures when there are unobserved nodes at work. Ancestor relations are nonmodular features and hence learning them is more difficult than modular features. A dynamic programming algorithm is presented for computing posterior probabilities of ancestor relations exactly. Empirical tests suggest that ancestor relations can be learned from observational data almost as accurately as arcs even in the presence of unobserved nodes.

A critical assessment of the standard molar gibbs free energy of formation of NiWO4

Three independent studies have been reported on the free energy of formation of NiWO4. Results of these measurements are analyzed by the �third-law� method, using thermal functions for NiWO4 derived from both low and high temperature heat capacity measurements. Values for the standard molar enthalpy of formation of NiWO4 at 298·15 K obtained from �third-law� analysis are compared with direct calorimetric determinations. Only one set of free energy measurements is found to be compatible with calorimetric enthalpies of formation. The selected value for ?f H m 0 (NiWO4, cr, 298·15 K) is the average of the three calorimetric measurements, using both high temperature solution and combustion techniques, and the compatible free energy determination. A new set of evaluated data for NiWO4 is presented.

On the achievable rates of sources having a group alphabet in a distributed source coding setting

We consider the problem of compression via homomorphic encoding of a source having a group alphabet. This is motivated by the problem of distributed function computation, where it is known that if one is only interested in computing a function of several sources, then one can at times improve upon the compression rate required by the Slepian-Wolf bound. The functions of interest are those which could be represented by the binary operation in the group. We first consider the case when the source alphabet is the cyclic Abelian group, Zpr. In this scenario, we show that the set of achievable rates provided by Krithivasan and Pradhan [1], is indeed the best possible. In addition to that, we provide a simpler proof of their achievability result. In the case of a general Abelian group, an improved achievable rate region is presented than what was obtained by Krithivasan and Pradhan. We then consider the case when the source alphabet is a non-Abelian group. We show that if all the source symbols have non-zero probability and the center of the group is trivial, then it is impossible to compress such a source if one employs a homomorphic encoder. Finally, we present certain non-homomorphic encoders, which also are suitable in the context of function computation over non-Abelian group sources and provide rate regions achieved by these encoders.

Standard Gibbs energy of formation of Pb2Ru2O6.5

Lead ruthenate is used as a bifunctional electrocatalyst for both oxygen evolution and reduction and as a conducting component in thick-film resistors. It also has potential applications in supercapacitors and solid oxide fuel cells. However, thermodynamic properties of the compound have not been reported in the literature. The standard Gibbs energy of formation has now been determined in the temperature range from 873 to 1123 K using a solid-state cell incorporating yttria-stabilized zirconia (YSZ) as the electrolyte, a mixture of PbO + Pb2Ru2O6.5 + Ru as the measuring electrode, and Ru + RuO2 as the reference. The design of the measuring electrode is based on a study of phase relations in the ternary system Pb–Ru–O at 1123 K. For the reaction,S0884291400095625_eqnU1 the standard enthalpy of formation and standard entropy at 298.15 K are estimated from the high-temperature measurements. An oxygen potential diagram for the system Pb–Ru–O is composed based on data obtained in this study and auxiliary information from the literature

On the Compressibility of non-Abelian-Group Sources in a Distributed Source Coding Setting

We consider the problem of compression of a non-Abelian source.This is motivated by the problem of distributed function computation,where it is known that if one is only interested in computing a function of several sources, then one can often improve upon the compression rate required by the Slepian-Wolf bound. Let G be a non-Abelian group having center Z(G). We show here that it is impossible to compress a source with symbols drawn from G when Z(G) is trivial if one employs a homomorphic encoder and a typical-set decoder.We provide achievable upper bounds on the minimum rate required to compress a non-Abelian group with non-trivial center. Also, in a two source setting, we provide achievable upper bounds for compression of any non-Abelian group, using a non-homomorphic encoder.

Voltage and Temperature Scalable Standard Cell Leakage Models Based on Stacks for Statistical Leakage Characterization

With extensive use of dynamic voltage scaling (DVS) there is increasing need for voltage scalable models. Similarly, leakage being very sensitive to temperature motivates the need for a temperature scalable model as well. We characterize standard cell libraries for statistical leakage analysis based on models for transistor stacks. Modeling stacks has the advantage of using a single model across many gates there by reducing the number of models that need to be characterized. Our experiments on 15 different gates show that we needed only 23 models to predict the leakage across 126 input vector combinations. We investigate the use of neural networks for the combined PVT model, for the stacks, which can capture the effect of inter die, intra gate variations, supply voltage(0.6-1.2 V) and temperature (0 - 100degC) on leakage. Results show that neural network based stack models can predict the PDF of leakage current across supply voltage and temperature accurately with the average error in mean being less than 2% and that in standard deviation being less than 5% across a range of voltage, temperature.