Emotion and performance

The study of emotions in organizational settings has attained considerable prominence in recent years, but I critical issue remains unresolved. This is the relationship between emotion and performance. in this special issue, 5 articles address this topic from a variety of viewpoints. Two are theoretical essays that deal, respectively, with emotion and creativity and the relationships between individual and team performance. Three are empirical studies that canvass the emotion-performance nexus across levels of analysis: within person, between persons, and in groups. Between them, the 5 articles present a strong case for the nexus of emotions and performance, but, more important, they provide a platform for potentially fruitful future research in this burgeoning area.

Muscle metabolites and performance during high-intensity, intermittent exercise

Six men were studied during four 30-s all-out exercise bouts on an air-braked cycle ergometer. The first three exercise bouts were separated by 4 min of passive recovery; after the third bout, subjects rested for 4 min, exercised for 30 min at 30-35% peak O-2 consumption, and rested for a further 60 min before completing the fourth exercise bout. Peak power and total work were reduced (P < 0.05) during bout 3 [765 +/- 60 (SE) W; 15.8 +/- 1.0 kJ] compared with bout 1 (1,168 +/- 55 mT, 23.8 +/- 1.2 kJ), but no difference in exercise performance was observed between bouts 1 and 4 (1,094 +/- 64 W, 23.2 +/- 1.4 kJ). Before bout 3, muscle ATP, creatine phosphate (CP), glycogen, pH, and sarcoplasmic reticulum (SR) Ca2+ uptake were reduced, while muscle lactate and inosine 5'-monophosphate were increased. Muscle ATP and glycogen before bout 4 remained lower than values before bout I (P < 0.05), but there were no differences in muscle inosine 5'-monophosphate, lactate, pH, and SR Ca2+ uptake. Muscle CP levels before bout 4 had increased above resting levels. Consistent with the decline in muscle ATP were increases in hypoxanthine and inosine before bouts 3 and 4. The decline in exercise performance does not appear to be related to a reduction in muscle glycogen. Instead, it may be caused by reduced CP availability, increased H+ concentration, impairment in SR function, or some other fatigue-inducing agent.

Novel composite membranes for gas separation: Preparation and performance

High performance composite membranes based on molecular sieving silica (MSS) were synthesized using sols containing silicon co-polymers (methyltriethoxysilane and tetraethylorthosilicate). Alpha alumina supports were treated with hydrochloric acid prior to sol deposition. Permselectivity of CO2 over CH4 as high as 16.68 was achieved whilst permeability of CO2 up to 36.7 GPU (10(-6) cm(3) (STP) cm(-2) . s(-1) . cm Hg-1) was measured. The best membrane's permeability was finger printed during various stages of the synthesis process showing an increase in CO2/CH4 permselectivity by over 25 times from initial support condition (no membrane film) to the completion of pore structure tailoring. Transport measurement results indicate that the membrane pretreated with HCl has highest permselectivity and permeation rate. In particular, there is a definite cut-off pore size between 3.3 and 3.4 angstroms which is just below the kinetic diameters of Ar and CH4. This demonstrates that the mechanism for the separation in the prepared composite membrane is molecular sieving (activated diffusion), rather than Knudsen diffusion.

Computational chemistry on Fujitsu vector-parallel processors: Development and performance of applications software

In this and a preceding paper, we provide an introduction to the Fujitsu VPP range of vector-parallel supercomputers and to some of the computational chemistry software available for the VPP. Here, we consider the implementation and performance of seven popular chemistry application packages. The codes discussed range from classical molecular dynamics to semiempirical and ab initio quantum chemistry. All have evolved from sequential codes, and have typically been parallelised using a replicated data approach. As such they are well suited to the large-memory/fast-processor architecture of the VPP. For one code, CASTEP, a distributed-memory data-driven parallelisation scheme is presented. (C) 2000 Published by Elsevier Science B.V. All rights reserved.

Expectation Propagation with Factorizing Distributions: A Gaussian Approximation and Performance Results for Simple Models

We discuss the expectation propagation (EP) algorithm for approximate Bayesian inference using a factorizing posterior approximation. For neural network models, we use a central limit theorem argument to make EP tractable when the number of parameters is large. For two types of models, we show that EP can achieve optimal generalization performance when data are drawn from a simple distribution.

Aesthetic value: between universality and exclusivity

This study brings a reflection on aesthetic values, trying to consider connections between universality, social exclusion and contemporary violence.

Prognostic value of NDRG1 and SPARC protein expression in breast cancer patients

An increasing number of studies have shown altered expression of secreted protein acidic and rich in cysteine (SPARC) and N-myc down-regulated gene (NDRG1) in several malignancies, including breast carcinoma; however, the role of these potential biomarkers in tumor development and progression is controversial. In this study, NDRG1 and SPARC protein expression was evaluated by immunohistochemistry on tissue microarrays containing breast tumor specimens from patients with 10 years of follow-up. NDRG1 and SPARC protein expression was determined in 596 patients along with other prognostic markers, such as ER, PR, and HER2. The status of NDRG1 and SPARC protein expression was correlated with prognostic variables and patient clinical outcome. Immunostaining revealed that 272 of the 596 cases (45.6%) were positive for NDRG1 and 431 (72.3%) were positive for SPARC. Statistically significant differences were found between the presence of SPARC and NDRG1 protein expression and standard clinicopathological variables. Kaplan-Meier analysis showed that NDRG1 positivity was directly associated with shorter disease-free survival (DFS, P < 0.001) and overall survival (OS, P < 0.001). In contrast, patients expressing low levels of SPARC protein had worse DFS (P = 0.001) and OS (P = 0.001) compared to those expressing high levels. Combined analysis of the two markers indicated that DFS (P < 0.001) and OS rates (P < 0.001) were lowest for patients with NDRG1-positive and SPARC-negative tumors. Furthermore, NDRG1 over-expression and SPARC down-regulation correlated with poor prognosis in patients with luminal A or triple-negative subtype breast cancer. On multivariate analysis using a Cox proportional hazards model, NDRG1 and SPARC protein expression were independent prognostic factors for both DFS and OS of breast cancer patients. These data indicate that NDRG1 over-expression and SPARC down-regulation could play important roles in breast cancer progression and serve as useful biomarkers to better define breast cancer prognosis.