Social Exchange at Work and Emotional Exhaustion: The Role of Personality

Unbalanced social-exchange processes at work have been linked to emotional exhaustion. In addition to organizational factors, individual differences are important determinants of reciprocity perceptions. This study explored whether broad and narrow personality traits were associated with perceived lack of reciprocity (organizational and interpersonal levels), and whether personality moderated the relationship between reciprocity and emotional exhaustion, in a sample of 322 civil servants. Extraversion, agreeableness, emotional stability, internal locus of control, and Type A behavior predicted reciprocity. The relationship between perceived lack of reciprocity with the organization and emotional exhaustion was stronger for individuals reporting lower negative affect or higher extraversion. These findings highlight the importance of personality for understanding perceived reciprocity at work and its impact on emotional exhaustion.

Changing profile in the use of anti-asthma drugs

Data regarding the total number of anti-asthma drugs dispensed via community pharmacies within Northern Ireland from 1980 to 1997 were collected and analysed. The use of anti-asthma drugs within this population increased markedly over the study period from 19.84 DDDs/1000/day to 84.07 DDDs/1000/day. With the exception of the non-selective beta(2)-agonists, there has been an overall increasing trend in the utilization of all of the anti-asthma drugs during the study period. Most of the increase is attributable to the increase in prescribing of the selective beta(2)-agonists and the glucocorticoids, This increase in the utilization of anti-asthma drugs may be explained by an increasing prevalence of the condition, increased adherence to asthma management protocols or to the prescribing of more intensive drug therapies.

Texture profile analysis of bioadhesive polymeric semisolids: Mechanical characterization and investigation of interactions between formulation components

This study reports the use of texture profile analysis (TPA) to mechanically characterize polymeric, pharmaceutical semisolids containing at least one bioadhesive polymer and to determine interactions between formulation components. The hardness, adhesiveness, force per unit time required for compression (compressibility), and elasticity of polymeric, pharmaceutical semisolids containing polycarbophil (1 or 5% w/w), polyvinylpyrrolidone (3 or 5% w/w), and hydroxyethylcellulose (3, 5, or 10% w/w) in phosphate buffer (pH 6.8) were determined using a texture analyzer in the TPA mode (compression depth 15 mm, compression rate 8 mm s(-1) 15 s delay period). Increasing concentrations of polycarbophil, poly vinylpyrrolidone, and hydroxyethylcellulose significantly increased product hardness, adhesiveness, and compressibility but decreased product elasticity. Statistically, interactions between polymeric formulation components were observed within the experimental design and were probably due to relative differences in the physical states of polyvinylpyrrolidone and polycarbophil in the formulations, i.e., dispersed/dissolved and unswollen/swollen, respectively. Increased product hardness and compressibility were possibly due to the effects of hydroxyethylcellulose, polyvinylpyrrolidone, and polycarbophil on the viscosity of the formulations. Increased adhesiveness was related to the concentration and, more importantly, to the physical state of polycarbophil. Decreased product elasticity was due to the increased semisolid nature of the product. TPA is a rapid, straightforward analytical technique that may be applied to the mechanical characterization of polymeric, pharmaceutical semisolids. It provides a convenient means to rapidly identify physicochemical interactions between formulation components. (C) 1996 John Wiley & Sons, Inc.

A profile-based tool for finding pipeline parallelism in sequential programs

Traditional static analysis fails to auto-parallelize programs with a complex control and data flow. Furthermore, thread-level parallelism in such programs is often restricted to pipeline parallelism, which can be hard to discover by a programmer. In this paper we propose a tool that, based on profiling information, helps the programmer to discover parallelism. The programmer hand-picks the code transformations from among the proposed candidates which are then applied by automatic code transformation techniques.

This paper contributes to the literature by presenting a profiling tool for discovering thread-level parallelism. We track dependencies at the whole-data structure level rather than at the element level or byte level in order to limit the profiling overhead. We perform a thorough analysis of the needs and costs of this technique. Furthermore, we present and validate the belief that programs with complex control and data flow contain significant amounts of exploitable coarse-grain pipeline parallelism in the program’s outer loops. This observation validates our approach to whole-data structure dependencies. As state-of-the-art compilers focus on loops iterating over data structure members, this observation also explains why our approach finds coarse-grain pipeline parallelism in cases that have remained out of reach for state-of-the-art compilers. In cases where traditional compilation techniques do find parallelism, our approach allows to discover higher degrees of parallelism, allowing a 40% speedup over traditional compilation techniques. Moreover, we demonstrate real speedups on multiple hardware platforms.