Interpersonal Power: A Review, Critique, and Research Agenda

Power is a fundamental force in social relationships and is pervasive throughout various types of interactions. Although research has shown that the possession of power can change the powerholder, the full extent of power's consequences on individuals' decision making capabilities and social interactions within organizations is not fully understood. The goal of this paper is to review, synthesize, and critique the literature on power with a focus on its organizational and managerial implications. Specifically, we propose a definition of power that takes into account its three defining characteristics-having the discretion and means to enforce one's will-and summarize the extant literature on how power influences individuals' thoughts, emotions, and actions both in terms of prosocial and antisocial outcomes. In addition, we highlight important moderators of power and describe ways in which it can be studied in a more rigorous manner by examining methodological issues and pitfalls with regard to its measurement and manipulation. We also provide future research directions to motivate and guide the study of power by management scholars. Our desire is to present a thorough and parsimonious account of power's influence on individuals within an organizational context, as well as provide a foundation that scholars can build upon as they continue to make consequential contributions to the study of power.

IPH Response to Draft planning policy statement 18 Renewable energy - March 2008

IPH welcomes the Planning Policy Statement 18 Renewable Energy (PPS18) and the opportunity to comment on the publication.  IPH applies a holistic model of health which emphasises a wide range of social determinants, including economic, environmental, social and biological factors. IPH considers that the health impacts of renewable energy should be considered as part of PPS18. We wish to make the following general observations in relation to the Proposed Plan:  IPH welcomes the sustainable approach by the Department of the Environment to encourage and facilitate the provision of renewal energy in Northern Ireland. PPS18 can support the move to reduce pollutants entering the environment. However there is a need to consider wider public health concerns in the adoption of PPS18. Encouraging renewable energy (while balancing this with environmental and conservation concerns) will benefit health locally, and on a global scale. Climate change has been identified as one of the most important public health challenges of the 21st Century and therefore any policy which seeks to address this major issue is welcomed.

Biophysical requirements of power-supply systems: nuclear energy and fossil energy

The report presents a grammar capable of analyzing the process of production of electricity in modular elements for different power-supply systems, defined using semantic and formal categories. In this way it becomes possible to individuate similarities and differences in the process of production of electricity, and then measure and compare “apples” with “apples” and “oranges” with “oranges”. For instance, when comparing the various unit operations of the process of production of electricity with nuclear energy to the analogous unit operations of the process of production of fossil energy, we see that the various phases of the process are the same. The only difference is related to characteristics of the process associated with the generation of heat which are completely different in the two systems. As a matter of facts, the performance of the production of electricity from nuclear energy can be studied, by comparing the biophysical costs associated with the different unit operations taking place in nuclear and fossil power plants when generating process heat or net electricity. By adopting this approach, it becomes possible to compare the performance of the two power-supply systems by comparing their relative biophysical requirements for the phases that both nuclear energy power plants and fossil energy power plants have in common: (i) mining; (ii) refining/enriching; (iii) generating heat/electricity; (iv) handling the pollution/radioactive wastes. This report presents the evaluation of the biophysical requirements for the two powersupply systems: nuclear energy and fossil energy. In particular, the report focuses on the following requirements: (i) electricity; (ii) fossil-fuels, (iii) labor; and (iv) materials.

Influence of inter-electrode distance, contraction type, and muscle on the relationship between the sEMG power spectrum and contraction force.

INTRODUCTION: Spectral frequencies of the surface electromyogram (sEMG) increase with contraction force, but debate still exists on whether this increase is affected by various methodological and anatomical factors. This study aimed to investigate the influence of inter-electrode distance (IED) and contraction modality (step-wise vs. ramp) on the changes in spectral frequencies with increasing contraction strength for the vastus lateralis (VL) and vastus medialis (VM) muscles. METHODS: Twenty healthy male volunteers were assessed for isometric sEMG activity of the VM and VL, with the knee at 90° flexion. Subjects performed isometric ramp contractions in knee extension (6-s duration) with the force gradually increasing from 0 to 80 % MVC. Also, subjects performed 4-s step-wise isometric contractions at 10, 20, 30, 40, 50, 60, 70, and 80 % MVC. Interference sEMG signals were recorded simultaneously at different IEDs: 10, 20, 30, and 50 mm. The mean (F mean) and median (F median) frequencies and root mean square (RMS) of sEMG signals were calculated. RESULTS: For all IEDs, contraction modalities, and muscles tested, spectral frequencies increased significantly with increasing level of force up to 50-60 % MVC force. Spectral indexes increased systematically as IED was decreased. The sensitivity of spectral frequencies to changes in contraction force was independent of IED. The behaviour of spectral indexes with increasing contraction force was similar for step-wise and ramp contractions. CONCLUSIONS: In the VL and VM muscles, it is highly unlikely that a particular inter-electrode distance or contraction modality could have prevented the observation of the full extent of the increase in spectral frequencies with increasing force level.

Simultaneous B(0)- and B(1)+-map acquisition for fast localized shim, frequency, and RF power determination in the heart at 3 T.

High-field (>or=3 T) cardiac MRI is challenged by inhomogeneities of both the static magnetic field (B(0)) and the transmit radiofrequency field (B(1)+). The inhomogeneous B fields not only demand improved shimming methods but also impede the correct determination of the zero-order terms, i.e., the local resonance frequency f(0) and the radiofrequency power to generate the intended local B(1)+ field. In this work, dual echo time B(0)-map and dual flip angle B(1)+-map acquisition methods are combined to acquire multislice B(0)- and B(1)+-maps simultaneously covering the entire heart in a single breath hold of 18 heartbeats. A previously proposed excitation pulse shape dependent slice profile correction is tested and applied to reduce systematic errors of the multislice B(1)+-map. Localized higher-order shim correction values including the zero-order terms for frequency f(0) and radiofrequency power can be determined based on the acquired B(0)- and B(1)+-maps. This method has been tested in 7 healthy adult human subjects at 3 T and improved the B(0) field homogeneity (standard deviation) from 60 Hz to 35 Hz and the average B(1)+ field from 77% to 100% of the desired B(1)+ field when compared to more commonly used preparation methods.

Predictors of HIV-protection behaviour in HIV-positive men who have sex with casual male partners: a test of the explanatory power of an extended Information-Motivation-Behavioural Skills model.

This prospective study applies an extended Information-Motivation-Behavioural Skills (IMB) model to establish predictors of HIV-protection behaviour among HIV-positive men who have sex with men (MSM) during sex with casual partners. Data have been collected from anonymous, self-administered questionnaires and analysed by using descriptive and backward elimination regression analyses. In a sample of 165 HIV-positive MSM, 82 participants between the ages of 23 and 78 (M=46.4, SD=9.0) had sex with casual partners during the three-month period under investigation. About 62% (n=51) have always used a condom when having sex with casual partners. From the original IMB model, only subjective norm predicted condom use. More important predictors that increased condom use were low consumption of psychotropics, high satisfaction with sexuality, numerous changes in sexual behaviour after diagnosis, low social support from friends, alcohol use before sex and habitualised condom use with casual partner(s). The explanatory power of the calculated regression model was 49% (p<0.001). The study reveals the importance of personal and social resources and of routines for condom use, and provides information for the research-based conceptualisation of prevention offers addressing especially people living with HIV ("positive prevention").

On [summation of 1 raised to the power 1] equivalence relations over the natural numbers

"Vegeu el resum a l'inici del document del fitxer adjunt"

Ticks (Acari: Ixodidae) on wild animals from the Porto-Primavera Hydroelectric power station area, Brazil

From June 2000 to June 2001, a total of 741 ticks were collected from 51 free-living wild animals captured at the Porto-Primavera Hydroelectric power station area, located alongside an approximately 180 km course of the Paraná river, between the states of São Paulo and Mato Grosso do Sul, comprising 9 species of 3 genera: Ambly-omma (7 species), Boophilus (1) and Anocentor (1). A total of 421 immature Amblyomma ticks were reared in laboratory until the adult stage, allowing identification of the species. A. cajennense was the most frequent tick species (mostly immature stages) collected on 9 host species: Myrmecophaga tridactyla, Tamandua tetradactyla,Cerdocyon thous, Puma concolor,Tayassu tajacu, Mazama gouazoubira,Hydrochaeris hydrochaeris,Alouatta caraya, Cebus apella. Other tick species were less common, generally restricted to certain host taxa.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Combining probabilistic land-use change and tree population dynamics modelling to simulate responses in mountain forests

Altitudinal tree lines are mainly constrained by temperature, but can also be influenced by factors such as human activity, particularly in the European Alps, where centuries of agricultural use have affected the tree-line. Over the last decades this trend has been reversed due to changing agricultural practices and land-abandonment. We aimed to combine a statistical land-abandonment model with a forest dynamics model, to take into account the combined effects of climate and human land-use on the Alpine tree-line in Switzerland. Land-abandonment probability was expressed by a logistic regression function of degree-day sum, distance from forest edge, soil stoniness, slope, proportion of employees in the secondary and tertiary sectors, proportion of commuters and proportion of full-time farms. This was implemented in the TreeMig spatio-temporal forest model. Distance from forest edge and degree-day sum vary through feed-back from the dynamics part of TreeMig and climate change scenarios, while the other variables remain constant for each grid cell over time. The new model, TreeMig-LAb, was tested on theoretical landscapes, where the variables in the land-abandonment model were varied one by one. This confirmed the strong influence of distance from forest and slope on the abandonment probability. Degree-day sum has a more complex role, with opposite influences on land-abandonment and forest growth. TreeMig-LAb was also applied to a case study area in the Upper Engadine (Swiss Alps), along with a model where abandonment probability was a constant. Two scenarios were used: natural succession only (100% probability) and a probability of abandonment based on past transition proportions in that area (2.1% per decade). The former showed new forest growing in all but the highest-altitude locations. The latter was more realistic as to numbers of newly forested cells, but their location was random and the resulting landscape heterogeneous. Using the logistic regression model gave results consistent with observed patterns of land-abandonment: existing forests expanded and gaps closed, leading to an increasingly homogeneous landscape.