Promoting while checking self-interest : a conflict-based governance approach to rebalance corporate power disequilibria in Canada and the United States

La délégation du pouvoir de gestion aux administrateurs et aux gestionnaires, une caractéristique intrinsèque à la gestion efficace de grandes entreprises dans un contexte de capitalisme, confère une grande discrétion à l’équipe de direction. Cette discrétion, si elle n’est pas surveillée, peut mener à des comportements opportunistes envers la corporation, les actionnaires et les autres fournisseurs de capital qui n’ont pas de pouvoir de gestion. Les conflits entre ces deux classes d’agents peuvent émerger à la fois de décisions de gouvernance générale ou de transactions particulières (ie. offre publique d’achat). Dans les cas extrêmes, ces conflits peuvent mener à la faillite de la firme. Dans les cas plus typiques, ils mènent l’extraction de bénéfices privés pour les administrateurs et gestionnaires, l’expropriation des actionnaires, et des réductions de valeur pour la firme. Nous prenons le point de vue d’un petit actionnaire minoritaire pour explorer les méchanismes de gouvernance disponibles au Canada et aux États‐Unis. Après une synthèse dans la Partie 1 des théories sous‐jacentes à l’étude du pouvoir dans la corporation (séparation de la propriété et du contrôle et les conflits d’agence), nous concentrons notre analyse dans la Partie 2 sur les différents types de méchanismes (1) de gouvernance interne, (2) juridiques et (3) marchands, qui confèrent du pouvoir aux deux classes d’agents. Nous examinons comment les intérêts de ces deux classes peuvent être réalignés afin de prévenir et résoudre les conflits au sein de la firme. La Partie 3 explore un équilibre dynamique de pouvoir corporatif qui cherche à minimiser le potentiel d’opportunisme toute en préservant une quantité de discrétion suffisante pour la gestion efficace de la firme. Nous analysons des moyens pour renforcer les protections des actionnaires minoritaires et proposons un survol des pistes de réforme possibles.

Development and Deployment of Wireless Sensor Network in Paddy Fields of Kuttanad

The evolution of wireless sensor network technology has enabled us to develop advanced systems for real time monitoring. In the present scenario wireless sensor networks are increasingly being used for precision agriculture. The advantages of using wireless sensor networks in agriculture are distributed data collection and monitoring, monitor and control of climate, irrigation and nutrient supply. Hence decreasing the cost of production and increasing the efficiency of production. This paper describes the development and deployment of wireless sensor network for crop monitoring in the paddy fields of Kuttanad, a region of Kerala, the southern state of India.

The Kineticist's Workbench: Combining Symbolic and Numerical Methods in the Simulation of Chemical Reaction Mechanisms

The Kineticist's Workbench is a program that simulates chemical reaction mechanisms by predicting, generating, and interpreting numerical data. Prior to simulation, it analyzes a given mechanism to predict that mechanism's behavior; it then simulates the mechanism numerically; and afterward, it interprets and summarizes the data it has generated. In performing these tasks, the Workbench uses a variety of techniques: graph- theoretic algorithms (for analyzing mechanisms), traditional numerical simulation methods, and algorithms that examine simulation results and reinterpret them in qualitative terms. The Workbench thus serves as a prototype for a new class of scientific computational tools---tools that provide symbiotic collaborations between qualitative and quantitative methods.

Influence of the friends' network in drug use and violent behavior among young people in the nightlife recreational context

Resumen tomado de la publicaci??n

Effect of arousal increase in predictable and random task switching : Evidence for the involvement of the anterior attentional network in random but not in predictable task switching

Resumen tomado de la publicaci??n

Quantifying uncertainty in the simulation of crop-climate processes

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (λ, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966–1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of λ near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

Quantification of physical and biological uncertainty in the simulation of the yield of a tropical crop using present-day and doubled CO2 climates

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (lambda, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966-1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of lambda near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

Establishment of a Cross-European Field Site Network in the ALARM Project for Assessing Large-Scale Changes in Biodiversity

The field site network (FSN) plays a central role in conducting joint research within all Assessing Large-scale Risks for biodiversity with tested Methods (ALARM) modules and provides a mechanism for integrating research on different topics in ALARM on the same site for measuring multiple impacts on biodiversity. The network covers most European climates and biogeographic regions, from Mediterranean through central European and boreal to subarctic. The project links databases with the European-wide field site network FSN, including geographic information system (GIS)-based information to characterise the test location for ALARM researchers for joint on-site research. Maps are provided in a standardised way and merged with other site-specific information. The application of GIS for these field sites and the information management promotes the use of the FSN for research and to disseminate the results. We conclude that ALARM FSN sites together with other research sites in Europe jointly could be used as a future backbone for research proposals

Novel supramolecular network in tri- and mono-nuclear oxovanadium(V)-salicyl-hydroximate: Synthesis, structure and catalytic oxidation of hydrocarbons using H2O2 as terminal oxidant

oxovanadium(V) salicylhydroximate complexes, [VO(SHA)(H2O)]center dot 1.58H(2)O (1) and [V3O3(CSHA)(3) (H2O)(3)]center dot 3CH(3)COCH(3) (2) have been synthesized by reaction of VO43- with N-salicyl hydroxamic acid (SHAHS) and N-(5-chlorosalicyl) hydroxamic acid (CSHAH(3)), respectively, in methanol medium. Compound 1 on reaction with pyridine 2,6-dicarboxylic acid (PyDCH2) yields mononuclear complex [VO(SHAH(2))(PyDC)] (3). Treatment of compound 3 with hydrogen peroxide at low pH (2-3) and low temperature (0-5 degrees C) yields a stable oxoperoxovanadium(V) complex H[VO(O-2)(PyDC)(H2O)]center dot 2.5H(2)O (4). All four complexes (1-4) have been characterized by spectroscopic (IR, UV-Vis, V-51 NMR) and single crystal X-ray analyses. Intermolecular hydrogen bonds link complex 1 into hexanuclear clusters consisting of six {VNO5} octahedra surrounded by twelve {VNO5} octahedra to form an annular ring. While the molecular packing in 2 generates a two-dimensional framework hydrogen bonds involving the solvent acetone molecules, the mononuclear complexes 3 and 4 exhibit three-dimensional supramolecular architecture. The compounds 1 and 2 behave as good catalysts for oxygenation of benzylic, aromatic, carbocyclic and aliphatic hydrocarbons to their corresponding hydroxylated and oxygenated products using H2O2 as terminal oxidant; the process affords very good yield and turnover number. The catalysis work shows that cyclohexane is a very easily oxidizable substrate giving the highest turnover number (TON) while n-hexane and n-heptane show limited yield, longer time involvement and lesser TON than other hydrocarbons. (C) 2008 Elsevier Ltd. All rights reserved.

Entropy versus APE production: on the buoyancy power input in the oceans energy cycle

This letter argues that the current controversy about whether Wbuoyancy, the power input due to the surface buoyancy fluxes, is large or small in the oceans stems from two distinct and incompatible views on how Wbuoyancy relates to the volume-integrated work of expansion/contraction B. The current prevailing view is that Wbuoyancy should be identified with the net value of B, which current theories estimate to be small. The alternative view, defended here, is that only the positive part of B, i.e., the one converting internal energy into mechanical energy, should enter the definition of Wbuoyancy, since the negative part of B is associated with the non-viscous dissipation of mechanical energy. Two indirect methods suggest that by contrast, the positive part of B is potentially large.

Integration of chaos theory and mathematical models in building simulation: Part I: Literature review

Current mathematical models in building research have been limited in most studies to linear dynamics systems. A literature review of past studies investigating chaos theory approaches in building simulation models suggests that as a basis chaos model is valid and can handle the increasingly complexity of building systems that have dynamic interactions among all the distributed and hierarchical systems on the one hand, and the environment and occupants on the other. The review also identifies the paucity of literature and the need for a suitable methodology of linking chaos theory to mathematical models in building design and management studies. This study is broadly divided into two parts and presented in two companion papers. Part (I) reviews the current state of the chaos theory models as a starting point for establishing theories that can be effectively applied to building simulation models. Part (II) develops conceptual frameworks that approach current model methodologies from the theoretical perspective provided by chaos theory, with a focus on the key concepts and their potential to help to better understand the nonlinear dynamic nature of built environment systems. Case studies are also presented which demonstrate the potential usefulness of chaos theory driven models in a wide variety of leading areas of building research. This study distills the fundamental properties and the most relevant characteristics of chaos theory essential to building simulation scientists, initiates a dialogue and builds bridges between scientists and engineers, and stimulates future research about a wide range of issues on building environmental systems.

Integration of chaos theory and mathematical models in building simulation: Part II: Conceptual frameworks

Current mathematical models in building research have been limited in most studies to linear dynamics systems. A literature review of past studies investigating chaos theory approaches in building simulation models suggests that as a basis chaos model is valid and can handle the increasing complexity of building systems that have dynamic interactions among all the distributed and hierarchical systems on the one hand, and the environment and occupants on the other. The review also identifies the paucity of literature and the need for a suitable methodology of linking chaos theory to mathematical models in building design and management studies. This study is broadly divided into two parts and presented in two companion papers. Part (I), published in the previous issue, reviews the current state of the chaos theory models as a starting point for establishing theories that can be effectively applied to building simulation models. Part (II) develop conceptual frameworks that approach current model methodologies from the theoretical perspective provided by chaos theory, with a focus on the key concepts and their potential to help to better understand the nonlinear dynamic nature of built environment systems. Case studies are also presented which demonstrate the potential usefulness of chaos theory driven models in a wide variety of leading areas of building research. This study distills the fundamental properties and the most relevant characteristics of chaos theory essential to (1) building simulation scientists and designers (2) initiating a dialogue between scientists and engineers, and (3) stimulating future research on a wide range of issues involved in designing and managing building environmental systems.