Fisheries Instrument Choice under Uncertainty

This paper uses data from an actual fishery to construct a tractable and dynamic model to compare expected profit and its variance, optimal stock size, optimal harvest rate and optimal fishing effort under different management regimes under uncertainty. The results provide a comparison of instrument choice between a total harvests control and a total effort control under uncertainty, an original method to evaluate the tradeoffs between profits and other criteria in a dynamic context, and provide guidance as to the relative merits of catch and effort controls in fisheries management.fisheries management, uncertainty

The Relevance-Based Model of Context in Processing Puns

While the essential role context plays in the understanding of expressions and utterances has never been questioned, the way it is perceived has evolved from a static factor established prior to the process of utterance interpretation, indeed a prerequisite for processing information, to a dynamic entity which emerges in this process. The latter view is espoused by relevance theorists, who define context as “the set of premises used in interpreting an utterance” (Sperber and Wilson 1986/95: 15) and treat it as a mental construct undergoing diverse modifications as the comprehender of an utterance processes and interprets incoming verbal information and other communicative signals supplied by the communicator. The aim of this paper is to consider the usefulness of this model of context for analyzing the derivation of meaning in puns, i.e. utterances in which, instead of its usual function of allowing the comprehender to resolve ambiguities ubiquitous in language and communication, the context plays a different role of leading him to entertain, and often to accept two diverse readings[…

Sleptons without Hadrons

Multilepton searches for electroweakino and slepton pair production at hadron colliders remain some of the best means to test weak-scale supersymmetry. Searches at the CERN Large Hadron Collider, however, are limited by large diboson and top quark pair backgrounds, despite the application of traditional, central jet vetoes. In this context, we report the impact of introducing dynamic jet vetoes in searches for colorless superpartners. As a representative scenario, we consider the Drell-Yan production of a pair of right-handed smuons decaying into a dimuon system accompanied with missing transverse energy. As an exploratory step, we consider several global and local measures of the leptonic and hadronic activity to construct the veto. In most all cases, we find that employing a dynamic jet veto improves the sensitivity, independently of the integrated luminosity. The inclusion of non-perturbative multiple particle interactions and next-to-leading order jet merging does not alter this picture. Directions for further improvements are discussed.Comment: 18 pages; 7 figures; additional discussions added; journal version; results unchange

The Role of Dynamic Capabilities in Outsourcing Sales and Marketing Functions: A Resource-Advantage Perspective in the Context of Consumer Packaged Goods

Outsourcing refers to contracting out the functions to a third party instead of conducting them in-house. The main contribution of this dissertation is to develop and test a model of successful outsourcing in the accomplishment of headquarters selling task. Specifically, it intends to (a) provide a theoretical framework for outsourcing partnership performance, (b) explore the potential complementarities construct in the context of a dyadic outsourcing relationship, (c) examine the role of learning dynamic capabilities in turning potential complementarities into outsourcing success, and (d) explicate the role of structural social capital as an antecedent to learning dynamic capability construct . The conceptual framework of the model is based on the resource-advantage theory which posits that resources, potential complementarities and dynamic capabilities are explicated as sub-constructs. The pool of respondents who are the practicing managers of outsourcing in the consumer packaged goods industry was used to test the hypothesized relationships. The findings showed that the learning dynamic capabilities construct is the most important factor affecting in the outsourcing partnership performance in the context of headquarters selling task. The task-related resources of the outsourcer had a significant positive effect on potential complementarities. However, the positive effect of the outsourcee’s task-related resources on potential complementarities was not significant. Likewise, the positive effect of the potential complementarities on the outsourcing partnership performance did not emerge as significant. The effect of structural social capital of the outsourcer had a significant but negative influence on learning dynamic capabilities. The positive effect of structural social capital of the outsourcee on learning dynamic capabilities and the moderating role of learning dynamic capabilities were found to be insignificant

BGM: Building a Dynamic Guidance Map without Visual Images for Trajectory Prediction

Visual images usually contain the informative context of the environment, thereby helping to predict agents' behaviors. However, they hardly impose the dynamic effects on agents' actual behaviors due to the respectively fixed semantics. To solve this problem, we propose a deterministic model named BGM to construct a guidance map to represent the dynamic semantics, which circumvents to use visual images for each agent to reflect the difference of activities in different periods. We first record all agents' activities in the scene within a period close to the current to construct a guidance map and then feed it to a Context CNN to obtain their context features. We adopt a Historical Trajectory Encoder to extract the trajectory features and then combine them with the context feature as the input of the social energy based trajectory decoder, thus obtaining the prediction that meets the social rules. Experiments demonstrate that BGM achieves state-of-the-art prediction accuracy on the two widely used ETH and UCY datasets and handles more complex scenarios