Influence of nucleus accumbens core or shell stimulation on early long-term potentiation in the dentate gyrus of freely moving rats

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2010

Implementation of Multi-Core Processor Based on PLASMA (Most MIPS I) IP Core

Multi-core processors is a design philosophy that has become mainstream in scientific and engineering applications. Increasing performance and gate capacity of recent FPGA devices has permitted complex logic systems to be implemented on a single programmable device. By using VHDL here we present an implementation of one multi-core processor by using the PLASMA IP core based on the (most) MIPS I ISA and give an overview of the processor architecture and share theexecution results.

On group strategy-proof mechanisms for a many-to-one matching model

For the many-to-one matching model in which firms have substitutable and quota q-separable preferences over subsets of workers we show that the workers-optimal stable mechanism is group strategy-proof for the workers. In order to prove this result, we also show that under this domain of preferences (which contains the domain of responsive preferences of the college admissions problem) the workers-optimal stable matching is weakly Pareto optimal for the workers and the Blocking Lemma holds as well. We exhibit an example showing that none of these three results remain true if the preferences of firms are substitutable but not quota q-separable.

Nuclear Weapons as Symbols. The Role of Norms in Nuclear Policy Making

Throughout history, nuclear weapons have been considered to be the ultimate weapons. This understanding largely detached them from the portfolio of conventional military means and assigned them a symbolic meaning that influenced the identity and norms creation of nations. In most countries today, the development of nuclear weapons is considered morally prohibitive, incompatible with a country’s identity and international outlook. In some states, however, these negative norms are overridden by a positive set of norms, causing nuclear weapons to become either symbols of invulnerability to perceived threats or the regalia of major power status. Main purpose of this paper is to explore on the conditions that cause most states to develop a moral aversion to nuclear weapons, yet effectively lead to their glorification in others. Many studies on the normative understanding of nuclear weapons consider the existence of a negative normative predisposition, often referred to as ‘nuclear taboo’, as a major factor in preventing their acquisition and use. Other studies acknowledge the existence of a nuclear taboo inhibiting the use of nuclear weapons, but point to the existence of the opposing effect of norms, frequently referred to as the ‘nuclear myth’, when it comes to the acquisition of nuclear weapons. This myth emerges when certain symbolic meanings are attached to nuclear weapons, such as a state’s identity, self-image, and its desired position in the international system. With 180 odd countries in the world abstaining from the acquisition of nuclear weapons and 8 countries in possession of them (with two further countries assumed to have pursued their acquisition), one might consider the dominance of the nuclear taboo over the nuclear myth to be the rule. The core question is thus why and how this relationship reversed in the case of defectors.

A class of stochastic games with infinitely many interacting agents related to Glauber dynamics on random graphs

We introduce and study a class of infinite-horizon nonzero-sum non-cooperative stochastic games with infinitely many interacting agents using ideas of statistical mechanics. First we show, in the general case of asymmetric interactions, the existence of a strategy that allows any player to eliminate losses after a finite random time. In the special case of symmetric interactions, we also prove that, as time goes to infinity, the game converges to a Nash equilibrium. Moreover, assuming that all agents adopt the same strategy, using arguments related to those leading to perfect simulation algorithms, spatial mixing and ergodicity are proved. In turn, ergodicity allows us to prove “fixation”, i.e. that players will adopt a constant strategy after a finite time. The resulting dynamics is related to zerotemperature Glauber dynamics on random graphs of possibly infinite volume.

The Core ideas and axioms of classical fascism (1919-1945)

This article presents and explores the axioms and core ideas, or idées-force, of the Fascist ideologies of the first third of the twentieth century. The aim is to identify the features that define the term “Classical Fascism” as a conceptual category in the study of politics and to uncover the core ideas of its political theory. This analysis requires an appraisal of both the idées-force themselves and the political use that is made of them. If these appreciations are correct, Classical Fascism is characterized by a set of ideological and political aims and methods in which ideas, attitudes and behaviours are determined by an anti-democratic palingenetic ultranationalism underpinned by a sacralized ideology; the quest for a united, indissoluble society as apolitical system and, at the same time, the collective myth that mobilizes and redeems the nation; and third, violence as a political vehicle applied unchecked against internal opposition and against external enemies who challenge the nation´s progression towards the dream of rebirth and the culmination of this progression in the form of an empire.

UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?

Block factor methods offer an attractive approach to forecasting with many predictors. These extract the information in these predictors into factors reflecting different blocks of variables (e.g. a price block, a housing block, a financial block, etc.). However, a forecasting model which simply includes all blocks as predictors risks being over-parameterized. Thus, it is desirable to use a methodology which allows for different parsimonious forecasting models to hold at different points in time. In this paper, we use dynamic model averaging and dynamic model selection to achieve this goal. These methods automatically alter the weights attached to different forecasting models as evidence comes in about which has forecast well in the recent past. In an empirical study involving forecasting output growth and inflation using 139 UK monthly time series variables, we find that the set of predictors changes substantially over time. Furthermore, our results show that dynamic model averaging and model selection can greatly improve forecast performance relative to traditional forecasting methods.

A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models

This paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the parameters defining the model which applies in each regime and the out-of-sample probability of a break occurring. In an extensive empirical evaluation involving many important macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast majority of cases. However, we find no single forecasting model consistently works best in the presence of structural breaks. In many cases, the formal modeling of the break process is important in achieving good forecast performance. However, there are also many cases where simple, rolling OLS forecasts perform well.

UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?

Block factor methods offer an attractive approach to forecasting with many predictors. These extract the information in these predictors into factors reflecting different blocks of variables (e.g. a price block, a housing block, a financial block, etc.). However, a forecasting model which simply includes all blocks as predictors risks being over-parameterized. Thus, it is desirable to use a methodology which allows for different parsimonious forecasting models to hold at different points in time. In this paper, we use dynamic model averaging and dynamic model selection to achieve this goal. These methods automatically alter the weights attached to different forecasting model as evidence comes in about which has forecast well in the recent past. In an empirical study involving forecasting output and inflation using 139 UK monthly time series variables, we find that the set of predictors changes substantially over time. Furthermore, our results show that dynamic model averaging and model selection can greatly improve forecast performance relative to traditional forecasting methods.