Analysis of Central Banks Transparency in Countries on the Road to the European Single Currency

This paper aims to analyze the developments of the last decade and a half of monetary policy transparency followed by the central banks (CBs) in Central and Eastern European countries on the road to the euro adoption and to compare the results with those identified in the case of the European Central Bank (ECB). We approached the transparency level from the perspective of monetary policy strategies they use. The main results indicate increasing transparency within the considered timeframe for all monetary authorities subject to analysis, regardless of their monetary policy strategy, a higher level of transparency in the case of CBs applying a strategy of inflation targeting (IT) compared to those using the exchange rate as nominal anchor; a similar degree of transparency of the ECB and monetary authorities targeting inflation; the existence of a high degree of transparency, low inflation and stronger economic development in CEE states where the CBs target inflation compared to monetary authorities that are geared towards exchange rate targeting

MECHANISM TO DRAW MACLAURIN TRISECTRIX

It is used a geometrical method for generating Maclaurin trisectrix and based on it , thesynthesis of a mechanism that can draw it, is made. The structure of the found mechanism is R-RTRTtype, having two driving elements with correlated movements. This mechanism is analysedand the desired curve is obtained just for certain dimensions of the mechanism. The mechanism’smovement is studied based on some diagrams and different outputs are obtained for certain initialdimensions of the mechanism’s

KINEMATICS OF MATERIAL POINT ON THE COCHLEOID

They are shown the geometrical considerations and the properties of cochleoid, a flat curve in thespiral’s family. Determine the positions, velocities and accelerations of material point in motion on thecochleoid. They are obtained diagrams, which are interpreted

Global financial crisis-driven mutations affecting the transmission mechanism customized to monetary policy strategies. A VAR, SVAR and BVAR approach

This paper analyzes the transmission mechanisms of monetary policy in the Central and Eastern European (CEE) countries on the road to euro adoption depending on the monetary policy strategies used by the national central banks (CBs). The scientific construction of the paper is based on three methods: vector autoregressive (VAR), structural vector autoregressive (SVAR) and Bayesian techniques-estimated vector autoregressive (BVAR). The main results have indicated: 1) lack of similarity of the transmission mechanism, a high degree of heterogeneity in the transmission of monetary policy impulses indicated in all three cases subject to analysis: speed, persistence and amplitude, 2) an increase in the speed of monetary policy shocks transmission, a decrease in the amplitude of monetary policy shock impact and a reduction (or the maintaining at a similar level) of the persistence of monetary policy shock effects subsequent to the global financial crisis, regardless of the monetary policy strategy used

R-R-RTR MECHANISM PATHS

Let’s consider a mechanism with two conducting elements and a RTR dyad and the paths of a point onthe connecting rod with variable length are determined. Let’s consider the movements of the conductingelements correlated through linear relations. There are cases analysed when movement is intermittent or when aconducting element performs more rotations than the othe

From Monte Carlo to neural networks approximations of boundary value problems

In this paper we study probabilistic and neural network approximations for solutions to Poisson equation subject to H\" older data in general bounded domains of $\mathbb{R}^d$. We aim at two fundamental goals. The first, and the most important, we show that the solution to Poisson equation can be numerically approximated in the sup-norm by Monte Carlo methods, { and that this can be done highly efficiently if we use a modified version} of the walk on spheres algorithm { as an acceleration method. This provides estimates which are efficient with respect to the prescribed approximation error and with polynomial complexity in the dimension and the reciprocal of the error.} {A crucial feature is that} the overall number of samples does not not depend on the point at which the approximation is performed. As a second goal, we show that the obtained Monte Carlo solver renders { in a constructive way} ReLU deep neural network (DNN) solutions to Poisson problem, whose sizes depend at most polynomialy in the dimension $d$ and in the desired error. In fact we show that the random DNN provides with high probability a small approximation error and low polynomial complexity in the dimension

Network controllability solutions for computational drug repurposing using genetic algorithms

Control theory has seen recently impactful applications in network science, especially in connections with applications in network medicine. A key topic of research is that of finding minimal external interventions that offer control over the dynamics of a given network, a problem known as network controllability. We propose in this article a new solution for this problem based on genetic algorithms. We tailor our solution for applications in computational drug repurposing, seeking to maximize its use of FDA-approved drug targets in a given disease-specific protein-protein interaction network. We demonstrate our algorithm on several cancer networks and on several random networks with their edges distributed according to the Erdos-Renyi, the Scale-Free, and the Small World properties. Overall, we show that our new algorithm is more efficient in identifying relevant drug targets in a disease network, advancing the computational solutions needed for new therapeutic and drug repurposing approaches