No abstract

No abstract

The overall landscape of personal income taxation (PIT) has changed rapidly in numerous post-communist countries of Central and Eastern Europe (CEE), with the adoption of a form of flat-rate tax. Although the economic consequences of this change have been studied extensively, little is known about public opinion on the topic in these countries. This article aims to shed some light on how public opinion addresses the issue of flat-rate PIT in Romania. Logistic regression analysis is used to assess the impact of self-interest, education, age, gender, ideology, political trust, social solidarity, and political knowledge on public support for flat-rate PIT, based on survey data (N = 1105) from the Romanian Election Study (RES). The results suggest that high-income earners, women, and those with higher levels of political trust are more likely to support flat-rate PIT, while higher levels of social solidarity and more education increase the chances of being reluctant about it. Furthermore, the analysis finds no evidence that age, ideology, or political knowledge have an influence on people’s fiscal preferences. The article’s findings provide lessons for policymakers on how fiscal preferences arise and may evolve in a post-communist context, particularly in relation to recurring societal crises.

The calculus of natural frequencies plays an important role in modal analysis of spindle-bearing systems, especially is micro-milling or micro-grinding applications in medicine (surgery and dentistry). Each natural frequency is associated with spindle mass, and therefore material, on which the heating generated in bearings causes axial and radial expansion. Because the radial expansion is limited by the housing and bearings, the most important thermal deformation becomes the axial one. The natural frequency changes caused by temperature evolution due to heating sources in a spindle is analyzed. The heating interval is split in an equal number of intervals, each limit of interval representing a simulation. A predictor is proposed in order to construct a function that shows the dependency of natural frequencies of temperature. The continuous space in an interval is covered by this predictor. The result of predictor is compared with a nonlinear universal approximator known for its capability in prediction, a feedforward neural network. In this preliminary application, the spindle has a predefined shape and the heating sources are placed in predefined locations of spindle - the location of angular contact bearings that are the major sources of heat in the assembly. The spindle is modeled as connected regular geometric bodies - hollow cylinders and hollow truncated cone. The truncated cone is approximated by connected sections of hollow cylinders. The user can see in a graphical interface the changes of natural frequencies with the temperature for didactic scope or a possible optimization of the lifetime of the spindle-bearing assembly. The further development will investigate the possibility of implementation online of simulation using finite elements method.

An extremely important role in modeling shaft - bearing systems, whether it's purely mechanical applications (motors) or medical applications (micro-milling spindles in orthopedics or dentistry), is represented by the bearings. They are the main cause of heat generation in the whole shaft-bearing assemble, but they also bring a major contribution to the radial force of thermal preload, deformations of the shaft or vibrations. Optimization of rotating shafts often gives possibility to adjust the performance but also to increase the service life of the milling tool, as a function of preloading of bearing, which is particularly important in orthopedics due to the overloading of assembly during the surgical act. The forces acting on the bearing, whether of mechanical origin (the force of strain) is due to the thermal effect generated by the friction of the balls on the inner / outer ring and the lubricant used, result in a change in the ball bearing contact angle effect in the overall system analysis. Moreover, dynamically, this angle also changes as a result of external negligible effects that can be considered for a more accurate or neglected model in the case of an approximate model (e.g. centrifugal force, moments, effect gyroscopic, etc.). Advanced graphical interface, calculates the value of the angle on the outer and inner ring, based on the revolution of the axis. The model can be simplified or complicated by giving the user the possibility to include factors that raise the accuracy. This allows you to define the geometric dimensions of the bearing, material constants, the revolution values for which a dynamic analysis is being performed, and graphic display selection of angles as well as export values in tabbed format to be used in other industry-specific applications.

Salmonella is a zoonotic disease that is transmitted from animal products by contact with sick animals or the environments where these animals are living. The mathematical model of transmission disease improve the students' understanding of pathogen dynamics, the role of factors that influence the transmission and control of a specific pathogen and the trend of antimicrobial resistance for this pathogen. The tendency to increase of resistance of Salmonella to antibiotic and combination of antibiotics suggest that models are useful in simulation of different scenarios for dynamic of transmission of this disease. There are two main Salmonella types: Typhimurium serotype and Enteritidis serotype. Both types are included in the software toolbox in a tutorial and interactive manners. The three models of Salmonella compartmental are presented in friendly manner to user with possibility to automatically generation of system equations using built-in templates. Tools that calculate the R0 number and stability analysis are provided as modules in order to evaluate how the experimental data are fit to model or to evaluate the influence of constant coefficients over mathematical model. Because Salmonella typhi bacteria is responsible for a communicable disease, Typhoid fever, an optional module is append to main software in order to give to student the possibility to improve the knowledge with mathematical model of this disease as direct result of a particular bacteria from a larger group of bacteria. The educational software has a friendly GUI (Graphic User Interface) that help student to understand better the dynamic of a specific pathogen modeled by class of larger mathematical models, the compartmental models.

Multi-layer flow-modulating stent is a new advanced technology suitable for complex aortic aneurysms. Computational fluid dynamics is a mechanical bioengineering field for analyzing fluid flow, heat transfer, and associated phenomena, using computer-based simulation. Computational fluid analysis can be useful for student to understand the physical phenomenon that are involved in hemodynamic of blood flow through single layer or multilayer stents and according to geometry of blood vessel and as one of the help tool to choose what type of stent is more suitable for a particular case. In absence of a stent, aneurysm wall are sheared by turbulence flow. Multilayer stent reduces the vortex and the flow is closer to a laminar flow. The pressure in an inlet section becomes more uniform and the flow is improved. The study of the multilayer stent can help students to understand much better the clinical situation. The software tool is construct as a toolbox that call open source computational fluid dynamic solver. The GUI (Graphic User Interface) present an option to see the inlet velocity for different section of blood vessel along with option that set the hemodynamic of blood. The user has the possibility to adjust some geometrical parameters and also few possibility of visualization of dynamic flow. The models are validated by using a multiphysics CAD tool and the results of comparison are acceptable for didactic use of the proposed tool. The tool has been constructed in a modular way, so the next developments can be added as simple connection via a button to a new GUI and access to libraries of the main program.

The aneurysm geometry is an important factor in analyze and predict the risk of rupture but also in selection of patients suitable for surgical intervention, e.g. endovascular Guglielmi detachable coiling. The most used actually technique for evaluation the risk for abdominal aortic aneurysm (AAA) rupture is the maximum diameter (Dmax) of the aorta, but also other dimensions are used for assessment of risk for cerebral aneurysm. In most of the cases, the aneurysm geometry is measured manually using computed tomography (CT) or three-dimensional (3D) angiography. By this method, the accuracy and reproducibility can vary substantially from user to user and even in the case of the same user, during the repeatedly measurements. We propose software based on GUI for automatic and semi-automatic usage for processing of 2D images, containing aneurysm, useful in virtual education or e-learning process. The image is first segmented, and the user can select points to perform automatically extract of geometrical parameters using algorithms from computational geometry. The various parameters that describe the shape of reproducibility are statistically analyzed if the user selects this option. The software for intracranial aneurysm geometry quantification has a separate module used for prediction the risk of rupture. A specialized module is used for work with original image; the operations in this case are based on interactive selections made by user: points and polygons with option to extract different shape descriptor for feature selection. The prediction in this stage can be manually selected from two options related to a set of data: a liner one and a nonlinear one based of simple regressive nonlinear model. The results are very encouraging and the future developments are taken into account.