Miracle-dz/UniFAR-FTUs huggingface dataset:
(When) Are Intergovernmental Transfers Used to Bail Out Regional Governments? Evidence from Spain 1986-2001

This paper analyses the main determinants of a central government’s decision to use grants to bail out regional governments (i.e., the determinants of additional grants assigned by a central government to regions due to an increase in their issue of debt). The estimated grant equation is derived from a model of a federation, based on Goodspeed (2002), where regions are Stakelberg leaders and the central government’s objective is to maximize a weighted sum of the welfare of the representative consumers from all the regions. The specified equation is estimated separately with a panel data set of discretionary and non-discretionary grants for 15 Spanish regions during the period 1986-2001, using the within and the GMM estimators (Arellano and Bond, 1991), respectively. The results show that the Spanish central government uses grants to partially bailout regions. Such fiscal rescue operations are more intense when: i) the region is responsible for providing health care; ii) debt limits exist (and they have not been properly designed); iii) regional voters are relatively indifferent between the incumbent and the challenger (i.e., there is a high proportion of swing voters).
Muscle strength assessment of upper and lower limbs in elite male karate athletes: comparative study between different age groups

The main aim of this study was to characterize the muscle strength profile the shoulder external and internal rotators and the knee flexors and extensors in elite Serbian male Karate athletes. The second aim was to compare the muscle strength between the hamstrings and quadriceps in male karate athletes of different age groups.The sample was composed of three groups of male karate athletes. First group included seniors (24.1±3.72), the second-juniors (17.6±0.84) and the third group was composed of cadets (15.85±0.69). The following isokinetic parameters were used in the research: Maximal force of right leg extensors (Right_Ext), Maximal force of left leg extensors (Left_Ext), Maximal force of right leg flexors (Right_Flx), Maximal force of left leg flexors (Left_Flx), Maximal force of external rotation of the right arm (Right_Ext_Rot), Maximal force of external rotation of the left arm (Left_Ext_Rot), Maximal force of internal rotation of the right arm (Right_Int_Rot), Maximal force of internal rotation of the left arm (Left_Int_Rot). Based on the discriminant analysis, all variables significantly contribute to the difference between the groups, except maximal force of internal rotation of the right arm. We found that the seniors significantly differ from the cadets in all parameters, and the difference is in favour of seniors (p≤0.05). Seniors and juniors differ in maximal force of left leg extensors, maximal force of right leg flexors, maximal force of internal rotation of the left arm and maximal force of external rotation of the left arm. Juniors and cadets differ in maximal force of left leg flexors and maximal force of internal rotation of the left arm, the difference is in favour of juniors. To conclude, the lower and upper limbs’ isokinetic parameters were significantly higher in the senior compared junior and cadet group. Since only elite competitors were tested, the findings could be of importance for both the selection and training design of karate athletes.
Distributed computing as a new opportunity for stakeholders in dairy cattle management and breeding

currently the uses of on-farm computers and of centralized performance-recording based tools are considered as two opposite models for dairy management. However, dividing the problem into complementary tasks, each of which is optimally solved, is an opportunity that should also be considered by stakeholders. recent development solved data exchange issues allowing the use of adapted distributed computing algorithms. as example milk yield and composition are given. Different research projects and several commercial companies are focussing on the development of on-farm tools, mostly near infrared (nir) based, other projects are developing and implementing tools based on mid infrared (mir), available only through performance recording. Both are complementary, as nir based measurements are easier and less expensive, available at every milking, but mir based measurements are more precise, however only obtained every 4 weeks. numerous advantages arise when combining both types of measurements. it will be shown that statistical theory exists to base advanced modelling on, using optimally the longitudinal data generated by this type of setting. this will open different novel opportunities to optimize currently used on-farm and off-farm management and breeding tools.
Using the Euler-Maruyama Method for Finding a Solution to Stochastic Financial Problems

The purpose of this paper is to survey stochastic differential equations and Euler-Maruyama method for approximating the solution to these equations in financial p roblems. It is not possible to get explicit solution and analytically answer for many of stochastic differential equations, but in the case of linear stochastic differential equations it may be possible to get an exp licit answer. We can approximate the solution with standard numerical methods, such as Euler-Maruyama method, Milstein method and Runge-Kutta method. We will use Euler-Maruyama method for simulat ion of stochastic differential equations for financial problems, such as asset pricing model, square-root asset pricing model, payoff for a European call option and estimating value of European call option and Asian option to buy the asset at the future time. We will d iscuss how to find the approximated solutions to stochastic differential equations for financial problems with examples . Index Iterms—Stochastic Differential Equations, EulerMaruyama method, Asset pricing model, Square-Root asset pricing model.
Effect of oysters Crassostrea virginica and bottom shear velocity on benthic-pelagic coupling and estuarine water quality

Increasing the biomass of bivalve suspensions feeders has been proposed as a means to improve water quality in eutrophic estuaries such as the Chesapeake Bay. However, water quality impacts are likely to be determined by the balance of bivalve feeding and the deposition and sedi- ment regeneration of nutrients from particulate organic matter. In shallow-water environments, ben- thic and pelagic processes are closely coupled and water flow can regulate the supply of seston to the bivalves. In addition, such flow may regulate benthic-pelagic nutrient fluxes through mass transfer limitation and resuspension. We studied the interacting effects of juvenile oysters Crassostrea vir- ginica and bottom shear velocity on phytoplankton biomass and on nutrient regeneration in a series of three 4 wk long comparative experimental ecosystem experiments. All mesocosms had a 1000 l water volume, a 1 m 2 sediment surface area, and a 1 m water-column depth, and the same realistic water-column mixing (turbulence intensity 1 cm s -1 ). The systems included a multi-component meso- cosm with moderate bottom shear velocity (0.6 cm s -1 ) and 2 standard cylindrical tanks with an unre- alistically low bottom shear velocity (0.1 cm s -1 ). Oysters shifted processes to the sediments by decreasing phytoplankton biomass without stimulating additional blooms and by increasing light penetration to the bottom. Through complex and indirect relationships, the interaction of oysters and enhanced shear velocity significantly affected microphytobenthos biomass. Light, as enhanced by the oyster feeding on phytoplankton, increased microphytobenthos biomass; a moderate bottom- shear velocity eroded the biomass. Microphytobenthos biomass decreased nutrient regeneration from the sediments to the water column and may have implications for water quality in low-energy parts of shallow-water estuaries such as Chesapeake Bay. Enhanced bottom shear in more energetic parts of shallow estuaries negatively affects microphytobenthos biomass and may increase nutrient regeneration from the sediments.
Preservice Teachers’ Perception Levels Concerning Consumer Environmental Consciousness

People who strive to prevent harm to the environment while utilizing it and to maintain a livable environment is related to educational and cultural values. If we want the next generation to live in an environment as undisturbed as we live in now, environmentally friendly products should be consumed and waste should be prevented. Thus, raising an environmental consciousness among consumers is of vital importance. Environmental consciousness is shaped by individuals’ knowledge, attitudes, sensitivity and beneficial behavior towards environment. In this sense, the primary aim of this study is to determine preservice teachers’ perception levels of consumer environmental consciousness in terms of different variables. The sample of the study consists of 396 preservice teachers from various departments in the Faculty of Education in Ahi Evran University between the 2015-2016 academic years. 70.2% of the sample is female while 29.8% is male. The Consumer Environment Consciousness Scale (CESS) which was developed by the researcher, and contains 28 items, 20 of which are positive and 8 of which are negative, was used for data collection. The gathered data was analyzed using SPSS 17 software. The study findings suggest that the participant preservice teachers have a medium level of consumer environment consciousness and this consciousness differs significantly in terms of gender, income level and whether or not they have had environment lessons before. Additionally, there was found to be no meaningful difference in perception levels in terms of residential area the participants live in.
Systemic Approaches for the Potential Mechanisms of Common Respiratory Diseases Caused by Air Pollution in China

Min Zhang1, Zhiye Fang1, Yun Zhang2, Zhigang Liu3 and Youming Zhang4* 1Department of Thorax Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen, PR China 2Faculty of Health and Life Sciences, Oxford Brookes University, Oxford, UK 3Institute of Allergy and Immunology, Shenzhen University, Shenzhen, PR China 4Molecular Genetics Group, National heart and Lung Institute, Imperial College London, London, UK
A Nonparametric Approach to Evaluating Inflation-Targeting Regimes

We use a variety of nonparametric test statistics to evaluate the inflation- targeting regimes of Australia, Canada, New Zealand, Sweden and the UK. We argue that a sensible approach of evaluation must rely on a variety of methods, among them parametric and nonparametric econometric methods, for robustness and completeness. Our evaluation strategy is based on examining two possible policy implications of inflation targeting: First, a welfare implication and second, a real variability implication. The welfare implication involves evaluating a utility function, and tested by testing whether (1) the distributions of the levels and the growth rates of private consumption and leisure per capita remained unchanged under inflation targeting, i.e., first-order stochastic dominance; and (2) testing a linear combination of consumption and leisure per capita, where the parameter describing the utility of leisure or the relative preference of leisure is calibrated. Then we introduce nonparametric univariate and multivariate statistical methods to test whether the first and second moments of a variety of real variables, such as the real exchange rate depreciation rate, real GDP per capita growth rate in addition to private consumption per capita and leisure per capita growth rates, remained unchanged under inflation targeting, decreased or increased significantly. There seems to be some evidence of increased welfare under inflation-targeting regimes, but no concrete evidence is found that inflation targeting policy, in general, reduces real variability. Some cross country differences are also found.
A critical analysis of dimensions and curve fitting practice in economics.

When dealing with sustainability we are concerned with the biophysical as well as the monetary aspects of economic and ecological interactions. This multidimensional approach requires that special attention is given to dimensional issues in relation to curve fitting practice in economics. Unfortunately, many empirical and theoretical studies in economics, as well as in ecological economics, apply dimensional numbers in exponential or logarithmic functions. We show that it is an analytical error to put a dimensional unit x into exponential functions ( a x ) and logarithmic functions ( x a log ). Secondly, we investigate the conditions of data sets under which a particular logarithmic specification is superior to the
Well-posed Bayesian geometric inverse problems arising in subsurface flow

In this paper, we consider the inverse problem of determining the permeability of the subsurface from hydraulic head measurements, within the framework of a steady Darcy model of groundwater flow. We study geometrically defined prior permeability fields, which admit layered, fault and channel structures, in order to mimic realistic subsurface features; within each layer we adopt either a constant or continuous function representation of the permeability. This prior model leads to a parameter identification problem for a finite number of unknown parameters determining the geometry, together with either a finite number of permeability values (in the constant case) or a finite number of fields (in the continuous function case). We adopt a Bayesian framework showing the existence and well-posedness of the posterior distribution. We also introduce novel Markov chain Monte Carlo (MCMC) methods, which exploit the different character of the geometric and permeability parameters, and build on recent advances in function space MCMC. These algorithms provide rigorous estimates of the permeability, as well as the uncertainty associated with it, and only require forward model evaluations. No adjoint solvers are required and hence the methodology is applicable to black-box forward models. We then use these methods to explore the posterior and to illustrate the methodology with numerical experiments.
A Test for Two-Sample Repeated Measures Designs: Effect of High-Dimensional Data

Problem statement: High-dimensional repeated measures data are increasingly encountered in various areas of modern science since classical multivariate statistics, e.g,. Hotelling’s T2, are not well defined in the case of high-dimensional data. Approach: In this study, the test statistics with no specific form of covariance matrix for analyzing high-dimensional two-sample repeated measures designs with common equal covariance are proposed. The asymptotic distributions of the proposed test statistics also were derived. Results: A simulation study exposes the approximated Type I errors in the null case very well even though the number of subjects of each sample as small as 10. Numerical simulations study indicates that the proposed test have good power. Application of the new tests is demonstrated using data from the body-weight of male Wistar rats example. Conclusion: The proposed test statistics have an asymptotically distributed as standard normal distributions, under the null hypothesis. Simulation studies show that these test statistics still accurately control Type I error and have quite good power for any the covariance matrix pattern considered.
AN EMPIRICAL INVESTIGATION OF THE RELATIONSHIP AMONG P/E RATIO, STOCK RETURN AND DIVIDEND YIELS FOR ISTANBUL STOCK EXCHANGE

The price to earnings ratio (P/E) is widely used, particularly by practitioners, as a measure of relative stock valuation. Price to earnings is an indicator which indicates current mood of investors how much they are willing to pay per unit of company earnings. Traditionally, the P/E ratio has been assumed to be an indicator of the quality of an investment; a relatively low P/E ratio implies a good investment, whereas a relatively high P/E ratio indicates a “poor” investment prospect. The aim of this study is to identify relationship among market stock return, dividend yields and price to earnings ratio affect in the period 2000.01-2009.12. Therefore, to determine long-run and short-run relationship, Johansen cointegration tests, error-correction models and Granger causality tests are used.
Temperature gradient driven heat flux closure in fluid simulations of collisionless reconnection

Recent efforts to include kinetic effects in fluid simulations of plasmas have been very promising. Concerning collisionless magnetic reconnection, it has been found before that damping of the pressure tensor to isotropy leads to good agreement with kinetic runs in certain scenarios. An accurate representation of kinetic effects in reconnection was achieved in a study by Wang et al. (Phys. Plasmas, vol. 22, 2015, 012108) with a closure derived from earlier work by Hammett and Perkins (Phys. Rev. Lett., vol. 64, 1990, 3019). Here, their approach is analysed on the basis of heat flux data from a Vlasov simulation. As a result, we propose a new local closure in which heat flux is driven by temperature gradients. This way, a more realistic approximation of Landau damping in the collisionless regime is achieved. Previous issues are addressed and the agreement with kinetic simulations in different reconnection set-ups is improved significantly. To the authors’ knowledge, the new fluid model is the first to perform well in simulations of the coalescence of large magnetic islands.
Mining hybrid uml models from event logs of SOA systems

In the paper we consider a method for mining so-called “hybrid” UML models, that refers to software process mining. Models are built from execution traces of information systems with service-oriented architecture (SOA), given in the form of event logs. While common reverse engineering techniques usually require the source code, which is often unavailable, our approach deals with event logs which are produced by a lot of information systems, and some heuristic parameters. Since an individual type of UML diagrams shows only one perspective of a system’s model, we propose to mine a combination of various types of UML diagrams (namely, sequence and activity ), which are considered together with communication diagrams. This allows us to increase the expressive power of the individual diagram. Each type of diagram correlates with one of three levels of abstraction (workflow, interaction and operation), which are commonly used while considering web-service interaction. The proposed algorithm consists of four tasks. They include splitting an event log into several parts and building UML sequence, activity and communication diagrams. We also propose to encapsulate some insignificant or low-level implementation details (such as internal service operations) into activity diagrams and connect them with a more general sequence diagram by using interaction use semantics. To cope with a problem of immense size of synthesized UML sequence diagrams, we propose an abstraction technique based on regular expressions. The approach is evaluated by using a developed software tool as a Windows-application in C#. It produces UML models in the form of XML-files. The latter are compatible with well-known Sparx Enterprise Architect and can be further visualized and utilized by that tool.
TEXT DEPENDENT SPEAKER RECOGNITION ON DIGITAL SIGNAL PROCESSOR: IMPLEMENTATION AND OPTIMIZATION

Speaker recognition is the process of automatically recognizing the speaker, based on individual information included in speech signals. The speaker is identified by investigating the extracted features of the unknown speech and then comparing it with the stored extracted features in the database. This paper describes the implementation of text dependent Speaker Recognition System on TMS320C6713 DSK using Code Composer Studio v3.1 as the Integrated Development Environment (IDE). Feature extraction is done using Mel Frequency Cepstral Coefficients and the compressed speech signal is stored in a speaker database. A distortion measure based on minimization of Euclidean distance is used to match an unknown speaker’s voice with the database. Digital Signal Processors being the fastest method for implementing signal processing solutions offers an excellent platform for developing the specified system. Finally, we provide the software and hardware optimization techniques for reducing the number of clock cycles aiding the development of a faster system.
Social Desirability in Positive Psychology: Bias or Desirable Sociality?

Part of the research presented in this article was supported by the Russian Foundation for Humanities grant 06-06-00449a to the Institute of Existential Psychology and Life Enhancement (EXPLIEN). I am grateful to the other members of our Personal Potential research group at the Moscaw State University, who assisted in data collection and took part in discussions relevant to the contents of this article: Tamara Gordeeva, Irina Burovikhina, Anna Fam, Elena Rasskazova, Anastasia Salikhova, Valentina Sheviakhova. I am especially grateful to Dmitry Leontiev for his steady support, helpful comments and for coining the term 'desirable sociality'.
Secure Opportunistic Routing for Wireless Multi-Hop Networks Using LPG and Digital Signature

ExOR is an opportunistic multi-hop routing protocol transmitting packets through multiple routing paths which enhances the throughput of wireless network. Since diverse attacks happen aiming at wireless network routing and ExOR is lack of security, it is necessary to enhance the capability of preventing malicious attack for routing protocol(16)(19). SecExOR, a secure opportunistic multi-hop routing protocol based on ExOR using key-sharing by Lagrange Polynomial Group and digital signature, is proposed in this paper. SecExOR sets up public and private keys to network nodes for authentication before transmitting of packets. Digital signature using unsymmetrical keys and hash function is employed ensuring reality of routing information. Communication keys based on Lagrange Polynomial Group are pre-shared to be used in the encryption of parts of routing information and packet data avoiding leak and disguise. Simulation indicates that SecExOR protocol successfully resists wireless network attacks and displays effective security performance while maintaining the high throughput of original ExOR.
Primary Teacher Students’ Understanding of Fraction Representational Knowledge in Slovenia and Kosovo

The study of primary teacher students’ knowledge of fractions is very important because fractions present a principal and highly complex set of concepts and skills within mathematics. The present study examines primary teacher students’ knowledge of fraction representations in Slovenia and Kosovo. According to research, there are five subconstructs of fractions: the part-whole subconstruct, the measure subconstruct,the quotient subconstruct, the operator subconstruct and the ratio subconstruct. Our research focused on the part-whole and the measure subconstructs of fractions, creating nine tasks that were represented by different modes of representation: area/region, number line and sets of objects. The sample consisted of 76 primary teacher students in Slovenia and 93 primary teacher students in Kosovo. Both similarities and differencesof the primary teacher students’ interpretations of the representations across the two countries were revealed and compared. The findings suggest that primary teacher students from both countries need to upgrade their understanding of fractions. The analysis confirms that the formal mathematical knowledge acquired by primary teacher students is not necessarily adequate for teaching elementary concepts in school.