Miracle-dz/UniFAR-FTUs huggingface dataset:
European Integration and Europeanization Processes in Welfare Systems: A Comparative Analysis with Typological Purpose

European Integration and Europeanization processes in social field are the focus of the analysis here proposed. Starting from the social implications and from the effects that the different European welfare regimes have on them, it will be shown a possible re-arrangement of the differences within the various regimes, as well as of their relationships and their new characterizations. The aim is highlight the dual thrust between Europeanization and decentralization of social policy in some European countries, which are considered as a guidance of specific welfare regimes, in order to understand at what level of governance the decisions that shape this area can be attributed. However, the analysis involved five Nations (Italy, Germany, France, Spain and United Kingdom) and ten local contexts, two for each Nation (Milan and Naples, Berlin and Munich, Paris and Rouen, Barcelona and Vigo, London and Liverpool). What result is a comparative geographic and policy analysis based on a mixed methods approach intended as a merge of quantitative and qualitative approaches, techniques and tools. The analysis contemplates jointly the study of supranational, national and subnational directions, but also the study of local dynamics concerning the spread of specific: models of implementation, kind of decision-making processes in social policies and type of regimes that this decision generates. The structure of the study is growing both in macro perspective (through multivariate and multi-level analysis of social indicators and subsequent cluster analysis) as well as in the micro perspective (through the analysis of projects in different local contexts and in particular by applying impact, implementation and comparative network analysis). The conclusion was the realization of a general model of interpretation and classification of the changes occurred in the different European welfare regimes.
The little-studied cluster Berkeley 90 I. LS III +46 11: a very massive O3.5 If* + O3.5 If* binary

Context. It appears that most (if not all) massive stars are born in multiple systems. At the same time, the most massive binaries are hard to find owing to their low numbers throughout the Galaxy and the implied large distances and extinctions. Aims. We want to study LS III +46 11, identified in this paper as a very massive binary; another nearby massive system, LS III +46 12; and the surrounding stellar cluster, Berkeley 90. Methods. Most of the data used in this paper are multi-epoch high S/N optical spectra, although we also use Lucky Imaging and archival photometry. The spectra are reduced with dedicated pipelines and processed with our own software, such as a spectroscopicorbit code, CHORIZOS, and MGB. Results. LS III +46 11 is identified as a new very early O-type spectroscopic binary [O3.5 If* + O3.5 If*] and LS III +46 12 as another early O-type system [O4.5 V((f))]. We measure a 97.2-day period for LS III +46 11 and derive minimum masses of 38.80 ± 0.83 M� )
Effect of Cassoy-urea Pellet as a Protein Source in Concentrate on Ruminal Fementation and Digestibility in Cattle

Four male crossbred native beef cattle (average body weight of 427.7 kg) were randomly allocated to four types of cassoy-urea pellet as a source of protein in concentrate according to a 4x4 Latin square design to determine effect of diets on ruminal fermentation and nutrient digestibility. The four types of cassoy-urea pellets contained cassava hay, soybean meal, urea and binding agent at 79.2:19.8:0:1 (27.9% CP dry matter), 78.4:19.6:1:1 (30.4% CP), 77.6:19.4:2:1 (33.0% CP) and 99:0:0:1 (23.8% CP) for dietary treatments; 1, 2, 3 and 4, respectively. All four concentrate mixtures contained similar crude protein levels (11% CP) and were fed to animals in two equal parts (0.5% of body weight per day) while urea-treated rice straw (5% urea) was given ad libitum. The experiment revealed that dietary concentrate treatments had no effect on dry matter intake while digestibilities of neutral-detergent fiber and crude protein were higher (p<0.05) in cattle fed dietary treatments 1, 2 and 3 than in cattle fed dietary treatment 4. Ruminal ammonia-nitrogen (NH 3 -N), was higher and acetic acid concentration (C2) and ratio of C2 to propionic acid (C3) were lower (p<0.05) in cattle fed dietary treatments 1, 2 and 3 than in those on treatment 4. It is concluded that use of cassoy-urea pellet as a protein source in concentrates for cattle resulted in improvement of digestibility, ruminal fermentation and rumen ecology. Further research using cassoy-urea pellet in feeding trials with milking cows and fattening beef should be undertaken.
Modeling Consumer Credit Scoring Through Bayes Network

In this research TAN Bayes, Markov Bayes and Markov-FS data mining methods were used to predict andcompare the performance of these three Bayes networks and to identify the inputs or predictors that differentiate “good credit” from “bad credit”. The results indicated the Markov model is slightly better at predicting correctly; however, the Markov-FS model is only a couple of percentage points behind the Markov model. This may mean it would be better to use the Markov-FS model since it uses fewer inputs to calculate its results, thereby saving on data collection and entry time and processing time.
Development and evaluation of porous membrane pellets of disopyramide phosphate for sustained release

Aim of the present study was to prepare pellets of disopyramide phosphate (DPP) using blend of Hydroxy Propyl Methyl Cellulose (HPMC K4M) and Avicel PH 101 (Microcrystalline cellulose) and to coat the prepared pellets by mixture of Eudragit L100 and Eudragit S100 to obtain microporous membrane for controlled release. Extrusion/spheronization method was employed to produce spherical discrete pellets of uniform size. Solid, porous, discrete, reproducible pellets were obtained. Sieve analysis data indicated that the size of prepared pellets was in the range of 850 – 1180 μm. Yield of pellets was found to be 96.5%. Prepared pellets were spherical in shape, with pores on the surface, as evidenced by scanning electron microscopy (SEM). Compatibility of the drug after encapsulation in the pellets was confirmed by DSC and by FTIR. The prepared pellets were analyzed quantitatively for the drug content and were found to be 96.2%. In vitro drug release studies indicated F3C2 as optimized formulation. Formulation F3C2 shows 93.26% drug release up to 12 hrs. It was also observed that there was no significant release of drug in gastric pH. The release kinetics for all the formulations indicated that drug release followed non-Fickian diffusion. In vivo study of DPP (300 mg) pellets was carried out in healthy albino rats. Plasma DPP concentrations and other pharmacokinetic parameters were statistically analyzed. The results of paired T-test for the comparison of pharmacokinetic data showed that there was no significant variation between the marketed (Norpace® CR) and F3C2. The stability studies performed on F3C2 showed no significant difference in drug content. It was concluded that the drug release performance was greatly affected by microporous membrane coating used in the preparation of pellets.
Study of the nonlinear dynamics of vortex flow in a pipe

This work outlines a numerical investigation of the dynamics of a high Reynolds number axisymmetric vortex flow in a pipe with high levels of swirl. A global picture of bifurcations in the flow is revealed by mapping the branches of equilibrium fixed points, their stability behavior and possible transitions to vortex breakdown or other secondary branches. These branches characterize a domain of local attractiveness where the flow tends to align itself along a low dimensional subspace. In order to study the local stability characteristics of the branches, we developed numerical schemes for Linear Stability Analysis both through direct simulations and thorugh System Identification. We further study the nonlinear dynamics of the flow along this attractive domain and model the transients with low order models. A central role in the investigation is played by low and least order, mean-field Galerkin models of the local dynamics near bifurcation branches. Indeed, as this is a first case study of mean field Galerkin models in a flow configuration with multiple coexisting attractors, the technical and conceptual aspects of these models and of their identification, are of independent interest. The unveiled picture is that of an inertial manifold that is well approximated with only few dominant coherent structures, or modes that are well characterized by temporal and spatial frequencies, and that continuously deform with changes in the operating conditions.
A TWO-STAGE PLUG-IN BANDWIDTH SELECTION AND ITS IMPLEMENTATION FOR COVARIANCE ESTIMATION

The two most popular bandwidth choice rules for kernel HAC estimation have been proposed by Andrews (1991) and Newey and West (1994). This paper suggests an alternative approach that estimates an unknown quantity in the optimal bandwidth for the HAC estimator (called normalized curvature) using a general class of kernels, and derives the optimal bandwidth that minimizes the asymptotic mean squared error of the estimator of normalized curvature. It is shown that the optimal bandwidth for the kernel-smoothed normalized curvature estimator should diverge at a slower rate than that of the HAC estimator using the same kernel. An implementation method of the optimal bandwidth for the HAC estimator, which is analogous to the one for probability density estimation by Sheather and Jones (1991), is also developed. The finite sample performance of the new bandwidth choice rule is assessed through Monte Carlo simulations.
SURVEY ON VARIOUS IMAGE CONTRAST ENHANCEMENT TECHNIQUES

In this paper a survey on various image contrast enhancement techniques has been done. Colour image enhancement plays an important role in digital image processing. Contrast enhancement is an optimization problem and is done for the images which are experiencing poor quality. Po or quality on images is due to various factors like environmental lighting conditions, defects in photographic devices etc. Therefore image contrast enhancement is important in order to improve the human acceptance rate. Most of the papers are based on his togram equalization technique and its extensions. Histogram equalization is a contrast enhancement technique based on histogram of the image. Each technique has got its own advantages as well as disadvantages. Various contrast enhancement techniques have b een proposed by different authors as an extension of the traditional histogram equalization. They are power constrained contrast enhancement, dynamic range compression, colour model conversion, gamma correction and channel division methodologies. Several recent papers are being surveyed under each technique.
Phylogenetic Analysis of allopolyploid species

In principle all methods of phylogenetic analysis presuppose that evolution is divergent, hence phylogenetic analysis of allopolyploids poses the problem that allopolyploids by definition have evolved by reticulation. The use of sequence data for phylogenetic analysis may solve part of the problem but other problems may arise. Sequences from the nuclear genome of the allopolyploids may be extracted from each of the genomes derived from the progenitor species and, provided that these genomes have not interacted, it is possible to track the evolutionary history of each genome and hence of the allopolyploid. Data from the organellar genomes, usually the plastids, may provide additional information about the direction of the initial hybridization event creating the allopolyploid, e.g., point to the maternal (in most seed plants) or paternal (in conifers) parent. A method that efficiently and selectively amplifies genome specific sequences from allopolyploids is briefly described. Examples from the Triticeae (i.e., the genera Hordeum, Triticum, and Hordelymus) are used to discuss the potential strength and possible problems of the method related to phylogenetic analysis of allopolyploids.
A new controller design of electro-hydraulic servo system based on empirical mode decomposition

The signal of electro-hydraulic servo system is non-stationary and time-varying due to the influence of vibration, noise and mechanical impact. The traditional digital filter always suffers delay in time domain and the delay increases along with the increasing of frequency. Considering the features of electro-hydraulic servo system, the Hilbert-Huang transform method is an effective method to decompose the original signal and obtain the noise components. Some improvements are made based on Hilbert Huang transform method and a new real time on-line filtering method is proposed in this paper. This improved filter is able to decompose out the noise components and other interference components from original signal, and remove them off in real time. Based on this new on-line filter, a new controller is also designed. Compared the filtering result with the traditional digital filter, this new controller’s control performance is much better.
Topology optimization of wave barriers for railway induced vibrations in buildings

Abstract. In order to reduce environmental ground vibration due to railway traffic, mitigation measures at the source, the transmission path and the receiver can be applied. Mitigation measures on the transmission path are particularly appealing in situations with existing track and buildings. In this contribution, the optimal design of stiff wave barriers is considered. Up to now, wall barriers with a rectangular cross section have mostly been studied. However, current construction methods of wave barriers provide a wide flexibility in design geometry. Therefore further improvement is feasible. Topology optimization is used to discover novel, improved design geometries. Stiffer material is inserted into a design domain located between the source and a building. The objective is to minimize the amount of stiffer material in the design domain while satisfying the required vibration criteria in the building. The optimization problem is solved using a gradient based method and the adjoint method is used to enable an efficient calculation of the sensitivities. In this way, an optimal geometry is determined that considerably reduces the required amount of stiffer material. Topology optimized stiff wave barriers are therefore effective in reducing vibration levels, outperforming the rectangular wave barriers. The design contains, however, small features, making it sensitive to geometric imperfections, and a worst case robust optimization is applied. The resulting smaller sensitivity with respect to geometric imperfections also ensures that a posteriori design simplifications have a minimal impact on the barriers performance.
The Diagnostic Value of Irisin and Visfatin in Experimental Testicular Torsion

Telif Hakkı 2017 Sağlık Bilimleri Üniversitesi Haseki Eğitim ve Araştırma Hastanesi Haseki Tıp Bülteni, Galenos Yayınevi tarafından basılmıştır. Ad­dress­for­Cor­res­pon­den­ce/Ya­z›fl­ma­Ad­re­si:­Fatma Saraç University of Health Sciences, Haseki Training and Research Hospital, Clinic of Pediatric Surgery, İstanbul, Turkey E-mail: fsarac75@gmail.com ORCID ID: orcid.org/0000-0003-0894-7787 Received/Gelifl­Tarihi:­5 April 2017 Ac­cep­ted/Ka­bul­Ta­ri­hi:­12 April 2017 Deneysel Testis Torsiyonunda İrisin ve Visfatin’in Tanısal Değeri
Evaluating the quality of in-service trainings for employees of Islamic Azad University (Buin- Zahra Branch) using CIPP model

Article history: Received June 22, 2013 Received in revised format 28 August 2013 Accepted 15 September 2013 Available online September 17 2013 This research aims to evaluate the quality of the in-service trainings for the employees of Islamic Azad University (Buin-Zahra Branch) using CIPP model in 2013. Statistical population of the research includes all employees who participated in in-service trainings from 2003 to 2012. Cronbach's alpha was used as one of the methods for evaluating the reliability in this research, and the reliability coefficient in case of the mentioned questionnaire was obtained as 0.80. Moreover, the study used structural equation modeling in order to assess the reliability of the questionnaire, while this method confirmed its reliability. Besides, content validity and construct validity methods have been used to examine the validity of the questionnaire, and the results confirmed the validity of the mentioned questionnaire. Then, the obtained data of the questionnaire were analyzed using SPSS, Smart PLS and LISREL software packages in two categories of descriptive and inferential section. The results of the analysis show that the dimensions of context, input, process, and product are at a desirable level for the in-service trainings of employees in Islamic Azad University (Buin-Zahra Branch). Additionally, the findings show that there was a significant relationship between the different dimensions of the quality evaluation of the in-service trainings of the employees of Islamic Azad University, Buin-Zahra Branch.
Measurements of Ultra-Shallow Junction (USJ) Sheet Resistance with a Non-Penetrating Four Point Probe

An accurate method to measure the four point probe (4PP) sheet resistance (Rs) of USJ Source-Drain structures is described. The new method utilizes Elastic Material probes (EM- probe) to form non-penetrating contacts to the silicon surface. The probe design is kinematic and the force is controlled to ensure elastic deformation of the probe material. The probe material is selected so that large direct tunneling currents can flow through the native oxide thereby forming a low impedance contact. Sheet resistance measurements on USJ implanted P+/N structures with SIMS junction depths as shallow as 15 nm have been measured. The sheet resistance values obtained with the new EM-probe 4PP method were found to be consistent with expectations. In this paper, the method will be demonstrated on a variety of implanted USJ structures.
A Variational Bayesian Algorithm for Clustering of Large and Complex Networks

We propose the Blockloading algorithm for the clustering of large and complex graphs with tens of thousands of vertices according to a Stochastic Block Model (SBM). Blockloading is based on generalized Variational Bayesian EM (VBEM) schemes and works for weighted and unweighted graphs. Existing Variational (Bayesian) EM methods have to consider each possible number of clusters sepa- rately to determine the optimal number of clusters and are prone to converge to local optima making multiple restarts necessary. These factors impose a severe restriction on the size and complexity of graphs these methods can handle. In con- trast, the Blockloading algorithm restricts restarts to subnetworks in a way that provides error correction of an existing cluster assignment. The number of clusters need not be specified in advance because Blockloading will return it as a result. We show that Blockloading outperforms all other variational methods regarding reliability of the results and computational efficiency.
Small-Scale Irrigation, Farm Income and Access to Essential Services in the Busa Community of the Upper West Region of Ghana

The worsening poverty situation in the Upper West Region of Ghana coupled with the risky nature of farming due to the joint impacts of rain-fed dependence and minimal use of irrigation in Ghana called for the need to examine small-scale irrigation usage and its effect on farmers’ income and access to essential services. The study was carried out in Busa where 300 farmers were randomly sampled. The Conditional Recursive Mixed-Processes (CRMP) was used to estimate two Probit and a multiple linear regression models. The study revealed that market information and participation as well as input cost affected farmers’ decision to use irrigation. Also, irrigation usage, market participation and price information, capital invested and institutional support had significant effects on farm income. However, occupation, farmers’ educational attainment and incomes were the significant determinants of access-to-essential services in this area. Hence, irrigation is relevant to promoting farm income in the area since its use translate into increased income. Farmers in the area would minimize production costs and risks when encouraged or motivated to initiate or participate in small-scale irrigation since such schemes are not cost and technically intensive. Keywords : Access to Essential Services, Conditional Recursive Mixed-Processes, Farm Income, Regression, Small-Scale Irrigation
Maximum Power Point Tracking for Photovoltaic Systems under Partial Shading Conditions Using Bat Algorithm

The vibrant, noiseless, and low-maintenance characteristics of photovoltaic (PV) systems make them one of the fast-growing technologies in the modern era. This on-demand source of energy suffers from low-output efficiency compared with other alternatives. Given that PV systems must be installed in outdoor spaces, their efficiency is significantly affected by the inevitable complication called partial shading (PS). Partial shading occurs when different sections of the solar array are subjected to different levels of solar irradiance, which then leads to a multiple-peak function in the output characteristics of the system. Conventional tracking techniques, along with some nascent/novel approaches used for the tracking maximum power point (MPP), are unsatisfactory when subjected to PS, eventually leading to the reduced efficiency of the PV system. This study aims at investigating the use of the bat algorithm (BA), a nature-inspired metaheuristic algorithm for MPP tracking (MPPT) subjected to PS conditions. A brief explanation of the behavior of the PV system under the PS condition and the advantages of using BA for estimating the MPPT of the PV system under PS condition is discussed. The deployment of the BA for the MPPT in PV systems is then explained in detail highlighting the simulation results which verifies whether the proposed method is faster, more efficient, sustainable and more reliable than conventional and other soft computing-based methods. Three testing conditions are considered in the simulation, and the results indicate that the proposed technique has high efficiency and reliability even when subjected to an acute shading condition.
Automatic Resonance Tuning and Feedforward Learning of Biped Walking using Adaptive Oscillators

In this contribution, we propose a novel approach to achieve two fundamental features of adaptive control in rhythmic movements: The automatic locking of the controller to the system’s resonance frequency, and the progressive transfer from feedback to feedforward control. This is realized by using adaptive oscillators, i.e. mathematical tools capable of synchronizing to a periodic input and learning this input’s main features (frequency, amplitude). In particular, these concepts are illustrated here on a simulated walking task. Automatic resonance tuning emerges from the interaction between the plant (the biped walker), the controller, and the movement phase directly estimated by the adaptive oscillator. Progressive transfer to feedforward control is realized by learning the control pattern (initially provided by the feedback controller) with local filters. In conclusion, this paper illustrates to potential relevance of using adaptive oscillators as central elements in adaptive control of rhythmic tasks.