Miracle-dz/UniFAR-FTUs huggingface dataset:
Workload characterization for trend analysis

The methodology of analysis proposed in this paper aims at predicting the workload of a computer. This methodology consists of applying an algorithm of clustering to the workload, its jobs being identified by a pair (X,P), where X is the resource-vector of the job and P stands for the priority given to the job by the user.The hereby obtained clusters are then associated to the ai activities developed in the system and determine the influence of each ai to the overall workload. By repeating this operation at different times, either the periodicity or the monotonic changes that may occur in each activity are determined. This makes it possible to predict the evolution of the overall workload and consequently to evaluate changes to be carried out in the system.The above methodology is applied to a specific case and is illustrated in its various phases. The results obtained have validated the method. The study is still going on, with continuous periodical observations in order to update the data.
A mechanism for parallel electric field generation in the MHD limit: possible implications for the coronal heating problem in the two stage mechanism

Context. Using Particle-In-Cell simulations i.e. in the kinetic plasma description, the discovery of a new mechanism of parallel electric field generation was recently reported. Aims. We show that the electric field generation parallel to the uniform unperturbed magnetic field can be obtained in a much simpler framework using the ideal magnetohydrodynamics (MHD) description. Methods. We solve numerically ideal, 2.5D, MHD equations in Cartesian coordinates, with a plasma beta of 0.0001 starting from the equilibrium that mimics a footpoint of a large curvature radius, solar coronal loop or a polar region plume. On top of such an equilibrium, a purely Alfvenic, linearly polarised, plane wave is launched. Results. In ideal MHD the electric field parallel to the uniform unperturbed magnetic field appears due to fast magnetosonic waves which are generated by the interaction of weakly non-linear Alfven waves with the transverse density inhomogeneity. In the context of the coronal heating problem a new two stage mechanism of plasma heating is presented by putting emphasis, first, on the generation of parallel electric fields within an ideal MHD description directly, rather than focusing on the enhanced dissipation mechanisms of the Alfven waves and, second, dissipation of these parallel electric fields via kinetic effects. It is shown that for a single Alfven wave harmonic with frequency v = 7 Hz and longitudinal wavelength λ A = 0.63 Mm, and a putative Alfven speed of 4328 km s -1 , the generated parallel electric field could account for 10% of the necessary coronal heating requirement. It is also shown that the amplitude of the generated parallel electric field exceeds the Dreicer electric field by about four orders of magnitude, which implies realisation of the run-away regime with associated electron acceleration. Conclusions. We conjecture that wide spectrum (10 -4 -10 3 Hz) Alfven waves, based on the observationally constrained spectrum, could provide the necessary coronal heating requirement. The exact amount of energy that could be deposited by such waves through our mechanism of parallel electric field generation can only be calculated once a more complete parametric study is done. Thus, the "theoretical spectrum" of the energy stored in parallel electric fields versus frequency needs to be obtained.
Enabling Testing of Android Apps

Existing approaches for automated testing of An- droid apps are designed to achieve different goals and exhibit some pros and cons that should be carefully considered by developers and testers. For instance, random testing (RT) provides a high ratio of infeasible inputs or events, and test cases generated with RT and systematic exploration-based testing (SEBT) are not representative of natural (i.e., real) application usage scenarios. In addition, collecting test scripts for automated testing is expensive. We address limitations of existing tools for GUI-based testing of Android apps in a novel hybrid approach called T+. Our approach is based on a novel framework, which is aimed at generating actionable test cases for different testing goals. The framework also enables GUI-based testing without expensive test scripts collection for the stakeholders.
A modified clipping algorithm for reduction of PAPR in OFDM systems

In the present scenario, orthogonal frequency division multiplexing (OFDM) systems are greatly utilized in multimedia applications due to their robustness to frequency selective fading channels. OFDM forms the basis for various wireless standards due to its high data rate achieving potential and high spectral efficiency. Despite these advantages, the challenge faced in implementing OFDM system, is high peak to average power ratio (PAPR) that degrades the system performance. To overcome the problem of PAPR, a modified clipping algorithm is proposed in this paper. In the present scheme, successive peaks are clipped adaptively. The complementary cumulative distribution function (CCDF) and the bit error rate (BER) performance for the present scheme are analyzed. The simulation results reveal that appreciable reduction in PAPR of around 4dB may be obtained in the proposed technique.
Intensive lifestyle intervention provides rapid reduction of serum fatty acid levels in women with severe obesity without lowering omega‐3 to unhealthy levels†

Serum fatty acid (FA) levels were monitored in women with severe obesity during intensive lifestyle intervention. At baseline, total FA levels and most individual FAs were elevated compared to a matching cohort of normal and overweight women (healthy controls). After 3 weeks of intensive lifestyle intervention, total level was only 11–12% higher than in the healthy controls and with almost all FAs being significantly lower than at baseline, but with levels of omega‐3 being similar to the healthy controls. This is contrary to observations for patients subjected to bariatric surgery where omega‐3 levels dropped to levels significantly lower than in the lifestyle patients and healthy controls. During the next 3 weeks of treatment, the FA levels in lifestyle patients were unchanged, while the weight loss continued at almost the same rate as in the first 3 weeks. Multivariate analysis revealed that weight loss and change of serum FA patterns were unrelated outcomes of the intervention for lifestyle patients. For bariatric patients, these processes were associated probably due to reduced dietary input and increased input from the patients’ own fat deposits, causing a higher rate of weight loss and simultaneous reduction of the ratio of serum eicosapentaenoic to arachidonic acid.
Macrophage receptors for lumican. A corneal keratan sulfate proteoglycan.

PURPOSE Keratan sulfate proteoglycans (KSPGs) of the cornea exhibit a characteristic change in glycosylation resulting from stromal inflammation and scarring. To examine potential roles for these molecules in the pathobiology of the cornea, the authors investigated interaction of inflammatory macrophages with KSPGs in vitro. METHODS Attachment and spreading of mouse peritoneal macrophages were examined on surfaces coated with corneal proteoglycans, intact or with modified glycosylation. Solution-phase interactions were demonstrated using soluble proteoglycans labeled with 125I-Iodine or with fluorescein. The affinity and specificity of these interactions were determined by competitive inhibition with unlabeled proteoglycans. RESULTS Macrophages did not adhere to intact corneal KSPGs but did attach and spread rapidly on the lumican core protein after the removal of keratan sulfate chains. Arterial lumican, a nonsulfated form of this proteoglycan, also stimulated macrophage attachment. Labeled arterial lumican specifically bound to macrophages with high affinity. Flow cytometry demonstrated a high proportion of macrophages binding lumican. Lumican binding was inhibited by divalent cation-chelators and by polyanions. Inhibition and kinetics of lumican binding were distinct from interaction of macrophages with maleated bovine serum albumin, collagen, laminin, and fibronectin. CONCLUSIONS The highly sulfated KSPGs of cornea do not promote macrophage adhesion; however, the low-sulfate lumican present in pathologic corneas may act to localize macrophages in regions of inflammation. The lumican receptor differs from macrophage scavenger receptors and from receptors for several other extracellular matrix molecules.
Performance of Dynamic MIMO Systems in Presence of Nakagami Fading Channel

Abstract-This paper presents a new way to realize the dynamic model of MIMO channel in presence of m-Nakagami fading. The dynamic model is compared with the static model of MIMO channel and the performance analysis of SISO, SIMO, MISO and MIMO systems is evaluated in presence of m-Nakagami distribution. All the results are plotted between signal to noise ratio (SNR) and bit error rate (BER) which are well validated and in excellent agreement.
Political communication in direct democratic campaigns : enlightening or manipulating?

Political Communication: an Integrated Approach H. Kriesi The Context of the Campaigns H. Kriesi & L. Bernhard Design of the Study: an Integrated Approach R. Hanggli , C. Schemer & P. Rademacher Coalition Formation L. Bernhard & H. Kriesi Construction of the Frames R. Hanggli , L. Bernhard & H. Kriesi Message Delivery L. Bernhard Media Organizations in Direct Democratic Campaigns P. Rademacher , M. A. Gerth & G. Siegert Coverage of the Campaigns in the Media M. A. Gerth , U. Dahinden , & G. Siegert Key Factors in Frame-building R. Hanggli The Role of Predispositions H. Kriesi The Role of Knowledge H. Bonfadelli & T. N. Friemel When Campaign Messages meet Ideology. The Role of Arguments for Voting Behavior W. Wirth, J. Matthes , & C. Schemer The Impact of Positive and Negative Effects in Direct-Democratic Campaigns W. Wirth , C. Schemer , R. Kuhne & J. Matthes Conclusion H. Kriesi Bibliography
Educational Choices, Family Background, and Social Mobility

Education is generally considered a valuable tool to improve individual socio-economic status. In European peripheral countries, up to the late 1970s, only a small elite had access to higher education and such privilege guaranteed a comfortable socio-economic position, not only via the job market, but also by allowing the sustainability of pre-existing social links. From then on, democratization of access to higher education should have prompted a decrease in social and economic inequalities within and across countries. However, current data still reflects that, despite gained access to social uplifting tools, individuals from less favored backgrounds appear to not have been able to close the various gaps separating them from the more privileged ones. In this chapter, the authors analyze recent data to characterize higher education attendance in Portugal, highlighting some factors that may still block the socio-economic improvement of the less favored students and suggesting policy measures to overcome them.
Approximation algorithm for embedding metrics into a two-dimensional space

In this paper, we present a polynomial-time approximation algorithm for computing an embedding of an arbitrary metric into a two-dimensional space. The algorithm finds an embedding whose additive distortion is at most cε*, where ε* is the smallest additive distortion possible and c is an absolute constant. To our knowledge, this is the first result of this type, i.e., it gives an algorithm that finds (approximately) optimal embedding of a given distance matrix into a fixed d-dimensional space, where d < 1 is low, under any standard definition of embedding (see Related Work).
Abstraction and Identity

and want to settle cross-sortal identity claims of the form: Both abstraction principles, however, are silent with regard to this identity - a special instance of the Caesar Problem . In what follows, we outline two distinct strategies to resolve the C-R problem . The first strategy decides such cross-abstraction identities in terms of whether or not the equivalence relations appearing on the right hand side of the abstraction principles are identical, while the second strategy settles such identities by appeal to the relevant equivalence classes. We then focus our discussion on the latter approach and offer three ways of implement- ing this strategy. Ultimately, we argue that this strategy fails, as each attempt to appeal to equivalence classes faces unsurmountable difficulties.
Meta-CASE Support for Method-Based Software Development

This paper defines the scope and context of meta-CASE technology in software engineering. It then outlines the role of meta-CASE tools in “multi-perspective software development”; that is, development in which multiple participants deploy multiple methods to specify their respective areas of concern. CONTEXT: SOFTWARE ENGINEERING Software engineering is the discipline of software development. It provides and combines (1) methods for software development, which in turn provide techniques for specification, implementation, quality assurance, coordination, management and control of development; and (2) automated tool support for many of the activities in this process. A model representing such a development process (its constituent activities and their ordering) is generally termed a software development life cycle model. As Fig. 1 illustrates, the final objective of software engineering is to produce a software artefact (application) and install it in an environment. Developers working in a particular organisation use tools based on methods to produce such an artefact. These methods support a particular software development life cycle. The software application that is produced by this process is used by application users. Fig. 1 shows these high level software development activities in this setting. Life Cycle Methods Tools Organisation Environment (Problem World) used-by S O F T W A R E method engineering & process modelling meta-CASE computer-aided software engineering
Dimensionality Reduction Evolution and Validation

In this paper, proposing visualized and quantitative evaluation methods for validation dimensionality reduction techniques performance. Four well known techniques for dimensionality reduction evaluated, verify the capacity of generating a lower dimensional chemical space with minimum information error. Real chemical database used to generate a sample with specific structure as an input to evolution process. The evaluation is performed in two ways: first visually checking the sample structure, second measuring the local and global distance based error rate that are trained on the low-dimensional data representation. All the evaluation have been done for the four dimensional reduction techniques then result shows weather "trustable" to technique that likely preserves properties with low generalization error and "Un-trustable" which does not preserve the properties.
Constructing a Cloud Computing Based Social Networks Data Warehousing and Analyzing System

The research area of Social networks analysis has been recognized as extremely time-consuming tasks as well as large storage space is always necessary in order to store the social data, especially to deal with the data in the World Wide Web. Therefore, how to design an architecture and environment for performing social networks analysis is very essential. In this paper, we proposed a data warehousing and analyzing system which is based on the concept of cloud computing. The system has also been implemented and evaluated under the proposed environment with different cloud computing approaches.
Editors' introduction: Resampling methods in econometrics

This special issue gathers a collection of articles presenting new advances in the field of resampling methods in econometrics. Both exact (Monte Carlo tests) and improved asymptotic (bootstrap) procedures are studied. A wide array of models and problems are studied: inference on nonlinear models, limited dependent variables, GMM methods, nonparametric regression, time series analysis (unit roots, cointegration, long memory), and specification tests (goodness-of-fit tests, autocorrelation tests, conditional density functions).
Dynamic Thermal Models for Human Body Dissipation

The IR emissivity of human skin is extremly high and measurements of infrared radiation emitted by the skin can be converted directly into accurate temperature value. This process is known as Body IR Thermography. Skin temperature increase associated with increased vascular flow and increased metabolism. In this paper a novel multi-resolution real-time 3D thermal imaging system as potential solution for a human body 3D thermal models standardisation is presented. The system consists of a high-resolution offline 3D scanner and a real-time low-resolution 3D scanner, both of them paired together with a thermal imaging camera. The emphasis of this paper is the presentation of the novel concept of the standardisation of human body 3D thermal models, captured by the multi-resolution real-time 3D thermal imaging system. The standardisation procedure utilises skeleton detection, skeleton transformation, mesh optimisation, and texture mapping. The presented concept enables novel and practical methods for human body 3D thermal models comparison and analysis.
Nanobelts of Semiconducting Oxides

Ultralong beltlike (or ribbonlike) nanostructures (so-called nanobelts) were successfully synthesized for semiconducting oxides of zinc, tin, indium, cadmium, and gallium by simply evaporating the desired commercial metal oxide powders at high temperatures. The as-synthesized oxide nanobelts are pure, structurally uniform, and single crystalline, and most of them are free from defects and dislocations. They have a rectanglelike cross section with typical widths of 30 to 300 nanometers, width-to-thickness ratios of 5 to 10, and lengths of up to a few millimeters. The beltlike morphology appears to be a distinctive and common structural characteristic for the family of semiconducting oxides with cations of different valence states and materials of distinct crystallographic structures. The nanobelts could be an ideal system for fully understanding dimensionally confined transport phenomena in functional oxides and building functional devices along individual nanobelts.
Reconfigurable video coding on multicore

This article provides an overview of the main objectives of the new RVC standard, with an emphasis on the features that enable efficient implementation on platforms with multiple cores. A brief introduction to the methodologies that efficiently map RVC codec specifications to multicore platforms is accompanied with an example of the possible breakthroughs that are expected to occur in the design and deployment of multimedia services on multicore platforms.
Kaldorian mechanisms of regional growth: An empirical application to the case of ALADI 1980-2007

According to Kaldor (1970), regional growth patterns arise from a cumulative causation process as broadly combining two substantial mechanisms i.e. a productivity regime, known as the “Kaldor-Verdoorn” law, and a demand regime due to the expansion of exportations. This paper attempts to assess empirically the Kaldor’s framework in characterizing economic growth for 11 ALADI countries from a panel data set over period 1980 to 2007. After having controlled industrial heterogeneity, the results are indicating the existence of two regional trends within member states, especially in terms of external demand constraint. It can be pointed out a group of countries for which the link between productivity gains and demand growth has become weaker, due to an increasing external dependence as well as a detrimental competitive position. Finally, findings are quite conclusive insofar as the existence of the Kaldorian mechanisms is corroborated in explaining trajectories of ALADI countries while both increasing returns to scale and demand led growth are seemingly playing a significant role in the region.
Simplemkl Alain Rakotomamonjy Stéphane Canu

Multiple kernel learning (MKL) aims at simultaneously learning a kernel and the associated predictor in supervised learning settings. For the support vector machine, an efficient and general multiple kernel learning algorithm, based on semi-infinite linear programming, has been recently proposed. This approach has opened new perspectives since it makes MKL tractable for large-scale problems, by iteratively using existing support vector machine code. However, it turns out that this iterative algorithm needs numerous iterations for converging towards a reasonable solution. In this paper, we address the MKL problem through a weighted 2-norm regularization formulation with an additional constraint on the weights that encourages sparse kernel combinations. Apart from learning the combination, we solve a standard SVM optimization problem, where the kernel is defined as a linear combination of multiple kernels. We propose an algorithm, named SimpleMKL, for solving this MKL problem and provide a new insight on MKL algorithms based on mixed-norm regularization by showing that the two approaches are equivalent. We show how SimpleMKL can be applied beyond binary classification, for problems like regression, clustering (one-class classification) or multiclass classification. Experimental results show that the proposed algorithm converges rapidly and that its efficiency compares favorably to other MKL algorithms. Finally, we illustrate the usefulness of MKL for some regressors based on wavelet kernels and on some model selection problems related to multiclass classification problems.
Persuasive System Design Analysis of Mobile Warning Apps for Citizens

Large-scale emergencies, such as hurricane Katrina in 2005 that also damaged large parts of New Orleans or the 2013 Central European flood, have shown the importance of an appropriate warning as well as instruction of the affected people on-site. Nowadays modern mobile devices are widely spread throughout the population in many parts of the world and apps are available for warning as well as giving advice, which have the advantage to reach citizens individually, i.e. based on their current location. However, disaster communication is prone to many kinds of biases and strong emotions such as fears, making it difficult to point the crowd in the intended direction. It is therefore all the more important that the messages are well chosen and presented to the users. Comments or feedback from the users about products or services i.e. in web stores, rating web services or app stores are a valuable source for an in-use requirement engineering. Within this paper, we will firstly analyze user comments about two of the most important mobile warning apps in Germany. Secondly, we will correlate the findings with the Persuasive System Design model as a method to design for the domain of emergency management. Based on our analysis we will discuss this approach, revealing that most importantly system trustworthiness and reliability suffer from malfunction of apps and inappropriate messages undermine a successful persuasion strategy.