Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of the use of declarative languages for enhanced embedded system software development

With the increased demand for programmability in embedded applications, the pressure for producing high performance software in a timely fashion has grown over the years. For this reason, declarative languages, as they provide more abstraction than traditional languages like Java, could be used to code embedded system applications. In this paper we present comparative results of the use of declarative languages to describe embedded applications. We designed the MP3*, an embedded application containing the IMDCT algorithm (an essential part of an MP3 player) together with an Address Book and Sokoban and Tic-tac-toe games. We coded all applications in Ocaml and Prolog to analyze the resulting abstraction and performance, and then compared them to the Java equivalent codes. For some applications, a comparison with a language that is especially oriented for embedded systems was also provided. The main objective of this study is the analysis of the abstraction level achieved with the shift from the imperative programming paradigm to the declarative paradigm, considering its impact in terms of performance and memory in the embedded systems domain.
C A ] 2 2 M ar 2 00 4 Wavelets on Fractals ∗ †

We show that there are Hilbert spaces constructed from the Hausdorff measures H on the real line R with 0 < s < 1 which admit multiresolution wavelets. For the case of the middle-third Cantor set C ⊂ [0, 1], the Hilbert space is a separable subspace of L(R, (dx)) where s = log 3 (2). While we develop the general theory of multi-resolutions in fractal Hilbert spaces, the emphasis is on the case of scale 3 which covers the traditional Cantor set C. Introducing ψ 1 (x) = √ 2χ C (3x− 1) and ψ 2 (x) = χ C (3x) − χ C (3x− 2) we first describe the subspace in L(R, (dx)) which has the following family as an orthonormal basis (ONB): ψi,j,k(x) = 2 j ψi(3 j x− k), where i = 1, 2, j, k ∈ Z. Since the affine iteration systems of Cantor type arise from a certain algorithm in R which leaves gaps at each step, our wavelet bases are in a sense gap-filling constructions. Work supported by the National Science Foundation. AMS Subject Classification: [2000] 41A15, 42A16, 42A65, 42C40, 43A65, 46L60, 47D25, 46L45.
Ventricular mass index using magnetic resonance imaging accurately estimates pulmonary artery pressure

Magnetic resonance imaging (MRI) can provide accurate anatomical measurements of the cardiac ventricles. This study investigated whether a calculated ventricular mass index (VMI) would provide an accurate means of estimating pulmonary artery pressure noninvasively, and compared the results with conventional Doppler echocardiography and invasive measurement. A total of 26 subjects referred for investigation of pulmonary hypertension were studied by MRI and echocardiography within 2 weeks of cardiac catheterisation. The correlations for mean pulmonary artery pressure were as follows: VMI (ratio of right ventricular mass over left ventricular mass) r=0.81; pulmonary artery systolic pressure (echocardiography) r=0.77. The confidence intervals for the VMI were narrower than for echocardiography. Sensitivity and specificity for pulmonary hypertension were 84 and 71% respectively for the VMI compared with 89 and 57% for echocardiography. The calculated ventricular mass index provides an accurate and practical means of estimating pulmonary artery pressure noninvasively in pulmonary hypertension and may provide a more accurate estimate than Doppler echocardiography. This may be because it reflects the right ventricular response to sustained pulmonary hypertension over a long period and is not influenced by short-term physiological variables affecting echocardiography, such as heart rate, posture, hydration status and oxygen supplementation.
An Overview of Topic Discovery in Twitter Communication through Social Media Analytics

The need for automatic methods of topic discovery in the Internet grows exponentially with the amount of available textual information. Nowadays it becomes impossible to manually read even a small part of the information in order to reveal the underlying topics. Social media provide us with a great pool of user generated content, where topic discovery may be extremely useful for businesses, politicians, researchers, and other stakeholders. However, conventional topic discovery methods, which are widely used in large text corpora, face several challenges when they are applied in social media and particularly in Twitter ‐ the most popular microblogging platform. To the best of our knowledge no comprehensive overview of these challenges and of the methods dedicated to address these challenges does exist in IS literature until now. Therefore, this paper provides an overview of these challenges, matching methods and their expected usefulness for social media analytics.
Net influx of plasma 6‐[18F]fluoro‐l‐DOPA (FDOPA) to the ventral striatum correlates with prefrontal processing of affective stimuli

Dopaminergic neurotransmission in the ventral and dorsal striatum interact with central processing of rewarding and reward‐indicating stimuli, and may affect frontocortical–striatal–thalamic circuits regulating goal‐directed behaviour. Thirteen healthy male volunteers were investigated with multimodal imaging, using the radioligand 6‐[18F]fluoro‐l‐DOPA (FDOPA) for positron emission tomography (PET) measurements of dopamine synthesis capacity, and also functional magnetic resonance imaging (fMRI) in a cognitive activation paradigm. We calculated the correlation between FDOPA net blood–brain influx (; ml/g/min) in the ventral and associative dorsal striatum and BOLD signal changes elicited by standardized affectively positive, negative and neutral visual stimuli. The magnitude of in the ventral striatum was positively correlated with BOLD signal increases in the left anterior cingulate cortex and right insular operculum elicited by positive vs. neutral stimuli, but not negative vs. neutral stimuli. In the dorsal striatum, the magnitude of was positively correlated with processing of positive and negative stimuli in the left dorsolateral prefrontal cortex. These findings suggest that dopamine synthesis capacity in the ventral striatum correlates with the attentional processing of rewarding positive stimuli in the anterior cingulate cortex of healthy subjects. Dopaminergic neurotransmission in the associative dorsal striatum has been associated previously with habit learning. The observed correlation between dopamine synthesis capacity in the dorsal striatum and BOLD signal changes in the dorsolateral prefrontal cortex suggests dopaminergic modulation of processing of emotional stimuli in brain areas associated with motor planning and executive behaviour control.
Task-level imitation learning using variance-based movement optimization

Recent advances in the field of humanoid robotics increase the complexity of the tasks that such robots can perform. This makes it increasingly difficult and inconvenient to program these tasks manually. Furthermore, humanoid robots, in contrast to industrial robots, should in the distant future behave within a social environment. Therefore, it must be possible to extend the robot's abilities in an easy and natural way. To address these requirements, this work investigates the topic of imitation learning of motor skills. The focus lies on providing a humanoid robot with the ability to learn new bi-manual tasks through the observation of object trajectories. For this, an imitation learning framework is presented, which allows the robot to learn the important elements of an observed movement task by application of probabilistic encoding with Gaussian Mixture Models. The learned information is used to initialize an attractor-based movement generation algorithm that optimizes the reproduced movement towards the fulfillment of additional criteria, such as collision avoidance. Experiments performed with the humanoid robot ASIMO show that the proposed system is suitable for transferring information from a human demonstrator to the robot. These results provide a good starting point for more complex and interactive learning tasks.
The Concept of Sustainable Strategy Implementation

The idea of sustainable development has been present in the field of management for many years, yet the challenges and rules of contemporary business mean that it remains topical. At the same time, the results of much research indicates an unsatisfactory level of execution of development concepts. Due to this, the subject of the study encompasses the implementation of the idea of sustainability in the strategy execution process, lending it a holistic and balanced nature. The purpose of the paper is an examination of the relationship between strategy implementation and the effectiveness of the strategy execution process. The relationships between the perspectives defined and results obtained by organizations were investigated. The research demonstrated the existence of a positive correlation of varied intensity. It is thus possible to identify a positive influence of the integration of the idea of sustainability with strategy execution, which is reflected in the effectiveness of activities undertaken.
Copper Nanoparticles for Printed Electronics: Routes Towards Achieving Oxidation Stability

In the past few years, the synthesis of Cu nanoparticles has attracted much attention because of its huge potential for replacing expensive nano silver inks utilized in conductive printing. A major problem in utilizing these copper nanoparticles is their inherent tendency to oxidize in ambient conditions. Recently, there have been several reports presenting various approaches which demonstrate that copper nanoparticles can resist oxidation under ambient conditions, if they are coated by a proper protective layer. This layer may consist of an organic polymer, alkene chains, amorphous carbon or graphenes, or inorganic materials such as silica, or an inert metal. Such coated copper nanoparticles enable achieving high conductivities by direct printing of conductive patterns. These approaches open new possibilities in printed electronics, for example by using copper based inkjet inks to form various devices such as solar cells, Radio Frequency Identification (RFID) tags, and electroluminescence devices. This paper provides a review on the synthesis of copper nanoparticles, mainly by wet chemistry routes, and their utilization in printed electronics.
Crystal structure of the outer membrane protease OmpT from Escherichia coli suggests a novel catalytic site

OmpT from Escherichia coli belongs to a family of highly homologous outer membrane proteases, known as omptins, which are implicated in the virulence of several pathogenic Gram‐negative bacteria. Here we present the crystal structure of OmpT, which shows a 10‐stranded antiparallel β‐barrel that protrudes far from the lipid bilayer into the extracellular space. We identified a putative binding site for lipopolysaccharide, a molecule that is essential for OmpT activity. The proteolytic site is located in a groove at the extracellular top of the vase‐shaped β‐barrel. Based on the constellation of active site residues, we propose a novel proteolytic mechanism, involving a His—Asp dyad and an Asp—Asp couple that activate a putative nucleophilic water molecule. The active site is fully conserved within the omptin family. Therefore, the structure described here provides a sound basis for the design of drugs against omptin‐mediated bacterial pathogenesis. Coordinates are in the Protein Data Bank (accession No. 1I78)
Deep web data source selection based on subject and probability model

The users wish to search for fewer data sources and retrieve better quality results, so the data source selection becomes the core technology in the deep web data integration. In the data source selection, it normally considers both the data source correlation to the user's query and the document content duplication. We propose a new two step data source selection strategy by first ranking on data source correlation, then adjusting them by document content duplication. We firstly get source correlation scores based on sample document ranks and optimizes the accuracy of correlation scores based on the subject content correlation deviation probability modeling; and finally improves the data source ranks based on the subject content duplication. The test results shows our method has a better data source selection accuracy rate and document recall rate when the data source selection is based on a few sampling documents.
One-armed oscillations in Be star discs

Aims: In this paper we study the effect of the quadrupole-term in the gravitational potential of a rotationally deformed central Be star on one armed density waves in the circumstellar disc. The aim is to explain the observed long-term violet over red (V/R) intensity variations of the double peaked Balmer emission-lines, not only in cool Be star systems, but also in the hot systems like gamma Cas. Methods: We have carried out semi-analytic and numerical studies of low-frequency one armed global oscillations in near Keplerian discs around Be stars. In these we have investigated surface density profiles for the circumstellar disc which have inner narrow low surface density or gap regions, just interior to global maxima close to the rapidly rotating star, as well as the mode inner boundary conditions. Results: Our results indicate that it is not necessary to invoke extra forces such as caused by line absorption from the stellar flux in order to explain the long-term V/R variations in the discs around massive Be stars. When there exists a narrow gap between the star and its circumstellar disc, with the result that the radial velocity perturbation is non-zero at the inner disc boundary, we find oscillation (and V/R) periods in the observed range for plausible magnitudes for the rotational quadrupole term.
Gender in Facial Representations: A Contrast-Based Study of Adaptation within and between the Sexes

Face aftereffects are proving to be an effective means of examining the properties of face-specific processes in the human visual system. We examined the role of gender in the neural representation of faces using a contrast-based adaptation method. If faces of different genders share the same representational face space, then adaptation to a face of one gender should affect both same- and different-gender faces. Further, if these aftereffects differ in magnitude, this may indicate distinct gender-related factors in the organization of this face space. To control for a potential confound between physical similarity and gender, we used a Bayesian ideal observer and human discrimination data to construct a stimulus set in which pairs of different-gender faces were equally dissimilar as same-gender pairs. We found that the recognition of both same-gender and different-gender faces was suppressed following a brief exposure of 100ms. Moreover, recognition was more suppressed for test faces of a different-gender than those of the same-gender as the adaptor, despite the equivalence in physical and psychophysical similarity. Our results suggest that male and female faces likely occupy the same face space, allowing transfer of aftereffects between the genders, but that there are special properties that emerge along gender-defining dimensions of this space.
Introduction of a Microsurgical In-Vivo Embolization-Model in Rats: The Aorta-Filter Model

Vascular thrombosis with subsequent distal embolization remains a critical event for patients. Prevention of this life-threatening event can be achieved pharmacologically or mechanically with intravascular filter systems. The ability to evaluate the risk of embolization of certain techniques and procedures in vascular and microvascular surgery, such as, tissue glue or fibrin based haemostatic agents lacks convincing models. We performed 64 microvascular anastomoses in 44 rats, including 44 micro-pore polyurethane filter-anastomoses and 20 non-filter anastomoses. The rats were re-anesthetized and the aorta was re-exposed and removed four hours, three, seven, fourteen, thirty-one days, and six months postoperatively. The specimens were examined macro- and microscopically with regard to the appearance of the vessel wall, condition of the filter and the amount of thrombembolic material. Typical postoperative histopathological changes in vessel architecture were observed. Media necrosis was the first significant change three days postoperatively. Localized intimal hyperplasia, media necrosis, increase of media fibromyocytes and adventitial hypercellularity were seen to a significant extent at day seven postoperatively. Significant neovascularization of adventitia adjacent to the filter was seen after 14 days. A significant amount of thrombotic material was seen after four hours, three and 14 days interval. Only three intravascular filters became completely occluded (6.82%). The aorta-filter-anastomosis model appeared to be a valid in-vivo model in situations at risk for thrombembolic events, for microsurgical research and allowed sensitive analysis of surgical procedures and protection of the vascularized tissue. It may be suitable for a wide range of in-vivo microvascular experiments particularly in the rat model.
Generalized Transform Analysis of Affine Processes And Asset Pricing Applications

Non-linearities are often important considerations in many applications in finance and economics such as pricing securities, computing equilibria, and conducting structural estimations. This paper generalizes the class of transform analysis for affine jump diffusions in Duffie, Pan, and Singleton (2000), which facilitates analytical treatment of a wide range of such problems. We apply our method to several examples, including option pricing, modeling nonlinear Taylor rules, modeling correlated defaults, and GMM estimation. We also provide detailed analysis of the power of our method in three concrete examples: (1) pricing defaultable bonds with statedependent recovery; (2) computing the equilibrium of a Lucas economy with non-i.i. d. trees; and (3) computing equilibrium in an economy with investors having heterogeneous beliefs about a variety of fundamentals .
The mediums and the messages: exploring the language of Islamic State media through sentiment analysis

ABSTRACT This study applies the method of sentiment analysis to the online media released by the Islamic State (IS) in order to distinguish the ways in which IS uses language within their media, and potential ways in which this language differs across various online platforms. The data used for this sentiment analysis consist of transcripts of IS-produced videos, the text of IS-produced online periodical magazines, and social media posts from IS-affiliated Twitter accounts. It was found that the language and discourse utilised by IS in their online media is of a predominantly negative nature, with the language of videos containing the highest concentration of negative sentiment. The words and phrases with the most extreme sentiment values are used as a starting point for the identification of specific narratives that exist within online IS media. The dominant narratives discovered with the aid of sentiment analysis were: 1) the demonstrated strength of the IS, 2) the humiliation of IS enemies, 3) continuous victory, and 4) religious righteousness. Beyond the identification of IS narratives, this study serves to further explore the utility of the sentiment analysis method by applying it to mediums and data that it has not traditionally been applied to, specifically, videos and magazines.
Honeypots For Cloud Computing

With the advance of internet use and the search for greater mobility, cloud computing is becoming an option for those who want to access their data and other services from anywhere . With the increased use and adoption of this technology by large companies, security has become a big issue to their growth. Cloud computing facilities (public as well as private) are becoming targets of numerous malicious attacks. In this paper, we provide a survey of cloud computing, highlighting security strategies using honeypots. We present some models of honeypots available in the literature and conclude the paper with a critical analysis.
Approximate inference for disease mapping with sparse Gaussian processes

Gaussian process (GP) models are widely used in disease mapping as they provide a natural framework for modeling spatial correlations. Their challenges, however, lie in computational burden and memory requirements. In disease mapping models, the other difficulty is inference, which is analytically intractable due to the non‐Gaussian observation model. In this paper, we address both these challenges. We show how to efficiently build fully and partially independent conditional (FIC/PIC) sparse approximations for the GP in two‐dimensional surface, and how to conduct approximate inference using expectation propagation (EP) algorithm and Laplace approximation (LA). We also propose to combine FIC with a compactly supported covariance function to construct a computationally efficient additive model that can model long and short length‐scale spatial correlations simultaneously. The benefit of these approximations is computational. The sparse GPs speed up the computations and reduce the memory requirements. The posterior inference via EP and Laplace approximation is much faster and is practically as accurate as via Markov chain Monte Carlo. Copyright © 2010 John Wiley & Sons, Ltd.
Measuring the Attack Surfaces of SAP Business Applications

Software vendors such as SAP are increasingly concerned about mitigating the security risk of their software. Code quality improvement is a traditional approach to mitigate security risk; measuring and reducing the attack surface of software is a complementary approach. In this paper, we introduce a method for measuring the attack surfaces of SAP business applications implemented in Java. We implement a tool as an Eclipse plugin to measure an SAP software system’s attack surface in an automated manner. We demonstrate the feasibility of our approach by measuring the attack surfaces of three versions of an SAP software system. SAP’s software developers can use the tool as part of the software development process to improve software quality and security. SAP’s customers can also use the tool to mitigate their security risk.
Compact Time-Domain Models of Complex RF Structures Based on the Real Eigenmodes of Segments

Wideband modeling of complex loss-free isotropic RF structures is a challenging task in electrical engineering. This paper presents a new formalism to create compact wideband equivalent models of complex RF structures. In a first step, the complex structure is partitioned into segments. On the basis of the segment's eigenmodes with either vanishing tangential electric or magnetic fields on the boundary and a correction term, systems of ordinary differential equations (ODEs) are derived. In consequence, real eigenvalue problems need to be solved for each segment in addition to the actual field distribution in the segment, which only needs to be computed for a small number of discrete frequency samples for the correction term. Linking the established ODE systems of the segments with a suitable concatenation scheme leads to an ODE system for the entire structure. This system allows the computation of complex structure responses because of transient port excitation and the determination of transient 3-D fields in the structure. As a side product, the frequency-domain transfer function of the complex structure is available. Besides the theoretical derivations, two validation examples for the time-domain scheme are presented. These examples show that the method provides a good approximation of the transient processes in the structures under consideration.