Miracle-dz/UniFAR-FTUs huggingface dataset:
Global code motion/global value numbering

We believe that optimizing compilers should treat the machine-independent optimizations (e.g., conditional constant propagation, global value numbering) and code motion issues separately. ’ Removing the code motion requirements from the machine-independent optimization allows stronger optimizations using simpler algorithms. Preserving a legal schedule is one of the prime sources of complexity in algorithms like PRE [18, 13] or global congruence finding [2, 20].
Local Gaussian process regression for real-time model-based robot control

High performance and compliant robot control requires accurate dynamics models which cannot be obtained analytically for sufficiently complex robot systems. In such cases, machine learning offers a promising alternative for approximating the robot dynamics using measured data. This approach offers a natural framework to incorporate unknown nonlinearities as well as to continually adapt online for changes in the robot dynamics. However, the most accurate regression methods, e.g. Gaussian processes regression (GPR) and support vector regression (SVR), suffer from exceptional high computational complexity which prevents their usage for large numbers of samples or online learning to date. Inspired by locally linear regression techniques, we propose an approximation to the standard GPR using local Gaussian processes models inspired by. Due to reduced computational cost, local Gaussian processes (LGP) can be applied for larger sample-sizes and online learning. Comparisons with other nonparametric regressions, e.g. standard GPR, nu-SVR and locally weighted projection regression (LWPR), show that LGP has higher accuracy than LWPR and close to the performance of standard GPR and nu-SVR while being sufficiently fast for online learning.
GRID APPROACH TO SATELLITE MONITORING SYSTEMS INTEGRATION

This paper highlights the challenges of satellite monitoring systems integration, in particular based on Grid platform, and reviews possible solutions for these problems. We describe integration issues on different levels: data integration level and task management level (job submission in terms of Grid). We show example of described technologies for integration of monitoring systems of Ukraine (National Space Agency of Ukraine, NASU) and Russia (Space Research Institute RAS, IKI RAN). Another example refers to the development of InterGrid infrastructure that integrates several regional and national Grid systems: Ukrainian Academician Grid (with Satellite data processing Grid segment) and RSGS Grid (Chinese Academy of Sciences).
Comparison of probabilistic combination methods for protein secondary structure prediction

MOTIVATION Protein secondary structure prediction is an important step towards understanding how proteins fold in three dimensions. Recent analysis by information theory indicates that the correlation between neighboring secondary structures are much stronger than that of neighboring amino acids. In this article, we focus on the combination problem for sequences, i.e. combining the scores or assignments from single or multiple prediction systems under the constraint of a whole sequence, as a target for improvement in protein secondary structure prediction. RESULTS We apply several graphical chain models to solve the combination problem and show that they are consistently more effective than the traditional window-based methods. In particular, conditional random fields (CRFs) moderately improve the predictions for helices and, more importantly, for beta sheets, which are the major bottleneck for protein secondary structure prediction.
Ionization state, excited populations and emission of impurities in dynamic finite density plasmas: I. The generalized collisional–radiative model for light elements

The paper presents an integrated view of the population structure and its role in establishing the ionization state of light elements in dynamic, finite density, laboratory and astrophysical plasmas. There are four main issues, the generalized collisional–radiative picture for metastables in dynamic plasmas with Maxwellian free electrons and its particularizing to light elements, the methods of bundling and projection for manipulating the population equations, the systematic production/use of state selective fundamental collision data in the metastable resolved picture to all levels for collisonal–radiative modelling and the delivery of appropriate derived coefficients for experiment analysis. The ions of carbon, oxygen and neon are used in illustration. The practical implementation of the methods described here is part of the ADAS Project.
A global double‐fluorescent Cre reporter mouse

The Cre/loxP system has been used extensively for conditional mutagenesis in mice. Reporters of Cre activity are important for defining the spatial and temporal extent of Cre‐mediated recombination. Here we describe mT/mG, a double‐fluorescent Cre reporter mouse that expresses membrane‐targeted tandem dimer Tomato (mT) prior to Cre‐mediated excision and membrane‐targeted green fluorescent protein (mG) after excision. We show that reporter expression is nearly ubiquitous, allowing visualization of fluorescent markers in live and fixed samples of all tissues examined. We further demonstrate that mG labeling is Cre‐dependent, complementary to mT at single cell resolution, and distinguishable by fluorescence‐activated cell sorting. Both membrane‐targeted markers outline cell morphology, highlight membrane structures, and permit visualization of fine cellular processes. In addition to serving as a global Cre reporter, the mT/mG mouse may also be used as a tool for lineage tracing, transplantation studies, and analysis of cell morphology in vivo. genesis 45:593–605, 2007. © 2007 Wiley‐Liss, Inc.
Time-course gene profiling and networks in demethylated retinoblastoma cell line

Retinoblastoma, a very aggressive cancer of the developing retina, initiatiates by the biallelic loss of RB1 gene, and progresses very quickly following RB1 inactivation. While its genome is stable, multiple pathways are deregulated, also epigenetically. After reviewing the main findings in relation with recently validated markers, we propose an integrative bioinformatics approach to include in the previous group new markers obtained from the analysis of a single cell line subject to epigenetic treatment. In particular, differentially expressed genes are identified from time course microarray experiments on the WERI-RB1 cell line treated with 5-Aza-2′-deoxycytidine (decitabine; DAC). By inducing demethylation of CpG island in promoter genes that are involved in biological processes, for instance apoptosis, we performed the following main integrative analysis steps: i) Gene expression profiling at 48h, 72h and 96h after DAC treatment; ii) Time differential gene co-expression networks and iii) Context-driven marker association (transcriptional factor regulated protein networks, master regulatory paths). The observed DAC-driven temporal profiles and regulatory connectivity patterns are obtained by the application of computational tools, with support from curated literature. It is worth emphasizing the capacity of networks to reconcile multi-type evidences, thus generating testable hypotheses made available by systems scale predictive inference power. Despite our small experimental setting, we propose through such integrations valuable impacts of epigenetic treatment in terms of gene expression measurements, and then validate evidenced apoptotic effects.
Using MIMO Techniques to Enhance Communication Among Static and Mobile Nodes in Wireless Sensor Networks

Wireless sensor networks are evolving to hybridnetworks in which static and mobile sensor nodes cooperate in order to address challenging requirements imposed by new emerging applications. However, due to the ad hoc nature of the network and especially to resources constraints of the sensor nodes, this cooperation is not trivial, requiring a number of retransmissions thus wasting precious resources. In this paper the use of cooperative multiple input multiple output (MIMO) techniques is proposed to overcome transmission problems, ensuring a reliable and more efficient communication link with less retransmissions. Extensive simulation experiments support the proposal, and the results highlight the benefits in using MIMO to deliver messages from static to mobile nodes in wireless sensor networks.
A Decentralized and Ontology-Based Approach to Infrastructure Monitoring

We introduce infrastructure monitoring as an application domain that demands decentralized system designs. This is motivated by the large scale of these systems, the heterogeneity of components and the large number of stakeholders involved. Decentralization aggravates the issue of semantic interoperability, which we propose to tackle with a system information model based on formal ontologies. As a foundation for designing ontology-based infrastructure monitoring systems, we present a layered functional architecture and illustrate potential deployment scenarios. In particular, we detail the decentralized realization of the reasoning layer and describe an algorithm for distributed evaluation of conjunctive queries over distributed knowledge bases. A short description of the prototype implementation and first evaluation results are provided.
Partially-regular LDPC codes with linear encoding complexity and improved thresholds

We consider an ensemble of systematic low-density parity-check (LDPC) codes of length N with linear encoding complexity, i.e., with complexity O(N). We call these codes partially-regular, since they can be considered as modifications of regular LDPC codes. Further, their iterative decoding thresholds on the binary erasure channel (BEC) are found to be significantly better than the thresholds of the corresponding regular LDPC codes.
Tunable non-uniform filter bank mixing cosine modulation with perceptual frequency warping by allpas

A novel nonuniform cosine modulated filter bank is presented, mixing the concepts of warped DFT (Discrete Fourier Transform) filter bank and pseudoQMF system (Quadrature Mirror Filter). Unequal bandwidths are achieved by allpass transformation of uniform polyphase system. The cosine modulation results in real valued channel signals, and hence simplified subband processing. The considered filter bank can well approximate popular psychoacoustic scales, and moreover dynamically change its frequency characteristics. Key-words: time-frequency analysis, signal representations, filter banks, multirate processing, allpass transformation, nonuniform cosine modulated filter bank, perceptual frequency warping *) This work was supported by Białystok Technical University under the grant W/WI/3/02
Importance of promoter methylation of GATA4 gene in epithelial ovarian cancer.

AIMS Ovarian cancer is the most lethal gynecological malignancy, with typically late diagnosis. Altered DNA methylation of tumor suppressor gene promoters probably plays a relevant role in ovarian carcinogenesis and frequently occurs as an early event in the development of different types of cancer including ovarian carcinoma. GATA4 methylation has been reported in a variety of human cancers. The aim of this study was to investigate promoter methylation of the GATA4 gene in ovarian cancer by comparison with that in normal ovarian tissue. METHODS To search for promoter methylation of the GATA4 gene we used MSP (methylation-specific PCR) to compare the methylation status in 67 tissue samples of ovarian cancer with that in 40 control samples. RESULTS In our study, methylation-specific PCR revealed GATA4 promoter methylation in 21 of 67 specimens with ovarian cancer (31.3%), and in none of the control ovarian tissue samples. CONCLUSION These results confirm that methylation in the GATA4 promoter region could play an important role in ovarian carcinogenesis, and show new loci which are highly methylated only in ovarian cancer samples and which are associated predominantly with the endometrioid type of ovarian carcinoma.
Scaling factor design issues in variable step size incremental resistance MPPT in PV systems

Conventional maximum power point tracker (MPPT) uses fixed step size perturbation in order to track the maximum power point (MPP), therefore the tracking efficiency has decreased due to steady state oscillations around the MPP. Recently, many techniques have been developed proposing new approaches in the field of variable step size MPPT to overcome the shortcoming of the fixed step size techniques. These approaches update the controlling parameters adaptively using a convenient scaling factor (N) to pick the MPP. However most of them need some prior analysis in order to design the appropriate value of N, which control the hall performance of the variable step size tracker. In this paper, a new approach has proposed to design N. this approach has been develop based on the overall small signal model of the PV system around the MPP. Therefore using linear control techniques the bounded value of the scaling factor has been calculated. The validity and the feasibility of the proposed analysis have been verified using MATLAB SIMULINK toolbox, and also experimental using digital signal processor (DSP).
Features in Continuous Parallel Coordinates

Continuous Parallel Coordinates (CPC) are a contemporary visualization technique in order to combine several scalar fields, given over a common domain. They facilitate a continuous view for parallel coordinates by considering a smooth scalar field instead of a finite number of straight lines. We show that there are feature curves in CPC which appear to be the dominant structures of a CPC. We present methods to extract and classify them and demonstrate their usefulness to enhance the visualization of CPCs. In particular, we show that these feature curves are related to discontinuities in Continuous Scatterplots (CSP). We show this by exploiting a curve-curve duality between parallel and Cartesian coordinates, which is a generalization of the well-known point-line duality. Furthermore, we illustrate the theoretical considerations. Concluding, we discuss relations and aspects of the CPC's/CSP's features concerning the data analysis.
Numerical Evaluation of Information- Theoretic Measures

Information theoretic measures are of paramount importance in Bayesian inference. Yet, their direct application in practice has been somewhat limited by the severe computational diiculties encountered in complex problems. In this paper we discuss implementation strategies for fast numerical computations of Entropies and Kullback-Leibler divergences that are relevant to Bayesian inference and design problems. We illustrate the methods proposed with examples in model diagnostics and information theoretic design.
Link-based and content-based evidential information in a belief network model

This work presents an information retrieval model developed to deal with hyperlinked environments. The model is based on belief networks and provides a framework for combining information extracted from the content of the documents with information derived from cross-references among the documents. The information extracted from the content of the documents is based on statistics regarding the keywords in the collection and is one of the basis for traditional information retrieval (IR) ranking algorithms. The information derived from cross-references among the documents is based on link references in a hyperlinked environment and has received increased attention lately due to the success of the Web. We discuss a set of strategies for combining these two types of sources of evidential information and experiment with them using a reference collection extracted from the Web. The results show that this type of combination can improve the retrieval performance without requiring any extra information from the users at query time. In our experiments, the improvements reach up to 59% in terms of average precision figures.
Dynamics of implied volatility surfaces

Abstract The prices of index options at a given date are usually represented via the corresponding implied volatility surface, presenting skew/smile features and term structure which several models have attempted to reproduce. However, the implied volatility surface also changes dynamically over time in a way that is not taken into account by current modelling approaches, giving rise to `Vega' risk in option portfolios. Using time series of option prices on the SP500 and FTSE indices, we study the deformation of this surface and show that it may be represented as a randomly fluctuating surface driven by a small number of orthogonal random factors. We identify and interpret the shape of each of these factors, study their dynamics and their correlation with the underlying index. Our approach is based on a Karhunen-Loève decomposition of the daily variations of implied volatilities obtained from market data. A simple factor model compatible with the empirical observations is proposed. We illustrate how this approach models and improves the well known `sticky moneyness' rule used by option traders for updating implied volatilities. Our approach gives a justification for use of `Vega's for measuring volatility risk and provides a decomposition of volatility risk as a sum of contributions from empirically identifiable factors.
Learning language with the wrong neural scaffolding: the cost of neural commitment to sounds

Does tuning to one's native language explain the “sensitive period” for language learning? We explore the idea that tuning to (or becoming more selective for) the properties of one's native-language could result in being less open (or plastic) for tuning to the properties of a new language. To explore how this might lead to the sensitive period for grammar learning, we ask if tuning to an earlier-learned aspect of language (sound structure) has an impact on the neural representation of a later-learned aspect (grammar). English-speaking adults learned one of two miniature artificial languages (MALs) over 4 days in the lab. Compared to English, both languages had novel grammar, but only one was comprised of novel sounds. After learning a language, participants were scanned while judging the grammaticality of sentences. Judgments were performed for the newly learned language and English. Learners of the similar-sounds language recruited regions that overlapped more with English. Learners of the distinct-sounds language, however, recruited the Superior Temporal Gyrus (STG) to a greater extent, which was coactive with the Inferior Frontal Gyrus (IFG). Across learners, recruitment of IFG (but not STG) predicted both learning success in tests conducted prior to the scan and grammatical judgment ability during the scan. Data suggest that adults' difficulty learning language, especially grammar, could be due, at least in part, to the neural commitments they have made to the lower level linguistic components of their native language.
The Mediating Role of Early Maladaptive Schemas in the Relation between Quality of Attachment Relationships and Symptoms of Depression in Adolescents

Background: Quality of attachment relations between adolescents and their parents and peers may be related to early maladaptive schemas as well as to symptoms of depression. Aims: The aim of the current study was to assess whether schema domains and maladaptive schemas mediate the relation between indices of quality of attachment relationships with parents and peers and symptoms of depression in non-clinical adolescents (N = 222). Method: A battery of questionnaires was completed, including measures of quality of attachment relations, maladaptive schemas, and depression. Results: The schema domains of disconnection and rejection and other-directedness mediated the relation between quality of attachment relationships and symptoms of depression. More precisely, the schemas’ mistrust/abuse and social isolation mediated the relation between trust in parents and depressive symptoms, whereas the schemas’ social isolation and self-sacrifice mediated the relation between alienation from peers and symptoms of depression. Conclusions: The mediation analyses suggest that treatment of adolescent depression could be focused on both attachment bonds and on changing maladaptive schemas.
Simultaneous Multi-Wavelength Observations of the TeV Blazar Mrk 421 during February − March, 2003: X-Ray and NIR Correlated Variability ∗

We report the result of simultaneous multi-wavelength observations of the TeV blazar Mrk 421 during February–March 2003. We observed Mrk 421 using the Pachmarhi Array of Cerenkov Telescopes (PACT) of Tata Institute of Fundamental Research at Pachmarhi, India. Other simultaneous data were taken from the literature and public data archives. We have analyzed the high quality X-ray (2–20 keV) observations from the NASA Rossi X-Ray Timing Explorer (RXTE). We obtained a possible correlated variability between X-ray and J band (1.25 μ) near infrared (NIR) wavelength. This is the first case of X-ray and NIR correlated variability in Mrk 421 or any high energy peaked (HBL) blazar. The correlated variability reported here indicates a similar origin for the NIR and X-ray emissions. The emission is not affected much by the environment of the surrounding medium of the central engine of Mrk 421. The observations are consistent with the shock-in-jet model for the emissions.
Regularization Formulations and Numerical Solutions for Image Processing

This work is concerned both with the enhancement of bounded variation images as well as the extraction of usually smoother distributions from imaging data such as optical flows and intensity modulations. For these tasks, novel variational principles are formulated to select solutions which are preferred from an application-oriented perspective. These variational formulations are analyzed analytically and numerically, and they are efficiently implemented computationally. Specifically, formulations and discretizations of these variational principles are consistent with application requirements and free of expedient modifications such as convenient boundary conditions. Also, a geometric multigrid framework is developed for high-order optimality systems, and iterative schemes are adapted to be suitable for image processing systems used in a clinical environment.
Comparison of two bounds of the quantum correlation set

From a geometric viewpoint, quantum nonlocality between two parties is represented as the difference of two convex bodies, namely the sets of possible results of classical and quantum correlation experiments, the latter of which is called the quantum correlation set. Whereas little is known about the quantum correlation set, Tsirelson's theorem (1980) can be seen as the exact characterization of possible pairwise quantum correlations, where mean values of individual observables are discarded. In this paper, we compare two previously shown bounds of the quantum correlation set in the case where two parties have m and n choices of dichotomic observables, respectively. One bound comes from the direct application of Tsirelson's theorem and the no-signalling condition. The other bound, recently introduced by Avis, Imai and Ito, refines the application of Tsirelson's theorem in the previous bound. We show that for any m, n ges 2, this new bound is strictly tighter than the earlier bound. In other words, there are correlations that satisfy Tsirelson's theorem, but are not realizable in a quantum setting.