Miracle-dz/UniFAR-FTUs huggingface dataset:
Runtime monitoring of web service choreographies using streaming XML

A wide range of web service choreography constraints on the content and sequentiality of messages can be translated into Linear Temporal Logic (LTL). Although they can be checked statically on abstractions of actual services, it is desirable that violations of these specifications be also detected at runtime. In this paper, we show that, given a suitable translation of LTL formulæ into XQuery expressions, such runtime monitoring of choreography constraints is possible by feeding the trace of messages to a streaming XQuery processor. The forward-only fragment of LTL is introduced; it represents the fragment of LTL supported by available streaming engines.
Magnetism and Pressure-Induced Superconductivity of Checkerboard-Type Charge-Ordered Molecular Conductor β-(meso-DMBEDT-TTF)2X (X = PF6 and AsF6)

The metallic state of the molecular conductor β-(meso-DMBEDT-TTF)2X (DMBEDT-TTF = 2-(5,6-dihydro-1,3-dithiolo[4,5-b][1,4]dithiin-2-ylidene)-5,6-dihydro-5,6-dimethyl-1,3-dithiolo[4,5-b][1,4]dithiin, X = PF6, AsF6) is transformed into the checkerboard-type charge-ordered state at around 75–80 K with accompanying metal-insulator (MI) transition on the anisotropic triangular lattice. With lowering temperatures, the magnetic susceptibility decreases gradually and reveals a sudden drop at the MI transition. By applying pressure, the charge-ordered state is suppressed and superconductivity appears in β-(meso-DMBEDT-TTF)2AsF6 as well as in the reported β-(meso-DMBEDT-TTF)2PF6. The charge-ordered spin-gapped state and the pressure-induced superconducting state are discussed through the paired-electron crystal (PEC) model, where the spin-bonded electron pairs stay and become mobile in the crystal, namely the valence-bond solid (VBS) and the resonant valence bonded (RVB) state in the quarter-filled band structure.
A survey on user specific search using organized search history

User performs various complex operations over the web such as planning purchases, finance related work or researches. It's always easy to decompose the complex task or query into smaller ones to issue multiple queries. A web search engines play a vital role and keep the track of a user over long-time period. The primary means of accessing information online is still through keyword queries to a search engine. Organizing the user search histories is one of the way to improve the output. While searching, the search engine can keep their old queries and clicks. Grouping of related queries in the search history is useful for a variety of search engine applications. Query grouping allows the search engine to better understand a user's session and tailor that user's search experience according to their needs. In this paper, we study, analyze and review various techniques for organizing user search histories in terms of generation of query logs, query groups and their clustering and their potential.
Knowledge retrieval using hybrid semantic web search

Rapid emergence of knowledge retrieval techniques have assists in innovation especially in search engine related field. However, there is still room for improvement related to data reliability. Most knowledge on the Web is presented as natural-language text that understandable by human but difficult for computers to interpret. Therefore, Semantic Web approach is widely used to give more reliable application. This paper presents an idea of combining three concepts to enhance knowledge retrieval processes using Semantic Web technologies. Instead of using ontology and clustering/categorization alone, we are injecting user profiling concept from Relational Database (RDB) to ensure more reliable data are obtained in terms of users? perspective. The impact of Knowledge Retrieval using proposed technique will be continues in future work.
Programming Shell Scripts by Demonstration

: Command-line interfaces are heavily used by system administrators to manage computer systems. Tasks performed at a command line may often be repetitive, leading to a desire for automation. However, the critical nature of system administration suggests that humans also need to supervise an automated system’s behavior. This paper presents a programming by demonstration approach to capturing repetitive command line procedures, which is based on a machine learning technique called version space algebra. The interactive design of this learning system enables the user to supervise the system’s training process, as well as allowing the user and system to alternate control of the learned procedure’s execution.
Linked data for Open Vocabularies and HIVE’s global framework

This paper summarizes new trends and advances in Knowledge Organization from the perspective of linked open data (LOD). Although this is particularly important to galleries, libraries, archives and museums, the so-called GLAM community, it is of more general relevance, and part of the value of LOD lies in its adoption beyond that community. LOD includes descriptive metadata and vocabulary encoding schemes that are being “skosified” (encoded in the SKOS format) or rendered in OWL (the web ontology language) and made available not only “on” the web, but “for” the semantic web. The paper highlights a few exemplary initiatives in the field. The paper also introduces the HIVE ( Helping Interdisciplinary Vocabularies Engineering ) framework and discusses the HIVE-ES (Espana) extension for Spanish language vocabularies, leading to a more global approach for linked open vocabularies (LOV).
Narrowband Interference Separation for Synthetic Aperture Radar via Sensing Matrix Optimization-Based Block Sparse Bayesian Learning

High-resolution synthetic aperture radar (SAR) operating with a large bandwidth is subject to impacts from various kinds of narrowband interference (NBI) in complex electromagnetic environments. Recently, many radio frequency interference (RFI) suppression approaches for SAR based on sparse recovery have been proposed and demonstrated to outperform traditional ones in preserving the signal of interest (SOI) while suppressing the interference by exploiting their intrinsic structures. In particular, the joint recovery strategy of SOI and NBI with a cascaded dictionary, which eliminates the steps of NBI reconstruction and time-domain cancellation, can further reduce unnecessary system complexity. However, these sparsity-based approaches hardly work effectively for signals from an extended target or NBI with a certain bandwidth, since neither of them is sparse in a prescient domain. Moreover, sub-dictionaries corresponding to different components in the cascaded matrix are not strictly independent, which severely limits the performance of separated reconstruction. In this paper, we present an enhanced NBI separation algorithm for SAR via sensing matrix optimization-based block sparse Bayesian learning (SMO-BSBL) to solve these problems above. First, we extend the block sparse Bayesian learning framework to a complex-valued domain for the convenience of radar signal processing with lower computation complexity and modify it to deal with the separation problem of NBI in the contaminated echo. For the sake of improving the separated reconstruction performance, we propose a new block coherence measure by defining the external and internal block structure, which is used for optimizing the observation matrix. The optimized observation matrix is then employed to reconstruct SOI and NBI simultaneously under the modified BSBL framework, given a known and fixed cascaded dictionary. Numerical simulation experiments and comparison results demonstrate that the proposed SMO-BSBL is effective and superior to other advanced algorithms in NBI suppression for SAR.
Nanostructure patterns of piezoelectric and ferroelectric complex oxides with various shapes, obtained by natural lithography and pulsed laser deposition

A variety of patterns of well-ordered perovskite-type complex oxide nanostructures were obtained by pulsed laser deposition (PLD) on conductive single crystalline substrates through latex sphere monolayer and double-layer masks. Patterns obtained via deposition through hexagonally close packed (hcp) latex sphere monolayers include the usual arrays of hexagonally ordered nanoislands, hexagonal arrays of nanorings of much lower height coexisting with hexagonal nanoislands, hcp shell-like structures, and hexagonally interconnected nanocrown arrays. The formation of the nanopatterns depends on the ambient gas pressure during PLD, with well-separated nanoislands obtained at low pressures, and interconnected nanocrowns formed at high pressures. After annealing, the obtained BaTiO3 and SrBi2Ta2O9 nanopatterns were examined by piezoresponse force microscopy using conductive scanning probes. Under an external biasing electric field, polarization domain reversal was observed in the nanopatterns with deep submicron lateral dimensions. BaTiO3 nanocrowns ∼9 nm high are ferroelectric, while SrBi2Ta2O9 nanorings of ∼5 nm thickness show at least piezoelectric activity. In addition to the patterns of hexagonally ordered nanostructure arrays, a pattern of rhombohedrally ordered nanostructure arrays was also fabricated by deposition through latex sphere double layers.
Genetic Mapping in a Natural Population of Collared Flycatchers (Ficedula albicollis): Conserved Synteny but Gene Order Rearrangements on the Avian Z Chromosome

Data from completely sequenced genomes are likely to open the way for novel studies of the genetics of nonmodel organisms, in particular when it comes to the identification and analysis of genes responsible for traits that are under selection in natural populations. Here we use the draft sequence of the chicken genome as a starting point for linkage mapping in a wild bird species, the collared flycatcher—one of the most well-studied avian species in ecological and evolutionary research. A pedigree of 365 flycatchers was established and genotyped for single nucleotide polymorphisms in 23 genes selected from (and spread over most of) the chicken Z chromosome. All genes were also found to be located on the Z chromosome in the collared flycatcher, confirming conserved synteny at the level of gene content across distantly related avian lineages. This high degree of conservation mimics the situation seen for the mammalian X chromosome and may thus be a general feature in sex chromosome evolution, irrespective of whether there is male or female heterogamety. Alternatively, such unprecedented chromosomal conservation may be characteristic of most chromosomes in avian genome evolution. However, several internal rearrangements were observed, meaning that the transfer of map information from chicken to nonmodel bird species cannot always assume conserved gene orders. Interestingly, the rate of recombination on the Z chromosome of collared flycatchers was only ∼50% that of chicken, challenging the widely held view that birds generally have high recombination rates.
‘Spiritual Risk’: A Parental Perception of Risk for Children in the Ultra-Orthodox Jewish Community

This article addresses child protection in close-knit religious communities. Specifically, it presents the findings of a qualitative research project that examined Ultra-Orthodox Jewish parents’ perceptions and ascribed meanings of child risk and protection based on fifty in-depth interviews with parents from Israel and the USA. Here, we hone in on one key theme that emerged from our analysis of the interviews, which the interviewees themselves referred to as ‘spiritual risk’. ‘Spiritual risk’ is a complex construct comprising the following three interrelated dimensions: (i) a decline in observance of the Torah and the commandments, (ii) violation of socio-cultural norms and rules and (iii) a decline in spiritual beliefs, including the sense of connection with G-d. In the eyes of parents, it is decline in these three dimensions that constitutes the ‘spiritual risk’ to the child. ‘Spiritual risk’ can be a consequence of parental maltreatment and can result in children and adolescents moving away from the Ultra-Orthodox religious world and leaving their community. The results of this study advocate context-informed and religious-sensitive prevention and intervention programmes. They also highlight the need to include context and religious competency in the training of professionals working with diverse communities.
An improved lattice reduction aided detection scheme in MIMO systems

Multiple input multiple output(MIMO) system has been widely researched in recent years. To match high-speed data stream, detector in receiver becomes especially important. Exiting detectors, such as zero-forcing(ZF), minimum mean square error(MMSE) and maximum likelihood(ML) can not meet the demand. So lattice reduction aided detection(LRAD) has been introduced as a new type of MIMO detector. The key point of LRAD is to transform the system model into an equivalent one with better-conditioned channel matrix. As a result, LRAD can significantly improve bit error rate(BER) performance with small additional complexity in MIMO systems. But at the same time, it brings a lot of problems, such as detection signal constellation distortion and quantization error diffusion. In particular, quantization operation in LRAD is suboptimal, because the quantization operation will cause quantization error. In order to meet this challenge, this paper proposes an improved LRAD algorithm based on quantization error correction using noise prediction. The proposed algorithm correct quantization error by generating a list of candidate values from the original LRAD detected estimated values. Then the final better estimates are searched by ML criterion. Simulation results show that improved performance can be obtained, whereas additional complexity is reasonable small. The performance of the improved LRAD algorithm is shown to improve at least 0.8dB compared with conventional algorithms.
Design of a wide speed range control strategy of switched reluctance motor for electric vehicles

The electric drive system is one of the most important parts of electric vehicles (EVs), whose function is the conversion between electric energy and mechanical energy. Switched reluctance motor (SRM) has the features of simple construction, high starting torque, wide speed range, high efficiency and high reliability which are appropriate for EVs drive system. Firstly, instantaneous torque control and average torque control strategies are compared. Then the better control strategy is selected to operate SRM for a wide speed range. Three different control methods are selected to operate the SRM at different speed ranges. Turn-on and turn-off angles are regulated on-line to optimize the system efficiency. Finally, experimental results verify the correctness of the proposed control methods.
A Combined Method for Mitigating Sparsity Problem in Tag Recommendation

Tag recommendation is a specific recommendation task for recommending metadata (tag) for a web resource (item) during user annotation process. In this context, sparsity problem refers to situation where tags need to be produced for items with few annotations or for user who tags few items. Most of the state of the art approaches in tag recommendation are rarely evaluated or perform poorly under this situation. This paper presents a combined method for mitigating sparsity problem in tag recommendation by mainly expanding and ranking candidate tags based on similar items' tag and existing tag ontology. We evaluated the approach on two public social book marking datasets. The experiment results show better accuracy for recommendation in sparsity situation over several state of the art methods.
Introducing E-Learning in a Norwegian Service Company with Participatory Design and Evolutionary Prototyping Techniques

Over a 2-year period, we have participated in the introduction of e-learning in a Norwegian service company, a gas station division of an oil company. This company has an advanced computer network infrastructure for communication and information sharing, but the primary task of the employees is serving customers. We identify some challenges to introducing e-learning in this kind of environment. A primary emphasis has been on using participatory design techniques during the planning stages and evolutionary prototyping during the implementation stages. We describe a conceptual framework for analysis that takes into account technological, pedagogical and organizational factors. The data we present include interview excerpts and video recorded images and it documents the planning, implementation, and preliminary use of a moderately successful e-learning pilot system. The paper provides new insight into the successful co-existence of old and new technologies and multiple information seeking strategies.
Pointer analysis: building a foundation for effective program analysis

Pointer analysis is a fundamental enabling technology for program analysis. By improving the scalability of precise pointer analysis we can make a positive impact across a wide range of program analyses used for many different purposes, including program verification and model checking, optimization and parallelization, program understanding, hardware synthesis, and more. In this thesis we present a suite of new algorithms aimed at improving pointer analysis scalability. These new algorithms make inclusion-based analysis (the most precise flow- and context-insensitive pointer analysis) over 4× faster while using 7× less memory than the previous state-of-the-art; they also enable flow-sensitive pointer analysis to handle programs with millions of lines of code, two orders of magnitude greater than the previous state-of-the-art. We present a formal framework for describing the space of pointer analysis approximations. The space of possible approximations is complex and multidimensional, and until now has not been well-defined in a formal manner. We believe that the framework is useful as a method to meaningfully compare the precision of the multitude of existing pointer analyses, as well as aiding in the systematic exploration of the entire space of approximations.
The shape of an accretion disc in a misaligned black hole binary

We model the overall shape of an accretion disc in a semidetached binary system in which mass is transferred on to a spinning black hole the spin axis of which is misaligned with the orbital rotation axis. We assume the disc is in a steady state. Its outer regions are subject to differential precession caused by tidal torques of the companion star. These tend to align the outer parts of the disc with the orbital plane. Its inner regions are subject to differential precession caused by the Lense–Thirring effect. These tend to align the inner parts of the disc with the spin of the black hole. We give full numerical solutions for the shape of the disc for some particular disc parameters. We then show how an analytic approximation to these solutions can be obtained for the case when the disc surface density varies as a power law with radius. These analytic solutions for the shape of the disc are reasonably accurate even for large misalignments and can be simply applied for general disc parameters. They are particularly useful when the numerical solutions would be slow.
High speed image registration of head CT and MR images based on Levenberg-Marquardt algorithms

A medical image fusion technique provides insight into lesion diagnosis and spatial relationships among anatomical structures. In radiotherapy planning for CyberKnife treatment, for instance, the accurate area being irradiated is determined and calculated based on a fusion image of CT and MR images. Hence the risk of the normal tissues being irradiated could be brought down. However, commonly used mouse-based registration yields variations in the accuracy of the results due to manual operations. In addition, there are some pending issues such as the increased physical burdens to the operators and the requirement for a substantial investment of time. Therefore, in recent years many researches have attempted to automate the registration for multimodality images. In this paper, a CAD (Computer Aided Diagnosis) system is developed to assist radiotherapy planning for CyberKnife treatment. We propose a new automatic image registration technique for image fusion of head CT (Computed Tomography) and MR (Magnetic resonance) images. In our method, the minimization of ratio image uniformity and the maximization of normalized mutual information on VOIs (Volumes Of Interest) are performed based on Levenberg-Marquardt algorithm. We evaluated our proposed method by 5 clinical cases and discussed the accuracy of the registration results with computational time.
Sensing Cytosolic RpsL by Macrophages Induces Lysosomal Cell Death and Termination of Bacterial Infection

The intracellular bacterial pathogen Legionella pneumophila provokes strong host responses and has proven to be a valuable model for the discovery of novel immunosurveillance pathways. Our previous work revealed that an environmental isolate of L. pneumophila induces a noncanonical form of cell death, leading to restriction of bacterial replication in primary mouse macrophages. Here we show that such restriction also occurs in infections with wild type clinical isolates. Importantly, we found that a lysine to arginine mutation at residue 88 (K88R) in the ribosome protein RpsL that not only confers bacterial resistance to streptomycin, but more importantly, severely attenuated the induction of host cell death and enabled L. pneumophila to replicate in primary mouse macrophages. Although conferring similar resistance to streptomycin, a K43N mutation in RpsL does not allow productive intracellular bacterial replication. Further analysis indicated that RpsL is capable of effectively inducing macrophage death via a pathway involved in lysosomal membrane permeabilization; the K88R mutant elicits similar responses but is less potent. Moreover, cathepsin B, a lysosomal protease that causes cell death after being released into the cytosol upon the loss of membrane integrity, is required for efficient RpsL-induced macrophage death. Furthermore, despite the critical role of cathepsin B in delaying RpsL-induced cell death, macrophages lacking cathepsin B do not support productive intracellular replication of L. pneumophila harboring wild type RpsL. This suggests the involvement of other yet unidentified components in the restriction of bacterial replication. Our results identified RpsL as a regulator in the interactions between bacteria such as L. pneumophila and primary mouse macrophages by triggering unique cellular pathways that restrict intracellular bacterial replication.
Time series prediction and the wavelet transformS

One problem with the one step ahead prediction is the trade-oo between the noise concella-tion and the details detection. The methods proposed up to now perform a global analysis of the data and lead to missing some details (underrtting) or at the opposite including noise (overrtting). To solve this problem , we propose a preprocessing procedure inspired by the wavelet transform. This one decomposes the signal into some ltered series. Each of them is then modeled by a neural network which provides a one step prediction rule. The sum of these predictions can be seen as a prediction of the original series. Tests on sunspot data and comparison substantiate our approach.