Miracle-dz/UniFAR-FTUs huggingface dataset:
APEX Introspection APEX Policy Engine APEX State Application OpenMP Runtime Synchronous Asynchronous Triggered

Power is the most critical resource for the exascale high performance computing. In the future, system administrators might have to pay attention to the power consumption of the machine under different work loads. Hence, each application may have to run with an allocated power budget. Thus, achieving the best performance on future machines requires optimal performance subject to a power constraint. This additional performance requirement should not be the responsibility of HPC (High Performance Computing) application developers. Optimizing the performance for a given power budget should be the responsibility of high-performance system software stack. Modern machines allow power capping of CPU and memory to implement power budgeting strategy. Finding the best runtime environment for a node at a given power level is important to get the best performance. This paper presents ARCS (Adaptive Runtime Configuration Selection) framework that automatically selects the best runtime configuration for each OpenMP parallel region at a given power level. The framework uses OMPT (OpenMP Tools) API, APEX (Autonomic Performance Environment for eXascale), and Active Harmony frameworks to explore configuration search space and selects the best number of threads, scheduling policy, and chunk size for a given power level at run-time. We test ARCS using the NAS Parallel Benchmark, and proxy application LULESH with Intel Sandybridge, and IBM Power multi-core architectures. We show that for a given power level, efficient OpenMP runtime parameter selection can improve the execution time and energy consumption of an application up to 40% and 42% respectively.
Factors Associated with Knowledge of Diabetes in Patients with Type 2 Diabetes Using the Diabetes Knowledge Test Validated with Rasch Analysis

Objective In patients with Type 2 diabetes, to determine the factors associated with diabetes knowledge, derived from Rasch analysis, and compare results with a traditional raw scoring method. Research Design & Methods Participants in this cross-sectional study underwent a comprehensive clinical and biochemical assessment. Diabetes knowledge (main outcome) was assessed using the Diabetes Knowledge Test (DKT) which was psychometrically validated using Rasch analysis. The relationship between diabetes knowledge and risk factors identified during univariate analyses was examined using multivariable linear regression. The results using raw and Rasch-transformed methods were descriptively compared. Results 181 patients (mean age±standard deviation = 66.97±9.17 years; 113 (62%) male) were included. Using Rasch-derived DKT scores, those with greater education (β = 1.14; CI: 0.25,2.04, p = 0.013); had seen an ophthalmologist (β = 1.65; CI: 0.63,2.66, p = 0.002), and spoke English at home (β = 1.37; CI: 0.43,2.31, p = 0.005) had significantly better diabetes knowledge than those with less education, had not seen an ophthalmologist and spoke a language other than English, respectively. Patients who were members of the National Diabetes Service Scheme (NDSS) and had seen a diabetes educator also had better diabetes knowledge than their counterparts. Higher HbA1c level was independently associated with worse diabetes knowledge. Using raw measures, access to an ophthalmologist and NDSS membership were not independently associated with diabetes knowledge. Conclusions Sociodemographic, clinical and service use factors were independently associated with diabetes knowledge based on both raw scores and Rasch-derived scores, which supports the implementation of targeted interventions to improve patients' knowledge. Choice of psychometric analytical method can affect study outcomes and should be considered during intervention development.
Predicting translational diffusion of evolutionary conserved RNA structures by the nucleotide number

Ribonucleic acids are highly conserved essential parts of cellular life. RNA function is determined to a large extent by its hydrodynamic behaviour. The presented study proposes a strategy to predict the hydrodynamic behaviour of RNA single strands on the basis of the polymer size. By atom-level shell-modelling of high-resolution structures, hydrodynamic radius and diffusion coefficient of evolutionary conserved RNA single strands (ssRNA) were calculated. The diffusion coefficients D of 17–174 nucleotides (nt) containing ssRNA depended on the number of nucleotides N with D = 4.56 × 10−10 N−0.39 m2 s−1. The hydrodynamic radius RH depended on N with RH = 5.00 × 10−10 N0.38 m. An average ratio of the radius of gyration and the hydrodynamic radius of 0.98 ± 0.08 was calculated in solution. The empirical law was tested by in solution measured hydrodynamic radii and radii of gyration and was found to be highly consistent with experimental data of evolutionary conserved ssRNA. Furthermore, the hydrodynamic behaviour of several evolutionary unevolved ribonucleic acids could be predicted. Based on atom-level shell-modelling of high-resolution structures and experimental hydrodynamic data, empirical models are proposed, which enable to predict the translational diffusion coefficient and molecular size of short RNA single strands solely on the basis of the polymer size.
Low-Dimensional Projection of Reactive Islands in Chemical Reaction Dynamics Using a Supervised Dimensionality Reduction Method

Transition state theory is a standard framework for predicting the rate of a chemical reaction. Although the transition state theory has been successfully applied to numerous chemical reaction analyses, many experimental and theoretical studies have reported chemical reactions with a reactivity which cannot be explained by the transition state theory due to dynamic effects. Dynamical systems theory provides a theoretical framework for elucidating dynamical mechanisms of such chemical reactions. In particular, reactive islands are essential phase space structures revealing dynamical reaction patterns. However, the numerical computation of reactive islands in a reaction system of many degrees of freedom involves an intrinsic challenge -- the curse of dimensionality. In this paper, we propose a dimensionality reduction algorithm for computing reactive islands in a reaction system of many degrees of freedom. Using the supervised principal component analysis, the proposed algorithm projects reactive islands into a low-dimensional phase space with preserving the dynamical information on reactivity as much as possible. The effectiveness of the proposed algorithm is examined by numerical experiments for H\'enon-Heiles systems extended to many degrees of freedom. The numerical results indicate that our proposed algorithm is effective in terms of the quality of reactivity prediction and the clearness of the boundaries of projected reactive islands. The proposed algorithm is a promising elemental technology for practical applications of dynamical systems analysis to real chemical systems.
Robust far-field speaker identification under mismatched conditions

While speaker identification performance has improved dramatically over the past years, the presence of interfering noise and the variety of channel conditions pose a major obstacle. Particularly the mismatch between training and test condition leads to severe performance degradations. In this paper we investigate speaker identification based on data simultaneously recorded with multiple microphones in a farfield setup under different noise and reverberation conditions. Dramatic performance degradation is observed, especially when training and test conditions mismatch. To address this mismatch we apply our robust frame-based score competition approach in which we combine and compete models trained on multiple conditions. To further improve this approach we add simulated, i.e. artificially created training data on a variety of noise conditions for additional model training. Our experimental results show that the extended approach significantly improves speaker identification performance under adverse and mismatching conditions.
A Critique of the Community of Inquiry Framework.

This conceptual paper critiques the popular Community of Inquiry (CoI) framework that is widely used for studying text-based asynchronous online discussion. It re-examines the three main aspects of the CoI framework (cognitive presence, social presence, and teaching presence) and their relationship, and further highlights the specificity and complexity of online discussion forums. The paper argues that CoI underestimates the complex multi-functionality of communicative acts which often combine instruction, knowledge construction, and social interaction in a single utterance. It clarifies the confused relation of cause and effect in the CoI framework and specifies the leadership functions of teaching presence and how they are intertwined with the social and cognitive functions. It argues that social presence goes beyond a mere aspect or component of online discussion; it is the backdrop of everything that goes on. All online utterances are inherently social despite of their apparent intention. The relatively unstructured nature of intellectual engagement is contrasted with the four-stage cognitive development assumed by the CoI framework. The concept of a specifically communicative level of analysis is introduced and a game metaphor and Gadamer’s notion of a “fusion of horizons” employed to explain its workings in online discussion forums. Resume Cette etude theorique critique le populaire cadre de reference sur le Community of Inquiry (CoI) qui est largement utilise pour l’etude des discussions asynchrones en ligne a base de texte. Celle-ci reexamine les trois volets principaux du cadre de reference CoI (presence cognitive, presence sociale et presence enseignante) ainsi que la relation entre ceux-ci. Elle met aussi en lumiere la specificite et la complexite des forums de discussion en ligne. L’article avance que le CoI sous-estime la multifonctionnalite complexe des actions communicatives qui font souvent simultanement appel a l’instruction, la construction du savoir et l’interaction sociale a chaque fois qu’on fait un enonce. L’article clarifie la relation parfois floue entre la cause et l’effet dans le cadre de reference CoI et precise les fonctions de leadership qui sont attribuables a la presence enseignante, ainsi que comment ces fonctions sont entrelacees avec les fonctions sociales et cognitives. L’article avance aussi que la presence sociale est plus qu’un simple aspect ou une simple composante de la discussion en ligne; elle est la trame de fond de tout ce qui se passe. Malgre leur apparente intention, tous les enonces faits en ligne ont par nature un caractere social. On fait la differenciation entre la nature plutot non structuree de l’implication intellectuelle et le developpement cognitif en quatre etapes adopte par le cadre de reference CoI. On presente la notion d’un niveau d’analyse specifiquement communicatif et on emploie une metaphore de jeu ainsi que la notion de « fusion des horizons » de Gadamer pour expliquer les rouages de cette notion dans le cadre de forums de discussion.
Efficient Large-Scale Service Clustering via Sparse Functional Representation and Accelerated Optimization

Clustering techniques offer a systematic approach to organize the diverse and fast increasing Web services by assigning relevant services into homogeneous service communities. However, the ever increasing number of Web services poses key challenges for building large-scale service communities. In this paper, we tackle the scalability issue in service clustering, aiming to accurately and efficiently discover service communities over very large-scale services. A key observation is that service descriptions are usually represented by long but very sparse term vectors as each service is only described by a limited number of terms. This inspires us to seek a new service representation that is economical to store, efficient to process, and intuitive to interpret. This new representation enables service clustering to scale to massive number of services. More specifically, a set of anchor services are identified that allows each service to represent as a linear combination of a small number of anchor services. In.
Kaiser filter for antialiasing in digital photogrammetry

Image aliasing is a problem appearing as artefacts in digitally resampled images, which degrades the quality of the image. In digital rectification and texture mapping, pixels from an input image are transformed to pixels of an output image. The discrete nature of a digital image causes aliasing in the transformed image. In this paper the source of aliasing and the theory of antialiasing are described. The necessity of a precise filter design in antialiasing is discussed and a filter based on a Kaiser adjustable window is designed. Different practical antialiasing methods are described as well as interpolation methods, which are conventional in photogrammetry. Selected antialiasing methods are implemented and applied to a close range image. An objective analysis is carried out by applying inverse transformations to rectified images and deriving some measures to estimate the information loss for each method by comparing original and reconstructed images. Results indicate that interpolation methods are not capable of removing or reducing aliasing in highly decimating transformations. The output images of interpolation methods therefore suffer from edge corruption and interfusion of small features. Applying a Kaiser filter with a precise antialiasing method results in the least information loss and considerably reduces aliasing at the expense of higher computation load.
Optimal trajectories for multi robot localization

This paper considers the problem of multi robot localization. The analysis is focused on the problem of determining which are the optimal robot trajectories in order to minimize the localization error at the final robot configurations. Furthermore, the analysis takes into account several constraints expressing the maximum robot energy consumption. The problem is formulated as an optimal control problem. For the special case of holonomic vehicles, an analytical solution is derived. In particular, this solution satisfies second order differential equations. The trajectories corresponding to this optimal control are plotted for different initial and final robot configurations and for several values of the system parameters (characterizing the precision of the robot sensors and the values of the constraints). Extensive simulations validate the derived analytical results.
Missense variants in the X‐linked gene PRPS1 cause retinal degeneration in females

Retinal dystrophies are a heterogeneous group of disorders of visual function leading to partial or complete blindness. We report the genetic basis of an unusual retinal dystrophy in five families with affected females and no affected males. Heterozygous missense variants were identified in the X‐linked phosphoribosyl pyrophosphate synthetase 1 (PRPS1) gene: c.47C > T, p.(Ser16Phe); c.586C > T, p.(Arg196Trp); c.641G > C, p.(Arg214Pro); and c.640C > T, p.(Arg214Trp). Missense variants in PRPS1 are usually associated with disease in male patients, including Arts syndrome, Charcot–Marie–Tooth, and nonsyndromic sensorineural deafness. In our study families, affected females manifested a retinal dystrophy with interocular asymmetry. Three unrelated females from these families had hearing loss leading to a diagnosis of Usher syndrome. Other neurological manifestations were also observed in three individuals. Our data highlight the unexpected X‐linked inheritance of retinal degeneration in females caused by variants in PRPS1 and suggest that tissue‐specific skewed X‐inactivation or variable levels of pyrophosphate synthetase‐1 deficiency are the underlying mechanism(s). We speculate that the absence of affected males in the study families suggests that some variants may be male embryonic lethal when inherited in the hemizygous state. The unbiased nature of next‐generation sequencing enables all possible modes of inheritance to be considered for association of gene variants with novel phenotypic presentation.
Semantic Retrieval Based on SPARQL and Fuzzy Ontology for Electronic Commerce

Information retrieval is the important work for Electronic Commerce. Ontology-based semantic retrieval is a hotspot of current research. In order to achieve fuzzy semantic retrieval, this paper proposes an approach using Resource Description Framework (RDF) and fuzzy ontology. First, we apply RDF data model to represent e-commerce information on the Semantic Web. Then, introducing new data type referred as fuzzy linguistic variables to RDF data model, the semantic query expansion in SPARQL query language is constructed by order relation, equivalence relation and inclusion relation between fuzzy concepts defined in linguistic variable ontologies. Examples show that this research facilitates the semantic retrieval through fuzzy concepts for Electronic Commerce on the Semantic Web.
Intensity-Based Visual Servoing for Instrument and Tissue Tracking in 3D Ultrasound Volumes

This paper presents a three dimensional ultrasound (3DUS)-based visual servoing technique for intraoperative tracking of the motion of both surgical instruments and tissue targets. In the proposed approach, visual servoing techniques are used to control the position of a virtual ultrasound probe so as to keep a target centered within the virtual probe's field-of-view. Multiple virtual probes can be servoed in parallel to provide simultaneous tracking of instruments and tissue. The technique is developed in the context of robotic beating-heart intracardiac surgery in which the goal of tracking is to both provide guidance to the operator as well as to provide the means to automate the surgical procedure. To deal with the low signal-to-noise ratio (SNR) of the 3DUS volumes, an intensity-based method is proposed that requires no primitive extraction or image segmentation since it directly utilizes the image intensity information as a visual feature. This approach is computationally efficient and can be applied to a wide range of tissue types and medical instruments. This paper presents the first validation of these techniques through offline robot and tissue tracking using actual in vivo cardiac volume sequences from a robotic beating-heart surgery.
Using Subjectivity Analysis to Improve the Precision of Information Extraction System – A Review

— “Information Extraction” systems, face a crucial problem of false hits because of a number of reasons, observations show that a large number of these false hits are due to the presence of subjectivity in the text. This observation motivates the exploration of the notion of using subjectivity analysis to decrease the number of false hits by the Information Extraction systems. “Subjectivity Analysis” system is the one which identifies and extracts information related to opinions, attitudes and sentiments from the text. This paper presents a review on the method of subjectivity analysis, and then using its results to improve precision of information extraction system.
Signed poisson map for shape analysis

Statistical shape analysis is a widely studied topic with applications ranging in biology, anatomy, neuroscience, agriculture, paleontology, etc. In many cases, two sets of shapes are input to the algorithm and the output is a mean shape with a scalar map defined on it indicating the local discrepancy between the two groups. In this work, we propose a new shape analysis algorithm. It is able to handle shapes with arbitrary topology. Specifically, the algorithm constructs a Signed Poisson Map (SPM) by solving two Poisson equations on the volumetric shapes, and statistical analysis is then carried out on the SPMs. The algorithm is tested on both synthetic and real shape data sets.
Uniting the Quiescent Emission and Burst Spectra of Magnetar Candidates

Spectral studies of quiescent emission and bursts of magnetar candidates based on XMM-Newton, Chandra, and Swift data are presented. Spectra of both the quiescent emission and the burst for most magnetar candidates are reproduced by a photoelectrically absorbed two-blackbody function (2BB). There is a strong correlation between the lower and higher temperatures of 2BB (kTLT and kTHT) for the magnetar candidates of which the spectra are well reproduced by 2BB. In addition, a square of radius for kTLT (R 2 LT ) is well correlated with a square of radius for kTHT (R 2 ). The ratio kTLT =kTHT � 0.4 is nearly constant irrespective of the objects and/or emission types (i.e., the quiescent emission and the burst). This would imply that an emission mechanism is common among the magnetar candidates. The relation between the quiescent emission and the burst might be analogous to a relation between the solar microflare and the solar flare. Three anomalous X-ray pulsars (AXPs) (4U 0142+614, 1RXS J170849.0� 400910, and 1E 2259+586) seem to have an excess above � 7 keV, which well agrees with a nonthermal hard component discovered by the International Gamma-Ray Astrophysics Laboratory (INTEGRAL).
Deployment of One-Sided Communication Technique for Parallel Computing in Katsevich CT Image Reconstruction

This paper focuses on the implementation of parallel approach of Katsevich CT image reconstruction algorithm using one-sided communication technique. One-sided communication is a new feature provided by MPI-2 standard. It natively supports new network techniques such as InfiniBand and Myrinet. In this project, we implement three kinds of one-sided approaches for Katsevich algorithm. The results are compared the other P2P models on the performance metrics speedup, efficiency, and cost
Remarks on Superenergy Tensors

We define super-energy tensors for arbitrary physical fields, including the gravitational, electromagnetic and massless scalar fields. We also define super-super-energy tensors, and so on. All these tensors satisfy the so-called "Dominant Superenergy Property" among other interesting and good properties. The possibility of interchange of superenergy between gravitational and other fields is considered.
Axon Branching Requires Interactions between Dynamic Microtubules and Actin Filaments

Cortical neurons innervate many of their targets by collateral axon branching, which requires local reorganization of the cytoskeleton. We coinjected cortical neurons with fluorescently labeled tubulin and phalloidin and used fluorescence time-lapse imaging to analyze interactions between microtubules and actin filaments (F-actin) in cortical growth cones and axons undergoing branching. In growth cones and at axon branch points, splaying of looped or bundled microtubules is accompanied by focal accumulation of F-actin. Dynamic microtubules colocalize with F-actin in transition regions of growth cones and at axon branch points. In contrast, F-actin is excluded from the central region of the growth cone and the axon shaft, which contains stable microtubules. Interactions between dynamic microtubules and dynamic actin filaments involve their coordinated polymerization and depolymerization. Application of drugs that attenuate either microtubule or F-actin dynamics also inhibits polymerization of the other cytoskeletal element. Importantly, inhibition of microtubule or F-actin dynamics prevents axon branching but not axon elongation. However, these treatments do cause undirected axon outgrowth. These results suggest that interactions between dynamic microtubules and actin filaments are required for axon branching and directed axon outgrowth.