Miracle-dz/UniFAR-FTUs huggingface dataset:
Flexible self-healing gradients

Self-healing gradients are distributed estimates of the distance from each device in a network to the nearest device designated as a source, and are used in many pervasive computing systems. With previous self-healing gradient algorithms, even the smallest changes in the source or network can produce small estimate changes throughout the network, leading to high communication and energy costs. We observe, however, that in many applications, such as routing and geometric restriction of processes, devices far from the source need only coarse estimates, and that a device need not communicate when its estimate does not change. We have therefore developed Flex-Gradient, a new self-healing gradient algorithm with a tunable trade-off between precision and communication cost. When distance is estimated using Flex-Gradient, the constraints between neighboring devices are flexible, allowing estimates to vary by an amount proportional to a device's distance to the source. Frequent small changes in the network or source thus cause frequent estimate changes only within a distance proportional to the magnitude of the change, as verified in simulation on a network of 1000 devices. This can enable drastic reductions in the communication and energy cost of gradient-based algorithms.
The physiological demands of elite epée fencers during competition

ABSTRACT The aim of this study was to determine the physiological demands of epée fencing performance. Eight elite male epée fencers competed in a competition consisting of 7 Poule and 7 Direct Elimination (DE) fights. Core temperature (TC), heart rate (HR), movement patterns, training load, and differentiated ratings of perceived exertion (RPE) were collected for all Poule and DE fights. Expired gas, and energy expenditure (EE) were measured using breath-by-breath gas analysis during selected fights, along with blood lactate concentration. Maximal HR and RPE were greater in DE than Poule fights. There was a tendency for greater increases in TC in DE compared to Poule fights (p = 0.052). Blood lactate concentration decreased during the competition from Poule to DE suggesting reliance on phosphocreatine and aerobic energy sources during fencing. High oxygen consumption (~50 ml.kg−1.min−1) and EE (~13 kcal.min−1) were recorded in both Poule and DE. Fencers covered 3 times more distance in DE than Poule fights. High training load scores were also recorded. This is the first study to show an increased physiological strain, with high aerobic and anaerobic demands, as fencing competition progressed from Poule to DE. Additionally, there was a considerable energy demand exhibited during epée competition.
Supporting Information Molecular Dynamics Investigation of gluazo, a Photo-Switchable Ligand for the Glutamate Receptor GluK2

Supporting Information Molecular Dynamics Investigation of gluazo, a Photo-Switchable Ligand for the Glutamate Receptor GluK2 Yanan Guo, Tino Wolter, Tomáš Kubař, Martin Sumser, Dirk Trauner, Marcus Elstner1∗ 1 Department of Theoretical Chemical Biology, Institute of Physical Chemistry, Karlsruhe Institute of Technology, Kaiserstr. 12, 76131, Karlsruhe, Germany 2 Department of Chemistry, Ludwig-Maximilians-Universität München and Center of Integrated Protein Science, Butenandtstr. 5–13, 81377 Munich, Germany ∗ E-mail: marcus.elstner@kit.edu (ME)
The Use of Effective Strategies to Improve Saudi EFL Dyslexic Learners' Writing Skills

The use of techniques and strategies is instrumental in teaching different language skills to physically and mentally healthy learners; however, the importance of devising special techniques and strategies to teach dyslexic learners cannot be denied in English as Foreign Language (EFL) classrooms. Dyslexic learners have difficulties particularly in the recognition of words and putting them into writing. Based on the review of previous works and contexts, the present study aims at implementing the two strategies, i.e., multisensory and chunking, to improve Saudi EFL dyslexic learners’ writing skills. The work utilized a qualitative method to collect the data from the participants, i.e., four EFL teachers. Structured interviews were conducted with four EFL teachers from the ‘Alkhamisah Ashrah’ primary school to collect the data and apply the strategies, i.e., multisensory and chunking, to dyslexic learners and see their impacts on dyslexic learners’ writing skill. The study was conducted to develop awareness among parents and society at large about the learning difficulties and needs of dyslexic learners. In addition to this, the study aims to draw the attention of the Ministry of Education, educational institutions, researchers, and pedagogues to measure the academic needs of Saudi EFL dyslexic learners by devising different strategies. Furthermore, the study provides recommendations for the establishment of special schools, infrastructural facilities, well trained teachers, a rubric of strategies, special curriculum, and syllabus to meet the academic needs and enhance comprehension and writing abilities of Saudi EFL dyslexic learners.
Effects of a nonnative species of Poaceae on aquatic macrophyte community composition: A comparison with a native species

Invader-dominated systems of exotic species frequently damage native communities, mainly because there is a shift in the competition–facilitation balance, and competition intensifies in communities structured by facilitation. We tested whether areas dominated by the exotic species African signalgrass [Urochloa arrecta (Hack. ex T. Dur. & Schinz) O. Morrone & F. Zuloaga] can affect the assemblage structure of aquatic plants in tropical freshwater ecosystems, compared with the native species, anchored waterhyacinth [Eichhornia azurea (Sw.) Kunth]. We predicted that the dominance of African signalgrass (expressed as an increase in biomass) would reduce species richness, diversity, and functional diversity of the macrophyte assemblages, when compared with anchored waterhyacinth. Species cover and the occurrence of associated species were assessed in quadrats (1 m), located in sites dominated by exotic species (African signalgrass), native species (anchored waterhyacinth), and without dominance. The effects of dominance on species richness and diversity of aquatic macrophytes were assessed through generalized linear model and composition with detrended correspondence analysis. African signalgrass negatively affected species richness and Shannon diversity, whereas anchored waterhyacinth showed no effects on species richness and Shannon diversity. However, native species positively affected functional diversity. Our study showed that invasive species reduced the presence of rooted-submerged species, whereas native species facilitated the occurrence of rooted-submerged and free-submerged species. Thus, African signalgrass was able to change the composition of the macrophyte assemblage and can represent a threat to native communities of tropical freshwater ecosystems.
Dependence analysis based cyber-physical security assessment for critical infrastructure networks

Critical infrastructures like smart grid and smart transportations are large-scale distributed CPSs and cyber-physical security is pivotal to their safety and security. Efficient security assessment can help administrators to protect CINs effectively and we propose a universal quantitative cyber-physical security assessment methodology which is based on cyber-physical dependence analyses. For given CPS, we first construct the cyber-physical dependence model and dependence probability matrixes to analyze the dependences among assets quantitatively. Then we introduce security indexes and define the cyber-physical security metric ACPI to quantify the cyber-physical security state of each node in the CPS. Furthermore, we design the cyber-physical security assessment algorithm which can compute the ACPI values and discovery potential threats propagating paths in the CPS. Our methodology can be used for distributed CPS by dividing the whole CPS into smaller sub-ones and applying the same methods and rules. Finally, simulations demonstrate the high time efficiency of our assessment algorithm.
Unsupervised track classification based on Hierarchical Dirichlet Processes

An unsupervised track classification approach is applied to sonar multistatic multitarget tracking. Appropriate discriminative and aggregative features are derived from beamformed and normalized matched-filtered data as recorded from a linear array towed behind an AUV. A clustering algorithm based on Hierarchical Dirichlet Processes is proposed for unsupervised classification of tracks. Overall improvement of target tracking is demonstrated via the Optimal Subpattern Assignment metric.
Influence of EEG electrodes on the BOLD fMRI signal

Measurement of the EEG during fMRI scanning can give rise to image distortions due to magnetic susceptibility, eddy currents or chemical shift artifacts caused by certain types of EEG electrodes, cream, leads, or amplifiers. Two different creams were tested using MRS and T2* measurements, and we found that the one with higher water content was superior. This study introduces an index that quantifies the influence of EEG equipment on the BOLD fMRI signal. This index can also be used more generally to measure the changes in the fMRI signal due to the presence of any type of device inside (or outside) of the field of view (e.g., with fMRI and diffuse optical tomography, infrared imaging, transcranial magnetic stimulation, ultrasound imaging, etc.). Quantitative noise measurements are hampered by the normal variability of functional activation within the same subject and by the different slice profiles obtained when inserting a subject multiple times inside a MR imaging system. Our measurements account for these problems by using a matched filtering of cortical surface maps of functional activations. The results demonstrate that the BOLD signal is not influenced by the presence of EEG electrodes when using a properly constructed MRI compatible recording cap. Hum. Brain Mapping 14:108–115, 2001. © 2001 Wiley‐Liss, Inc.
Term Selection and Result Reranking for Question Retrieval by Exploiting Hierarchical Classification

Question retrieval aims to increase the accessibility of the community Question Answer (cQA) archives and has attracted increasing research interests recently. In this paper, we present a novel method for improving the question retrieval performance by investigating the question term selection and weighting as well as reranking results. Different from previous work, we propose a hierarchical question classification method with a sparse regularization to mimc user's question labeling in cQAs. Based on the hierarchical classification, we explore the local context of the question for term selection and reranking results and then integrating them into our proposed general question retrieval framework. The experimental results on a Yahoo! Answers dataset show the effectiveness of our method as compared to existing general question retrieval models and some state-of-the-art methods of utilizing category information for question retrieval.
Tunable electrically small UHF PIFA-as-a-package

A tunable electrically small PIFA-as-a-package antenna for miniature wireless device applications has been developed using conventional printed circuit board processing techniques and commercial-off-the-shelf surface mount switches. The design is scalable to any frequency and form factor, while enabling adaptive tuning of the characteristically narrow band resonance of electrically small antennas. Our UHF prototype measures less than 2" (.08lambda) on its longest side and provides approximately -9 dBi of gain from 419-472 MHz. Simulated and measured results will be discussed in the presentation
An Energy Efficient MAC Protocol for WSNs

Polling as one kind of the TDMA medium access control protocols has the advantage of energy conservation, however, its extensibility is not as good as that of contention-based protocol. The controllable threshold polling medium access protocol (CTP-MAC) in this paper is designed to realize the self-organizing in slot assignment and synchronization. Methods of the imbedded Markov-chain theory and the probability generating function are used to propose an analysis model of energy efficient for wireless sensor network. Mathematic analyses are compared with the simulations results.
Utilising Evolutionary Approaches and Object Oriented Techniques for Design Space Exploration

In this paper we examine how multi-objective evolutionary algorithms can assist in design space exploration. In this approach an engineer specifies certain hard and soft performance requirements for a multi-processor system, and allows it to be generated automatically by competitive evolution/optimisation, thus obviating the need for detailed design. To make the proposal concrete, we use the Intel IXP1200 network processor as a baseline complex system design and show how various improvements can be make to this architecture by evolutionary/competitive design. Various approaches to multi-objective optimisation (Darwin, Lamarck Baldwin, etc.) are compared and contrasted in their ability to generate architectures meeting various constraints. Our paper highlights the flexibility that this approach bestows on the designer, along with the potential to achieve cost savings and performance improvement
Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic.
A genome-wide scan for coronary heart disease suggests in Indo-Mauritians a susceptibility locus on chromosome 16 p 13 and replicates linkage with the metabolic syndrome on 3 q 27

1Institute of Biology of Lille, CNRS UPRES A 8090, Lille, France, 2SSR Centre for Medical Studies and Research, Moka, Mauritius, 3Endocrinology Service, Saint Louis Hospital, Paris, France, 4Cardiac Trust Fund, Pamplemousses, Mauritius, 5Cardiac Unit, Victoria Hospital, Mauritius, 6SSR National Hospital, Pamplemousses, Mauritius, 7Barts and The London Genome Centre, Queen Mary and Westfield College, London, UK and 8Janssen Research Foundation, Beerse, Belgium
outputs An infrastructure for building semantic web portals

One important task of semantic web portals is to offer both end users and applications a seamless access to knowledge contained in heterogeneous data sources in specific user communities. As such it is important to ensure that i) high quality metadata are extracted from heterogeneous sources in an automated manner and ii) comprehensive querying facilities are provided thus enabling knowledge to be accessed as easily as possible. However, current semantic web portals have only marginally addressed these issues. In this paper, we present our work, the KMi semantic web portal infrastructure, which pays special attention to these issues. Central to our infrastructure are three components: i) an automated metadata extraction tool, ASDI, which supports the extraction of high quality metadata from heterogeneous sources, ii) an ontology-driven question answering tool, AquaLog, which makes use of the domain specific ontology and the semantic metadata extracted by ASDI to answers questions in natural language format, and iii) a semantic search engine, which enhances traditional text-based searching by making use of the underlying ontologies and the extracted metadata. A semantic web portal application has been built, which illustrates the usage of this infrastructure.
Effects of Basic Computer Training on the Self-Efficacy of Adult Learner’s Utilization of Online Learning

The purpose of this chapter is to develop a theoretical framework for studying the effects of computer self-efficacy and applying these results to online learning. There is evidence to suggest that computer training can be a significant factor in improved computer self-efficacy (Loboda, 2002; Karsten & Roth, 1998; Smith, 1994; Torkzadeh & Koufteros, 1994). Self-efficacy is the belief that one is capable of performing in a certain manner to attain certain goals (Ormrod, 2006). Psychologist Albert Bandura proposed the theory of self-efficacy to help explain how we approach goals, tasks, and challenges (Bandura, 1977). In other words, Bandura says that if you have high self-efficacy toward a task you are more likely to make more of an effort, and persist longer than those of a low self-efficacy (Bandura, 2001). Improving computer self-efficacy could help students perform better in online coursework. As instructors strive to improve their efficiency and effectiveness, a possible instructional link ABSTRACT
Relationships Among Meditation, Perfectionism, Mindfulness, and Performance Anxiety Among Collegiate Music Students

I examined the use of meditation practices among collegiate-level musicians (N = 255), along with the degree to which these practices contributed to music performance anxiety (MPA) when controlling for trait perfectionism and trait mindfulness. Findings indicated that approximately 48% of the participants sampled had engaged in meditation during the past 6 months and that, holding mindfulness and perfectionist traits constant, participants who meditated at least weekly tended to report less MPA. Additionally, higher trait mindfulness predicted lower performance anxiety, whereas higher self-oriented as well as socially prescribed perfectionism predicted higher MPA scores. The type of meditation participants engaged in did not seem to significantly affect performance anxiety.
Internal posture sensing for a flexible frame modular mobile robot

A sensor fusion algorithm for flexible framed modular mobile robots is presented in this paper. This algorithm uses traditional Kalman filters and rigid axle kinematic models to predict the global posture of each axle. A Covariance Intersection filter is then proposed for fusing these axle modules using data provided by the compliant frame module. Modeling and instrumentation of the compliant frame module is the remaining focus. The instrumented frame is required to estimate the relative posture of the axles as well as the force components and moment that the beam exerts on each axle. These estimates must also be valid for large deflections in order to accommodate a reasonable turning radius. To accomplish these goals the beam equations are derived. A linear interpolation of the strain gauge data is used to calculate posture, force, and moment estimates. Experimental results show that the frame module can yield accurate relative posture estimates for large deflection.
Environment–Flexibility Coalignment and Performance: An Analysis in Large versus Small Firms

This paper takes a wide‐ranging transnational look, within the frame of he European Union, at the differences between large and small firms based on practices of flexibility. More specifically, the research aims to evaluate whether small firms form a homogeneous body in applying flexible practices as opposed to large firms, as well as observing the differential effects on performance when there are discrepancies in the coalignment levels between a firm’s actual flexibility and that required by the environment. The hypotheses are tested using data from 417 European firms. The results reveal that (1) good coalignments between actual and required flexibility (flexibility fit) have a greater influence on business performance in the case of small firms; (2) there are significant differences between small and large firms as regards operative flexibility, strategic flexibility, financial flexibility (organizational slack), and performance. The large firms analyzed coalign their flexibility fit better in their various dimensions (structural, operative, and strategic); (3) the degree of metaflexibility can be greater among small firms, which represents a greater information processing capacity, thus enabling the flexibility fit to be constantly coaligned to changes in the environment. However, a greater metaflexibility is not immediately reflected in the flexibility fit; and (4) this greater flexibility fit among large firms can be favored by their greater financial flexibility.
The RODOS System : Decision Support For Nuclear Off-Site Emergency Management In Europe

INTRODUCTION Experience gained after the Chernobyl accident clearly demonstrated the importance of improving administrative, organisational and technical emergency management arrangements in Europe. The more important areas where technical improvements were needed were early warning monitoring, communication networks for the rapid and reliable exchange of radiological and other information and decision support systems for off-site emergency management. Administratively, the most pressing need was to promote greater coherence in response to any future emergency; a lack of coherence contributed to the loss of public confidence in how the consequences of the Chernobyl accident were managed in different European countries. The scope and content of the European Commission’s research, in the area of nuclear emergency management following the Chernobyl accident, were largely determined by these needs. Under the auspices of its RTD (Research and Technological Development) Framework Programmes, the European Commission has supported the development of the RODOS (Real-time On-line DecisiOn Support) system for off-site emergency management. The main objectives of the RODOS project were:
An 80-Tile Sub-100-W TeraFLOPS Processor in 65-nm CMOS

This paper describes an integrated network-on-chip architecture containing 80 tiles arranged as an 8x10 2-D array of floating-point cores and packet-switched routers, both designed to operate at 4 GHz. Each tile has two pipelined single-precision floating-point multiply accumulators (FPMAC) which feature a single-cycle accumulation loop for high throughput. The on-chip 2-D mesh network provides a bisection bandwidth of 2 Terabits/s. The 15-FO4 design employs mesochronous clocking, fine-grained clock gating, dynamic sleep transistors, and body-bias techniques. In a 65-nm eight-metal CMOS process, the 275 mm2 custom design contains 100 M transistors. The fully functional first silicon achieves over 1.0 TFLOPS of performance on a range of benchmarks while dissipating 97 W at 4.27 GHz and 1.07 V supply.