Miracle-dz/UniFAR-FTUs huggingface dataset:
Visual Cortex Spatially Specific fMRI Repetition Effects in Human

[PDF] [Full Text] [Abstract] , November , 2007; 17 (11): 2601-2608. Cereb. Cortex Christian F. Altmann, Oliver Doehrmann and Jochen Kaiser Selectivity for Animal Vocalizations in the Human Auditory Cortex [PDF] [Full Text] [Abstract] , October 15, 2008; 28 (42): 10631-10640. J. Neurosci. Bram-Ernst Verhoef, Greet Kayaert, Edit Franko, Joris Vangeneugden and Rufin Vogels Dependent Stimulus Similarity-Contingent Neural Adaptation Can Be Time and Cortical Area [PDF] [Full Text] [Abstract] , August 8, 2012; . Cereb. Cortex Sarah Weigelt, Wolf Singer and Axel Kohler Feature-Based Attention Affects Direction-Selective fMRI Adaptation in hMT+ [PDF] [Full Text] [Abstract] , September , 2013; 23 (9): 2169-2178. Cereb. Cortex Sarah Weigelt, Wolf Singer and Axel Kohler Feature-Based Attention Affects Direction-Selective fMRI Adaptation in hMT+ [PDF] [Full Text] [Abstract] , January 15, 2014; . Cereb. Cortex Soojin Park, Talia Konkle and Aude Oliva Parametric Coding of the Size and Clutter of Natural Scenes in the Human Brain
Group-awareness for Mobile Cooperative Learning

Collaborative learning traditionally relies on the arrangement of space and physical artifacts to mediate group activities. Our claim is that CSCL environments should enhance collaborative learning in a complementary way without introducing additional burden to human participants. This paper present research results on how tracking the location of people could be used to incorporate automatic group awareness in existing and new CSCL applications that support mobile cooperative learning. After presenting the requirements and structure of a middleware to handle automatic group awareness based on location information, two applications are presented. Experiments in a real setting on a jigsaw activity, with students using laptops with WiFi on a university course, confirm the validity of using location technology to automatically derive group structure and the positive effect on the learning results
ENCOURAGING THE GRAND COALITION IN CONVEX COOPERATIVE GAMES

C Abstract. A solution function for convex transferable utility games en- courages the grand coalition if no player prefers (in a precise sense defined in the text) any coalition to the grand coalition. We show that the Shapley value encourages the grand coalition in all convex games and the -value encourages the grand coalitions in convex games up to three (but not more than three) players. Solution functions that encourage the grand coalition in convex games always produce allocations in the core, but the converse is not necessarily true.
Validation of the Life Role Salience Scale in a South African setting

This study aimed to validate the Life Role Salience Scale (LRSS) in a South African context. Respondents were 300 working adults (72.3% = women; 57.9% = non-white; mean age = 35.12 years, SD = 10.25 years; mostly from the finance sector = 35.6%). Confirmatory factor and exploratory factor analyses were conducted to determine the LRSS’s factor structure and reliability of scores from the scale for the South African sample. Results yielded five factors emerging from the analyses: Homecare role reward value and homecare role commitment; marital role reward value and marital role commitment; occupational role commitment; occupational role value reward; and parental role reward value. The reliability of scores from the LRSS ranged from 0.79 (parental role reward value) to 0.95 (homecare role reward value and homecare role commitment). The LRSS shows validity for research use in South Africa.
T Trunk   Trace Anchor Guard Branch   Trace Guard Side   Exit

Trace based compilation is a technique used in managed language runtimes to detect and compile frequently executed program paths. The goal is reduced compilation time and improved code quality since only “hot” parts of methods are ever compiled. Trace compilation is well suited for interpreter based runtime environments because the control flow of an application program is highly visible and recordable. In this technical report, we show that trace compilation is also feasible and beneficial in runtime environments without interpreters. We present the implementation of a trace based Java compiler for the meta-circular Maxine Virtual Machine from Sun Microsystems. Maxine uses a tiered compilation strategy. Methods are first compiled with a non optimizing JIT compiler in order to collect profiling information, and then recompiled with an optimizing compiler for long term execution. We record traces via dynamic insertion and removal of instrumentation code in non optimized methods. We then optimize and link recorded traces using the already existing optimizing compiler.
Design of Energy Efficient Topologies for Wireless On-Body Channel

Advanced applications in the area of remote health monitoring can be realized by Wireless Body Area Networks (WBANs). This paper investigates the physical propagation channel at 2.45 GHz near real humans and presents an application for cross-layer design in order to optimize the energy consumption of single-hop and multi-hop network topologies. The characterization of the physical layer is an important element in the development of a WBAN. Propagation measurements are performed on real humans in a multipath environment and propagation models are proposed. As a cross-layer application, the proposed path loss models are used to evaluate the energy efficiency of different network topologies. The paper investigates which topology is the most energy efficient in WBANs: single-hop or multi-hop communication.
Multi-Scale Time-Changed Birth Processes for Pricing Multi-Name Credit Derivatives

Abstract We develop two parsimonious models for pricing multi-name credit derivatives. We derive closed form expression for the loss distribution, which then can be used in determining the prices of tranche and index swaps and more exotic derivatives on these contracts. Our starting point is the model of Ding et al., 2008, which takes the loss process as a time-changed birth process. We introduce stochastic parameter variations into the intensity of the loss process and use the multi-time scale approach of Fouque et al., 2003 and obtain explicit perturbation approximations to the loss distribution. We demonstrate the competence of our approach by calibrating it to the CDX index data.
Analysis of Automatic Multi-label GrabCut using NPR for natural image segmentation

Automatic Multi-label GrabCut is an extension of the standard GrabCut technique to segment a given image automatically into its natural segments without any user intervention. The Normalized Probabilistic Rand (NPR) index is able to give meaningful comparisons by comparing different images and different segmentations of the same image. In this paper, more analysis is conducted to evaluate the efficiency of the developed automatic multi-label GrabCut using the NPR index. Based on using more than one human ground truth, segmentations are conducted on a large scale of the Berkeley's benchmark of natural images. The NPR, PR and GCE metrics produced acceptable accuracy measures emphasizing the scalability of the proposed technique for large scale datasets. Comparisons are applied for different images and experiments show that the NPR is the most efficient score to determine good segmentation compared to other metrics.
Myoelectric teleoperation of a complex robotic hand

An unusual method of teleoperation of complex anthromorphic robotic hands, i.e., converting the myoelectric signal generated by the operator's muscles during movement into robot commands replicating the motion is discussed. The feasibility of using this approach for commanding more than one degree-of-freedom (DOF), as exemplified by the pincher type grip in current myoelectric hands, is still in question. The feasibility study described addresses myoelectric control of NASA/Johnson Space Center's 16-DOF Utah/MIT Dextrous Hand for several grasping options. Myoelectric signal processing approaches, data collection apparatus, and preliminary data for key and chuck grasps are discussed. <<ETX>>
The Translation Regulatory Subunit eIF3f Controls the Kinase-Dependent mTOR Signaling Required for Muscle Differentiation and Hypertrophy in Mouse

The mTORC1 pathway is required for both the terminal muscle differentiation and hypertrophy by controlling the mammalian translational machinery via phosphorylation of S6K1 and 4E-BP1. mTOR and S6K1 are connected by interacting with the eIF3 initiation complex. The regulatory subunit eIF3f plays a major role in muscle hypertrophy and is a key target that accounts for MAFbx function during atrophy. Here we present evidence that in MAFbx-induced atrophy the degradation of eIF3f suppresses S6K1 activation by mTOR, whereas an eIF3f mutant insensitive to MAFbx polyubiquitination maintained persistent phosphorylation of S6K1 and rpS6. During terminal muscle differentiation a conserved TOS motif in eIF3f connects mTOR/raptor complex, which phosphorylates S6K1 and regulates downstream effectors of mTOR and Cap-dependent translation initiation. Thus eIF3f plays a major role for proper activity of mTORC1 to regulate skeletal muscle size.
Knowledge Extraction In Hadith Using Data Mining Technique

Muslims believe that the Sunnah of the Prophet Muha mm d(SAAW) is the second of the two revealed fundamental sources of Islam, after the Holy Qur'an . Hadith can provide a Gold Standard "ground truth" for AI (Artificial Intelligent) knowledge extraction and k nowledge representation experiments. In the present tudy, the extracted Islamic knowledge represented the focal p oint of the research, three famous books in Hadith science framed the corpus of the study. This study attempte d to explore new approach to classify Hadith using data mining techniques to classify Hadith according to i ts validity degree (Sahih, Hasan, Da'eef and Maudo' ), the proposed Hadith classifier model was built through learning process, DT classifier modeling had been represented by the tree structure model, and the at tribu es of the instances originally were obtained from the source books. Whilst some attributes were indicated as null values, or missing values. A novel mechan ism called missing data detector (MDD) was employed to handle these missing data. This mechanism was gener at d based on the Isnad validity methods in Hadith scien ce. The results of the research were compared with the resource books, concurrently with the point of view of the experts in the Hadith science. The findings of the research showed that the performance of DT Hadith c lassifier had significant effect with DDM, the CCR was sharply increased from (50.1502 %) to (97.597%) Fur the more, the favorable obtained results indicated hat the DT Modeling is a viable approach to classify Ha dith due to the ease of rules induction and results interpretation
The Ω key management service

In this paper we i.ntroduce R, a distributed public key management service for open networks. f’l offers interfaces by which clients can register, retrieve, and revoke public keys, and escrow, use (to decrypt messages), and recover private keys, all of which can be subjected to access control policy. R is built using multiple servers in a way that ensures its correct operation despite the malicious corruption of fewer than one-third of its component servers. We describe the design of R, the protocols underlying its operation, performance in our present implementation, and an experimental application of the service.
The conceptualisation of school and teacher connectedness in adolescent research: a scoping review of literature

Abstract The aim of this scoping review was to map and summarise research relating to school and teacher connectedness, in order to increase current understanding of the ways these terms have been conceptualised in adolescent research. Specifically, this scoping review focuses on the analysis of the actual definitions used and the ways in which school connectedness and teacher connectedness are operationalised in existing measures. Using the terms connectedness, teacher and school as keywords, we searched SCOPUS, Web of Science, ERIC, the Cochrane Library and the EPPI Centre Database of Education Research for relevant peer-review articles published in English from 1990 to 2016. 350 papers were selected for the review. Many studies failed to provide a definition of school or teacher connectedness and there were some differences in the way these constructs were operationalised in the main measures. Future research should be thorough in the definition of these constructs, and ensure consistency between the definition used and the operationalisation of the connectedness construct in the selected measure. Unpacking the global concept of school connectedness and examining the role of its different components (global feelings towards school, teacher connectedness, relationships with classmates, etc.) separately may also contribute to building a more coherent body of evidence in this area. Reflecting on the place of school and teacher connectedness in the broader context of the literature on school climate and bridging distances between the research on school connectedness and that on related constructs is another necessary step to move this field forward.
Energy efficient transmit beamforming under queueing stability constraints

This paper considers the problem of energy efficient beamforming allocation in a cellular wireless network. Unlike most of the existing work that considers the problem at the physical layer, we include in our analysis the impact of the bursty traffic patterns of the users. We formulate a stochastic optimization problem that minimizes the average transmit power of the network such that the queues of the users are stable. We then develop a solution that combines Lyapunov optimization and mixed integer quadratic problem (MIQP). We provided a fundamental complexity analysis of the resulting optimization problem and show that it is NP-hard. We then provide a Semi-Definite Relaxation (SDR) of the problem and develop an algorithm with low complexity to get as close as possible to the desired optimal solution. Our claims are corroborated by simulation results.
Discovering Weblog Communities: A content- and topology-based approach

Weblogs have become a leading form of self-publication on the web. Personal weblogs are often considered to represent a person, and the links between webogs can naturally be given a social interaction. Against this background, finding a community around a given weblog—i.e., identifying a set of weblogs that forms a natural group together with the starting point, because of content or social reasons—is a very natural task. Traditional methods for community finding methods focus almost exclusively on topology analysis. In this paper we present a novel method for discovering weblog communities that incorporates both topology analysis and content analysis. We evaluate our method in a small-scale user study, analyze the contributions of the various components of our approach, and compare it against a state-of-the-art topologybased community finding algorithm.
HMM parameter optimization using tabu search [speech recognition]

Hidden Markov model (HMM) is regularly trained via mathematic functions optimized by gradient-based methods such as Baum-Welch (BW) algorithm. However, optimization from gradient-based methods usually yields only a local optimum. In this paper, tabu search (TS), an artificial intelligence (AI) technique able to step back from a local optimum and search for other optima, is employed to attack this difficulty. This paper aims to utilize HMM with TS for speaker-independent (SI) continuous speech recognition. The experiment starts from a single speaker experiment in order to design and adjust the algorithm. Then, multi-Gaussian context-dependent (CD) model is applied for SI system. The results show the merit of this new algorithm comparing with the original BW.
Effects of Temperature and X-rays on Plastic Scintillating Fiber and Infrared Optical Fiber

In this study, we have studied the effects of temperature and X-ray energy variations on the light output signals from two different fiber-optic sensors, a fiber-optic dosimeter (FOD) based on a BCF-12 as a plastic scintillating fiber (PSF) and a fiber-optic thermometer (FOT) using a silver halide optical fiber as an infrared optical fiber (IR fiber). During X-ray beam irradiation, the scintillating light and IR signals were measured simultaneously using a dosimeter probe of the FOD and a thermometer probe of the FOT. The probes were placed in a beaker with water on the center of a hotplate, under variation of the tube potential of a digital radiography system or the temperature of the water in the beaker. From the experimental results, in the case of the PSF, the scintillator light output at the given tube potential decreased as the temperature increased in the temperature range from 25 to 60 °C. We demonstrated that commonly used BCF-12 has a significant temperature dependence of −0.263 ± 0.028%/°C in the clinical temperature range. Next, in the case of the IR fiber, the intensity of the IR signal was almost uniform at each temperature regardless of the tube potential range from 50 to 150 kVp. Therefore, we also demonstrated that the X-ray beam with an energy range used in diagnostic radiology does not affect the IR signals transmitted via a silver halide optical fiber.
Evaluation of a genomic classifier in radical prostatectomy patients with lymph node metastasis

Objective To evaluate the performance of the Decipher test in predicting lymph node invasion (LNI) on radical prostatectomy (RP) specimens. Methods We identified 1,987 consecutive patients with RP who received the Decipher test between February and August 2015 (contemporary cohort). In the contemporary cohort, only the Decipher score from RP specimens was available for analysis. In addition, we identified a consecutive cohort of patients treated with RP between 2006 and 2012 at the University of California, San Diego, with LNI upon pathologic examination (retrospective cohort). The retrospective cohort yielded seven, 22, and 18 tissue specimens from prostate biopsy, RP, and lymph nodes (LNs) for individual patients, respectively. Univariable and multivariable logistic regression analyses were used to evaluate the performance of Decipher in the contemporary cohort with LNI as the endpoint. In the retrospective cohort, concordance of risk groups was assessed using validated cut-points for low (<0.45), intermediate (0.45–0.60), and high (>0.60) Decipher scores. Results In the contemporary cohort, 51 (2.6%) patients had LNI. Decipher had an odds ratio of 1.73 (95% confidence interval, 1.46–2.05) and 1.42 (95% confidence interval, 1.19–1.7) per 10% increase in score on univariable and multivariable (adjusting for pathologic Gleason score, extraprostatic extension, and seminal vesicle invasion), respectively. No significant difference in the clinical and pathologic characteristics between the LN positive patients of contemporary and retrospective cohorts was observed (all P>0.05). Accordingly, among LN-positive patients in the contemporary cohort and retrospective cohort, 80% and 77% had Decipher high risk scores (P=1). In the retrospective cohort, prostate biopsy cores with the highest Gleason grade and percentage of tumor involvement had 86% Decipher risk concordance with both RP and LN specimens. Conclusion Decipher scores were highly concordant between pre- and post-surgical specimens. Further, Decipher scores from RP tissue were predictive of LNI at RP. If validated in a larger cohort of prostate biopsy specimens for prediction of adverse pathology at RP, Decipher may be useful for improved pre-operative staging.
Complete Genome Sequence of Leifsonia xyli subsp. cynodontis Strain DSM46306, a Gram-Positive Bacterial Pathogen of Grasses

ABSTRACT We announce the complete genome sequence of Leifsonia xyli subsp. cynodontis, a vascular pathogen of Bermuda grass. The species also comprises Leifsonia xyli subsp. xyli, a sugarcane pathogen. Since these two subspecies have genome sequences available, a comparative analysis will contribute to our understanding of the differences in their biology and host specificity.
Job Satisfaction : Key Factors Influencing Information Technology ( IT ) Professionals in Washington DC

A problem most organizations face is how to retain skilled employees. As technology has gone from common to prevalent over the past twenty years, retaining skilled information technology (IT) professionals has become more difficult. Therefore, this study focused on examining job satisfaction of IT professionals in the D.C. area, paying particular attention to two of the most important factors of job satisfaction for IT workers: autonomy and the opportunity for advancement. Association of Information Technology Professionals (AITP) members from the D.C. metro area were surveyed using the Minnesota Satisfaction Questionnaire (MSQ). This paper reviewed existing literature to find what other researchers have done to ensure that IT professionals get job satisfaction. The paper went further to identify the most pertinent job satisfaction factors as follows: personality trait, values: extrinsic and intrinsic, working condition and social influence. This study employed quantitative research methods in order to address the research questions; what are the factors that influence IT professional's perceptions of job satisfaction and can organizations and management influence the issue of job satisfaction among IT professionals. The results of this study indicate that general satisfaction is significantly associated with satisfaction levels regarding autonomy and intrinsic factors.
METE: meeting end-to-end QoS in multicores through system-wide resource management

Management of shared resources in emerging multicores for achieving predictable performance has received considerable attention in recent times. In general, almost all these approaches attempt to guarantee a certain level of performance QoS (weighted IPC, harmonic speedup, etc) by managing a single shared resource or at most a couple of interacting resources. A fundamental shortcoming of these approaches is the lack of coordination between these shared resources to satisfy a system level QoS. This is undesirable because providing end-to-end QoS in future multicores is essential for supporting wide-spread adoption of these architectures in virtualized servers and cloud computing systems. An initial step towards such an end-to-end QoS support in multicores is to ensure that at least the major computational and memory resources on-chip are managed efficiently in a coordinated fashion. In this paper, we propose METE, a platform for end-to-end on-chip resource management in multicore processors. Assuming that each application specifies a performance target/SLA, the main objective of METE is to dynamically provision sufficient on-chip resources to applications for achieving the specified targets. METE employs a feedback based system, designed as a Single-Input, Multiple-Output (SIMO) controller with an Auto-Regressive-Moving-Average (ARMA) model, to capture the behaviors of different applications. We evaluate a specific implementation of METE that manages cores, shared caches and off-chip bandwidth in an integrated manner on 8 and 16 core systems using a detailed full system simulator and workloads derived from the SPECOMP and SPECJBB multithreaded benchmarks. The collected results indicate that our proposed scheme is able to provision shared resources among co-runner applications dynamically over the course of execution, to provide end-to-end QoS and satisfy specified performance targets. Furthermore, the elegance of the control theory based multi-layer resource provisioning is in assuring QoS guarantees.