Miracle-dz/UniFAR-FTUs huggingface dataset:
Movement Imagery for Speech in Healthy Women: Influences on Articulation Accuracy and Fluidity, Imagery Times, and Expectations of Success

The use of movement imagery in speech performance has received less attention than it has in many other professional disciplines. 30 healthy monolingual native English speakers participated in this within-subjects study. Participants' speech accuracy and fluidity was compared when they used movement imagery and when they did not. The timing of imagery and articulation were compared using a chronometric paradigm. Participants' expectations of improvement when using movement imagery for speech were compared to their actual performance. The results from this study support the use of movement imagery for speech with a single imaging event for the purpose of improving speech fluidity, but not for improving articulation accuracy. The chronometric system as a tool for monitoring adherence to the movement imagery protocol for speech proved valuable. Finally, while estimation inflation has been reported by some using movement imagery techniques, this was not the case for the participants of this study.
International survey of the distribution of serotypes of Streptococcus pyogenes (group A streptococci).

To determine whether there are major differences in the distribution of Streptococcus pyogenes serotypes in different countries and to compare the typing results obtained in different laboratories with the same cultures, an international survey of the distribution of such serotypes was carried out in 1964-65 in 12 laboratories in different parts of the world.The cultures typed were a representative selection of those causing disease in each country, were as far as possible uninfluenced by seasonal changes and local prevalences, and included separate collections from cases of scarlet fever, sore throat, and other streptococcal diseases.Typing was carried out by the T-agglutination method in 12 laboratories and by the M-precipitation method as well in 8. Between 80% and 98% of the cultures were typable by T-agglutination in the different laboratories, and between 23% and 56% by M-precipitation.Some T-agglutination patterns were associated with a single M-antigen but others included members of several M-types. The same M-antigen was rarely found in streptococci with different T-agglutination patterns. The two methods could therefore conveniently be used as a combined system of typing.Certain streptococcal types were relatively common in most countries, but there were considerable national differences in type-distribution. Separate analysis of the cultures obtained from individual streptococcal diseases showed that there were also differences in type-distribution between streptococci isolated from scarlet fever, from sore throat, and from septic lesions not associated with the respiratory tract.
Estimation of global aortic pulse wave velocity by flow‐sensitive 4D MRI

The aim of this study was to determine the value of flow‐sensitive four‐dimensional MRI for the assessment of pulse wave velocity as a measure of vessel compliance in the thoracic aorta. Findings in 12 young healthy volunteers were compared with those in 25 stroke patients with aortic atherosclerosis and an age‐matched normal control group (n = 9). Results from pulse wave velocity calculations incorporated velocity data from the entire aorta and were compared to those of standard methods based on flow waveforms at only two specific anatomic landmarks. Global aortic pulse wave velocity was higher in patients with atherosclerosis (7.03 ± 0.24 m/sec) compared to age‐matched controls (6.40 ± 0.32 m/sec). Both were significantly (P < 0.001) increased compared to younger volunteers (4.39 ± 0.32 m/sec). Global aortic pulse wave velocity in young volunteers was in good agreement with previously reported MRI studies and catheter measurements. Estimation of measurement inaccuracies and error propagation analysis demonstrated only minor uncertainties in measured flow waveforms and moderate relative errors below 16% for aortic compliance in all 46 subjects. These results demonstrate the feasibility of pulse wave velocity calculation based on four‐dimensional MRI data by exploiting its full volumetric coverage, which may also be an advantage over standard two‐dimensional techniques in the often‐distorted route of the aorta in patients with atherosclerosis. Magn Reson Med, 2010. © 2010 Wiley‐Liss, Inc.
2016 Ieee International Conference on Big Data (big Data) Shooting a Moving Target: Motion-prediction-based Transmission for 360-degree Videos

—Enabled by the rapid development of virtual reality hardware and software, 360-degree video content has proliferated. From the network perspective, 360-degree video transmission imposes significant challenges because it consumes 4∼6x the bandwidth of a regular video with the same resolution. To address these challenges, in this paper, we propose a motion-prediction-based transmission mechanism that matches network video transmission to viewer needs. Ideally, if viewer motion is perfectly known in advance, we could reduce bandwidth consumption by 80%. Practically, however, to guarantee the quality of viewing experience, we have to address the random nature of viewer motion. Based on our experimental study of viewer motion (comprising 16 video clips and over 150 subjects), we found the viewer motion can be well predicted in 100∼500ms. We propose a machine learning mechanism that predicts not only viewer motion but also prediction deviation itself. The latter is important because it provides valuable input on the amount of redundancy to be transmitted. Based on such predictions, we propose a targeted transmission mechanism that minimizes overall bandwidth consumption while providing probabilistic performance guarantees. Real-data-based evaluations show that the proposed scheme significantly reduces bandwidth consumption while minimizing performance degradation, typically a 45% bandwidth reduction with less than 0.1% failure ratio.
Adaptive Algorithms to Track the PARAFAC Decomposition of a Third-Order Tensor

The PARAFAC decomposition of a higher-order tensor is a powerful multilinear algebra tool that becomes more and more popular in a number of disciplines. Existing PARAFAC algorithms are computationally demanding and operate in batch mode - both serious drawbacks for on-line applications. When the data are serially acquired, or the underlying model changes with time, adaptive PARAFAC algorithms that can track the sought decomposition at low complexity would be highly desirable. This is a challenging task that has not been addressed in the literature, and the topic of this paper. Given an estimate of the PARAFAC decomposition of a tensor at instant t, we propose two adaptive algorithms to update the decomposition at instant t+1, the new tensor being obtained from the old one after appending a new slice in the 'time' dimension. The proposed algorithms can yield estimation performance that is very close to that obtained via repeated application of state-of-art batch algorithms, at orders of magnitude lower complexity. The effectiveness of the proposed algorithms is illustrated using a MIMO radar application (tracking of directions of arrival and directions of departure) as an example.
Parallelizing MCMC with Random Partition Trees

The modern scale of data has brought new challenges to Bayesian inference. In particular, conventional MCMC algorithms are computationally very expensive for large data sets. A promising approach to solve this problem is embarrassingly parallel MCMC (EP-MCMC), which first partitions the data into multiple subsets and runs independent sampling algorithms on each subset. The subset posterior draws are then aggregated via some combining rules to obtain the final approximation. Existing EP-MCMC algorithms are limited by approximation accuracy and difficulty in resampling. In this article, we propose a new EP-MCMC algorithm PART that solves these problems. The new algorithm applies random partition trees to combine the subset posterior draws, which is distribution-free, easy to re-sample from and can adapt to multiple scales. We provide theoretical justification and extensive experiments illustrating empirical performance.
Why does MTR change with neuronal depolarization?

T1 and T2 relaxation, and magnetization transfer (MT) of the rat brain were measured during experimentally induced spreading depression (SD). All measured MR parameters changed during SD: T1 relaxation increased by approximately 13%, whereas the T2 increase was substantially larger (88%). MT results showed an MT ratio (MTR) decrease of 9%. The lack of change in the MT exchange rate indicated that the MT processes between water and macromolecular protons are not affected by neuronal depolarization. The observed decrease in MTR was only caused by changes in T1 and T2 relaxation. Magn Reson Med 47:472–475, 2002. © 2002 Wiley‐Liss, Inc.
New single-poly EEPROM with cell size down to 8F/sup 2/ for high density embedded nonvolatile memory applications

A novel EEPROM memory cell with new program and erase operations fabricated by standard CMOS logic process is presented. The cell which consists of two N-Type MOSFET transistors in series is programmed by select gate controlled channel hot hole and erased by channel hot electron injection along with more than 10/sup 5/ cycles of endurance and 1000 hours of data retention at 150/spl deg/C. Without an additional P-well or N-well serving as the coupling gate, the area of a bit can be as small as 8F/sup 2/, the smallest area reported for single-poly EEPROM cells.
Iterative multi scaling-enhanced Inexact Newton-method for microwave imaging

In the last years, several approaches have been proposed for solving inverse problems arising in microwave imaging [1] and related applications including non-invasive diagnostics, biomedical imaging, remote sensing, and subsurface prospecting [1]-[4]. In a microwave imaging problem, the targets are illuminated by incident waves and scattered field samples are measured outside the investigation area [1]-[4]. In order to retrieve the unknwon objects from the measurements, different stochastic [1][3] and deterministic [2][4] approaches have been proposed. As for these latter, they are usually based on iterative procedures such as gradient or Newton-type methods. In this framework, an approach based on an Inexact-Newton method (IN) has been recently proposed for solving inverse scattering problems formulated through electric field integral equations (EFIEs) [4]. Such a method has been validated on synthetic and experimental results as well as extended to contrast source formulations [5] showing several advantages in terms of stability, accuracy, and convergence rate with respect to state-of the art techniques [4]. However, it can suffer from local minima because of its deterministic nature. In order to overcome/mitigate such a drawback, the iterative multiscaling approach (IMSA) introduced in [2] for conjugate-gradient methods is considered in this paper. The IMSA is a synthetic zoom procedure that, thanks to an efficient exploitation of the available information from scattering data, guarantees higher resolution and enhanced reconstruction with respect to the corresponding “bare” approaches whatever the inversion technique [2][3]. Thanks to these features, it represents a candidate solution for improving the performances of IN and avoiding some intrinsic drawbacks caused by the limited amount of indipendent data and the deterministic nature of the same approach. In the following, the integration of the IMSA with the IN method (IMSA-IN technique) will be described and its performances will be compared to those of the standard IN implementation (Bare-IN).
Scaling ADLs within the MDS.

BACKGROUND Dependency in activities of daily living (ADLs) is a reality within nursing homes, and we describe ADL measurement strategies based on items in the Minimum Data Set (MDS) and the creation and distributional properties of three ADL self-performance scales and their relationship to other measures. METHODS Information drawn from four data sets for a multistep analysis was guided by four study objectives: (1) to identify the subcomponents of ADLs that are present in the MDS battery; (2) to demonstrate how these items could be aggregated within hierarchical and additive ADL summary scales; (3) to describe the baseline and longitudinal distributional properties of these scales in a large, seven-state MDS database; and (4) to evaluate how these scales relate to two external criteria. RESULTS Prevalence and factor structure findings for seven MDS ADL self-performance variables suggest that these items can be placed into early, middle, and late loss ADL components. Two types of summary ADL self-performance measures were created: additive and hierarchical. Distributional properties of these scales are described, as is their relationship to two external ADL criteria that have been reported in prior studies: first as an independent variable predicting staff time involved in resident care; second as a dependent variable in a study of the efficacy of two programs to improve resident functioning. CONCLUSIONS The new ADL summary scales, based on readily available MDS data, should prove useful to clinicians, program auditors, and researchers who use the MDS functional self-performance items to determine a resident's ADL status.
Integrated admission and congestion control for QoS support in clusters

Admission and congestion control mechanisms are integral parts of any Quality of Service (QoS) design for networks that support integrated traffic. In this paper we propose an-admission control algorithm and a congestion control algorithm for clusters, which are increasingly being used in a diverse set of applications that require QoS guarantees. The uniqueness of our approach is that we develop these algorithms for wormhole-switched networks. We use QoS-capable wormhole routers and QoS-capable network interface cards (NICs), referred to as Host Channel Adapters (HCAs) in InfiniBand/spl trade/ Architecture (IBA), to evaluate the effectiveness of these algorithms. The admission control is applied at the HCAs and the routers, while the congestion control is deployed only at the HCAs. Simulation results indicate that the admission and congestion control algorithms are quite effective in delivering the assured performance. The proposed credit-based congestion control algorithm is simple and practical in that it relies on hardware already available in the HCA to regulate traffic injection.
The emerging role of SHANK genes in neuropsychiatric disorders

The genetic heterogeneity of neuropsychiatric disorders is high, but some pathways emerged, notably synaptic functioning. A large number of mutations have been described in genes such as neuroligins, neurexins, and SHANK that play a role in the formation and the maintenance of synapses. This review focuses on the disorders associated with mutations in SHANK3 and the other members of its family, SHANK1 and SHANK2. SHANKs are scaffolding proteins of the postsynaptic density of glutamatergic synapses. SHANK3 has been described in the Phelan‐McDermid syndrome (PMS), but also in autism spectrum disorders (ASD) and schizophrenia associated to moderate to severe intellectual disability (ID) and poor language. The evolution of patients with PMS includes symptoms of bipolar disorder and regression. SHANK2 has been identified in patients with ASD with mild to severe ID. SHANK1 has been associated with high‐functioning autism in male patients, while carrier females only display anxiety and shyness. Finally, based on neuropathological findings in animal models and patients, a possible role of SHANK in Alzheimer's disease is discussed. Altogether, this review describes the clinical trajectories associated with different mutations of the SHANK genes and provides information to further investigate the role of the SHANK genes in neuropsychiatric disorders. © 2013 Wiley Periodicals, Inc. Develop Neurobiol 74: 113–122, 2014
A Non-Local Means Filter for Removing the Poisson Noise

A new image denoising algorithm to deal with the Poisson noise model is given, which is based on the idea of Non-Local Mean. By using the "Oracle" concept, we establish a theorem to show that the Non-Local Means Filter can effectively deal with Poisson noise with some modification. Under the theoretical result, we construct our new algorithm called Non-Local Means Poisson Filter and demonstrate in theory that the filter converges at the usual optimal rate. The filter is as simple as the classic Non-Local Means and the simulation results show that our filter is very competitive.
Optimal channel assignment for military MANET using integer optimization and constraint programming

The military is developing, purchasing, and fielding mobile ad-hoc network (MANET) radios capable of connecting highly mobile units operating in rugged terrain over long distances. These radios offer tremendous new capabilities, including high data rates and automatic traffic relay, but have large electromagnetic spectrum requirements. We explore the challenges faced by a spectrum manager in allocating the minimum number of channels to support communications for military forces conducting tactical operations. In previous work, we identified the vast computational challenges of solving this problem when considering the effects of cumulative co-channel interference. We present a new method to solve this problem using heuristic, integer optimization, and constraint programming techniques. We apply our methods to realistic data sets from a large U.S. Marine Corps combat scenario, and provide detailed performance results. We also outline our plan for further developing this method to consider multiple time steps. To our knowledge, we are the first to describe an algorithm for solving a realistic, large-scale interference-aware minimum-order channel assignment problem to global or near-global optimality.
Optimal wireless energy charging policy for a mobile node in Smart Grid environment

Recently, mobile devices are equipped with wireless energy charging capability. They can be charged wirelessly by chargers located at different locations. The prices that the chargers apply to the mobile user/node can be changed, e.g., due to the implementation of demand side management in smart grid environment. The mobile node can use this price information (e.g., obtained through wireless communication) to make its charging decision accordingly. In this paper, we study an optimal wireless energy charging policy for the mobile node. The mobile node's objective is to minimize the cost due to the price of using charging service from chargers and the cost of having not enough energy. We formulate and solve a Markov decision process to obtain such an optimal policy. Additionally, we analytically prove that the optimal charging policy has a threshold structure. That is, the mobile node will use the charging service if its energy level is below a certain threshold. The performance evaluation shows the proposed energy charging policy achieves much better performance compared with a naive policy of always charging.
On the Utility of Anonymized Flow Traces for Anomaly Detection

The sharing of network traces is an important prerequisite for the development and evaluation of efficient anomaly detection mechanisms. Unfortunately, privacy concerns and data protection laws prevent network operators from sharing these data. Anonymization is a promising solution in this context; however, it is unclear if the sanitization of data preserves the traffic characteristics or introduces artifacts that may falsify traffic analysis results. In this paper, we examine the utility of anonymized flow traces for anomaly detection. We quantitatively evaluate the impact of IP address anonymization, namely variations of permutation and truncation, on the detectability of large-scale anomalies. Specifically, we analyze three weeks of un-sampled and non-anonymized network traces from a medium-sized backbone network. We find that all anonymization techniques, except prefix-preserving permutation, degrade the utility of data for anomaly detection. We show that the degree of degradation depends to a large extent on the nature and mix of anomalies present in a trace. Moreover, we present a case study that illustrates how traffic characteristics of individual hosts are distorted by anonymization.
BallotShare: Exploring the design space of digital voting in a workplace environment

Digital voting is used in a variety of contexts from politics to mundane everyday decisions. One of the motivations underlying many group decision-making systems is the promotion of participation, yet there is little research that explores how features of digital voting systems can be designed to facilitate this, other than providing multiple voting channels. In this paper we propose a framework that explores the design space of digital voting from the perspective of participation. We ground our discussion in the design of BallotShare, a first configuration of our proposed framework, designed to enable the study of group decision-making practices deployed in a workplace setting. Across five weeks, participants created and took part in non-standard polls relating to events and other spontaneous group decisions. Following interviews with participants we identify significant drivers and limitations of individual and collective participation in the voting process: social visibility, social inclusion, commitment and delegation, accountability, influence and privacy. © 2014 Newcastle University. Printed and published by Newcastle University, Computing Science, Claremont Tower, Claremont Road, Newcastle upon Tyne, NE1 7RU, England. Bibliographical details VLACHOKYRIAKOS, V. , DUNPHY, P., TAYLOR, N. , COMBER, R. , OLIVIER, P. BallotShare: Exploring the Design Space of Digital Voting in a Workplace Environment [By] V. Vlachokyriakos, P. Dunphy, N. Taylor, R. Comber and P. Olivier Newcastle upon Tyne: Newcastle University: Computing Science, 2014. (Newcastle University, Computing Science, Technical Report Series, No. CS-TR-1410)
An Architecture for Mobility Support in a Next-Generation Internet

The current internetworking architecture presents some limitations to naturally support mobility, security and multi- homing. Among the limitations, the IP semantic overload seems to be a primary issue to be considered. In this paper we present a next generation internetworking architecture to overcome the IP semantic overload by introducing an identity layer located between the network and transport layers. This new layer provides a stable cryptographic identifier for end-hosts and seamlessly allows the deployment of new services, such as mobility, multi-homing and security. A prototype was implemented and evaluated considering some mobility scenarios, including intra-domain, inter-domain and simultaneous node mobility.
The NetLogger methodology for high performance distributed systems performance analysis

We describe a methodology that enables the real-time diagnosis of performance problems in complex high-performance distributed systems. The methodology includes tools for generating precision event logs that can be used to provide detailed end-to-end application and system level monitoring; a Java agent-based system for managing the large amount of logging data; and tools for visualizing the log data and real-time state of the distributed system. We developed these tools for analyzing a high-performance distributed system centered around the transfer of large amounts of data at high speeds from a distributed storage server to a remote visualization client. However this methodology should be generally applicable to any distributed system. This methodology called NetLogger has proven invaluable for diagnosing problems in networks and in distributed systems code. This approach is novel in that it combines network, host, and application-level monitoring, providing a complete view of the entire system.