Miracle-dz/UniFAR-FTUs huggingface dataset:
Composite Structure Analysis of a Hollow Cantilever Beam Filled with Electro-Rheological Fluid

Unwanted vibrations within structures can become an ever increasing problem as structural components are made lighter with the use of advanced materials and tighter design tolerances. Increased operating bandwidth further compounds the problem resulting in the build up of unwanted vibrations within optimally designed structures. The alteration of the spectral signature of a structural component will enable the aforementioned design criteria to be satisfied. The use of a hollow structural component filled with Electro-Rheological fluid will enable the spectral signature of the component to be altered electrically. Experimental data obtained for a hollow cantilever beam filled with Electro-Rheological fluid is presented in this paper. Analysis of the data is carried out to determine heuristic values for the beams effective stiffness and damping coefficient. The effects of applying an electric field to the ER fluid are outlined from the results obtained. Comparison of the results is then made with those predicted by a model of an oscillating composite structure cantilever beam. Differences between the predicted and the heuristic data is then examined with regard to a hypothesis based on the behaviour of the induced ER fluid's microscopic structure.
Auditory-based automatic speech recognition

In this paper we develop a physiologically motivated model of peripheral auditory processing and evaluate how the different processing steps influence automatic speech recognition in noise. The model features large dynamic compression (>60 dB) and a realistic sensory cell model. The compression range was well matched to the limited dynamic range of the sensory cells and the model yielded surprisingly high recognition scores. We also developed a computationally efficient simplified model of auditory processing and found that a model of adaptation could improve recognition accuracy. Adaptation is a basic principle of neuronal processing, which accentuates signal onsets. Applying this adaptation model to melfrequency cepstral coefficient (MFCC) feature extraction enhanced recognition accuracy in noise (AURORA 2 task, averaged recognition scores) from 56.4% to 75.6% (clean training condition), a relative improvement of 41% in word error rate. Adaptation outperformed RASTA processing by more than 10%, which corresponds to a relative improvement of 31%.
Interaction of magnetic and non-magnetic metals with graphene

The investigation of the electronic properties of graphene-metal interfaces is of great current interest, not only from a fundamental point of view, but also with respect to possible applications in electronic devices and other fields. The (111) surface of iridium is used as a template for graphene growth, in view of the weak interaction between the partners, and due to the excellent structural quality. The used experimental method is photoemission and –absorption. The intercalation of transition metal thin films offers the possibility to modify the electronic properties of graphene. I report on my findings for graphene on bulk and intercalated metals in between graphene and Ir(111). Intercalated copper layers are a particularly important example since the signatures of hybridization between metal states and the graphene π band are especially clear. Moreover the mechanism of band gap opening can be explained by DFT calculations. On the other hand electronic and magnetic structure investigations for intercalated cobalt layers show the emergence of ferromagnetic ordering in the cobalt films and is reported and analyzed by recourse to theory. The transfer of magnetic moment onto the formerly paramagnetic graphene π states is evident from xray magnetic circular dichroism measurements at the carbon K edge. Altogether, a consistent overview of metal-graphene interface electronic structure is given.
Executive function and fluid intelligence after frontal lobe lesions

Many tests of specific ‘executive functions’ show deficits after frontal lobe lesions. These deficits appear on a background of reduced fluid intelligence, best measured with tests of novel problem solving. For a range of specific executive tests, we ask how far frontal deficits can be explained by a general fluid intelligence loss. For some widely used tests, e.g. Wisconsin Card Sorting, we find that fluid intelligence entirely explains frontal deficits. When patients and controls are matched on fluid intelligence, no further frontal deficit remains. For these tasks too, deficits are unrelated to lesion location within the frontal lobe. A second group of tasks, including tests of both cognitive (e.g. Hotel, Proverbs) and social (Faux Pas) function, shows a different pattern. Deficits are not fully explained by fluid intelligence and the data suggest association with lesions in the right anterior frontal cortex. Understanding of frontal lobe deficits may be clarified by separating reduced fluid intelligence, important in most or all tasks, from other more specific impairments and their associated regions of damage.
phylogenetics with

Computational evolutionary biology, statistical phylogenetics, and coalescent-based population genetics are becoming increasingly central to the analysis and understanding of molecular sequence data. We present the Bayesian Evolutionary Analysis by Sampling Trees (BEAST) software package version 1.7, which implements a family of Markov chain Monte Carlo (MCMC) algorithms for Bayesian phylogenetic inference, divergence time dating, coalescent analysis, phylogeography, and related molecular evolutionary analyses. This package includes an enhanced graphical user interface program called Bayesian Evolutionary Analysis Utility (BEAUti) that enables access to advanced models for molecular sequence and phenotypic trait evolution that were previously available to developers only. The package also provides new tools for visualizing and summarizing multispecies coalescent and phylogeographic analyses. BEAUti and BEAST 1.7 are open source under the GNU lesser general public license and available at http://beast-mcmc.googlecode. com and http://beast.bio. ed.ac. uk.
The State of Coronary Arteries in Perimenopausal Women With Chest Pain

Background The goal of the study was to assess the state of coronary arteries in perimenopausal women undergoing examination before prescription of hormonal replacement therapy. Methods One hundred ninety-three patients were screened, and 43 of them were selected for inclusion to the study. Pretest probability of coronary heart disease (CHD) was 47% for patients with typical angina pain and 20.5% with atypical pain. Patients with typical and atypical pain syndromes had no essential differences in terms of age, but had different hormonal status assessed by follicle stimulating hormone level and different menopause durations. Results Atherosclerotic lesion causing luminal occlusion by more than 50% was detected in 13 (61.9%) patients with typical pain syndrome and in eight (36.4%) patients with atypical pain syndrome manifestations. Numbers of patients with intact coronary arteries were six (28.6%) and 10 (45.5%) in groups with typical and atypical pain syndrome, respectively. Myocardial bridges were found in five (23.8%) patients with typical pain syndrome and seven (31.8%) patients with atypical manifestations. Conclusion In spite of modest pretest CHD probability in the group with typical pain syndrome and low pretest CHD probability in the group with atypical manifestations, patients with major atherosclerotic lesions were detected in both groups. Use of this approach to assessment of the state of coronary arteries allows detecting patients at high risk of cardiovascular complications and avoiding the use of hormonal replacement therapy in them.
Cell Broadband Engine Architecture and its first implementation - A performance view

The Cell Broadband Engine™ (Cell/B.E.) processor is the first implementation of the Cell Broadband Engine Architecture (CBEA), developed jointly by Sony, Toshiba, and IBM. In addition to use of the Cell/B.E. processor in the Sony Computer Entertainment PLAYSTATION® 3 system, there is much interest in using it for workstations, media-rich electronics devices, and video and image processing systems. The Cell/B.E. processor includes one PowerPC® processor element (PPE) and eight synergistic processor elements (SPEs). The CBEA is designed to be well suited for a wide variety of programming models, and it allows for partitioning of work between the PPE and the eight SPEs. In this paper we show that the Cell/B.E. processor can outperform other modern processors by approximately an order of magnitude and by even more in some cases.
On the Suitability of Discrete-Time Receivers for Software-Defined Radio

CMOS radio receiver architectures, based on radio frequency (RF) sampling followed by discrete-time (D-T) signal processing via switched-capacitor circuits, have recently been proposed for dedicated radio standards. This paper explores the suitability of such D-T receivers for highly flexible software-defined radio (SDR) receivers. Via symbolic analysis and simulations the authors analyze the properties of D-T receivers, and show that at least three challenges exist to make a D-T receiver work for SDR: 1) the sampling clock frequency is related to the radio frequency, complicating baseband filter design; 2) a frequency-dependent phase shift is introduced by pseudo-quadrature and pseudo-differential sampling; 3) the conversion gain of a charge sampling front-end is strongly frequency-dependent. Compared to a mixer based radio receiver, extra costs are needed to solve these problems.
Dogwild! – Distributed Hogwild for CPU & GPU

Deep learning has enjoyed tremendous success in recent years. Unfortunately, training large models can be very time consuming, even on GPU hardware. We describe a set of extensions to the state of the art Caffe library [3], allowing training on multiple threads and GPUs, and across multiple machines. Our focus is on architecture, implementing asynchronous SGD without increasing Caffe’s complexity. We isolate parallelization from Caffe’s existing SGD code, train unmodified models, and run on commodity hardware. Isolation is achieved by extending the Hogwild model, i.e. running parallel SGD solvers without synchronization, by also removing synchronization between solvers and components in charge of streaming gradients between nodes. In this modular design, components interact exclusively through unsynchronized reads and writes to the weight buffer. Each component is free to loop over the weights at a different pace, keeping both compute and network resources fully utilized. SGD’s resiliency against gradient loss allows further performance improvements by avoiding reliable network protocols. It enables the use of multicast messages, and of low level packets streaming through raw sockets or InfiniBand verbs. We show linear performance scaling for small clusters on MNIST, and early results on ImageNet.
Heat Treatments of Fe-Mn-Si Based Alloys: Mechanical Properties and Related Shape Memory Phenomena

Heat treatments are usual means for modifying alloy microstructures and, consequently, to control mechanical properties. The aim of this work was to find suitable processes for improving the shape memory effect (SME) of Fe–Mn–Si-based alloys. In particular, we studied mechanisms that affect the plastic deformation of the austenite phase. A Fe–15Mn–5Si–9Cr–5Ni alloy was deformed by rolling at different temperatures and subsequently annealed at recovery- and recrystallization-temperature. The mechanical properties of the material after processing were evaluated by performing tension and flexure tests. The SME of room temperature deformed specimens was measured after heating them to 550°C for shape recovery. We found that the material rolled at 800°C followed by an annealing treatment at 650°C recovers nearly 95 % of a 3 % deformation. In this thermo-mechanical condition, the material has a yield stress of 450 MPa and an ultimate tensile strength of 880 MPa, corresponding to a total elongation of about 16 %. Optical and electron microscopy observations show that the matrix annealed at high temperature contains a low density of defects. As a consequence, there are fewer nucleation sites for martensite and the associated SME is low. On the other hand, annealing at intermediate temperatures (around 650°C) produces a favorable structure containing a large density of stacking faults.
Effects of Three-Lobe Bearing Geometries on Rigid-Rotor Stability

The stability of a rigid rotor mounted in three-lobe bearings is theoretically studied for which the preload factor, offset factor, and load orientation are systematically varied. Rigid-rotor stability maps are presented. Results indicate that bearings with offset factors of 0.1 or less and moderate preload factors are often more stable than those with larger offset factors. Results also indicate that, for a given preload and load orientation, a particular offset factor exists which produces minimum stability (such bearing geometries should be avoided). Finally, increasing the preload factor was found to increase the rigid-rotor stability. Presented at the 36th Annual Meeting in Pittsburgh, Pennsylvania, May 11–14, 1981
REMOVAL OF ARTIFACTS AND ANALYSIS OF EEG SIGNAL USING DATA DRIVEN PARAMETERS

— Artifacts causes the incorrect reading of Electroencephalography (EEG) Signal. Specific filtering technique is to be adopted to remove the artifacts. In this paper, combination of Adaptive Filtering (AF) and Stationary Wavelet Transform (SWT) is proposed to remove artifacts from EEG signal. Statistical Parameters have been computed from the clean EEG signal. The result reveals the variations of the parameters during normal, pre-ictal and ictal status.
Molecular analysis of neural crest migration

The neural crest (NC) cells have been called the ‘explorers of the embryos’ because they migrate all over the embryo where they differentiate into a variety of diverse kinds of cells. In this work, we analyse the role of different molecules controlling the migration of NC cells. First, we describe the strong similarity between the process of NC migration and metastasis in tumour cells. The epithelial–mesenchymal transition process that both kinds of cells undergo is controlled by the same molecular machinery, including cadherins, connexins, Snail and Twist genes and matrix metalloproteases. Second, we analysed the molecular signals that control the patterned migration of the cephalic and trunk NC cells. Most of the factors described so far, such as Eph/ephrins, semaphorins/neuropilins and Slit/Robo, are negative signals that prohibit the migration of NC cells into target areas of the embryo. Finally, we analyse how the direction of migration is controlled by regulation of cell polarity and how the planar cell polarity or non-canonical Wnt signalling is involved in this process.
Sending Hidden Data via Google Suggest

Google Suggest is a service incorporated within Google Web Search which was created to help user find the right search phrase by proposing the autocompleting popular phrases while typing. The paper presents a new network steganography method called StegSuggest which utilizes suggestions generated by Google Suggest as a hidden data carrier. The detailed description of the method's idea is backed up with the analysis of the network traffic generated by the Google Suggest to prove its feasibility. The traffic analysis was also performed to discover the occurrence of two TCP options: Window Scale and Timestamp which StegSuggest uses to operate. Estimation of method steganographic bandwidth proves that it is possible to insert 100 bits of steganogram into every suggestions list sent by Google Suggest service.
Segmentation of ultrasound B-mode images with intensity inhomogeneity correction

Displayed ultrasound (US) B-mode images often exhibit tissue intensity inhomogeneities dominated by nonuniform beam attenuation within the body. This is a major problem for intensity-based, automatic segmentation of video-intensity images because conventional threshold-based or intensity-statistic-based approaches do not work well in the presence of such image distortions. Time gain compensation (TGC) is typically used in standard US machines in an attempt to overcome this. However this compensation method is position-dependent which means that different tissues in the same TGC time-range (or corresponding depth range) will be, incorrectly, compensated by the same amount. Compensation should really be tissue-type dependent but automating this step is difficult. The main contribution of this paper is to develop a method for simultaneous estimation of video-intensity inhomogeneities and segmentation of US image tissue regions. The method uses a combination of the maximum a posteriori (MAP) and Markov random field (MRF) methods to estimate the US image distortion field assuming it follows a multiplicative model while at the same time labeling image regions based on the corrected intensity statistics. The MAP step is used to estimate the intensity model parameters while the MRF step provides a novel way of incorporating the distributions of image tissue classes as a spatial smoothness constraint. We explain how this multiplicative model can be related to the ultrasonic physics of image formation to justify our approach. Experiments are presented on synthetic images and a gelatin phantom to evaluate quantitatively the accuracy of the method. We also discuss qualitatively the application of the method to clinical breast and cardiac US images. Limitations of the method and potential clinical applications are outlined in the conclusion.
Constructing Bayesian Networks for Medical Diagnosis from Incomplete and Partially Correct Statistics

The paper discusses several knowledge engineering techniques for the construction of Bayesian networks for medical diagnostics when the available numerical probabilistic information is incomplete or partially correct. This situation occurs often when epidemiological studies publish only indirect statistics and when significant unmodeled conditional dependence exists in the problem domain. While nothing can replace precise and complete probabilistic information, still a useful diagnostic system can be built with imperfect data by introducing domain-dependent constraints. We propose a solution to the problem of determining the combined influences of several diseases on a single test result from specificity and sensitivity data for individual diseases. We also demonstrate two techniques for dealing with unmodeled conditional dependencies in a diagnostic network. These techniques are discussed in the context of an effort to design a portable device for cardiac diagnosis and monitoring from multimodal signals.
Robust Gradient-Based 3-D/2-D Registration of CT and MR to X-Ray Images

One of the most important technical challenges in image-guided intervention is to obtain a precise transformation between the intrainterventional patient's anatomy and corresponding preinterventional 3-D image on which the intervention was planned. This goal can be achieved by acquiring intrainterventional 2-D images and matching them to the preinterventional 3-D image via 3-D/2-D image registration. A novel 3-D/2-D registration method is proposed in this paper. The method is based on robustly matching 3-D preinterventional image gradients and coarsely reconstructed 3-D gradients from the intrainterventional 2-D images. To improve the robustness of finding the correspondences between the two sets of gradients, hypothetical correspondences are searched for along normals to anatomical structures in 3-D images, while the final correspondences are established in an iterative process, combining the robust random sample consensus algorithm (RANSAC) and a special gradient matching criterion function. The proposed method was evaluated using the publicly available standardized evaluation methodology for 3-D/2-D registration, consisting of 3-D rotational X-ray, computed tomography, magnetic resonance (MR), and 2-D X-ray images of two spine segments, and standardized evaluation criteria. In this way, the proposed method could be objectively compared to the intensity, gradient, and reconstruction-based registration methods. The obtained results indicate that the proposed method performs favorably both in terms of registration accuracy and robustness. The method is especially superior when just a few X-ray images and when MR preinterventional images are used for registration, which are important advantages for many clinical applications.
A comprehensive data-driven approach to evaluating quality of experience on large-scale internet video service

Internet video is currently one of the most popular Internet services, accounting for more than 50% of the overall Internet traffic. Various access patterns of users worldwide contribute to increasing complex scenarios of Internet video. Under the circumstances, there emerges a valuable yet challenging topic that industry and academia keep focusing on: how to evaluate quality of experience (QoE) of Internet video in the wild? In this paper, we propose a comprehensive data-driven approach to evaluate QoE based on massive dataset extracted from a large-scale Internet video service provider. With the methods of feature engineering and fuzzy theory, we exploit user's situational features and session's quality features. Then we conceive an appropriate QoE evaluating model called bagging-based Bayesian factorization machine to correlate the aforementioned features with user's QoE. The experimental results demonstrate that our approach is adaptive for QoE evaluation on Internet video both in efficiency and effectiveness. Moreover, our approach achieves higher degree of accuracy compared with baseline methods, including what associated works present.
Mental fatigue alters the speed and the accuracy of the ball in table tennis

ABSTRACT This study aimed at evaluating the effects of mental and muscle fatigue on table tennis performance. Mental fatigue (MF) was induced by completion of 90 minutes of the AX-CPT; muscle fatigue was induced by completion of an eccentric exercise performed with the elbow flexors (biceps fatigue, BF) or the knee extensors (quadriceps fatigue, QF). The control condition consisted of watching a movie. Stroke parameters (speed and accuracy of the ball), as well as feelings of fatigue and force production capacity of the elbow flexors (BF, MF and control conditions) and knee extensors (QF condition), were assessed pre and post fatigue protocols. Feelings of fatigue increased post fatigue protocols. Force production capacity decreased only in the BF and QF conditions. BF and MF induced a decrease in accuracy. This decrease in accuracy was associated with an increased ball speed in the BF condition, and a decreased ball speed in the MF condition. QF had a negligible effect on stroke performance. Our results suggest that both mental fatigue, and muscle fatigue, significantly impair table tennis performance and therefore coaches should take into account both the physical and mental state of table tennis players to optimize performance.