Miracle-dz/UniFAR-FTUs huggingface dataset:
Meta-analysis of the placebo-treated groups in clinical trials of progressive MS

The behavior of the control groups can substantially affect the power and outcome of a clinical trial.We report a meta-analysis of the control groups of four large, double-blind, placebo-controlled clinical trials of immunosuppressive treatment of progressive MS to address the sensitivity of five hypothetical definitions of treatment failure (TF). The rate of TF in the aggregate control groups (n = 427) was 31% when a confirmed increase of 1.0 expanded disability status scale (EDSS) point was required at the end of the trial; it was 51% when confirmation was not required and TF was allowed at the first point where the criteria for TF were met. The rate of confirmed TF was 45% when the TF criteria were indexed to baseline EDSS, accounting for the observed differences in staying times at different EDSS levels. We developed models predicting TF in progressive MS. In addition to baseline EDSS, the pyramidal functional score and, for one definition, brainstem functional score were associated with probability of TF. NEUROLOGY 1996;46: 1613-1619
Image denoising based on Haar wavelet transform

Wavelet transform has widely applied in image denoising, and how to select the threshold is the key to wavelet image denoising. The paper put forward the algrithm for image denoising based on harr wavelet transform. Fisrt, The image with noise is decomposed by Haar wavelt transform, then select the soft threshold to clean the image noise. Experiments show that the algorithm can reduce image noise effectively and improve the detail effect of picture and raise the PSNR value of image.
MOOC Pedagogy: Gleaning Good Practice from Existing MOOCs

The revolutionary potential of massive open online courses (MOOCs) has been met with much skepticism, particularly in terms of the quality of learning offered. Believing that a focus on learning is more important than a focus on course completion rates, this position paper presents a pedagogical assessment of MOOCs using Chickering and Gamson's Seven Principles of Good Practice in Undergraduate Education and Bloom's taxonomy, based on the author's personal experience as a learner in four xMOOCs. Although most xMOOCs have similar characteristics, the author shows that they are not all offered in exactly the same way, and some provide more sound pedagogy that develops higher order thinking, whereas others do not. The author uses this evaluation, as well as reviews of other xMOOCs in the literature, to glean some good pedagogical practices in xMOOCs and areas for improvement.
HEp-2 Cells Classification Using Morphological Features and a Bundle of Local Gradient Descriptors

A system for automatic classification of staining patterns in IIF imaging is presented. A full pipeline of pre-processing, feature extraction and classification stages is designed in order to overcome specific challenges posed by the nature of the data. In the preprocessing stage the images are subjected to normalization and de-noising using a sparse representation-based technique. A set morphological features, extracted using multi-level thresholding, is combined with a bundle of local gradient descriptors, selected so as to encode textural and structural information of the fluorescent patterns in multiple scales. The proposed method was evaluated using a dataset with over 10K images achieving over 90 percent of classification accuracy.
A Magneto-Electric Dipole for Unidirectional UWB Communications

A new magneto-electric dipole antenna is designed. The antenna is composed of a horizontal bowtie electric dipole, a center-fed loop antenna functioning as a magnetic dipole and a rectangular cavity. A microstrip-to-stripline transition is employed as a balun to feed the antenna. A prototype was fabricated and measured. Results show that an impedance bandwidth of 110%, with SWR ≤ 2 from 3.08 to 10.6 GHz, was achieved. A stable gain of 8.7 ±1.9 dBi was realized by using the rectangular cavity. Stable radiation pattern with low cross polarization ( ≤ -20 dB), low back radiation ( ≤ -13 dB) and symmetrical E- and H-plane patterns was found over the operating frequencies. Moreover, the impulse response is analyzed which reveals the antenna with good time domain characteristic.
On the improvement of a fault classification scheme with implications for white-box testing

Different testing techniques can be more or less effective on different fault types; therefore, testing methods that are most likely to detect the most common fault types should be preferred. However, to enable such a selection of testing methods, a suitable and effective fault classification scheme is essential. Much software testing research proposes techniques to generate test cases and evaluates these techniques based on some hypothesized fault classification scheme. However, there is a lack in the justification of whether such 'hypothesized faults' are realistic and how often these faults occur. Recently, Pan et al. analyzed the syntactic changes in the source code, made in fixing faults, of 7 open source software projects implemented in Java. Based on their experience, they proposed a fault classification scheme with relative frequencies of each fault type. As always, readers may question whether the resulting fault classification is reasonable and appropriate. Hence, we applied their method to Checkstyle, another open source Java program, as the subject of our study, hoping to validate the appropriateness of their fault classification scheme, with particular application for selecting testing methods. While we generally found their classification scheme reasonable, we also noted that some faults could be classified in multiple ways. We also found that the frequencies of fault categories in Checkstyle were significantly different to the seven systems studied by Pan et al., which had all shown to have quite similar frequencies. We identified several potential improvements to their classification, permitting the classification of a larger proportion of faults. We have identified new implications of the combined results for white-box testing, and proposed follow-up studies to examine these issues in more detail.
Right Ventricle Functional Assessment: Have New Techniques Supplanted the Old Faithful Conductance Catheter?

This review explores the historical development of conductance catheterization of the human right ventricle (RV) and its current diagnostic role in assessing RV function in an era of contemporary noninvasive imaging. Significant advances in echocardiography, cardiothoracic computed tomography, and cardiac magnetic resonance in the last decade have led a paradigm shift away from invasive hemodynamic assessment toward noninvasive measurement of RV function. However, imaging modalities are not without some disadvantages. For example, they do not provide the beat-to-beat pressure-volume assessment that is obtained by conductance catheterization, which is still arguably the gold standard for measuring cardiac performance. Right heart catheterization remains an integral part of the assessment of patients with RV dysfunction, and a burgeoning interest in early RV insufficiency in a range of cardiopulmonary diseases has brought the detailed interrogation of RV function back into focus. Although conductance volume assessment of the RV is more limited than the left ventricle, the scope for improving the understanding of RV adaptation to pulmonary and valvular pathologies and RV myocardial disease by using a conductance catheter still exists. We review the up-to-date functional applications of echocardiography and computed tomography/cardiac magnetic resonance to assess the RV and illustrate the potential of contemporary conductance catheter techniques to complement noninvasive imaging in the assessment of RV function.
Enzyme Structure and Mechanism

This book explores the mechanisms of enzyme catalysis and specificity, from both the theoretical and experimental points of view. The emphasis is on kinetics and chemical thermodynamics as methods for establishing mechanisms at the atomic level for enzymes whose tertiary structure has already been solved by X-ray crystallography. Those with a good grasp of first-year organic chemistry, physical chemistry, and introductory biochemistry will find that this book starts where their basic courses left off, with a review of catalytic mechanisms and the equations of enzyme kinetics, and then moves into such topics as pre-steady-state kinetics and experimental methods, pH dependence, enzyme-substrate complementarity, and specificity. One chapter is devoted to explaining in detail how kinetic experiments have helped elucidate the mechanisms of selected enzymes by means of the detection of intermediates; the author is careful to discuss what constitutes proof that a certain substance is an intermediate, and reviews sources of possible experimental error. Although the book contains little on multi-substrate systems or on the methods of structure determination themselves, it is nevertheless a well-written, compact introduction to an important field.
A Simulation Of Disagreement For Control Of Rational Cheating In Peer Review

Understanding the peer review process could help research and shed light on the mechanisms that underlie crowdsourcing. In this paper, we present an agent-based model of peer review built on three entities — the paper, the scientist and the conference. The system is implemented on a BDI platform (Jason) that allows to define a rich model of scoring, evaluating and selecting papers for conferences. Then, we propose a programme committee update mechanism based on disagreement control that is able to remove reviewers applying a strategy aimed to prevent papers better than their own to be accepted ("rational cheating"). We analyze a homogeneous scenario, where all conferences aim to the same level of quality, and a heterogeneous scenario, in which conferences request different qualities, showing how this affects the update mechanism proposed. We also present a first step toward an empirical validation of our model that compares the amount of disagreements found in real conferences with that obtained in our simulations.
MIXED-PHASE SPEECH MODELING AND FORMANT ESTIMATION , USING DIFFERENTIAL PHASE SPECTRUMS

This paper introduces a new speech model, termed as the mixed-phase model, based on the assumption that the speech signal is produced by convolution of a maximum phase glottal excitation signal with a minimum phase vocal tract filter impulse response. The glottal excitation signal is assumed to be an anti-causal stable signal and the vocal tract filter is assumed to be causal and stable. For estimating resonances of the maximum phase signal (source) and the minimum phase filter (vocal tract filter), use of differential phase spectrums of z-transforms is proposed.
Fabrication and tailoring of silicon photonic devices via focused ion beam

As Silicon Photonics is developing further towards integration on a single platform, the need for precise fabrication is paramount and no matter how developed a technology is, there is always potential for error at the wafer and chip level. In combination with Focused Ion Beam (FIB) technology, we present direct write methods to fabricate and tailor Silicon Photonic devices to offer the potential of prototyping, testing and correction in a post-processing environment. However, inherent in most FIB processing is the introduction of large optical loss due to damage and implantation of Gallium, because Gallium is typically the gas species used in FIBs. Therefore, methods of processing to minimise potential loss and changes to the original device design will be presented alongside results and a discussion offering a comparison with other potential methods.
Efficacy of ALK 5 inhibition in myelofibrosis

1Department of Immunology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, USA. 2Department of Hematology, Tianjin Medical University General Hospital, Tianjin, China. 3Department of Oncology, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, New York, USA. 4Department of Pathology, Peggy and Stephenson Cancer Center, Oklahoma University Health Sciences Center, Oklahoma City, Oklahoma, USA. 5Department of Biotherapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Key Laboratory of Cancer Immunology and Biotherapy, Key Laboratory of Cancer Prevention and Therapy, Tianjin, PR China. 6Translational Science, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, USA. 7Department of Hematopathology and Laboratory Medicine, 8Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, USA. 9Leukemia Center, Memorial Sloan Kettering Cancer Center, New York City, New York, USA.
An efficient low cost background subtraction method to extract foreground object during human tracking

Moving object detection in video streams is the fundamental and relevant step in many computer vision applications such as video surveillance for people tracking. Background subtraction is a widely used approach for detecting moving objects in videos from static cameras. This paper describes an efficient background subtraction technique for extracting the moving objects from a scene. Gaussian mixture models (GMM) gives best results than other segmentation methods.
X-ray residual stress analysis in thin films under grazing incidence – basic aspects and applications

Abstract Residual stress fields in polycrystalline materials induced by mechanical surface processing or coating often are highly inhomogeneous with respect to depth z below the sample surface. This even applies for thin films, the thickness of which is usually much smaller than the penetration depth t of the X-rays. Therefore, X-ray residual stress analysis in thin films is advantageously performed under grazing diffraction conditions. To avoid erroneous averaging over the film thickness, both the radiation used and the methods applied to analyse the residual stress distributions have to be adapted carefully to the particular situation. In this paper some fundamental aspects concerning the meaning of the X-ray penetration depth for very thin films and the important role of refraction in the generalised non-symmetric case of grazing incidence diffraction are discussed and illustrated by practical examples from different fields in thin film diffraction analysis.
Fast incremental maintenance of approximate histograms

Many commercial database systems maintain histograms to summarize the contents of large relations and permit efficient estimation of query result sizes for use in query optimizers. Delaying the propagation of database updates to the histogram often introduces errors into the estimation. This article presents new sampling-based approaches for incremental maintenance of approximate histograms. By scheduling updates to the histogram based on the updates to the database, our techniques are the first to maintain histograms effectively up to date at all times and avoid computing overheads when unnecessary. Our techniques provide highly accurate approximate histograms belonging to the equidepth and Compressed classes. Experimental results show that our new approaches provide orders of magnitude more accurate estimation than previous approaches.An important aspect employed by these new approaches is a backing sample, an up-to-date random sample of the tuples currently in a relation. We provide efficient solutions for maintaining a uniformly random sample of a relation in the presence of updates to the relation. The backing sample techniques can be used for any other application that relies on random samples of data.
Mechanisms of backtrack recovery by RNA polymerases I and II

Significance Transcription of the genetic information from DNA into RNA is the central process of gene expression, and it is performed by enzymes called RNA polymerases (Pol). Transcription is interspersed with a proofreading mechanism called backtracking, during which the polymerase moves backward on the DNA template and displaces the RNA 3′ end from its active site. Backtrack recovery can happen by diffusion of the enzyme along the DNA or cleavage of the backtracked RNA. Using single-molecule optical tweezers and stochastic theory, we quantified distinct diffusion and cleavage rates of Pol I and Pol II and described distinct backtrack recovery strategies of these essential enzymes. During DNA transcription, RNA polymerases often adopt inactive backtracked states. Recovery from backtracks can occur by 1D diffusion or cleavage of backtracked RNA, but how polymerases make this choice is unknown. Here, we use single-molecule optical tweezers experiments and stochastic theory to show that the choice of a backtrack recovery mechanism is determined by a kinetic competition between 1D diffusion and RNA cleavage. Notably, RNA polymerase I (Pol I) and Pol II recover from shallow backtracks by 1D diffusion, use RNA cleavage to recover from intermediary depths, and are unable to recover from extensive backtracks. Furthermore, Pol I and Pol II use distinct mechanisms to avoid nonrecoverable backtracking. Pol I is protected by its subunit A12.2, which decreases the rate of 1D diffusion and enables transcript cleavage up to 20 nt. In contrast, Pol II is fully protected through association with the cleavage stimulatory factor TFIIS, which enables rapid recovery from any depth by RNA cleavage. Taken together, we identify distinct backtrack recovery strategies of Pol I and Pol II, shedding light on the evolution of cellular functions of these key enzymes.
FURTHER STUDIES IN THE COMBINATION OF GRAVIMETRIC AND SATELLITE DATA

Abstract : The report is composed of two portions. The first is a general theoretical discussion of the problem of assuming compatibility of surface gravity data and potential coefficients derived from satellite orbital analysis. The second part of the report describes a combination of gravimetric and satellite data using 5 degrees x 5 degrees mean free air anomalies supplied by the Aeronautical Chart and Information Center, and a set of potential coefficients designated NWL 81 derived by Anderle. Several methods were applied to this data to obtain an adjusted set of potential coefficients complete to n = 15 plus an additional number of higher degree resonance terms. In addition three sets of adjusted 5 degrees x 5 degrees mean free air anomalies were obtained. From these anomalies a set of potential coefficients complete to n = 30 was derived by the development formulas. Analysis of the various solutions indicated that one was to be preferred over all others. Problems continue to remain with respect to proper weighting of the data.
Edge guided single depth image super resolution

Recently, consumer depth cameras have gained significant popularity due to their affordable cost. However, the limited resolution and quality of the depth map generated by these cameras are still problems for several applications. In this paper, we propose a novel framework for single depth image super resolution guided by a high resolution edge map constructed from the edges in the low resolution depth image via a Markov Random Field (MRF) optimization. With the guidance of the high resolution edge map, the high resolution depth image is up-sampled via a joint bilateral filter. The edge guidance not only helps avoid artifacts introduced by direct texture prediction, but also reduces the jagged artifacts and preserves the sharp edges. Experimental results demonstrate the effectiveness of our proposed algorithm compared to previously reported methods.
A truthful incentive mechanism for emergency demand response in colocation data centers

Data centers are key participants in demand response programs, including emergency demand response (EDR), where the grid coordinates large electricity consumers for demand reduction in emergency situations to prevent major economic losses. While existing literature concentrates on owner-operated data centers, this work studies EDR in multi-tenant colocation data centers where servers are owned and managed by individual tenants. EDR in colocation data centers is significantly more challenging, due to lack of incentives to reduce energy consumption by tenants who control their servers and are typically on fixed power contracts with the colocation operator. Consequently, to achieve demand reduction goals set by the EDR program, the operator has to rely on the highly expensive and/or environmentally-unfriendly on-site energy backup/generation. To reduce cost and environmental impact, an efficient incentive mechanism is therefore in need, motivating tenants' voluntary energy reduction in case of EDR. This work proposes a novel incentive mechanism, Truth-DR, which leverages a reverse auction to provide monetary remuneration to tenants according to their agreed energy reduction. Truth-DR is computationally efficient, truthful, and achieves 2-approximation in colocation-wide social cost. Trace-driven simulations verify the efficacy of the proposed auction mechanism.
Estimating Speech Recognition Accuracy Based on Error Type Classification

Methods for estimating the speech recognition accuracy without using manually transcribed references are beneficial to the research and development of automatic speech recognition technology. This paper proposes recognition accuracy estimation methods based on error type classification (ETC). ETC is an extension of confidence estimation. In ETC, each word in the recognition results (recognized word sequences) for the target speech data is probabilistically classified into three categories: the correct recognition (C), substitution error (S), and insertion error (I). Deletion errors (D) that can occur at interword positions in the recognition results are also probabilistically detected. By summing these CSID probabilities individually, the numbers of CSIDs and, as a result, the two standard recognition accuracy measures, i.e., the percent correct and word accuracy (WAcc), for the speech data can be estimated without using the reference transcriptions. Two recognition accuracy estimation methods based on ETC are proposed. In the first easy-to-use method, ETC is performed by converting the recognition results represented as word confusion networks into word alignment networks (WANs). In the second and more accurate method, the WAN-based ETC results are refined with conditional random fields (CRFs) using various types of additional features extracted for each of the recognized words. Experiments using English and Japanese lecture speech corpora show that the recognition accuracy can be accurately estimated with the CRF-based method. The correlation coefficient and root mean square error between the lecture-level true WAccs calculated using the reference transcriptions and those estimated with the CRF-based method are 0.97 and lower than 2%, respectively. A series of additional experiments and analyses are also conducted to better understand the effectiveness of the CRF-based method.