Miracle-dz/UniFAR-FTUs huggingface dataset:
Informed Ego-noise Suppression Using Motor Data-driven Dictionaries

The suppression of ego-noise for (humanoid) robots is typically addressed by learning-based techniques. In this paper, we propose a novel approach which models significant parts of ego-noise spectrograms based on motor data and does not require a prior training step. Accordingly, the intrinsic harmonic structure of ego noise is taken into account by introducing a nonnegative matrix factorization (NMF) framework with motor data-driven dictionaries. Limited improvement was observed by employing an additional pre-trained small-sized dictionary accounting for the residual ego-noise. The presented approach exhibits comparable suppression performance to an audio only-based approach trained specifically to the scenario, while the number of dictionary elements which require prior learning can be reduced by a factor of two. For ego-noise resulting from previously unseen movements, the proposed method shows consistently superior suppression results while the audio only-based approach degrades drastically.
Feature-based Extraction using Typed Dependencies on Political Commentaries

Document-level sentiment classification determines the sentiment orientation of a given text. However, it fails to identify the pieces of information that make a text positive, neutral, or negative. Feature-based extraction overcomes this limitation by identifying the objects and opinions being described in the text. Furthermore, feature-based extraction maps these opinions to their corresponding objects allowing fine-grained sentiment classification. There have been abundant researches made on opinion mining of products and news, but there is no featurebased extraction done under political domain. This work aims to extract relevant features and opinions in political commentaries by using grammatical relations and labels (part of speech, phrasal, and clausal labels) in the parse tree.
Cholesterol Levels and Statin Use in Patients With Coronary Heart Disease Treated in Primary Care Settings

Introduction Therapy with 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors, or statins, has proven to be effective in the treatment of lipid disorders. However, statin therapy continues to be underused, even though statins are a relatively safe and well-tolerated class of agents. In this study, we assessed trends in lipid control in patients with heart disease who receive most of their health care in primary care clinics. The objective was to determine whether systems of care implemented within a large medical group are associated with improved treatment and control of dyslipidemia in a high-risk group of coronary heart disease patients. Methods All adults with heart disease in a Minnesota medical group (N = 2947) were identified using diagnosis and procedure codes related to coronary heart disease (sensitivity = 0.85; positive predictive value = 0.89) in 1996. Study subjects were observed from 1995 to 1998. Subjects had a baseline and follow-up test for low-density lipoprotein cholesterol and high-density lipoprotein cholesterol. Changes between baseline and follow-up measurements and trends in the use of statins and other lipid-active agents among the study subjects were analyzed. Results Among 1388 subjects with two or more eligible lipid measurements, mean low-density lipoprotein cholesterol improved from 137.6 mg/dL to 111.0 mg/dL (P < .001), and mean high-density lipoprotein cholesterol improved from 42.3 mg/dL to 46.3 mg/dL (P < .001). The percentage of patients with low-density lipoprotein cholesterol ≤100 mg/dL rose from 12.5% to 39.8% (P < .001), and the percentage with high-density lipoprotein cholesterol ≥40 mg/dL rose from 52.5% to 67.6% (P < .001). In multivariate models, statin use was identified as the main factor that contributed to the improvement in low-density lipoprotein cholesterol (P < .001). Men had greater decreases in low-density lipoprotein cholesterol than women after adjusting for other variables (P < .001). Statin use rose from 24.3% at baseline to 69.6% at follow-up. The statin discontinuation rate was 8.3% for baseline statin users and 12.2% for subjects who used statins at any time during the study period. Conclusion Investment in better heart disease care for patients in primary care clinics led to major improvement in lipid control over 30 months, primarily due to increased statin use. Improvements in low-density lipoprotein cholesterol and high-density lipoprotein cholesterol were sufficient to substantially reduce risk of subsequent major cardiovascular events.
Ordering diffusion-weighted MRI measurements improves results from partially completed scans

P. A. Cook, M. R. Symms, P. A. Boulby, D. C. Alexander Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom, Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, London, United Kingdom Introduction Diffusion-tensor MRI often uses a spherical sampling scheme, which acquires images sequentially with diffusion weighting gradients in unique directions distributed isotropically on the hemisphere. If not all of the measurements can be completed, the quality of diffusion tensors fitted to the partial scan is sensitive to the order of the gradient directions in the scanner protocol. Dubois et al [1] propose a novel acquisition scheme that improves the results from partial scans by making the electrostatic repulsion dependent on the order of the points in the acquisition sequence. However, Cook et al [2] showed that similar results are possible by ordering the directions in an isotropic point set without modifying any of the directions. This has the advantage of preserving the isotropic distribution of the complete set of points, and allows the method to be incorporated into existing scanner protocols without changing the data yielded from a complete scan. However, the method of Cook et al divided the directions into independent subsets for use in motion correction, and a partial scan consisting of an incomplete number of these subsets may be anisotropic. In this work we propose a new ordering that is explicitly designed to provide the best results from any partially completed data.
Modeling for text compression

The best schemes for text compression use large models to help them predict which characters will come next. The actual next characters are coded with respect to the prediction, resulting in compression of information. Models are best formed adaptively, based on the text seen so far. This paper surveys successful strategies for adaptive modeling that are suitable for use in practical text compression systems. The strategies fall into three main classes: finite-context modeling, in which the last few characters are used to condition the probability distribution for the next one; finite-state modeling, in which the distribution is conditioned by the current state (and which subsumes finite-context modeling as an important special case); and dictionary modeling, in which strings of characters are replaced by pointers into an evolving dictionary. A comparison of different methods on the same sample texts is included, along with an analysis of future research directions.
Convergence of the standard RLS method and UDUT factorisation of covariance matrix for solving the algebraic Riccati equation of the DLQR via heuristic approximate dynamic programming

The main focus of this article is to present a proposal to solve, via UDUT factorisation, the convergence and numerical stability problems that are related to the covariance matrix ill-conditioning of the recursive least squares (RLS) approach for online approximations of the algebraic Riccati equation (ARE) solution associated with the discrete linear quadratic regulator (DLQR) problem formulated in the actor–critic reinforcement learning and approximate dynamic programming context. The parameterisations of the Bellman equation, utility function and dynamic system as well as the algebra of Kronecker product assemble a framework for the solution of the DLQR problem. The condition number and the positivity parameter of the covariance matrix are associated with statistical metrics for evaluating the approximation performance of the ARE solution via RLS-based estimators. The performance of RLS approximators is also evaluated in terms of consistence and polarisation when associated with reinforcement learning methods. The used methodology contemplates realisations of online designs for DLQR controllers that is evaluated in a multivariable dynamic system model.
An inverse technique for excitation design in nerve fascicle activation: a theoretical study

Position selective stimulation of nerves is an important problem in FES systems, but no systematic method exists to determine the spatio-temporal excitation current profile. In this paper, we provide a theoretical background towards solving this problem. The efficacy of the technique is investigated through Monte Carlo experiments based on simplified computer models of a nerve.
Exploring the formation of Alzheimer's disease senile plaques in silico.

An experimental simulation environment suitable for exploring the neuroinflammatory hypothesis of Alzheimer's disease (AD) has been developed. Using scientific literature, we have calculated parameters and rates and constructed an interactive model system. The simulation can be manipulated to explore competing hypotheses about AD pathology, i.e. can be used as an experimental "in silico" system. In this paper, we outline the assumptions and aspects of the model, and illustrate qualitative and quantitative findings. The interactions of amyloid beta deposits, glial cell dynamics, inflammation and secreted cytokines, and the stress, recovery, and death of neuronal tissue are investigated. The model leads to qualitative insights about relative roles of the cells and chemicals in the disease pathology.
BOSTON UNIVERSITY GRADUATE SCHOOL OF ARTS AND SCIENCES Thesis COUNTING FINGERS IN REAL TIME USING COMPUTER-VISION TECHNIQUES by STEPHEN C. CRAMPTON

A video-based human-computer interface called Finger Counter was developed to control a computer with a small set of hand signals. Finger Counter works in real time with an inexpensive, consumer-grade camera, such as a webcam. Finger Counter ’s background-differencing algorithm compensates for camera noise and vibration to segment the hand from a cluttered background in settings with lowimage quality or camera motion. Finger Counter ’s rules-based protrusion estimator determines the number of fingers a user holds up in front of the camera. Finger Counter applications include a game designed to teach children to count with their fingers and a program that allows the user to “finger paint” on a computer screen. Experiments show that Finger Counter quickly and reliably detected the hand signals of test subjects.
Inverted Grid-Based kNN Query Processing with MapReduce

With the increasing availability of LBS (Location Based Services) and mobile internet, the amount of spatial data is growing larger and larger. It poses new requirements and challenges towards cloud environments, such as how to accomplish efficient index and query processing on large scale spatial data. A scalable and distributed spatial data index is a best choice for the effective processing of the spatial data analysis and query. There are several approaches that implement distributed indices and query processing with MapReduce, such as R-tree and Voronoi-based index. However, R-tree is unsuitable for parallelization and query processing on Voronoi-based index needs extra computation for localization or local index reconstruction. The regularity of grid partition is much easier to scale and parallel comparing with the above two approaches. Inverted Index utilizes limited index entries to index unlimited data points. In this paper, we propose a new distributed spatial data index: Inverted Grid Index, which is a combination of inverted index and grid partition. Our index structure is more simple and suitable for large-scale parallel spatial query application. We present MapReduce-based approaches that both construct Inverted Grid Index and process kNN query over large spatial data sets. Extensive experiments have been done to evaluate the scalability and the performance of kNN query processing on our index structure. The results demonstrate the efficiency and scalability of our kNN query algorithm based on Inverted Grid Index.
Sparse Text Indexing in Small Space

In this work, we present efficient algorithms for constructing sparse suffix trees, sparse suffix arrays, and sparse position heaps for b arbitrary positions of a text T of length n while using only O(b) words of space during the construction. Attempts at breaking the naïve bound of Ω(nb) time for constructing sparse suffix trees in O(b) space can be traced back to the origins of string indexing in 1968. First results were not obtained until 1996, but only for the case in which the b suffixes were evenly spaced in T. In this article, there is no constraint on the locations of the suffixes. Our main contribution is to show that the sparse suffix tree (and array) can be constructed in O(nlog 2b) time. To achieve this, we develop a technique that allows one to efficiently answer b longest common prefix queries on suffixes of T, using only O(b) space. We expect that this technique will prove useful in many other applications in which space usage is a concern. Our first solution is Monte Carlo, and outputs the correct tree with high probability. We then give a Las Vegas algorithm, which also uses O(b) space and runs in the same time bounds with high probability when b = O(√ n). Additional trade-offs between space usage and construction time for the Monte Carlo algorithm are given. Finally, we show that, at the expense of slower pattern queries, it is possible to construct sparse position heaps in O(n + blog b) time and O(b) space.
Geographic Community Analysis of Mobile Social Network

Location-based Mobile Social Networks (MSNs) are becoming increasingly popular given the success of Online Social Networks (OSNs), such as Facebook and MySpace, and recent availability of GPS-embedded mobile platforms, such as Apple iPhones and Google Android phones. MSNs extend existing OSNs by allowing a user to know where her friends are and to meet new people nearby who share her interests. There are few studies, however, on how users are connected through these emerging MSNs. In this paper, we present analysis results of a commercial MSN for which we applied the community-finding algorithm on geographic graphs of user movements and identified geographic characteristics of different locations. The discovered relationship between physical locations provides insights on user travel patterns that have implications on city planning and user similarity studies.
Purification and properties of an alginate lyase from a marine bacterium.

An unidentified pseudomonad isolated by enrichment procedures from decomposing seaweed was grown in defined medium containing sodium alginate as the sole carbon source. The alginate lyase recovered from disrupted bacterial cells was purified by a procedure of (NH4)2SO4 precipitation, gel filtration and ion-exchange chromatography. From sodium dodecyl sulphate/polyacrylamide-gel-electrophoresis experiments a mol.wt. of about 50 000 was determined. The enzyme was active against both algal and bacterial alginate preparations. Kinetic studies together with analysis of the unsaturated oligouronide products of alginate lyase action indicated the enzyme was specific for guluronic acid-containing regions of the macromolecular substrate. The specificity of the enzyme can be used to give information about the primary composition of alginate samples.
Solving Complex Quadratic Equations with Full-rank Random Gaussian Matrices

We tackle the problem of recovering a complex signal x ∈ ℂn from quadratic measurements of the form y = x∗Aix, where $\left\{ {{{\mathbf{A}}_i}} \right\}_{i = 1}^m$ is a set of complex iid standard Gaussian matrices. This non-convex problem is related to the well understood phase retrieval problem where Ai is a rank-1 positive semidefinite matrix. Here we study a general full-rank case which models a number of key applications such as molecular geometry recovery from distance distributions and compound measurements in phaseless diffractive imaging. Most prior work either addresses the rank-1 case or focuses on real measurements. The several papers that address the full-rank complex case adopt the semidefinite relaxation approach and are thus computationally demanding. In this paper we propose a method based on the standard framework comprising a spectral initialization followed by iterative gradient descent updates. We prove that when the number of measurements exceeds the signal’s length by some constant factor, a globally optimal solution can be recovered from complex quadratic measurements with high probability. Numerical experiments on simulated data corroborate our theoretical analysis.
CORONARY Impact of the Complexity of Bifurcation Lesions Treated With Drug-Eluting Stents The DEFINITION Study ( De fi nitions and impact of complEx biFurcation lesIons on clinical outcomes after percutaNeous coronary IntervenTIOn using drug-eluting steNts )

Fro Tu Au of Ko OBJECTIVES The present study established criteria to differentiate simple from complex bifurcation lesions and compared 1-year outcomes stratified by lesion complexity after provisional stenting (PS) and 2-stent techniques using drug-eluting stents. BACKGROUND Currently, no criterion can distinguish between simple and complex coronary bifurcation lesions. Comparisons of PS and 2-stent strategies stratified by lesion complexity have also not been reported previously. METHODS Criteria of bifurcation complexity in 1,500 patients were externally tested in another 3,660 true bifurcation lesions after placement of drug-eluting stents. The primary endpoint was the occurrence of a major adverse cardiac event (MACE) at 12 months. The secondary endpoint was the rate of stent thrombosis (ST). RESULTS Complex (n 1⁄4 1,108) bifurcation lesions were associated with a higher 1-year rate of MACE (16.8%) compared with simple (n 1⁄4 2,552) bifurcation lesions (8.9%) (p < 0.001). The in-hospital ST and 1-year target lesion revascularization rates after 2-stent techniques in the simple group (1.0% and 5.6%, respectively) were significantly different from those after PS (0.2% [p 1⁄4 0.007] and 3.2% [p 1⁄4 0.009], respectively); however, 1-year MACE rates were not significantly different between the 2 groups. For complex bifurcation lesions, 2-stent techniques had lower rates of 1-year cardiac death (2.8%) and in-hospital MACE (5.0%) compared with PS (5.3%, p 1⁄4 0.047; 8.4%, p 1⁄4 0.031). CONCLUSIONS Complex bifurcation lesions had higher rates of 1-year MACE and ST. The 2-stent and PS techniques were overall equivalent in 1-year MACE. However, 2-stent techniques for complex lesions elicited a lower rate of cardiac death and in-hospital MACE but higher rates of in-hospital ST and revascularization at 1 year for simple lesions. (J Am Coll Cardiol Intv 2014;7:1266–76) © 2014 by the American College of Cardiology Foundation. m the *Nanjing First Hospital, Nanjing Medical University, Nanjing, China; ySan Giovanni Battista Hospital, University of Turin, rin, Italy; zBeijing Fuwai Cardiovascular Hospital, Beijing, China; xHospital of Prince Wales, Sydney, New South Wales, stralia; kBangkok General Hospital, Bangkok, Thailand; {Nanjing Heart Center, Nanjing, China; #Medistra Hospital, University Indonesia Medical School, Jakarta, Indonesia; **Mount Sinai Beth Israel, New York, New York; yyQueen Elizabeth Hospital, wloon, Hong Kong; zzNorthern Hospital, Shenyang, China; xxBeijing Anzhen Hospital, Capital Medical University, Beijing, AB BR E V I A T I O N S
Using the event calculus to reason about problem diagrams

Central to the problem frames approach is the distinction of three different descriptions: requirements R, domain assumptions W and specifications S, tied together with the so-called 'frame concern', a proof obligation that has to hold between them if a problem diagram is to be correct: S, W |- R. The form this proof should take is not fixed a priori. It might, however, be desirable to automate it in order to allow for an efficient analysis of large diagrams. To make this possible, we follow some earlier suggestions to use the Event Calculus as a suitable formalism for these descriptions. The main contribution of the present paper is a set of consistency rules as well as guidelines for passing from a problem diagram to its formal description.
Distributed algorithm for optimized vertex coloring

Vertex coloring is a well probed problem in graph theory. The problem of graph coloring is known to be NP-complete problem. Such NP complete problems can easily be solved with the help of distributed computing and parallelism, since distributed algorithms are applicable in many real life applications. In this paper we are using distributed algorithm for solving vertex coloring problem. The main objective of this paper is to minimize the number of colors used for achieving the proper vertex coloring of the graph. We have performed an experimental study employing distributed algorithm. We have presented an experimental analysis of simple and elegant distributed algorithm for achieving optimized vertex coloring problem.
Induced folding in RNA recognition by Arabidopsis thaliana DCL1

DCL1 is the ribonuclease that carries out miRNA biogenesis in plants. The enzyme has two tandem double stranded RNA binding domains (dsRBDs) in its C-terminus. Here we show that the first of these domains binds precursor RNA fragments when isolated and cooperates with the second domain in the recognition of substrate RNA. Remarkably, despite showing RNA binding activity, this domain is intrinsically disordered. We found that it acquires a folded conformation when bound to its substrate, being the first report of a complete dsRBD folding upon binding. The free unfolded form shows tendency to adopt folded conformations, and goes through an unfolded bound state prior to the folding event. The significance of these results is discussed by comparison with the behavior of other dsRBDs.
A New Local Search Strategy for SAT

Recently, a new search strategy called configuration checking (CC) was proposed, for handling the cycling problem of local search. The CC strategy was used to improve the EWLS algorithm, a state-of-the-art local search for Minimum Vertex Cover (MVC). In this paper, we use this strategy to develop a local search algorithm for SAT called CWcc and a local search algorithm for weighted MAX-2-SAT called ANGScc. The CC strategy takes into account the circumstances of the variables when selecting a variable to flip. Experimental results show that the configuration checking strategy is more efficient than previous strategies for handling the cycling problem. We further improve CWcc; the resulting algorithm SWcc outperforms a state-of-the-art local search SAT solver TNM. ANGScc is also competitive with a state-of-the-art weighted MAX-2-SAT local search algorithm. Finally, we conduct some further analysis and experiments to compare the CC strategy with two other methods for handling the cycling problem: the tabu mechanism and the promising decreasing variable exploitation strategy.