Miracle-dz/UniFAR-FTUs huggingface dataset:
Angiotensin-converting enzyme inhibition and radial artery compliance in patients with congestive heart failure.

Congestive heart failure is characterized by a clear-cut impairment of arterial compliance of medium-sized arteries, but whether this alteration is irreversible or can be favorably affected by cardiovascular drugs currently used in congestive heart failure treatment is unknown. We studied 9 congestive heart failure patients (New York Heart Association class II; age, [mean +/- SEM] 60.7 +/- 3.3 years) receiving diuretic and digitalis treatment in whom arterial compliance was assessed at the level of the radial artery by an echotracking device capable of measuring the arterial diameter along the entire cardiac cycle. Beat-to-beat arterial blood pressure was concomitantly measured by a Finapres device that allowed diameter-pressure curves and compliance-pressure curves (Langewouters' formula) to be calculated for the entire systolic-diastolic blood pressure range. Arterial compliance was expressed as the area under the compliance-pressure curve normalized for pulse pressure (compliance index). Data were collected before and after 4 and 8 weeks of oral administration of benazepril (10 mg/day). Ten healthy subjects were studied before and after an observational period of 4 weeks (5 subjects) or 8 weeks (5 subjects), and 9 age-matched mildly essential hypertensive subjects studied before and after 4 to 12 weeks of benazepril administration served as control subjects. In congestive heart failure patients, baseline compliance index was significantly less than in normotensive and hypertensive subjects. However, the compliance index showed a marked increase after 4 weeks of benazepril administration (+95.7 +/- 24.9%, P < .05); the increase was also marked after 8 weeks of angiotensin-converting enzyme inhibitor treatment (+77.7 +/- 4.2%, P < .05). (ABSTRACT TRUNCATED AT 250 WORDS)
Rapsyn Escorts the Nicotinic Acetylcholine Receptor Along the Exocytic Pathway via Association with Lipid Rafts

The 43 kDa receptor-associated protein rapsyn is a myristoylated peripheral protein that plays a central role in nicotinic acetylcholine receptor (AChR) clustering at the neuromuscular junction. In a previous study, we demonstrated that rapsyn is specifically cotransported with AChR via post-Golgi vesicles targeted to the innervated surface of theTorpedo electrocyte (Marchand et al., 2000). In the present study, to further elucidate the mechanisms for sorting and assembly of postsynaptic proteins, we analyzed the dynamics of the intracellular trafficking of fluorescently labeled rapsyn in the transient-expressing COS-7 cell system. Our approach was based on fluorescence, time-lapse imaging, and immunoelectron microscopies, as well as biochemical analyses. We report that newly synthesized rapsyn associates with the trans-Golgi network compartment and traffics via vesiculotubular organelles toward the cell surface of COS-7 cells. The targeting of rapsyn organelles appeared to be mediated by a microtubule-dependent transport. Using cotransfection experiments of rapsyn and AChR, we observed that these two molecules codistribute within distal exocytic routes and at the plasma membrane. Triton X-100 extraction on ice and flotation gradient centrifugation demonstrated that rapsyn and AChR are recovered in low-density fractions enriched in two rafts markers: caveolin-1 and flotillin-1. We propose that sorting and targeting of these two companion molecules are mediated by association with cholesterol–sphingolipid-enriched raft microdomains. Collectively, these data highlight rapsyn as an itinerant vesicular protein that may play a dynamic role in the sorting and targeting of its companion receptor to the postsynaptic membrane. These data also raise the interesting hypothesis of the participation of the raft machinery in the targeting of signaling molecules to synaptic sites.
Compressive Parameter Estimation for Sparse Translation-Invariant Signals Using Polar Interpolation

We propose new compressive parameter estimation algorithms that make use of polar interpolation to improve the estimator precision. Our work extends previous approaches involving polar interpolation for compressive parameter estimation in two aspects: (i) we extend the formulation from real non-negative amplitude parameters to arbitrary complex ones, and (ii) we allow for mismatch between the manifold described by the parameters and its polar approximation. To quantify the improvements afforded by the proposed extensions, we evaluate six algorithms for estimation of parameters in sparse translation-invariant signals, exemplified with the time delay estimation problem. The evaluation is based on three performance metrics: estimator precision, sampling rate and computational complexity. We use compressive sensing with all the algorithms to lower the necessary sampling rate and show that it is still possible to attain good estimation precision and keep the computational complexity low. Our numerical experiments show that the proposed algorithms outperform existing approaches that either leverage polynomial interpolation or are based on a conversion to a frequency-estimation problem followed by a super-resolution algorithm. The algorithms studied here provide various tradeoffs between computational complexity, estimation precision, and necessary sampling rate. The work shows that compressive sensing for the class of sparse translation-invariant signals allows for a decrease in sampling rate and that the use of polar interpolation increases the estimation precision.
NVSim: A Circuit-Level Performance, Energy, and Area Model for Emerging Nonvolatile Memory

Various new nonvolatile memory (NVM) technologies have emerged recently. Among all the investigated new NVM candidate technologies, spin-torque-transfer memory (STT-RAM, or MRAM), phase-change random-access memory (PCRAM), and resistive random-access memory (ReRAM) are regarded as the most promising candidates. As the ultimate goal of this NVM research is to deploy them into multiple levels in the memory hierarchy, it is necessary to explore the wide NVM design space and find the proper implementation at different memory hierarchy levels from highly latency-optimized caches to highly density- optimized secondary storage. While abundant tools are available as SRAM/DRAM design assistants, similar tools for NVM designs are currently missing. Thus, in this paper, we develop NVSim, a circuit-level model for NVM performance, energy, and area estimation, which supports various NVM technologies, including STT-RAM, PCRAM, ReRAM, and legacy NAND Flash. NVSim is successfully validated against industrial NVM prototypes, and it is expected to help boost architecture-level NVM-related studies.
Utilizing recommender algorithms for enhanced information retrieval

Retrieving relevant items which meet a user's information need is the key objective of information retrieval (IR). Current IR systems generally seek to satisfy search queries independently without considering search history information from other searchers. By contrast, algorithms used in recommender systems (RSs) are designed to predict the future popularity of an item by aggregating ratings of the reactions of previous users of an item. This observation motivates us to explore the application of RS methods in IR to increase search effectiveness. In this study, we examine the suitability of recommender algorithms (RAs) for use in IR applications and methods for combining RAs into IR systems by fusing their respective outputs. A novel RA is proposed to enhance the RS performance in our integrated application. Experimental results are reported for an extended version of the FIRE 2011 personalized IR data collection. Noticeably better results are obtained using our approach.
Universal dependencies for Uyghur

The Universal Dependencies (UD) Project seeks to build a cross-lingual studies of treebanks, linguistic structures and parsing. Its goal is to create a set of multilingual harmonized treebanks that are designed according to a universal annotation scheme. In this paper, we report on the conversion of the Uyghur dependency treebank to a UD version of the treebank which we term the Uyghur Universal Dependency Treebank (UyDT). We present the mapping of the Uyghur dependency treebank’s labelling scheme to the UD scheme, along with a clear description of the structural changes required in this conversion.
Fault Detection for Fuzzy Systems With Intermittent Measurements

This paper investigates the problem of fault detection for Takagi-Sugeno (T-S) fuzzy systems with intermittent measurements. The communication links between the plant and the fault detection filter are assumed to be imperfect (i.e., data packet dropouts occur intermittently, which appear typically in a network environment), and a stochastic variable satisfying the Bernoulli random binary distribution is utilized to model the unreliable communication links. The aim is to design a fuzzy fault detection filter such that, for all data missing conditions, the residual system is stochastically stable and preserves a guaranteed performance. The problem is solved through a basis-dependent Lyapunov function method, which is less conservative than the quadratic approach. The results are also extended to T--S fuzzy systems with time-varying parameter uncertainties. All the results are formulated in the form of linear matrix inequalities, which can be readily solved via standard numerical software. Two examples are provided to illustrate the usefulness and applicability of the developed theoretical results.
Does Wide Posterior Multiple Level Release Improve the Correction of Adolescent Idiopathic Scoliosis Curves?

Study Design Retrospective matched cohort study. Objective To compare results of posterior correction and fusion with a hybrid construct using a standard posterior release (SPR) versus adding a wide posterior release (WPR), in adolescent idiopathic scoliosis (AIS) treated at a single institution, with a minimum 2-year follow-up. Summary of Background Data Although the importance of posterior release has been enhanced for the correction of AIS, there have been no reports comparing correction results when posterior wide release (excision of all posterior ligaments and bilateral extended facetectomy at multiple levels) is used. Methods A retrospective study of 46 patients with AIS was performed. Posterior-only hybrid instrumentation with sublaminar wires was included. SPR group consisted of 25 patients and WPR group consisted of 21 patients. Results There was no difference in sex, age, type of curve, number of instrumented levels, length of surgery, and preoperative main curve Cobb (SPR: 60±10 degrees WPR: 59±8 degrees). In the WPR group, the amount of main curve correction obtained was significantly greater (SPR: 57% vs. WPR: 68.6%) P<0.001, and maintained at final follow-up (SPR: 51.6% vs. WPR: 61.8%) P<0.05. Preoperative and postoperative proximal thoracic and lumbar secondary curves were similar in both the groups. T5-T12 preoperative kyphosis were (SPR: 22.2±11 degrees vs. WPR: 19±11 degrees) the degrees corrected in postoperation (SPR: +1.2±6 degrees vs. WPR: −0.9±9 degrees) and at final follow-up (SPR: +1.6±8 degrees vs. WPR: −0.8±11 degrees), and were not statistically different P>0.05. Minor complications were similar in both groups and no major complications were found. Conclusions Posterior wide release at multiple levels improves coronal main curve correction in patients with AIS, without an increase in the incidence of complications. Furthermore, it improves fusion surface and makes insertion of sublaminar wires easier.
ONE-shot blind CFO estimation for OFDM with multi-antenna receiver

In this paper, we propose a new blind carrier frequency offset (CFO) estimation method for orthogonal frequency division multiplexing (OFDM) with multi-antenna receiver. The proposed method is one-shot and works with only a single OFDM block, which differs from the existing works for multi-antenna receiver. We show that, the proposed method not only supports fully loaded transmission, but also outperforms the existing maximum likelihood estimator for multi-antenna receiver. The numeral results are provided to corroborate the proposed studies.
A sampler for stream macroinvertebrates and organic matter occurring on boulders and bedrock in pools

Among the wide variety o f benthic sampling methods and devices, none to our knowledge has been described for quantitatively sampling the benthos associated with large boulders and bedrock in still-water pools. Benthic samplers for stream pools, such as the stovepipe core, are designed for fine substrates (MERRJTT et al. 1996). However, still-water pools dominated by boulders/bedrock, with cobble, gravel, leaves and sticks in the crevices between boulders, are often a major habitat. In o ur studies of mountain streams in Puerto Rico, an average of 47% (range: 15-77%) o f pool substrate measurements are boulder or bedrock ( diameter ~ 256 mm). Thus, we developed a benthic sampler for use on boulder/bedrock habitats in still-water pools where use o f traditional samplers i s not tractable d ue to the laek o f flow and large substrate sizes. The sampler, which we call the "benthic block net," can be used for sampling quantitatively (abundance/biomass per unit area) or semiquantitatively (relative abundances/biomass). Because still-water boulder/bedrock pools are important habitats in various high-gradient streams throughout the world, our sampler may be useful in a variety of benthological studies.
The structure of alginate, chitin and chitosan fibres

Abstract This chapter discusses the fibres produced from natural polymers such as alginates, chitin and chitosan. The chapter reviews specific properties of these polymers and the fibres obtained from them, together with the methods of producing fibres. The chapter also discusses the influence of polymer structure and spinning conditions on the properties of fibres obtained from these biopolymers. The chapter includes the main fields of applications and the future prospects for alginates, chitin, chitosan and fibres produced from them (composite fibres, nanofibres, nanoporous).
Comparison of Performance for SVM Based Relevance Feedback Document Retrieval in Several Vector Space Models

We investigate the following data mining problems from the document retrieval: From a large data set of documents, we need to find documents that relate to human interest as few iterations of human testing or checking as possible. In each iteration a comparatively small batch of documents is evaluated for relating to the human interest. We apply active learning techniques based on Support Vector Machine for evaluating successive batches, which is called relevance feedback. Our proposed approach has been very useful for document retrieval with relevance feedback experimentally. In this paper, we adopt several Vector Space Models into our proposed method, and then show the comparison results of the performance of our method in several Vector Space Models.
A Simple Ultrawideband Planar Rectangular Printed Antenna With Band Dispensation

A compact planar ultrawideband (UWB) antenna with band notched characteristics is presented. Modification in the shape of radiation element and ground plane with two symmetrical bevel slots on the lower edge of the radiation element and on the upper edge of the ground plane makes the antenna different from the rectangular printed monopole. These slots improve the input impedance bandwidth and the high frequency radiation characteristics. With this design, the reflection coefficient is lower than 10 dB in the 3.1-10.6 GHz frequency range and radiation pattern is similar to dipole antenna. With the inclusion of an additional small radiation patch, a frequency-notched antenna is also designed and good out of band performance from 5.0-6.0 GHz can be achieved. Measured results confirm that the antenna is suitable for UWB applications due to its compact size and high performance. Also an approximate empirical expression to calculate the lowest resonant frequency is proposed.
Amorphous Data-parallelism in Irregular Algorithms ∗

Most client-side applications running on multicore processors are likely to be irregular programs that deal with complex, pointerbased data structures such as large sparse graphs and trees. However, we understand very little about the nature of parallelism in irregular algorithms, let alone how to exploit it effectively on multicore processors. In this paper, we show that, although the behavior of irregular algorithms can be very complex, many of them have a generalized data-parallelism that we call amorphous data-parallelism. The algorithms in our study come from a variety of important disciplines such as data-mining, AI, compilers, networks, and scientific computing. We also argue that these algorithms can be divided naturally into a small number of categories, and that this categorization provides a lot of insight into their behavior. Finally, we discuss how these insights should guide programming language support and parallel system implementation for irregular algorithms.
WHP 196 DVB-T 2 : The Common Simulation Platform

The DVB-T2 Common Simulation Platform (CSP) is a software model of an endto-end DVB-T2 chain, begun by SIDSA and AICIA and developed collaboratively by a number of organisations within DVB including Pace and Panasonic. BBC R&D has become a major contributor, making the model fully compliant to the specification; modifying it to participate in the DVB-T2 Validation and Verification work; extending it to work with multiple PLPs and to process T2-MI input; and adding a simulation of the Receiver Buffer Model and features to help with parameter design and checking. This document provides an overview of the CSP and a description of the architecture and principles involved. The Common Simulation Platform has now been released under an open-source licence on Sourceforge. Additional key words:
Tripartite relationship among P300, clinical features and brain structure in neuroleptic‐naive schizophrenia

Abstract Auditory P300 abnormalities in schizophrenia patients have been repeatedly reported by many studies. However, reported relationships among P300 abnormalities, clinical features and other biological variables, such as abnormalities in structural brain imaging, are notably discrepant. This is partially due to the inclusion of patients who have had long‐term administration of neuroleptics and those from whom this treatment has been withdrawn. The present study measures event‐related potentials in 13 neuroleptic‐naive schizophrenia patients using an auditory oddball paradigm to clarify the relationships among P300 amplitude, clinical features and brain structure. All patients underwent computed tomography to estimate the area of the right and left frontal cortical sulci and Sylvian fissures. Clinical symptoms were assessed using the Positive And Negative Syndrome Scale. The high correlation coefficients were obtained between P300 amplitude and the anxiety/depression factor score (r =−0.77), the positive factor score (r =−0.58) and between P300 amplitude and the area ratios of the fronto‐temporal region (r =−0.66). These findings show that fronto‐temporal region and P300 amplitude are closely related to the earliest stage of illness even in neuroleptic‐naive patients.
Mobile Gait Match-on-Card Authentication from Acceleration Data with Offline-Simplified Models

Biometrics have become important for authentication on mobile devices, e.g. to unlock devices before using them. One way to protect biometric information stored on mobile devices from disclosure is using embedded smart cards (SCs) with biometric match-on-card (MOC) approaches. Computational restrictions of SCs thereby also limit biometric matching procedures. We present a mobile MOC approach that uses offline training to obtain authentication models with a simplistic internal representation in the final trained state, whereat we adapt features and model representation to enable their usage on SCs. The obtained model is used within SCs on mobile devices without requiring retraining when enrolling individual users. We apply our approach to acceleration based mobile gait authentication, using a 16 bit integer range Java Card, and evaluate authentication performance and computation time on the SC using a publicly available dataset. Results indicate that our approach is feasible with an equal error rate of ~12% and a computation time below 2s on the SC, including data transmissions and computations. To the best of our knowledge, this thereby represents the first practically feasible approach towards acceleration based gait match-on-card authentication.
Safe Gap based (SG) reactive navigation for mobile robots

In this paper a new real-time collision avoidance approach for mobile robots moving in dense and cluttered environments is presented. Our method is to adapt the Closest Gap (CG) Navigation technique, which we have proposed in an earlier work [1], to generate safer and smoother robot trajectories. This is achieved by introducing an additional step in analyzing the structure of obstacles surrounding the robot, and generating instantaneous subgoals which drive the robot towards a collision-free area. The performance of this approach as compared with the CG method is demonstrated with simulation and experimental results.
PANEL: Position-based Aggregator Node Election in Wireless Sensor Networks

In this paper, we introduce PANEL, a position-based aggregator node election protocol for wireless sensor networks. The novelty of PANEL with respect to other aggregator node election protocols is that it supports asynchronous sensor network applications where the sensor readings are fetched by the base stations after some delay. In particular, the motivation for the design of PANEL was to support reliable and persistent data storage applications, such as TinyPEDS. PANEL ensures load balancing, and it supports intra-and inter-cluster routing allowing sensor to aggregator, aggregator to aggregator, base station to aggregator, and aggregator to base station communications. We also present simulation results showing that PANEL is very energy efficient.
The Jacobi–Davidson method

The Jacobi–Davidson method is a popular technique to compute a few eigenpairs of large sparse matrices. Its introduction, about a decade ago, was motivated by the fact that standard eigensolvers often require an expensive factorization of the matrix to compute interior eigenvalues. Such a factorization may be infeasible for large matrices as arise in today's large‐scale simulations. In the Jacobi–Davidson method, one still needs to solve “inner” linear systems, but a factorization is avoided because the method is designed so as to favor the efficient use of modern iterative solution techniques, based on preconditioning and Krylov subspace acceleration. Here we review the Jacobi–Davidson method, with the emphasis on recent developments that are important in practical use. (© 2006 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Constraint-Based Polymorphism in Cecil

We are developing a static type system for object-oriented languages that strives to guarantee statically and completely the absence of certain large classes of run-time errors, to enable polymorphic abstractions to be written and typechecked once separately from any current or future instantiations, and to avoid forcing code to be written unnaturally due to static type system limitations. The type system supports bounded parametric polymorphism, where the bounds on type variables can be expressed using a mixture of recursive subtype and signature constraints; this kind of bounding supports F-bounded polymorphism, Theta-style where clauses, and covariant and contravariant type parameters as special cases. The type system coexists with many advanced language features, including multi-methods, independent inheritance and subtyping, mutable and immutable state, ﬁrst-class lexically-scoped functions, and mixed statically and dynamically typed code. We have implemented this type system in the Cecil language, and we have used it to successfully typecheck a 100,000-line Cecil program, the Vortex optimizing compiler.