Miracle-dz/UniFAR-FTUs huggingface dataset:
Stent Thrombogenicity Early in High-Risk Interventional Settings Is Driven by Stent Design and Deployment and Protected by Polymer-Drug Coatings

Background— Stent thrombosis is a lethal complication of endovascular intervention. Concern has been raised about the inherent risk associated with specific stent designs and drug-eluting coatings, yet clinical and animal support is equivocal. Methods and Results— We examined whether drug-eluting coatings are inherently thrombogenic and if the response to these materials was determined to a greater degree by stent design and deployment with custom-built stents. Drug/polymer coatings uniformly reduce rather than increase thrombogenicity relative to matched bare metal counterparts (0.65-fold; P=0.011). Thick-strutted (162 &mgr;m) stents were 1.5-fold more thrombogenic than otherwise identical thin-strutted (81 &mgr;m) devices in ex vivo flow loops (P<0.001), commensurate with 1.6-fold greater thrombus coverage 3 days after implantation in porcine coronary arteries (P=0.004). When bare metal stents were deployed in malapposed or overlapping configurations, thrombogenicity increased compared with apposed, length-matched controls (1.58-fold, P=0.001; and 2.32-fold, P<0.001). The thrombogenicity of polymer-coated stents with thin struts was lowest in all configurations and remained insensitive to incomplete deployment. Computational modeling–based predictions of stent-induced flow derangements correlated with spatial distribution of formed clots. Conclusions— Contrary to popular perception, drug/polymer coatings do not inherently increase acute stent clotting; they reduce thrombosis. However, strut dimensions and positioning relative to the vessel wall are critical factors in modulating stent thrombogenicity. Optimal stent geometries and surfaces, as demonstrated with thin stent struts, help reduce the potential for thrombosis despite complex stent configurations and variability in deployment.
The changing role of external stakeholders: from imaginary friends to effective actors or non-interfering friends

Recent shifts in university governance have relied on increased autonomy. Within this context, the enhanced role attributed to governance boards at the expense of academic bodies and the role of external stakeholders has gained momentum. With the aim of understanding the extent of the influence of external stakeholders at the institutional level, the perceptions of Rectors and Senate members from 26 European higher education institutions were analysed. Their views saw external members of boards as representing the interests of the society at large and bringing outside beliefs and pressures to the university. However, Rectors would prefer to see them as allies, avoiding interfering strongly in the private lives of institutions.
Resilience in the General Population: Standardization of the Resilience Scale (RS-11)

Background The objectives of the study were to generate normative data for the RS-11 for different age groups for men and women and to further investigate the construct validity and factor structure in the general population. Methods Nationally representative face-to face household surveys were conducted in Germany in 2006 (n = 5,036). Results Normative data for the RS-11 were generated for men and women (53.7% female) and different age levels (mean age (SD) of 48.4 (18.0) years). Men had significantly higher mean scores compared with women (60.0 [SD = 10.2] vs. 59.3 [SD = 11.0]). Results of CFA supported a one-factor model of resilience. Self-esteem (standardized β = .50) and life satisfaction (standardized β =.20) were associated with resilience. Conclusions The normative data provide a framework for the interpretation and comparisons of resilience with other populations. Results demonstrate a special importance of self-esteem in the understanding of resilience.
Comparison of two concentrated winding topologies applied on an axial flux permanent magnet machine

Axial flux machines with internal stator and two outer rotor discs are either specified as N-S- or N-N-type, dependant on the flux path through the stator. While the N-S- type has to be equipped with tooth-wound coils, the N-N- type allows the application of core-wound coils. The main difference between these winding configurations is the alignment of the end turns. Since the stator of a N-N-machine requires additional space for a yoke, this drawback can be potentially balanced out by using core-wound coils. This paper gives an analytical approach in order to evaluate both stator types including the respective winding configurations. It is shown that tooth- and core-wound coils are subject to the same winding factor if the same number of slots per pole and phase (SPP) is chosen. Apart from that, a comparison of the stator losses under the supposition of identical stator volumes is drawn. The result reveals that the N-N- machine is likely to produce more iron and copper losses, if the SPP is near to 1/3, as it is compulsory for tooth-wound coils. Eventually, it is reasoned that the N-N-machine gets more competitive if core-wound coils with a SPP of about 1/6 are applied.
Effect of different docid orderings on dynamic pruning retrieval strategies

Document-at-a-time (DAAT) dynamic pruning strategies for information retrieval systems such as MaxScore and Wand can increase querying efficiency without decreasing effectiveness. Both work on posting lists sorted by ascending document identifier (docid). The order in which docids are assigned -- and hence the order of postings in the posting lists -- is known to have a noticeable impact on posting list compression. However, the resulting impact on dynamic pruning strategies is not well understood. In this poster, we examine the impact on the efficiency of these strategies across different docid orderings, by experimenting using the TREC ClueWeb09 corpus. We find that while the number of postings scored by dynamic pruning strategies do not markedly vary for different docid orderings, the ordering still has a marked impact on mean query response time. Moreover, when docids are assigned by lexicographical URL ordering, the benefit to response time for is more pronounced for Wand than for MaxScore.
HRV analysis using ballistocardiogram with LabVIEW

The HRV analysis plays an important role in health monitoring. HRV is considered as a vital parameter for cardiac assessment. This paper deals with HRV analysis using ballistocardiogram (BCG) signal. The BCG signals from some subjects are acquired using piezoelectric sensors and National Instruments data acquisition card (DAQ) and processed using National Instruments LabVIEW. HRV indices are calculated using HRV analyzer in NI Biomedical workbench. In this paper it observed that the HRV indices in subjects having tachycardia and bradycardia were showing variations.
Common Body of Knowledge for Information Security

The need for skilled information security professionals has led various academic, governmental, and industrial organizations to work to develop a common body of knowledge (CBK) for the security domain. A CBK is a framework and collection of information that provides a basis for understanding terms and concepts in a particular knowledge area. It defines the basic information that people who work in that area are expected to know. The International Information Systems Security Certification Consortium ([ISC]; www.isc2.org) defines a CBK as a taxonomy of topics relevant to professionals around the world. Information security is a multidisciplinary endeavor. In practice, professionals need knowledge and experience from fields such as management, business administration, ethics, sociology, and political science. Yet, existing CBKs focus on specific information security subdomains and thus offer limited understanding and narrow perceptions of the overall domain. Our aim is to identify and define an InfoSec CBK to serve as a tool for developing an information security curriculum
Infrequent Changes of Policy Target : Stop-Go Monetary Policy under Ambiguity

In many countries, the monetary policy instrument remains unchanged for a long period and shows infrequent responses to exogenous shocks. The purpose of this paper is to provide a new explanation on why the central bank’s policy instrument remains so unchanged. In the following analysis, we explore how Knightian uncertainty affects optimal monetary policy. We apply the Choquet expected decision theory to a new Keynesian model. A main result is that the policymaker may frequently keep the interest rate unchanged even when exogenous shocks change output gaps and inflation rates. This never happens when the policymaker has no uncertainty aversion. But to the extent that a change of the interest rate increases uncertainty, the policymaker, who has some uncertainty aversion, may maintain an unchanged policy stance for some significant periods and make discontinuous changes of the target rate following a Taylor rule. Our analysis departs from previous studies in that the policymaker can observe noisy information of relevant macro variables before making the policy decision. The optimal monetary policy rule allows time-variant feedback parameters. This leads to an optimal stop-go policy rule that sometimes responds to output and inflation gaps but sometimes does not. JEL Classification Numbers: E40, E52, D81
A Sequential Partial Optimization Algorithm for Minimax Design of Separable-Denominator 2-D IIR Filters

A sequential partial optimization method is presented in this paper for the minimax design of two-dimensional infinite impulse response filters with separable denominator. The method converts the minimax design problem into a sequence of smaller subproblems, each updating only one pair of second-order denominator factors. The necessary and sufficient stability triangles for one-dimensional filters are used as the stability constraints on the two-dimensional filters. The first-order Taylor expansion and a trust-region method are used to deal with the nonconvexity of the subproblems and guarantee the convergence of the solution algorithm. By comparing with a corresponding joint optimization method, the sequential partial optimization algorithm is shown to converge faster for filters with relatively high denominator order. This is mainly due to the observation that the trust region to assure the convergence is usually much smaller for the joint optimization method. Moreover, the limit solution of the sequential partial optimization algorithm has been proved to be a Karush-Kuhn-Tucker point of the design problem. Design examples demonstrate that the proposed algorithm has obtained smaller maximum frequency response errors than the competing methods both for filters with separable denominator of the same order and for filters with nonseparable denominator of about the same implementation complexity.
Joint MIMO and parallel interference cancellation for the HSDPA

The paper studies high data rate transmissions over frequency selective Rayleigh fading channels, in the downlink of the high speed data packet access (HSDPA) system of the Third Generation Partnership Project (3GPP). We propose, for HSDPA, a combination of transmit and receive diversity schemes, based on 2/spl times/2 multiple-input-multiple-output (MIMO), with a multiple access interference (MAI) cancellation scheme, which consists of a variation of the conventional parallel interference cancellation (PIC). Alamouti space-time coding/MIMO schemes achieve better results for channel profiles closer to a uniform power profile. However, these kinds of channel profiles present higher levels of inter-path interference (IPI), which is responsible for the increased higher level of MAI. On the other hand, PIC has a better performance in situations where several users present the same received power. For these reasons, the PIC fits perfectly with the 2/spl times/2 MIMO scheme. Hence, we consider the use of a specific type of clipped soft decision (CSD) PIC, optimized for MIMO operation. The use of MIMO combined with the proposed PIC scheme can achieve a high performance improvement over the corresponding schemes, and, hence, HSDPA is able to increase the data rate, also with a performance improvement in bit error rate (BER).
Network Product Coding

Network coding is a useful tool to increase the multicast capacity of networks. The traditional approach to network coding involving XOR operation has several limitations such as low robustness and can support only two users/packets at a time, per relay, in the mixing process to achieve optimal error performance. We propose the employment of product coding at the rday station instead of xor and investigate such a system where we use the relay to generate product codes by combining packets from different users. Our scheme uses relays to transmit only the redundancy of the product code instead of the whole product code. We seek to employ product coding can be able to support more than two users/packets per relay per slot, while maintaining a good error performance. Our scheme can accomodate as many users per relay as the costituent block code allows, thus reducing the number of relays required in the network. Product codes also offer increased robustness and flexibility as well as several other advantages, such as proper structure for burst error correction without extra interleaving. We compare the performance of such a scheme to the conventional xor scheme and see that our scheme not only reduces the number of relays required but gives improved error performance as well as. Another encouraging result is that our scheme starts to significantly outperform the conventional one by introducing a gain at the relay.
Opinion Mining For Text Classification

-There are several micro-blogging services available today such as Twitter, Tumblr, Jisko, Thimbl, Wordpress, blog, etc. These micro-bloggers communicate in the form of posts containing videos, images, text, links, etc. This large amount of raw data may overwhelm the users. One solution to this problem is the classification of this raw data. As these raw data such as “tweets” do not account for sufficient word occurrences, we approach traditional methods of classification such as-Bag of Words, Naïve Bayes classifier, frequency distribution. However, to address this problem, we propose to use a small set of domain-specific features extracted from the author’s profile and text. The proposed approach effectively classifies the text to a predefined set of generic classes such as Positive, Negative, Neutral.
A printed dual band antenna with a ground plane and electromagnetically-coupled feed for wireless body area networks

This paper presents a printed dual band antenna with a full ground plane and electromagnetically coupled feed for body area network devices operating in the industrial, scientific, and medical (ISM) band at 2.45 GHz and 4.9GHz public safety Wireless Local Area Networks (WLAN) band (4.94-4.99GHz). Performance along with parametric analyses are presented. Investigations have been carried out to assess its performance for body centric wireless communication. The electromagnetically-coupled feed is tuned to fill a null in the radiation pattern and to achieve impedance matching. The proposed antenna exhibits a wide radiation pattern along the body surface to provide maximum coverage and its narrow width (14mm) makes it suitable for on-body applications.
An Exploration Algorithl 11 for Autonornous Mobile Robots

In this paper we present an exploration algorithm for mobile robots in unknown environments. During the task of exploration, a robot must have a way of navigating around the environment while making sensible decisions on where to explore next. Our approach uses an algorithm which will navigate the robot toward the largest unexplored region in the environment in order to maximise efficiency. We have tested this approach on a simulator, with good results.
SMG5–PNRC2 is functionally dominant compared with SMG5–SMG7 in mammalian nonsense-mediated mRNA decay

In mammals, nonsense-mediated mRNA decay (NMD) functions in post-transcriptional gene regulation as well as mRNA surveillance. A key NMD factor, Upf1, becomes hyperphosphorylated by SMG1 kinase during the recognition of NMD substrates. Hyperphosphorylated Upf1 interacts with several factors including SMG5, SMG6, SMG7 and PNRC2 to trigger rapid mRNA degradation. However, the possible cross-talk among these factors and their selective use during NMD remain unknown. Here, we show that PNRC2 is preferentially complexed with SMG5, but not with SMG6 or SMG7, and that downregulation of PNRC2 abolishes the interaction between SMG5 and Dcp1a, a component of the decapping complex. In addition, tethering experiments reveal the function of Upf1, SMG5 and PNRC2 at the same step of NMD and the requirement of SMG6 for Upf1 for efficient mRNA degradation. Intriguingly, microarray results reveal the significant overlap of SMG5-dependent NMD substrates more with PNRC2-dependent NMD substrates than with SMG7-dependent NMD substrates, suggesting the functional dominance of SMG5-PNRC2, rather than SMG5-SMG7, under normal conditions. The results provide evidence that, to some extent, endogenous NMD substrates have their own binding preference for Upf1-interacting adaptors or effectors.
Constructing an ensemble learning model by using Euclidean distance

The support vector machine (SVM) has a good generalization performance, but the classification result of the SVM in some real problems is often unsatisfied. Because SVM is sensitive to the noisy data and it may not be effective under the high level of noise. To improve the performance of SVM in the noisy environment, we propose an ensemble learning model to address the noise problem in this work. First, we employ the noise-tolerant probabilistic Support Vector Machine. Then a Naïve Bayesian classifier is established in the model. Finally the decision of the two classifiers is appropriately combined to give the final decision. We use the Euclidean distance to complete the integration based on a probabilistic interpretation. The ensemble learning model is evaluated on an artificial dataset for a classification task. Compared with single classifier, the ensemble learning model exhibits good performance in the noisy environment.
Detection and Correction of Phonetic Errors with a New Orthographic Dictionary

The Phonetic and the Homophone Error problem in a language have been characterized as a symbol substitution problem. Phonetically equivalent symbols or symbol combinations in the language are grouped together. Each group or a number of related groups give(s) rise to a dictionary or a number of dictionaries. A new design methodology for Orthographic Dictionaries in alphabetic languages has been described. The dictionaries include the root words. The meanings are stored only in case of Homophone words. Words are sorted on the basis of a Phonetic Ordering Scheme. The dictionaries are being used to detect and correct the Phonetic Error and the Homophone Error in isolated words of Bengali. The methodologies described in this paper can be used in developing spell-checkers not only for other Indian languages which have evolved from the ancient Brahmi script and have a common phonetic structure but also for other alphabetic languages with suitable modifications.
DEGREE SPECTRA OF UNARY RELATIONS ON 〈ω,≤〉

A computable presentation of the linearly ordered set (ω,≤), where ω is the set of natural numbers and ≤ is the natural order on ω, is any linearly ordered set L = (ω,≤L) isomorphic to (ω,≤) such that ≤L is a computable relation. Let X be subset of ω and XL be the image of X in the linear order L under the isomorphism between (ω,≤) and L. The degree spectrum of X is the set of all Turing degrees of XL as one runs over all computable presentations of (ω,≤). In this paper we study the degree spectra of subsets of ω.
An adaptive step size GPU ODE solver for simulating the electric cardiac activity

Simulation of electric cardiac activity requires the solution of a very large system of ordinary differential equations, which requires long computing times. Modern Graphic Processing Units (GPU) are powerful computing devices, which have been used to simulate electric cardiac activity. However, the numerical techniques applied were based on fixed time step. In this paper we describe an adaptive step size solver written for GPUs, and its application to simulate the behavior of a model of 300 atrial cells. Results presented in this study show that a robust adaptive step ODE solver can be implemented in a GPU. As expected, GPU implementations achieved much better performance than CPU solutions. In addition, the presented adaptive methodology achieved a computation time reduction up to a 25% versus a fix step implementation.
An Introduction to Evolutionary Algorithms and Their Application to the Aerofoil Design Problem { Part Ii: the Results

This paper is the second part of a short course on the utilisation of Evolutionary Algorithms as an eeective means to solve the Aerofoil Design Problem in Aerodynamics. In it their application to both Direct and Inverse Aerofoil Design Problem is described, and results are given. Finally, several possible parallel models for Evolutionary Algorithms are discussed, and the results of the application of one of them to the above problem are presented.
Global combine on mesh architectures with wormhole routing

Several algorithms are discussed for implementing global combine (summation) on distributed memory computers using a two-dimensional mesh interconnect with wormhole routing. These include algorithms that are asymptotically optimal for short vectors (O(log(p)) for p processing nodes) and for long vectors (O(n) for n data elements per node), as well as hybrid algorithms that are superior for intermediate n. Performance models are developed that include the effects of link conflicts and other characteristics of the underlying communication system. The models are validated using experimental data from the Intel Touchstone DELTA computer. Each of the combine algorithms is shown to be superior under some circumstances. <<ETX>>
An Optimized Collaborative Filtering Approach with Item Hierarchy-Interestingness

Collaborative filtering algorithm is one of the most successful recommender technologies and has been widely adopted in recommender systems. However, the traditional collaborative filtering always suffers from sparsity problem of dataset. Item resource has hierarchy itself, and people's interests are centralized in several hierarchies. In addition, rating is multivariate with several factors: user's interest and item's quality etc. The proposed algorithm makes corresponding modification based on the traditional algorithm with the ideas above. Experimental results show that the algorithm can guarantee the accuracy of the system recommended by the case, effectively alleviate the data sparsity problem.