Miracle-dz/UniFAR-FTUs huggingface dataset:
Low-complexity stochastic Generalized Belief Propagation

The generalized belief propagation (GBP), introduced by Yedidia et al., is an extension of the belief propagation (BP) algorithm, which is widely used in different problems involved in calculating exact or approximate marginals of probability distributions. In many problems, it has been observed that the accuracy of GBP outperforms that of BP considerably. However, due to its generally higher complexity compared to BP, its application is limited in practice. In this paper, we introduce a stochastic version of GBP called stochastic generalized belief propagation (SGBP) that can be considered as an extension to the stochastic BP (SBP) algorithm introduced by Noorshams et al. They have shown that SBP reduces the complexity per iteration of BP by an order of magnitude in alphabet size. In contrast to SBP, SGBP can reduce the computation complexity if certain topological conditions are met by the region graph associated to a graphical model. However, this reduction can be larger than only one order of magnitude in alphabet size. In this paper, we characterize these conditions and the amount of complexity gain that one can obtain by using SGBP. Finally, using similar proof techniques employed by Noorshams et al., for general graphical models satisfy contraction conditions, we prove the asymptotic convergence of SGBP to the unique GBP fixed point, as well as providing non-asymptotic upper bounds on the mean square error and on the high probability error.
Impact of Aldosterone Receptor Blockade Compared With Thiazide Therapy on Sympathetic Nervous System Function in Geriatric Hypertension

Aldosterone receptor blockade and thiazide therapy effectively lower blood pressure in geriatric hypertension. Their impact on sympathetic nervous system function has not been evaluated. In a double-blind, randomized study, 36 patients with stage 1 hypertension underwent 6 months of therapy with either aldosterone receptor blockade (spironolactone, n=19; 68±1 years) or hydrochlorothiazide (n=17; 68±2 years). Arterial blood pressure, [3H]-norepinephrine (NE) kinetics (extravascular NE release rate), and &agr;-adrenergic responsiveness (forearm vasoconstriction to graded intrabrachial artery NE infusions) were evaluated at baseline, after a 4-week antihypertensive medication withdrawal, and after spironolactone or hydrochlorothiazide treatment. Arterial blood pressure decreased significantly with both spironolactone (160±3 to 134±2 mm Hg; 77±2 to 68±2 mm Hg) and hydrochlorothiazide (161±4 to 145±4 mm Hg; 78±2 to 73±2 mm Hg) treatment. Sympathetic nervous system activity was significantly reduced after spironolactone (plasma NE: 378±40 to 335±20 pg/mL, P=0.04; [3H]-NE release rate: 2.74±0.3 to 1.97±0.2 &mgr;g/min per meter squared, P=0.04) but not hydrochlorothiazide (plasma NE: 368±25 to 349±23 pg/mL, P=0.47; [3H]-NE release rate: 2.63±0.4 to 2.11±0.2 mg/min per meter squared, P=0.21). &agr;-Adrenergic responsiveness was unchanged with either drug treatment. These findings demonstrate a beneficial effect of aldosterone receptor blockade on reducing sympathetic nervous system activity and blood pressure in hypertensive older patients.
Differentiated Backoff Strategies for Prioritized Random Access Delay in Multiservice Cellular Networks

In this paper, a novel prioritization mechanism for random access strategies in cellular networks is proposed. The proposed prioritized random access strategy sets different retransmission probabilities to users, depending on their priorities. First, a mathematical analysis method for simultaneously evaluating throughput and access delay, considering an infinite population model and different retransmission policies, is developed. Most of the previous related research has been done, considering both finite population and saturation conditions where all the nodes in the system always have a packet ready to be transmitted, and the transmission queue of each station is assumed to be always nonempty. This assumption is a good approximation for a local area network working at full capacity. However, in a cellular system, the assumptions of a finite population and every node in a cell always having a packet to transmit are not very realistic. Here, the analytical results consider a Poisson arrival process-which is more suitable for the traffic model in a cellular system-for the users in the cells. Then, considering slotted ALOHA as a random access strategy and the developed analysis method, the case where two different types of service exist (low-and high-priority users) is mathematically analyzed. With the proposed prioritized random access strategy, the average access delay achieved for the high priority users is always lower than that for the low-priority users. Additionally, a mathematical expression for the throughput is derived with and without service differentiation. Finally, two approaches for finding the optimum retransmission probabilities are developed; in the first approach, the number of backlogged packets is required, whereas a simpler and efficient alternative method requires only the knowledge of the mean new packet arrival rate. For the performance analysis, four of the most common backoff algorithms are considered: (1) Uniform (UB); (2) Binary Exponential (BEB); (3) Negative Exponential (XB); and (4) Geometric (GB).
Reduction of NBTI-Induced Degradation on Ring Oscillators in FPGA

Ring Oscillators are used for variety of purposes to enhance reliability on LSIs or FPGAs. This paper introduces an aging-tolerant design structure of ring oscillators that are used in FPGAs. The structure is able to reduce NBTI-induced degradation in a ring oscillator's frequency by setting PMOS transistors of look-up tables in an off-state when the oscillator is not working. The evaluation of a variety of ring oscillators using Altera Cyclone IV device (60nm technology) shows that the proposed structure is capable of controlling degradation level as well as reducing more than 37% performance degradation compared to the conventional oscillators.
Discovering Algebraic Specifications for Java Classes ; CU-CS-985-04

Modern programs make extensive use of reusable software libraries. For example, a study of a number of large Java applications shows that between 17% and 30% of the classes in those applications use the container classes from the java.util package. Given this extensive code reuse in Java programs, it is important for the reusable interfaces to have clear and unambiguous documentation. Unfortunately, most documentation is expressed in English, and therefore does not always satisfy the above requirements. Worse yet, there is no way of checking that the documentation is consistent with the associated code. Formal specifications, such as algebraic specifications, do not suffer from these problems; however, they are notoriously hard to write. To alleviate this difficulty we describe a tool that automatically derives documentation for interfaces of Java classes. Our tool probes Java classes by invoking them on dynamically generated tests and captures the information observed during their execution as algebraic axioms. While the tool is not complete or correct from a formal perspective we demonstrate that it significantly alleviates the task of writing formal documentation for reusable components.
Feature statistical retrieval applied to content based copy identification

In many image or video retrieval systems, the search for similar objects in the database includes a spatial access method to a multidimensional feature space. This step is generally considered as a problem independent of the features and the similarity type. The well known multidimensional nearest neighbor search has also been widely studied by the database community as a generic method. We propose a novel strategy dedicated to pseudo-invariant features retrieval and more specifically applied to content based copy identification. The range of a query is computed during the search according to deviation statistics between original and observed features. Furthermore, this approximate search range is directly mapped onto a Hilbert space-filling curve, allowing an efficient access to the database. Experimental results give excellent response times for very large databases both on synthetic and real data. This work is used in a TV monitoring system including more than 13000 hours of video in the reference database.
Interactions Between the Ur Element RNA Oligonucleotide and CstF-64 in C. elegans Nematodes

In C. elegans, RNA processing of downstream operon genes through SL2 trans-splicing is crucial for polycistronic transcripts to be separated into monocistronic transcripts. The Ur element RNA sequence, which is important for proper SL2 trans-splicing, is found in the intercistronic region (ICR) of the pre-mRNA. The ICR is located between the 3’ end of one gene and the trans-splice site of a downstream operon gene. Lasda has shown that the Ur element sequence is required for downstream SL2 trans-splicing and proposed that it defines the 5’splice site on the SL2 RNA (Lasda, Allen, & Blumenthal, 2010). This project investigates whether there is an interaction between the Ur element RNA oligonucleotide and purified GST CstF-64, a 3’end formation factor. The Ur element RNA oligo contains short stem-loop and multiple UAYYUU motifs similar to Ur element RNA sequence found in ICRs. These experiments specifically analyze whether various mutant and wild type Ur element RNA oligos pull down GST CstF-64 directly, in the absence of extract. Results suggest that the wild type Ur element RNA oligo interacts directly with GST CstF-64, while the mutant RNA oligo does not pull down GST CstF-64. The results also suggest that the region containing the UAYYUU is required for GST CstF-64 binding, while the stem-loop is not important. Additionally, preliminary crosslinking results suggest that GST CstF-64 directly binds the loop and first UAYYUU motif of the Ur element RNA oligo.
Gene Expression From Random Libraries of Yeast Promoters

Genomewide techniques to assay gene expression and transcription factor binding are in widespread use, but are far from providing predictive rules for the function of regulatory DNA. To investigate more intensively the grammar rules for active regulatory sequence, we made libraries from random ligations of a very restricted set of sequences. Working with the yeast Saccharomyces cerevisiae, we developed a novel screen based on the sensitivity of ascospores lacking dityrosine to treatment with lytic enzymes. We tested two separate libraries built by random ligation of a single type of activator site either for a well-characterized sporulation factor, Ndt80, or for a new sporulation-specific regulatory site that we identified and several neutral spacer elements. This selective system achieved up to 1:104 enrichment of the artificial sequences that were active during sporulation, allowing a high-throughput analysis of large libraries of synthetic promoters. This is not practical with methods involving direct screening for expression, such as those based on fluorescent reporters. There were very few false positives, since active promoters always passed the screen when retested. The survival rate of our libraries containing roughly equal numbers of spacers and activators was a few percent that of libraries made from activators alone. The sequences of ∼100 examples of active and inactive promoters could not be distinguished by simple binary rules; instead, the best model for the data was a linear regression fit of a quantitative measure of gene activity to multiple features of the regulatory sequence.
Towards the Semantic Interpretation of Personal Health Messages from Social Media

Recent attempts have been made to utilise social media platforms, such as Twitter, to provide early warning and monitoring of health threats in populations (i.e. Internet bio-surveillance). It has been shown in the literature that a system based on keyword matching that exploits social media messages could report flu surveillance well ahead of the Centers of Disease Control and Prevention (CDC). However, we argue that a simple keyword matching may not capture semantic interpretation of social media messages that would enable healthcare experts or machines to extract and leverage medical knowledge from social media messages. In this paper, we motivate and describe a new task that aims to tackle this technology gap by extracting semantic interpretation of medical terms mentioned in social media messages, which are typically written in layman's language. Achieving such a task would enable an automatic integration between the data about direct patient experiences extracted from social media and existing knowledge from clinical databases, which leads to advances in the use of community health experiences in healthcare services.
A Test of the Particle Paradigm in N-Body Simulations

We present results of tests of the evolution of small “fluid elements” in cosmological N-body simulations, to examine the validity of their treatment as particles. We find that even very small elements typically collapse along one axis while expanding along another, often to twice or more their initial comoving diameter. This represents a possible problem for high-resolution uses of such simulations.
JUSTIÇA ORGANIZACIONAL, ATITUDES RETALIATÓRIAS E O COMPROMETIMENTO ORGANIZACIONAL: UM ESTUDO COMPARATIVO LONGITUDINAL COM JOVENS TRABALHADORES

O presente artigo tem por objetivo analisar como se encontram configuradas a percepcao de justica e atitudes retaliatorias em relacao as dimensoes do comprometimento organizacional em jovens trabalhadores. Os conceitos de Justica Organizacional e Comprometimento tem sido estudados em conjunto no contexto do Comportamento Organizacional mostrando uma associacao entre a percepcao de justica e o engajamento do funcionario, no entanto, os estudos que relacionam atitudes retaliatorias diretamente ao comprometimento ainda sao pouco explorados. Tendo em vista essa lacuna, realizou-se estudo junto a jovens trabalhadores de uma instituicao profissionalizante com a aplicacao de questionarios de percepcao de justica, atitudes retaliatorias e de comprometimento organizacional. Como principais resultados, verificou-se que as dimensoes de justica organizacional possuem correlacoes significativas com o comprometimento no publico estudado e o comprometimento influencia negativamente a possibilidade de emissao de atitudes retaliatorias. Em relacao ao sexo, foram averiguadas, de modo geral, medias maiores para homens, no entanto, a faixa de interpretacao desses resultados foi a mesma para ambos os sexos.
Smart antenna for doa using music and esprit

Smart adaptive antenna technology is considered to be the last technology frontier that has the potential of leading to large increases in systems performance. Time domain techniques have been extensively exploited. Space domain techniques, on the other hand, have not been exploited to the same extent. When applied to wireless, the benefits of smart adaptive array a antennas are as follows: (i) increased covered, which is important in the early stages of life cycle, (ii) increased capacity, which is important in the later stages of life cycle, (iii) improved link quality, (iv) reduced costs and increased return on investment, (v) lower handset power consumption, and (vi) assistance in user location by means of direction finding. This paper discusses an experimental neural network based smart antenna capable of performing direction finding and the necessary beam forming. The algorithm operates in two stages. The field of view of the antenna array is divided into spatial sectors ,then each network is trained in the first stage to detect signals emanating from sources in that sector. According to the outputs of the first stage, one or more networks of the second stage can be activated so as to estimate the exact location of the sources. No a priori knowledge is required about the number of sources, and the networks can be designed to arbitrary angular resolution. Some experimental results are shown and compared with other algorithms, such as, the Fourier Transform and the MUSIC algorithm AND ESPRIT variations is done in the proposed research work
A Novel Visual Discriminator for Network Traffic Patterns

The wavelet transform has been shown to be a powerful tool for characterising network traffic.However, the resulting decomposition of a wavelet transform typically forms a high-dimension space. This is obviously problematic on compact representations,visualizations, and modelling approaches that are based on these high-dimensional data. In this study, we show how data projection techniques can represent the high-dimensional wavelet decomposition in a low dimensional space to facilitate visual analysis. A low dimensional representation can significantly reduce the model complexity. Hence, features in the data can be presented with a small number of parameters. We demonstrate these projections in the context of network traffic pattern analysis. The experimental results show that the proposed method can effectively discriminate between different application flows, such as FTP and P2P.
Concrete Computation of Global Illumination Using Structured Sampling

A new methodology is presented for the computation of global illumination using structured sampling. Analytical/numerical solutions for illumination are developed for simple lighting configurations. These solutions are subsequently used to generate accurate reference images. The structured sampling solution for global illumination is then discussed, comprising sample placement for illumination calculation, reconstruction for light transfer and finally resampling and filtering of illumination samples for display. A first approximation to this technique is presented using a priori placement of samples, irregular polygon reflectors, grid resampling and a conical filter for display. The new algorithm is evaluated for image quality, and compared to the traditional radiosity-based approach. These first results show that the structured sampling solution yields significant computational savings while maintaining high image quality.
Iterative D.C. Optimization of Precoding in Wireless MIMO Relaying

Optimizations of precoding matrices in precode-and-forward (PF) MIMO relaying are nonconvex programs in precoding matrix variables. The semidefinite relaxation (SDR) technique, which relaxes the concerned nonconvex quadratic constraints by (convex) semi-definite ones, can locate the optimal solutions, provided that the numbers of relaying antennas and users are very small. The computational complexity of the SDR grows explosively even with a very moderate increase in the numbers of relaying antennas and/or users, making the existing semidefinite programming (SDP) solvers incapable. In this paper, much more efficient problem formulations of precoding matrix design that exploit the spectral matrix optimization are developed. Such formulations have a low dimensionality and are computationally-tractable nonconvex matrix programs. Furthermore, by exploiting their partial convex structures in the d.c. (difference of two convex functions) framework, new effective iterative solutions are obtained. Extensive simulation results are presented to support the computational advantage of the proposed approach and show that the proposed approach can effectively handle all three considered optimization problems of precoding matrices in MIMO PF relaying, while the SDR approach either is computationally impractical or fails.
A New Efficient Optimal 2D Views Selection Method Based on Pivot Selection Techniques for 3D Indexing and Retrieval

In this paper, we propose a new method for 2D/3D object indexing and retrieval. The principle consists of an automatic selection of optimal views by using an incremental algorithm based on pivot selection techniques for proximity searching in metric spaces. The selected views are afterward described by four well-established descriptors from the MPEG-7 standard, namely: the color structure descriptor (CSD), the scalable color descriptor (SCD), the edge histogram descriptor (EHD) and the color layout descriptor (CLD). We present our results on two databases: The Amsterdam Library of Images (ALOI-1000), consisting of 72,000 color images of views, and the Columbia Object Image Library (COIL-100), consisting of 7200 color images of views. The results prove the performance of the developed method and its superiority over the k-means algorithm and the automatic selection of optimal views proposed by Mokhtarian et al.
Trace: Tennessee Research and CreativeExchange Protective effect of anti-SUAM antibodies on Streptococcus uberis mastitis

In the present study, the effect of anti‑recombinant Streptococcus uberis adhesion molecule (SUAM) antibodies against S. uberis intramammary infections (IMI) was evaluated using a passive protection model. Mammary quarters of healthy cows were infused with S. uberis UT888 opsonized with affinity purified anti‑rSUAM antibodies or hyperimmune sera. Non‑opsonized S. uberis UT888 were used as a control. Mammary quarters infused with opsonized S. uberis showed mild‑to undetectable clinical symptoms of mastitis, lower milk bacterial counts, and less infected mammary quarters as compared to mammary quarters infused with non‑opsonized S. uberis . These findings suggest that anti‑rSUAM antibodies interfered with infection of mammary gland by S. uberis which might be through preventing adherence to and internalization into mammary gland cells, thus facilitating clearance of S. uberis , reducing colonization, and caus‑ ing less IMI.
Association rules-based Ontology Enrichment

Among the most powerful tools for knowledge representation, we cite the ontology which allows knowledge structuring and sharing. In order to achieve efficient domain knowledge bases content, the latter has to establish well linked and knowledge between its components. In parallel, data mining techniques are used to discover hidden structures within large databases. In particular, association rules are used to discover co-occurrence relationships from past experiences. In this context, we propose, to develop a method to enrich existing ontologies with the identification of novel semantic relations between concepts in order to have a better coverage of the domain knowledge. The enrichment process is realized through discovered association rules. Nevertheless, this technique generates a large number of rules, where some of them, may be evident or already declared in the knowledge base. To this end, the generated association rules are categorized into three main classes: known knowledge, novel knowledge and unexpected rules. We demonstrate the applicability of this method using an existing mammographic ontology and patient's records.