Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient distributed arithmetic based DWT architecture for multimedia applications

This paper presents a novel architecture for 9/ Discrete Wavelet Transform (DWT) based on Distributed Arithmetic (DA). The proposed architecture optimizes the performance by exploiting the computational redundancy. The DWT inner product of coefficient matrix is distributed over the input by careful analysis of input, output and coefficients word lengths. In the coefficient matrix, linear maps are used to assign the necessary computation processing elements in space domain. The result is a low hardware complexity DWT processor for 9/7 transforms, which allows two times faster clock than the direct implementation. In the proposed architecture reducing the clock frequency by two or the supply voltage and maintaining the same throughput as of other architecture achieve the low power by a factor of four. The proposed architecture is therefore scalable and can operate at high speed / consumes low power and has reduced computational complexity (improvement of 77.6% over filter based and 40.27% over lifted based architectures) as compared to already published 9/7 biorthogonal wavelet architectures.
On the 2R conjecture for multi-agent systems

We consider a simple dynamical model of agents distributed on the real line. The agents have a limited vision range and they synchronously update their positions by moving to the average position of the agents that are within their vision range. This dynamical model was initially introduced in the social science literature as a model of opinion dynamics and is known there as the “Krause model”. It gives rise to surprising and partly unexplained dynamics that we describe and discuss in this paper. One of the central observations is the 2R-conjecture: when sufficiently many agents are distributed on the real line and have their position evolve according to the above dynamics, the agents eventually merge into clusters that have inter-cluster distances roughly equal to 2R (R is the vision range of the agents). This observation is supported by extensive numerical evidence and is robust under various modifications of the model. It is easy to see that clusters need to be separated by at least R. On the other hand, the unproved bound 2R that is observed in practice can probably only be obtained by taking into account the specifics of the model's dynamics. In this paper, we study these dynamics and consider a number of issues related to the 2R conjecture that explicitly uses the model's dynamics. In particular, we provide bounds for the vision range that lead all agents to merge into only one cluster, we analyze the relations between agents on finite and infinite intervals, and we introduce a notion of equilibrium stability for which clusters of equal weights need to be separated by at least 2R to be stable. These results, however, do not prove the conjecture. To understand the system behavior for a large agent density, we also consider a version of the model that involves a continuum of agents. We study properties of this continuous model and of its equilibria, and investigate the connections between the discrete and continuous versions.
Overview of vectorless/early power grid verification

The power distribution network of an integrated circuit must be checked throughout the design process to ensure that supply voltage fluctuations do not exceed certain critical thresholds. One way of doing this is by simulation, which requires knowledge of the circuit currents that load the grid. These currents are hard to specify. In many cases, and certainly during early power grid design, they may be simply unknown because the circuit itself may not yet be specified. Vector-less verification refers to the class of techniques, developed over the last 12 years, for verifying the grid in the absence of complete information about the circuit currents.
Squeezing a Big Orange into Little Boxes: The AscotDB System for Parallel Processing of Data on a Sphere

AscotDB is a new, extensible data analysis system developed at the University of Washington for the interactive analysis of data from astronomical surveys. AscotDB is a layered system: It builds on SciDB to provide a shared-nothing, parallel array processing and data management engine. AscotDB wraps SciDB with a Python middleware that enables efficient storage and manipulation of spherical data, such as images from telescopes or satellites. The goal is to support the efficient storage of raw pixel-level data without any prior preprocessing steps. To enable both exploratory and deep analysis of the data, AscotDB’s front-end design integrates a python interface with a graphical interface based on the Astronomy Collaborative Toolkit (ASCOT). AscotDB supports seamless switching between these two modes of interaction and captures a precise trace of a user’s operations on the data to ensure repeatability. In this paper, we present an overview of the AscotDB system. While based on astronomy as its key application-domain, AscotDB primitives are general enough to be applicable to other scientific fields concerned with data on a sphere.
Multi-way relay networks: characterization, performance analysis and transmission scheme design

Multi-way relay networks (MWRNs) are a growing research area in the field of relay based wireless networks. Such networks provide a pathway for solving the ever increasing demand for higher data rate and spectral efficiency in a general multi-user scenario. MWRNs have potential applications in video conferencing, file sharing in a social network, as well as satellite networks and sensor networks. Recent research on MWRNs focuses on efficient transmission protocol design by harnessing different network coding schemes, higher dimensional structured codes and advanced relaying protocols. However, the existing research misses out the characterization and analysis of practical issues that influence the performance of MWRNs. Moreover, the existing transmission schemes suffer some significant limitations, that need to be solved for maximizing the benefits of MWRNs. In this thesis, we investigate the practical issues that critically influence the performance of a MWRN and propose solutions that can outperform existing schemes. To be specific, we characterize error propagation phenomenon for additive white Gaussian noise (AWGN) and fading channels with functional decode and forward (FDF) and amplify and forward (AF) relaying protocols, propose a new pairing scheme that outperforms the existing schemes for lattice coded FDF MWRNs in terms of the achievable rate and error performance and finally, analyze the impact of imperfect channel state information (CSI) and optimum power allocation on MWRNs. At first, we analyze the error performance of FDF and AF MWRNs with pairwise transmission using binary phase shift keying (BPSK) modulation in AWGN and Rayleigh fading channels. We quantify the possible error events in an L-user FDF or AF MWRN and derive accurate asymptotic bounds on the probability for the general case that a user incorrectly decodes the messages of exactly k (k ∈ [1, L− 1]) other users. We show that at high signal-to-noise ratio (SNR), the higher order error events (k ≥ 3) are vii
Semen quality in relation to biomarkers of pesticide exposure.

We previously reported reduced sperm concentration and motility in fertile men in a U.S. agrarian area (Columbia, MO) relative to men from U.S. urban centers (Minneapolis, MN; Los Angeles, CA; New York, NY). In the present study we address the hypothesis that pesticides currently used in agriculture in the Midwest contributed to these differences in semen quality. We selected men in whom all semen parameters (concentration, percentage sperm with normal morphology, and percentage motile sperm) were low (cases) and men in whom all semen parameters were within normal limits (controls) within Missouri and Minnesota (sample sizes of 50 and 36, respectively) and measured metabolites of eight current-use pesticides in urine samples provided at the time of semen collection. All pesticide analyses were conducted blind with respect to center and case-control status. Pesticide metabolite levels were elevated in Missouri cases, compared with controls, for the herbicides alachlor and atrazine and for the insecticide diazinon [2-isopropoxy-4-methyl-pyrimidinol (IMPY)]; for Wilcoxon rank test, p = 0.0007, 0.012, and 0.0004 for alachlor, atrazine, and IMPY, respectively. Men from Missouri with high levels of alachlor or IMPY were significantly more likely to be cases than were men with low levels [odds ratios (ORs) = 30.0 and 16.7 for alachlor and IMPY, respectively], as were men with atrazine levels higher than the limit of detection (OR = 11.3). The herbicides 2,4-D (2,4-dichlorophenoxyacetic acid) and metolachlor were also associated with poor semen quality in some analyses, whereas acetochlor levels were lower in cases than in controls (p = 0.04). No significant associations were seen for any pesticides within Minnesota, where levels of agricultural pesticides were low, or for the insect repellent DEET (N,N-diethyl-m-toluamide) or the malathion metabolite malathion dicarboxylic acid. These associations between current-use pesticides and reduced semen quality suggest that agricultural chemicals may have contributed to the reduction in semen quality in fertile men from mid-Missouri we reported previously.
An Architecture of e-Butler: A Consumer-Centric Online Personalization System

This paper presents an architecture of the e-Butler service, i.e. a personalized consumer-centric infomediary delivering a broad range of shopping-related services to consumers. In order to provide these services effectively, e-Butler should be "intelligent". This paper describes how a certain level of intelligence can be achieved through the utilization of a broad range of technologies, including data mining, personalization, profiling, recommender systems, data warehousing, Web proxy servers, data monitoring and XML-based technologies, that are integrated into a unique architecture of e-Butler.
Diameters of the orbital tubes in long-term interferometric SAR surveys

This letter studies the impact of the use of permanent scatterers (PS) on the distribution of the perpendicular baselines in long-term satellite interferometric synthetic aperture radar surveys. This letter also evaluates the relation between the radar center frequency and the dispersion of the estimates of the elevations of the PS as a function of noise and of the time jitter due to atmospheric disturbances.
Semantically Secure Lattice Codes for the Gaussian Wiretap Channel

We propose a new scheme of wiretap lattice coding that achieves semantic security and strong secrecy over the Gaussian wiretap channel. The key tool in our security proof is the flatness factor, which characterizes the convergence of the conditional output distributions corresponding to different messages and leads to an upper bound on the information leakage. We not only introduce the notion of secrecy-good lattices, but also propose the flatness factor as a design criterion of such lattices. Both the modulo-lattice Gaussian channel and genuine Gaussian channel are considered. In the latter case, we propose a novel secrecy coding scheme based on the discrete Gaussian distribution over a lattice, which achieves the secrecy capacity to within a half nat under mild conditions. No a priori distribution of the message is assumed, and no dither is used in our proposed schemes.
Speaker-aware long short-term memory multi-task learning for speech recognition

In order to address the commonly met issue of overfitting in speech recognition, this article investigates Multi-Task Learning, when the auxiliary task focuses on speaker classification. Overfitting occurs when the amount of training data is limited, leading to an over-sensible acoustic model. Multi-Task Learning is a method, among many other regularization methods, which decreases the overfitting impact by forcing the acoustic model to train jointly for multiple different, but related, tasks. In this paper, we consider speaker classification as an auxiliary task in order to improve the generalization abilities of the acoustic model, by training the model to recognize the speaker, or find the closest one inside the training set. We investigate this Multi-Task Learning setup on the TIMIT database, while the acoustic modeling is performed using a Recurrent Neural Network with Long Short-Term Memory cells.
Green wave-based virtual traffic light management scheme with VANETs

Green intelligent transportation systems GITS have received significant attention in recent years. Traffic congestion, which is an important research topic on intelligent transportation systems ITS, is rapidly becoming one of the most serious problems affecting urban areas. This study utilises the vehicular ad hoc networks VANETs technology to build a virtual traffic light VTL environment to reduce traffic congestion. The objective of this study is to adjust the traffic light signal time length on-demand to enable vehicles to pass through numerous intersections rapidly, thereby saving energy and reducing fuel consumption. The traffic phase combination algorithm and VTL operation mechanism are also addressed to improve the traffic congestion situation in urban areas. Simulation results indicate that the proposed scheme can increase the percentage of traffic flow and the average speed of all vehicles in all intersections, thereby saving energy.
Glutaredoxins Grx3 and Grx4 regulate nuclear localisation of Aft1 and the oxidative stress response in Saccharomyces cerevisiae

Grx3 and Grx4, two monothiol glutaredoxins of Saccharomyces cerevisiae, regulate Aft1 nuclear localisation. We provide evidence of a negative regulation of Aft1 activity by Grx3 and Grx4. The Grx domain of both proteins played an important role in Aft1 translocation to the cytoplasm. This function was not, however, dependent on the availability of iron. Here we demonstrate that Grx3, Grx4 and Aft1 interact each other both in vivo and in vitro, which suggests the existence of a functional protein complex. Interestingly, each interaction occurred independently on the third member of the complex. The absence of both Grx3 and Grx4 induced a clear enrichment of G1 cells in asynchronous cultures, a slow growth phenotype, the accumulation of intracellular iron and a constitutive activation of the genes regulated by Aft1. The grx3grx4 double mutant was highly sensitive to the oxidising agents hydrogen peroxide and t-butylhydroperoxide but not to diamide. The phenotypes of the double mutant grx3grx4 characterised in this study were mainly mediated by the Aft1 function, suggesting that grx3grx4 could be a suitable cellular model for studying endogenous oxidative stress induced by deregulation of the iron homeostasis. However, our results also suggest that Grx3 and Grx4 might play additional roles in the oxidative stress response through proteins other than Aft1.
Genetic and biochemical characterization of clathrin-deficient Saccharomyces cerevisiae

Clathrin is important but not essential for yeast cell growth and protein secretion. Diploid Saccharomyces cerevisiae cells heterozygous for a clathrin heavy-chain gene (CHC1) disruption give rise to viable, slow-growing, clathrin heavy-chain-deficient meiotic progeny (G. Payne and R. Schekman, Science 230:1009-1014, 1985). The possibility that extragenic suppressors account for growth of clathrin-deficient cells was examined by deletion of CHC1 from haploid cell genomes by single-step gene transplacement and independently by introduction of a centromere plasmid carrying the complete CHC1 gene into diploid cells before eviction of a chromosomal CHC1 locus and subsequent tetrad analysis. Both approaches yielded clathrin-deficient haploid strains. In mutants missing at least 95% of the CHC1 coding domain, transcripts related to CHC1 were not detected. The time course of invertase modification and secretion was measured to assess secretory pathway functions in the viable clathrin-deficient cells. Core-glycosylated invertase was converted to the mature, highly glycosylated form at equivalent rates in mutant and wild-type cells. Export of mature invertase from mutant cells was delayed but not prevented. Abnormal vacuoles, accumulated vesicles, and Golgi body-derived structures were visualized in mutant cells by electron microscopy. We conclude that extragenic suppressors do not account for the viability of clathrin-deficient cells and, furthermore, that many standard laboratory strains can sustain a CHC1 disruption. Clathrin does not appear to mediate protein transfer from the endoplasmic reticulum to the Golgi body but may function at a later stage of the secretory pathway.
Phenotypic plasticity and genetic adaptation to high-altitude hypoxia in vertebrates

Summary High-altitude environments provide ideal testing grounds for investigations of mechanism and process in physiological adaptation. In vertebrates, much of our understanding of the acclimatization response to high-altitude hypoxia derives from studies of animal species that are native to lowland environments. Such studies can indicate whether phenotypic plasticity will generally facilitate or impede adaptation to high altitude. Here, we review general mechanisms of physiological acclimatization and genetic adaptation to high-altitude hypoxia in birds and mammals. We evaluate whether the acclimatization response to environmental hypoxia can be regarded generally as a mechanism of adaptive phenotypic plasticity, or whether it might sometimes represent a misdirected response that acts as a hindrance to genetic adaptation. In cases in which the acclimatization response to hypoxia is maladaptive, selection will favor an attenuation of the induced phenotypic change. This can result in a form of cryptic adaptive evolution in which phenotypic similarity between high- and low-altitude populations is attributable to directional selection on genetically based trait variation that offsets environmentally induced changes. The blunted erythropoietic and pulmonary vasoconstriction responses to hypoxia in Tibetan humans and numerous high-altitude birds and mammals provide possible examples of this phenomenon. When lowland animals colonize high-altitude environments, adaptive phenotypic plasticity can mitigate the costs of selection, thereby enhancing prospects for population establishment and persistence. By contrast, maladaptive plasticity has the opposite effect. Thus, insights into the acclimatization response of lowland animals to high-altitude hypoxia can provide a basis for predicting how altitudinal range limits might shift in response to climate change.
Assessing transmissibility of HIV-1 drug resistance mutations from treated and from drug-naive individuals

Objectives:Surveillance drug resistance mutations (SDRMs) in drug-naive patients are typically used to survey HIV-1-transmitted drug resistance (TDR). We test here how SDRMs in patients failing treatment, the original source of TDR, contribute to assessing TDR, transmissibility and transmission source of SDRMs. Design:This is a retrospective observational study analyzing a Portuguese cohort of HIV-1-infected patients. Methods:The prevalence of SDRMs to protease inhibitors, nucleoside reverse transcriptase inhibitors (NRTIs) and nonnucleoside reverse transcriptase inhibitors (NNRTIs) in drug-naive and treatment-failing patients was measured for 3554 HIV-1 subtype B patients. Transmission ratio (prevalence in drug-naive/prevalence in treatment-failing patients), average viral load and robust linear regression with outlier detection (prevalence in drug-naive versus in treatment-failing patients) were analyzed and used to interpret transmissibility. Results:Prevalence of SDRMs in drug-naive and treatment-failing patients were linearly correlated, but some SDRMs were classified as outliers – above (PRO: D30N, N88D/S, L90 M, RT: G190A/S/E) or below (RT: M184I/V) expectations. The normalized regression slope was 0.073 for protease inhibitors, 0.084 for NRTIs and 0.116 for NNRTIs. Differences between SDRMs transmission ratios were not associated with differences in viral loads. Conclusion:The significant linear correlation between prevalence of SDRMs in drug-naive and in treatment-failing patients indicates that the prevalence in treatment-failing patients can be useful to predict levels of TDR. The slope is a cohort-dependent estimate of rate of TDR per drug class and outlier detection reveals comparative persistence of SDRMs. Outlier SDRMs with higher transmissibility are more persistent and more likely to have been acquired from drug-naive patients. Those with lower transmissibility have faster reversion dynamics after transmission and are associated with acquisition from treatment-failing patients.
Interdisciplinary Journal of Information, Knowledge, and Management Critical Success Factors for Implementing Business Intelligence Systems in Small and Medium Enterprises on the Example of Upper Silesia, Poland

The main objective of this article is to identify the critical success factors (CSFs) for Business Intelligence (BI) systems implementation in small and medium enterprises (SMEs). The structure of the article is subordinated to this objective. The paper identifies the term Business Intelligence, characteristics of Business Intelligence systems, and various perspectives of their development. Then, the existing CSFs of IT projects and BI projects proposed by various authors in literature are reviewed. Next, on the basis of statistical data and literature, the role of SMEs in the economy and the barriers to their development are assessed. The obtained results allowed us to determine that one of the barriers to the SMEs development is the implementation and use of IT. Subsequently , using in-depth interviews with SMEs, the SMEs need for BI systems as well as the determinants and barriers to their implementation are recognized. Based on the findings, using critical thinking and inductive reasoning, the authors of the article along with the researched enterprises have defined CSFs that are crucial for implementing BI systems in SMEs. The results obtained may be useful for managers, policy makers, business analysts, and IT specialists in dealing with planning and implementation of BI systems in SMEs.
Application of Artificial Neural Network and Geographical Information System Models to Predict and Evaluate the Quality of Diyala River Water, Iraq

This research discusses application Artificial Neural Network (ANN) and Geographical Information System (GIS) models on water quality of Diyala River using Water Quality Index (WQI). Fourteen water parameters were used for estimating WQI: pH, Temperature, Dissolved Oxygen, Orthophosphate, Nitrate, Calcium, Magnesium, Total Hardness, Sodium, Sulphate, Chloride, Total Dissolved Solids, Electrical Conductivity and Total Alkalinity. These parameters were provided from the Water Resources Ministryfrom seven stations along the river for the period 2011 to 2016. The results of WQI analysis revealed that Diyala River is good to poor at the north of Diyala province while it is poor to very polluted at the south of Baghdad City. The selected parameters were subjected to Kruskal-Wallis test for detecting factors contributing to the degradation of water quality and for eliminating independent variables that exhibit the highest contribution in p-value. The analysis of results revealed that ANN model was good in predicting the WQI. The confusion matrix for Artificial Neural Model (NNM) gave almost 96% for training, 85.7% for testing and 100% for holdout. In relation to GIS, six color maps of the river have been constructed to give clear images of the water quality along the river.
A multi-agent system infrastructure for software component market-place: an ontological perspective

In this paper, we introduce a multi-agent system architecture and an implemented prototype for software component market-place. We emphasize the ontological perspective by discussing the ontology modeling for component market-place, UML extensions for ontology modeling, and the idea of ontology transfer which makes the multi-agent system to adapt itself to the dynamically changing ontologies.