Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast Power Allocation for Secure Communication With Full-Duplex Radio

This paper considers a method for improving physical layer security of wireless networks with full-duplex radio. In particular, fast algorithms are developed to compute power allocations in subcarriers, subject to power and rate constraints, to maximize the secrecy capacity of a three-node network consisting of a source, a full-duplex destination, and an eavesdropper. A residual level of radio self-interference channel is considered. The optimal power allocation at the destination is found to be significant especially when its power budget is high. Also studied in this paper are a network with multiple full-duplex destinations and another network with multiple sources. Using the algorithms developed in this paper, we are able to show that a multiuser strategy that optimizes the power distributions among the users (in terms of either the sources or the destinations) can yield a substantial gain of secrecy capacity over a single-user strategy.
Machine Learning Based Recommendation System

Recommendation system has been seen to be very useful for user to select an item amongst many. Most existing recommendation systems rely either on a collaborative approach or a content based approach to make recommendations. We have applied machine learning techniques to build recommender systems. We have taken two approaches. In the first approach a content based recommender system is built, which uses collaborative data, so that it gets the effect of a hybrid approach to get better result of recommendation. Attributes used for content based recommendations are assigned weights depending on their importance to users. The weight values are estimated from a set of linear regression equations obtained from a social network graph which captures human judgment about similarity of items. In the second approach agent of call centre have been recommended some procedure depending on the current state of online call. A combination of K-Means Algorithm and Hidden Markov model is used.
Calculation of thermal noise in atomic force microscopy

Thermal fluctuations of the cantilever are a fundamental source of noise in atomic force microscopy. We calculated thermal noise using the equipartition theorem and considering all possible vibration modes of the cantilever. The measurable amplitude of thermal noise depends on the temperature, the spring constant K of the cantilever and on the method by which the cantilever deflection is detected. If the deflection is measured directly, e.g. with an interferometer or a scanning tunneling microscope, the thermal noise of a cantilever with a free end can be calculated from square root kT/K. If the end of the cantilever is supported by a hard surface no thermal fluctuations of the deflection are possible. If the optical lever technique is applied to measure the deflection, the thermal noise of a cantilever with a free end is square root 4kT/3K. When the cantilever is supported thermal noise decreases to square root kT/3K, but it does not vanish.
Machine Learning vs Deterministic Rule-Based System for Document Stream Segmentation

Classical document stream Segmentation methods rely on physical separators (white pages, pages with a specific stamp, etc) to automatically split documents from the stream (detecting the beginning and the ending of documents). In order to reduce costly efforts, a recent work using a contextual rulebased approach was proposed to automate this process. Such rules tend to detect continuity, rupture or uncertainty between pairs of pages. Even if these first results were encouraging, performance remained unsatisfactory. In this context, we propose to compare this existing rule-based approach to a machine learningmethod basedon Doc2Vecsoas toevaluate andcompare their strengths and weaknesses. This study was led on a corpus of more than 4,000 real administrative documents composed of more than 8,000 pages. The machine learning approach gives better results on multipage documents while the rule-based method performs best with single page documents.
Surface functionalities of gold nanoparticles impact embryonic gene expression responses

Abstract Incorporation of gold nanoparticles (AuNPs) into consumer products is increasing; however, there is a gap in available toxicological data to determine the safety of AuNPs. In this study, we utilised the embryonic zebrafish to investigate how surface functionalisation and charge influence molecular responses. Precisely engineered AuNPs with 1.5 nm cores were synthesised and functionalized with three ligands: 2-mercaptoethanesulfonic acid (MES), N,N,N-trimethylammoniumethanethiol (TMAT), or 2-(2-(2-mercaptoethoxy)ethoxy)ethanol. Developmental assessments revealed differential biological responses when embryos were exposed to the functionalised AuNPs at the same concentration. Using inductively coupled plasma–mass spectrometry, AuNP uptake was confirmed in exposed embryos. Following exposure to MES- and TMAT-AuNPs from 6 to 24 or 6 to 48 h post fertilisation, pathways involved in inflammation and immune response were perturbed. Additionally, transport mechanisms were misregulated after exposure to TMAT and MES-AuNPs, demonstrating that surface functionalisation influences many molecular pathways.
Dopamine transporter‐dependent and ‐independent actions of trace amine β‐phenylethylamine

β‐Phenylethylamine (β‐PEA) is an endogenous amine that is found in trace amounts in the brain. It is believed that the locomotor‐stimulating action of β‐PEA, much like amphetamine, depends on its ability to increase extracellular dopamine (DA) concentrations owing to reversal of the direction of dopamine transporter (DAT)‐mediated DA transport. β‐PEA can also bind directly to the recently identified G protein‐coupled receptors, but the physiological significance of this interaction is unclear. To assess the mechanism by which β‐PEA mediates its effects, we compared the neurochemical and behavioral effects of this amine in wild type (WT), heterozygous and ‘null’ DAT mutant mice. In microdialysis studies, β‐PEA, administered either systemically or locally via intrastriatal infusion, produced a pronounced outflow of striatal DA in WT mice whereas no increase was detected in mice lacking the DAT (DAT‐KO mice). Similarly, in fast‐scan voltammetry studies β‐PEA did not alter DA release and clearance rate in striatal slices from DAT‐KO mice. In behavioral studies β‐PEA produced a robust but transient increase in locomotor activity in WT and heterozygous mice. In DAT‐KO mice, whose locomotor activity and stereotypy are increased in a novel environment, β‐PEA (10–100 mg/kg) exerted a potent inhibitory action. At high doses, β‐PEA induced stereotypies in WT and heterozygous mice; some manifestations of stereotypy were also observed in the DAT‐KO mice. These data demonstrate that the DAT is required for the striatal DA‐releasing and hyperlocomotor actions of β‐PEA. The inhibitory action on hyperactivity and certain stereotypies induced by β‐PEA in DAT‐KO mice indicate that targets other than the DAT are responsible for these effects.
Going Beyond the Rhetoric

Health is a fundamental human right. Unfortunately the pursuit of good health remains a struggle for marginalized individuals/groups because of the rise of new centres of power. Hepworth (this issue) argues that critical health psychologists can contribute to the promotion of public health by moving towards ‘greater practice and action orientation’. Until we learn to become more actively involved in translating our research into practice, our efforts will only end up being done in vain. To pursue our humanitarian aims, CHP needs to move beyond the confines of its academic circle and begin to share its vision with a greater audience—society itself.
Evolution and Comparative Genomics of Campylobacter jejuni ST-677 Clonal Complex

Campylobacter is the most common bacterial cause of gastroenteritis in the European Union with over 200,000 laboratory-confirmed cases reported annually. This is the first study to describe findings related to comparative genomics analyses of the sequence type (ST)-677 clonal complex (CC), a Campylobacter jejuni lineage associated with bacteremia cases in humans. We performed whole-genome sequencing, using Illumina HiSeq sequencing technology, on five related ST-677 CC isolates from two chicken farms to identify microevolution taking place at the farms. Our further aim was to identify novel putative virulence determinants from the ST-677 CC genomes. For this purpose, clinical isolates of the same CC were included in comparative genomic analyses against well-known reference strains of C. jejuni. Overall, the ST-677 CC was recognized as a highly clonal lineage with relatively small differences between the genomes. Among the farm isolates differences were identified mainly in the lengths of the homopolymeric tracts in genes related to the capsule, lipo-oligosaccharide, and flagella. We identified genomic features shared with C. jejuni subsp. doylei, which has also been shown to be associated with bacteremia in humans. These included the degradation of the cytolethal distending toxin operon and similarities between the capsular polysaccharide biosynthesis loci. The phase-variable GDP-mannose 4,6-dehydratase (EC 4.2.1.47) (wcbK, CAMP1649), associated with the capsular polysaccharide biosynthesis locus, may play a central role in ST-677 CC conferring acid and serum resistance during different stages of infection. Homology-based searches revealed several additional novel features and characteristics, including two putative type Vb secretion systems and a novel restriction modification/methyltransferase gene cluster, putatively associated with pathogenesis and niche adaptation.
Adaptive Gray Level Difference to Speed Up Fractal Image Compression

Fractal image compression is a lossy compression technique that has been developed in the early 1990s. It makes use of the local self similarity property existing in an image and finds a contractive mapping affine transformation (fractal transform) T, such that the fixed point of T is close to the given image in a suitable metric. It has generated much interest due to its promise of high compression ratios with good decompression quality. The other advantage is its multiresolution property, i.e. an image can be decoded at higher or lower resolutions than the original without much degradation in quality. However, the encoding time is computationally intensive. In this paper, a new method to reduce the encoding time based on computing the gray level difference of domain and range blocks, is presented. A comparison for best match is performed between the domain and range blocks only if the range block gray level difference is less than the domain block gray level difference. This reduces the number of comparisons, and thereby the encoding time considerably, while obtaining good fidelity and compression ratio for the decoded image. Experimental results on standard gray scale images (512times512, 8 bit) show that the proposed method yields superior performance over conventional fractal encoding
Factors associated with T2 Shine-Through Effect in Hepatic Hemangiomas on Diffusion-weighted MR Sequences

Poster: "ECR 2014 / C-0229 / Factors associated with T2 Shine-Through Effect in Hepatic Hemangiomas on Diffusion-weighted MR Sequences" by: "R. Duran1, M. Ronot2, A. kerbaol2, B. Van Beers2, V. Vilgrain3; 1Lausanne/CH, 2Clichy/FR, 3Clichy /FR"
Visual Encodings of Temporal Uncertainty: A Comparative User Study

A number of studies have investigated different ways of visualizing uncertainty. However, in the temporal dimension, it is still an open question how to best represent uncertainty, since the special characteristics of time require special visual encodings and may provoke different interpretations. Thus, we have conducted a comprehensive study comparing alternative visual encodings of intervals with uncertain start and end times: gradient plots, violin plots, accumulated probability plots, error bars, centered error bars, and ambiguation. Our results reveal significant differences in error rates and completion time for these different visualization types and different tasks. We recommend using ambiguation - using a lighter color value to represent uncertain regions - or error bars for judging durations and temporal bounds, and gradient plots - using fading color or transparency - for judging probability values.
FORMULATION DEVELOPMENT AND OPTIMIZATION OF NATEGLINIDE-LOADED ETHYL CELLULOSE NANOPARTICLES BY BOX-BEHNKEN DESIGN

Objective: Application of nanotechnology in drug delivery system has released leading new areas of research in sustained release of drugs. The objective of the present study is development and optimization of polymeric nanoparticles of Nateglinide (NTG). Methods: Nateglinide loaded ethyl cellulose (EC) nanoparticles were prepared by the solvent evaporation technique. Response surface methodology (RSM) using the Box-Behnken design was used to optimize the formulation of Nateglinide nanoparticles. The Box-Behnken design consisting of 14 runs, three-factor, three levels and two centre point was used in this study. The particle size, zeta potential and entrapment efficiency of Nateglinide nanoparticles were investigated with respect to three independent variables including stirring speed (X 1 ), time (X 2 ) and surfactant concentration (X 3 ). The optimized nanoparticle is then subjected to characterization studies including morphology, particle size, zeta potential, % Drug Loading (DL) and % Entrapment Efficiency (EE). Results: Nateglinide nanoparticles under the optimized conditions gave rise to the DL of 14.30±0.27 %, EE of 72.19±0.24 %, mean diameter of 172 nm and zeta potential value of-15.6 mV. Conclusion: The optimized nanoparticles formulation with improved characteristic properties could be a promising delivery system for Nateglinide.
Estimating integrated information with TMS pulses during wakefulness, sleep, and under anesthesia

This paper relates a recently proposed measure of information integration to experiments investigating the evoked high-density electroencephalography (EEG) response to transcranial magnetic stimulation (TMS) during wakefulness, early non-rapid eye movement (NREM) sleep and under anesthesia. We show that bistability, arising at the cellular and population level during NREM sleep and under anesthesia, dramatically reduces the brain's ability to integrate information.
Moisture retention and conductivity properties of waste refuse: a laboratory study.

The modelling of infiltration and moisture movement within a porous medium requires information on the moisture retention and hydraulic conductivity properties. In this study, the unsaturated hydraulic behaviour of a compacted waste sample based on the composition of Lyndhurst Landfill site in Melbourne, Australia was investigated in laboratory. Two fundamental aim of the study were to establish the moisture retention characteristics of Municipal Solid Waste (MSW) sample and measure its unsaturated hydraulic conductivity. In landfilled waste, the particle and pore size distribution, heterogeneity of waste composition and leachate chemistry complicate the determination of moisture retention and hydraulic conductivity. In this study the modification and use of a standard pressure plate apparatus was described which can be used establish moisture retention properties of samples of 230 mm in diameter. The experiments showed that the moisture retention characteristics of compacted waste sample were comparable to soils. It has been shown that water retention in waste is a function of its position relative to the phreatic surface, in other words, its hydraulic boundary conditions which will vary with elevation. Some difficulties and limitations of using this method were discussed. As with conventional inert soils, laboratory determination of unsaturated hydraulic conductivity is difficult and recourse is often made to analytical methods as those presented by van Genuchten (1980). One aim of this study was to compare the unsaturated hydraulic conductivity of MSW obtained using Passioura' s (1976) onestep outflow test method with predictions using van Genuchten's model. Good agreement is observed between the predictive model and experimental method for unsaturated hydraulic conductivities at low moisture contents but there is poor agreement at high degrees of saturation. This latter discrepancy is attributed to the difficulty of measuring retention properties of large pores at low suctions and the applicability of the van Genuchten model to such a material. Results also suggest that dual porosity exists within waste.
An object-based approach to similar image retrieval

This paper proposes a new object-based approach to similar image retrieval. First the salient regions of an image are detected by using a novel segmentation method based on a multi-scale inhomogeneous diffusion model applied to color and texture features. Each detected region is then represented by a feature vector composed from the characteristic color, texture and shape features of a region whose features are invariant under rotation. Scale invariance is also addressed for the color and shape properties. An R* tree-based indexing scheme is applied over the feature space to ensure efficient searching. By applying a suitable user interface, the method can handle sub-image queries and object-based queries with regard to a certain object or objects in the input image specified by the user. Experiments conducted on a large number of images taken from photo-CD data and collected from the Internet, show that the method performs well for a large variety of natural images.
A Fast Least-Squares Solution-Seeker Algorithm for Vector-Perturbation

Finding the least-squares solution to a system of linear equations where the unknown vector is comprised of integers, but the matrix coefficient and given vector are comprised of real or complex numbers is a problem equivalent to finding the closest lattice-point to a given point and is well known that the search is hard. However, in communications applications the given vector is not arbitrary but rather is an unknown lattice-point that has been perturbed by an additive offset vector whose statistical properties are known, making it relatively easier to decode. In this paper we will discuss the vector- perturbation technique proposed for solving this problem and analyse a possible solution for overcome the complexity issues.
2 SOFTWARE QUALITY MANAGEMENT

It is difficult to imagine our world without software. Since software is so ubiquitous, we need to stay in control. We have to make sure that the systems and their software run as we intend – or better. Only if software has the right quality, we will stay in control and not suddenly realize that things are going awfully wrong. Software quality management is the discipline that ensures that the software we are using and depending upon is of right quality. With solid understanding and discipline in software quality management, we can be sure that our products will deliver according to expectations, both in terms of customer and market commitments as well as business performance. This article provides a brief overview on concepts and application of software quality management. It is driven by practical experiences from many companies and is illustrated with best practices so that readers can transfer these concepts to their own environments.
Geometric modelling of industrial preforms: Woven and braided textiles

Abstract Predictive calculations of the physical properties of fibrous preforms and composite parts require an appropriate description of the preform geometry. Most internal dimensions of a preform are set during its manufacturing through mechanical interactions occurring between the tows and threads. However, the global shape and the interlacing patterns of the constituent textiles are determined independently. In this paper, a formal procedure for the description of the interlacing patterns is proposed. This procedure, which is based on the individual textile manufacturing processes, is general in the textiles considered and in the possible applications. The interlacing patterns are expressed by a series of vectors that follow a universal set of criteria and are generated from the values taken by the processing parameters. Defining examples are given for three-dimensional woven textiles and three-dimensional tubular braided textiles, and geometrical applications are also presented. Further examples for warp-knitted textiles and multiple-layer stacks will be given in a subsequent paper, together with examples of physical applications.
Clinical toxicology of acrylonitrile.

Acrylonitrile monomer is used in the production of artificial fibres and resins. It has been used as a fumigant. Acrylonitrile has acute toxic effects for men and animals on over-exposure by inhalation of the vapor, dermal absorption of the liquid and oral intake. Symptoms in men are non-specific and predominantly related to the central nervous system, the respiratory tract, the skin and to the gastrointestinal tract. Severe acrylonitrile intoxication is followed by loss of consciousness, convulsions, respiratory arrest and death. The detailed investigation of a patient with complaints after chronic exposure demonstrates the necessity of objective neurophysiologic studies. Acrylonitrile has carcinogenic properties in animals. It is also embryotoxic and teratogenic. Epidemiological studies in men exposed to acrylonitrile are not convincing. There may be a slight excess of deaths from lung cancers and other malignant tumors. Effects of potential antidotes were studied in animal experiments. Rats were intoxicated with lethal doses of acrylonitrile by different routes of application. The cyanide antidotes 4-dimethylaminophenol plus thiosulfate showed some protective effect only after oral but not after i.p. or inhalational acrylonitrile administration. Of the sulfhydryl compounds cysteine, N-acetyl-cysteine, cysteamine and diethyldithiocarbamate, the two antidotes cysteine and N-acetylcysteine proved to be especially effective. From these experiments a tentative schedule of antidotal therapy for humans accidentally intoxicated with acrylonitrile is inferred, using N-acetylcysteine by analogy with the therapeutic regimen effective in cases of paracetamol poisoning.
Modeling interconnect variability using efficient parametric model order reduction

Assessing IC manufacturing process fluctuations and their impacts on IC interconnect performance has become unavoidable for modern DSM designs. However, the construction of parametric interconnect models is often hampered by the rapid increase in computational cost and model complexity. In this paper we present an efficient yet accurate parametric model order reduction algorithm for addressing the variability of IC interconnect performance. The efficiency of the approach lies in a novel combination of low-rank matrix approximation and multi-parameter moment matching. The complexity of the proposed parametric model order reduction is as low as that of a standard Krylov subspace method when applied to a nominal system. Under the projection-based framework, our algorithm also preserves the passivity of the resulting parametric models.