Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Lower Bound on DHP: Towards the Equivalence of DHP and DLP for Important Elliptic Curves Used for Implementation

In 2004, Muzereau et al. showed how to use a reduction algorithm of the discrete logarithm problem to Diffie-Hellman problem in order to estimate lower bound on Diffie-Hellman problem on elliptic curves. They presented their estimates for various elliptic curves that are used in practical applications. In this paper, we show that a much tighter lower bound for Diffie-Hellman problem on those curves can be achieved, if one uses the multiplicative group of a finite field as an auxiliary group. Moreover, improved lower bound estimates on Diffie-Hellman problem for various recommended curves are also given which are the tightest; thus, leading us towards the equivalence of Diffie-Hellman problem and the discrete logarithm problem for these recommended elliptic curves.
Silencing the Breast Cancer Resistance Protein Expression and Function in Caco-2 Cells Using Lentiviral Vector-Based Short Hairpin RNA

A series of stable breast cancer resistance protein (BCRP, ABCG2) knockdown cell lines were produced by transduction of Caco-2 cells with lentiviral vector-based short hairpin RNA (shRNA). Caco-2 cell is a human intestinal-derived cell line widely used to study intestinal drug absorption. Caco-2 expresses three apical drug efflux transporters: BCRP, P-glycoprotein (P-gp; ABCB1), and multidrug resistance protein 2 (MRP2, ABCC2). BCRP and P-gp in particular play a significant role in pharmacokinetics because of their expression at several key interfaces. Overexpression of BCRP in cancer cells may also be a mechanism of tumor resistance to chemotherapeutic drugs. The goal of this study was to engineer and characterize Caco-2 cell clones with stable knockdown of BCRP expression. The shRNA/BCRP lentiviral particles were used to infect a stable clone of Caco-2 cells. Expression of BCRP was monitored using quantitative polymerase chain reaction (qPCR), Western blotting, immunofluorescence microscopy, and bidirectional transport of probe substrates, estrone-3-sulfate (E3S), and pheophorbide A (PhA). Based on qPCR, expression of BCRP mRNA was knocked down in five clones with a maximum of 97% silencing in clone D. Silencing of BCRP gene expression was maintained for at least 25 passages. Expression of BCRP protein was also reduced significantly. Functionally, BCRP knockdown was reflected in significant reduction of the efflux ratio of E3S and PhA. Clone D in particular should be a useful model for identifying and characterizing P-gp substrates and inhibitors without interference from BCRP and/or MRP2. In addition, it can be used in conjunction with wild-type or vector control Caco-2 cells to identify BCRP substrates.
Human driver emulation and cognitive decision making for autonomous cars

A cognitive decision making algorithm, which tries to emulate human driver behaviour, for autonomous vehicles is presented in this paper. The decision making process, as well as the integration of the decision making with real time control in different traffic scenarios is studied through simulations using vehicle dynamics model for a car like vehicle. The decision making algorithm was found to perform better, when integrated with the ANFIS Fuzzy Logic longitudinal Control than with conventional PID control. The simulation results with the different traffic scenarios demonstrate the successful integration of the real time control and decision making modules of the Intelligent Vehicle Architecture.
Acoustic Doppler sonar for gait recogination

A person's gait is a characteristic that might be employed to identify him/her automatically. Conventionally, automatic for gait-based identification of subjects employ video and image processing to characterize gait. In this paper we present an Acoustic Doppler Sensor(ADS) based technique for the characterization of gait. The ADS is very inexpensive sensor that can be built using off-the-shelf components, for under $20 USD at today's prices. We show that remarkably good gait recognition is possible with the ADS sensor.
hybridFS: integrating NAND flash-based SSD and HDD for hybrid file system

In this paper, we present a hybrid file system, called hybridFS, whose primary objective is to put together attractive features of both HDD and SSD, to construct a large-scale, virtualized address space in a cost-effective way. HybridFS was designed to take advantage of SSD's high I/O performance, while providing a flexible internal structure to utilize excellent sequential performance of existing file systems. To optimize the limited space capacity of SSD partition, hybridFS supports to define several data sections whose extent size can differ from each other. Such a pre-determined extent size enables to define a data section in such a way to minimize the wasted hole of an extent, by closely matching a multiple of extent size to the file size to be allocated in the data section. Several experiments were conducted to verify the performance of hybridFS.
The bright incubate at night: sexual dichromatism and adaptive incubation division in an open-nesting shorebird

Ornamentation of parents poses a high risk for offspring because it reduces cryptic nest defence. Over a century ago, Wallace proposed that sexual dichromatism enhances crypsis of open-nesting females although subsequent studies found that dichromatism per se is not necessarily adaptive. We tested whether reduced female ornamentation in a sexually dichromatic species reduces the risk of clutch depredation and leads to adaptive parental roles in the red-capped plover Charadrius ruficapillus, a species with biparental incubation. Males had significantly brighter and redder head coloration than females. During daytime, when visually foraging predators are active, colour-matched model males incurred a higher risk of clutch depredation than females, whereas at night there was no difference in depredation risk between sexes. In turn, red-capped plovers maintained a strongly diurnal/nocturnal division of parental care during incubation, with males attending the nest largely at night when visual predators were inactive and females incubating during the day. We found support for Wallace's conclusion that reduced female ornamentation provides a selective advantage when reproductive success is threatened by visually foraging predators. We conclude that predators may alter their prey's parental care patterns and therefore may affect parental cooperation during care.
Tetrahedral Mesh Compression

In the last years, substantial progress has been achieved in the area of volume visualization on irregular grids, which is mainly based on tetrahedral meshes. No attempts have been made so far to compress tetrahedral meshes losslessly, although this is especially important for scientific applications since even moderately fine meshes consume several mega-bytes of storage. In this paper we close this gap and present compression and decompression algorithms, which reduce the storage space required for the connectivity to few bits per tetrahedron. Thus a tetrahedral mesh can almost be reduce to the vertex coordinates, that consume in a common representation about one quarter of the total storage space. We introduce and analyze the generalization of several triangle mesh compression algorithms to the tetrahedral case. We show that the implemented approach achieves the highest compression rates. We round off our work with solutions for the compression of vertex coordinates and additional attributes, which might be attached to the mesh. CR Categories: I.3. 5 [Computer Graphics]: Computational Geometry and Object Modeling—object representations I.3. 6 [Computer Graphics]: Methodology and Techniques—Graphics data structures and data types E.4 [E.4 Coding and Information Theory]: Data compaction and compression
Biodiesel as an Alternative Fuel for Diesel Engines

There is growing interest in biodiesel (fatty acid methyl ester or FAME) because of the similarity in its properties when compared to those of diesel fuels. Diesel engines operated on biodiesel have lower emissions of carbon monoxide, unburned hydrocarbons, particulate matter, and air toxics than when operated on petroleum-based diesel fuel. Production of fatty acid methyl ester (FAME) from rapeseed (nonedible oil) fatty acid distillate having high free fatty acids (FFA) was investigated in this work. Conditions for esterification process of rapeseed oil were 1.8 % H2SO4 as catalyst, MeOH/oil of molar ratio 2 : 0.1 and reaction temperature 65 °C, for a period of 3h. The yield of methyl ester was > 90 % in 1 h. The amount of FFA was reduced from 93 wt % to less than 2 wt % at the end of the esterification process. The FAME was pureed by neutralization with 1 M sodium hydroxide in water solution at a reaction temperature of 62 ̊C. The final FAME product met with the biodiesel quality standard, and ASTM D 6751. Keywords—Alternative Fuels, Biodiesel, Fatty Acid, Methyl Ester, Seed Oil, Transesterification.
Gestion dynamique des règles métiers dans les systèmes d'information dédiés à la conception collaborative

Ce memoire contribue a la comprehension des problematiques liees a la coherence des modeles experts dans un contexte de conception cooperative. Des lors qu'au moins deux concepteurs cooperent a un niveau technique de conception, ils partagent de nombreux objets, parametres, informations ou morceaux de modeles. Cependant ils ne peuvent travailler toujours simultanement et des phases de travail asynchrones sont indispensables. L'objectif de notre travail est de specifier les mecanismes necessaires pour mettre en oeuvre des regles metier repondant aux coherences techniques entre concepteurs. On peut imaginer lors de ces phases asynchrones un serveur espionnant l'evolution des modeles de chaque concepteur. Nous definissons des modeles de regles metiers et des mecanismes qui permettent d'evaluer si deux etudes paralleles divergent au dela de la simple comparaison syntaxique des modeles. Cette mesure de la divergence est alors est utilise pour notifier en temps voulu les acteurs de la necessite de provoquer une session de synchronisation et de negociation. Nous proposons des solutions originales pour assister ces activites de conception cooperative. Elles sont basees sur l'utilisation d'un modele de partage qui est simultanement versionne par les differents collaborateurs. Ces versions sont analysees par des mecanismes syntaxiques et sur la base de contraintes metiers. Ces mecanismes permettent la mesure des evolutions paralleles des versions de modeles afin de communiquer aux differents concepteurs l'etat de coherence de l'environnement de conception et la necessite de provoquer des tâches collaboratives. Au dela de cette proposition theorique, nous avons developpe un demonstrateur qui valide une part des propositions avancees
Meta Analysis of Gene Expression Data within and Across Species

Since the second half of the 1990s, a large number of genome-wide analyses have been described that study gene expression at the transcript level. To this end, two major strategies have been adopted, a first one relying on hybridization techniques such as microarrays, and a second one based on sequencing techniques such as serial analysis of gene expression (SAGE), cDNA-AFLP, and analysis based on expressed sequence tags (ESTs). Despite both types of profiling experiments becoming routine techniques in many research groups, their application remains costly and laborious. As a result, the number of conditions profiled in individual studies is still relatively small and usually varies from only two to few hundreds of samples for the largest experiments. More and more, scientific journals require the deposit of these high throughput experiments in public databases upon publication. Mining the information present in these databases offers molecular biologists the possibility to view their own small-scale analysis in the light of what is already available. However, so far, the richness of the public information remains largely unexploited. Several obstacles such as the correct association between ESTs and microarray probes with the corresponding gene transcript, the incompleteness and inconsistency in the annotation of experimental conditions, and the lack of standardized experimental protocols to generate gene expression data, all impede the successful mining of these data. Here, we review the potential and difficulties of combining publicly available expression data from respectively EST analyses and microarray experiments. With examples from literature, we show how meta-analysis of expression profiling experiments can be used to study expression behavior in a single organism or between organisms, across a wide range of experimental conditions. We also provide an overview of the methods and tools that can aid molecular biologists in exploiting these public data.
Robust $H_{\infty }$ Fuzzy Output-Feedback Control With Multiple Probabilistic Delays and Multiple Missing Measurements

In this paper, the robust H∞-control problem is investigated for a class of uncertain discrete-time fuzzy systems with both multiple probabilistic delays and multiple missing measurements. A sequence of random variables, all of which are mutually independent but obey the Bernoulli distribution, is introduced to account for the probabilistic communication delays. The measurement-missing phenomenon occurs in a random way. The missing probability for each sensor satisfies a certain probabilistic distribution in the interval. Here, the attention is focused on the analysis and design of H∞ fuzzy output-feedback controllers such that the closed-loop Takagi-Sugeno (T-S) fuzzy-control system is exponentially stable in the mean square. The disturbance-rejection attenuation is constrained to a given level by means of the H∞-performance index. Intensive analysis is carried out to obtain sufficient conditions for the existence of admissible output feedback controllers, which ensures the exponential stability as well as the prescribed H∞ performance. The cone-complementarity-linearization procedure is employed to cast the controller-design problem into a sequential minimization one that is solved by the semi-definite program method. Simulation results are utilized to demonstrate the effectiveness of the proposed design technique in this paper.
Water Drinking Acutely Improves Orthostatic Tolerance in Healthy Subjects

Background—Orthostatic symptoms and syncope are common, even in apparently healthy subjects. In patients with severe autonomic dysfunction, water drinking elicits an acute pressor response and improves orthostatic hypotension. We tested the hypothesis that water drinking also improves orthostatic tolerance in healthy subjects. Methods and Results—In a randomized, controlled, crossover fashion, 13 healthy subjects (9 men, 4 women, 31±2 years) ingested 500 mL and 50 mL of mineral water 15 minutes before head-up tilt on two separate days. Finger blood pressure, brachial blood pressure, heart rate, thoracic impedance, and blood flow velocity in the brachial artery and the middle cerebral artery were measured. Orthostatic tolerance was determined as the time to presyncope during a combined protocol of 20 minutes of 60° head-up tilt alone, followed by additional increasing steps of lower body negative pressure (−20, −40, and −60 mm Hg for 10 minutes each or until presyncope). Drinking 500 mL of water improved orthostatic tolerance by 5±1 minute (range, −1 to +11 minutes, P <0.001). After drinking 500 mL of water, supine mean blood pressure increased slightly (P <0.01) as the result of increased peripheral resistance (P <0.01). It also blunted both the increase in heart rate and the decrease in stroke volume with head-up tilt. Cerebral blood flow regulation improved after water drinking. Conclusions—Water drinking elicits an acute hemodynamic response and changes in cerebrovascular regulation in healthy subjects. These effects are associated with a marked improvement in orthostatic tolerance.
An Analysis Dictionary Learning Algorithm under a Noisy Data Model with Orthogonality Constraint

Two common problems are often encountered in analysis dictionary learning (ADL) algorithms. The first one is that the original clean signals for learning the dictionary are assumed to be known, which otherwise need to be estimated from noisy measurements. This, however, renders a computationally slow optimization process and potentially unreliable estimation (if the noise level is high), as represented by the Analysis K-SVD (AK-SVD) algorithm. The other problem is the trivial solution to the dictionary, for example, the null dictionary matrix that may be given by a dictionary learning algorithm, as discussed in the learning overcomplete sparsifying transform (LOST) algorithm. Here we propose a novel optimization model and an iterative algorithm to learn the analysis dictionary, where we directly employ the observed data to compute the approximate analysis sparse representation of the original signals (leading to a fast optimization procedure) and enforce an orthogonality constraint on the optimization criterion to avoid the trivial solutions. Experiments demonstrate the competitive performance of the proposed algorithm as compared with three baselines, namely, the AK-SVD, LOST, and NAAOLA algorithms.
A Data Mining Approach to Motif Function Prediction

Conserved protein sequence motifs are short stretches of amino acid sequence patterns that encode the function of proteins. Several sequence pattern searching algorithms and programs exist for identifying candidate protein motifs at the whole genome level. However, a much needed and important task is to determine the functions of the newly identified protein motifs. The Gene Ontology (GO) project is an endeavor to annotate the function of genes or protein sequences with terms from a dynamic, controlled vocabulary and these annotations serve well as a knowledge base. This paper presents methods to mine the GO knowledge base and use the association between the GO terms assigned to a sequence and the motifs matched by the same sequence as evidence for predicting the functions of novel protein motifs automatically. The task of assigning GO terms to protein motifs is viewed as both a binary classification and information retrieval problem. The mutual information of a motif and a GO term association is found to be a very useful feature. We take advantage of the known motifs to train a logistic regression classifier, which allows us to combine mutual information with other frequency-based features and obtain a probability of correct association. The trained logistic regression model has intuitively meaningful and logically plausible parameter values, and performs very well empirically according to our evaluation criteria. The method has a great potential for detecting and augmenting information about the functions of newly discovered candidate protein motifs.
Hysteresis Torque Estimation Method Based on Iron-Loss Analysis for Permanent Magnet Synchronous Motor

In the design process of permanent magnet synchronous motors (PMSMs), the hysteresis torque has so far been ignored under the understanding that it is already small enough. However, for some delicate applications, such as an exoskeleton wearable robot, the hysteresis torque, whose proportion increases under no-load or low-load conditions, needs to be further minimized even though the hysteresis torque has low magnitude. Conventional methods using hysteresis models to calculate the hysteresis torque require a lot of computation resources. Therefore, this paper proposes a simpler method in order to estimate the hysteresis torque using iron-loss experimental data. In the proposed method, the hysteresis torque is derived from the hysteresis loss, which is separated from the iron-loss experimental data by using the modified Steinmetz equation. Finally, the hysteresis torque of the proposed surface-mounted PMSM is measured via experiments to verify the validity of the proposed method. The hysteresis torque is obtained by subtracting the mechanical friction torque from the no-load offset torque. The experimental result is compared with the results obtained from the proposed method.
Detecting Non-compositional MWE Components using Wiktionary

We propose a simple unsupervised approach to detecting non-compositional components in multiword expressions based on Wiktionary. The approach makes use of the definitions, synonyms and translations in Wiktionary, and is applicable to any type of MWE in any language, assuming the MWE is contained in Wiktionary. Our experiments show that the proposed approach achieves higher F-score than state-of-the-art methods.
A Fuzzy Filter for the Removal of Gaussian Noise in Colour Image Sequences

In this paper a new fuzzy filter for the removal of ad- ditive Gaussian noise in colour image sequences is presented. The proposed method, which is a colour extension of our previous work on greyscale images, consists of two subfilters. The first subfilter av- erages the noise in each of the colour bands separately. In this aver- aging, the weights of the neighbouring pixels are determined by fuzzy rules. Even though the filtering is performed in each colour band sep- arately, information from the other colour bands is also used in the fuzzy rules. In this way, we can be more confident whether a neigh- bouring pixel is similar to the pixel being filtered. In order to further improve the results, a second subfilter is applied too. This colour restorating filter is based on the simplified assumption that for simi- lar pixels the pixel value difference should be approximately the same in all colour bands. A pixel is estimated from its neighbours by esti- mating the differences in each colour band equal to the average over all colour bands. Experimental results show that, in terms of average PSNR and average NCD, the proposed colour extension of our previ- ous work outperforms the usual colour extension of a greyscale filter, in which the Y component in the YU Vtransform is filtered with the original greyscale method and the chrominance bands U and V are averaged.
A Field Guide to Genetic Programming

Genetic programming (GP) is a systematic, domain-independent method for getting computers to solve problems automatically starting from a high-level statement of what needs to be done. Using ideas from natural evolution, GP starts from an ooze of random computer programs, and progressively refines them through processes of mutation and sexual recombination, until high-fitness solutions emerge. All this without the user having to know or specify the form or structure of solutions in advance. GP has generated a plethora of human-competitive results and applications, including novel scientific discoveries and patentable inventions. This unique overview of this exciting technique is written by three of the most active scientists in GP. See www.gp-field-guide.org. uk for more information on the book.
Douglas fir (pseudotsuga menziesii) plantlets responses to as, PB, and sb-contaminated soils from former mines

ABSTRACT Phytoremediation of metalloids by conifers is not widely studied although they may be relevant for several contaminated sites, especially those located in cold areas and sometimes under dry climates. Here, seeds of Douglas fir were sown in greenhouse on three soils collected in two French former mines: a gold mine (soils L1 and L2) and a lead and silver mine (soil P). These soils are highly contaminated by Pb, As, and Sb at different concentrations. Plants were harvested after ten weeks. Growth parameters, primary metabolite content, and shoot and root ionomes were determined. Douglas firs grown on the soils L1 and P had a lower biomass than controls and a higher oxidation status whereas those grown on the soil L2 exhibited a more developed root system and only slight modifications of carbon and nitrogen nutrition. Based on trace element (TE) concentrations in shoots and roots and their translocation factor (TF), Douglas fir could be a relevant candidate for As phytoextraction (0.8 g. kg−1 dry weight in shoots and a TF of 1.1) and may be used to phytostabilize Pb and Sb (8.8 g and 127 mg. kg−1 in roots for Pb and Sb, respectively, and TF lower than 0.1).