Miracle-dz/UniFAR-FTUs huggingface dataset:
Les processus d'influence publicitaire : un essai de modélisation intégrant implication vis à vis de la publicité, caractéristiques psychologiques et publicitaires

Cette these a pour ambition de mieux comprendre les processus d'influence d'une publicite sur l'attitude d'un individu vis-a-vis de la marque, objet de la dite publicite, en poursuivant trois objectif:- confirmer et affiner dans un contexte francais la nature des differents elements mediateurs du changement d'attitude, donnant naissance a ce que la litterature nomme >-demontrer et caracteriser la variabilite de ces routes en fonction d'un certain nombre de parametres lies au type de publicite (a tendance informative ou plutot emotionnelle) et a la psychologie de lindividu; - eclaircir le role intermediaire joue par l'implication publicitaire, distinguant ses trois grandes familles d'antecedents (publicite, individu et contexte d'exposition), statuant sur la nature d'etat du concept et mettant en exergue ses consequences sur la route de persuasion empruntee. En termes de methodologie, ce travail se caracterise par la volonte de retranscrire autant que faire se peut la realite d'une situation d'exposition a une publicite, ce qui se traduit concretement par: - la mise en place d'une collecte de donnees en collaboration avec une societe de pretests publicitaires gfk,- des precautions particulieres dans la creation et la validation des echelles de mesure utilisees, et enfin, - le recours a des profils psychologiques ou d'implication publicitaire, constitues au moyen de typologies a posteriori a partir de plusieurs variables considerees simultanement et donc plus a meme de restituer la diversite de la realite. Les resultats obtenus repondent aux ob jectifs initiaux de cette recherche, validant un grand nombre d'hypothese emises sur le plan conceptuel et permettent in fine de tracer, pour l'avenir des voies d'investigations precises, envisageant, par exemple, d'appliquer ce travail a d'autres produits et publicites ou d'integrer sur le terrain des concepts restes jusqu'a present a une niveau uniquement theorique, comme la notion tres vaste, mais prometteuse, de motivation.
Energy-Efficient Resource Allocation in Cellular Network with Ambient RF Energy Harvesting

Simultaneous wireless information and power transfer is an innovative way to provide electrical energy for user equipments. However, most previous works mainly focus on energy harvesting over a relatively narrow frequency range. Due to small energy harvested by the users, the practical applications are usually limited to low power devices. In this paper, an energy-efficient uplink resource allocation problem is investigated in a cellular network with ambient radio frequency (RF) energy harvesting. In order to obtain sufficient energy, a broadband rectenna is adopted to harvest ambient RF energy over six frequency bands at the same time. From the viewpoint of service arrival in the ambient transmitter, a new energy arrival model is presented. The problem of sub-carrier and power allocation is formulated as a mixed-integer nonlinear programming problem. The objective is to maximize the energy efficiency while satisfying the energy causality and the total data rate requirement. In order to reduce the computational complexity, a suboptimal solution is derived by employing a quantum-behaved particle swarm optimization (QPSO) algorithm. Simulation results show that the QPSO method has higher energy efficiency than a conventional particle swarm optimization approach.
Ciprofloxacin-Resistant Salmonella enterica Serotype Typhi, United States, 1999–2008

We report 9 ciprofloxacin-resistant Salmonella enterica serotype Typhi isolates submitted to the US National Antimicrobial Resistance Monitoring System during 1999–2008. The first 2 had indistinguishable pulsed-field gel electrophoresis patterns and identical gyrA and parC mutations. Eight of the 9 patients had traveled to India within 30 days before illness onset.
Oestrogen and seasonal effects on the production of an oestrus-associated glycoprotein in oviducal fluid of sheep.

In 14 cyclic ewes, the oestrus-associated glycoprotein in the oviducal fluid was never detected between Days 7 and -2 of the oestrous cycle and it was present in 5% of fluid samples collected on Day -1, 59% on Day 0, 96% on Day 1, 100% on Day 2, 79% on Day 3, 31% on Day 4, 16% on Day 5, and 4% on Day 6. Its presence generally coincided with the period of high flow rate of oviducal fluid which occurs around oestrus. The duration of detectable levels of the oestrus-associated glycoprotein did not vary significantly during the breeding season from a mean (+/- s.d.) of 3.9 +/- 1.0 days. However, the peak flow rate of oviducal fluid dropped from 1.63 +/- 0.50 (early) to 1.38 +/- 0.40 (mid-) and to 0.85 +/- 0.21 ml/day late in the season. Anoestrous ewes (3) induced to ovulate by treatment with progesterone implants and gonadotrophin showed low peak fluid flow rates (0.92 +/- 0.30 ml/day) and the presence of the oestrus-associated glycoprotein for a shorter period (2.7 +/- 0.7 days). Pregnancy (N = 3) did not appear to prolong the production of the protein. The injection of 25 micrograms oestradiol benzoate into 3 anoestrous, 2 mid-cycle and 9 ovariectomized ewes caused an increase in fluid flow rate and appearance of the glycoprotein 1-2 days later. The glycoprotein was present for a longer period in response to the exogenous oestrogen--6.8 +/- 1.6 days in the ovariectomized ewes, 7.9 +/- 1.3 days in anoestrous ewes, and 8.4 +/- 0.8 days in the dioestrous ewes. (ABSTRACT TRUNCATED AT 250 WORDS)
A text watermarking algorithm based on word classification and inter-word space statistics

Text documents can be watermarked by patterning theinter-word spaces. This paper proposes a textwatermarking algorithm that exploits the novel conceptsof word classification and inter-word space statistics. Thewords are classified using some features. Severaladjacent words are grouped into a segment, and thesegments are also classified using the word classinformation. The same amount of information is insertedinto each of the segment classes. The information isencoded by modifying some statistics of inter-word spacesof the segments belonging to the same class. Severaladvantages over the conventional word-shift algorithmsare discussed.
VAXcluster: a closely-coupled distributed system

A VAXcluster is a highly available and extensible configuration of VAX computers that operate as a single system. To achieve performance in a multicomputer environment, a new communications architecture, communications hardware, and distributed software were jointly designed. The software is a distributed version of the VAX/VMS operating system that uses a distributed lock manager to synchronize access to shared resources. The communications hardware includes a 70 megabit per second message-oriented interconnect and an interconnect port that performs communications tasks traditionally handled by software. Performance measurements show this structure to be highly efficient, for example, capable of sending and receiving 3000 messages per second on a VAX-11/780.
Technological Communication Tools in Use - The Shape of Knowledge Shared within Software Development Teams

Knowledge is a strong competitive source for organizations, giving sustainability, and generating long-term success to them. Communication is the basis of the software project since it provides a way to share knowledge among development team members. Technological tool adoption is one of the strategies to improve communication within software development teams and provide the knowledge sharing among its members. Thus, this paper aims to investigate the shape of the knowledge shared by software development teams through technological communication tools (tech-comm-tools). We collected data through a structured questionnaire and face-to-face interviews. The findings point out the team knowledge is shared by mean texts, photos, and videos according to four categories, such as notification, issues, support to clients, and
New insights from a fixed point analysis of single cell IEEE 802.11 WLANs

We study a fixed point formalisation of the well known analysis of Bianchi. We provide a significant simplification and generalisation of the analysis. In this more general framework, the fixed point solution and performance measures resulting from it are studied. Uniqueness of the fixed point is established. Simple and general throughput formulas are provided. It is shown that the throughput of any flow will be bounded by the one with the smallest transmission rate. The aggregate throughput is bounded by the reciprocal of the harmonic mean of the transmission rates. In an asymptotic regime with a large number of nodes, explicit formulas for the collision probability, the aggregate attempt rate and the aggregate throughput are provided. The results from the analysis are compared with ns2 simulations, and also with an exact Markov model of the back-off process. It is shown how the saturated network analysis can be used to obtain TCP transfer throughputs in some cases.
A Dual Pass Video Stabilization System Using Iterative Motion Estimation and Adaptive Motion Smoothing

In this paper, we propose a novel dual pass video stabilization system using iterative motion estimation and adaptive motion smoothing. In the first pass, the transformation matrix to stabilize each frame is returned. The global motion estimation is carried out by a novel iterative method. The intentional motion is estimated using adaptive window smoothing. Before the beginning of the second pass, we obtain the optimal trim size for a specific video based on the statistics of the transformation parameters. In the second pass, the stabilized video is composed according to the optimal trim size. Experimental results show the superior performance of the proposed method in comparison to other existing methods.
EVA: a flexible programming method for evolving systems

The authors' goal is to establish a flexible programming support for evolving systems that will enable one to modify programs using less labor, while maintaining good quality during service life. EVA (evolution mechanism for flexible agent) was developed to allow a flexible programming support system to be constructed based on their programming method for evolving systems. They consider that programming methods for evolving systems need to satisfy the following essential conditions. First, they need to make it easy to specify changes in a system in terms of new requirements. Second, they need to have a procedure for transmitting the new requirements to a program. Third, they need to be able to guarantee that the resultant program will meet the new requirements. Finally, because of the repetitive nature of much evolving systems work, they need to provide for the reuse of similar modifications during programming. In order to overcome limitations in program modification techniques which have only considered programming products, programming processes have been introduced into the method. To achieve their goal, they have formulated programming products and programming processes using such formal techniques as functional programming, type theory, modules, parameterized programming and natural deduction, and have constructed a mechanism of reusing these formal programming processes. The paper explains a case study which shows how to develop an evolving system using EVA and it discusses how one can use EVA's mechanism effectively.
Target Recognition and Tracking based on Data Fusion of Radar and Infrared Image Sensors

Target recognition and tracking is a very important research area in pattern recognition. Systems for target recognition and tracking based on single sensor (radar or infrared image sensor) have their limitations. We present the approaches of target recognition and tracking based on data fusion of radar/infrared image sensors, which can make use of the complement and redundancy of data from different sensors. Data fusion at characteristic level can combine characteristics from different sensors to improve the ability of object recognition. Approaches of target recognition based on inference of rules and a neural classifier are presented to deal with the recognition of dot targets and surface targets. Data fusion at decision level can improve the reliability and anti-interference of object tracking, an approach of object tracking by on decision certainty is presented.
Super Parsing:Sentiment Classification with Review Extraction

This paper describes the sentiment classification with review extraction. Whole process can be illustrated logically as: (1) extract the review expressions on specific subjects and attach sentiment tag and weight to each expression; (2) calculate the sentiment indicator of each tag by accumulating the weights of all the expression with the corresponding tag; (3) given the indicators on different tags, use a classifier to predict the sentiment label of the text. A system approximate text analysis (ATA) is used for review extraction in stage 1. It follows the idea of super parsing, which enables non-adjacent constituents to be merged to deduce a new one. To traverse the valid constituent combinations in super parsing, an algorithm named candidate list algorithm (CLA) is proposed. Then the performance of three kinds of classifiers (a simple linear classifier, SVM and decision tree) in stage 3 is studied. The experiments on on-line documents show that the SVM algorithm achieves the best performance
chlB Requirement for Chlorophyll Biosynthesis under Short Photoperiod in Marchantia polymorpha L.

Chlorophylls (Chls) play pivotal roles in energy absorption and transduction and also in charge separation in reaction centers in all photosynthetic organisms. In Chl biosynthesis steps, only a step for the enzymatic reduction of protochlorophyllide (Pchlide) to chlorophyllide (Chlide) is mediated by both nuclear- and chloroplast-encoded genes in land plants. Many plants encode the genes for light-dependent Pchlide reductase (LPOR) and light-independent Pchlide reductase (DPOR) in the nucleus and chloroplast genome, respectively. During the diversification of land plants, the reduction step of Pchlide to Chlide has become solely dependent on LPOR, and the genes for DPOR have been lost from chloroplast genome. It remains unclear why DPOR persists in some land plants, how they were eliminated from chloroplast genomes during the diversification of land plants, and under what environmental conditions DPOR was required. We demonstrate that DPOR is functional in liverwort (Marchantia polymorpha L.) and plays an important role in Chl biosynthesis. Having established a plastid transformation system in liverwort, we disrupted chlB, which encodes a subunit of DPOR in the M. polymorpha chloroplast genome. Morphological and Chl content analysis of a chlB mutant grown under different photoperiods revealed that DPOR is particularly required for Chl biosynthesis under short-day conditions. Our findings suggest that an environmental condition in the form of photoperiod is an important factor that determines the loss or retention of chloroplast-encoded genes mediating Pchlide reduction to Chlide.
Visualizing second-order tensor fields with hyperstreamlines

A method developed to help scientists visualize 3D tensor data is presented. The method is based on the concept of a hyperstreamline, the simplest continuous tensor structure that can be extracted from a tensor field. Hyperstreamlines for a particular case of symmetric tensor fields are introduced, and a structural depiction of symmetric tensor fields is derived from the representation of many hyperstreamlines. A method for visualizing unsymmetric tensor data by encoding an additional vector field along the trajectory of the hyperstreamlines is discussed. <<ETX>>
Pattern dynamics in a large Fresnel number laser close to threshold

A high Fresnel number laser close to threshold can be set at a detuning value where it displays only the first transverse pattern with zero intensity in its center. However, the availability of a large phase space gives rise to a new type of dynamics. Precisely, for this highly symmetric situation, the intensity pattern undergoes a transition between stable and oscillating superpositions of traveling and standing waves. Such a transition corresponds to the so-called Takens-Bogdanov bifurcation. We report experimental evidence of such a behavior. @S1050-2947~97! 01409-1#
Illegal Migration, Wages, and Remittances: Semi-Parametric Estimation of Illegality Effects

We consider the issue of illegal migration from Mexico to the US, and examine whether the lack of legal status causally impacts on outcomes, specifically wages and remitting behavior. These outcomes are of particular interest given the extent of legal and illegal migration, and the resulting financial flows. We formalize this question and highlight the principal empirical problem using a potential outcome framework with endogenous selection. The selection bias is captured by a control function, which is estimated non-parametrically. The framework for remitting is extended to allow for endogenous regressors (e.g. wages). We propose a new re-parametrisation of the control function, which is linear in case of a normal error structure, and test linearity. Using Mexican Migration project data, we find considerable and robust illegality effects on wages, the penalty being about 12% in the 1980s and 22% in the 1990s. For the latter period, the selection bias is not created by a normal error structure; wrongly imposing normality overestimates the illegality effect on wages by 50%, while wrongly ignoring selection leads to a 50% underestimate. In contrast to these wage penalties, legal status appears to have mixed effects on remitting behavior.
Efficient flow-sensitive interprocedural computation of pointer-induced aliases and side effects

We present practical approximation methods for computing interprocedural aliases and side effects for a program written in a language that includes pointers, reference parameters and recursion. We present the following results: 1) An algorithm for flow-sensitive interprocedural alias analysis which is more precise and efficient than the best interprocedural method known. 2) An extension of traditional flow-insensitive alias analysis which accommodates pointers and provides a framework for a family of algorithms which trade off precision for efficiency. 3) An algorithm which correctly computes side effects in the presence of pointers. Pointers cannot be correctly handled by conventional methods for side effect analysis. 4) An alias naming technique which handles dynamically allocated objects and guarantees the correctness of data-flow analysis. 5) A compact representation based on transitive reduction which does not result in a loss of precision and improves precision in some case. 6) A method for intraprocedural alias analysis which is based on a sparse representation.
The effect of windstress change on future sea level change in the Southern Ocean

AOGCMs of the two latest phases (CMIP3 and CMIP5) of the Coupled Model Intercomparison Project, like earlier AOGCMs, predict large regional variations in future sea level change. The model‐mean pattern of change in CMIP3 and CMIP5 is very similar, and its most prominent feature is a zonal dipole in the Southern Ocean: sea level rise is larger than the global mean north of 50°S and smaller than the global mean south of 50°S in most models. The individual models show widely varying patterns, although the inter‐model spread in local sea level change is smaller in CMIP5 than in CMIP3. Here we investigate whether changes in windstress can explain the different patterns of projected sea level change, especially the Southern Ocean feature, using two AOGCMs forced by the changes in windstress from the CMIP3 and CMIP5 AOGCMs. We show that the strengthening and poleward shift of westerly windstress accounts for the most of the large spread among models in magnitude of this feature. In the Indian, North Pacific and Arctic Oceans, the windstress change is influential, but does not completely account for the projected sea level change.
Model Predictive Control Applied to an Improved Five-Level Bidirectional Converter

This paper presents an improved five-level bidirectional converter (iFBC) controlled by finite control set model predictive control (FCS-MPC). This control strategy consists in using the discrete time nature of the iFBC to define its state in each sampling interval. Using FCS-MPC the switching frequency is not constant; however, it is suitable to follow the current reference with low total harmonic distortion (THD). The iFBC prototype that was specially developed for obtaining experimental results is described in detail along the paper, as well as its principle of operation, power theory, and current control strategy. The iFBC was experimentally validated connected to the power grid through a second-order LfCf passive filter operating as an active rectifier and as a grid tie inverter. For both operation modes, the experimental results confirm the good performance (in terms of efficiency, low current THD, and controlled output voltage) of the iFBC controlled by FCS-MPC.
Maternal Early Pregnancy Serum Metabolites and Risk of Gestational Diabetes Mellitus.

CONTEXT Significant gaps remain in the understanding of genetic and environmental risk factors, as well as related mechanisms that contribute to gestational diabetes mellitus (GDM). OBJECTIVES This study aimed to investigate early pregnancy maternal serum metabolites and subsequent risk of GDM. DESIGN Information on participant characteristics and GDM diagnosis was collected using in-person interviews and medical record abstraction, respectively. Early pregnancy serum samples were used for nontargeted metabolite profiling using a gas chromatography-mass spectrometry platform. Lasso regression was used to select a set of metabolites that are jointly associated with GDM case-control status. We evaluated the predictive performance of the set of selected metabolites using a receiver operating characteristics curve and area under the curve. PARTICIPANTS A total of 178 GDM cases and 180 controls participated in a pregnancy cohort study. RESULTS A set of 17 metabolites (linoleic acid, oleic acid, myristic acid, d-galactose, d-sorbitol, o-phosphocolamine, l-alanine, l-valine, 5-hydroxy-l-tryptophan, l-serine, sarcosine, l-pyroglutamic acid, l-mimosine, l-lactic acid, glycolic acid, fumaric acid, and urea) differentiated GDM cases from controls. Fold changes of relative abundance of these metabolites among GDM cases compared with controls ranged from 1.47 (linoleic acid) to 0.78 (5-hydroxy-l-tryptophan). Addition of these selected metabolites to a set of well-known GDM risk factors improved the area under the curve significantly from 0.71 to 0.87 (P = 3.97E-07). CONCLUSIONS We identified combinations of metabolites in early pregnancy that are associated with subsequent risk of GDM. Replication of findings may improve understanding of GDM pathogenesis and may have implications for the design of GDM prevention and early diagnosis protocols.