Miracle-dz/UniFAR-FTUs huggingface dataset:
Web Information Retrieval: Towards Social Information Search Assistants

Searching for information is commonly an individual task which aims at solving any information need. To do that, one may go to a library, or go surfing the Web in order to find relevant information. Indeed, due to the large amount of available documents, the Web has become a favorite information source for solving daily information needs. An issue remains: the Web is in perpetual evolution; so the problem is less the existence of relevant information rather than the way users find it. One may compare searching for information on the Web with “looking for a needle in a haystack. ” Thus, searching the Web suffers from many limits that can be reduced by using a search assistant. Such an assistant helps the user to find relevant information on the Web. At the beginning, those assistants were principally helping each user individually. Nowadays, we are witnessing the rise of social approaches in such systems. Those latter systems help users to find relevant information by using other users’ experience, shared information. Therefore, each user is helped thanks to the mass crowd. This chapter underlines this search assistants evolution, it is organized as follows: section 1 introduces the underlying concepts and limits of traditional information search process and its application to the Web. Section 2 explains the search assistant concept by detailing their evolution from individual to social approaches. Sections 3 up to 5 present current approaches that search assistants may use to help any user to query and browse the Web as well as to improve search-related activities. To conclude, future trends for Web information assistants are discussed.
Property Taxation and the Economy after the Barker Review

This paper analyses the roles of property and land values in the UK economy and considers property tax reform with the objectives of improving macro-economic stability, resource allocation, economic inequality and the environment. With UK house prices at all-time peaks relative to incomes, concerns about affordability and the distributional consequences have increased. The Barker Review for the UK Treasury of new housing supply reported in 2004 and recommended extensive reforms of the land use planning system, as well as various other reforms, including new development taxes. This paper argues that these taxes are unwise compared to the property tax reforms proposed here.
Homeownership and Local Voting in Disadvantaged Urban Neighborhoods

Homeownership has long been considered the cornerstone of the American dream, and considerable research has pointed to the social benefits of homeownership for both families and communities. Yet research concerning this link between homeownership and social participation has recently undergone critique for failing to consider neighborhood context. Do homeowners in disadvantaged urban neighborhoods become active participants in neighborhood improvement, or do they feel stuck in undesirable neighborhoods where they perceive little potential for change? The research addresses endogeneity concerns and shows that, when compared to renters, homeowners are more likely to have voted in recent local elections. Neighborhood context does moderate these relationships, with homeowners in disadvantaged neighborhoods being more likely to vote than owners in other areas. These findings suggest that, despite potential household-level costs associated with owning a home in a disadvantaged urban area, responsible homeownership in such areas promotes local political involvement among lower-income residents.
Programme Heterogeneity and Propensity Score Matching: An Application to the Evaluation of Active Labour Market Policies

This paper investigates the question whether it really matters for microeconometric evaluation studies to take account of the fact that the programmes under consideration are heterogeneous. Assuming that selection into the different sub-programmes and the potential outcomes are independent given observable characteristics, estimators based on different propensity scores are compared and applied to the analysis of the active labour market policy in a Swiss region. Furthermore, the issues of heterogeneous effects and aggregation are addressed. The econometric considerations as well as the results of the application suggest that an approach that incorporates the possibility of having multiple programmes could be an important tool in applied work.
A fast non‐negativity‐constrained least squares algorithm

In this paper a modification of the standard algorithm for non‐negativity‐constrained linear least squares regression is proposed. The algorithm is specifically designed for use in multiway decomposition methods such as PARAFAC and N‐mode principal component analysis. In those methods the typical situation is that there is a high ratio between the numbers of objects and variables in the regression problems solved. Furthermore, very similar regression problems are solved many times during the iterative procedures used. The algorithm proposed is based on the de facto standard algorithm NNLS by Lawson and Hanson, but modified to take advantage of the special characteristics of iterative algorithms involving repeated use of non‐negativity constraints. The principle behind the NNLS algorithm is described in detail and a comparison is made between this standard algorithm and the new algorithm called FNNLS (fast NNLS). © 1997 John Wiley & Sons, Ltd.
EXCESSIVE DAYTIME SLEEPINESS AMONG TURKISH PUBLIC TRANSPORTATION DRIVERS : A RISK FOR ROAD TRAFFIC ACCIDENTS ?

Aims: This study evaluated the prevalence of, and the risk factors for, obstructive sleep apnoea syndrome (OSAS) and excessive day time sleepiness (EDS) as well as its relation to road traffic accidents (RTA) among Turkish public transportation drivers. Materials and methods: Male public transportation drivers (618) from the largest public transportation corporation (IETT) in Turkey were analysed after responding to questionnaires about their demographics, traffic accident histories, sleep habits, excessive daytime sleepiness (Epworth), and the likelihood of having apnoea (STOP-BANG). We also measured anthropometric data for all of the drivers. Frequency, mean, Chi-square, student T-test and regression analyses were used in statistical analyses. Results: Six hundred and eighteen male public transportation bus drivers with mean age (years) of 43.08 ± 5.41 and with mean BMI (kg/m2) 29.01 ± 3.92 were recruited. There was a positive and significant relation between age and BMI with obstructive sleep apnoea (OSA) (p= 0.000). OSA risk was high in 442 (71.5 %) drivers and 297 (48.1 %) had EDS. There was a positive relationship between OSA risk and the risk of EDS (p = 0.000). Five hundred and thirtyone (86.6 %) drivers had a past history of RTA but there was no significant relationship between a past RTA and OSA risk (p = 0.06). However, there was a statistically significant difference in the risk of EDS (ESS ≥10) in those with past history of RTA compared to those without (p = 0.000). The independent determinants of excessive day time sleepiness were the OSA risk and the abdominal adiposity (p < 0.001). Conclusion: In conclusion, we found a high prevalence of OSAS in the largest city transportation company in Turkey. Our results further suggest that age and BMI increase the risk of developing obstructive sleep apnoea syndrome (OSAS). We confirm a high incidence of falling asleep while driving and a high rate of road traffic accidents in OSAS patients.
II . New 3 D − 1 D corrected abundances from a VLT / UVES spectrum 1

We present a new abundance analysis of HE 1327−2326, the currently most iron-poor star, based on observational data obtained with VLT/UVES. We correct the 1D LTE abundances for 3D effects to provide an abundance pattern that supersedes previous works, and should be used to observationally test current models of the chemical yields of the first-generation SNe. Apart from confirming the 1D LTE abundances found in previous studies before accounting for 3D effects, we make use of a novel technique to apply the 3D−1D corrections for CNO which are a function of excitation potential and line strength for the molecular lines that comprise the observable CH, NH, and OH features. We find that the fit to the NH band at 3360 Å is greatly improved due to the application of the 3D−1D corrections. This may indicate that 3D effects are actually observable in this star. We also report the first detection of several weak Ni lines. The cosmologically important element Li is still not detected; the new Li upper limit is extremely low, A(Li) < 0.62, and in stark contrast with results not only from Based on observations collected at the European Southern Observatory, Paranal, Chile (Proposal ID 075.D-0048). McDonald Observatory, The University of Texas at Austin, 1 University Station, C1400, Austin, TX 78712-0259; anna@astro.as. utexas.edu Max-Planck-Institut für Astrophysik, Karl-Schwarzschild-Str. 1, Postfach 1317, D−85741 Garching b. München, Germany Department of Astronomy and Space Physics, Uppsala University, Box 515, SE-751-20 Uppsala, Sweden; norbert@astro.uu. se National Astronomical Observatory of Japan, 2-1-21 Osawa, Mitaka, Tokyo, 181-8588 Japan Department of Astronomical Science, The Graduate University of Advanced Studies, Mitaka, Tokyo, 181-8588 Japan
Sampling Analysis in Weighted Fractional Fourier Transform Domain

We propose a new method for analysis of the sampling and reconstruction conditions of signals by use of the weighted fractional Fourier transform (WFRFT). It is shown that the WFRFT domain may provide a novel understanding of sampling process. The proposed sampling theorem generalizes classical Shannon sampling theorem and Fourier series expansion, and provides a full-reconstruction procedure of certain signals that are not band-limited in the traditional Fourier sense. An orthogonal sampling basis for the class of band-limited signals in the sense of WFRFT is also given. Experimental results are proposed to verify the accuracy and effectiveness of the obtained results.
Performance analysis of passive UHF RFID tags with GNU-radio

Performance evaluation of passive Radio Frequency Identification (RFID) tags is a crucial but challenging task. In fact, tag performance depends on multiple factors like the goodness of the conjugate matching between chip and antenna, the chip sensitivity, and the strength and quality of backscattered signal. Moreover, passive RFID tags lack wired connectors and therefore cannot be directly interfaced with conventional measurement instruments. Some solutions for tag testing and performance evaluation are commercially available on the market, but they are expensive and not totally flexible. In this work we propose a novel approach to the problem of tag performance analysis based on Software-Defined Radio (SDR). We show that a SDR tool for UHF RFID reading allows the characterization of tag performance by any metric and for any operating frequency, with a total equipment cost below 1000 USD. We present the methodology to measure tag sensitivity, differential radar cross-section and Signal-to-Noise ratio, and provide numerical results for five different tags.
The EE-method, an evolutionary engineering developer tool: neural net character mapping

Summary form only given. Evolutionary engineering (EE) challenge is to prove that it is possible to build systems (i.e. solutions) without going through any design process. Evolutionary engineering is defined to be "the art of using evolutionary algorithms approach such as genetic algorithms to build complex systems". Our main goal is to show that the EE-method is a good setting. In this paper, we show step by step, using the EE-method, how to build a neural net based system. The EE-method can be viewed as just a GP appliance. The need of a well-specified approach determines the necessity for such method. Also, to improve the effectiveness of the evolvability principle on a complex systems, we present in this paper a more complex example: an evolved neural net pattern recognizer that maps an input character image to a standard representation i.e. image or code . This application needs a recurrent neural net of 105 neurons, so the weights table contains 11025 entries, the evolution process has to tune 11025 parameters. The search space is: 2/sup 11025*7/ where 7 is the weight binary code. This task is hyper complex. The results show that the evolvability principle is effective.
DC motor drive with high torque at low speeds

DC drives are still very important especially for low voltages and low power (e.g. in cars and robots). In this paper a converter is analyzed which makes it possible to control the voltage across the machine (and therefore the speed) from zero to input voltage with a quadratic dependence of the duty cycle. This enables high torque at low speeds with better efficiency. The circuit is explained, the model of the drive, the design of the devices, and some experimental results are given.
Deliverable 2 . 1 Mixed Reality Dance Performance

This report contains a description of the work done in MIRALab, University of Geneva, and LIG, EPF Lausanne, concerning the simulation of virtual dancers and body gesture recognition for the interaction avatar-autonomous. It summarizes the different steps needed to create and animate bodies in a virtual environment. Document ID eRENA-D2.1 Type Deliverable report with video material on eRENA tape Status Final Version 1.0 Date May, 1998. Authors Stéphane Carion, Pierre Beylot, Nadia MagnenatThalmann, (MIRALAB,Univ. of Geneva); Luc Emering, Soraia Raupp Musse, Daniel Thalmann (LIG, EPF Lausanne) Task 2.1. & 2.2 eRENA-D2.1 Mixed Reality Dance Performance May 1998 1 ESPRIT Project 25379 DELIVERABLE 2.1 Mixed Reality Dance Performance
A Personalized Recommender Integrating Item-Based and User-Based Collaborative Filtering

Recommender systems employ prediction algorithms to provide users with items that match their interests. The collaborative filtering (CF) is the most popular system and the two of the most famous techniques in CF are the user-based CF (UBCF) and item-based CF (IBCF). Nevertheless each of them takes only one-directional information from the user-item ratings matrix to generate recommendations. In other words, the UBCF utilizes user similarities and the IBCF tries to make a prediction by utilizing item similarities. It means that methods may use only half of the total information from the given data set. For completing the missing part of usable information, this paper proposes a CF algorithm integrating the UBCF and IBCF, which takes both vertical and horizontal information in the user-item matrix. It produces perdition using IBCF to form a dense user-item matrix and then recommends using UBCF based on the dense matrix. The experimental results on MovieLens dataset show that the proposed algorithm outperformed in terms of prediction accuracy and robustness to data sparseness.
A Comparison of Machine Learning Classifiers Applied to Financial Datasets

*Abstract—The main purpose of this project is to analyze several Machine Learning techniques individually and compare the efficiency and classification accuracy of those techniques. Three algorithms are used (Naïve Bayes learning, feed forward Artificial Neural Networks with Backpropagation, and Decision Trees learning using C4.5) over two datasets (“European companies” and “Japanese companies”) characterized by 59 financial features each.
Dynorphin Promotes Abnormal Pain and Spinal Opioid Antinociceptive Tolerance

The nonopioid actions of spinal dynorphin may promote aspects of abnormal pain after nerve injury. Mechanistic similarities have been suggested between opioid tolerance and neuropathic pain. Here, the hypothesis that spinal dynorphin might mediate effects of sustained spinal opioids was explored. Possible abnormal pain and spinal antinociceptive tolerance were evaluated after intrathecal administration of [d-Ala2,N-Me-Phe4, Gly-ol5]enkephalin (DAMGO), an opioid μ agonist. Rats infused with DAMGO, but not saline, demonstrated tactile allodynia and thermal hyperalgesia of the hindpaws (during the DAMGO infusion) and a decrease in antinociceptive potency and efficacy of spinal opioids (tolerance), signs also characteristic of nerve injury. Spinal DAMGO elicited an increase in lumbar dynorphin content and a decrease in the μ receptor immunoreactivity in the spinal dorsal horn, signs also seen in the postnerve-injury state. Intrathecal administration of dynorphin A(1–17) antiserum blocked tactile allodynia and reversed thermal hyperalgesia to above baseline levels (i.e., antinociception). Spinal dynorphin antiserum, but not control serum, also reestablished the antinociceptive potency and efficacy of spinal morphine. Neither dynorphin antiserum nor control serum administration altered baseline non-noxious or noxious thresholds or affected the intrathecal morphine antinociceptive response in saline-infused rats. These data suggest that spinal dynorphin promotes abnormal pain and acts to reduce the antinociceptive efficacy of spinal opioids (i.e., tolerance). The data also identify a possible mechanism for previously unexplained clinical observations and offer a novel approach for the development of strategies that could improve the long-term use of opioids for pain.
Motion Planning for Autonomous Vehicle Based on Radial Basis Function Neural Network in Unstructured Environment

The autonomous vehicle is an automated system equipped with features like environment perception, decision-making, motion planning, and control and execution technology. Navigating in an unstructured and complex environment is a huge challenge for autonomous vehicles, due to the irregular shape of road, the requirement of real-time planning, and the nonholonomic constraints of vehicle. This paper presents a motion planning method, based on the Radial Basis Function (RBF) neural network, to guide the autonomous vehicle in unstructured environments. The proposed algorithm extracts the drivable region from the perception grid map based on the global path, which is available in the road network. The sample points are randomly selected in the drivable region, and a gradient descent method is used to train the RBF network. The parameters of the motion-planning algorithm are verified through the simulation and experiment. It is observed that the proposed approach produces a flexible, smooth, and safe path that can fit any road shape. The method is implemented on autonomous vehicle and verified against many outdoor scenes; furthermore, a comparison of proposed method with the existing well-known Rapidly-exploring Random Tree (RRT) method is presented. The experimental results show that the proposed method is highly effective in planning the vehicle path and offers better motion quality.
Union Decline in Britain

This paper considers the rapid decline in unionization that has occurred in Britain since the late 1970s. The overwhelming factor underpinning falling unionization was a failure to organize new establishments set up in the last twenty years or so, thus confirming that developments since 1990 represent a continuation of the pattern revealed in earlier work for the 1980–90 period. The sharpest falls in unionization occurred in private manufacturing establishments set up after 1980. Finally, there is some evidence that it is age of workplace, rather than age of worker, that is the critical age-based factor behind union decline.
Repositories of Community Memory as Visualized Activities in 3D Virtual Worlds

In this paper, we propose that visualized activities and experiences created in 3D virtual worlds may provide a new type of learning community memory. We explore how such activities and experience can be captured, crystallized, and reused with this technology in three prototypes designed on two platforms. This approach can support learning communities by addressing the common challenge of acquiring and communicating tacit knowledge that resides in practices and relations developed by the participants. Based on our experiences, we discuss the possibilities and challenges for creating and using repositories of community memory as visualized activities in 3D virtual worlds, outlining a framework for capturing, visualizing, and accessing such activities. The results of our exploration demonstrated that repositories of the 'fluid' community knowledge might be in fact created and used. At the same time, more extensive evaluation and further research are required for developing the approach suggested.
"Group Inversion Approach" for Detection of Soil Moisture Temporal-Invariant Locations

This paper presents an approach denominated Group Inversion Approach (GIA) which aims at detecting soil moisture temporal invariants, i.e., the stable temporal soil moisture locations, by using mainly remotely sensed data. The soil moisture temporal invariants are those locations where independently of the absolute value changes, the relative spatial distribution of soil moisture remains almost constant. In this procedure, the soil moisture values estimated from different inversion approaches and sensor configurations are compared among themselves and with the ground data. The procedure has been tested in a watershed of around 7,000 km2 with data collected during the SMEX’02 experiment in Iowa (USA). The results indicate that fields with inversion errors lower than five times the soil moisture variability detected with ground measurements represent well the mean watershed soil moisture values. The GIA technique has been also found in good agreement with the classical technique used to detect the stable soil moisture features, based exclusively on ground measurements.
Identification, Cloning, and Initial Characterization of a Novel Mouse Testicular Germ Cell-Specific Antigen1

Abstract A monoclonal antibody, designated TES101, was raised by immunizing BALB/c mice with an allogenic mouse testicular homogenate followed by immunohistochemical selection as the initial screening method. By searching the expressed sequence tag (EST) database with the N-terminal amino acid sequence of TES101 reactive protein, we found that the predicted amino acid sequence encoded by a mouse testicular EST clone matched the TES101 protein sequence. Sequence analysis of the clone revealed no homologous molecule in the DNA/protein database. Based on data obtained from N-terminal amino acid analysis of the TES101 protein, the derived amino acid sequence contained a signal peptide region of 25 amino acids and a mature protein region of 225 amino acids, which translated into a protein with a molecular weight of 24 093. Northern blot analysis showed that mRNA of the TES101 protein was found in testis but not in any other mouse tissues examined. Western blot analysis revealed that TES101 reacted with a 38-kDa band on SDS-PAGE under nonreducing conditions, and this reactivity was abrogated under reducing conditions. Immunoelectron microscopic studies demonstrated that the molecule was predominantly located on the plasma membrane of spermatocytes and spermatids but not in Sertoli cells or interstitial cells, including Leydig cells. Thus, the TES101 protein is a novel molecule present primarily on the surface of developing male germ cells. TES101 protein may play a role in the processes underlying male germ cell formation.