Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of carbon grains in the deuteration of H{2}

Aims. The production of molecular hydrogen and its deuterated forms onto carbonaceous dust grains is investigated in detail. The goal of this study is to estimate the importance of the chemistry occuring on grain surfaces for the deuteration of H(2). Furthermore, we aim to find a robust and general surface chemical model that can be used in different astrophysical environments. Methods. Surface processes are described for the cases of graphitic and amorphous-carbon grains, where laboratory work is available. Langmuir-Hinshelwood, as well as Eley-Rideal surface chemistries are included in the model and their relative contributions highlighted. Analytic expressions are derived for H(2), HD, and D(2) formation efficiencies for both types of grains. Rate equations are tested against stochastic methods. Results. As expected, rate equations and stochastic methods diverge for grain sizes below a critical value a(crit). For these sizes, D(2) formation decreases to favour HD formation. The formation efficiencies of H(2) and D(2) can be calculated by adding a correction factor to the rate equations methods ( this factor is a simple exponential factor that becomes unity when a > a(crit)). We find that, because of the presence of chemisorbed sites, which can store atoms to form molecules up to high grain temperatures, the formation efficiency of HD and D(2) is very high compared to models where only physisorption sites are taken into account. When considering a realistic distribution of dust grains, we find that the formation rates of H(2) and HD are enhanced by an order of magnitude if small grains are taken into account. The formation of D(2), on the other hand, comes from the contribution of small (
Lyon's auditory features and MRAM features comparison for non-intrusive speech quality assessment in narrowband speech

Lyon's auditory features and Multi-Resolution Auditory Model (MRAM) features for narrowband speech sampled at 8 kHz for different degradations are computed. The Gaussian Mixture Model (GMM) has been used to map these auditory features of narrowband speech into the objective mean opinion score (MOS) using Expectation Maximization (EM) algorithm. Non-intrusive speech quality assessment has been done using Lyon's auditory features and MRAM features and their efficacy has been compared in terms of the correlation coefficients between the subjective MOS and the computed objective MOS. The results in terms of root mean square error (RMSE) between the subjective MOS and the computed objective MOS are computed and compared. The results in terms of the correlation coefficients are also compared with ITU-T Recommendation P.563, a standard for non-intrusive speech quality assessment, on ITU-T supplement-23, NOIZEUS-960 and NOIZEUS-2240 databases.
Fast and robust vehicle positioning on graph-based representation of drivable maps

In this paper, we propose a car positioning approach that does not rely on GPS. We propose to use car wheel speeds and road maps in order to achieve robust positioning of the vehicle. The vehicle positioning is achieved by applying particle filtering on a graph-based representation of a road map. We show that the vehicle positioning is feasible and robust with these two inputs at a really low computational cost. We achieve car positioning with an averaged 5 m accuracy within a 100 km drivable road map on a 12 km sequence.
User Perspectives on Tabletop Therapy

Technology-based activities are becoming more popular in therapy programs, and direct-touch interactive tabletops seem particularly suited to many therapy tasks. To better understand the potential benefit of interactive tabletops in rehabilitation, we examined users’ attitudes as they performed rehabilitation activities on a multi-touch tabletop and a normal, non-interactive surface. This revealed the elements of multi-touch tabletops and their associated activities that contribute to their success in rehabilitation programs and identify improvements for future designs. We found that although the engaging and dynamic nature of the interactive tasks was preferred, many participants were heavily influenced by prior exposure to commercial interaction devices and expected very precise and responsive sensing. We discuss the implications of user expectations and experiences on the design of future activities and rehabilitation technologies.
Development and Verification of Iterative Decoder for LDPC-RS Product Codes

LDPC codes provide good random error performance nearer to Shannon limit. The LDPC codes have some residue errors which cannot be corrected even after large number of iterations such errors can be corrected by concatenating LDPC codes with RS codes. This paper describes the development of an iterative decoder scheme for LDPC-RS product codes which made LDPC codes and Turbo codes popular. The iterative structure consists of a soft decision decoding of LDPC codes and hard decision decoding of RS codes. The concatenated scheme provides higher performance than the iterative decoder for LDPC codes. The iterative scheme is developed in MATLAB and FPGA kit is used for practical verification.
D-optimal Bayesian Interrogation for Parameter and Noise Identification of Recurrent Neural Networks

We introduce a novel online Bayesian method for the identification of a family of noisy recurrent neural networks (RNNs). We develop Bayesian active learning technique in order to optimize the interrogating stimuli given past experiences. In particular, we consider the unknown parameters as stochastic variables and use the D-optimality principle, also known as `\emph{infomax method}', to choose optimal stimuli. We apply a greedy technique to maximize the information gain concerning network parameters at each time step. We also derive the D-optimal estimation of the additive noise that perturbs the dynamical system of the RNN. Our analytical results are approximation-free. The analytic derivation gives rise to attractive quadratic update rules.
Process for diagnosis method selection of Flight Critical Systems

The purpose of our work presented in this paper is to propose a design process to make easier the implementation of diagnosis functions in order to improve Sensor Acquisition System efficiency into Flight Critical Systems. This process aims to evaluate the different existing diagnosis methods considering application needs and aerospace requirements and constraints. As a result, it enables to guide designers in the determination of the Sensor Acquisition System architecture including diagnosis functions.
Lexical priming in fluent and with developmental stuttering children.

PURPOSE To examine the possible relationship between lexical variables (categorization and naming) and developmental stuttering. METHODS Thirty Brazilian Portuguese speaking children with ages ranging from 7 to 9 years and 11 months participated in the study. We applied a lexical priming paradigm to experimentally investigate whether children with developmental stuttering (Research Group) differed from their fluent peers (Control Group), with respect to reaction time in three conditions - control (without prime); semantically related prime, and semantically independent prime - of two experimental tasks: categorization and naming of the target stimulus. RESULTS No difference between groups was observed in reaction time on the categorization task. However, there was a condition effect showing that, for both groups, reaction time was shorter in the semantically related prime condition when compared to the no prime condition. In the naming task, a between-group difference was observed in reaction time, indicating a longer reaction time in the Research Group than the Control Group. There was no condition effect on naming, i.e. the Research Group showed slower reaction time regardless of prime type. CONCLUSIONS The results confirm the hypothesis that, in children with developmental stuttering, readiness in motor programming of speech is slowed when compared to fluent children. There is no difference between groups when the lexical function does not require speech readiness.
Mobile Search Engine Personalization Enhanced with Recommendation System with an Impact of Affect Analysis

As the amount of web information grows rapidly, we propose a personalized search engine with an affect analysis. In this paper, we propose a new web search personalization which recommends the user with the additional information about the content they searched. It gives the user knowledge about the content which they never knew. The user preferences are organized in ontology based, multifacet user profiles, which are used to adapt a personalized ranking function for rank adaptation of future results. To recommend the users with additional information we have to analyse the other user’s click through data. Based on the client - server model, we also present a detailed architecture and design for implementation of personalized mobile search engine with an impact of affect analysis. We prototype PMSE on the google android platform. Experimental results show that PMSE significantly improves the precision comparing to the baseline.
THE IMPACT OF THE 1990S ECONOMIC BOOM ON LESS-EDUCATED WORKERS IN RURAL AMERICA: DID THE RISING TIDE LIFT ALL BOATS?

We use national longitudinal survey data (NLSY79) to investigate the impact of local labor market conditions on the employment and earnings of rural non-college-educated workers. Results suggest that local economic conditions in the late 1990s did have a positive impact on wages, and the effect is larger for workers with no more than a high school degree compared to their college-educated counterparts. We find little evidence of a difference between rural and urban impacts, suggesting that the 1990s boom helped both rural and urban less-educated workers. These results suggest that an expanding economy continues to be a powerful anti-poverty force.
Asset Rich, But Income Poor: Australian Housing Wealth and Retirement in an International Context

This paper examines patterns of housing wealth among the aged in Australia over time and compares Australian housing wealth patterns with those in North America and Western Europe, to determine if the Australian elderly hold particularly high levels of housing wealth, and if this leads to a relative overconsumption of housing. The paper uses data from the three most recent Australian Bureau of Statistics (ABS) Household Expenditure Surveys (1993-94, 1998-99 and 2003-04).
Risk and Return Trade-Offs in Partnering Strategies between Co-ops and IOFs

ABSTRACT Changes in grain handling technologies and favorable terms on rail services are encouraging construction of state of the art grain handling facilities. Given these are high fixed and low marginal cost operations that are becoming increasingly vertically interdependent, the investments have substantial risks and opportunities. Partnerships are being formed to capitalize construction of fixed assets, provide a means to share specialized services, or to facilitate acquisitions or mergers. Given the mixture of corporate structures in this industry, including investor owned (IOF) and cooperatives, partnership agreement terms must accommodate the interest of a variety of stakeholder types. The purpose of this paper is to develop a financial model to evaluate classes of these partnerships and then compare distributions of risk and returns to each partner. A stochastic simulation model, specified as being highly representative of some contemporary partnerships, was developed for these purposes. Alternative partnership terms are specified and evaluated.
Estimating Implied Valuation Parameters: Extension and Application to Ground Lease Rentals

A problem that often arises in applied finance is one where decision-makers need to choose a value for some parameter that will affect the cash flows between two parties such as a rental rate or an exercise price. Because the values of the cash flows also depend on various unobservable parameters identifying the value of the policy parameter that achieves the desired allocation between the parties is no simple task often resulting in disputes and the invocation of ad-hoc approaches. We show how this problem can be solved using an extension of the well-known 'implied volatility' technique from option pricing and apply it to the determination of equilibrium rental rates on ground leases of commercial land.
Active and fast particle driven Alfven eigenmodes in Alcator C-Mod

Alfven eigenmodes sAEsd are studied to assess their stability in high density reactor relevant regimes where Ti < Te and as a diagnostic tool. Stable AEs are excited with active magnetohydrodynamics antennas in the range of the expected AE frequency. Toroidal Alfven eigenmode sTAEd damping rates between 0.5%, g / v , 4.5% have been observed in diverted and limited Ohmic plasmas. Unstable AEs are excited with a fast ion tail driven by H minority ion cyclotron radio frequency sICRFd heating with electron densities in the range of ne = 0.5‐2 3 10 20 m ˛3 . Energetic particle modes or TAEs have been observed to decrease in frequency and mode number with time up to a large sawtooth collapse, indicating the role fast particles play in stabilizing sawteeth. In the current rise phase, unstable modes with frequencies that increase rapidly with time are observed with magnetic pick-up coils at the wall and phase contrast imaging density fluctuation measurements in the core. Modeling of these modes constrains the calculated safety factor profile to be very flat or with slightly reversed shear. AEs are found to be more stable for an inboard than for central or outboard ICRF resonances in qualitative agreement with modeling. © 2005 American Institute of Physics . fDOI: 10.1063/1.1865012g
net Real Time Facial Expression Analysis Using PCA

Face recognition has been very important issue in computer vision and pattern recognition over the last several decades. One difficulty in face recognition is how to handle the variations in the expression, pose and illumination when only a limited number of training samples are available. In this project, we performed Real Time Facial Expression Analysis Using PCA. Initially the Eigen space was created with Eigen values and eigenvectors. From this space, the Eigen faces are constructed, and the most relevant Eigen faces have been selected using Principal Component Analysis (PCA). With these Eigen faces the input test images are classified based on Facial Expression Classifier. The proposed method was carried out by taking the picture database. The database was obtained with 10 photographs of each person at different expressions. These expressions can be classified into some discrete classes like happy, anger, disgust, sad and neutral. Absence of any expression is the “neutral” expression. There are 30 persons in database. The database is kept in the train folder which contains each person having all his/her photographs.
Direct Detection of Galactic Halo Dark Matter

The Milky Way galaxy contains a large, spherical component which is believed to harbor a substantial amount of unseen matter. Recent observations indirectly suggest that as much as half of this “dark matter” may be in the form of old, very cool white dwarfs, the remnants of an ancient population of stars as old as the galaxy itself. We conducted a survey to find faint, cool white dwarfs with large space velocities, indicative of their membership in the galaxy's spherical halo component. The survey reveals a substantial, directly observed population of old white dwarfs, too faint to be seen in previous surveys. This newly discovered population accounts for at least 2 percent of the halo dark matter. It provides a natural explanation for the indirect observations, and represents a direct detection of galactic halo dark matter.
Public Transport: Making the Right Mobility Choices

Most cities recognize the need to provide a public transportation system. However, choosing which mode or modes to offer can be challenging. This article highlights some of the factors to be considered when choosing the optimal mode for a particular location. These factors include: capacity; costs; space and urban integration; customer expectations of quality and comfort; environmental impact; political timing factors; legacy systems; and knowledge availability. Each mode has its own merits and areas of relevance. Each city or region also has its own priorities and characteristics, so that no universal solution can meet the needs of every area. Therefore, selecting a mode requires a complex multidisciplinary analysis and a frank assessment of what that region values and needs in the short, medium and long terms.
FABS: file and block surveillance system for determining anomalous disk accesses

Despite increasingly sophisticated security measures, attackers have continued to find ways to gain access to stored data with impacts including data disclosure, modification, or deletion. There currently exist no tools independent of the operating system to monitor storage status. The authors introduced FABS as a comprehensive tool to monitor storage for anomalous accesses. A scalable GUI prototype, VisFlowConnect-SS, which represents storage accesses visually to human operators, was also introduced. The goal is an integrated storage-based monitoring system that provides intrusion detection, minimizes attack damage, and assists with post-attack forensic analysis.
The Quantum way of Cloud Computing

Quantum Computing and Cloud Computing are the technologies which have the capability to shape the future of computing. Quantum computing focuses on creating super-fast computers using the concepts of quantum physics whereas Cloud computing allows the computing power to be provided as a service. This paper presents a theoretical approach towards the possibility of a Quantum-Cloud i.e. quantum computing as a service. This will combine the fields of quantum computing and cloud computing, resulting into an evolutionary technology. Also, this paper discusses the possible advantages of this in the near future.
Using a Dynamic Schedule to Increase the Performance of Tiling in Stencil Computations

A stencil computation determines the values of points in a grid of some dimensionality by repeatedly evaluating a given function of a grid point and its neighbors. The parallelization and optimization of stencil computations are subject of ongoing research. The most prevalent approach is the subdivision of the iteration domain into smaller pieces, called tiles. We give an overview of a method to increase the performance of one such tiling algorithm further by employing a dynamic schedule for tile processing, improving both load balance and cache efficiency. A set of onedimensional stencil benchmarks exhibits a performance increase of up to 20% in comparison to the Pochoir stencil compiler.
HippogriffDB: Balancing I/O and GPU Bandwidth in Big Data Analytics

As data sets grow and conventional processor performance scaling slows, data analytics move towards heterogeneous architectures that incorporate hardware accelerators (notably GPUs) to continue scaling performance. However, existing GPU-based databases fail to deal with big data applications efficiently: their execution model suffers from scalability limitations on GPUs whose memory capacity is limited; existing systems fail to consider the discrepancy between fast GPUs and slow storage, which can counteract the benefit of GPU accelerators. In this paper, we propose HippogriffDB, an efficient, scalable GPU-accelerated OLAP system. It tackles the bandwidth discrepancy using compression and an optimized data transfer path. HippogriffDB stores tables in a compressed format and uses the GPU for decompression, trading GPU cycles for the improved I/O bandwidth. To improve the data transfer efficiency, HippogriffDB introduces a peer-to-peer, multi-threaded data transfer mechanism, directly transferring data from the SSD to the GPU. HippogriffDB adopts a query-over-block execution model that provides scalability using a stream-based approach. The model improves kernel efficiency with the operator fusion and double buffering mechanism. We have implemented HippogriffDB using an NVMe SSD, which talks directly to a commercial GPU. Results on two popular benchmarks demonstrate its scalability and efficiency. HippogriffDB outperforms existing GPU-based databases (YDB) and in-memory data analytics (MonetDB) by 1-2 orders of magnitude.
The Voice of the Citizen Consumer: A History of Market Research, Consumer Movements, and the Political Public Sphere

PART I. INTRODUCTION PART II. PRODUCING KNOWLEDGE ABOUT CITIZENS AND CONSUMERS: MARKET RESEARCH AND OPINION POLLING PART III. ACTING ON ONE'S OWN INITIATIVE: CONSUMER MOVEMENTS PART IV. COMMUNICATING KNOWLEDGE: MARKET RESEARCH, DATA PROTECTION, AND THE POLITICAL PART V. OUTLOOK: CITIZENS AND CONSUMERS IN THE TWENTIETH CENTURY
Photodynamic therapy as an adjunctive to scaling and root planing in treatment of chronic periodontitis in smokers.

OBJECTIVE To compare photodynamic therapy (PDT) as an adjunctive treatment of chronic periodontitis with scaling and root planing (Sc/Rp) in smokers. METHODS This is a split-mouth, single-masked randomized controlled clinical trial conducted at the Faculty of Dentistry, King Abdulaziz University, Jeddah, Saudi Arabia between May 2010 and March 2011. Fifty-four teeth with probing depth of ≥5mm at one or more periodontal sites in 20 smokers diagnosed with moderate to severe chronic periodontitis were selected. In each patient, at least one tooth was randomly assigned to Sc/Rp plus PDT (test group) and the contra-lateral tooth was assigned to Sc/Rp only (control). Plaque index (PI), bleeding on probing (BOP), probing depth (PD), recession and clinical attachment level (CAL) were recorded at baseline and 3 months after the periodontal treatment. Descriptive statistics and Wilcoxon signed ranked test were used for data analysis. RESULTS There was a statistically significant improvement in PD, CAL, BOP, and PI after periodontal treatment in both groups. No statistically significant differences between the 2 groups in any of the periodontal parameters were found at baseline (p>0.05), but a statistically significant greater reduction in PD (p=0.028) and CAL (p=0.044) in the test compared to the control group was found at the 3-month follow up. CONCLUSION Photodynamic therapy might have an additional benefit to scaling and root planing when treating smokers affected with periodontitis.
Degrees of Undecidability in Rewriting

Undecidability of various properties of first order term rewriting systems is well-known. An undecidable property can be classified by the complexity of the formula defining it. This gives rise to a hierarchy of distinct levels of undecidability, starting from the arithmetical hierarchy classifying properties using first order arithmetical formulas and continuing into the analytic hierarchy, where also quantification over function variables is allowed. In this paper we consider properties of first order term rewriting systems and classify them in this hierarchy. Weak and strong normalization for single terms turn out to be Sigma-0-1-complete, while their uniform versions as well as dependency pair problems with minimality flag are Pi-0-2-complete. We find that confluence is Pi-0-2-complete both for single terms and uniform. Unexpectedly weak confluence for ground terms turns out to be harder than weak confluence for open terms. The former property is Pi-0-2-complete while the latter is Sigma-0-1-complete (and thereby recursively enumerable). The most surprising result is on dependency pair problems without minimality flag: we prove this to be Pi-1-1-complete, which means that this property exceeds the arithmetical hierarchy and is essentially analytic.