Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing consumer vanity in Australia and China

Given the unmistakable trend toward a more integrated global economy and the tremendous impact of vanity on consumer demand for countless goods and services, there exists a need for more cross-cultural research on the important psychological construct known as consumer vanity (Netemeyer, Burton, and Lichtenstein 1995). Survey data was collected from 400 university students in Australia and China. This study followed the comprehensive analytical framework proposed by Steenkamp and Baumgartner (1998) to assess measurement equivalence in cross-cultural consumer research through the use of multiple-group confirmatory factor analysis. The 21-item consumer vanity measure was found to possess adequate metric invariance and scalar invariance for factor mean comparisons across the countries. Several theoretical perspectives were used to generate research hypotheses regarding cultural differences in each component of the consumer vanity construct. Hypothesis testing results lent support to most of the research hypotheses.
Progress in RoboComp

During the last six years the RoboComp robotics framework has been steadily growing in the number of software components, the variety of robots supported and in new solutions to the maintenance of large robotics software repositories. In this paper we present recent advances in the formal definition of the RoboComp component model and a new set of tools based on Domain Specific Languages that have been created to simplify the whole development cycle of the components. Moreover, a new robot simulation tool has been created providing perfect integration with RoboComp and better control over experiments than current existing simulators. Finally, the paper describes a working solution to the important problem of communications middleware independence, which allows users to decide which middleware the components will be compiled with. Our solution has been validated by the integration of Nerve, a novel middleware for critical robotics tasks, in RoboComp.
A multigrid perspective on the parallel full approximation scheme in space and time

For the numerical solution of time‐dependent partial differential equations, time‐parallel methods have recently been shown to provide a promising way to extend prevailing strong‐scaling limits of numerical codes. One of the most complex methods in this field is the “Parallel Full Approximation Scheme in Space and Time” (PFASST). PFASST already shows promising results for many use cases and benchmarks. However, a solid and reliable mathematical foundation is still missing. We show that, under certain assumptions, the PFASST algorithm can be conveniently and rigorously described as a multigrid‐in‐time method. Following this equivalence, first steps towards a comprehensive analysis of PFASST using blockwise local Fourier analysis are taken. The theoretical results are applied to examples of diffusive and advective type.
Repeating Spatial-Temporal Motifs of CA3 Activity Dependent on Engineered Inputs from Dentate Gyrus Neurons in Live Hippocampal Networks

Anatomical and behavioral studies, and in vivo and slice electrophysiology of the hippocampus suggest specific functions of the dentate gyrus (DG) and the CA3 subregions, but the underlying activity dynamics and repeatability of information processing remains poorly understood. To approach this problem, we engineered separate living networks of the DG and CA3 neurons that develop connections through 51 tunnels for axonal communication. Growing these networks on top of an electrode array enabled us to determine whether the subregion dynamics were separable and repeatable. We found spontaneous development of polarized propagation of 80% of the activity in the native direction from DG to CA3 and different spike and burst dynamics for these subregions. Spatial-temporal differences emerged when the relationships of target CA3 activity were categorized with to the number and timing of inputs from the apposing network. Compared to times of CA3 activity when there was no recorded tunnel input, DG input led to CA3 activity bursts that were 7× more frequent, increased in amplitude and extended in temporal envelope. Logistic regression indicated that a high number of tunnel inputs predict CA3 activity with 90% sensitivity and 70% specificity. Compared to no tunnel input, patterns of >80% tunnel inputs from DG specified different patterns of first-to-fire neurons in the CA3 target well. Clustering dendrograms revealed repeating motifs of three or more patterns at up to 17 sites in CA3 that were importantly associated with specific spatial-temporal patterns of tunnel activity. The number of these motifs recorded in 3 min was significantly higher than shuffled spike activity and not seen above chance in control networks in which CA3 was apposed to CA3 or DG to DG. Together, these results demonstrate spontaneous input-dependent repeatable coding of distributed activity in CA3 networks driven by engineered inputs from DG networks. These functional configurations at measured times of activation (motifs) emerge from anatomically accurate feed-forward connections from DG through tunnels to CA3.
Selective fusion of heterogeneous classifiers

There are two main paradigms in combining different classification algorithms: Classifier Selection and Classifier Fusion. The first one selects a single model for classifying a new instance, while the latter combines the decisions of all models. The work presented in this paper stands in between these two paradigms aiming to tackle the disadvantages and benefit from the advantages of both. In particular, this paper proposes the use of statistical procedures for the selection of the best subgroup among different classification algorithms and the subsequent fusion of the decision of the models in this subgroup with simple methods like Weighted Voting. Extensive experimental results show that the proposed approach, Selective Fusion, improves over simple selection and fusion methods, leading to performance comparable with the state-of-the-art heterogeneous classifier combination method of Stacking, without the additional computational cost and learning problems of meta-training.
Performance Evaluation of OFDM Transceiver For BPSK & QAM Modulation Techniques

The telecommunication industries insisted on new technology with high transmission abilities standardized by IEEE 802.16 also referred as WiMAX . It has two patterns fixed(802.16d-2004) and mobile(802.16d-2005) which are based on OFDM. This paper is about study and implementation of Convolutional coded WiMAX system comparing different modulation schemes such as BPSK and QAM . The performance has been concluded based on BER and SNR through MATLAB Simulation. Keywords—BER, BPSK, IFFT, IEEE 802.16 OFDM, QAM, SNR, WiMAX I. INTRODUCTION WiMAX is introduced by the Institute of Electrical and Electronic Engineers(IEEE) which is designated by 802.16 to provide world wide interoperability for microwave access.There are fixed(802.16d) and mobile(802.16e) WiMAX.This technology offers a high speed,secure,sophisticate, last mile broadband service,ensuring a flexible and cheap solution to certain rural access zones.In a fixed wireless communication, WiMAX can replace the telephone company's copper wire networks, the cable TV's coaxial cable infrastructure. In its mobile variant it can replace cellular networks. In comparison with Wi-Fi and Cellular technology, Wi- Fi provides a high data rate, but only on a short range of distances and with a slow movement of the user. And Cellular offers larger ranges and vehicular mobility, but it provides lower data rates, and requires high investments for its deployment. WiMAX tries to balance this situation. WiMAX fills the gap between Wi-Fi and Cellular, thus providing vehicular mobility, and high service areas and data rates . WiMAX is a standards based technology for wireless MANs conforming to parameters which enable interoperability. WiMAX developments have been rapidly moving forward. since the initial standardization efforts in IEEE 802.16. Standards for Fixed WiMAX (IEEE 802.16d- 2004) were announced as final in 2004, followed by Mobile WiMAX (IEEE 802.16e) in 2005, which are based on orthogonal frequency division multiplexing (OFDM) technology. OFDM is a transmission technique built for high speed bi-directional wired or wireless data communication(1,2). OFDM has high PAPR. Advantages of OFDM : 1. Channel bandwidth is divided into multiple subchannels ,i.e multicarrier transmission which is a method for the efficient utilization of the band width. 2. Subcarriers are orthogonal to each other in frequency domain which reduces ISI and frequency- selective fading. The technique is based upon the idea of multi-carrier modulation (MCM) where transmitted data is modulated on several orthogonal carrier frequencies. The subcarriers are closely spaced together but still orthogonal, which means that they are perpendicular in a mathematical sense, and do not interfere with each other. The implementations of OFDM in WIMAX technology today have been done by using FFT and its inverse operation IFFT,uses the formula given below. (1)
Microfluidic bead-based methods for DNA analysis

This report describes a rapid solid-phase melting curve analysis method for single-nucleotide polymorphism (SNP) genotyping. The melting curve analysis is based on dynamic allele-specific hybridization (DASH). The DNA duplexes are conjugated on beads that are immobilized on the surface of a microheater chip with integrated heaters and temperature sensors. SNP on PCR products were scored, illustrating the sensitivity and robustness of the system. The method is based on random bead immobilization by microcontact printing. Single-bead detection and multiplexing were performed with a heating rate more than 20 times faster than conventional DASH. Analyses that took more than 15 min could be performed in less that 1 min, enabling ultrarapid SNP analysis. In addition, an array version of the chip was implemented enabling the preparation of an array of bead arrays for high-throughput and rapid SNP genotyping.
Critical Infrastructure Attack Modeling

The development and connection of information and communication technologies with industrial control systems in the so-called critical infrastructure have contributed to the emergence of new complex threats. The critical infrastructure has become a target of sophisticated cyber attacks which exploit several, also unknown, vulnerabilities in one course of an attack. The paper proposes an attack modeling method enabling us to determine the vulnerabilities and riskful exposure of the systems. Organizational changes to ensure cyber defense of the critical infrastructure are also proposed.
An Effective Approach for Live Media Streaming Based on BitTorrent

In this paper, we present a solution that incorporates BitTorrent mechanism into P2P streaming. In our solution, several modifications have been incorporated into BitTorrent to support on-time delivery. First, we give the pieces different priorities based on their scheduled playback deadline. Second, source behaves in a push-based way instead of pull-based way. Finally, we import a block-level tit-for-tat policy and periodical examination of active neighbors to avoid low start and reinforce the fairness of system. Our simulations indicate that our proposals improve the bandwidth utilization and accommodate high scalability and resilience, and a good streaming quality can be achieved.
The Industry Effect on the Relationship Between Leverage and Returns

This paper aims to investigate the impact of leverage on stock returns. The analysis is performed both on a full sample basis and on an industry basis. Industry class is generally considered as an important risk factor. The sample used consisted of Italian listed non financial companies over the period 2000/12–2010/3. The main contribution of our work is that we enhance the capital structure studies by broadening the limited work that has been accomplished on the base of leverage as an explanatory variable of returns, in a totally different environment, that of a county of the South European region. The empirical findings, on the full sample, show that the leverage risk factor presents a strong — positive and statistically significant relationship with stock returns at the medium and high levered deciles. At the industry level analysis the leverage factor has a positive relation with excess returns for most industries. Overall, leverage in Italy is a priced risk factor.
Econometric Models in Romanian Tourism under the Impact of Sustainable Development

After the year 1989 Romanian tourism has grown chaotic and failed to have any link to the concept and sustainable development principles. Sustainability, in general, and the tourism sustainability, especially, combine different aspects – economic, social, environmental etc. in a harmonious way. In the paper the authors have proposed to test multiple linear regression models, in order to, finally demonstrate the impact of sustainable development on tourism activity. Following analyses have established links between nature, size of the tourism, economic, social and ecological indicators, thus demonstrating the impact of sustainable development on tourism also. The authors propose two original econometric models of dependence between the index of net using the tourist accommodation capacity in operation and indicators expressing the quality of life and sustainable development.
A latent risk approach for modeling individuallevel data consisting of multiple event timesSujit

Lifetime data often arises in the form of multiple events times for a sample of individuals. In such cases event times are often associated with the occurrence of quite diierent events, the event times can not be considered independent the distribution of time to occurrence of one event may change after the occurrence of another, events can occur simultaneously, partial censoring may be present and available covariate information may provide useful explanation. We formulate a general class of models rich enough to accommodate all of these features. The models are built using latent waiting time variables. Observed waiting times are viewed as minima of suitable subsets of these latent variables providing attractive competing risk interpretation. The latent waiting times are assumed to follow proportional hazards or accelerated life model speciications. Model tting is carried out using a data augmentation algorithm which routinely handles censoring. We illustrate with the analysis of a sample of trivariate event times for patients with a clinical diagnosis of AIDS. Harvard Pilgrim Health Care for providing the AIDS data set and for numerous important conversations. The authors also thank Carl Morris of the Department of Statistics at 1 Harvard University for valuable discussions in focusing this eeort.
Effects of Frequency and Acceleration Amplitude on Osteoblast Mechanical Vibration Responses: A Finite Element Study

Bone cells are deformed according to mechanical stimulation they receive and their mechanical characteristics. However, how osteoblasts are affected by mechanical vibration frequency and acceleration amplitude remains unclear. By developing 3D osteoblast finite element (FE) models, this study investigated the effect of cell shapes on vibration characteristics and effect of acceleration (vibration intensity) on vibrational responses of cultured osteoblasts. Firstly, the developed FE models predicted natural frequencies of osteoblasts within 6.85–48.69 Hz. Then, three different levels of acceleration of base excitation were selected (0.5, 1, and 2 g) to simulate vibrational responses, and acceleration of base excitation was found to have no influence on natural frequencies of osteoblasts. However, vibration response values of displacement, stress, and strain increased with the increase of acceleration. Finally, stress and stress distributions of osteoblast models under 0.5 g acceleration in Z-direction were investigated further. It was revealed that resonance frequencies can be a monotonic function of cell height or bottom area when cell volumes and material properties were assumed as constants. These findings will be useful in understanding how forces are transferred and influence osteoblast mechanical responses during vibrations and in providing guidance for cell culture and external vibration loading in experimental and clinical osteogenesis studies.
A Query-oriented XML Fragment Search Approach on A Relational Database System

In this paper, we propose a query-oriented frag- ment search approach for efficient and effective XML search engines on relational database systems. Conventional ap- proaches for XML fragment search have only considered sta- tistics of XML documents stored in a database system to rank a search result. As a result, almost all XML fragment search engines have attained negative results in the research field of information retrieval (IR). To cope with this problem, consider- ing not only statistics in the database system but also ones extracted from a query helps to improve retrieval accuracy of XML fragment search engines; however, it is also faced with a problem related with their efficiencies. Therefore, we have to devise ways of achieving both highly-relevant search results and efficient query processing. We implemented our XML search engine adopting the query-oriented fragment search approach, and found that it allows users to search XML fragments more accurately and effectively than conventional ones on our XML search engine.
Statistical Sketching for Non-Photorealistic Rendering Models and Animations

This paper further investigates the use of a statistical sketching model previously introduced in [Mignotte (2003)]. In this Bayesian framework, the localization and deformation of each pencil stroke of the sketch to be synthesized is viewed as the search of its Maximum A Posteriori (MAP) estimate. First, we improve this model by bringing a pencil stroke rendering procedure combined with a local rendering example-based process to significantly enhance its application for automatic synthesis of artistic depiction styles. Second, we show how this sketch synthesis procedure is suitable to easily synthesize a continuous gamut of sketch styles. Finally, we show how this model can also be exploited for several other interesting NPR applications. Among them, we describe a metamorphosis process between two sketches over times. We illustrate the interest and potential of these unsupervised techniques with images simulating automatic synthesis of various illustration styles and animated sequences with NPR effects.
EXPLORING WEAK AND OVERLAPPED RETURNS OF A LIDAR WAVEFORM WITH A WAVELET-BASED ECHO DETECTOR

Full waveform data recording the reflected laser signal from ground objects have been provided by some commercial airborne LIDAR systems in the last few years. Waveform data enable users to explore more information and characteristics of the earth surface than conventional LIDAR point cloud. An important application is to extract extra point clouds from waveform data in addition to the point cloud generated by the online process of echo detection. Some difficult-to-detect points, which may be important to topographic mapping, can be rediscovered from waveform data. The motivation of this study is to explore weak and overlapped returns of a waveform. This paper presents a wavelet-based echo detection algorithm, which is compared with the zero-crossing detection method for evaluation. Some simulated waveforms deteriorated with different noises are made to test the limitations of the detector. The experimental results show that the wavelet-based detector outperformed the zero-crossing detector in both difficult-to-detect cases. The detector is also applied to a real waveform dataset. In addition to the total number of echoes provided by the instrument, the detector found 18% more of echoes. The proposed detector is significant in finding weak and overlapped returns from waveforms.
Adaptive Mechanisms in Virtual Education Environment

1 Radoslav Fasuga, radoslav.fasuga@vsb.cz 2 Jana Sarmanova, jana.sarmanova@vsb.cz Abstract Knowledge mining process based on logs in virtual education systems is one from many techniqu es, which can help to receive information for automated adaptation – selection of study materials. Target o f this Article is to describe possible ways of Automated Adaptation for walk-through study materials in virt ual education environment. Article describes goals and weaknesses for several adaptive algorithms in oppos ite to manual modification of study materials. Algorithms respect Student Activity Protocol, Study Groups and Authors for finding best available adaptation. Benefit of this solution is to simplify user orientation in st udy materials and growing efficiency of their education.
Autosomal Dominant Hypercholesterolemia: Needs for Early Diagnosis and Cascade Screening in the Tunisian Population

Autosomal dominant hypercholesterolemia (ADH) is characterized by an isolated elevation of plasmatic low-density lipoprotein (LDL), which predisposes to premature coronary artery disease (CAD) and early death. ADH is largely due to mutations in the low-density lipoprotein receptor gene (LDLR), the apolipoprotein B-100 gene (APOB), or the proprotein convertase subtilisin/kexin type 9 (PCSK9). Early diagnosis and initiation of treatment can modify the disease progression and its outcomes. Therefore, cascade screening protocol with a combination of plasmatic lipid measurements and DNA testing is used to identify relatives of index cases with a clinical diagnosis of ADH. In Tunisia, an attenuated phenotypic expression of ADH was previously reported, indicating that the establishment of a special screening protocol is necessary for this population.
Risky decision-making is associated with residential choice in healthy older adults

As our society becomes more mobile and people reside farther away from their immediate families, competent decision-making has become critical for the older adults wishing to maintain their independence. However, very little is known about the relationship between residential choice and decision-making. Here we use the Balloon Analog Risk Task (BART) to examine risk-taking in two samples of older adults, one living in a retirement community and another living independently. We also used a cognitive model to gain insight into the cognitive factors underlying decision-making in these groups. We found that older adults living in a retirement community were more risk averse than their independent counterparts. Furthermore, this difference appeared to be motivated by group differences in initial perception of risk. This study suggests an intriguing difference between these two residential groups, and also points to the utility of using laboratory methods in research on real-world problems.
PLUG-IN VEHICLE CONTROL STRATEGY : FROM GLOBAL OPTIMIZATION TO REAL-TIME APPLICATION

Plug-in hybrid electric vehicles (PHEVs) have demonstrated the potential to significantly increase fuel economy. However, the overall efficiency of the powertrain system of any Hybrid Electric Vehicle (HEV) depends on the vehicle-level control strategy. To optimize the energy flow, a global optimization algorithm, based on the Bellman principle, was used to generate the most efficient operating conditions for a parallel pre-transmission hybrid and a specific driving cycle. Several driving cycles were analyzed, each of them repeated a number of times to assess the impact of driving distance. The engine, electric machine, and transmission operating modes were then used to generate a rulebased control strategy in PSAT, Argonne’s vehicle system modeling software.