Miracle-dz/UniFAR-FTUs huggingface dataset:
Elementary school children’s attentional biases in physical and numerical space

Numbers are conceptualized spatially along a horizontal mental line. This view is supported by mounting evidence from healthy adults and patients with unilateral spatial neglect. Little is known about children's representation of numbers with respect to space. This study investigated elementary school children's directional biases in physical and numerical space to better understand the relation between space and number. We also examined the nature of spatial organization in numerical space. In two separate tasks, children (n = 57) were asked to bisect a physical line and verbally estimate the midpoint of number pairs. In general, results indicated leftward biases in both tasks, but the degree of deviation did not correlate between the tasks. In the number bisection task, leftward bias (underestimating the midpoint) increased as a function of numerical magnitude and interval between number pairs. In contrast, a rightward deviation was found for smaller number pairs. These findings suggest that different underlying spatial attentional mechanisms might be directed in physical and numerical space in young school children, which would be integrated in adulthood.
The Implementation of Trust Model in the P2P Patch Distribution System

In order to effectively improve the success rate of transactions among nodes of p2p patch distribution system, this trust model was introduced to the p2p patch distribution system, the design of trust model was given and the specific implementation of each module was described in detail, finally the performance of trust model achieved were tested.
Geolocation by time difference of arrival using hyperbolic asymptotes

The paper proposes a new simplified algorithm to estimate the location of an emitter by utilizing time difference of arrival (TDOA) measurements. This is achieved by recasting the estimation problem in prolate spheroidal coordinates. Prolate spheroidal coordinates greatly simplify the TDOA equations, producing a set of linear equations in the far field limit. The set of linear equations corresponds to the hyperbolic asymptotes of the TDOA measurements. We also develop a systematic approach that associates the hyperbolic asymptotes with the emitter. In the near field, the far field solution can be used to "seed" the iterative maximum likelihood (ML) estimate, enabling convergence to the ML solution.
Extending mobile user ambient awareness for nomadic text entry

Nowadays, we input text not only on stationary devices, but also on handheld devices while walking, driving, or commuting. Text entry on the move, which we term as nomadic text entry, is generally slower. This is partially due to the need for users to move their visual focus from the device to their surroundings for navigational purposes and back. To investigate if better feedback about users' surroundings on the device can improve performance, we present a number of new and existing feedback systems: textual, visual, textual & visual, and textual & visual via translucent keyboard. Experimental comparisons between the conventional and these techniques established that increased ambient awareness for mobile users enhances nomadic text entry performance. Results showed that the textual and the textual & visual via translucent keyboard conditions increased text entry speed by 14% and 11%, respectively, and reduced the error rate by 13% compared to the regular technique. The two methods also significantly reduced the number of collisions with obstacles.
Mycobacterial PIMs Inhibit Host Inflammatory Responses through CD14-Dependent and CD14-Independent Mechanisms

Mycobacteria develop strategies to evade the host immune system. Among them, mycobacterial LAM or PIMs inhibit the expression of pro-inflammatory cytokines by activated macrophages. Here, using synthetic PIM analogues, we analyzed the mode of action of PIM anti-inflammatory effects. Synthetic PIM1 isomer and PIM2 mimetic potently inhibit TNF and IL-12 p40 expression induced by TLR2 or TLR4 pathways, but not by TLR9, in murine macrophages. We show inhibition of LPS binding to TLR4/MD2/CD14 expressing HEK cells by PIM1 and PIM2 analogues. More specifically, the binding of LPS to CD14 was inhibited by PIM1 and PIM2 analogues. CD14 was dispensable for PIM1 and PIM2 analogues functional inhibition of TLR2 agonists induced TNF, as shown in CD14-deficient macrophages. The use of rough-LPS, that stimulates TLR4 pathway independently of CD14, allowed to discriminate between CD14-dependent and CD14-independent anti-inflammatory effects of PIMs on LPS-induced macrophage responses. PIM1 and PIM2 analogues inhibited LPS-induced TNF release by a CD14-dependent pathway, while IL-12 p40 inhibition was CD14-independent, suggesting that PIMs have multifold inhibitory effects on the TLR4 signalling pathway.
Development of a direct teaching system for a cooperative cell-production robot considering safety and operability

A direct teaching system emphasizing safety and operability for SP02, an upper-body humanoid that cooperates with a human in a cell-production workspace has been described. The system has a direct teaching device, which enables an operator to teach a multi-D.O. F manipulator at comfortable posture despite large changes in the pose of an end-effector. The double-checked safety-related part(SRP/CS) introducing a safety module satisfies the safety performance defined in the international safety standard. To make the teaching easier to perform, impedance parameters in a variable impedance control are set through several direct teaching experiments. Through a simple direct teaching experiment, the safety performance of the SRP/CS and the teaching performance of the direct teaching system was successfully confirmed.
THREE-DIMENSIONAL LOCALIZATION ALGORITHM FOR MIXED NEAR-FIELD AND FAR-FIELD SOURCES BASED ON ESPRIT AND MUSIC METHOD

A three-dimensional (3-D) source localization algorithm of joint elevation, azimuth angles and range estimation for the mixed near-fleld (NF) and far-fleld (FF) sources is presented in this paper. We flrst estimate the elevation angles of all mixed sources by using the generalized ESPRIT method. With the elevation angle estimates, the range parameters of all mixed sources are obtained, and then both the NF and FF sources are distinguished. Finally, with the elevation angle and range estimates, the azimuth angles of all mixed sources are acquired based on the conventional high-resolution MUSIC method. The proposed algorithm avoids parameter match operation, and requires neither a multidimensional search nor high-order statistics (HOS). Simulation and experiment results show the performance of the proposed algorithm in this paper.
An original approach for the localization of objects in images

Presents an algorithm for the detection of faces in images using shared-weight replicated neural networks. A neural net forms rough hypotheses about the position of faces. These hypotheses are then verified using a second neural network. The algorithm applies to images where the size of the faces is unknown a priori. The computational time which is necessary for the complete processing of an image is reasonable. With a classical workstation an image of size 512*512 is treated in 50 seconds including smoothing and normalization of the image. This algorithm can be easily installed on a more specialized machine as the major part of the operation is based on convolutions with kernels of size 5*5 or 8*8. In this paper, the authors assume that the face are well oriented in the image. It is possible to eliminate this assumption by following an approach similar to the one used for the scale problem. A net is trained to be insensitive to the precise orientation of the face. This kind of segmentation algorithm can be applied to other problems where the objects to be detected cannot be characterized easily by its outline or by classical primitives in image processing.
Artificial Brownian motors: Controlling transport on the nanoscale

In systems possessing spatial or dynamical symmetry breaking, Brownian motion combined with unbiased external input signals, deterministic and random alike, can assist directed motion of particles at submicron scales. In such cases, one speaks of ``Brownian motors. '' In this review the constructive role of Brownian motion is exemplified for various physical and technological setups, which are inspired by the cellular molecular machinery: the working principles and characteristics of stylized devices are discussed to show how fluctuations, either thermal or extrinsic, can be used to control diffusive particle transport. Recent experimental demonstrations of this concept are surveyed with particular attention to transport in artificial, i.e., nonbiological, nanopores, lithographic tracks, and optical traps, where single-particle currents were first measured. Much emphasis is given to two- and three-dimensional devices containing many interacting particles of one or more species; for this class of artificial motors, noise rectification results also from the interplay of particle Brownian motion and geometric constraints. Recently, selective control and optimization of the transport of interacting colloidal particles and magnetic vortices have been successfully achieved, thus leading to the new generation of microfluidic and superconducting devices presented here. The field has recently been enriched with impressive experimental achievements in building artificial Brownian motor devices that even operate within the quantum domain by harvesting quantum Brownian motion. Sundry akin topics include activities aimed at noise-assisted shuttling other degrees of freedom such as charge, spin, or even heat and the assembly of chemical synthetic molecular motors. This review ends with a perspective for future pathways and potential new applications.
The Involvement of Norepinephrine in Behaviors Related to Psychostimulant Addiction

Although it is generally accepted that the abuse-related effects of amphetamines and cocaine result from the activation of the brain dopaminergic (DA) system, the psychostimulants also alter other neurotransmitter systems. In particular, they increase extracellular levels of norepinephrine (NE) and serotonin by inhibiting respective plasma membrane transporters and/or inducing release. The present review will discuss the preclinical findings on the effects of the NE system modulation (lesions, pharmacological and genetic approaches) on behaviors (locomotor hyperactivity, behavioral sensitization, modification of intracranial self-stimulation, conditioned place preference, drug self-administration, extinction/reinstatement of drug seeking behavior) related to the psychostimulant addiction.
High performance Deep Packet Inspection on multi-core platform

Deep Packet Inspection (DPI) provides the ability to perform Quality of Service (QoS) and Intrusion Detection on network packets. But since the explosive growth of Intrnet, performance and scalability issues have been raised due to the gap between network and end-system speeds. This article describles how a desirable DPI system with multi-gigabits throughput and good scalability should be like by exploiting parallelism on Network Interface Card, network stack and user applications. Connection-based Parallelism, Affinity-based Scheduling and Lock-free Data Structure are the main technologies introduced to alleviate the performance and scalability issues. A common DPI application L7-Filter is used as an example to illustrate the applicaiton level parallelism.
Modeling competences in Service-Oriented Virtual Organization Breeding Environments

Support for organization competences is an important function of Virtual Organization Breeding Environments (VOBEs), allowing VOBE members to publish and consult about the activities they may perform. In Service-Oriented VOBEs (SOVOBEs), organized systematically around the concept of services, existing competence models should be extended to support the service-orientation of SOVOBEs. In this paper, a refinement of the 4-C competence model is presented. The main enhancements consist of 1) the redefinition of the concept of a service as regards competences 2) a clear distinction of the relations between activities, services, capabilities and competences, and 3) the introduction of contextual capabilities.
Security in RFID based smart retail system

Recent developments in RFID and NFC technologies help manufacturer to find out ways of replacing traditional object identification such as bar code with RFID tags. These RFID tags are passive and cheaper tags that enable object tracking a reality. Tags can also help retailers to allow customers to shop in a smarter way allowing customers to purchase items through smart retailers enabled with RFID readers in the shopping cart. C1G2 tags allow tackling against counterfeit items using its minimal cryptography approaches such as XOR, 16 bit PRNG, CRC techniques, and separate memory for storing secret pins. The proposed model creates secure perimeter to realize smart shopping environment and supply chain management. In this paper, we have extended the application of RFID technology to smart shopping environment allowing customer to shop authentic items which lessen counterfeit item sale in the market. Our technique can even strengthen tag based product sale in open market where chance of selling counterfeit items are high.
oRGB: A Practical Opponent Color Space for Computer Graphics

Designed for computer graphics, oRGB is a new color model based on opponent color theory. It works well for both HSV-style color selection and computational applications such as color transfer. oRGB also enables new applications such as a quantitative cool-to-warm metric, intuitive color manipulation and variations, and simple gamut mapping.
Smart Multi-Task Bregman Clustering and Multi-Task Kernel Clustering

Multitask Bregman Clustering (MBC) alternatively updates clusters and learns relationship between clusters of different tasks, and the two phases boost each other. However, the boosting does not always have positive effect, it may also cause negative effect. Another issue of MBC is that it cannot deal with nonlinear separable data. In this paper, we show that MBC's process of using cluster relationship to boost the updating clusters phase may cause negative effect, i.e., cluster centroid may be skewed under some conditions. We propose a smart multi-task Bregman clustering (S-MBC) algorithm which identifies negative effect of the boosting and avoids the negative effect if it occurs. We then extend the framework of S-MBC to a smart multi-task kernel clustering (S-MKC) framework to deal with nonlinear separable data. We also propose a specific implementation of the framework which could be applied to any Mercer kernel. Experimental results confirm our analysis, and demonstrate the superiority of our proposed methods.
Effects of resolution and helium abundance in A star surface convection simulations

We present results from 2D radiation-hydrodynamical simulations of fully compressible convection for the surface layers of A-type stars with the ANTARES code. Spectroscopic indicators for photospheric convective velocity fields show a maximum of velocities near Teff ∼ 8000 K with the largest values measured for the subgroup of Am stars. Thus far, no prognostic model, neither theoretical nor numerical, is able to exactly reproduce the line profiles of sharp line A and Am stars in that temperature range. As the helium abundance of A stars is not known from observations, we have considered two extreme cases for our simulations: a solar helium abundance as an upper limit and zero helium abundance as a lower limit. The simulation for the helium free case is found to differ from the case with solar helium abundance by larger velocities, larger flow structures, and by a sign reversal of the flux of kinetic energy inside the hydrogen ionisation zone. Both simulations show extended shock fronts emerging from the optical surface, as well as mixing far below the region of partial ionisation of hydrogen, and vertical oscillations emerging after initial perturbations have been damped. We discuss problems related to the rapid radiative cooling at the surface of A-type stars such as resolution and efficient relaxation. This includes identifying the radiative cooling rate Qrad, which poses the most severe time step limitation for the dynamical equation for the evolution of energy density, as a stiff term. It is thus a numerical rather than a physical constraint for the numerical simulation of these objects. The present work is F. Kupka, J. Ballot, and H.J.Muthsam 31 considered as a step towards a systematic study of convection in Ato F-type stars, encouraged by the new data becoming available for these objects from both asteroseismological missions and from high resolution spectroscopy. Accepted: 2009, September 22
Ordering and correlation of cluster orientations in CaCd6

In order to study the low-temperature phase transition in CaCd6, which is attributed to a reordering of the innermost tetrahedral cluster shells, accurate Embedded-Atom-Method potentials are developed for this system. With these potentials, the ideal cluster structure and the couplings between neighbouring clusters are determined. From these data, an effective Hamiltonian for the cluster orientations is derived. The Hamiltonian is used in Monte Carlo simulations, which exhibit a sharp jump in the internal energy near the expected transition temperature.
Semi-automatic tumor segmentation based on modified sparse field method

Active contour methods for image segmentation allow a contour to deform iteratively to partition an image into various regions. Active contours are often implemented with level set methods because of their power and versatility. The primary drawback of level set methods is that, they are slow to compute. In this paper, we discussed the sparse field method (SFM) proposed by Whitaker that allows one to implement level set active contours efficiently. In active contour, stopping term depends on gradient of image only. In practice, the discrete gradients are bounded and then the stopping function is never zero on the edges, and the curve may pass through the object boundary. In this paper, we proposed the new method of edge detection for active contours based on local adaptive threshold technique via variational energy minimization. As an application, our method has been used for tumor segmentation from magnetic resonance images and experimental results show desirable performances of our method.
A New Speech Enhancement Method based on wavelet thresholding the multitaper spectrum

It is known that the “musical noise” encountered in most frequency domain algorithms is partially due to the large variance estimates of the spectra. To address this issue, we propose in this paper the use of lowvariance spectral estimators based on wavelet thresholding the multitaper spectra. We extend the signal subspace approach in the frequency domain and incorporate the wavelet thresholded multitaper spectra into the proposed shorttime spectral amplitude estimator. Listening tests showed that the use of multitaper spectrum estimation combined with wavelet thresholding suppressed the musical noise and yielded better quality than the recently proposed subspace
Toward unibody robotic structures with integrated functions using multimaterial additive manufacturing: Case study of an MRI-compatible interventional device

In this paper, a new multifunctional compliant joint is introduced for the design of unibody robotic mechanisms. Developed in the demanding context of interventional MRI, the compliant joint integrates kinematic, actuation, braking and sensing functions. Such integration is performed thanks to multimaterial additive manufacturing. Design and experimental behavior of the component are presented. A robotic assistant built with the proposed component and made of a single element is then introduced. It offers interesting performances while being compact and MR-compatible.
IoT-Based Big Data Storage Systems in Cloud Computing: Perspectives and Challenges

Internet of Things (IoT) related applications have emerged as an important field for both engineers and researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations especially in cloud computing. This paper first provides a functional framework that identifies the acquisition, management, processing and mining areas of IoT big data, and several associated technical modules are defined and described in terms of their key characteristics and capabilities. Then current research in IoT application is analyzed, moreover, the challenges and opportunities associated with IoT big data research are identified. We also report a study of critical IoT application publications and research topics based on related academic and industry publications. Finally, some open issues and some typical examples are given under the proposed IoT-related research framework.
Smarter Lunchrooms - Ohio: Using Production and Sales Records to Measure Change in Food Selection

Background: The 2010 Healthy, Hunger-Free Kids Act (HHFKA) updated the national school meals standards from the 1995 to the 2010 Dietary Guidelines for Americans. The HHFKA are the most comprehensive changes to the national school meal standards in 15 years. Measurement of food selection is essential to determine the impact of the new rules. This study develops an indicator, using production records, to track food selection in school cafeterias. Methods: Participating Ohio school districts applied interventions from The Smarter Lunchrooms Movement to cafeterias. Using MyPlate as a model and production records from two school districts, a coding system was developed to categorize foods, which were used to create the indicator, My Tray. Results: My Tray provides a visual snapshot of entrees, grains, vegetables, fruits, and milk selection. Students attending study schools selected fruits and vegetables to make 24% and 31% of the tray respectively. High school students selected the most fruit (22%) and elementary students selected 18%. Vegetable selection was highest in the elementary schools (37%), middle school was 29%, and high school selection was at 19%. Conclusion: My Tray displays food groups selection. My Tray is designed to track changes in lunchroom food selection. The tool can also be used to aggregate data across months, which can help to make comparisons across categories. Food service staff can use My Tray to track the impact of cafeteria interventions. The goal of establishing an indicator, using production, was challenging because of different recording methods, chasing missing information, and combination food items.
Structure based semantic measurement for information filtering agents

With the volume of information on the Internet growing at an exponential rate, the needs of users to have their search results effectively filtered is increasingly important. A problem with most of the current search engines is that they only search on the specified keyword, which may be present in only a limited number of pages. This paper examines how a tree threshold function can be used in an information filtering agent (IFA) to extend the original keyword search to cover other related words within the domain, creating a keyword weighted semantic tree. The examination in this paper also considers how the metrics of the tree structure (shape, size, weights) influence the choice of related words for use in the extended search and what advantage this has over traditional methods. Further, that using a reduced word tree, which has been pruned using the tree pruning algorithm produces a significant increase in the number of profitable results for the user. Using these factors the analysis demonstrates equal accuracy to the benchmark comparison IFA but with increased efficiency and only a slight increase in execution time.