Miracle-dz/UniFAR-FTUs huggingface dataset:
A Grid of Language Resource Repositories

The DAM-LR (Distributed Access Management for Language Resources) project aims at virtually integrating various European language resource archives that allow users to navigate and operate in a single unified domain of language resources. This type of integration introduces Grid technology to the humanities disciplines and forms a federation of archives. It is the basis for establishing a research infrastructure for language resources which will finally enable eHumanities. Currently, the complete architecture is designed based on a few well-known components and some components have already been tested. Based on the technological insights gathered and due to discussions within the international DELAMAN (Digital Endangered Languages and Music Archives Network) network the ethical and organizational basis for such a federation is defined.
Time-Modulation of Linear Arrays for Real-Time Reconfigurable Wireless Power Transmission

This paper proposes a smart wireless power transmission method, based on a two-step procedure, exploiting real-time beaming of time-modulated arrays. The sideband radiation phenomenon, which is usually a drawback of these radiating systems, is favorably used for intentional wireless power transfer (WPT): in a first step to precisely localize the tag to be powered and in the second one to perform directive WPT. The approach is first theoretically discussed, then the numerical procedure, which integrates full-wave analysis of the antenna array with nonlinear simulation of the modulated nonlinear feeding network, is used to validate the principle of operation and to include nonlinearities and electromagnetic couplings affecting the whole system performance. The procedure allows a flexible design of the time-modulated-array-based WPT system, taking into account the impact of different array elements layout and spacing on localization and power transmission performance. Experiment of the first step is carried out in a real indoor environment at 2.45 GHz: a TI MSP430 drives a Schottky-diode-based network to provide proper modulated RF excitations of the array elements. Measurements show that the system is able to select tags to be energized randomly distributed in a 100 °-scanning range.
Secure Sketch Metamorphosis: Tight Unified Bounds

A noisy non-uniformly distributed secret often needs to be transformed into a stable high-entropy key. Biometric systems and physically unclonable functions (PUFs) exemplify the need for this conversion. Secure sketches are a useful tool hereby as they alleviate the noisiness while keeping the corresponding min-entropy loss to a minimum. The novelty of our work is twofold. First, seven secure sketch constructions, all based on a binary [n, k, d] block code, are proven to be largely interchangeable. Despite having different looks and properties, all exhibit the same min-entropy loss, when fed with the same probability distribution. Second, for PUF-induced distributions with practical relevance, we derive new unified bounds on the min-entropy loss, considerably tighter than the more general well-known (n− k) bound. Our bounds allow for an efficient evaluation and are hence suitable for reducing the implementation footprint of the sketch. This is beneficial for resource-constrained devices in particular.
An Improved DV-hop Localization Algorithm Based on Modified Hop-Size

DV-Hop algorithm is a range free algorithm that uses hop distance in its calculations. An improved DV-Hop algorithm is proposed by changing the average hop-size. The evaluation of the performance was carried out on wireless sensor network localization. Sensors were placed according to two functions, pseudo random and sobol quasi random. The latter was chosen because it guarantees space coverage when space dimensions increase. Localization errors are compared to those of the basic DV-Hop algorithm. The proposed algorithm proved effectiveness in remarkably decreasing the localization error of the sensors. An important application is in a nuclear power plant process control test facility (NPCTF) where a wireless sensor network is an effective tool to collect data for fault diagnostics. The location of the fault is crucial. Hence, minimum localization error is of utmost importance.
On the complexity of package recommendation problems

Recommendation systems aim to recommend items that are likely to be of interest to users. This paper investigates several issues fundamental to such systems. We model recommendation systems for packages of items. We use queries to specify multi-criteria for item selections and express compatibility constraints on items in a package, and use functions to compute the cost and usefulness of items to a user. We study recommendations of points of interest, to suggest top-k packages. We also investigate recommendations of top-k items, as a special case. In addition, when sensible suggestions cannot be found, we propose query relaxation recommendations to help users revise their selection criteria, or adjustment recommendations to guide vendors to modify their item collections. We identify several problems, to decide whether a set of packages makes a top-k recommendation, whether a rating bound is maximum for selecting top-k packages, whether we can relax the selection query to find packages that users want, and whether we can update a bounded number of items such that the users' requirements can be satisfied. We also study function problems for computing top-k packages, and counting problems to find how many packages meet the user's criteria. We establish the upper and lower bounds of these problems, all matching, for combined and data complexity. These results reveal the impact of variable sizes of packages, the presence of compatibility constraints, as well as a variety of query languages for specifying selection criteria and compatibility constraints, on the analyses of these problems.
Modified AS1411 Aptamer Suppresses Hepatocellular Carcinoma by Up-Regulating Galectin-14

Aptamers are small synthetic oligonucleotides that bind to target proteins with high specificity and affinity. AS1411 is an aptamer that binds to nucleolin, which is overexpressed in the cytoplasm and occurs on the surface of cancer cells. We investigated the therapeutic potential of aptamers in hepatocellular carcinoma (HCC) by evaluating anti-tumor effects and confirming the affinity and specificity of AS1411- and modified AS1411-aptamers in HCC cells. Cell growth was assessed using the MTS assay, and cell death signaling was explored by immunoblot analysis. Fluorescence-activated cell sorting was performed to evaluate the affinity and specificity of AS1411-aptamers in SNU-761 HCC cells. We investigated the in vivo effects of the AS1411-aptamer using BALB/c nude mice in a subcutaneous xenograft model with SNU-761 cells. Treatment with a modified AS1411-aptamer significantly decreased in vitro (under normoxic [P = 0.035] and hypoxic [P = 0.018] conditions) and in vivo (under normoxic conditions, P = 0.041) HCC cell proliferation compared to control aptamers. AS1411- and control aptamers failed to control HCC cell proliferation. However, AS1411- and the modified AS1411-aptamer did not induce caspase activation. Decrease in cell growth by AS1411 or modified AS1411 was not prevented by caspase or necrosis inhibitors. In a microarray, AS1411 significantly enhanced galectin-14 expression. Suppression of HCC cell proliferation by the modified AS1411-aptamer was attenuated by galectin-14 siRNA transfection. Modified AS1411-aptamer suppressed HCC cell growth in vitro and in vivo by up-regulating galectin-14 expressions. Modified AS1411-aptamers may have therapeutic potential as a novel targeted therapy for HCC.
An Improvised Localization Scheme Using Active RFID for Accurate Tracking in Smart Homes

Out of several location sensing systems developed over the past few years, Radio Frequency Identification is one of the efficient techniques that uses radio waves for wireless communication. In this paper Radio Frequency Identification is used as a Colony based localized technique for accurate tracking of objects in Smart Homes. In order to accurately determine the position of an object, a backtracking algorithm is used. This algorithm identifies those reference tags which are identified by the LANDMARC system. Colonies based upon the spatial co-relation between the reference tags are used to get the original neighboring tags to compute the location of an object situated near an obstacle.
Towards a Distributed Architecture for Value Added Services to Digital Libraries

Scientific communities are relying more and more on value added services offered by different systems on top of digital document repositories and libraries. Current systems, like CiteSeer and Google Scholar, offer important services to these communities but show their limitations when it comes to scalability, decentralize control and plan for a sustainable model for community support. In this paper we propose and describe a new distributed and service oriented architecture to support the creation of such services. Our architecture aims at lowering the technological barriers to build distributed community environments by providing a small number of key core services and a layered architecture for extension services.
Go Ahead: A Partial Reconfiguration Framework

Exploiting the benefits of partial run-time reconfiguration requires efficient tools. In this paper, we introduce the tool Go Ahead that is able to implement run-time reconfigurable systems for all recent Xilinx FPGAs. This includes in particular support for low cost and low power Spartan-6 FPGAs. Go Ahead assists during floor planning and automates the constraint generation. It interacts with the Xilinx vendor tools and triggers the physical implementation phases all the way down to the final configuration bit streams. Go Ahead enables the building of flexible systems for integrating many reconfigurable modules very efficiently into a system. The tool targets (re)usability, portability to future devices, and migration paths among reconfigurable systems featuring different FPGAs or even FPGA families. Moreover, it provides a scripting interface and all features can be accessed remotely.
Asymmetric temporal interactions of sound‐evoked excitatory and inhibitory inputs in the mouse auditory midbrain

The temporal coding of sound is critical for the auditory system. Little is known about how sound evokes the timing of synaptic currents at higher levels of the auditory system and how the integration of these currents results in neural firing. In the inferior colliculus, excitatory and inhibitory synaptic currents evoked by long‐duration sounds have different temporal properties with excitatory currents more variable than inhibitory currents. Within a neuron, the sequence of synaptic events suggests the fastest sound‐evoked excitatory postsynaptic current (EPSCs) usually followed the inhibitory postsynaptic currents (IPSCs), and the slowest EPSCs preceded by IPSCs. Knowledge about the timing of neural activity in the midbrain is important for understanding how temporally complex sounds such as speech are processed and communicated to higher centres of the system.
An adaptive force reflective teleoperation control method using online environment impedance estimation

This paper proposes a new adaptive method for two-channel bilateral teleoperation systems control; the control method consists of adaptive force feedback and motion command scaling factors that ensure stable teleoperation with maximum achievable transparency at every moment of operation. The method is based on the integration of the real time estimation of the robot's environment impedance with the adaptive force and motion scaling factors generator. This paper formulates the adaptive scaling factors for stable teleoperation based on the impedance models of master, slave and estimated impedance of the environment. Feasibility and accuracy of an online environment impedance estimation method are analyzed through simulations and experiments. Then the proposed adaptive bilateral control method is verified through simulation studies. Results show stable interactions with maximum transparency for the simulated teleoperation system.
Hypoxic immunomodulation results in increased disease risk and altered behavior via non-canonical pathways

Hypoxia/reoxygenation is a critical event in the development of multiple adverse psychological outcomes, including anxiety-like behaviors and cognitive impairment. The role linking brain-based IL-1 to these various impairments, especially memory formation and recall, has been the focus of many studies yet the exact mechanism is undefined. More specifically, adenosine-dependent activation of caspase-1 has been shown to be a crucial mediator of hypoxia-induced brain-based cognitive impairment. In this study, we examined the mechanism underlying memory recall after an acute hypoxic incident. Following reoxygenation, confirmation of increased caspase-1 activity in the amygdala by 65% was determined using a novel ICV-IHC approach but no change was observed in the hippocampus. Mice were then injected with glyburide and DMPX to understand the involvement of K+ efflux/A2A AR. Both glyburide and DMPX significantly reduced the level of caspase-1 activation in the amygdala after hypoxia/reoxygenation. In correlation with the reduction in caspase-1 activation, both drugs restored novel object recognition memory and therefore memory recall. Caspase-1 activation was neuron-induced with greater co-localization of neurons and caspase-1 in the amygdala of hypoxic animals when compared to controls. Similarly, neuron-specific knockout of IGF-I significantly reduced caspase-1 activation in the amygdala following hypoxia/reoxygenation corresponding with correction of novel object recognition. Hypoxia/reoxygenation induced a significant increase in the phosphorylation of IRS-1 and p70SK but no change in IGF-I, PKA, or
Supporting Information - Dresch et al. 2010

The root mean square error (RMSE), as implemented in the Fakhouri et al. study, was calculated using Giant protein concentrations as model inputs and the corresponding lacZ mRNA concentrations as outputs [1]. Data points were taken at 20 different Giant concentration levels, uniformly ranging from 0 to 1. Each term in the RMSE was weighted by the number of actual data points over which each lacZ concentration was averaged. In our sensitivity analysis, this weighted RMSE was used as the objective function. The Pearson correlation coefficient, as implemented in the Zinzen et al. study, was calculated using Dorsal, Twist, and Snail protein concentrations as model inputs and the corresponding rho and vnd mRNA concentrations as outputs, which can be found at DVEx database (http://www.dvex.org) [2]. Enhancer-like structures used to calculate sensitivities of the Zinzen et al. model For the results shown in Figure 3, we used two representative pairs of enhancer structures proposed by Zinzen et al. The remaining structures were analyzed as shown in Figure S7. Each representative pair of enhancer structures is defined by the number of modules and binding sites in each of the representative enhancers. An enhancer with more than one module (Md > 1) is assumed to have identical, independent modules contributing to the expression of that gene. D, T/S, T, and S represent the number of binding sites for Dorsal, Twist/Snail, Twist, and Snail, respectively, in each module. A T/S binding site differs from other binding sites in that it can be occupied by either the Twist or Snail protein. The first set of representative enhancers has, for the rho-like
FICA: A novel intelligent crawling algorithm based on reinforcement learning

The web is a huge and highly dynamic environment which is growing exponentially in content and developing fast in structure. No search engine can cover the whole web, thus it has to focus on the most valuable pages for crawling. So an efficient crawling algorithm for retrieving the most important pages remains a challenging issue. Several algorithms like PageRank and OPIC have been proposed. Unfortunately, they have high time complexity and low throughput. In this paper, an intelligent crawling algorithm based on reinforcement learning, called FICA is proposed that models a random surfing user. The priority for crawling pages is based on a concept we call logarithmic distance. FICA is easy to implement and its time complexity is O(E*logV) where V and E are the number of nodes and edges in the web graph respectively. Comparison of FICA with other proposed algorithms shows that FICA outperforms them in discovering highly important pages. Furthermore, FICA computes the importance (ranking) of each page during the crawling process. Thus, we can also use FICA as a ranking method for computation of page importance. A nice property of FICA is its adaptability to the web in that it adjusts dynamically with changes in the web graph. We have used UK's web graph to evaluate our approach.
Testing the NHS: the tensions between personalized and collective medicine produced by personal genomics in the UK

This study examines direct-to-consumer genetic testing (DTCGT) in the UK using the Social Construction of Technology framework to draw conclusions about how commercial genotyping is being shaped by principal groups involved with the technology. Different tests are available including single nucleotide polymorphism genotyping for ancestry and health information, the latter being the focus of this study. I conducted interviews with DTCGT users, and genetics clinicians who had either been consulted about DTCGT or who were willing to discuss their views. This paper is about one of the study’s three themes, the NHS. DTCGT seemed to provide a point of focus for conflict between personalized and collective medicine in the UK, rather than being its cause. This suggests that DTCGT is more likely to achieve stability by virtue of being superseded by new technologies, rather than by achieving closure.
Prediction of urban passenger transport based-on wavelet SVM with quantum-inspired evolutionary algorithm

Based on least squares wavelet support vector machines (LS-WSVM) with quantum-inspired evolutionary algorithm (QEA), the prediction model of urban passenger transport is proposed , that can provide the theoretical foundation of forecasting passenger volume of urban transport accurately. The prediction model of urban passenger transport is established by using LS-WSVM, whose regularization parameter and kernel parameter are adjusted using quantum-inspired evolutionary algorithm. QEA with quantum chromosome and quantum mutation has better global search capacity. The parameters of LS-WSVM can be adjusted using quantum-inspired evolutionary optimization. Combining with the data of the urban volume of passenger transport of Xipsilaan over years, the prediction model of urban passenger transport is validated, the simulation results indicate that the prediction model is effective, and based on LS-WSVM has more improvement than LS-SVM with Gaussian kernel in predicting precision, and then the improved LS-WSVM with QEA is efficient than with cross-validation method for tuning parameters.
Searching Music in the Emotion Plane

Music plays an important role in human’s history, even more so in the digital age. Never before has such a large collection of music been created and accessed daily by people. Because almost all music is created to convey emotion, music organization and retrieval by emotion is a meaningful way for accessing music information. The proliferation of tiny mobile devices and the like also calls for content-based retrieval of music through a small display space.
ARTIFICIAL INTELIGENCE METHOD USED FOR NANOSCALE POLYMER DESIGNE

This paper deals with the use of Artificial Intelligence Methods (AI) for designing new molecules with desired physical, chemical and biological properties. It is an important and difficult problem in the chemical, material and pharmaceutical industries. Traditional methods involve a laborious and expensive trial-and-error procedure. So, it is of a considerable importance the development of computer-assisted approaches towards the automation of the nano scale molecular design. It simplifies and increases the selectivity of the synthetic processes related to the considered final properties of the polymers/copolymers.
2 7 M ay 2 00 5 Surface-mode microcavity

Novel optical microcavities based on zero-group-velocity surface modes in photonic crystals are proposed and demonstrated. It has been shown that high quality factors can be easily obtained for such microcavities in photonic crystal slabs. With increasing of the cavity length, the quality factor is gradually enhanced and the resonant frequency converges to that of the zero-groupvelocity surface mode in the photonic crystal. Different from a conventional cavity, the number of the resonant modes is fixed despite the cavity length, determined only by the number of surface modes with zero group velocity. ∗Electronic address: min@imit.kth. se
Segregación escolar por origen nacional en España

The aims of this research are to estimate the magnitude of school segregation by national origin in compulsory secondary education in Spain and its Autonomous Communities, and to compare with the results from other countries in the European Union. In order to achieve those aims, we used the PISA-2015 database and estimate the Gorard index. Our results indicate that the magnitude of school segregation by national origin in Spain is 0.45 (below the European average). However, net segregation values reflect a less optimistic image for Spain, from the third country with the least segregation of the European Union, becomes the seventh.
Face recognition based on 4 Dimensions Local Binary Patterns

In face recognition, LBP (Local Binary Patterns) is a very popular method, which can solve the defects of the traditional local feature extraction methods with fixed scale and small extraction scale. However, the LBP operator only describes the relationship between the center pixel and its neighborhood pixels, it ignores the relationship among the operators. 3DLBP (3 Dimensions Local Binary Patterns) operator embodies this relationship to get a better local description. However, both of them neglect the center pixel value, which also reflects some properties of the image points. In this paper, we propose a novel face recognition method based on 4DLBP (4 Dimensions Local Binary Patterns), which adds the pixel value of the center point into the 3DLBP features for face recognition. We firstly partition the face image into small blocks, and then we extract the 4DLBP features of the blocked images, and combine the features to obtain the final facial features. Finally, we use the extreme learning machine (ELM) as classifier to train and classify the face images. The experimental results show the proposed method has better performances than the traditional methods.
Text Region Segmentation From Heterogeneous Images

††† Summary Text in images contains useful information which can be used to fully understand images . This paper proposes an unified method to segment a text region from images such as Scene text images , Caption text & Document images using Contourlet transform . Contourlets not only possess the main features of wavelets (namely, multiscale and time-frequency localization), but also offer a high degree of directionality and anisotropy. It decomposes the image into set of directional sub bands with texture details capture in different orientations at various scales. As the contourlet transform is not shift-invariant , non subsampled contourlet transform NSCT is used here to extract text regions from heterogeneous images. Proposed system is tested on various kind of images & shown promising result .