Miracle-dz/UniFAR-FTUs huggingface dataset:
Approximate Geometric Query Tracking over Distributed Streams

Effective Big Data analytics pose several difficult challenges for modern data management architectures. One key such challenge arises from the naturally streaming nature of big data, which mandates efficient algorithms for querying and analyzing massive, continuous data streams (that is, data that is seen only once and in a fixed order) with limited memory and CPU-time resources. Such streams arise naturally in emerging large-scale event monitoring applications; for instance, network-operations monitoring in large ISPs, where usage information from numerous sites needs to be continuously collected and analyzed for interesting trends. In addition to memoryand time-efficiency concerns, the inherently distributed nature of such applications also raises important communication-efficiency issues, making it critical to carefully optimize the use of the underlying network infrastructure. In this paper, we provide a brief introduction to the distributed data streaming model and the Geometric Method (GM), a generic technique for effectively tracking complex queries over massive distributed streams. We also discuss several recently-proposed extensions to the basic GM framework, such as the combination with streamsketching tools and local prediction models, as well as more recent developments leading to a more general theory of Safe Zones and interesting connections to convex Euclidean geometry. Finally, we outline various challenging directions for future research in this area.
Adaptive color image compression based on visual attention

This paper reports an adaptive still color image compression method which produces automatically selected ROI with a higher reconstruction quality with respect to the rest of the input image. The ROI are generated on-the fly with a purely data-driven technique based on visual attention. Inspired from biological vision, the multicue visual attention algorithm detects the most visually salient regions of an image. Thus, when operating in systems with low bit rate constraints, the adaptive coding scheme favors the allocation of a higher number of bits to those image regions that are more conspicuous to the human visual system. The compressed image files produced by this adaptive method are fully compatible with the JPEG standard, which favors their widespread utilization.
Impact of Role-play Activity on Evolution of Cohesion among Students with Specific Language Impairment

In the present study we aimed to evaluate the effect of role-play on group cohesion among students with specific language impairmentt. This pre and post-test study rely on role-play and primarily based on two standardized assessment methods. Twelve students with specific language impairment were participated. After twenty-seven sessions of role-play, group cohesion index and sociometric scale were established and carried out accordingly. The results characterized as statistically significant. This study laid useful groundwork for the future implementation of role-play that may provide additional insights into group cohesion of children with specific language impairment research.
A Coarse-Grained Pessimistic Message Logging Scheme for Improving Rollback Recovery Efficiency

As a common technology for fault tolerance and load balance, rollback-recovery faces the challenges of scalability and inherent variability in those long-running large-scale applications with grids as the computing infrastructure. Among the rollback recovery schemes, pessimistic message logging protocols (PMLPs) and coordinated checkpointing protocols (CCPs) are the most popular in practice. Although PMLPs are good in scalability, their fault-free overhead sometimes is prohibitive. CCPs introduce relatively lower overhead, but they are poor in scalability. This work employs partition strategy and introduces the concept of pessimism grain to rollback recovery, striking a balance between good scalability and acceptable overhead. For a partitioned system, a coarse-grained pessimistic message-logging protocol is proposed to achieve scalability and asynchrony both in fault-free execution and in fault recovery. The impact of pessimism grain on the performance is evaluated theoretically. Experimental results show that the pessimism grain is one of the key configuration parameters to reach a desired performance level.
Characterization of Entamoeba histolytica Intermediate Subunit Lectin-Specific Human Monoclonal Antibodies Generated in Transgenic Mice Expressing Human Immunoglobulin Loci

ABSTRACT Four fully human monoclonal antibodies (MAbs) to Entamoeba histolytica intermediate subunit lectin (Igl) were prepared in XenoMouse mice, which are transgenic mice expressing human immunoglobulin loci. Examination of the reactivities of these MAbs to recombinant Igl1 and Igl2 of E. histolytica showed that XEhI-20 {immunoglobulin G2(κ) [IgG2(κ)]} and XEhI-28 [IgG2(κ)] were specific to Igl1, XEhI-B5 [IgG2(κ)] was specific to Igl2, and XEhI-H2 [IgM(κ)] was reactive with both Igls. Gene analyses revealed that the VH and VL germ lines were VH3-48 and L2 for XEhI-20, VH3-21 and L2 for XEhI-28, VH3-33 and B3 for XEhI-B5, and VH4-4 and A19 for XEhI-H2, respectively. Flow cytometry analyses showed that the epitopes recognized by all of these MAbs were located on the surfaces of living trophozoites. Confocal microscopy demonstrated that most Igl1 and Igl2 proteins were colocalized on the surface and in the cytoplasm, but different localization patterns in intracellular vacuoles were also present. The preincubation of trophozoites with XEhI-20, XEhI-B5, and XEhI-H2 caused significant inhibition of the adherence of trophozoites to Chinese hamster ovary cells, whereas preincubation with XEhI-28 did not do so. XEhI-20, XEhI-B5, and XEhI-H2 were injected intraperitoneally into hamsters 24 h prior to intrahepatic challenge with E. histolytica trophozoites. One week later, the mean abscess size in groups injected with one of the three MAbs was significantly smaller than that in controls injected with polyclonal IgG or IgM isolated from healthy humans. These results demonstrate that human MAbs to Igls may be applicable for immunoprophylaxis of amebiasis.
A Gate-Controlled Bidirectional Spin Filter Using Quantum Coherence

We demonstrate a quantum coherent electron spin filter by directly measuring the spin polarization of emitted current. The spin filter consists of an open quantum dot in an in-plane magnetic field; the in-plane field gives the two spin directions different Fermi wavelengths resulting in spin-dependent quantum interference of transport through the device. The gate voltage is used to select the preferentially transmitted spin, thus setting the polarity of the filter. This provides a fully electrical method for the creation and detection of spin-polarized currents. Polarizations of emitted current as high as 70% for both spin directions (either aligned or anti-aligned with the external field) are observed.
Scalable Chord-Based, Cluster-Enhanced Peer-to-Peer Architecture Supporting Range Queries

Over the Internet today, computing and communications environments are more complex and chaotic than classical distributed systems, lacking any centralized organization or hierarchical control. Peer-to-Peer network overlays provide a good substrate for creating large-scale data sharing, content distribution and application-level multicast applications. We present a scalable, cluster-enhanced P2P overlay network designed to share large sets of replicated distributed objects in the context of large-scale highly dynamic infrastructures. The system extends an existing architecture with an original solution designed to achieve optimal implementation results for range queries, as well as provide a fault-tolerant substrate. It also optimizes message routing in hop-count and throughput, whilst providing an adequate consistency among replicas.
A study on the importance of selection pressure and low dimensional weak learners to produce robust ensembles

Ensembles of classifiers have been studied for some time. It is widely known that weak learners should be accurate and diverse. However, in the real world there are many constraints and few have been said about the robustness of ensembles and how to develop it. In the context of random subspace methods, this paper addresses the question of developing ensembles to face problems under time constraints. Experiments show that selecting weak learners based on their accuracy can be used to create robust ensembles. Thus, the selection pressure in ensembles is a key technique to create not just effective ensembles but also robust ones. Moreover, the experiments motivate further research on ensembles made of low dimensional classifiers which achieve general accurate results.
Hybrid differential evolution method for the mixed H2/H&#8734;robust control problem under pole assignment

This paper is concerned with the mixed H2/H∞control problem combined with robust pole placement in linear matrix inequality (LMI) regions. Based on Differential Evolution algorithms (DEs), Salomon's Evolutionary Gradient Search method (EGS) and LMIs, a hybrid algorithm is presented for numerical computation of a robus fixed-order, static or dynamic, output feedback controller. This approach does not require that all speciacations are enforced by a single closed-loop Lyapunov function. This allows to reduce the conservatism of the usual existin methods. This approach can be used for synthesis of reduced or full order controllers. Examples borrowed from the literature are discussed to validate this approach.
On the Evolution of Pulsar Beams

We have analysed polarization data for a large number of isolated pulsars to investigate the evolution of pulsar radio beams. Assuming that a circular beam is directed along the axis of a dipolar magnetic field, we demonstrate that the distribution of magnetic inclination angles for the parent population of all pulsars is not flat but highly concentrated towards small inclination angles and that, consequently, the average beaming fraction is only ∼ 10 per cent. Furthermore, we find that there is a tendency for the beam axis to align with the rotational axis on a time-scale of ∼ 107 yr. This has interesting consequences for statistical studies of the pulsar population. Finally, the luminosity of pulsars is shown to be independent of the impact parameter, which indicates that pulsar beams are sharp-edged and have a relatively flat integrated intensity distribution.
The life of norms : a critical assessment of the construction and diffusion of the race anti-discrimination norm

This thesis examines the genesis and evolution of the anti-discrimination norm directed at race and ethnicity. The thesis seeks to answer: how is the antidiscrimination norm linked to race and ethnicity produced and diffused transnationally and how is it internalised in domestic institutions and government practices? The inquiry mainly assesses the constructivist model of the norm life cycle proposed by Martha Finnemore and Kathryn Sikkink. The model presents the development of international norms as a process that consists of three stages: emergence, cascading and domestic internalisation driven by three different sets of actors who employ different mechanisms to bring about normative change. The thesis investigates and ultimately challenges certain assumptions of the proposed model by examining the factors that account for the construction and domestic institutionalisation of the racial anti-discrimination norm in five contexts – the USA (First and Second Reconstruction periods, 1865-1877 and 1954-1975), the UK (1960s-1970s), the EU (1990s-2000s), the Czech Republic (1990s- present) and Hungary (1990s-present). It uses process tracing to re-consider and problematise the model’s claims about the primary agents that drive the production and the institutionalisation of the anti-discrimination norm in each of the five cases, their motives and the mechanisms they employ to facilitate normative change. The thesis disputes several of the main assumptions of Finnemore and Sikkink’s model. The findings demonstrate that national political elites are a key factor that determines the progress of the racial anti-discrimination norm in each stage of the norm life cycle model. They also problematise the ideational basis for the motives of norm entrepreneurs, which, in fact, consist of a complex mixture of ideational and instrumental considerations. The thesis further develops the stages of the norm life cycle model. It challenges the overall design of the model and its assumed linear progression of norm evolution.
Nourseothricin N-Acetyl Transferase: A Positive Selection Marker for Mammalian Cells

Development of Nourseothricin N-acetyl transferase (NAT) as a selection marker for mammalian cells is described. Mammalian cells are acutely susceptible to Nourseothricin, similar to the widely used drug Puromycin, and NAT allows for quick and robust selection of transfected/transduced cells in the presence of Nourseothricin. NAT is compatible with other selection markers puromycin, hygromycin, neomycin, blasticidin, and is a valuable addition to the repertoire of mammalian selection markers.
Collaborative Signal and Information Processing for Target Detection with Heterogeneous Sensor Networks

In this paper, an approach for target detection and acquisition with heterogeneous sensor networks through strategic resource allocation and coordination is presented. Based on sensor management and collaborative signal and information processing, low-capacity low-cost sensors are strategically deployed to guide and cue scarce highperformance sensors in the network to improve the data quality, with which the mission is eventually completed more efficiently with lower cost. We focus on the problem of designing such a network system in which issues of resource selection and allocation, system behavior and capacity, target behavior and patterns, the environment, and multiple constraints such as the cost must be addressed simultaneously. Simulation results offer significant insight into sensor selection and network operation, and demonstrate the great benefits introduced by guided search in an application of hunting down and capturing hostile vehicles on the battlefield.
Jointly Feature Learning and Selection for Robust Tracking via a Gating Mechanism

To achieve effective visual tracking, a robust feature representation composed of two separate components (i.e., feature learning and selection) for an object is one of the key issues. Typically, a common assumption used in visual tracking is that the raw video sequences are clear, while real-world data is with significant noise and irrelevant patterns. Consequently, the learned features may be not all relevant and noisy. To address this problem, we propose a novel visual tracking method via a point-wise gated convolutional deep network (CPGDN) that jointly performs the feature learning and feature selection in a unified framework. The proposed method performs dynamic feature selection on raw features through a gating mechanism. Therefore, the proposed method can adaptively focus on the task-relevant patterns (i.e., a target object), while ignoring the task-irrelevant patterns (i.e., the surrounding background of a target object). Specifically, inspired by transfer learning, we firstly pre-train an object appearance model offline to learn generic image features and then transfer rich feature hierarchies from an offline pre-trained CPGDN into online tracking. In online tracking, the pre-trained CPGDN model is fine-tuned to adapt to the tracking specific objects. Finally, to alleviate the tracker drifting problem, inspired by an observation that a visual target should be an object rather than not, we combine an edge box-based object proposal method to further improve the tracking accuracy. Extensive evaluation on the widely used CVPR2013 tracking benchmark validates the robustness and effectiveness of the proposed method.
Defocus map estimation from a single image using principal components

Light is a mixture of multiple spectral components. An image is a response of the scene with respect to these spectra. Principal components are more compact representation of the data compared to any other representations. Hence accuracy of the estimated defocus parameter is higher in principal component representation than any other customary used representations. In this paper, we present comparison between principal component representation and customary gray scale representation for depth map creation. The presented results shows that the depth maps obtained using principal component are smoother than depth maps obtained using gray scale representation. Besides that, the noise estimation using principal components is much more accurate than using Wiener strategy.
Filtration of interstellar hydrogen in the two‐shock heliospheric interface: Inferences on the local interstellar cloud electron density

The solar system is moving through the partially ionized local interstellar cloud (LIC). The ionized matter of the LIC interacts with the expanding solar wind forming the heliospheric interface. The neutral component (interstellar atoms) penetrates through the heliospheric interface into the heliosphere, where it is measured directly in situ' as pick-up ions and neutral atoms (and as anomalous cosmic rays) or indirectly through resonant scattering of solar Ly α. When crossing the heliospheric interface, interstellar atoms interact with the plasma component through charge exchange. This interaction leads to changes of both neutral gas and plasma properties. The heliospheric interface is also the source of radio emissions which have been detected by the Voyager since 1983. In this paper, we have used a kinetic model of the flow of the interstellar atoms with updated values of velocity, temperature, and density of the circumsolar interstellar hydrogen and calculated how all quantities which are directly associated to the observations vary as a function of the interstellar proton number density n p,LIC These quantities are the degree of filtration, the temperature and the velocity of the interstellar H atoms in the inner heliosphere, the distances to the bow shock (BS), heliopause, and termination shock, and the plasma frequencies in the LIC, at the BS and in the maximum compression region around the heliosphere which constitutes the barrier' for radio waves formed in the interstellar medium. Comparing the model results with recent pickup ion data, Ly α measurements, and low-frequencies radio emissions, we have searched for a number density of protons in the local interstellar cloud compatible with all observations. We find it difficult in the frame of this model without interstellar magnetic field to reconcile the distance to the shock and heliopause deduced from the time delay of the radio emissions with other diagnostics and discuss possible explanations for these discrepancies, as the existence of an additional interstellar magnetic pressure (2.1 μG < B < 4 μG for a perpendicular magnetic field). We also conclude that on the basis of this model the most likely value for the proton density in the local interstellar cloud is in the range 0.04 cm -3 < n p,LIC < 0.07 cm -3 .
Adaptive Tracking Control for Robots with Unknown Kinematic and Dynamic Properties

It has been almost two decades since the first globally tracking convergent adaptive controllers were derived for robot with dynamic uncertainties. However, the problem of concurrent adaptation to both kinematic and dynamic uncertainties has never been systematically solved. This is the subject of this paper. We derive a new adaptive Jacobian controller for trajectory tracking of robot with uncertain kinematics and dynamics. It is shown that the robot endeffector is able to converge to a desired trajectory with the uncertain kinematics and dynamics parameters being updated online by parameter update laws. The algorithm requires only to measure the end-effector position, besides the robot's joint angles and joint velocities. The proposed controller can also be extended to adaptive visual tracking control with uncertain camera parameters, taking into consideration the uncertainties of the nonlinear robot kinematics and dynamics. Experimental results are presented to illustrate the performance of the proposed controllers. In the experiments, we demonstrate that the robot's shadow can be used to control the robot.
Modelling Composite Emotions in Affective Agents

It is important for artificial agents to accurately infer human emotions in order to provide believable interactions. However, there is currently a lack of empirical results supporting affective agent to propose effective computational models for this purpose through analyzing individual profile information and the interaction outcomes. In this paper, we bridge this gap with a game-based empirical study. We propose a general model for interactions between an agent and a user in competitive game settings. Based on results from over 450 players in over 2,500 game sessions, we construct a regression model using a player's education level, age, gender and the interaction outcome as explanatory factors to compute his/her composite emotions consisting of the six basic emotions.
Algebraic lattice codes achieve the capacity of the compound block-fading channel

We propose a lattice coding scheme that achieves the capacity of the compound block-fading channel. Our lattice construction exploits the multiplicative structure of number fields and their group of units to absorb ill-conditioned channel realizations. To shape the constellation, a discrete Gaussian distribution over the lattice points is applied. A by-product of our results is a refined analysis of the probability of error of the lattice Gaussian distribution in the AWGN channel.
A specific role for hippocampal mossy fiber's zinc in rapid storage of emotional memories

We investigated the specific role of zinc present in large amounts in the synaptic vesicles of mossy fibers and coreleased with glutamate in the CA3 region. In previous studies, we have shown that blockade of zinc after release has no effect on the consolidation of spatial learning, while zinc is required for the consolidation of contextual fear conditioning. Although both are hippocampo-dependent processes, fear conditioning to the context implies a strong emotional burden. To verify the hypothesis that zinc could play a specific role in enabling sustainable memorization of a single event with a strong emotional component, we used a neuropharmacological approach combining a glutamate receptor antagonist with different zinc chelators. Results show that zinc is mandatory to allow the consolidation of one-shot memory, thus being the key element allowing the hippocampus submitted to a strong emotional charge to switch from the cognitive mode to a flashbulb memory mode. Individual differences in learning abilities have been known for a long time to be totally or partially compensated by distributed learning practice. Here we show that contextual fear conditioning impairments due to zinc blockade can be efficiently reduced by distributed learning practice.
Direction estimation of walking people using a single image

Motivation: Being able to estimate the walking direction of people would be usuful for many applications such as autonomous cars and robots. For these applications, it is necessary to recognize the surrounding environments in order to avoid collisions with people. We consider walking direction estimation to be one of challenging topics in this area. In this project we do not consider the detection of people in images and assume that they have been already detected.