Miracle-dz/UniFAR-FTUs huggingface dataset:
A Distributed CSP Approach for Solving Multi-agent Planning Problems

Distributed or multi-agent planning extends classical AI planning to domains where several agents can plan and act together. There exist many recent developments in this discipline that range over different approaches for distributed planning algorithms, distributed plan execution processes or communication protocols among agents. One of the key issues about distributed planning is that it is the most appropriate way to tackle certain kind of planning problems, specially those where a centralized solving is infeasible. In this paper we present a new planning framework aimed at solving planning problems in inherently distributed domains where agents have a collection of private data which cannot share with other agents. However, collaboration is required since agents are unable to accomplish its own tasks alone or, at least, can accomplish its tasks better when working with others. Our proposal motivates a new planning scheme based on a distributed search of heuristic information and on a constraint programming resolution process.
A Multimodal Approach to Speaker Diarization on TV Talk-Shows

In this article, we propose solutions to the problem of speaker diarization of TV talk-shows, a problem for which adapted multimodal approaches, relying on other streams of data than only audio, remain largely under exploited. Hence we propose an original system that leverages prior knowledge on the structure of this type of content, especially the visual information relating to the active speakers, for an improved diarization performance. The architecture of this system can be decomposed into two main stages. First a reliable training set is created, in an unsupervised fashion, for each participant of the TV program being processed. This data is assembled by the association of visual and audio descriptors carefully selected in a clustering cascade. Then, Support Vector Machines are used for the classification of the speech data (of a given TV program). The performance of this new architecture is assessed on two French talk-show collections: Le Grand Échiquier and On n'a pas tout dit. The results show that our new system outperforms state-of-the-art methods, thus evidencing the effectiveness of kernel-based methods, as well as visual cues, in multimodal approaches to speaker diarization of challenging contents such as TV talk-shows.
Poleward moving auroral forms (PMAFs) revisited: responses of aurorae, plasma convection and Birkeland currents in the pre- and postnoon sectors under positive and negative IMF B y conditions

Abstract. Using five case studies, we investigate the dynamical evolution of dayside auroral precipitation in relation to plasma convection, classifying it by the IMF By component and position with respect to noon. Auroral observations were made by meridian scanning photometers (MSPs) and an all-sky camera (ASC) in Ny Alesund, Svalbard at 76° MLAT, while the spatial structure of the ionospheric plasma convection is inferred from SuperDARN radars and ion drift observations from spacecraft in polar orbit. The IMF configuration of major interest here is one pointing southward and with a dominant east-west component. Our emphasis is on the auroral phenomenon of PMAFs (poleward moving auroral forms), which are ionospheric signatures of pulsed reconnection at the magnetopause. We distinguish between PMAFs/prenoon and PMAFs/postnoon. These two activities are found to be separated by an auroral form around noon with attenuated emission at 630.0 nm. We document for the first time that this "midday gap aurora" appears in the form of a midday auroral brightening sequence (MABS). We study the PMAF activity consisting of an initial brightening phase and the later stages of PMAF evolution in relation to plasma convection cells, flow vorticity, and precipitation boundaries in the prenoon and postnoon sectors for both By polarities. Flow channels (PIFs) associated with PMAFs are strengthened by polarization effects at auroral boundaries. Addressing the implications of our proposed, extended perspective on dayside auroral morphology under southeast/west IMF for M-I coupling associated with pulsed magnetopause reconnection (FTEs), we draw inferences on the MLT-dependent geoeffectiveness (Birkeland current/auroral intensity) of magnetopause FTEs (subsolar region versus flanks).
Progressive low bit rate coding of simple 3D objects with matching pursuit

Summary form only given. The paper presents a low rate progressive 3D mesh compression scheme for simple, genus-zero 3D objects. The proposed scheme is based on signal representation using redundant expansions on the 2D-sphere. First, generic input data is re-sampled as a function on the 2D-sphere, and the signal value for each point on the regular grid is obtained by performing nearest neighbor interpolation within four points from the initial 3D model. The model representation is then constructed using a matching pursuit algorithm, with an over-complete dictionary of atoms, defined on a sphere. In order to capture the particular characteristics of the 3D models efficiently, we propose a dictionary construction based on two generating functions, a Gaussian to capture low-frequency components, and a modified combination of a Gaussian and its second derivative to capture high-frequency components of the input signal. Compared to state-of-the-art encoders, our method has been shown to offer very good compression efficiency, but the performance is limited by the resampling step that maps the input model on the 2D-sphere. Matching pursuit has, however, the advantage of providing an intrinsically progressive scheme, that is also very flexible.
Big steps toward understanding dynein

Dynein is a microtubule-based molecular motor that is involved in various biological functions, such as axonal transport, mitosis, and cilia/flagella movement. Although dynein was discovered 50 years ago, the progress of dynein research has been slow due to its large size and flexible structure. Recent progress in understanding the force-generating mechanism of dynein using x-ray crystallography, cryo-electron microscopy, and single molecule studies has provided key insight into the structure and mechanism of action of this complex motor protein.
Steganalysis: Using the blind deconvolution to retrieve the hidden data

Steganography has gained a substantial attention due to its application in wide areas. Steganography as it literally mean is hiding the information (stego data) inside the data (communication data) so that the receiver can only extract the desired information from the data. Steganalysis is the reverse process of steganography in which the information about the original data is hardly available, from the received data the extractor needs to identify the original data. Since this belong to a class of inverse problems it is hard to find the approximate match of the original data from the received one. In most of the cases this will fall under the category of ill-posed problems. The stego-data that has been embedded into the communication data can be considered as linear bounded operator operating on the input data and the reverse process (the Steganalysis) can be thought like a deconvolution problem by which we can extract the original data. Here we are assuming the watermarking as a linear operation with a bounded linear operator K : X→Y where X and Y are spaces of Bounded Variation (BV). The forward problem (the Steganography) is a direct convolution and the reverse (backward) problem (steganalysis) is a de-convolution procedure. In this work we are embedding a Gaussian random variable array with zero mean and with a specific variance into the data and we show how the original data can be extracted using the regularization method. The results are shown to substantiate the ability of the method to perform steganalysis.
Physiological control of low-dimensional glottal models with applications to voice source parameter matching

This study explores the possibility for physical models of the glottis to accurately reproduce target glottal flow waveforms. A set of rules is proposed for controlling a two-mass physical model through activation levels of laryngeal muscles. The proposed rules convert muscle activities into physical quantities such as fold adduction, mass, thickness, depth, stiffness. Numerical simulations of the glottal model, controlled through this set of rules, are used in order to construct a codebook between muscular activations and a set of relevant acoustic parameters of the voice source, such as foundamental frequency, open quotient, speed quotient, and return quotient. The paper explores the potentialities of the derived codebook for the control of the glottal model, and its applications to voice source parameter matching. A fitting procedure is developed, and it is shown that the parameters of the physiologically-controlled two-mass model can be matched to fit target signals (glottal flow pulses) with good accuracy.
TCP/ICN: Carrying TCP over Content Centric and Named Data Networks

Today's Internet applications and protocols are not compatible with Information Centric Networking (ICN) protocols and there is no straightforward way of rapidly switching protocol architectures. Network operators incrementally deploying an ICN infrastructure will have to provide compatibility with existing TCP/IP applications and manage co-existence of IP and ICN networks. One approach to co-existence is to allow TCP and the applications using it to work transparently over an ICN substrate instead of over IP. This paper presents a TCP/ICN proxy capable of carrying TCP traffic between TCP/IP endpoints over ICN network. The main challenge for this approach to co-existence is transforming the TCP push model to the ICN pull model. We evaluated several alternative TCP/ICN proxy designs in a simulation environment. We chose the most promising of these designs and developed a proof-of-concept *nix implementation. Performance measurements of both simulation and real implementation demonstrate that with our proxy design TCP can traverse ICN networks without significant additional delay or loss of goodput.
Quantitative genetic variance in experimental fly populations evolving with or without environmental heterogeneity

Heterogeneous environments are typically expected to maintain more genetic variation in fitness within populations than homogeneous environments. However, the accuracy of this claim depends on the form of heterogeneity as well as the genetic basis of fitness traits and how similar the assay environment is to the environment of past selection. Here, we measure quantitative genetic (QG) variance for three traits important for fitness using replicated experimental populations of Drosophila melanogaster evolving under four selective regimes: constant salt‐enriched medium (Salt), constant cadmium‐enriched medium (Cad), and two heterogeneous regimes that vary either temporally (Temp) or spatially (Spatial). As theory predicts, we found that Spatial populations tend to harbor more genetic variation than Temp populations or those maintained in a constant environment that is the same as the assay environment. Contrary to expectation, Salt populations tend to have more genetic variation than Cad populations in both assay environments. We discuss the patterns for QG variances across regimes in relation to previously reported data on genome‐wide sequence diversity. For some traits, the QG patterns are similar to the diversity patterns of ecological selected SNPs, whereas the QG patterns for some other traits resembled that of neutral SNPs.
Wireless sensor networks: Routing protocols and security issues

Wireless Sensor Network (WSN) is a wireless network consists of large number of sensor nodes. Routing protocols are used for communication in the network. Routing protocols discover the appropriate path to transmit the data and maintain the routes in the network. Many routing techniques in WSNs have been proposed. But without security, the use of these protocols becomes limited. Providing a secure communication between nodes is also an important task. In this paper, the classification of routing protocols with comparison is analyzed. This paper also study the various security threats on routing protocols of wireless sensor networks and some defense techniques are also mentioned.
Transforming Adult Social Care: Contemporary Policy and Practice

Introduction History of Adult Social Care Contemporary issues in Adult Social Care Governance of Adult Social Care Personalisation in Adult Social Care Integration of Health and Social Care Unpaid Carers and Adult Social Care Provision The Paid Adult Social Care Workforce Public and User Involvement Regulatory Frameworks, Inspection and Safeguarding Conclusions.
Desajuste educativo y movilidad laboral en España

Este articulo estudia las relaciones entre el desajuste educativo y la movili-dad laboral. Tras abordarse los aspectos teoricos de dicha relacion, se aportan datos sobre el desajuste educativo existente en el mercado de trabajo espanol y se realiza una investigacion empirica mediante la estimacion de un modelo de duracion (del tiempo de permanencia en una empresa). Al contrario que en Alba ( 1993), no se encuentra evidencia que apoye la prediccion del mode-lo neoclasico de desajuste educativo como fenomeno transitorio en el merca-do de trabajo espanol. Mas bien, los resultados indican que en Espana existe un desajuste permanente entre el sistema educativo y el mercado de trabajo. El analisis se lleva a cabo con una base de datos relativamente nueva, la Encuesta de Estructura, Conciencia y Biograffa de Clase (ECBC) realizada en Espana en 1991.
Competing Premarital Investment

This paper studies pre-marital parental investments in their children’s wealth where spousal wealth is a public good in marriage. By investing in their children’s wealth, parents increase the wealth of their children and the quality of the spouses that their children can marry. In large marriage markets, the hedonic return to investment internalizes all the external benefits of pre-marital investment in wealth so that the competitive equilibrium is efficient. Marriage market competition also increases investments in small marriage markets relative to no competition, but equilibrium investments are not efficient.
Cross-Genre Age and Gender Identification in Social Media

This paper gives a brief description on the methods adopted for the task of author-profiling as part of the competition PAN 2016 [1]. Author profiling is the task of predicting the author’s age and gender from his/her writing. In this paper, we follow a two-level ensemble approach to tackle the cross-genre author profiling task where training documents and testing documents are from different genres. We use the softvoting approach to build the classification ensemble. To include various feature sets, we first train logistic regression models using the extracted word n-gram, character n-gram, and part-of-speech n-gram features for each genre. We then ensemble single-genre predictive models trained on the blog, social media and Twitter data sources, to build our multi-genre ensemble approach. The experimental results indicate that our approach performs well in both single-genre and cross-genre author profiling tasks.
Increases in extracellular dopamine in the nucleus accumbens by cocaine are inversely related to basal levels: effects of acute and repeated administration

Repeated administration of cocaine enhances several of the behavioral and neurochemical responses to subsequent cocaine injections, an effect that has been attributed, in part, to decreased somatodendritic autoreceptor sensitivity of mesocorticolimbic dopamine (DA) neurons. Such changes in autoregulation may not only modify the direct effects of cocaine on extracellular DA levels but also result in tonically increased basal DA release in the terminal areas of the mesocorticolimbic DA system. The present study was therefore designed to investigate the effects of repeated cocaine administration on basal extracellular DA concentrations in the nucleus accumbens (NAC) using in vivo microdialysis procedures in halothane-anesthetized rats. We subsequently examined the relationship between basal DA levels and the increase in extracellular DA produced by an acute injection of cocaine, and determined whether this relationship was altered by prior, repeated exposure to cocaine. Rats received one daily intraperitoneal injection of cocaine (30 mg/kg) or its vehicle (saline) for 10 consecutive days. On days 1, 3, or 7 after termination of the repeated cocaine treatment, extracellular DA levels in the NAC were determined under basal conditions and following a single intraperitoneal cocaine challenge injection (10 mg/kg) in separate groups of rats. Repeated cocaine administration produced a substantial increase in basal DA release in the NAC that was most prominent on day 1 post-cocaine (mean +/- SEM: 10.7 +/- 2.55 nM vs 3.55 +/- 0.56 nM) but was no longer apparent on day 7 post-cocaine. Higher extracellular DA levels were also observed after cocaine challenge in rats that received repeated cocaine treatments. Similar to the increase in basal release, this effect was most pronounced on day 1 post-cocaine (23.6 +/- 4.36 nM vs 12.61 +/- 1.76 nM) but did not persist through day 7 post-cocaine. (ABSTRACT TRUNCATED AT 250 WORDS)
A Profit-Aware Virtual Machine Deployment Optimization Framework for Cloud Platform Providers

As a rising application paradigm, cloud computing enables the resources to be virtualized and shared among applications. In a typical cloud computing scenario, customers, Service Providers (SP), and Platform Providers (PP) are independent participants, and they have their own objectives with different revenues and costs. From PPs' viewpoints, much research work reduced the costs by optimizing VM placement and deciding when and how to perform the VM migrations. However, some work ignored the fact that the balanced use of the multi-dimensional resources can affect overall resource utilization significantly. Furthermore, some work focuses on the selection of the VMs and the target servers without considering how to perform the reconfigurations. In this paper, with a comprehensive consideration of PPs' interests, we propose a framework to improve their profits by maximizing the resource utilization and reducing the reconfiguration costs. Firstly, we use the vector arithmetic to model the objective of balancing the multi-dimensional resources use and propose a VM deployment optimization method to maximize the resource utilization. Then a two-level runtime reconfiguration strategy, including local adjustment and VM parallel migration, is presented to reduce the VM migration and shorten the total migration time. Finally, we conduct some preliminary experiments, and the results show that our framework is effective in maximizing the resource utilization and reducing the costs of the runtime reconfiguration.
On Optimal Filter Designs for Fundamental Frequency Estimation

Recently, we proposed using Capon's minimum variance principle to find the fundamental frequency of a periodic waveform. The resulting estimator is formed such that it maximizes the output power of a bank of filters. We present an alternative optimal single filter design and then proceed to quantify the similarities and differences between the estimators using asymptotic analysis and Monte Carlo simulations. Our analysis shows that the single filter can be expressed in terms of the optimal filterbank and that the methods are asymptotically equivalent but generally different for finite length signals.
Tumor Clustering Using Nonnegative Matrix Factorization With Gene Selection

Tumor clustering is becoming a powerful method in cancer class discovery. Nonnegative matrix factorization (NMF) has shown advantages over other conventional clustering techniques. Nonetheless, there is still considerable room for improving the performance of NMF. To this end, in this paper, gene selection and explicitly enforcing sparseness are introduced into the factorization process. Particularly, independent component analysis is employed to select a subset of genes so that the effect of irrelevant or noisy genes can be reduced. The NMF and its extensions, sparse NMF and NMF with sparseness constraint, are then used for tumor clustering on the selected genes. A series of elaborate experiments are performed by varying the number of clusters and the number of selected genes to evaluate the cooperation between different gene selection settings and NMF-based clustering. Finally, the experiments on three representative gene expression datasets demonstrated that the proposed scheme can achieve better clustering results.
Prevalence and Correlates of Sex Trafficking among Homeless and Runaway Youths Presenting for Shelter Services

The study reported in this article assessed prevalence and demographic correlates of sex trafficking in a purposive sample of 270 young people experiencing homelessness in three U.S. cities (Philadelphia; Phoenix; and Washington, DC) and at five host agencies. Participants were 57% male, 38% female, 4% transgender, and 1% other. The average age of participants was 20.7 years (SD = 2.0 years). The majority of the participants were African American (56%), followed by white (14%) and multiracial (14%). The Human Trafficking Interview and Assessment Measure detected that nearly one in five young people were victims of sex trafficking, either due to force, fraud, or coercion (FFC); age; or both. Those who were sex trafficked were more likely than those who were not sex trafficked to be female, sexual minorities, or Latino and to have either dropped out of high school or obtained a GED. Differences between being trafficked due to FFC and being trafficked due to age were also investigated. Findings support the need for development of targeted prevention and intervention efforts for young people experiencing homelessness that address sex trafficking victimization and related risk factors.
Model Fusion via a Master Fuzzy System with Special Application to Engineering Materials

Abstract To improve the modelling performance, one should either propose new modelling methodologies or make the best of existing models. In this paper, the study is concentrated on the latter solution, where a structure-free modelling paradigm is proposed to combine various modelling techniques in ‘symbiosis’ using a ‘master fuzzy system'. This approach is shown to be able to include the advantages of different modelling techniques altogether by minimising efforts relating optimisation of final structure. The proposed approach is then successfully applied to predict machining induced residual stresses for aerospace alloy components as well as mechanical properties of heat-treated alloy steels.
Exploring gender prediction from digital handwriting

This paper introduces an empirical investigation which directly addresses and explores gender prediction capacity from digitised handwriting data from several different perspectives - such as feature type (static/dynamic) and content (fixed/variable) types - in order to provide extensive experimental evidence and analysis to guide the development of a better understanding of the opportunities for and practical consequences of gender prediction from digital handwriting data.