Miracle-dz/UniFAR-FTUs huggingface dataset:
The Examination of White Matter Microstructure, Autism Traits, and Social Cognitive Abilities in Neurotypical Adults

The purpose of this study was to examine the relationships among mentalizing abilities, self-reported autism traits, and two white matter tracts, uncinate fasciculus (UF) and inferior longitudinal fasciculus (ILF), in neurotypical adults. UF and ILF were hypothesized to connect brain regions implicated in a neuroanatomical model of mentalizing. Data were available for 24 neurotypical adults (mean age = 21.92 (4.72) years; 15 women). Tract-based spatial statistics (TBSS) was used to conduct voxelwise cross-participant comparisons of fractional anisotropy (FA) values in UF and ILF as predicted by mentalizing abilities and self-reported autism traits. Self-reported autism traits were positively related to FA values in left ILF. Results suggest that microstructural differences in left ILF are specifically involved in the expression of subclinical autism traits in neurotypical individuals. INDEX WORDS: Diffusion tensor imaging, Mentalizing, Theory of mind, Uncinate fasciculus, Inferior longitudinal fasciculus THE EXAMINATION OF WHITE MATTER MICROSTRUCTURE, AUTISM TRAITS, AND SOCIAL COGNITIVE ABILITIES IN NEUROTYPICAL ADULTS
Intuition and Curriculum: From Precognition to Agency

concrete. Because an intuitive curriculum engenders a variety of individual interests among many students in the same milieu, it is hoped that this exposure to divergence demonstrates open-mindedness and consideration. That is, that students embrace resonance in learning, but realize the learning process is never concluded and to beware of the antipodal certainty that is also found in racism, stereotyping, and dogmatism. Providing Opportunities for Joy Liston (2001) uses the metaphor of Joy to symbolize the convergence of knowledge, curricular fields, human spirit, and community. She goes beyond the simple definition of joy as happiness to include the notions of possibility and compassion (p. 21).
A linear space algorithm for computing the hermite normal form

Computing the Hermite Normal Form of an <i>n</i> × <i>n</i> integer matrix using the best current algorithms typically requires <i>&Ogr;</i>(<i>n</i><sup>3</sup> log <i>M</i>) space, where <i>M</i> is a bound on the entries of the input matrix. Although polynomial in the input size (which is <i>&Ogr;</i>(<i>n</i><sup>2</sup> log <i>M</i>)), this space blow-up can easily become a serious issue in practice when working on big integer matrices. In this paper we present a new algorithm for computing the Hermite Normal Form which uses only <i>&Ogr;</i>(<i>n</i><sup>2</sup> log <i>M</i>) space (i.e., essentially the same as the input size). When implemented using standard algorithms for integer and matrix multiplication, our algorithm has the same time complexity of the asymptotically fastest (but space inefficient) algorithms. We also present a heuristic algorithm for HNF that achieves a substantial speedup when run on randomly generated input matrices.
Distributed Pricing Power Control for Downlink Co-tier Interference Coordination in Two-Tier Heterogeneous Networks

In this paper, we consider distributed power control schemes for downlink co-tier interference coordination in a two-tier heterogeneous network consisting of multiple femtocells under the coverage of a macrocell. We formulate a non cooperative game in order to solve this problem. First we propose an algorithm in which all femto access point simultaneously update their transmit power to maximize their individual payoff function according to a dynamic best response function. Numerical results show that in this non-cooperative game, all femtocells' transmit power converges quickly to Nash equilibrium points. Second, we develop a novel dynamic pricing power control scheme by using the update mechanism named gradient play to update the transmission powers of all femtocells. Numerical results show that the second proposal can attain lower transmission power but higher throughput in comparison with our first proposal, and both proposals outperform the conventional power control schemes.
The DNA Architectural Protein HMGB1 Facilitates RTA-Mediated Viral Gene Expression in Gamma-2 Herpesviruses

ABSTRACT Replication and transcription activator (RTA), an immediate-early gene product of gamma-2 herpesviruses including Kaposi's sarcoma-associated herpesvirus (KSHV) and murine gamma herpesvirus 68 (MHV-68), plays a critical role in controlling the viral life cycle. RTA acts as a strong transcription activator for several downstream genes of KSHV and MHV-68 through direct DNA binding, as well as via indirect mechanisms. HMGB1 (also called HMG-1) protein is a highly conserved nonhistone chromatin protein with the ability to bind and bend DNA. HMGB1 protein promoted RTA binding to different RTA target sites in vitro, with greater enhancement to low-affinity sites than to high-affinity sites. Box A or box B and homologues of HMGB1 also enhanced RTA binding to DNA. Transient transfection of HMGB1 stimulated RTA transactivation of RTA-responsive promoters from KSHV and MHV-68. Furthermore, MHV-68 viral gene expression, as well as viral replication, was significantly reduced in HMGB1-deficient cells than in the wild type. This abated viral gene expression was partially restored by HMGB1 transfection into HMGB1−/− cells. These results suggest an important function of the DNA architectural protein, HMGB1, in RTA-mediated gene expression, as well as viral replication in gamma-2 herpesviruses.
Survey on approaches to speech recognition in reverberant environments

This paper overviews the state of the art in reverberant speech processing from the speech recognition viewpoint. First, it points out that the key to successful reverberant speech recognition is to account for long-term dependencies between reverberant observations obtained from consecutive time frames. Then, a diversity of approaches that exploit the long-term dependencies in various ways is described, ranging from signal and feature dereverberation to acoustic model compensation tailored to reverberation. A framework for classifying those approaches is presented to highlight similarities and differences between them.
He II Recombination Lines from the First Luminous Objects

The hardness of the ionizing continuum from the first sources of UV radiation plays a crucial role in the reionization of the intergalactic medium (IGM). While usual stellar populations have soft spectra, miniquasars or metal-free stars with high effective temperatures may emit hard photons, capable of doubly ionizing helium and increasing the IGM temperature. Absorption within the source and in the intervening IGM will render the ionizing continuum of high-redshift sources inaccessible to direct observation. Here we show that He recombination lines from the first luminous objects are potentially detectable by the Next Generation Space Telescope. Together with measurements of the Hα emission line, this detection can be used to infer the ratio of He II to H I ionizing photons, Q = /. A measurement of this ratio would shed light on the nature and emission mechanism of the first luminous sources, with important astrophysical consequences for the reheating and reionization of the IGM.
Discriminative speaker adaptation with conditional maximum likelihood linear regression

We present a simplified derivation of the extended Baum-Welch procedure, which shows that it can be used for Maximum Mutual Information (MMI) of a large class of continuous emission density hidden Markov models (HMMs). We use the extended Baum-Welch procedure for discriminative estimation of MLLR-type speaker adaptation transformations. The resulting adaptation procedure, termed Conditional Maximum Likelihood Linear Regression (CMLLR), is used successfully for supervised and unsupervised adaptation tasks on the Switchboard corpus, yielding an improvement over MLLR. The interaction of unsupervised CMLLR with segmental minimum Bayes risk lattice voting procedures is also explored, showing that the two procedures are complimentary.
The Alpage Architecture at the SANCL 2012 Shared Task: Robust Pre-Processing and Lexical Bridging for User-Generated Content Parsing

We describe the architecture we set up during the SANCL shared task for parsing user-generated texts, that deviate in various ways from linguistic conventions used in available training treebanks. This architecture focuses in coping with such a divergence. It relies on the PCFG-LA framework (Petrov and Klein, 2007), as implemented by Attia et al. (2010). We explore several techniques to augment robustness: (i) a lexical bridge technique (Candito et al., 2011) that uses unsupervised word clustering (Koo et al., 2008); (ii) a special instanciation of self-training aimed at coping with POS tags unknown to the training set; (iii) the wrapping of a POS tagger with rule-based processing for dealing with recurrent non-standard tokens; and (iv) the guiding of out-of-domain parsing with predicted part-of-speech tags for unknown words and unknown (word, tag) pairs. Our systems ranked second and third out of eight in the constituency parsing track of the SANCL competition.
Yields from low metallicity, intermediate mass AGB stars:. Their role for the CNO and lithium abundances in Globular Cluster stars

We present the results of extensive computation of the Thermal Pulse phase AGB evolution of stars of metallicities in mass fraction 2 10 4 Z 0:01, for those masses in the range 2:5 M=M 6, which suer the Hot Bottom Burning (HBB) phase. The evolution is fully computed, by assuming a mass loss rate consistent with the observations of the Magellanic Clouds lithium-rich stars, and modelling convection with the Full Spectrum of Turbulence model by Canuto and Mazzitelli. The results are discussed in the framework of their importance for the evolution of proto-Globular Clusters, whose spectra show that the stars are very probably formed from matter contaminated by the ejecta of these stars, or have accreted it after formation. The main results we find are the following: 1) for metallicities Z 10 3 , masses above4 M suer complete CNO cycling in HBB, so that they show at the surface the result of this process, and the oxygen abundance is reduced; 2) most models suer the third dredge up. Although carbon is processed to nitrogen by HBB, the oxygen burning is so strong in the lowest metallicities (2 10 4 )t hatcarbon becomes more abundant than oxygen: in other words, low-metallicity intermediate mass stars may show up as carbon stars due to the drastic oxygen burning; 3) if Globular Cluster stars are contaminated by matter processed through these phases, we must expect a non negligible helium enhancement in their composition: from a Big Bang abundance Y= 0:24, e.g., we might expect an abundance Y= 0:28. This may have no practical consequences if pollution concerns only the external parts of the stars, but is very important if the stars formed as a whole from a helium rich environment. 4) The lithium yields, although not important for galactic chemical evolution, are very interestingly close to the initial Big Bang abundance: processing by HBB is the only way in which we can obtain substantial amounts of gas which have gone through full CNO burning, but preserve a reasonable abundance of lithium.
Application of wavelet and neural network models for wind speed and power generation forecasting in a Brazilian experimental wind park

The wind speed and wind generation forecasting are of extreme importance to aid in the planning studies and scheduled operation of hydrothermal and wind systems. This kind of generation is in the incipient phase in Brazil; however, the perspectives are mainly exciting aiming for increasing the potential of electricity generation. The use of wind power for producing electricity can create uncertainties in the generation. Therefore, the development of wind forecasting models is essential to integrate this kind of energy source with the generation system in an effective way. This work proposes the application of Artificial Neural Networks - ANN to produce a tool capable of accomplishing the wind speed forecasting. The ANN model is created using input data preprocessing by the Wavelet Transform - WT to extract important characteristics of the wind speed. Outputs of several ANNs show clearly the potential of the model based on WT compared with the others.
Family functioning and temperament as predictors of preschoolers coping with daily stressors.

Understanding how preschool children cope is a first step toward identifying adaptive ways of coping which reduce stress and ultimately can decrease the risk of dysfunctional behavior. However, the literature on preschoolers' coping is minimal, in part due to the lack of assessment tools. This research examined preschoolers coping with daily stress in an attempt to assess what coping styles would be used across different situations. I hypothesized that family environment and temperament would affect the coping style used and that temperament would moderate the effects of the family environment. the efficacy of the coping. A secondary question concerned In order to accomplish this, a scale was developed to assess coping across four situational domains. Using mothers as the primary reporter, the preschoolers' temperament, family functioning, and coping behaviors were assessed and the relationships were examined. I investigated the ability of family control and cohesiveness, child temperament, and an interaction of cohesiveness and temperament, to predict coping styles. This model was very good at predicting coping in situations where a child was trying to master a task; adequate for predicting coping in emotional situations; and had limited predictive ability in parent-child or peer situations. There was some support for the moderating effects of temperament. Temperament was a robust predictor of coping iv style, whereas family cohesion was not. Other findings suggest that children who have emotional temperaments used emotional types of coping. Children in families with more interfamily cohesion, or whose parents have higher levels of education, used more cognitive behavioral-problem solving. Ratings of coping efficacy resulted in cognitivebehavioral problem solving being most effective in Mastery situations, moderate emotional coping being most effective in Parent-child domain, and highly emotional coping was rated as most effective in Emotional situations.
Title of Thesis: Hybrid 3d-model Representation through Quadric Metrics and Hardware Accelerated Point-based Rendering Title of Thesis: Hybrid 3d-model Representation through Quadric Met- Rics and Hardware Accelerated Point-based Rendering Hybrid 3d-model Representation through Quadric Metrics and H

Title of Thesis: HYBRID 3D-MODEL REPRESENTATION THROUGH QUADRIC METRICS AND HARDWARE ACCELERATED POINT-BASED RENDERING Hanli Ni, Master of Science, 2005 Thesis directed by:Dr. Marc Olano The expectation for highly realistic 3D images has resulted in 3D models with millions of triangles. Traditional algorithms accelerate ren d ring speed by taking advantage of coherence within a triangle if the screen projection of the t riangle covers multiple pixels. However, as the triangle count increases and the triangle si ze decreases, screen projections of triangles cover fewer pixels. In some cases, projections are even sub-pixel size, which makes these acceleration algorithms ineffective. Alterna tively, points have the advantage of no explicit connectivity and the rendering pipeline can b e implemented using the latest 3D hardware functionalities. But sufficient densities an d proper sampling patterns are required for points to be effective. Previous research sugg ests that neither triangles nor points are the ultimate solution in terms of hardware render i g. In this study, we build a hybrid rendering system that takes advantage of both primit ives. Our system is composed of two components, preprocessing and rendering. During pre proc ssing, the system builds a hierarchical hybrid model taking a 3D polygonal model as in put. The system breaks the input polygonal model into patches by applying clustering a lgorithms on the model. Planar patches are rendered using triangles, while patches with hi gh variations are rendered with points. The clustering algorithm is based on quadric error m etrics, which is a good measure of the planarity of surfaces. Other metrics, such as shape, n ormal and size are used. The point representation of a patch is obtained through regular sampling of the triangle patch. The system uses traditional polygonal hardware rendering p ipeline for polygonal patch rendering. We implement point rendering pipeline using hardwa re vertex and pixel shaders. The final system combines the advantages of both polygonal an d poi t rendering pipelines and achieves relatively high image quality while maintaini ng interactive rendering speed. HYBRID 3D-MODEL REPRESENTATION THROUGH QUADRIC METRICS AND HARDWARE ACCELERATED POINT-BASED RENDERING
NoSQL: The death of the Star

In the last years, the problems of using generic storage techniques for very specific applications has been detected and outlined. Thus, some alternatives to relational DBMSs (e.g. BigTable and C-Store) are blooming. On the other hand, cloud computing is already a reality that helps to save money by eliminating the hardware as well as software fixed costs and just pay per use. Thus, specific software tools to exploit the cloud have also appeared. The trend in this case is to use implementations based on the MapReduce paradigm developed by Google. The basic goal of this talk will be the introduction and the discussion of these ideas from the point of view of Data Warehousing and OLAP. We will see advantages, disadvantages and some possibilities it offers.
Development of a Flexible Access Control Design by Extending RBAC

Role based access control (RBAC) has received much attention for more than a decade as one of the most attractive solutions for access control in Web-based information systems. However, its associated characteristics are often not suitable for a varying organization requiring a flexible structure. In order to address this limitation, it may essentially be required to assess more flexibility to access control mechanisms. To this end, we propose a new extended access control mechanisms incorporating three authentication dimensions based on user, department, and role. We then demonstrate that the proposed mechanisms can improve utilization of a Web-based knowledge-sharing system.
Éléments de sécurité dans l'architecture de systèmes répartis THINK.

Les architectures de noyaux monolithiques s'averant inadequates pour exploiter pleinement les resources materielles, on s'interesse dans cet article au modele exo-noyau et a l'architecture de systemes repartis THINK, du point de vue de la securite et de la preservation de la qualite de service offerte par le systeme. On presente donc le travail d'analyse effectue concernant les ressources materielles principales d'un ordinateur et les outils elementaires a implanter pour garantir une protection de ces ressources et de la qualite de service du systeme. On decrit aussi l'outil d'isolation logicielle des processus en cours d'implantation et on donne un exemple concret d'utilisation des outils elementaires proposes.
A probabilistic approach for the adaptive integration of multiple visual cues using an agent framework

Most current machine vision systems suffer from a lack of flexibility to account for the high variability of unstructured environments. As the state of the world evolves, the potential knowledge provided by different visual attributes can change, breaking the initial assumptions of a non-adaptive vision system. This thesis develops a new comprehensive computational framework for the adaptive integration of information from different visual algorithms. This framework takes advantage of the richness of visual information by adaptively considering; a variety of visual properties such as color, depth, motion, and shape. Using a probabilistic approach and uncertainty metrics, the resulting framework makes appropriate decisions about the most relevant visual attributes to consider. The framework is based on an agent paradigm. Each visual algorithm is implemented as an agent that adapts its behavior according to uncertainty considerations. These agents act as a group of experts, where each agent has a specific knowledge area. Cooperation among the agents is given by a probabilistic scheme that uses Bayesian inference to integrate the evidential information provided by them. To deal with the inherent nonlinearity of visual information, the relevant probability distributions are represented using a stochastic sampling approach. The estimation of the state of relevant visual structures is performed using an enhanced version of the particle filter algorithm. This enhanced version includes novel methods to adaptively select the number of samples used by the filter, and to adaptively find a suitable function to propagate the samples. The implementation of the computational framework is performed using a distributed multi-agent software architecture. This is tested for the case of visual target tracking using a mobile platform. The evaluation of the implementation using computer simulations and real situations compares positively with current state of the art visual target tracking techniques.
Memory, learning and language in autism spectrum disorder

Background and aims The ‘dual-systems’ model of language acquisition has been used by Ullman et al. to explain patterns of strength and weakness in the language of higher-functioning people with autism spectrum disorder. Specifically, intact declarative/explicit learning is argued to compensate for a deficit in non-declarative/implicit procedural learning, constituting an example of the so-called see-saw effect. Ullman and Pullman extended their argument concerning a see-saw effect on language in autism spectrum disorder to cover other perceived anomalies of behaviour, including impaired acquisition of social skills. The aim of this paper is to present a critique of Ullman et al.’s claims and to propose an alternative model of links between memory systems and language in autism spectrum disorder. Main contribution We argue that a four-system model of learning, in which intact semantic and procedural memory are used to compensate for weaknesses in episodic memory and perceptual learning, can better explain patterns of language ability across the autistic spectrum. We also argue that attempts to generalise the ‘impaired implicit learning/spared declarative learning’ theory to other behaviours in autism spectrum disorder are unsustainable. Conclusions Clinically significant language impairments in autism spectrum disorder are under-researched, despite their impact on everyday functioning and quality of life. The relative paucity of research findings in this area lays it open to speculative interpretation which may be misleading. Implications More research is needed into links between memory/learning systems and language impairments across the spectrum. Improved understanding should inform therapeutic intervention and contribute to investigation of the causes of language impairment in autism spectrum disorder with potential implications for prevention.