Miracle-dz/UniFAR-FTUs huggingface dataset:
Causality of holographic hydrodynamics

We study causality violation in holographic hydrodynamics in the gauge theory/string theory correspondence, focussing on Gauss-Bonnet gravity. The value of the Gauss-Bonnet coupling is related to the difference between the central charges of the dual conformal gauge theory. We show that, when this difference is sufficiently large, causality is violated both in the second-order truncated theory of hydrodynamics, as well as in the exact theory. We find that the latter provides more stringent constraints, which match precisely those appearing in the CFT analysis of Hofman and Maldacena.
Parkinson's Disease and Systemic Inflammation

Peripheral inflammation triggers exacerbation in the central brain's ongoing damage in several neurodegenerative diseases. Systemic inflammatory stimulus induce a general response known as sickness behaviour, indicating that a peripheral stimulus can induce the synthesis of cytokines in the brain. In Parkinson's disease (PD), inflammation was mainly associated with microglia activation that can underlie the neurodegeneration of neurons in the substantia nigra (SN). Peripheral inflammation can transform the “primed” microglia into an “active” state, which can trigger stronger responses dealing with neurodegenerative processes. Numerous evidences show that systemic inflammatory processes exacerbate ongoing neurodegeneration in PD patient and animal models. Anti-inflammatory treatment in PD patients exerts a neuroprotective effect. In the present paper, we analyse the effect of peripheral infections in the etiology and progression in PD patients and animal models, suggesting that these peripheral immune challenges can exacerbate the symptoms in the disease.
Simultaneous allocations of multiple tightly-coupled multi-robot tasks to coalitions of heterogeneous robots

Most multi-robot task allocation algorithms are concerned with the allocation of individual tasks to single robots. However certain types of tasks require a team of robots for their execution, and for the allocation of such tasks non-conflicting robot teams have to be formed. Most of the existing allocation algorithms for such tasks mainly address the robot-team formation and the tasks are allocated sequentially. However, allocating multiple tasks simultaneously will result in a more balanced distribution of robots into teams. A market based algorithm for simultaneous allocation of multiple tightly couple multi-robot tasks to coalitions of heterogeneous robots are proposed in this paper. The simultaneous allocations are deadlock-free and significant improvement in overall execution time is achieved as demonstrated by empirical evaluations.
Multivariate Contemporaneous Threshold Autoregressive Models

This paper proposes a contemporaneous-threshold multivariate smooth transition autoregressive (C-MSTAR) model in which the regime weights depend on the ex-ante probabilities that latent regime-specific variables exceed certain threshold values. A key feature of the model is that the transition function depends on all the parameters of the model as well as on the data. Since the mixing weights are also a function of the regime-specific noise covariance matrix, the model can account for contemporaneous regime-specific co-movements of the variables. The stability and distributional properties of the proposed model are discussed, as well as issues of estimation, testing and forecasting. The practical usefulness of the C-MSTAR model is illustrated by examining the relationship between US stock prices and interest rates.
The ARM program's water vapor intensive observation periods - Overview, initial accomplishments, and future challenges

A series of water vapor intensive observation periods (WVIOPs) were conducted at the Atmospheric Radiation Measurement (ARM) site in Oklahoma between 1996 and 2000. The goals of these WVIOPs are to characterize the accuracy of the operational water vapor observations and to develop techniques to improve the accuracy of these measurements. The initial focus of these experiments was on the lower atmosphere, for which the goal is an absolute accuracy of better than 2% in total column water vapor, corresponding to ~1 W m−2 of infrared radiation at the surface. To complement the operational water vapor instruments during the WVIOPs, additional instrumentation including a scanning Raman lidar, microwave radiometers, chilled-mirror hygrometers, a differential absorption lidar, and ground-based solar radiometers were deployed at the ARM site. The unique datasets from the 1996, 1997, and 1999 experiments have led to many results, including the discovery and characterization of a large (> 25%) sonde-to-sonde variab.
T C C C L     E T H

In this article we survey algorithmic lower bound results that have been obtained in the field of exact exponential time algorithms and parameterized complexity under certain assumptions on the running time of algorithms ∗Department of Computer Science and Engineering, University of California, USA. dlokshtanov@ucsd.edu †Institut für Informatik, Humboldt-Universiät , Berlin, Germany. dmarx@cs.bme. hu ‡The Institute of Mathematical Sciences, Chennai, India. saket@imsc.res.in ! "#$% &' ()* ! " "# $% $&'()*% ! solving CNF-S, namely Exponential time hypothesis (ETH) and Strong Exponential time hypothesis (SETH).
Ensuring the Consistency of Self-Reported Data: A Case Study

Much data available from on-line databases is self-reported. Because of this the quality and consistency of web available data is often suspect. This paper presents Supply Chain Diversifier, a service directory that collects and presents data from the Small Business Administration website and a number of web based subscription registries of minority vendors. Supply Chain Diversifier uses a number of automated tools including extraction, classification, standardization, and matching to present information on minority suppliers and classify them to the NAICS, or the North American Industry Classification System. The system enhances data quality by automatically collating data from multiple sources with semantics based on the NAICS taxonomy and using methods of statistical quality control to quantify the quality of the data presented. INTRODUCTION Much data of interest to organizations is self-reported: this includes data from surveys of customers, from registration of members or users, and so on. In collecting self-reported data, say over the world-wide web, the kinds of edit checks available are limited by the fact that data entry must be easy – otherwise members or customers may neglect to report the data of interest. As a result, the designer of “forms” for self-reporting often faces a choice between ensuring the quality and consistency of data, and ensuring that 155 Proceedings of the Seventh International Conference on Information Quality (ICIQ-02)
Family quality of life following early identification of deafness.

PURPOSE Family members' perceptions of their quality of life were examined following early identification of deafness in children. METHOD A questionnaire was used to solicit ratings of satisfaction from the family members of 207 children who were deaf and younger than 6 years of age. RESULTS Results indicated that families were generally satisfied with the areas of family life surveyed. Descriptive analysis suggested lower satisfaction ratings in the area of emotional well-being. Families also reported that their child's deafness had the largest impact on their emotional well-being. Family members of children using oral communication with a cochlear implant reported higher satisfaction with their child's speech production and perception outcomes than family members of children using hearing aids alone. IMPLICATIONS We recommend that service providers and early hearing detection and intervention program coordinators consider additional supports for family well-being following the early identification of deafness in children.
Autonomous Neural Development and Pruning

The main motivation behind this project comes from the observation that topological structures of neural networks intended for engineering purposes often seem to be chosen more or less arbitrarily or with a rule of thumb. This project seeks to explore a biological inspired method for autonomous development and pruning of non-noisy back-propagating neural networks. Learning will be divided in to three distinct phases development, pruning and apoptosis where the network will initially overexpand then contract to a more computationally tractable valency and topology. Thus, the actual computational efficiency of learning will be neglected in favor of ease of implementation and computational efficiency in actual usage.
Local Filtering: Improving the Performance of Approximate Queries on String Collections

We study efficient query processing for approximate string queries, which find strings within a string collection whose edit distances to the query strings are within the given thresholds. Existing methods typically hinge on the property that globally similar strings must share at least certain number of identical substrings or subsequences. They become ineffective when there are burst errors or when the number of errors is large. In this paper, we explore the opposite paradigm focusing on finding out the differences of database strings to the query string. We propose a new filtering method, called local filtering, based on the idea that two strings exhibiting substantial local dissimilarities must be globally dissimilar. We propose the concept of (positional) local distance to quantify the minimum amount of errors a query fragment contributes to the edit distance between the query and a data string. It also leads to effective pruning rules and can speed up verification via early termination. We devise a family of indexing methods based on the idea of precomputing (positional) local distances for all possible combinations of query fragments and edit distance thresholds. Based on careful analyses of subtle relationships among local distances, novel techniques are proposed to drastically reduce the amount of enumeration with no or little impact on the pruning power. Efficient query processing methods exploiting the new index and bit-parallelism are also proposed. Experimental results on real datasets show that our local filtering-based methods can achieve substantial speedup compared with state-of-the-art methods, and they are robust against factors such as dataset characteristics and large edit distance thresholds.
Haggle: a data-centric network architecture for mobile devices

Delay-tolerant and opportunistic networks relax the traditional assumption of end-to-end connectivity. Such networks are therefore suitable for content dissemination in sparsely connected regions of the world, and for complementing existing infrastructure by operating cost-free, high bandwidth, albeit high latency, content delivery services. In this work we argue, however, that content dissemination in the above contexts requires us to revisit delay-tolerant communication at the architectural level, looking at multiple issues such as naming and addressing, congestion control and application interfaces. We propose a new architecture, called Haggle, that leverages the principles of search, as known from desktop operating systems and the Web, in order to achieve truly data-centric communication. Searching is naturally data-centric and embeds principles, such as ranking, that can be used to bind data to interested receivers and to prioritize the data to send during node encounters. We herein give an overview of the Haggle architecture and its basic design.
La recherche d'information sur Internet au prisme de la théorie des facettes

La theorie des facettes sert de referentiel a cette recherche. Cette theorie a ete developpee dans le monde de l'information documentaire par Ranganathan (1933, 1967). L'auteur propose de decrire le contenu des documents selon une approche combinatoire et multidimensionnelle qui s'oppose aux classifications mono hierarchiques en vigueur jusque la. Pour Ranganathan, le contenu de tout document touche a cinq aspects de la realite : la Personnalite, la matiere, l'energie, l'espace et le Temps. A ces cinq perspectives s'ajoute une facette principale, representant generalement le domaine de la connaissance auquel on peut rattacher un document particulier (Agriculture, Medecine, etc.). Nous proposons dans ce travail de reinterroger la theorie des facettes de Ranganathan dans une perspective de recherche d'information sur internet. Nous nous interrogerons sur la faisabilite et la mise en oeuvre de telles descriptions pour les documents en ligne. La caracterisation des facettes passe par un travail multidisciplinaire mettant en œuvre des emprunts et des transpositions dans le domaine de la fouille de donnees, de la psychologie sociale, de l'informatique, des mathematiques, des sciences du langage, de la communication.
Tracking Human Arm from Monocular Videos

In this paper, we present a modified annealed particle filter which combines the annealed particle filter (proposed in [1], APF) with kinematic Jump Processes (proposed in [3], KJP), termed as APF+KJP. Compared with particle filter, the APF can make the particles more possibly converge to the global minimum, so the particles in APF are centralized with higher weight, while the KJP diffuse particles according to kinematical reasoning, samples found by KJP share the same projection on the image plane with the original sample and obtain the same weight. So the APF+KJP can effectively find particles with higher weight. Besides when the tracker find the incorrect global minimal, the KJP can help the tracker converge to the correct one. Experimental results demonstrate the performance of the proposed algorithm.
Pessimistic and Optimistic Induction

Learning methods vary in the optimism or pessimism with which they regard the informativeness of learned knowledge. Pessimism is implicit in hypothesis testing, where we wish to draw cautious conclusions from experimental evidence. However, this paper demonstrates that optimism in the utility of derived rules may be the preferred bias for learning systems themselves. We examine the continuum between naive pessimism and naive optimism in the context of a decision tree learner that prunes rules based on stringent (i.e., pessimistic) or weak (i.e., optimistic) tests of their signiicance. Our experimental results indicate that in most cases optimism is preferred, but particularly in cases of sparse training data and high noise. This work generalizes earlier ndings by Fisher and Schlimmer (1988) and Schaaer (1992), and we discuss its relevance to unsupervised learning, small disjuncts, and other issues.
ANALYSIS OF THE CHILDREN'S MOTIVATION FOR THE INTERNET USE AND THEIR ACTIVITIES IN THE ONLINE ENVIRONMENT/АНАЛИЗА ДЕЧИЈИХ МОТИВА ЗА КОРИШЋЕЊЕ ИНТЕРНЕТА И ЊИХОВИХ АКТИВНОСТИ У ОНЛАЈН ОКРУЖЕЊУ

The aim of this research was to explore the presence of information technologies in children's homes in Serbia and children's activities in the online environment, according to their age, gender and economic status, based on the theory of uses and gratifications. The research adopted the survey technique, investigating 979 children aged from 7 to 13 in five cities in Serbia: Belgrade, Nis, Novi Sad, Sabac and Valjevo. The results of our study indicate that children's age and economic status influence their usage of the computer and of the Internet, while both gender and age determine their preferred activities. It is established that there is a digital gap between the European and Serbian children. The lower opportunity to access the Internet may negatively affect children’s academic performances. Variations in the patterns of the Internet usage between boys and girls have been narrowed, while boys still remain in higher risks to be exposed to the unsafe content and behaviour in the web space. Motivation for online activities is moderated by the children’s age. Educational consequences are discussed and suggestions provided. Key words: children, Internet, uses and gratifications theory, online activities, motives. Циљ овог истраживања био је да се испита присуство информационих технологија у домовима деце у Србији, као и њихове активности у онлајн окружењу, посматрано према њиховим годинама, полу и економском статусу, засновано на теорији користи и задовољства. У истраживању је као техника коришћен упитник, док је узорак укључивао 979 деце узраста од 7 до 13 година из пет градова у Србији: Београда, Ниша, Новог Сада, Шапца и Ваљева. Резултати нашег истраживања указују на то да узраст и економски статус деце утичу на њихово коришћење рачунара и интернета, док пол и старост одређују њихове омиљене онлајн активности. Утврђено је да постоји дигитални јаз између европске и српске деце. Мања могућност приступа интернету може се негативно одразити на дечије академске перформансе. Разлике у коришћењу интернета између дечака и девојчица се смањују, али дечаци и даље остају у ризичнијем положају да буду изложени небезбедним садржајима и понашању у веб-простору. Мотивација за онлајн активности условљена је дечијим годинама. Дискутовано је о последицама за образовни сектор и предложене су могуће мере. Кључне речи: деца, интернет, теорија користи и задовољства, онлајн активности, мотивација.
Corneal confocal microscopy reveals trigeminal small sensory fiber neuropathy in amyotrophic lateral sclerosis

Although subclinical involvement of sensory neurons in amyotrophic lateral sclerosis (ALS) has been previously demonstrated, corneal small fiber sensory neuropathy has not been reported to-date. We examined a group of sporadic ALS patients with corneal confocal microscopy, a recently developed imaging technique allowing in vivo observation of corneal small sensory fibers. Corneal confocal microscopy (CCM) examination revealed a reduction of corneal small fiber sensory nerve number and branching in ALS patients. Quantitative analysis demonstrated an increase in tortuosity and reduction in length and fractal dimension of ALS patients’ corneal nerve fibers compared to age-matched controls. Moreover, bulbar function disability scores were significantly related to measures of corneal nerve fibers anatomical damage. Our study demonstrates for the first time a corneal small fiber sensory neuropathy in ALS patients. This finding further suggests a link between sporadic ALS and facial-onset sensory and motor neuronopathy (FOSMN) syndrome, a rare condition characterized by early sensory symptoms (with trigeminal nerve distribution), followed by wasting and weakness of bulbar and upper limb muscles. In addition, the finding supports a model of neurodegeneration in ALS as a focally advancing process.
Science Communication through Mass Media in Mother Tongue

The main role of media is to inform and entertain people and so we have to develop very interesting science fictions. It is obscured that science have widened gap with art and literature. We have to fill this gap through creative writings of science and technology. Mass media is using new innovative ideas of science and technology but under pressure of TRP and unethical practices, it is not able to follow through mysterious programs. The basic postulate to popularize science is that, it should be communicated in mother tongue.
THE MERGER RATE OF MASSIVE GALAXIES

We calculate the projected two point correlation function f r samples of luminous and massive galaxies in the COMBO-17 photometric redshift survey, focusing particula rly on the amplitude of the correlation function at small projected radii and exploring the constraints such me asurements can place on the galaxy merger rate. For nearly volume-limited samples with 0 . 4< z < 0.8, we find that 4±1% of luminousMB < −20 galaxies are in close physical pairs (with real space separation of < 30 proper kpc). The corresponding fraction for massive gala xies with M∗ > 2.5× 10M⊙ is 5±1%. Incorporating close pair fractions from the literature , the 2dFGRS and the SDSS, we find a fairly rapid evolution of the merger fraction o f massive galaxies between z = 0.8 and the present day. Assuming that the major merger timescale is of order the dynamical timescale for close massive galaxy pairs, we tentatively infer that ∼ 50% (70%) of all galaxies with present-day masses M∗ > 5×10M⊙ (remnants of mergers between galaxies with M∗ > 2.5×10M⊙) have undergone a major merger since z = 0.8(1): major mergers between massive galaxies are a significant driver of galaxy evolution over the last eight billion years. Subject headings: galaxies: general — galaxies: interactions — galaxies: evo lution
Acoustic Detection

The proposal of acoustic neutrino detection is living a renaissance: the interest in ultra high energy neutrino detection, the fast improvements of deep sea technology and the availability of large deep sea research infrastructures are the three main ingredients to explain the new interest in this technique. The status of simulation work, medium studies, sensor developments and first results from test experimental setups are presented.
The evaluation of visually impaired people's ability of defining the object location on touch-screen

Touch-screen has been used not only on home appliances but also on so many kinds of machines in public facilities at the present time. However the fact is that most of visually impaired people have a problem with the difficult usability of a touch-screen. We come up with an idea of Presentation Methods of Sound Information, which is thought to enable visually impaired people to define the object location on the touch-screen. We also make a proposal of the Concentration game content that is possible in improving the Sound localization's ability and evaluating the visually impaired people's characteristics of touch-screen's operation method. In this paper, we introduce the results of the experiment that we conducted with 5 visually impaired people. These are evaluated through the way of the finger moving on the touch-screen panel while using this content, and the ability of defining the object location.
Computational Capabilities of Random Automata Networks for Reservoir Computing

This paper underscores the conjecture that intrinsic computation is maximal in systems at the "edge of chaos". We study the relationship between dynamics and computational capability in random Boolean networks (RBN) for reservoir computing (RC). RC is a computational paradigm in which a trained readout layer interprets the dynamics of an excitable component (called the reservoir) that is perturbed by external input. The reservoir is often implemented as a homogeneous recurrent neural network, but there has been little investigation into the properties of reservoirs that are discrete and heterogeneous. Random Boolean networks are generic and heterogeneous dynamical systems and here we use them as the reservoir. A RBN is typically a closed system; to use it as a reservoir we extend it with an input layer. As a consequence of perturbation, the RBN does not necessarily fall into an attractor. Computational capability in RC arises from a tradeoff between separability and fading memory of inputs. We find the balance of these properties predictive of classification power and optimal at critical connectivity. These results are relevant to the construction of devices which exploit the intrinsic dynamics of complex heterogeneous systems, such as biomolecular substrates.