Miracle-dz/UniFAR-FTUs huggingface dataset:
Study of habit learning impairments in Tourette syndrome and obsessive-compulsive disorder using reinforcement learning models

Psychiatric and neurological disorders are currently classified according to their symptomatic manifestations and not their intrinsic pathophysiology [89]. This leads to severe difficulties in patients’ treatment and even diagnosis, and implies the need of developing new tools capable of objectively assessing the underlying neurophysiological impairments of such disorders [43] [80]. With this in mind, a reinforcement learning (RL) framework for the study of habit learning impairments during probabilistic classification learning task solving was created. This allowed the objective analysis of the behavioral data collected during the solving of the Weather Prediction Task (WPT) from several patients with Tourette syndrome (TS) and obsessivecompulsive disorder (OCD), and normal control (NC) subjects. Two distinct datasets were analyzed, one regarding NC and OCD adults, and one concerning NC and TS children. In the first dataset, multiple adults had solved versions of the WPT with different input sequences, whereas all the analyzed children had solved a task with the same input and feedback sequence. Several -learning models were created from the developed framework and fitted to the empirical data. These were compared through random effects Bayesian model selection (BMS) and, as a consequence, two models which reasonably explained the empirical data of the two datasets were selected. Parametric comparison within the selected models across the NC and OCD adults and the NC and TS children was then performed. A one-tailed -test revealed a tendency for increased switching in TS children ( ), which was also supported by a one-tailed Wilcoxon rank sum test ( ). RL-independent analysis of the data corroborated these results.
A Distributed Bio-Inspired Method for Multisite Grid Mapping

Computational grids assemble multisite and multiowner resources and represent the most promising solutions for processing distributed computationally intensive applications, each composed by a collection of communicating tasks. The execution of an application on a grid presumes three successive steps: the localization of the available resources together with their characteristics and status; the mapping which selects the resources that, during the estimated running time, better support this execution and, at last, the scheduling of the tasks. These operations are very difficult both because the availability and workload of grid resources change dynamically and because, in many cases, multisite mapping must be adopted to exploit all the possible benefits. As the mapping problem in parallel systems, already known as NP-complete, becomes even harder in distributed heterogeneous environments as in grids, evolutionary techniques can be adopted to find near-optimal solutions. In this paper an effective and efficient multisite mapping, based on a distributed Differential Evolution algorithm, is proposed. The aim is to minimize the time required to complete the execution of the application, selecting from among all the potential ones the solution which reduces the use of the grid resources. The proposed mapper is tested on different scenarios.
The effects of rain on TOPEX/Poseidon altimeter data

The presence of rain in the sub-satellite track can significantly degrade altimeter measurements by causing an attenuation of the backscattered signal, a change in its path length through the atmosphere and a change in the mean square slope of the sea surface. This can cause errors, not only in the measurement of the satellite altitude, but also in the determination of wind speed and wave height. TOPEX/Poseidon dual-frequency altimeter data (cycles 3 and 8) were searched for instances where the data were possibly degraded by the presence of rain over the North and inter-Tropical Atlantic. A subjective analysis of the data, similar to the one used in previous studies was conducted on the backscatter coefficient, wind speed, significant wave height, sea surface height, TOPEX Microwave Radiometer (TMR) brightness temperatures, liquid water content and data quality flags to identify the orbits possibly affected by rain. From the 105 probable rain events identified, the effects of rain on the TOPEX measurements and data quality parameters were characterized. The strong differential effect of rain on the Ku and C band measurements was then used to define a new rain flag based on a departure from the normal relationship between the C and Ku band backscatter. This new rain flag was shown to detect all the identified rain events, as well as new ones. The TMR rain flag, used operationally, was shown to flag too many altimeter samples and too few rain events, mainly because of its large resolution (few tens of kilometers compared to few kilometers for the altimeter). An estimation of the rainfall rate from the attenuation of the Ku band backscatter was proposed.
Learning About Income Inequality: What is the Impact of Information on Perceptions of Fairness and Preferences for Redistribution?

This paper studies whether limited information about inequality accounts for the (optimistic) beliefs and the (anti-tax) preferences of American voters. Unlike standard surveys, this experiment examines preferences for taxation while controlling for perceived economic opportunity, beliefs about how the economy works, and views about the sources of inequality. Random assignment to information exposure about income inequality is used to identify a causal relationship between awareness about income inequality and the perceived fairness of the economy. The first effect of information is an increase in pessimism about economic opportunity. After exposure to data, subjects are less likely to believe that people who work hard can get ahead in life through hard work alone (the odds of holding this view fall by one third). Many subjects say they are surprised by the data, and learning how much households in the top 0.1% earn raises support for general, unspecified government action against inequality by about 6 percentage points. However, the subjects who are exposed to information are not more willing to take specific action (pay higher taxes) compared to the uninformed control group.
Effects of rest interval on isokinetic strength and functional performance after short-term high intensity training.

OBJECTIVES: The ability to maximally generate active muscle tension during resistance training has been established to be a primary determinant for strength development. The influence of intrasession rest intervals may have a profound effect on strength gains subsequent to short-term high intensity training. The purpose of this study was to examine the effects of rest interval on strength and functional performance after four weeks of isokinetic training. METHODS: Fifteen healthy college aged individuals were randomly assigned to either a short rest interval group (group 1, n = 8) or a long rest interval group (group 2, n = 7). Subjects were evaluated for quadriceps and hamstring isokinetic strength at 60 (five repetitions) and 180 (30 repetitions) degrees/second and functional performance with the single leg hop for distance test. One leg of each subject was randomly assigned to a four week, three days/week isokinetic strength training programme for concentric knee extension and flexion performed at 90 degrees/second. Subjects in group 1 received a 40 second rest interval in between exercise sets, whereas subjects in group 2 received a 160 second rest period. RESULTS: A two factor analysis of variance for the pre-test--post-test gain scores (%) showed significantly greater improvements for isokinetic hamstring total work and average power at 180 degrees/second for the trained limb of subjects in group 2 than their contralateral non-trained limb and the subjects in group 1. Significantly greater improvements for the single leg hop for distance were also found for the trained limbs of subjects in both groups as compared with the non-trained limbs. CONCLUSIONS: The findings indicate that a relatively longer intrasession rest period resulted in a greater improvement in hamstring muscle strength during short term high intensity training.
Metareasoning in Symbolic Domains

Many AI problems, such as planning, grammar learning, program induction, and theory discovery, require searching in symbolic domains. Most models perform this search by evaluating a sequence of candidate solutions, generated in order by some heuristic. Human reasoning, though, is not limited to sequential trial and error. In particular, humans are able to reason about what the solution to a particular problem should look like, before comparing candidates against the data. In a program synthesis task, for instance, a human might first determine that the task at hand should be solved by a tail-recursive algorithm, before filling in the algorithm’s details.
Double Jeopardy: The Effect of Multiple Secondary Trauma Exposure on Subjective Age

Abstract The present study investigates whether secondary traumatization (i.e., family history of Holocaust survival and secondary exposure to captivity) is implicated in subjective age. Women exposed to different levels of secondary traumatization (N = 177) were assessed. Analyses of variance (ANOVAs) revealed that a Holocaust background and husband's captivity had a marginally significant positive effect on age appearance. Women with a Holocaust background whose husbands were held captive reported older interest age, indicating double jeopardy for older subjective age when two sources of secondary traumatization are present. A similar trend existed for behavior age. Possible explanations for these complex findings of risk and resilience are discussed.
Translation Model Based Cross-Lingual Language Model Adaptation: from Word Models to Phrase Models

In this paper, we propose a novel translation model (TM) based cross-lingual data selection model for language model (LM) adaptation in statistical machine translation (SMT), from word models to phrase models. Given a source sentence in the translation task, this model directly estimates the probability that a sentence in the target LM training corpus is similar. Compared with the traditional approaches which utilize the first pass translation hypotheses, cross-lingual data selection model avoids the problem of noisy proliferation. Furthermore, phrase TM based cross-lingual data selection model is more effective than the traditional approaches based on bag-of-words models and word-based TM, because it captures contextual information in modeling the selection of phrase as a whole. Experiments conducted on large-scale data sets demonstrate that our approach significantly outperforms the state-of-the-art approaches on both LM perplexity and SMT performance.
Impaired Lymphoid Organ Development in Mice Lacking the Heparan Sulfate Modifying Enzyme Glucuronyl C5-Epimerase

The development of lymphoid organs depends on cross talk between hematopoietic cells and mesenchymal stromal cells and on vascularization of the lymphoid primordia. These processes are orchestrated by cytokines, chemokines, and angiogenic factors that require tight spatiotemporal regulation. Heparan sulfate (HS) proteoglycans are molecules designed to specifically bind and regulate the bioactivity of soluble protein ligands. Their binding capacity and specificity are controlled by modification of the HS side chain by HS-modifying enzymes. Although HS proteoglycans have been implicated in the morphogenesis of several organ systems, their role in controlling lymphoid organ development has thus far remained unexplored. In this study, we report that modification of HS by the HS-modifying enzyme glucuronyl C5-epimerase (Glce), which controls HS chain flexibility, is required for proper lymphoid organ development. Glce−/− mice show a strongly reduced size of the fetal spleen as well as a spectrum of defects in thymus and lymph node development, ranging from dislocation to complete absence of the organ anlage. Once established, however, the Glce−/− primordia recruited lymphocytes and developed normal architectural features. Furthermore, Glce−/− lymph node anlagen transplanted into wild-type recipient mice allowed undisturbed lymphocyte maturation. Our results indicate that modification of HS by Glce is required for controlling the activity of molecules that are instructive for early lymphoid tissue morphogenesis but may be dispensable at later developmental stages and for lymphocyte maturation and differentiation.
The F-Box Protein AhSLF-S2 Physically Interacts with S-RNases That May Be Inhibited by the Ubiquitin/26S Proteasome Pathway of Protein Degradation during Compatible Pollination in Antirrhinum

Self-incompatibility S-locus–encoded F-box (SLF) proteins have been identified in Antirrhinum and several Prunus species. Although they appear to play an important role in self-incompatible reaction, functional evidence is lacking. Here, we provide several lines of evidence directly implicating a role of AhSLF-S2 in self-incompatibility in Antirrhinum. First, a nonallelic physical interaction between AhSLF-S2 and S-RNases was demonstrated by both coimmunoprecipitation and yeast two-hybrid assays. Second, AhSLF-S2 interacts with ASK1- and CULLIN1-like proteins in Antirrhinum, and together, they likely form an Skp1/Cullin or CDC53/F-box (SCF) complex. Third, compatible pollination was specifically blocked after the treatment of the proteasomal inhibitors MG115 and MG132, but they had little effect on incompatible pollination both in vitro and in vivo, indicating that the ubiquitin/26S proteasome activity is involved in compatible pollination. Fourth, the ubiquitination level of style proteins was increased substantially after compatible pollination compared with incompatible pollination, and coimmunoprecipitation revealed that S-RNases were ubiquitinated after incubating pollen proteins with compatible but not with incompatible style proteins, suggesting that non-self S-RNases are possibly degraded by the ubiquitin/26S proteasome pathway. Fifth, the S-RNase level appeared to be reduced after 36 h of compatible pollination. Taken together, these results show that AhSLF-S2 interacts with S-RNases likely through a proposed SCFAhSLF-S2 complex that targets S-RNase destruction during compatible rather than incompatible pollination, thus providing a biochemical basis for the inhibition of pollen tube growth as observed in self-incompatible response in Antirrhinum.
Spoken Dialogue System based on Information Extraction using Similarity of Predicate Argument Structures

We present a novel scheme of spoken dialogue systems which uses the up-to-date information on the web. The scheme is based on information extraction which is defined by the predicate-argument (P-A) structure and realized by semantic parsing. Based on the information structure, the dialogue system can perform question answering and also proactive information presentation. Feasibility of this scheme is demonstrated with experiments using a domain of baseball news. In order to automatically select useful domain-dependent P-A templates, statistical measures are introduced, resulting to a completely unsupervised learning of the information structure given a corpus. Similarity measures of P-A structures are also introduced to select relevant information. An experimental evaluation shows that the proposed system can make more relevant responses compared with the conventional "bag-of-words" scheme.
Hopfield neural networks: a survey

In this work we survey the Hopfield neural network, introduction of which rekindled interest in the neural networks through the work of Hopfield and others. Hopfield net has many interesting features, applications, and implementations and it comes in two flavors, digital and analog. A brief review of the model oriented towards pattern recognition is also considered. Some interesting variations of the network or neuron model are noted which are being considered by researchers may lead to better performance or overcome problems such as capacity of the network.
Living life on the edge - wide-field VLBI at 90 cm!

We report on a recent 90 cm wide-field VLBI survey of two 3.1 deg2 fields using the VLBA, Westerbork and Jodrell Bank telescopes. In-beam calibration was used to calibrate each field, the process was simplified by imaging the calibrators in DIFMAP and transferring the calibration solutions to AIPS using the newly developed DIFMAP task cordump. We detected and imaged 13 out of the 141 sources originally detected by the low resolution (54) WENSS survey of the same two fields. The sources were detected at 7− 12 sigma levels above the image noise, had total flux densities ranging between 85−1640 mJy and were between 16− 58 from the phase centre of each field. This is the first systematic (and non-biased), deep, high resolution survey of the low frequency radio sky. These initial results suggest that new instruments such as LOFAR should detect many compact radio sources and that plans to extend these arrays to baselines of several thousand kilometres are warranted.
Homologues of the Caenorhabditis elegans Fox-1 Protein Are Neuronal Splicing Regulators in Mammals

ABSTRACT A vertebrate homologue of the Fox-1 protein from C. elegans was recently shown to bind to the element GCAUG and to act as an inhibitor of alternative splicing patterns in muscle. The element UGCAUG is a splicing enhancer element found downstream of numerous neuron-specific exons. We show here that mouse Fox-1 (mFox-1) and another homologue, Fox-2, are both specifically expressed in neurons in addition to muscle and heart. The mammalian Fox genes are very complex transcription units that generate transcripts from multiple promoters and with multiple internal exons whose inclusion is regulated. These genes produce a large family of proteins with variable N and C termini and internal deletions. We show that the overexpression of both Fox-1 and Fox-2 isoforms specifically activates splicing of neuronally regulated exons. This splicing activation requires UGCAUG enhancer elements. Conversely, RNA interference-mediated knockdown of Fox protein expression inhibits splicing of UGCAUG-dependent exons. These experiments show that this large family of proteins regulates splicing in the nervous system. They do this through a splicing enhancer function, in addition to their apparent negative effects on splicing in vertebrate muscle and in worms.
Fiscal Policy for Economic Development: An Overview

F policy can foster growth and human development through a number of different channels. These channels include the macroeconomic (for example, through the influence of the budget deficit on growth) as well as the microeconomic (through its influence on the efficiency of resource use). But how precisely do these channels work in developing countries? Do the insights gleaned from the vast body of research on these topics in industrial countries carry over to developing countries? 1 From a macroeconomic perspective, one of the central insights from past research on developing countries is that prudent fiscal policy— that is, low budget deficits and low levels of public debt—is a key ingredient for economic growth, which in turn is essential for reducing poverty and improving social outcomes.2 Small budget deficits also reduce the risk of economic crises caused by concerns about the government’s ability to service its debt. They prevent interest bills from rising to levels that squeeze critical social spending and ensure that the stock of debt remains at levels consistent with a country’s capacity to service
Blind Separation of Multi-Dimensional Components via Subspace Decomposition: Performance Analysis

A prevalent approach to blind separation of multi-dimensional data is a two-step procedure. In the first step, the data are assigned a one-dimensional model. A separating algorithm is applied according to this model. This step corresponds to classical blind source separation (BSS). In the second step, the output is assigned into groups, representing the multi-dimensional components. In this paper, we consider an even more general case, in which the subpartition of the components in the first step may be into elements of any dimension, not necessarily one. We consider a piecewise stationary model and assume that the number and dimensions of the underlying multi-dimensional components are known. We obtain a closed-form analytical expression for the mean-square error (MSE) in the estimation of the multi-dimensional components using this two-step procedure. As expected, this approach is suboptimal in the presence of finite data-size errors. Therefore, we can predict the expected gain from using the correct model of the components, over any finer decomposition thereof. In addition, we demonstrate the dependence of this gain on the model parameters.
The ‘ Good Continuation ’ Principle of Perceptual Organization applied to the Generalization of Road Networks

Perceptual organization (or grouping) principles play a vital role in the understanding of images and maps, and their importance in map generalization has also long been recognized. This paper presents a brief review of the application of the principles in map generalization, and then examines their particular relevance to the generalization of road networks. It is shown how the ‘good continuation’ grouping principle can serve as the basis for analyzing a road network into a set of linear elements, here termed ‘strokes’. Further analysis allows the strokes to be ordered, to reflect their relative importance in the network. The deletion of the elements according to this sequence provides a simple and effective method of generalizing (attenuating) the network. This technique has been implemented, as part of the ‘GenSystem’ generalization software package developed at the Canada Centre for Remote Sensing. The implementation is outlined, and the effectiveness of the technique demonstrated.
Incremental Paradigms of Motif Discovery

We examine the problem of extracting maximal irredundant motifs from a string. A combinatorial argument poses a linear bound on the total number of such motifs, thereby opening the way to the quest for the fastest and most efficient methods of extraction. The basic paradigm explored here is that of iterated updates of the set of irredundant motifs in a string under consecutive unit symbol extensions of the string itself. This approach exposes novel characterizations for the base set of motifs in a string, hinged on notions of partial order. Such properties support the design of ad hoc data structures and constructs, and lead to develop an O(n(3)) time incremental discovery algorithm.