Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamics and Excitation of Radio Galaxy Emission-Line Regions. I. PKS 2356–61

Results are presented from a program of detailed long-slit spectroscopic observations of the extended emission-line region (EELR) associated with the powerful radio galaxy PKS 2356-61. The observations have been used to construct spectroscopic data cubes, which yield detailed information on the spatial variations of emission-line ratios across the EELR, together with its kinematic structure. We present an extensive comparison between the data and results obtained from the MAPPINGS II shock ionization code, and show that the physical properties of the line-emitting gas, including its ionization, excitation, dynamics and overall energy budget, are entirely consistent with a scenario involving autoionizing shocks as the dominant ionization mechanism. This has the advantage of accounting for the observed EELR properties by means of a single physical process, thereby requiring fewer free parameters than the alternative scheme involving photoionization by radiation from the active nucleus. Finally, possible mechanisms of shock formation are considered in the context of the dynamics and origin of the gas, specifically scenarios involving infall or accretion of gas during an interaction between the host radio galaxy and a companion galaxy.
Man made structure detection and verification of object recognition in images for the visually impaired

This paper presents two learning based algorithms that are designed for the purpose of extracting and processing suitable information in images for the visually impaired. Both algorithms are developed to be used within a specific modular sonification system. This system is designed to allow visually impaired people to explore images, actively on a touch screen, and to receive an auditory response about the image content at any current finger position. The first algorithm presented in this paper therefore addresses the problem of labeling regions within images, incorporating spatial dependencies. The second algorithm strives to alleviate the rejection of false object detections before sonification. This is crucial to avoid confusion on the side of the blind user, who can not check for a correct image labeling or object detection visually. Due to the modular design principle of the modular sonification system, both algorithms can be incorporated easily and efficiently.
Eurographics/ Ieee-vgtc Symposium on Visualization 2008 Timeradartrees: Visualizing Dynamic Compound Digraphs

The evolution of dependencies in information hierarchies can be modeled by sequences of compound digraphs with edge weights. In this paper we present a novel approach to visualize such sequences of graphs. It uses radial tree layout to draw the hierarchy, and circle sectors to represent the temporal change of edges in the digraphs. We have developed several interaction techniques that allow the users to explore the structural and temporal data. Smooth animations help them to track the transitions between views. The usefulness of the approach is illustrated by examples from very different application domains.
Man-machine cooperation for the on-line training of an evolving classifier

Touch sensitive interfaces enable new interaction methods, like using gesture commands. To easily memorize more than a dozen of gesture commands, it is important to be able to customize them. The classifier used to recognize drawn symbols must hence be customizable, able to learn from very few data, and evolving, able to learn and improve during its use. This work studies the importance and the impact of using reject to supervise the on-line training of the evolving classifier. The objective is to obtain a gesture command system that cooperates as best as possible with the user: to learn from its mistakes without soliciting him too often. There is a trade-off between the number of user interactions, to supervise the on-line learning, and the number of classification errors, that require a correction from the user.
PAC Reinforcement Learning Bounds for RTDP and Rand-RTDP Technical Report

Real-time Dynamic Programming (RTDP) is a popular algorithm for planning in a Markov Decision Process (MDP). It can also be viewed as a learning algorithm, where the agent improves the value function and policy while acting in an MDP. It has been empirically observed that an RTDP agent generally performs well when viewed this way, but past theoretical results have been limited to asymptotic convergence proofs. We show that, like true learning algorithms E and RMAX, a slightly modified version of RTDP satisfies a Probably Approximately Correct (PAC) condition (with better sample complexity bounds). In other words, we show that the number of timesteps in an infinite-length run in which the RTDP agent acts according to a non-optimal policy from its current state is less than some polynomial (in the size of the MDP), with high probability. We also show that a randomized version of RTDP is PAC with asymptotically equal sample complexity bounds, but has much less per-step computational cost, O(ln(S) ln(SA) + ln(A)), rather than O(S + ln(A)) when we consider only the dependence on S, the number of states and A, the number of actions of the MDP.
Ex-Ante Evaluation of Conditional Cash Transfer Programs: The Case of Bolsa Escola

Cash transfers targeted to poor people, but conditional on some behavior on their part, such as school attendance or regular visits to health care facilities, are being adopted in a growing number of developing countries. Even where ex-post impact evaluations have been conducted, a number of policy-relevant counterfactual questions have remained unanswered. These are questions about the potential impact of changes in program design, such as benefit levels or the choice of the means-test, on both the current welfare and the behavioral response of household members. This paper proposes a method to simulate the effects of those alternative program designs on welfare and behavior, based on microeconometrically estimated models of household behavior. In an application to Brazil's recently introduced federal Bolsa Escola program, the authors find a surprisingly strong effect of the conditionality on school attendance, but a muted impact of the transfers on the reduction of current poverty and inequality levels
Finite Time Distributions of Stochastically Modeled Chemical Systems with Absolute Concentration Robustness

Recent research in both the experimental and mathematical communities has focused on biochemical interaction systems that satisfy an “absolute concentration robustness” (ACR) property. The ACR property was first discovered experimentally when, in a number of different systems, the concentrations of key system components at equilibrium were observed to be robust to the total concentration levels of the system. Follow-up mathematical work focused on deterministic models of biochemical systems and demonstrated how chemical reaction network theory can be utilized to explain this robustness. Later mathematical work focused on the behavior of this same class of reaction networks, though under the assumption that the dynamics were stochastic. Under the stochastic assumption, it was proven that the system will undergo an extinction event with a probability of one so long as the system is conservative, showing starkly different long-time behavior than in the deterministic setting. Here we consider a general class .
Similarity of Temporal Query Logs Based on ARIMA Model

A challenging issue faced by modern information retrieval is that of determining and satisfying users' requirements relying only on very short text queries. In this paper, we propose an algorithm to find out related queries based on auto-regressive integrated moving average (ARIMA) model. First, we select and estimate ARIMA model of the temporal query logs. And then each query is denoted by a sequence of coefficients. We use the correlation of ARIMA coefficients as the similarity measurement. We call it as the ARIMA temporal similarity (ARIMA TS). This similarity describes how strongly two time series are linearly related. On the other hand, the ARIMA model could also be treated as a dimensionality reduction procedure. It can save storage space for a large database of the query logs. In addition, ARIMA model could be used as a tool to predict the trend of a query. The experimental results on two query logs of MSN search engine demonstrate that the proposed approach can achieve better similarity measurement efficiently
Genetic analysis of growth traits in Harnali sheep

Aim: The present investigation was to study genetic characteristics of Harnali sheep with respect to growth performance and to estimate genetic parameters. Materials and Methods: The 22 years (1992-2013) data of growth traits of a 1603 synthetic population of Harnali sheep maintained at Lala Lajpat Rai University of Veterinary and Animal Sciences, Hisar, was utilized for this study. A mixed methodology with regression on their dam's weight was used to study the effect of non-genetic factors on growth traits. Heritability, genetic and phenotypic correlations were estimated using paternal half-sib analysis for body weight at various ages and average daily gain (ADG) for different growth periods. Result: The overall least squares mean of body weights recorded for birth weight (BW), weaning weight (WW), six months body weight (SMW), one yearling body weight (YBW), average daily gain from birth to 3 months (ADG1) and average daily gain from 3 to 12 months (ADG2) were 3.35±0.05 kg, 12.41±0.08 kg, 16.30±0.12 kg, 21.88±0.08 kg, 100.66±0.86 g/day and 35.07±0.39 g/day, respectively. The effects of year of birth significantly (p<0.01) influenced the BW, WW, SMW, YWB, ADG1 and ADG2. The effects of sex of lamb significantly (p<0.01) influenced the BW, WW SMW, YWB, ADG1 and ADG2. The effects of dam's weight at lambing significantly (p<0.01) influenced BW, WW, SMW, YWB, ADG1 and ADG2. No definite trend was observed over the years for the averages of body weight and gain. The heritability estimates of BW, WW, SMW, YBW, ADG1 and ADG2 were 0.40±0.05, 0.38±0.05, 0.45±0.06, 0.29±0.05, 0.40±0.06 and 0.33±0.02, respectively. The male lambs were significantly heavier than females at all stages of growth. The heritability estimates were moderate for all the growth traits and high genetic correlations of BW and WW with SMW were found. Conclusion: Due to high heritability and positive correlations of SMW with other body weights and daily gain, it was concluded that selection on the basis of SMW would be the best approach to improve growth performance in Harnali sheep.
Assessment of image sensor technology for future NASA missions

An assessment of solid-state UV/visible image sensor technology for future NASA missions is presented. The paper attempts to summarize the state of the art in image sensor technology in the United States, Canada, Japan, and Europe. The state of the art and future trends are compared to a forecast of future NASA needs in scientific image sensors for planetary exploration, earth science, astrophysics, and spacecraft systems such as star trackers and optical communications.
The N-Methyl-D-Aspartate Receptor as a Neurobiological Intersection Between Bipolar Disorder and Alcohol Use: A Longitudinal Mismatch Negativity Study

Background: Comorbid risky alcohol use in bipolar disorder (BD) is recognized for its high prevalence and clinical relevance, though understanding of its neurobiological underpinning is limited. The N-methyl-D-aspartate (NMDA) receptor has recognized alterations in BD and is a major site of ethanol’s effects in the brain. The present study aimed to examine the NMDA receptor system in adolescents and young adults with BD by evaluating the longitudinal changes in a robust marker of NMDA function, mismatch negativity (MMN), in relation to changes in alcohol use patterns. Methods: Forty-six BD patients (aged 16–30) were recruited at baseline and 59% (n = 27) returned for follow-up 17.9 +/- 7.3 months later. At both time-points a two-tone, passive, duration-deviant MMN paradigm was conducted and alcohol measures were collected. Pearson’s correlations were performed between changes in MMN amplitudes and changes in alcohol use. Multiple regression was used to assess whether MMN amplitudes at baseline could predict alcohol use at follow-up. Results: Reduction in risky drinking patterns was associated with increased temporal MMN and decreased fronto-central MMN. Larger temporal MMN at baseline was a significant predictor of greater alcohol use at follow-up. Conclusions: Results suggest risky alcohol use in BD may further compound pre-existing NMDA receptor abnormalities and, importantly, reducing alcohol use early in stages of illness is associated with changes in MMN. This highlights the importance of monitoring alcohol use from first presentation. In addition, preliminary results present an exciting potential for utility of MMN as a neurobiological marker used to determine risk for alcohol misuse in BD.
Decoding real-field codes by an iterative Expectation-Maximization (EM) algorithm

In this paper, a new approach for decoding real-field codes based on finding sparse solutions of underdetermined linear systems is proposed. This algorithm iteratively estimates the positions and the amplitudes of the sparse errors (or noise impulses) using an expectation-maximization (EM) algorithm. Iterative estimation of amplitudes is done in the expectation step (E-step), while iterative estimation of error positions is done in the maximization step (M-step). Simulation results show 1-2 dB improvement over linear programming (LP) which has been previously used for error correction.
Sex addiction: therapist perspectives

ABSTRACT Sexual addiction may be defined as sexual behaviour that is “compulsive and yet continues despite adverse consequences”. Knowledge and understanding of sexual addiction has been impaired by the use of multiple labels, definitions, and assessment procedures, hence the present study investigated therapist perspectives and experiences of assessing and treating the condition. Interviews were conducted with nine psychosexual therapists and subjected to interpretive phenomenological analysis. Three superordinate themes emerged from the analysis. These were distress, risk, and treatment. The distress theme included three sub-themes: stress and coping; suicidal ideation; and partner experience. Three sub-themes formed the risk theme: physical safety; disease, dysfunctions, and pregnancy; and co-addiction. The treatment theme contained three sub-themes: awareness; assessment and diagnosis; and successful therapy. Findings have important implications for the diagnosis and treatment of sexual addiction. Future research should investigate these themes further and introduce interventions to support the safety and well-being of sexual addiction clients.
Quantitative control of ASYMMETRIC LEAVES2 expression is critical for leaf axial patterning in Arabidopsis

ASYMMETRIC LEAVES2 (AS2) is one of the key genes required for specifying leaf adaxial identity during leaf adaxial–abaxial polarity establishment. Previous data have shown that, in leaf development, AS2 is directly repressed by an abaxially located transcription factor KANADI1 (KAN1), so that the AS2 transcripts are restricted only in the adaxial leaf domain. It is shown here that, different from the spatial repression by KAN1, the quantitative repression of AS2 in the adaxial domain is also critical for ensuring normal leaf pattern formation. By analysing two gain-of-function as2 mutants, as2-5D and isoginchaku-2D (iso-2D), it is shown that the similar AS2-over-expressed phenotypes of these mutants reflect two different kinds of AS2 misexpression patterns. While as2-5D causes disruption of a KAN1-binding site at the AS2 promoter leading to derepression of AS2 in the abaxial side but without changing its expression level of a leaf, iso-2D results in over-expression of AS2 but without altering its adaxial expression pattern. In addition, it was found that, in iso-2D, levels of histone H3 lysine 27 trimethylation (H3K27me3) and H3K4me3 at the AS2 locus are significantly reduced and increased, respectively, compared with those in the wild type and as2-5D. These results suggest that during leaf patterning, quantitative control of the AS2 expression level might involve epigenetic regulations.
Cognitive problems among breast cancer survivors: loneliness enhances risk

Cancer survivors often experience cognitive difficulties after treatment completion. Although chemotherapy enhances risk for cognitive problems, it is likely only one piece of a complex puzzle that explains survivors' cognitive functioning. Loneliness may be one psychosocial risk factor. The current studies included both subjective and objective cognitive measures and tested whether lonelier breast cancer survivors would have more concentration and memory complaints and experience more concentration difficulties than their less lonely counterparts.
Bose-Einstein condensation: Twenty years after

The aim of this introductory article is two-fold. First, we aim to offer a general introduction to the theme of Bose-Einstein condensates, and briefly discuss the evolution of a number of relevant research directions during the last two decades. Second, we introduce and present the articles that appear in this Special Volume of Romanian Reports in Physics celebrating the conclusion of the second decade since the experimental creation of Bose-Einstein condensation in ultracold gases of alkali-metal atoms.
Time-aware Multi-Viewpoint Summarization of Multilingual Social Text Streams

A viewpoint is a triple consisting of an entity, a topic related to this entity and sentiment towards this topic. In time-aware multi-viewpoint summarization one monitors viewpoints for a running topic and selects a small set of informative documents. In this paper, we focus on time-aware multi-viewpoint summarization of multilingual social text streams. Viewpoint drift, ambiguous entities and multilingual text make this a challenging task. Our approach includes three core ingredients: dynamic viewpoint modeling, cross-language viewpoint alignment, and, finally, multi-viewpoint summarization. Specifically, we propose a dynamic latent factor model to explicitly characterize a set of viewpoints through which entities, topics and sentiment labels during a time interval are derived jointly; we connect viewpoints in different languages by using an entity-based semantic similarity measure; and we employ an update viewpoint summarization strategy to generate a time-aware summary to reflect viewpoints. Experiments conducted on a real-world dataset demonstrate the effectiveness of our proposed method for time-aware multi-viewpoint summarization of multilingual social text streams.
Cardiac Troponin T (TNNT2) Mutations in Chinese Dilated Cardiomyopathy Patients

Background. Dilated cardiomyopathy (DCM) is one of the leading causes of heart failure with high morbidity and mortality. Although more than 40 genes have been reported to cause DCM, the role of genetic testing in clinical practice is not well defined. Mutations in the troponin T (TNNT2) gene represent an important subset of known disease-causing mutations associated with DCM. Therefore, the aim of the present study was to determine the genetic variations in TNNT2 and the associations of those variations with DCM in Chinese patients. Methods. An approximately 4 kb fragment of the TNNT2 gene was isolated from 103 DCM patients and 192 healthy controls and was analyzed by DNA sequence analysis for genetic variations. Results. A total of 6 TNNT2 mutations were identified in 99 patients, including a G321T missense mutation (Leu84Phe) and 5 novel intronic mutations. Alleles of two novel SNPs (c.192 + 353 C>A, OR = 0.095, 95% CI: 0.013–0.714, P = 0.022; c.192 + 463 G>A, OR = 0.090, 95% CI: 0.012–0.675, P = 0.019) and SNP rs3729843 (OR = 1.889, 95% CI: 1.252–2.852; P = 0.002) were significantly correlated with DCM. Conclusions. These results suggest that the missense mutation (Leu84Phe) and two novel SNPs (c.192 + 353 C>A, c.192 + 463 G>A) in TNNT2 gene might be associated with DCM in the Chinese population.
Optimal Rate Sampling in 802.11 systems

Rate Adaptation (RA) is a fundamental mechanism in 802.11 systems. It allows transmitters to adapt the coding and modulation scheme as well as the MIMO transmission mode to the radio channel conditions, and in turn, to learn and track the (mode, rate) pair providing the highest throughput. So far, the design of RA mechanisms has been mainly driven by heuristics. In contrast, in this paper, we rigorously formulate such design as an online stochastic optimisation problem. We solve this problem and present ORS (Optimal Rate Sampling), a family of (mode, rate) pair adaptation algorithms that provably learn as fast as it is possible the best pair for transmission. We study the performance of ORS algorithms in stationary radio environments where the successful packet transmission probabilities at the various (mode, rate) pairs do not vary over time, and in non-stationary environments where these probabilities evolve. We show that under ORS algorithms, the throughput loss due to the need to explore sub-optimal (mode, rate) pairs does not depend on the number of available pairs. This is a crucial advantage as evolving 802.11 standards offer an increasingly large number of (mode, rate) pairs. We illustrate the efficiency of ORS algorithms (compared to the state-of-the-art algorithms) using simulations and traces extracted from 802.11 test-beds.
Tamper-proo ng Software Watermarks

We introduce a novel method called constant encoding, which can be used to tamper-proof a software watermark that is embedded in the dynamic data structures of a program. Our novel tamper-proofing method is based on transforming numeric or non-numeric constant values in the text of the watermarked program into function calls whose value depends on the watermark data structure. Under reasonable assumptions about the knowledge and resources of an attacker, we argue that no attacker can be certain that they have altered our tamperproofed watermark unless they take a risk of affecting program correctness in some way that may be difficult to detect. In this paper we also present a novel scheme for representing a numeric value as a Planted Plane Cubic Tree, and we describe how to use this scheme in a particularly-effective implementation of our constant encoding tamperproofing method.
Winter respiration of allochthonous and autochthonous organic carbon in a subarctic clear‐water lake

We studied a small subarctic lake to assess the magnitude of winter respiration and the organic carbon (OC) source for this respiration. The concentration and stable isotopic composition (δ13C) of dissolved inorganic carbon (DIC) accumulating in the lake water under ice was analyzed over one winter (7 months). The DIC concentration increased and the δ13C of DIC decreased over time, with the greatest changes at the lake bottom. Winter respiration was 26% of annual respiration in the lake. Keeling plot analysis demonstrated that the δ13C of respired DIC varied spatially, high δ13C values occurring at shallow (2.5 m, 221.7‰%) compared with intermediate (4 m, 225.1‰) and deep (6 m, 227.8‰) locations in the lake. The variation in the δ13C of respired DIC was related to the variation in the δ13C of the sediments between locations, suggesting that sediment OC supported much of the winter respiration and that the dominant OC source for respiration was OC from benthic algae at shallow locations and settled OC, of predominately terrestrial origin, at deep locations. The respiration of OC from benthic algae constituted 55% of the winter respiration, equaling 54% of the primary production by benthic algae the previous summer. The study indicates the importance of temporal and spatial variation in respiration for the metabolism and net DIC production in unproductive high‐latitude lakes; both allochthonous and autochthonous carbon can contribute to winter DIC accumulation and, consequently, to spring CO2 emissions from lakes.