Miracle-dz/UniFAR-FTUs huggingface dataset:
Schizotypy, theory of mind and the understanding of irony

Frith's (1992) cognitive neuropsychological model of schizophrenia proposed that the symptoms characteristic of that disorder can be accounted for in terms of differing degrees of theory of mind impairment. There is a large body of evidence indicating that individuals with schizophrenia perform poorly on tasks that are hypothesised to require a functioning theory of mind, and this review aims to introduce the main findings from these studies. Following consideration of thirty-four relevant papers, this review finds that the only unequivocal finding is that individuals with schizophrenia do show impaired theory of mind. How this impairment relates to schizophrenic symptomatology as predicted by Frith's model is far less certain, and several methodological limitations are discussed that could account for this uncertainty, before a new development in the field is introduced: the use of the schizotypy paradigm to test the predictions of Frith's theory in non-clinical samples. The schizotypy paradigm has been employed in three studies investigating ToM performance in healthy individuals to date (Langdon and Coltheart, 1999 Langdon and Coltheart, 2004 Pickup, 2006), and the findings from these studies show that schizotypal traits do influence ToM performance. These studies are reviewed, and future directions for research are recommended.
Left hemisphere dominance in reading the sensory qualities of others’ pain?

Abstract Seeing or imagining others in pain may activate both the sensory and affective components of the neural network (pain matrix) that is activated during the personal experience of pain. Transcranial magnetic stimulation (TMS), proved adept at highlighting the sensorimotor side of empathy for pain in studies where mere observation of needles penetrating body parts of a human model brought about a clear corticospinal motor inhibition. By using TMS, we investigated whether inferring the sensory properties of the pain of a model influenced the somatomotor system of an onlooker. Moreover, we tested the possible lateralization of the motor substrates underlying this reading process. We recorded motor-evoked potentials (MEPs) to left and right motor cortex stimulation during the observation of “flesh and bone” painful stimulations of right and left hands respectively. We found a significant reduction of onlookers’ MEPs amplitudes specific to the muscle penetrated in the model. Subjective inferences about localization and intensity of the observed pain were associated with specific patterns of motor modulation with larger inhibitory effects following stimulation of the left motor cortex. Thus, results indicate that the mental simulation of the sensory qualities of others’ pain may be lateralized to the left hemisphere.
Horizon-based screen-space ambient occlusion using mixture sampling

Ambient occlusion is a shading method which approximates the global illumination by taking into account attenuation of light due to occlusion. Screen-space ambient occlusion (SSAO) is a scene-independent improvement which performs the visibility test using depth buffer on GPU in real time. Shanmugam et.al [2007] efficiently reconstructs the surface using spheres that can be projected to screen, but has the overocclusion issue. Bavoil et.al [2008] approximates the ambient occlusion illumination A at a given surface point P by [EQUATION] where w is the sample directions at P within the unit normal-oriented hemisphere with azimuth angle θ and elevation angle α, the tangent angle t(θ) is the signed elevation angle of the surface tangent vector while the horizon angle h(θ) is the maximum elevation α ≥ t(θ) for which w is occluded for all α < h(θ), and W is a linear attenuation function. It overcomes the overocclusion problem of [Shanmugam and Arikan 2007]. However, the rough approximation of the geometry occluder makes the shadows lack of rich details. In this paper we propose a new SSAO solution which overcomes the issues of both above methods and provides more realistic results, as shown in Figure 1.
A fast convergence two-step procedure for AR modeling of power spectral densities

A new technique for the minimization of customary cost functions for all-pole modeling of power spectral densities is presented. In the literature, optimizations are usually based on unnormalized autoregressive (AR) coefficients. In contrast, the proposed method is centered on a two-step descent using normalized AR coefficients on the one hand and the residual power on the other hand. For each cost function, efficient ways to obtain gradients are derived and a descent-based optimization is formulated. The resulting procedure converges significantly faster than the corresponding gradient descents on un-normalized coefficients, while still being computationally efficient. In addition to the traditional Yule-Walker distance, the Itakura-Saito distance, the COSH distance, the RMS log-spectral ratio distance, and a mean-squared error cost function are treated. Convergence results and curves are presented accordingly for different situations.
Pattern matching information flow using GADT

Integrating security policies into security assurance mechanisms to ensure end-to-end behavior is still a challenge. Information flow analysis and type checking are effective methods for the analysis and verification of secure communications and processing. Language-based information flow security models use programming-language for specifying and enforcing security policy. Dependently typed programming is an efficient and powerful way to concisely communicate, represent, and then reason over security policies. In this paper we demonstrate an integration of policy elements in a subset of a language-based information flow security model implemented using dependent type programming. We illustrate how recent advances in type theory in secure domains make available enabling technologies for developing policy aware secure computing.
Examining the Relation Between Parental Ignorance and Youths’ Cyberbullying Perpetration

Past work has shown that parental perceptions of their children’s Internet activity (e.g., hours spent online) does not match their children’s actual Internet involvement; however, no work has examined whether this mismatch is related to youths’ cyberbullying perpetration. Study 1 consisted of 75 parent–child dyads that completed measures to assess youth Internet behavior (including cyberbullying behavior and parental rules regarding Internet behaviors). Results showed that parents, on average, underestimated whether their children cyberbullied others and overestimated parental rule enforcement. Study 2 (N = 165 youth) used a correlational design to examine the relations between youth cyberbullying perpetration and parent Internet rules. Results showed that parental ignorance (how much parents are unaware of their child’s Internet activities) positively correlated with cyberbullying behaviors. Finally, Study 3 (N = 96 youth) used a short-term longitudinal study using the same measure as Study 2 and found that Wave 1 parental ignorance was related to Time 2 cyberbullying perpetration. Overall, results suggest that the extent to which parents are unaware of their child’s online behaviors positively predict cyberbullying perpetration.
Un instrumento para evaluar la eficacia de los procedimientos de inducción de estado de ánimo: la "Escala de Valoración del Estado de Ánimo" (EVEA)

Se presenta un instrumento de autoinforme, la "Escala de Valoracion del Estado de Animo" (EVEA), desarrollado para medir estados de animo transitorios en los estudios que utilizan procedimientos de induccion de estado de animo (PIEAs). La EVEA fue aplicada a 402 estudiantes universitarios en varias investigaciones sobre cognicion y trastornos emocionales (Sanz, 1994a,b,c, 1997a,b; Sanz y Dobson, 1994). El analisis psicometrico de estos datos revelo que las subescalas de la EVEA (ansiedad, depresion, hostilidad y alegria) muestran indices adecuados de consistencia interna (coeficientes alfa entre ,88 y ,93), fiabilidad test-retest (correlaciones a los 7 y 25 minutos entre ,55 y ,88), validez factorial (cuatro factores que se corresponden con las subescalas), validez discriminante (diferenciacion entre estados de animo negativos y entre estos y los positivos), validez de criterio (correlaciones con medidas de sintomatologia depresiva}, y sensibilidad para detectar a nivel individual y grupal cambios en el estado de animo. Finalmente, a partir de estos indices, se proponen criterios para el analisis individual de los cambios en estado de animo producidos por los PIEAs.
Comparative study of information fusion methods for sonar images classification

Here, a comparative study of information fusion methods for sonar images classification is proposed. The automatic classification of sonar images is a very difficult problem. Our first task consists in finding a good image representation to classify the sea bottom. Classical approaches are based on texture analysis. Many methods can be considered to deal with this problem; however, the best choice of the considered method depends often on the kind of sediment. Once the features extraction method has been considered, many classifiers can be used. In order to extract features, four major texture analysis methods have been considered. The four sets of features are classified and different methods of information fusion, such as the weighted vote approach, or coming from the possibility theory and evidence theory, have been employed.
Expanding to the Internet: Pricing and Communications Strategies When Firms Compete on Multiple Channels

The author shows how firms' pricing and communications strategies may be affected by the size of the Internet: Firms have incentives to facilitate consumer search on the Internet, but only as long as the Internet's reach is limited. As the Internet is used by more consumers, firms' pricing and communications strategies on the Internet will mirror the strategies they pursue in a conventional channel. Firms can increase their market power by strategically using information on multiple channels to achieve finer consumer segmentation. The author suggests directions the Internet might take and derives managerial implications. The findings generalize to other channels that enable firms to segment consumers and inform them at low cost.
Readiness to change in alcohol-related illness : the role of perceived control, causal attributions and illness beliefs

READINESS TO CHANGE IN ALCOHOL-RELATED ILLNESS: THE ROLE OF PERCEIVED CONTROL. CAUSAL ATTRIBUTIONS AND ILLNESS BELIEFS. AIMS & OBJECTIVES: This research thesis is based on an exploratory study that investigated the influence of healthand drinking-related factors on motivation to change drinking behaviour in alcohol-related illness. Key factors relevant to behavioural intentions to change were drawn together from health and substance-dependency literature. The aim was to demonstrate links between causal, control and efficacy beliefs and readiness to change. Specific hypotheses were proposed for relationships between causal attributions, perceived control, abstinence self-efficacy, health value, alcohol dependency and stage of change. METHOD: The study involved 33 male and female participants diagnosed with an alcoholrelated illness. The sample included hospital in-patients and those seeking help from community agencies. Participants completed a semi-structured interview and six questionnaire measures, administered by the researcher. Relationships between variables were examined using bivariate analyses. The relative power of variables as predictors of readiness to change were examined using regression analysis. RESULTS: Significant differences were found between those classified as ‘ready to change’ and those ‘not ready to change’ in terms of alcohol dependency and abstinence selfefficacy. Perceived dependency was a significant and strong predictor of readiness to change. Behavioural self-blame, perceived control, and health-value were not significantly related to readiness to change. No significant relationships were found between perceived control and either self-efficacy or behavioural self-blame. However, significant relationships were found between alcohol dependency and both abstinence self-efficacy and perceived control over illness. CONCLUSIONS: The intensity, timing and type of intervention should be responsive to the motivational stage of the individual. The clinician needs to assess clients’ beliefs about the nature of their drinking problem. Problem drinkers need knowledge about how to regulate their behaviour and firm belief in their personal efficacy to take effective action and personal control over outcomes.
Spectra and anisotropy of magnetic fluctuations in the Earth's magnetosheath: Cluster observations

We investigate the spectral shape, the anisotropy of the wave vector distributions and the anisotropy of the amplitudes of the magnetic fluctuations in the Earth's magnetosheath within a broad range of frequencies [10 −3 , 10] Hz which corresponds to spatial scales from ~10 to 10 5 km. We present the first observations of a Kolmogorov-like inertial range of Alfvenic fluctuations δ B 2 ⊥ }~ f −5/3 in the magnetosheath flanks, below the ion cyclotron frequency f ci . In the vicinity of f ci , a spectral break is observed, like in solar wind turbulence. Above the break, the energy of compressive and Alfvenic fluctuations generally follows a power law with a spectral index between −3 and −2. Concerning the anisotropy of the wave vector distribution, we observe a clear change in its nature in the vicinity of ion characteristic scales: if at MHD scales there is no evidence for a dominance of a slab ( k l >> k ⊥ ) or 2-D ( k ⊥ >> k l ) turbulence, above the spectral break, ( f > f ci , kc /ω pi >1) the 2-D turbulence dominates. This 2-D turbulence is observed in six selected one-hour intervals among which the average ion β varies from 0.8 to 10. It is observed for both the transverse and compressive magnetic fluctuations, independently on the presence of linearly unstable modes at low frequencies or Alfven vortices at the spectral break. We then analyse the anisotropy of the magnetic fluctuations in a time dependent reference frame based on the field B and the flow velocity V directions. Within the range of the 2-D turbulence, at scales [1,30] kc /ω pi , and for any β we find that the magnetic fluctuations at a given frequency in the plane perpendicular to B have more energy along the B × V direction. This non-gyrotropy of the fluctuations at a fixed frequency is consistent with gyrotropic fluctuations at a given wave vector, with k ⊥ >> k l , which suffer a different Doppler shift along and perpendicular to V in the plane perpendicular to B .
Estimating the "neutral" real interest rate in real time

On September 20, the Federal Open Market Committee, the nation's monetary policymaking body, raised its target level of the federal funds rate by 25 basis points, the eleventh straight increase over the last fifteen months. The statement released immediately after the meeting said, "With underlying inflation expected to be contained, the Committee believes that policy accommodation can be removed at a pace that is likely to be measured. Nonetheless, the Committee will respond to changes in economic prospects as needed to fulfill its obligation to maintain price stability. " ; The statement clearly implies that the Committee believes that the real funds rate is below the so-called neutral real rate. What is the "neutral real rate"? According to Greenspan (1993), the real funds rate may be said to be neutral when it is at a level that, "if maintained, would keep the economy at its production potential over time. " Therefore, if the real funds rate is below the neutral real rate, policy is accommodative and the economy expands; if it is above the neutral real rate, policy is restrictive and the economy shrinks. ; The difficulty policymakers face is that it is not obvious exactly what the level of the neutral real rate is. It cannot be observed directly. There is no reliable way to estimate it. And it can change. ; This Economic Letter discusses the problems of estimation using both statistical methods and structural economic models. It focuses particularly on the vagaries of such estimations done in "real time," that is, without the benefit of long and reliable series of data.
Stability Analysis of Large-scale Time-delay Fuzzy Systems with Hybrid Models

One new method is presented in this paper to deal with the stability problems for a kind of complex large-scale fuzzy systems with hybrid models. These hybrid large-scale systems are composed of lots of interconnected subsystems, some of which are described by differential equations and others by Takagi-Sugeno fuzzy models. Also time-delay is considered in this paper. Novel techniques to cope with the interconnection between subsystems are developed. We obtain a set of LMI-based conditions to evaluate the stability of the whole system by checking the stability of the subsystems in parallel, where the computational complexity is greatly reduced. Finally, numerical simulation is given to illustrate its effectiveness.
Economic Freedom of the World: 2009 Annual Report

These four cornerstones underpin the design of the EFW index. Put simply, institutions and policies are consistent with economic freedom when they provide an infrastructure for voluntary exchange and protect individuals and their property from aggressors. In order to achieve a high EFW rating, a country must provide secure protection of privately owned property, even-handed enforcement of contracts, and a stable monetary environment. It also must keep taxes low, refrain from creating barriers to both domestic and international trade, and rely more fully on markets rather than the political process to allocate goods and resources. Since 1980, there has been a gradual but steady movement toward economic freedom. Monetary policy has been more stable, trade barriers have declined, high marginal tax rates reduced, and exchange rate controls virtually eliminated. Consider the following. The median inflation rate was 4% in 2007, down from 14% in 1980. Among the 93 countries with data in both periods, only 17 had a double-digit average annual rate of inflation during the period from 2003 to 2007, compared to 61 for the five years ending in 1980. The mean tariff rate fell from 26.2% in 1980 to 9.0% in 2007. The number of countries imposing marginal tax rates of 50% or more fell from 62 in 1980 to 9 in 2007. Fifty countries imposed exchange rate controls that generated a black market premium of 10% or more in 1980, but only three in 2007. The economic progress during this era has been impressive. The world’s inflation-adjusted, per-capita income rose from $5,400 in 1980 to $8,500 in 2005, an average annual growth rate of approximately 2% (Shleifer, 2009). Over this quarter of a century, the one-dollar-perday poverty rate fell from 34% to 19%, life expectancy has risen from 64.4 years to 68.1, and the infant mortality rate has fallen from 53% to 36%. Other indicators of quality of life such as school attendance, literacy, and access to clean water have all improved. Economic growth is primarily the result of gains from trade, capital investment, and the discovery of improved products, lower-cost production methods, and better ways of doing things. Numerous studies have shown that countries with more economic freedom grow more rapidly and achieve higher levels of per-capita income than those that are less free. Similarly, there is a positive relationship between changes in economic freedom and the growth of per-capita income. Given the sources of growth and prosperity, it is not surprising that increases in economic freedom and improvements in quality of life have gone hand in hand during the past quarter of a century.
A Fault-tolerance Framework for Distributed Component Systems

The requirement for higher reliability and availability of systems is continuously increasing even in domains not traditionally strongly concerned by such issues. Required solutions are expected to be efficient, flexible, reusable on rapidly evolving hardware and of course at low cost. Combining both model and component seems to be a very promising cocktail for building solutions to this problem. Hence, we will present in this paper an approach using a model as its first structural citizen all along the development process. Our proposal will be illustrated with an application modeled with UML (extended with some of its dedicated profiles). Our approach includes an underlying execution infrastructure/middleware, providing fault-tolerance services. For the component aspect, our framework promotes firstly an infrastructure based on the Component/Container/Connectorparadigm to provide run-time facilities enabling transparent management of fault-tolerance (mainly fault-detection and redundancy mechanisms). For the model-driven point of view, our framework provides tool support for assisting the users to model their applications and to deploy and configure them on computing platforms. In this paper we focus on the run-time support offered by the component framework, specially the replication-aw are interaction mechanism enabling a transparent replication management mechanisms and some additional system components dedicated to fault-detection and replicas management.
Study on Value Chain of Telecom VAS under Transformation Background

Driven by both technology and market, telecom industry is becoming a part of several converged industries in information society gradually from an independent industry which provides telecom products like voice or data. Under such background, this paper introduces a new value chain model of telecom value-added ser-vices in the new environment, providing theoretic support for transformation of telecom operators.
Fuzzy Approach for pattern recognition using Classification Algorithms

Fuzzy Logic (FL) is a multivalve logic that allows intermediate values to be defined between conventional evaluations like true/false, yes/no, high/low, etc. Pattern Recognition is the study of how machines can observe the environment, learn to distinguish patterns of interest from their background, and make sound and reasonable decisions about the categories of the patterns. ” Here we are using Supervised Classification (e.g. Discriminant Analysis) in which the input pattern is identified as a member of a predefined class and Unsupervised classification (e.g. clustering) in which the pattern is assigned to an unknown class. In this paper we are applying Fuzzy K-NN and K-NN both are classification methods (i.e. Supervised Learning and unsupervised learning) and classes identified by patterns and classifies by the K- nearest neighbors, it also give the previous knowledge about the problem classes