Miracle-dz/UniFAR-FTUs huggingface dataset:
Size matters, but not for everyone: individual differences for contrast discrimination.

It is very well known that contrast detection thresholds improve with the size of a grating-type stimulus, but it is thought that the benefit of size is abolished for contrast discriminations well above threshold [e.g., Legge, G. E. , & Foley, J. M. (1980)]. Here we challenge the generality of this view. We performed contrast detection and contrast discrimination for circular patches of sine wave grating as a function of stimulus size. We confirm that sensitivity improves with approximately the fourth-root of stimulus area at detection threshold (a log-log slope of -0.25) but find individual differences (IDs) for the suprathreshold discrimination task. For several observers, performance was largely unaffected by area, but for others performance first improved (by as much as a log-log slope of -0.5) and then reached a plateau. We replicated these different results several times on the same observers. All of these results were described in the context of a recent gain control model of area summation [Meese, T. S. (2004)], extended to accommodate the multiple stimulus sizes used here. In this model, (i) excitation increased with the fourth-root of stimulus area for all observers, and (ii) IDs in the discrimination data were described by IDs in the relation between suppression and area. This means that empirical summation in the contrast discrimination task can be attributed to growth in suppression with stimulus size that does not keep pace with the growth in excitation.
The Temperature Distribution of Dense Molecular Gas in the Center of NGC 253

We present interferometric maps of ammonia (NH3) of the nearby starburst galaxy NGC 253. The observations have been taken with the Australia Telescope Compact Array and include the para-NH3 (1, 1) and (2, 2) and the ortho-NH3 (3, 3) and (6, 6) inversion lines. Six major complexes of dense ammonia are identified, three of them on either side of the starburst center, out to projected galactocentric radii of ~250 pc. Rotational temperatures are derived toward selected individual positions, as well as for the entire southeastern and northwestern molecular complexes. The application of radiative transfer large velocity gradient models reveals that the bulk of the ammonia molecules is embedded in a one-temperature gas phase. Kinetic temperatures of this gas are ~200 and 140 K toward the southwest and northeast, respectively. The temperatures under which ammonia was formed in the past are with ≳30 K also warmer toward the southwest than toward the northeast (~15-20 K). This is indicated by the ortho-ammonia-to-para-ammonia ratio, which is ~1 and 1.5-2.5 toward the southwest and northeast, respectively. Ammonia column densities in the brightest complexes are in the range of (6-11) × 1014 cm-2, which adds up to a total ammonia mass of ~20 M☉, about evenly distributed toward both sides of the nucleus. Ammonia abundances relative to H2 are ~3 × 10-8. In the southwestern complex, the ammonia abundances increase from the starburst center to larger galactocentric radii. Toward the center of NGC 253, NH3 (1, 1), (2, 2), and (6, 6) are detected in absorption against an unresolved continuum source. At the same location, however, ammonia (3, 3) is found in emission, which indicates maser activity. This would be the first detected extragalactic NH3 maser. Evidence for an expanding shell in the southwestern complex is provided. The shell, with a dynamical age of ~1.3 Myr, is centered on an X-ray point source that must be located within the dense gas of NGC 253. The shell and X-ray properties can be reproduced by the energy input of a highly obscured young stellar cluster with a mass of ~105 M☉, which also heats the dense gas. A current star formation rate of ~2.8 M☉ yr-1 is derived for the nuclear starburst in NGC 253 based on its 1.2 cm continuum emission.
Causal Structure in Conditional Reasoning

Causal Structure in Conditional Reasoning Tevye R. Krynski (tevye@mit.edu) Joshua B. Tenenbaum (jbt@mit.edu) Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology 77 Massachusetts Ave., Cambridge, MA 02139 The Wason selection task presents subjects with a conditional statement of the form “if p then q”, and asks subjects to choose evidence to determine whether the statement is true. Prior accounts of people’s responses on the selection task have emphasized logical reasoning (Wason, 1966; Ahn & Graham, 1999), probabilistic reasoning (Oaksford & Chater, 1994), or social reasoning (Cosmides, 1989), as well as others. In contrast, we argue that the selection task often engages causal reasoning: for conditional statements in which p and q are causally related, people choose cards that will be most useful to determine which of several candidate causal structures is correct for a given situation. We have developed a model that extends Oaksford & Chater’s (1994) probabilistic information gain framework to handle causal hypotheses. The information gain framework of OC Glymour & Cheng, 1998), category learning (Rehder, 2003; Ahn, 1999), and judgment under uncertainty (Krynski & Tenenbaum, 2003). In this paper we analyze the role of causal structure in conditional reasoning (Over & Jessop, 1998), and argue that people’s responses on the Wason selection task reflect sophisticated abilities to induce causal structure. An important open question in causal reasoning is how people’s background knowledge interacts with observations when inferring causal structure. Causal domain knowledge places important constraints on which cause-effect relationships exist and how the effects depend functionally on the causes (Pearl, 2000; Krynski & Tenenbaum, 2003; Ahn, Kalish, Medin, & Gelman, 1995). This effectively specifies a hypothesis space of candidate causal structures, which we model using causal Bayes nets (Pearl, 2000). Observational evidence can then be used to determine which causal structure is most likely. We propose that this interplay of causal domain knowledge and observational evidence underlies people’s judgments on the Wason selection task. Why interpret conditionals causally? In contrast to OC i.e., p causally influences q, q causally influences p, or they have some common cause. The term “causally influences” does not necessarily mean
Scripts, Plans and Knowledge

"Of what a strange nature is knowledge! It clings to the mind, when it has once seized on it, like a lichen on the rock," Abstract We describe a theoretical system intended to facilitate the use of knowledge In an understand­ ing system. The notion of script is introduced to account for knowledge about mundane situations. A program, SAM, is capable of using scripts to under­ stand. The notion of plans is introduced to ac­ count for general knowledge about novel situa­ tions. I. Preface In an attempt to provide theory where there have been mostly unrelated systems, Minsky (1974) recently described the as fitting into the notion of "frames. " Minsky at­ tempted to relate this work, in what is essentially language processing, to areas of vision research that conform to the same notion. Mlnsky's frames paper has created quite a stir in AI and some immediate spinoff research along the lines of developing frames manipulators (e.g. Bobrow, 1975; Winograd, 1975). We find that we agree with much of what Minsky said about frames and with his characterization of our own work. The frames idea is so general, however, that It does not lend itself to applications without further specialization. This paper is an attempt to devel­ op further the lines of thought set out in Schank (1975a) and Abelson (1973; 1975a). The ideas pre­ sented here can be viewed as a specialization of the frame idea. We shall refer to our central constructs as "scripts. " II. The Problem Researchers in natural language understanding have felt for some time that the eventual limit on the solution of our problem will be our ability to characterize world knowledge. Various researchers have approached world knowledge in various ways. Winograd (1972) dealt with the problem by severely restricting the world. This approach had the po­ sitive effect of producing a working system and the negative effect of producing one that was only minimally extendable. Charniak (1972) approached the problem from the other end entirely and has made some interesting first steps, but because his work is not grounded in any representational sys­ tem or any working computational system the res­ triction of world knowledge need not critically concern him. Our feeling is that an effective characteri­ zation of knowledge can result in a real under­ standing system in the not too distant future. We expect that programs based on the theory we out­ …
Methicillin-Resistant Staphylococcus Aureus: A Pervasive Pathogen Highlights the Need for New Antimicrobial Development

Staphylococcus aureus (S. aureus) has entered the spotlight as a globally pervasive drug-resistant pathogen. While historically associated exclusively with hospital-acquired infections in immunocompromised hosts, the methicillin-resistant form of S. aureus has been spreading throughout communities since the 1990s. Indeed, it has now become a common household term: MRSA. S. aureus has developed numerous mechanisms of virulence and strategies to evade the human immune system, including a host of surface proteins, secreted enzymes, and toxins. In hospital intensive care units, the proportion of MRSA-related S. aureus infections has increased strikingly from just 2 percent in 1974 to 64 percent in 2004. Its presence in the community has been rising similarly, posing a significant public health burden. The growing incidence of MRSA unfortunately has been met with dwindling efforts to develop new, more effective antibiotics. The continued emergence of resistant strains of bacteria such as MRSA demands an urgent revival of the search for new antibiotics.
A fatal outcome of thoracic aortic aneurysm in a male patient with bicuspid aortic valve

Thoracic aortic aneurysm is often an asymptomatic but potentially lethal disease if its most catastrophic complication – aortic dissection – occurs. Thoracic aortic dissection is associated with a high mortality rate despite ongoing improvement in its management. We report a fatal outcome of thoracic aortic aneurysm in a male patient with bicuspid aortic valve. The patient was qualified for elective surgery of the ascending aorta and aortic valve at the age of 39 but he did not agree to undergo the proposed procedure. Three years later, he experienced acute aortic dissection and died despite a prompt diagnosis and complex management.
A framework for privacy-preserving healthcare data sharing

As healthcare data is quite valuable to many organizations for scientific research or analysis, the demand of sharing healthcare data have been growing rapidly. Nevertheless, health care data usually contains a lot of patient privacy. Sharing that data directly would bring huge threaten to patient privacy. It's necessary to develop practical methods to balance health care data sharing and privacy protection. Although many approaches have been developed to deal with these problems, most of them are focusing on a small scope of the problem with single theory. In this paper, we'd like to introduce a framework for privacy preserving data sharing with the view of practical application in more comprehensive way. The framework focuses on three key problems of privacy protection during data sharing which are privacy definition and detection, privacy protection policy management, privacy preserving health care data sharing. And solutions to these three problems are discussed in details. A simple implementation of the framework would be introduced to solve the problems of privacy-preserving electronic medical records publishing.
A collaborative speech enhancement approach for speech recognition in motorcycle environment

Aiming at the optimization of the speech recognition performance, we investigate various configurations for a speech front-end, which is part of a multimodal dialogue interaction interface of a wearable solution for information support of the motorcycle police force on the move. Initially, the practical value of various speech enhancement techniques is assessed, and subsequently a collaborative scheme employing independent speech enhancement channels, which operate in parallel on a common input, is proposed. It was experimentally found that the Adaboost.M1 algorithm is the most advantageous among a number of fusion methods. The improvement of speech recognition accuracy due to the collaborative speech enhancement scheme is expressed as gain of 8 % in terms of word recognition rate, when compared to the performance of the best speech enhancement channel, alone.
RSA AUTHENTICATION MECHANISMS IN CONTROL GRID COMPUTING ENVIRONMENT USING GRIDSIM TOOLKIT

There are security concerns when our sensitive data is placed in the third party infrastructure such as in the Grid Computing environment. As such, it is difficult to be assured that our data is in the safe hands.Thus, authentication has become the most critical factor pertaining to this.There are several approaches has been discussed in the grid computing environment on the safeguard, scalable and efficient authentication that are either Virtual Organization centric or Resource centric.Most of the grid computing uses public key infrastructure (PKI) to secure the identification, but the vulnerability are still cannot be avoid. In order to satisfy the security need of grid computing environment, we design an alternative authentication mechanism using RSA algorithm to ensure the user identification, and carry out the experiment in the Gridsim toolkit simulator.
Finding the Right Expert - Discriminative Models for Expert Retrieval

We tackle the problem of expert retrieval in Social Question Answering (SQA) sites. In particular, we consider the task of, given an information need in the form of a question posted in a SQA site, ranking potential experts according to the likelihood that they can answer the question. We propose a discriminative model (DM) that allows to combine different sources of evidence in a single retrieval model using machine learning techniques. The features used as input for the discriminative model comprise features derived from language models, standard probabilistic retrieval functions and features quantifying the popularity of an expert in the category of the question. As input for the DM, we propose a novel feature design that allows to exploit language models as features. We perform experiments and evaluate our approach on a dataset extracted from Yahoo! Answers, recently used as benchmark in the CriES Workshop, and show that our proposed approach outperforms i) standard probabilistic retrieval models, ii) a state-of-the-art expert retrieval approach based on language models as well as iii) an established learning to rank model.
Polarity of points for Gaussian random fields

We show that for a wide class of Gaussian random fields, points are polar in the critical dimension. Examples of such random fields include solutions of systems of linear stochastic partial differential equations with deterministic coefficients, such as the stochastic heat equation or wave equation with space–time white noise, or colored noise in spatial dimensions k≥1k≥1. Our approach builds on a delicate covering argument developed by M. Talagrand [Ann. Probab. 23 (1995) 767–775; Probab. Theory Related Fields 112 (1998) 545–563] for the study of fractional Brownian motion, and uses a harmonizable representation of the solutions of these stochastic PDEs.
Local analysis of visual motion

We inhabit an ever-changing environment, in which sensing, processing and acting upon these changes can be essential for survival. When we move or when objects in the world move, the visual images projected onto each of our retinas change accordingly. The psychologist J. J. Gibson noted that important environmental information is embedded in this pattern of local retinal image velocities (Gibson, 1950), and thus initiated a scientific quest to understand the mechanisms that might serve to estimate and represent these velocities. Since that time, visual motion perception has been the subject of extensive research in perceptual psychology, visual neurophysiology, and computational theory.
Self-Organized Cooperation in Swarm Robotics

Cooperation is a key concept used in multi-robot systems for performing complex tasks. In swarm robotics, a self-organized cooperation is applied, where robots with limited intelligence cooperate and interact locally to build up the desired global behavior. In this paper, we are studying a mobile object tracking scenario performed by a swarm of robots. The robustness, scalability and flexibility of swarm robots make it an attractive approach for missions like object tracking in complex and dynamic environments. As the individual robot capabilities are limited in swarm systems, the robots may not be able to track the mobile object continuously. This limitation is overcome using the robots communication capability. In order to increase the probability of object detection, we propose a greedy self-deployment strategy, where the robots are spread uniformly in the environment to be monitored. For detecting a moving target, the robots use a biologically inspired algorithm for collecting robots currently located in other regions to track the target. In such cooperative tasks the robots normally need to be time synchronized for simultaneous activation. A new proposal for time synchronization in swarm robots is introduced which exploits the mobility of the robots for handling possible disconnections in the network and synchronize them at the beginning of tracking time slots.
Health and Labour Income of Wage Earners and Self-Employed Workers in Cameroon

The objective of this paper is to assess the relationship between the health and the income from work of wage earners and self-employed workers in Cameroon. Health status is measured by a self-assessment of an individual's health; and income is measured by the monthly wage of the wage earners and monthly profits of the self-employed workers. This paper uses a simultaneous equation model to explore the relationship between health and income, allowing for the endogeneity of health, income, and selection into each employment status. The data used in this study is obtained from the 2007 Cameroon household consumption survey. Using OLS estimates, we find a positive and significant effect of health on labour incomes for self-employed workers. Using TSLS IV estimates, we find that health has a positive and significant effect on incomes for self-employed women, but not for men. We also undertake a reverse effect analysis from income to health, using the ordered probit estimation process. We find that, for men, the effect of income on health status is positive and significant for wage earners. For women, this effect is positive and significant for the self-employed.
Decreased hippocampal volume in healthy girls at risk of depression.

CONTEXT Researchers have documented that the hippocampus is smaller in individuals with depression than in those without. The temporal or causal association of this reduction in hippocampal volume in depression, however, is not known. OBJECTIVE To test the hypothesis that reduced hippocampal volume precedes and therefore may be implicated in the onset of depression. DESIGN We used magnetic resonance imaging to examine brain structure volume in individuals at high and low familial risk of depression. Anatomic images from magnetic resonance imaging were analyzed using both whole-brain voxel-based morphometry and manual tracing of the bilateral hippocampus. SETTING A research university. PARTICIPANTS Fifty-five girls aged between 9 and 15 years: 23 daughters of mothers with recurrent episodes of depression in the daughter's lifetime (high risk) and 32 age-matched daughters of mothers with no history of psychopathology (low risk). None of the girls had any past or current Axis I psychopathology. MAIN OUTCOME MEASURES Group differences in voxel-based morphometry brain matter density estimates and traced hippocampal volume. RESULTS Voxel-based morphometry analyses indicated that individuals at high risk of depression had significantly less gray matter density in clusters in the bilateral hippocampus (P < .001) than low-risk participants. Tracing yielded a volumetric reduction in the left hippocampus in the high-risk participants (P < .05). CONCLUSIONS Compared with individuals at low familial risk of the development of depression, high-risk individuals have reduced hippocampal volume, indicating that neuroanatomic anomalies associated with depression may precede the onset of a depressive episode and influence the development and course of this disorder.
Enhanced binary patterns for electrocardiogram (ECG) biometrics

Most, if not all, binary patterns variants consider signals observations separately; hence, binary patterns variants ignore any relationship among observations. In this paper we proposed an algorithm that enhances binary patterns extraction to accommodate for temporal progression changes. The enhanced binary patterns feature extraction extracts a single feature vector that captures changes occurred to observations over time. This enhancement is crucial in cases where the examined signal is repetitive in nature, such as ECG signal. Enhanced binary patterns were examined for ECG biometric application on ECG database with 1,012 subjects. The enhanced binary patterns achieved an EER of 7.89% in comparison to 12.4% and 12.3% for non-enhanced binary patterns and a state of the art work. We also showed that enhanced binary patterns features are capable to extract discriminative ECG features that reduced EER by 15% when compared to time-domain raw samples.
INDUCTION COUPLING BETWEEN JOINTLESS TRACK CIRCUITS AND TRACK-CIRCUIT-READER ANTENNA

This paper presents herein experiments and calculations of electromagnetic induction between jointless track circuits (JTCs) and track-circuit readers (TCRs). The paper uses transmission-line theory to simulate JTC currents ahead of shunt points and electromagnetism to calculate voltages induced in the TCR antenna. Based on these calculations, the JTC-to-TCR range is deflned. The paper derives expressions for the amplitude and phase of the voltage induced in the TCR antenna by the JTC current and uses them to quantitatively analyze the train control system. Experiments verify the conclusions reached based on the calculations.
Adaptive Convex Combination of APA and ZA-APA algorithms for Sparse System Identification

In general, one often encounters the systems that have sparse impulse response, with time varying system sparsity. Conventional adaptive filters which perform well for identification of non-sparse systems fail to exploit the system sparsity for improving the performance as the sparsity level increases. This paper presents a new approach that uses an adaptive convex combination of Affine Projection Algorithm (APA) and Zero-attracting Affine Projection Algorithm (ZA-APA)algorithms for identifying the sparse systems, which adapts dynamically to the sparsity of the system. Thus works well in both sparse and non-sparse environments and also the usage of affine projection makes it robust against colored input. It is shown that, for non-sparse systems, the proposed combination always converges to the APA algorithm, while for semi-sparse systems, it converges to a solution that produces lesser steady state EMSE than produced by either of the component filters. For highly sparse systems, depending on the value of the proportionality constant ($\rho$) in ZA-APA algorithm, the proposed combined filter may either converge to the ZA-APA based filter or produce a solution similar to the semi-sparse case i.e., outerperforms both the constituent filters.