Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-time electrophysiology in cognitive neuroscience : towards adaptive paradigms to study perceptual learning and decision making in humans

Today, psychological as well as physiological models of perceptual learning and decision-making processes have recently become more biologically plausible, leading to more realistic (and more complex) generative models of psychophysiological observations. In parallel, the young but exponentially growing field of Brain-Computer Interfaces (BCI) provides new tools and methods to analyze (mostly) electrophysiological data online. The main objective of this PhD thesis was to explore how the BCI paradigm could help for a better understanding of perceptual learning and decision making processes in humans. At the empirical level, I studied decisions based on tactile stimuli, namely somatosensory frequency discrimination. More specifically, I showed how an implicit sensory context biases our decisions. Using magnetoencephalography (MEG), I was able to decipher some of the neural correlates of those perceptual adaptive mechanisms. These findings support the hypothesis that an internal perceptual-reference builds up along the course of the experiment. At the theoretical and methodological levels, I propose a generic view and method of how real-time electrophysiology could be used to optimize hypothesis testing, by adapting the experimental design online. I demonstrated the validity of this online adaptive design optimization (ADO) approach to maximize design efficiency at the individual level. I also discussed the implications of this work for basic and clinical neuroscience as well as BCI itself
The structure of mode-locked regions in quasi-periodically forced circle maps

Using a mixture of analytic and numerical techniques we show that the mode-locked regions of quasi-periodically forced Arnold circle maps form complicated sets in parameter space. These sets are characterized by ‘pinched-off’ regions, where the width of the mode-locked region becomes very small. By considering general quasi-periodically forced circle maps we show that this pinching occurs in a broad class of such maps having a simple symmetry. © 2000 Elsevier Science B.V. All rights reserved.
Collaborative inquiry: Youth, social action, and critical qualitative research

Youth participatory action research is part of a revolutionary effort in educational research to take inquiry-based knowledge production out of the sole purview of academic institutions and include those who most directly experience the educational contexts that scholars endeavor to understand. Seeking to extend the robust legacy of participatory action research in schools and communities, in this article, we focus on the pedagogical contributions of youth participatory action research collaborations for the teaching of critical qualitative research. We discuss strategies developed and implemented in an after-school youth participatory action research seminar in order to highlight how collaborative educational spaces can contribute to teaching and engaging in critical qualitative research. We also reflect, in our role as educators and researchers, on the possibilities and limitations of teaching qualitative research critically and reflexively, particularly at the intersection of qualitative action research, critical literacies, and youth social action. We conclude with a discussion of the broader implications of collaborative inquiry for the teaching of qualitative research in education and beyond.
MPhil Macroeconomics : Economic Growth

2 Solow’s ‘shocker’ 5 2.1 Details of the model . 6 2.2 Steady state growth . 10 2.3 Technological change . 11 2.4 Growth accounting . 13 2.5 Decentralised economy . 17
Parallel Processing for Automatic Face Recognition using Eigenfaces

In this paper, we present a parallel face recognition algorithm based on \eigenfaces", which are known as the signiicant features because they are the eigenvec-tors(principal components) of a set of face images. Our work is composed of two phases: eigenface construction and face recognition. For the construction of eigenfaces, a solution of eigenvalue/eigenvector problem using parallel Jacobi transformation is suggested. In recognition phase, a set of weight components is calculated in parallel by projecting a input face image onto each of pre-computed eigenfaces at each processing elements(PE's). Our parallel face recognition approach were implemented and evaluated on the transputer based parallel computer using grey scale face images with moderately cluttered backgrounds. Experimental results reveals that time taken for both eigenface construction and recognition is sharply decreased as the number of PE's are increased.
Fluid extravasation caused by bladder perforation during bipolar transurethral resection using saline solution -a case report-

Transurethral resection of the prostate is the gold standard in the operative management of benign prostatic hyperplasia. Bipolar transurethral resection of the prostate using saline solution is a safe technique and reduces the risk of transurethral resection syndrome. This report discusses a rare complication of bipolar transurethral resection of the prostate: the extravasation of 0.9% saline solution into intraperitoneal and retroperitoneal cavities due to bladder perforation, resulting in respiratory difficulties.
Avoiding object misconceptions

This paper identifies and describes a number of misconceptions observed in students learning about object technology. It identifies simple, concrete, measures course designers and teachers can take to avoid these misconceptions arising. The context for this work centres on an introductory undergraduate course and a postgraduate course. Both these courses are taught by distance education. These courses both use Smalltalk as an introduction to object technology. More particularly, the undergraduate course uses Smalltalk as a first programming language.Distance education can limit the amount and speed of individual feedback that can be given in the early stages of learning. For this reason, particular attention has been paid to characterizing measures for avoiding elementary misconceptions seen in beginning learners. At the same time we also address some misconceptions observed in postgraduate students. The pedagogical issues discussed are of particular importance when devising an extended series of examples for teaching or assessment, or when designing a visual microworld to be used for teaching purposes.
Bursting Neurons Signal Input Slope

Brief bursts of high-frequency action potentials represent a common firing mode of pyramidal neurons, and there are indications that they represent a special neural code. It is therefore of interest to determine whether there are particular spatial and temporal features of neuronal inputs that trigger bursts. Recent work on pyramidal cells indicates that bursts can be initiated by a specific spatial arrangement of inputs in which there is coincident proximal and distal dendritic excitation (Larkum et al., 1999). Here we have used a computational model of an important class of bursting neurons to investigate whether there are special temporal features of inputs that trigger bursts. We find that when a model pyramidal neuron receives sinusoidally or randomly varying inputs, bursts occur preferentially on the positive slope of the input signal. We further find that the number of spikes per burst can signal the magnitude of the slope in a graded manner. We show how these computations can be understood in terms of the biophysical mechanism of burst generation. There are several examples in the literature suggesting that bursts indeed occur preferentially on positive slopes (Guido et al., 1992; Gabbiani et al., 1996). Our results suggest that this selectivity could be a simple consequence of the biophysics of burst generation. Our observations also raise the possibility that neurons use a burst duration code useful for rapid information transmission. This possibility could be further examined experimentally by looking for correlations between burst duration and stimulus variables.
Virtual Microscopy and Grid-Enabled Decision Support for Large-Scale Analysis of Imaged Pathology Specimens

Breast cancer accounts for about 30% of all cancers and 15% of cancer deaths in women. Advances in computer-assisted analysis hold promise for classifying subtypes of disease and improving prognostic accuracy. We introduce a grid-enabled decision support system for performing automatic analysis of imaged breast tissue microarrays. To date, we have processed more than 1 00 000 digitized specimens (1200 times 1200 pixels each) on IBM's World Community Grid (WCG). As a part of the Help Defeat Cancer (HDC) project, we have analyzed that the data returned from WCG along with retrospective patient clinical profiles for a subset of 3744 breast tissue samples, and have reported the results in this paper. Texture-based features were extracted from the digitized specimens, and isometric feature mapping was applied to achieve nonlinear dimension reduction. Iterative prototyping and testing were performed to classify several major subtypes of breast cancer. Overall, the most reliable approach was gentle AdaBoost using an eight-node classification and regression tree as the weak learner. Using the proposed algorithm, a binary classification accuracy of 89% and the multiclass accuracy of 80% were achieved. Throughout the course of the experiments, only 30% of the dataset was used for training.
Average and Quantile Effects in Nonseparable Panel Models

Nonseparable panel models are important in a variety of economic settings, including discrete choice. This paper gives identification and estimation results for nonseparable models under time-homogeneity conditions that are like �time is randomly assigned� or �time is an instrument. � Partial-identification results for average and quantile effects are given for discrete regressors, under static or dynamic conditions, in fully nonparametric and in semiparametric models, with time effects. It is shown that the usual, linear, fixed-effects estimator is not a consistent estimator of the identified average effect, and a consistent estimator is given. A simple estimator of identified quantile treatment effects is given, providing a solution to the important problem of estimating quantile treatment effects from panel data. Bounds for overall effects in static and dynamic models are given. The dynamic bounds provide a partial-identification solution to the important problem of estimating the effect of state dependence in the presence of unobserved heterogeneity. The impact of T, the number of time periods, is shown by deriving shrinkage rates for the identified set as T grows. We also consider semiparametric, discrete-choice models and find that semiparametric panel bounds can be much tighter than nonparametric bounds. Computationally convenient methods for semiparametric models are presented. We propose a novel inference method that applies in panel data and other settings and show that it produces uniformly valid confidence regions in large samples. We give empirical illustrations.
Interactive agent based user avatar in the virtual environment

Recent research of avatar-based user interfaces cannot adapt to different people and different situation for lack of personality. It would work more effectively that an interactive agent with certain personality preference acts as the user avatar in the virtual environment. Therefore, based on cognition and behavior theory, An ABI agent (Awareness-Based Interactive Agent) model is proposed to help people interactive in the virtual environment. Firstly, the definition of personality with degree description as well as the definition of action, mental state, and other descriptions was formally represented in ABI agent structure. Then based on a defined semantics information space, four typical personalities in term of semantics words are built for the sake of ABI agent intention generation. In order to build agent action mechanism, a utility function represented relationship between cost and benefit is defined. After mapping the intention in term of semantics word with the utility expression, intention generated is used for ABI agent to control the whole action process of choosing goal and planning action. Adjustment of agent personality domain is also discussed according to three different situations. The model has now realized as a design helper in a product industrial design supporting system. The result shows that the model is a valuable way for effective user interface development.
A United Access Control Model for Systems in Collaborative Commerce

The latest researches on access control model are dramatically different from conventional ones. Nowadays, most attention is paid to accessing across organizational boundaries. So, how to identify the applicant and determine authorization with limited information; how to express and exchange control rules expediently; how to protect confidential information and enhance collaboration simultaneously, are the most concerned problems. However, for large commercial organizations, a fine management of internal functions is of the same importance as external service management. It is very troublesome to control authorizations merely with attributes and composition of policies introduced from attribute-based access control (ABAC). So, we introduce a united access control model for systems in collaborative commerce, combining the advantages of conventional role-based access control (RBAC), task-based authentication control (TBAC) and that of recent ABAC and automated trust negotiation (ATN). Innovational ideas in the model are analyzed, and the implement architecture is discussed. The paper concludes with a summary of the united model’s benefits and future work.
Determinants of Online Auction Participation: How Much Do Web Knowledge and Risk Perception Matter?

This study extends the research on online consumer behavior by examining the effect of Web knowledge and risk perception on individual attitude towards and intention to participate in online auction. The survey findings show that individuals with high Web knowledge tend to form positive attitudes towards online auction. By contrast, individuals who have heightened concerns about Internet privacy and security show less favorable attitudes towards online auction. Consistent with the attitude-intention model, attitude appears to mediates the effect of know and risk perception on intention. Research and practical implications of these results are discussed.
Integrating Principles of Positive Minority Youth Development with Health Promotion to Empower the Immigrant Community: A Case Study in Chicago

ABSTRACT Growing vulnerabilities among immigrant families are further complicated by the context of US health care. This article discusses the critical need for health promotion initiatives that integrate principles of positive minority youth development. Mixed methods, including a CBPR (community-based participatory research) approach, are used to highlight narratives of immigrant youth who have participated in a health-promotion program infused within their high school curriculum. These narratives underscore contributing contextual influences and pathways to conscientization, civic action, how programming can effectively facilitate positive minority youth development, as well as individual and community-level empowerment that leads to increased health literacy.
Panel Cointegration Tests on the Fiscal Sustainability of German Laender

This paper provides new evidence on the sustainability of public finances in German states (Laender) by exploiting a newly compiled database covering the years 1950]2011. Unlike previous studies on Germany, we analyze fiscal sustainability by applying gsecond generationh panel cointegration techniques. A unique identification strategy for the selection of sub]panels improves the robustness of panel cointegration tests and reveals that Laender finances are hardly sustainable.
Identifying Emotion through Implicit and Explicit Measures: Cultural Differences, Cognitive Load, and Immersion

Measures of emotion should accurately characterize the nature of an emotional experience and determine whether that experience is universal or unique to a subgroup or culture. We investigated the value of assessing emotion through skin conductance (an easy-to-interpret physiological measure) and sliders (frequently used and direct measures of perceived emotion). This paper describes findings from two experiments. The first evaluated various slider configurations and found that measured emotions successfully characterized the emotional nature of short videos. The second experiment collected the slider and skin conductance measures of emotion while one sample of Japanese participants and another sample of Canadian participants viewed longer videos. The measures were sensitive enough to identify cultural differences consistent with existing literature and were also able to identify parts of the experience where members from different cultures reacted consistently, pinpointing content that provoked a universal experience. We offer a toolkit of data interpretation techniques to gain more insight into the implicit and explicit emotion data: analyses for expressiveness and agreement that can infer states such as engagement and fatigue. We summarize the aspects of our measurement approach and toolkit in a model: the ability to distinguish the emotional nature of stimuli, individuals, and affective interaction.
Head Start administrator and teacher perceptions of parental influence on preschool children’s nutrition education

Parents play a significant role in molding their children’s nutrition knowledge and behavior. The purpose of the present study was to explore parental influence on preschooler’s nutrition education from the perspectives of North Carolina–based Head Start coordinators and teachers. Investigators conducted 63 in-depth, structured interviews with Head Start Health/Nutrition Coordinators (n = 31) and teachers (n = 32). Interviews were recorded in digital audio format and transcribed verbatim. Following a grounded theory approach, researchers identified primary, emergent themes related to parental influence and a substantive-level model was developed. Head Start staff described parental background (i.e. nutrition knowledge, culture), socioeconomic status, food preferences and parental engagement/support of teacher provided nutrition education as the primary factors that affect preschooler’s nutrition education. The proposed theoretical model provides an initial understanding of the influence Head Start parents may have on their children’s nutrition education. The findings suggest more training and education opportunities for parents and teachers may be needed. Despite barriers, teachers and local community partners should continue to support parents in their efforts to reinforce positive nutrition messages among preschool children.
SiGe HMODFET "KAIST" micropower model and amplifier realization

The recently published small-signal KAIST model is used successfully to fit the measured RF characteristics of a novel SiGe n-HMODFET device operating at micropower levels and extracted small-signal model parameters for this device under micropower operation are presented here for the first time. This model is then used to predict the performance of a simple micropower amplifier (sub 300-/spl mu/W total power consumption), realized in SiGe technology, and a comparison of modeled versus measured data is included.
The Mass Function of Main-Sequence Stars in NGC 6397 from Near-Infrared and Optical High-Resolution Hubble Space Telescope Observations

We have investigated the properties of the stellar mass function in the globular cluster NGC 6397 through the use of a large set of Hubble Space Telescope (HST) observations. The latter include existing WFPC 2 images in the V and I bands, obtained at ~4. ′5 and 10' radial distances, as well as a series of deep images in the J and H bands obtained with the NIC 2 and NIC 3 cameras of the NICMOS instrument pointed, respectively, to regions located ~4. ′5 and ~3. ′2 from the center. These observations span the region from ~1 to ~3 times the cluster's half-light radius (rhl ≃ 3′) and have been subjected to the same, homogeneous data processing so as to guarantee that the ensuing results could be directly compared to one another. We have built color-magnitude diagrams that we use to measure the luminosity function of main-sequence stars extending from just below the turnoff all the way down to the hydrogen-burning limit. All luminosity functions derived in this way show the same, consistent behavior in that they all increase with decreasing luminosity up to a peak at MI ≃ 8.5 or MH ≃ 7 and then drop precipitously well before photometric incompleteness becomes significant. Within the observational uncertainties, at MI ≃ 12 or MH ≃ 10.5 (~0.09 M☉) the luminosity functions are compatible with zero. The direct comparison of our NIC 2 field with previous WFPC 2 observations of the same area shows that down to MH ≃ 11 there are no more faint, red stars than those already detected by the WFPC 2, thus excluding a significant population of faint, low-mass stars at the bottom of the main sequence. By applying the best available mass-luminosity relation appropriate to the metallicity of NGC 6397 and consistent with our color-magnitude diagrams to both the optical and the IR data, we obtain a mass function that shows a break in slope at ~0.3 M☉. No single-exponent power-law distribution is compatible with these data, regardless of the value of the exponent. We find that a dynamical model of the cluster can simultaneously reproduce the luminosity functions observed in the core, at ~3. ′2, 4. ′5, and 10' away from the center, as well as the surface brightness and velocity dispersion profiles of red giant stars, only if the model initial mass function (IMF) rises as m-1.6±0.2 in the range 0.8-0.3 M☉ and then drops as m0.2±0.1 below ~0.3 M☉. Adopting a more physical lognormal distribution for the IMF, we find that all these data taken together imply a best-fit distribution with mc ≃ 0.3 and σ ≃ 1.8.