Miracle-dz/UniFAR-FTUs huggingface dataset:
An algebraic approach for data-centric scientific workflows

Scientific workflows have emerged as a basic abstraction for structuring and executing scientific experiments in computational environments. In many situations, these workflows are computationally and data intensive, thus requiring execution in large-scale parallel computers. However, parallelization of scientific workflows remains low-level, ad-hoc and labor-intensive, which makes it hard to exploit optimization opportunities. To address this problem, we propose an algebraic approach (inspired by relational algebra) and a parallel execution model that enable automatic optimization of scientific workflows. We conducted a thorough validation of our approach using both a real oil exploitation application and synthetic data scenarios. The experiments were run in Chiron, a data-centric scientific workflow engine implemented to support our algebraic approach. Our experiments demonstrate performance improvements of up to 226% compared to an ad-hoc workflow implementation.
Anatomical Connections of the Visual Word Form Area

The visual word form area (VWFA), a region systematically involved in the identification of written words, occupies a reproducible location in the left occipitotemporal sulcus in expert readers of all cultures. Such a reproducible localization is paradoxical, given that reading is a recent invention that could not have influenced the genetic evolution of the cortex. Here, we test the hypothesis that the VWFA recycles a region of the ventral visual cortex that shows a high degree of anatomical connectivity to perisylvian language areas, thus providing an efficient circuit for both grapheme-phoneme conversion and lexical access. In two distinct experiments, using high-resolution diffusion-weighted data from 75 human subjects, we show that (1) the VWFA, compared with the fusiform face area, shows higher connectivity to left-hemispheric perisylvian superior temporal, anterior temporal and inferior frontal areas; (2) on a posterior-to-anterior axis, its localization within the left occipitotemporal sulcus maps onto a peak of connectivity with language areas, with slightly distinct subregions showing preferential projections to areas respectively involved in grapheme-phoneme conversion and lexical access. In agreement with functional data on the VWFA in blind subjects, the results suggest that connectivity to language areas, over and above visual factors, may be the primary determinant of VWFA localization.
Simplifying ADA by removing limitations

As presently proposed, ADA contains several rather arbitrary restrictions making the language unnecessarily complex, lacking in orthogonality and difficult to extend. This note illustrates how the elimination of such restrictions yields a simpler yet more powerful language. Particular topics are the following. A more flexible and natural interpretation of type equivalence removes the stringent limitations of the ADA name equivalence approach. Providing a uniform view on types, subprograms and modules solves most parameterization problems and dispenses with the need for a "generic" construct. Finally, a more complete specification for subprograms (and modules) removes some difficulties with side-effects and exception handling.
A MATLAB-Based Convolutional Neural Network Approach For Face Recognition System

The research on face recognition still continues after several decades since the study of this biometric trait exists. This paper discusses a method on developing a MATLAB-based Convolution Neural Network (CNN) face recognition system with Graphical User Interface (GUI) as the user input. The proposed CNN has the ability to accept new subjects by training the last two layers out of four layers to reduce the neural network training time. The image preprocessing steps were implemented in MATLAB, while the CNN algorithm was implemented in C language (using GCC compiler). The main purpose of this research is to develop a complete system of face recognition. A Graphical User Interface (GUI) in MATLAB links all the steps starting from image preprocessing to face identification process. Evaluation was carried out using the images of 40 subjects from AT & T database and 10 subjects from JAFFE database producing 100% accuracy with less than 1 minute average training time when inserting 1 to 10 new subjects into the system.
The Nature of the Importance-Satisfaction Relationship in Ratings: Evidence from the Normative Data of the Noel-Levitz Student Satisfaction Inventory

The nature of the relationship between importance and satisfaction in consumer ratings was studied on an aggregate basis using the national normative data from the last five annual surveys of student satisfaction conducted by the Noel-Levitz organization. The average importance and average satisfaction ratings for 11 scales of the Student Satisfaction Inventory were correlated. For three of the four college types (private 4-year, 2-year, and career), there was a linear relationship to the data, so that attributes with higher average satisfaction ratings also had higher average importance ratings. Conversely, when the mean importance and mean satisfaction ratings were plotted for the 4-year public colleges, there was a V-shape to the distribution, such that attributes with low average satisfaction or high average satisfaction received higher average importance ratings than the attributes with mid levels of satisfaction. These results indicate that both linear and non-linear associations between satisfaction and importance are possible.
Neural Patterns of the Implicit Association Test

The Implicit Association Test (IAT) is a reaction time based categorization task that measures the differential associative strength between bipolar targets and evaluative attribute concepts as an approach to indexing implicit beliefs or biases. An open question exists as to what exactly the IAT measures, and here EEG (Electroencephalography) has been used to investigate the time course of ERPs (Event-related Potential) indices and implicated brain regions in the IAT. IAT-EEG research identifies a number of early (250–450 ms) negative ERPs indexing early-(pre-response) processing stages of the IAT. ERP activity in this time range is known to index processes related to cognitive control and semantic processing. A central focus of these efforts has been to use IAT-ERPs to delineate the implicit and explicit factors contributing to measured IAT effects. Increasing evidence indicates that cognitive control (and related top-down modulation of attention/perceptual processing) may be components in the effective measurement of IAT effects, as factors such as physical setting or task instruction can change an IAT measurement. In this study we further implicate the role of proactive cognitive control and top-down modulation of attention/perceptual processing in the IAT-EEG. We find statistically significant relationships between D-score (a reaction-time based measure of the IAT-effect) and early ERP-time windows, indicating where more rapid word categorizations driving the IAT effect are present, they are at least partly explainable by neural activity not significantly correlated with the IAT measurement itself. Using LORETA, we identify a number of brain regions driving these ERP-IAT relationships notably involving left-temporal, insular, cingulate, medial frontal and parietal cortex in time regions corresponding to the N2- and P3-related activity. The identified brain regions involved with reduced reaction times on congruent blocks coincide with those of previous studies.
Book Reviews: The Language Complexity Game

From the Publisher: "How can language be both complex and subtle, yet simple and effortless? Eric Ristad's book tackles this deepest of questions with all the power and precision of modern computer science, coming up with the best analysis of human language complexity since Chomsky's famous demonstrations that natural languages cannot be described via simple linear patterns. " -- Robert C. Berwick, MIT "Eric Ristad's carefully reasoned and penetrating study brings together the theories of language structure and computational complexity in a most productive way, providing much new insight into the nature and use of language. " -- Noam Chomsky, MIT This monograph establishes a conceptually coherent and technically sound framework for the computational study of human language. The fundamental method of this framework is an adversarial game between two players, the first of whom attempts to establish that language is more complex than previously thought, and the second who tries to establish that language is less complex than previously thought. The expected outcome of such a language complexity game is a precise computational theory of language, that is empirically correct in all computationally significant respects. Ristad exemplifies this powerful framework with a far-ranging and detailed investigation of language computations related to anaphora. Artificial Intelligence series
Colour Interest Points for Image Retrieval

In image retrieval scenarios, many methods use interest point detection at an early stage to find regions in which descriptors are calculated. Finding salient locations in image data is crucial for these tasks. Observing that most current methods use only the luminance information of the images, we investigate the use of colour information in in- terest point detection. Based on the Harris corner detector, a way to use multi-channel images is explored and different colour spaces are evaluated. To determine the characteris- tic scale of an interest point, a new colour scale selection method is presented. We show that using colour informa- tion and boosting salient colours results in improved perfor- mance in retrieval tasks.
When the Rules of Discourse Change, but Nobody Tells You: Making Sense of Mathematics Learning From a Commognitive Standpoint

The interpretive framework for the study of learning introduced in this article and called commognitive is grounded in the assumption that thinking is a form of communication and that learning mathematics is tantamount to modifying and extending one's discourse. These basic tenets lead to the conclusion that substantial discursive change, rather than being necessitated by an extradiscursive reality, is spurred by commognitive conflict, that is, by the situation that arises whenever different interlocutors are acting according to differing discursive rules. The framework is applied in 2 studies, one of them featuring a class learning about negative numbers and the other focusing on 2 first graders learning about triangles and quadrilaterals. In both cases, the analysis of data is guided by questions about (a) features of the new mathematical discourse that set it apart from the mathematical discourse in which the students were conversant when the learning began; (b) students' and teachers' efforts toward the necessary discursive transformation; and (c) effects of the learning–teaching process, that is, the extent of discursive change actually resulting from these efforts. One of the claims corroborated by the findings is that school learning requires an active lead of an experienced interlocutor and needs to be fueled by a learning-teaching agreement between the interlocutor and the learners.
The “total cost of publication” in a hybrid open‐access environment: Institutional approaches to funding journal article‐processing charges in combination with subscriptions

As open‐access (OA) publishing funded by article‐processing charges (APCs) becomes more widely accepted, academic institutions need to be aware of the “total cost of publication” (TCP), comprising subscription costs plus APCs and additional administration costs. This study analyzes data from 23 UK institutions covering the period 2007–2014 modeling the TCP. It shows a clear rise in centrally managed APC payments from 2012 onward, with payments projected to increase further. As well as evidencing the growing availability and acceptance of OA publishing, these trends reflect particular UK policy developments and funding arrangements intended to accelerate the move toward OA publishing (“Gold” OA). Although the mean value of APCs has been relatively stable, there was considerable variation in APC prices paid by institutions since 2007. In particular, “hybrid” subscription/OA journals were consistently more expensive than fully OA journals. Most APCs were paid to large “traditional” commercial publishers who also received considerable subscription income. New administrative costs reported by institutions varied considerably. The total cost of publication modeling shows that APCs are now a significant part of the TCP for academic institutions, in 2013 already constituting an average of 10% of the TCP (excluding administrative costs).
Sodium Iodide Symporter and Phosphatase and Tensin Homolog Deleted on Chromosome Ten Expression in Cholangiocarcinoma Analysis with Clinicopathological Parameters

Background/Aims This study was performed to investigate the correlation of sodium iodide symporter (NIS) expression with the functionality and loss of phosphatase and tensin homolog deleted on chromosome ten (PTEN) expression in human cholangiocarcinoma (CCA). Methods Immunohistochemistry for the expression of NIS and PTEN was performed in 60 biopsy specimens of CCA. The clinicopathological parameters were retrospectively identified from medical records. The expression pattern of NIS and loss of PTEN expression were analyzed in association with the clinicopathological characteristics, including survival. Results Normal biliary trees displayed NIS expression, but hepatocytes did not. NIS expression was divided into two patterns: cytoplasmic and membranous. Fifty-nine cases, all except for one case, displayed NIS expression in tumor cells. Twenty-two cases (33.3%) were mixed pattern, and 39 cases (65.05%) were cytoplasmic pattern; the pure membranous pattern was not noted. There was no association between the NIS expression pattern and clinicopathological parameters, including age, sex, differentiation grade, T stage and tumor, node, metastasis stage (p>0.05). The survival rates were similar among various NIS expression patterns. Normal hepatocytes and biliary trees exhibited PTEN expression in the nucleus and cytoplasm. CCA cells displayed nuclear staining. Thirty-six (60.0%) of 60 cases displayed a loss of PTEN expression. The loss of PTEN expression was observed in the advanced T-stage group (p=0.0036), but there was no association between the loss of PTEN expression and other clinicopathological parameters (p>0.05). No association between the loss of PTEN expression and survival was noted. Conclusions NIS is expressed in most types of human CCA. The expression pattern suggests a role in cancer development. PTEN loss expression is common in the context of human CCA, especially in the advanced T stage.
Distant Supervision for Cancer Pathway Extraction from Text

Biological pathways are central to understanding complex diseases such as cancer. The majority of this knowledge is scattered in the vast and rapidly growing research literature. To automate knowledge extraction, machine learning approaches typically require annotated examples, which are expensive and time-consuming to acquire. Recently, there has been increasing interest in leveraging databases for distant supervision in knowledge extraction, but existing applications focus almost exclusively on newswire domains. In this paper, we present the first attempt to formulate the distant supervision problem for pathway extraction and apply a state-of-the-art method to extracting pathway interactions from PubMed abstracts. Experiments show that distant supervision can effectively compensate for the lack of annotation, attaining an accuracy approaching supervised results. From 22 million PubMed abstracts, we extracted 1.5 million pathway interactions at a precision of 25%. More than 10% of interactions are mentioned in the context of one or more cancer types, analysis of which yields interesting insights.
Fluid fragmentation shapes rain-induced foliar disease transmission

Plant diseases represent a growing threat to the global food supply. The factors contributing to pathogen transmission from plant to plant remain poorly understood. Statistical correlations between rainfalls and plant disease outbreaks were reported; however, the detailed mechanisms linking the two were relegated to a black box. In this combined experimental and theoretical study, we focus on the impact dynamics of raindrops on infected leaves, one drop at a time. We find that the deposition range of most of the pathogen-bearing droplets is constrained by a hydrodynamical condition and we quantify the effect of leaf size and compliance on such constraint. Moreover, we identify and characterize two dominant fluid fragmentation scenarios as responsible for the dispersal of most pathogen-bearing droplets emitted from infected leaves: (i) the crescent-moon ejection is driven by the direct interaction between the impacting raindrop and the contaminated sessile drop and (ii) the inertial detachment is driven by the motion imparted to the leaf by the raindrop, leading to catapult-like droplet ejections. We find that at first, decreasing leaf size or increasing compliance reduces the range of pathogen-bearing droplets and the subsequent epidemic onset efficiency. However, this conclusion only applies for the crescent moon ejection. Above a certain compliance threshold a more effective mechanism of contaminated fluid ejection, the inertial detachment, emerges. This compliance threshold is determined by the ratio between the leaf velocity and the characteristic velocity of fluid fragmentation. The inertial detachment mechanism enhances the range of deposition of the larger contaminated droplets and suggests a change in epidemic onset pattern and a more efficient potential of infection of neighbouring plants. Dimensionless parameters and scaling laws are provided to rationalize our observations. Our results link for the first time the mechanical properties of foliage with the onset dynamics of foliar epidemics through the lens of fluid fragmentation. We discuss how the reported findings can inform the design of mitigation strategies acting at the early stage of a foliar disease outbreak.
Who Will Answer My Question on Stack Overflow?

Stack Overflow is a highly successful Community Question Answering (CQA) service for software developers with more than three millions users and more than ten thousand posts per day. The large volume of questions makes it difficult for users to find questions that they are interested in answering. In this paper, we propose a number of approaches to predict who will answer a new question using the characteristics of the question (i.e. Topic) and users (i.e. Reputation), and the social network of Stack Overflow users (i.e. Interested in the same topic). Specifically, our approach aims to identify a group of users (candidates) who have the potential to answer a new question by using feature-based prediction approach and social network based prediction approach. We develop predictive models to predict whether an identified candidate answers a new question. This prediction helps motivate the knowledge exchanging in the community by routing relevant questions to potential answerers. The evaluation results demonstrate the effectiveness of our predictive models, achieving 44% precision, 59% recall, and 49% F-measure (average across all test sets). In addition, our candidate identification techniques can identify the answerers who actually answer questions up to 12.8% (average across all test sets).
Assessing self-efficacy and agency of secondary school students in a multi-cultural context: Implications for academic achievement

The concept of self -efficacy is based on the triadic reciprocality model symbolising a three way reciprocal relationship between: (a) personal factors i.e. cognition, emotion, and biological events (b) behaviour and (c) environmental factors (Maddux, 1995). Cognition, emotion and behaviour are the domains of personality which form the basis of research in self efficacy. Research has been extensive on the relationship between self-efficacy and performance attainment in academic settings. Self -report scales are common in the assessment of self-efficacy. Guidelines to construct scales to assess self -efficacy have been specified by Bandura (2001). These guidelines highlight the importance of developing self -report measures which are task specific, and take into consideration all three domains of self -efficacy and three levels within each domain. Suggestions to develop measures which are reliable and have content validity have been provided. The major aims of this present research were to assess students’ self -efficacy in mathematics, and explore agency. Participants were from multi-cultural secondary schools in Auckland. A scale was developed incorporating New Zealand curriculum specific items in mathematics for Years 11, 12 & 13, and items on related constructs which impact on self -efficacy such as: (a) motivation strategies, (b) cognitive and metacognitive strategies, (c) resource management, (d) self -regulated learning, (e meeting others’ expectations, and (f) self assertiveness. A qualitative self -report measure was designed to explore self -efficacy and agency in students. This paper reports the findings from this research in-progress, and discusses the implications for student achievement.
Hippocampal Activation and Memory Encoding in Borderline Personality Disorder

Individuals with borderline personality disorder (BPD) report everyday problems with forgetfulness and display deficits on standardized measures of memory functioning. The medial temporal lobe, involved in memory encoding and consolidation, is smaller in individuals with BPD and shows an altered pattern of resting metabolism. The neural correlates of disrupted memory formation in BPD have not been studied outside of the context of emotionallyvalenced material. To examine the neural underpinnings of memory encoding in BPD, the present study assessed eight females with BPD and an equal number of ageand sex-matched non-psychiatric controls. Participants viewed visual scenes during functional magnetic resonance imaging scanning and subsequently completed a recognition memory test outside the scanner. Compared to controls, individuals with BPD exhibited less activation in the right hippocampus for subsequently remembered versus forgotten scenes. These results suggest that hippocampal dysfunction during the formation of memories may underlie the memory disturbances associated with BPD.