Miracle-dz/UniFAR-FTUs huggingface dataset:
Lattice-based data structures for deterministic parallel and distributed programming

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Evidence-based digital literacy class for older, low-income African-American adults

ABSTRACT Based on our community engagement project involving 47 older, low-income African-American adults from a senior community center, this study analyzes how an underserved population acquires knowledge and skills related to digital technologies. We discuss the conceptualization, implementation, and evaluation of a weekly, four-month long computer class for members of the senior community center. Our mixed-method research shows the importance of taking into account both the multidimensional nature of adult learning and the social and cultural contexts in which learning occurs when working with underserved adult populations. Findings from our formative and evaluative research offer insights into changes in the computer class participants’ attitudes toward and perspectives on key digital literacy issues including security and privacy online and online information verification. Scholarly and policy implications are discussed in the context of digital competency and adult learning for marginalized populations.
bfb, a Novel ENU-Induced blebs Mutant Resulting from a Missense Mutation in Fras1

Fras1 is an extracellular matrix associated protein with essential roles in adhesion of epithelia and mesenchyme during early embryonic development. The adhesive function of Fras1 is achieved through interaction with a group of related proteins, Frem 1–3, and a cytoplasmic adaptor protein Grip1. Mutation of each of these proteins results in characteristic epithelial blistering and have therefore become known as “blebs” proteins. Human Fraser syndrome presents with a similar phenotype and the blebs mice have been instrumental in identification of the genetic basis of Fraser syndrome. We have identified a new ENU-induced blebs allele resulting from a novel missense mutation in Fras1. The resulting mouse strain, blood filled blisters (bfb), presents with a classic blebs phenotype but does not exhibit embryonic lethality typical of other blebs mutants and in addition, we report novel palate and sternal defects. Analysis of the bfb phenotype confirms the presence of epithelial-mesenchymal adhesion defects but also supports the emerging role of blebs proteins in regulating signalling during organogenesis. The bfb strain provides new opportunities to investigate the role of Fras1 in development.
Mixed coordination method for long-horizon optimal control problems

We present a new approach to solving long-horizon, discrete-time optimal control problems using the mixed coordination method. The idea is to decompose a long-horizon problem into subproblems along the time axis. The requirement that the initial state of a subproblem equal the terminal state of the preceding subproblem is relaxed by using Lagrange multipliers. The Lagrange multipliers and initial state of each subproblem are then selected as high-level variables. The equivalence of the two-level formulation and the original problem is proved for both convex and non-convex cases. The low-level subproblems are solved in parallel using extended differential dynamic programming (DDP). An efficient way to find the gradient and hessian of a low-level objective function with respect to high-level variables is developed. The high-level problem is solved using the modified Newton method. An effective procedure is developed to select initial values of multipliers based on the initial trajectory. The method can conv.
Influence of edge subdivision on the convex domination number

We study the influence of edge subdivision on the convex domination number. We show that in general an edge subdivision can arbitrarily increase and arbitrarily decrease the convex domination number. We also find some bounds for unicyclic graphs and we investigate graphs G for which the convex domination number changes after subdivision of any edge in G.
1 COLAB : RESEARCH AND DEVELOPMENT OF AN ONLINE LEARNING ENVIRONMENT FOR COLLABORATIVE DISCOVERY LEARNING

There are many design challenges which must be addressed in the development of collaborative scientific discovery learning environments. This paper presents an overview of how these challenges were addressed within Co-Lab, a web-based learning environment in which groups of learners can experiment through simulations and remote laboratories, and express acquired understanding in a runnable computer model. Co-Lab’s architecture is introduced and explicated from the perspective of addressing typical problem areas for students within collaborative discovery learning. From this view the processes of collaboration, inquiry, and modeling are presented with a description of how they have been supported in the past and how they are supported within Co-Lab’s design and tools. Finally a research agenda is proposed for collaborative discovery learning with the Co-Lab environment.
Removal of random-valued impulse noise using sparse representation

This paper proposes a novel two-stage denoising method for removing random-valued impulse noise from an image. First, an impulse noise detection scheme is used to detect the pixels which are likely to be corrupted by the impulse noise (called the noise candidates). Then the noise candidates are reconstructed by using the image inpainting method based on sparse representation in an iterative manner until convergence. The proposed method leads to a simple and very effective denoising algorithm for the random-valued impulse noise removal. It is experimentally shown that the proposed algorithm outperforms the state-of-the-art denoising techniques for the removal of impulse noise both visually and quantitatively.
Invisibility coherence for faster scan-line hidden surface algorithms

Invisibility coherence is a new technique developed to decrease the time necessary to render shaded images by existing scan-line hidden surface algorithms. Invisibility coherence is a technique for removing portions of a scene that are not likely to be visible. If a large portion of the scene is invisible, as is often the case in three-dimensional computer graphics, the processing time eliminated may be substantial. Invisibility coherence takes advantage of the observation that a minimal amount of processing needs to be done on objects (polygons, patches, or surfaces) that will be hidden by other objects closer to the viewer. This fact can be used to increase the efficiency of current scan-line algorithms, including both polygon-based and parametrically curved surface-based algorithms. Invisibility coherence was implemented and tested with the polygon hidden surface algorithm for constructive solid geometry developed by Peter Atherton [1]. The use of invisibility coherence substantially increases the efficiency of this scan-line algorithm. Invisibility coherence should work as well or even better with other scan-line hidden surface algorithms, such as the Lane-Carpenter, Whitted, and Blinn algorithms for parametrically curved surfaces [2]. , or the Watkins, Romney, and Bouknight algorithms for polygons [3, 4, 5].
Detecting Compositionality of Verb-Object Combinations using Selectional Preferences

In this paper we explore the use of selectional preferences for detecting noncompositional verb-object combinations. To characterise the arguments in a given grammatical relationship we experiment with three models of selectional preference. Two use WordNet and one uses the entries from a distributional thesaurus as classes for representation. In previous work on selectional preference acquisition, the classes used for representation are selected according to the coverage of argument tokens rather than being selected according to the coverage of argument types. In our distributional thesaurus models and one of the methods using WordNet we select classes for representing the preferences by virtue of the number of argument types that they cover, and then only tokens under these classes which are representative of the argument head data are used to estimate the probability distribution for the selectional preference model. We demonstrate a highly signicant correlation between measures which use these ‘typebased’ selectional preferences and compositionality judgements from a data set used in previous research. The type-based models perform better than the models which use tokens for selecting the classes. Furthermore, the models which use the automatically acquired thesaurus entries produced the best results. The correlation for the thesaurus models is stronger than any of the individual features used in previous research on the same dataset.
Some issues on the coherence of Min-based possibilistic causal networks

This paper focuses on Min-based possibilistic graphs which are natural counterparts of probabilistic causal networks. In particular, we discuss the coherence problem which concerns the nonrecovering of initial data provided by the expert. We show that the coherence problem should not be seen as a drawback, and has no influence neither on independence relations nor on propagation algorithms.
Decomposition of large-scale constrained problems using a genetic-based search

In this paper, a traditional genetic algorithm with an integer representation is developed to search suitable variable arrangements for decomposition problems into a Cooperative-Coevolution framework for large-scale constrained optimization problems. The function evaluation is based on the Variable Interaction Identification for Constrained Optimization Problems (VIIC), that detects interactions among variables in large-scale problems. The new algorithm is capable of getting variable arrangements where the number of subgroups, as well as variables in each subgroup, are not fixed as in traditional decomposition methods. The proposed method is compared against VIIC with neighborhood strategy (VIICN). Those algorithms are tested on a novel benchmark for large scale constrained problems with 100, 500 and 1000 dimensions. The numerical results indicate that the proposed method outperforms VIICN, with the computational time is greatly reduced, which makes DVIIC a viable method for solving large-scale constrained optimization problems.
Assessing the Value Relevance of Accounting Data after IFRS Introduction in Europe

European listed companies are required to prepare their consolidated financial statements in accordance to IFRS since 1st January 2005. IFRS are supposed lead to better accounting quality and to a closer association between market-based and accounting-based performance, or value relevance. We examine whether value relevance has improved after the compulsory adoption of IFRS using a sample of 3,721 companies listed on five European stock exchanges: Frankfurt, Madrid, Paris, London and Milan. We find little evidence of an improvement in value relevance. However, earnings are found to influence share price to a greater extent than prior to IFRS adoption, while the influence of the book value of equity is found to have decreased.
Towards Building Trusted Multinational Civil-Military Relationships Using Social Networks

Abstract : Trust in relationships is essential for deep sharing of information/intelligence and meaningful collaboration. Building the required level of trust is often a lengthy face-to-face process. Lack of trust seriously hampers effectiveness in situations such as emergency response to international crisis or the coming together of a coalition. Specifically, it leads to redundant analysis and information overload. Trust-based networks are a very promising avenue. Trust can be mapped to the digital world, at least partially, through attributes associated with Social Networking technologies. When combined with recommendation systems, trust-based results are better than traditional collaborative filtering techniques [1]. These systems have proven effective in finding good films to watch or for feeling confident about online purchasing, but can they be adapted to more high-stake endeavours such as intelligence information gathering? Since 2005, we have witnesses an unprecedented technological adaption rate in the form of social networking applications and the use of such recommender systems. However use by military and Other Government Departments (OGDs) has been very conservative. Can the formation of a military, OGD and Non-Government Organizations (NGO) social network allow for meaningful information sharing and trust between multinational civil-military actors? Would such a network increase access to pertinent operational information while decreasing the information overload of intelligence analysts? This paper takes a first look at the concepts of, trust, social networking, recommender systems and how they could be combined to decrease information overload.
Digitally mediated surveillance, privacy and social network sites

Drawing on the existing body of primarily youth-focused research, combined with two newer studies examining adults this annotated bibliography provides an examination of user understandings of digitally mediated surveillance (DMS) and privacy practices on social network sites (SNS). Particular focus will be paid to the key debate around youth and privacy attitudes (the ‘privacy paradox’), with an examination of newer research on adults and social network use. The emerging work on the ideologies, goals and beliefs of the companies behind SNS will also be examined
Ligand and Structure-Based Approaches for the Identification of Peptide Deformylase Inhibitors as Antibacterial Drugs

Peptide deformylase (PDF) is a metalloprotease catalyzing the removal of a formyl group from newly synthesized proteins, which makes it an important antibacterial drug target. Given the importance of PDF inhibitors like actinonin in antibacterial drug discovery, several reported potent PDF inhibitors were used to develop pharmacophore models using the Galahad module of Sybyl 7.1 software. Generated pharmacophore models were composed of two donor atom centers, four acceptor atom centers and two hydrophobic groups. Model-1 was screened against the Zinc database and several compounds were retrieved as hits. Compounds with Qfit values of more than 60 were employed to perform a molecular docking study with the receptor Escherichia coli PDF, then compounds with docking score values of more than 6 were used to predict the in silico pharmacokinetic and toxicity risk via OSIRIS property explorer. Two known PDF inhibitors were also used to perform a molecular docking study with E. coli PDF as reference molecules. The results of the molecular docking study were validated by reproducing the crystal structure of actinonin. Molecular docking and in silico pharmacokinetic and toxicity prediction studies suggested that ZINC08740166 has a relatively high docking score of 7.44 and a drug score of 0.78.
Breast Cancer Cells Induce Cancer-Associated Fibroblasts to Secrete Hepatocyte Growth Factor to Enhance Breast Tumorigenesis

It has been well documented that microenvironment consisting of stroma affects breast cancer progression. However, the mechanisms by which cancer cells and fibroblasts, the major cell type in stroma, interact with each other during tumor development remains to be elucidated. Here, we show that the human cancer-associated fibroblasts (CAFs) had higher activity in enhancing breast tumorigenecity compared to the normal tissue-associated fibroblasts (NAFs) isolated from the same patients. The expression level of hepatocyte growth factor (HGF) in these fibroblasts was positively correlated with their ability to enhance breast tumorigenesis in mice. Deprivation of HGF using a neutralizing antibody reduced CAF-mediated colony formation of human breast cancer cells, indicating that CAFs enhanced cancer cell colony formation mainly through HGF secretion. Co-culture with human breast cancer MDA-MB-468 cells in a transwell system enhanced NAFs to secret HGF as well as promote tumorigenecity. The newly gained ability of these “educated” NAFs became irreversible after continuing this process till fourth passage. These results suggested that breast cancer cells could alter the nature of its surrounding fibroblasts to secrete HGF to support its own progression through paracrine signaling.
Tail-recursive Distributed Representations and Simple Recurrent Networks

Representation poses important challenges to connectionism. The ability to compose representations structurally is critical in achieving the capability considered necessary for cognition. We are investigating distributed patterns that represent structure as part of a larger effort to develop a natural language processor. Recursive auto-associative memory (RAAM) representations show unusual promise as a general vehicle for representing classical symbolic structures in a way that supports compositionality. However, RAAMs are limited to representations for fixed-valence structures and can often be difficult to train. We provide a technique for mapping any ordered collection (forest) of hierarchical structures (trees) into a set of training patterns which can be used effectively in training a simple recurrent network (SRN) to develop RAAM-style distributed representations. The advantages in our technique are three-fold: first, the fixed-valence restriction on structures represented by patterns trained with RA.
The association between endothelial dysfunction and hypertensive retinopathy in essential hypertension

Background Endothelial dysfunction, which is characterized by an imbalance between relaxing and contracting factors, procoagulant and anticoagulant substances, and between pro-inflammatory mediators, may play a particularly significant role in the pathogenesis of atherosclerosis. Numerous experimental and clinical reports suggest that a high von Willebrand factor (vWF) level reflects endothelial damage or dysfunction. Hypertensive retinopathy (HR) is a condition characterized by a spectrum of retinal vascular signs in people with elevated blood pressure. The pathophysiological mechanism of HR is not completely understood. Elevated blood pressure alone does not fully account for the extent of retinopathy. Endothelial dysfunction and mechanisms known to be involved in vascular lesions may be involved in the pathophysiological mechanism of HR. Therefore, this study was designed to answer the following questions: (i) Do vWf levels change in HR? and (ii) Is there any relation between degree of HR and vWf levels? Material/Methods This study included 80 hypertensive patients with HR. Group 1 comprised 40 patients with grade I HR, and group 2 comprised 40 patients with grade II HR. We selected 40 healthy subjects for the control group. Results Level of vWf in group 2 was significantly higher than in group 1 (p=0.017) and the control group (p<0.001), and it was also higher in group 1 than in the control group (p<0.005). Also, vWf showed positive correlation with degree of HR in the hypertensive group (r=0.284, p=0.009) Conclusions Our study suggests that endothelial dysfunction, which is a mechanism known to be involved in vascular lesions, may promote the development of HR.
A spiking neural network model of the locust antennal lobe: Towards neuromorphic electronic noses inspired from insect olfaction

In analogy with the non-selectivity of gas sensors, an olfactory receptor neuron is not tuned to a specific odor and hence presents a lack of selectivity. Despite this shortcoming, insects have impressive abilities to recognize odors. Understanding how their olfactory system works could then be highly beneficial for designing efficient electronic noses. In particular, the antennal lobe, the first structure of the insect olfactory system, is known to encode odors by spatio-temporal patterns of activation of projection neurons. We propose here a simplified, but still biologically plausible, model of the locust antennal lobe. Our model is a network of single variable spiking neurons coupled via simple exponential synapses. Its reduced complexity allows a deeper understanding of the mechanisms responsible of the network oscillatory behavior and of the spatio-temporal coding of the stimulus. In particular, we show how a stimulus is robustly encoded at each oscillation of the network by a spatial assembly of quasi-synchronized projection neurons, each one being individually phase-locked to the local field potential. Moreover, it is shown that frequency adaptation is responsible of the temporal evolution of this spatial code and that this temporal aspect of the code is crucial in enhancing the distance between the representations of similar odors.
Predicate-based test generation for computer programs

The author first describes a number of existing testing strategies for simple predicates and then explains why intuitive extensions of such strategies are ineffective or impractical for testing compound predicates, which are predicates with one or more AND/OR operators. Two fault-based testing strategies for compound predicates are defined, BOR (Boolean operator) testing and BRO (Boolean and relational operator) testing. It is shown that for a predicate with n, n>0, AND/OR operators, at most n+2 (2*n+3) tests are needed to satisfy BOR (BRO) testing. Preliminary experimental results indicate that BOR and BRO testing are effective for the detection of various types of faults in a predicate and provide more specific guidance than branch testing for test generation. <<ETX>>
Effect of emotional experience on purch ase intention: a sequential mediation of social value and he donic value in a retail setting

The purpose of this study is to empirically examine the indirect effect of social and hedonic value on the relationship between emotional experience and purchase intention. The sample consists of 420 retail customers selected using the store intercept method. Process macro program is used to test the sequential mediating effect. The results of the study show that both social value and hedonic value individually mediates the relationship between emotional experience and purchase intention. Moreover, social and hedonic value sequentially mediates the relationship between emotional experience and purchase intention. Based on the study findings, managers should focus on improving the customer’s emotional experience by dealing with them as individuals with unique expectations. In addition, managers should lay a lot of emphasis on creating enjoyable and fun-packed shopping environment while at the same time creating an environment that encourages socialization.