Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating a Structural Model of Herd Behavior in Financial Markets

We develop a new methodology for estimating the importance of herd behavior in financial markets. Specifically, we build a structural model of informational herding that can be estimated with financial transaction data. In the model, rational herding arises because of information-event uncertainty. We estimate the model using 1995 stock market data for Ashland Inc., a company listed on the New York Stock Exchange. Herding occurs often and is particularly pervasive on certain days. In an information-event day, on average, 2 percent (4 percent) of informed traders herd-buy (sell). In 7 percent (11 percent) of information-event days, the proportion of informed traders who herd-buy (sell) is greater than 10 percent. Herding causes important informational inefficiencies, amounting, on average, to 4 percent of the asset's expected value.
On Security of Sovereign Joins

The goal of a sovereign joinoperation is to compute a query across independent database relations such that nothing beyond the join results is revealed. Each relation involved in a sovereign join is owned by a distinct entity and the party posing the query is distinct from the relation owners; it is not permitted to access the original relations. One notable recent research result proposed a secure technique for executing sovereign joins. It entails data owners sending their relations to an independent database service provider which executes a sovereign join with the aid of a tamper-resistant secure coprocessor. This achieves the goal of preventing information leakage during query execution. However, as we show in this paper, the proposed technique is actually insecure as it fails to prevent an attacker from learning the query results. We also suggest some measures to remedy the security problems.
Evaluation and Comparison of Textural Feature Representation for the Detection of Early Stage Cancer in Endoscopy

Esophageal cancer is the fastest rising type of cancer in the Western world. The novel technology of High Definition (HD) endoscopy enables physicians to find texture patterns related to early cancer. It encourages the development of a Computer-Aided Decision (CAD) system in order to help physicians with faster identification of early cancer and decrease the miss rate. However, an appropriate texture feature extraction, which is needed for classification, has not been studied yet. In this paper, we compare several techniques for texture feature extraction, including co-occurrence matrix features, LBP and Gabor features and evaluate their performance in detecting early stage cancer in HD endoscopic images. In order to exploit more image characteristics, we introduce an efficient combination of the texture and color features. Furthermore, we add a specific preprocessing step designed for endoscopy images, which improves the classification accuracy. After reducing the feature dimensionality using Principal Component Analysis (PCA), we classify selected features with a Support Vector Machine (SVM). The experimental results validated by an expert gastroenterologist show that the proposed feature extraction is promising and reaches a classification accuracy up to 96.48%.
An Application of Session Based Clustering to Analyze Web Pages of User Interest from Web Log Files

Problem statement: With the continued growth and proliferation of e-co mmerce, Web services and Web-based information systems, the volumes of click-stream and user data collected by Web-based organizations in their daily operations h ave reached astronomical proportions. Analyzing such data can help these organizations optimize the functionality of web-based applications and provide more personalized content to visitors. This type of analysis involved the automatic discovery of usage interest on the web pages which are often stored in web and applications server access logs. Approach: The usage interest on the web pages in various sess ions was partitioned into clusters such that sessions with "similar" interest were placed i n the same cluster using expectation maximization clustering technique as discussed in this study. Results: The approach results in the generation of usage profiles and automatic identification of user interest in each profile. Conclusion: The significance of the results will be helpful for org anizations for web site improvement based on their navigational interest and provide recommendations f or page(s) not yet visited by the user.
The Impact on Social Relationships of Shared Picture Book Reading in Early Learning Classrooms in South Korea: An Exploratory Study

This study aims to explore how the reading of picture books aids in young children’s understanding of social relationships. The interactions between children and teachers in eight kindergartens and six nurseries during and after the shared reading of a picture book were observed and qualitatively analyzed. A semi-structured interview with each participating teacher was conducted a week after the observed reading. In all but two cases, it was found that the teachers had chosen a picture book with a storyline (“story-type book”). Many books described the nature of friendship and ways to build and maintain those relationships. The children were engaged in guessing, remembering the story line, and empathizing with the protagonists in the books. However, verbal interactions between children and teachers were led mainly by the teachers. Post-reading activities that had been pre-planned by the teachers included art, drama, writing letters or poems, singing, games and campaigning for causes related to the books that had been read. This study discusses the role of the teacher in the context of reading picture books themed on social relationships and implications to children’s character education.
Effect of Alveolar Bone Grafting on Nasal Morphology, Symmetry, and Nostril Shape of Patients with Unilateral Cleft Lip and Palate

Objective To evaluate nasal morphology, symmetry, and nostril shape in patients with unilateral cleft lip and palate following mixed-dentition alveolar bone grafting. Design Prospective stereophotogrammetric study. Setting Hospital-based. Patients Thirty-nine patients with a history of repaired unilateral cleft lip and palate who received an iliac crest alveolar bone graft were recruited prospectively to participate in the study. Each patient served as his/her own control. Interventions Partial facial impressions of all patients were acquired before and a minimum of 6 months after the alveolar bone grafting procedure. Image acquisition and analysis of the casts constructed from these models were carried out using three-dimensional stereophotogrammetry. Main Outcome Measures Surface-based registrations and linear measurements were performed to assess nasal morphology and nostril shape. A modified Procrustes technique was used to determine the change in nasal symmetry. A two-tailed, paired t test and an analysis of covariance were used to assess statistical significance. Results Significant side-to-side asymmetry exists in the nasal region of patients with unilateral cleft lip and palate, both before and after alveolar bone grafting. No significant changes were observed between pre–alveolar bone graft and post–alveolar bone graft images based on linear measurements, asymmetry scores, and registrations. Gender and surgeon were not significant factors. Conclusion Under the conditions of this study, mixed-dentition alveolar bone grafting appears to have no significant long-term effect on nasal morphology, symmetry, or nostril shape.
Creating the Computer Industry

The major underlying factors that shaped the computer industry as it emerged, beginning in the mid-1940s, are the focus of this paper. Unlike many accounts that primarily discuss technological developments, this paper examines the interaction of three equally important elements: technology, customers and suppliers. The evolution of the computer industry is shown to have been driven initially by national-security customers, and later by cost-sensitive commercial customers. Technological advances made in response to these two customer types are identified, and the successes and failures of suppliers are analyzed in terms of changing customer requirements.
A Quasi - Genetic Process Algebra

Process Algebras, PAs, are formalisms able to capture the behaviour of a computing system by, for example, giving the labelled transition system, LTS, where states are nodes and where all the possible evolutions of the system are arcs; The drawing of the complete LTS is a NP-hard task, so that, the reaching of a particular 'desired' state is a problem which deserves some heuristic for improving the amount resources to be carried out. Let's take a look to Artificial Intelligence: Genetic Algorithms, GA's are metaheuristic techniques that have obtained good results in problems in which exhaustive techniques fail due to the size of the search space. GA's (21, 11) have been widely used to solve problems in the fields of combinatorial and numerical optimization. Due to their stochastic nature, their behaviour when dealing with some problems is difficult to pre- dict. However, there have been many attempts to develop models related with some of their features. Thus, in their origin, Holland developed the Schemata Theory(21) which tried to demonstrate their functioning by assuming that those configurations of variables, schematas, which contribute to build a good solution, tend to spread through the population as generations pass. Later on, many other attempts have been carried out in order to model some features of these al- gorithms. Thus, statistical models to predict population sizing or time to convergence have been developed in (12), (16), (3). In other works, like (13) (3), Markov Chains have been used for the same purposes. In this paper, as first step to define a Genetic Process Algebra (a Process Algebra which uses GAs to only choose and unfold the more promising branches of the LTS), a basic GA is formally defined and specified by the Markovian Process Algebra ROSA.
On growth curves and mixture models

The multilevel model of change and the latent growth model are flexible means to describe all sorts of population heterogeneity with respect to growth and development, including the presence of sub-populations. The growth mixture model is a natural extension of these models. It comes at hand when information about sub-populations is missing and researchers nevertheless want to retrieve developmental trajectories from sub-populations. We argue that researchers have to make rather strong assumptions about the sub-populations or latent trajectory classes in order to retrieve existing population differences. A simulated example is discussed, showing that a sample of repeated measures drawn from two sub-populations easily leads to the mistaken inference of three sub-populations, when assumptions are not met. The merits of methodological advises on this issue are discussed. It is concluded that growth mixture models should be used with understanding, and offer no free way to growth patterns in unknown sub-populations. Copyright © 2006 John Wiley & Sons, Ltd.
Transitioning from basic school to grade one: early identification of students at-risk for reading difficulties

ABSTRACT The purpose of this study was to identify the types of early reading tasks with which final year (5–6 year olds) Jamaican basic school children are struggling that place them at-risk for reading difficulties. A sample of 409 (224 females, 185 males) children in the final year of basic school were tested using measures of language development, phonological awareness, letter identification and letter-sound knowledge. Language development was found to be an area of strength. On measures of phonological awareness, letter identification and letter-sound knowledge, their performance indicated that these are the early reading tasks that place them at-risk for reading difficulties as 40% failed to identify sounds in the initial or final position in words, 32% were unable to identify letters and to match them with their sound, and 70% were unable to blend sounds dictated to identify words. Early identification of children at-risk for reading difficulties was highlighted.
A Personalized Audio Web Service Using MPEG-7 and MPEG-21 Standards

This paper presents a web service which delivers personalized audio information. The personalization process is automated and decentralized. The metadata which support personalization are separated in two categories: the metadata describing user preferences stored at each user and the resource adaptation metadata stored at the web service host. The multimedia models MPEG-21 and MPEG-7 are used to describe metadata information and the Web Ontology Language (OWL) to produce and manipulate ontological descriptions. SPARQL is used for querying the OWL ontologies. The MPEG Query Format (MPQF) is also used, providing a well-known framework for applying queries to the metadata and to the ontologies.
PED is overexpressed and mediates TRAIL resistance in human non-small cell lung cancer

PED (phosphoprotein enriched in diabetes) is a death‐effector domain (DED) family member with a broad anti‐apoptotic action. PED inhibits the assembly of the death‐inducing signalling complex (DISC) of death receptors following stimulation. Recently, we reported that the expression of PED is increased in breast cancer cells and determines the refractoriness of these cells to anticancer therapy. In the present study, we focused on the role of PED in non‐small cell lung cancer (NSCLC), a tumour frequently characterized by evasion of apoptosis and drug resistance. Immunohistochemical analysis of a tissue microarray, containing 160 lung cancer samples, indicated that PED was strongly expressed in different lung tumour types. Western blotting performed with specimens from NSCLC‐affected patients showed that PED was strongly up‐regulated (>6 fold) in the areas of tumour compared to adjacent normal tissue. Furthermore, PED expression levels in NSCLC cell lines correlated with their resistance to tumour necrosis factor related apoptosis‐inducing ligand (TRAIL)‐induced cell death. The involvement of PED in the refractoriness to TRAIL‐induced cell death was investigated by silencing PED expression in TRAIL‐resistant NSCLC cells with small interfering (si) RNAs: transfection with PED siRNA, but not with cFLIP siRNA, sensitized cells to TRAIL‐induced cell death. In conclusion, PED is specifically overexpressed in lung tumour tissue and contributes to TRAIL resistance.
Acting under uncertainty: discrete Bayesian models for mobile-robot navigation

Discrete Bayesian models have been used to model uncertainty for mobile-robot navigation, but the question of how actions should be chosen remains largely unexplored. This paper presents the optimal solution to the problem, formulated as a partially observable Markov decision process. Since solving for the optimal control policy is intractable, in general, it goes on to explore a variety of heuristic control strategies. The control strategies are compared experimentally, both in simulation and in runs on a robot.
Differential Dependence of Axo-Dendritic and Axo-Somatic GABAergic Synapses on GABAA Receptors Containing the α1 Subunit in Purkinje Cells

Synapse formation and maintenance require extensive transsynaptic interactions involving multiple signal transduction pathways. In the cerebellum, Purkinje cells (PCs) receive GABAergic, axo-dendritic synapses from stellate cells and axo-somatic synapses from basket cells, both with GABAA receptors containing the α1 subunit. Here, we investigated the effects of a targeted deletion of the α1 subunit gene on GABAergic synaptogenesis in PCs, using electrophysiology and immunoelectron microscopy. Whole-cell patch-clamp recordings in acute slices revealed that PCs from α10/0 mice lack spontaneous and evoked IPSCs, demonstrating that assembly of functional GABAA receptors requires the α1 subunit. Ultrastructurally, stellate cell synapses on PC dendrites were reduced by 75%, whereas basket cell synapses on the soma were not affected, despite the lack of GABAA-mediated synaptic transmission. Most strikingly, GABAergic terminals were retained in the molecular layer of adult α10/0 mice and formed heterologous synapses with PC spines characterized by a well differentiated asymmetric postsynaptic density. These synapses lacked presynaptic glutamatergic markers and postsynaptic AMPA-type glutamate receptors but contained δ2-glutamate receptors. During postnatal development, initial steps of GABAergic synapse formation were qualitatively normal, and heterologous synapses appeared in parallel with maturation of dendritic spines. These results suggest that synapse formation in the cerebellum is governed by neurotransmitter-independent mechanisms. However, in the absence of GABAA-mediated transmission, GABAergic terminals in the molecular layer apparently become responsive to synaptogenic signals from PC spines and form stable heterologous synapses. In contrast, maintenance of axo-somatic GABAergic synapses does not depend on functional GABAA receptors, suggesting differential regulation in distinct subcellular compartments.
A RBAC model considering the user reliability in workflow system

Role based access control (RBAC) is one of the most important access control model, in this paper we present a kind of role-based access control model for workflow systems, named RW_RBAC. Based on the traditional RBAC system, this article introduces the conception of user's reliability to control the role assignment in the workflow system. With the help of it, the system can choose the more appropriate user to do the task when there is more than one candidate.
A Sandwich Electrochemical Immunosensor Using Magnetic DNA Nanoprobes for Carcinoembryonic Antigen

A novel magnetic nanoparticle-based electrochemical immunoassay of carcinoembryonic antigen (CEA) was designed as a model using CEA antibody-functionalized magnetic beads [DNA/Fe3O4/ZrO2; Fe3O4 (core)/ZrO2 (shell) nano particles (ZMPs)] as immunosensing probes. To design the immunoassay, the CEA antibody and O-phenylenediamine (OPD) were initially immobilized on a chitosan/nano gold composite membrane on a glassy carbon electrode (GCE/CS-nano Au), which was used for CEA recognition. Then, horseradish peroxidase (HRP)-labeled anti-CEA antibodies (HRP-CEA Ab2) were bound to the surface of the synthesized magnetic ZMP nanoparticles as signal tag. Thus, the sandwich-type immune complex could be formed between secondary antibody (Ab2) modified DNA/ZMPs nanochains tagged by HRP and GCE/CS-nano Au. Unlike conventional nanoparticle-based electrochemical immunoassays, the recognition elements of this immunoassay included both electron mediators and enzyme labels, which obviously simplifies the electrochemical measurement process. The sandwich-type immunoassay format was used for online formation of the immunocomplex of CEA captured in the detection cell with an external magnet. The electrochemical signals derived from HRP during the reduction of H2O2 with OPD as electron mediator were measured. The method displayed a high sensitivity for CEA detection in the range of 0.008–200 ng/mL, with a detection limit of 5 pg/mL (estimated at a signal-to-noise ratio of 3). The precision, reproducibility, and stability of the immunoassay were good. The use of the assay was evaluated with clinical serum samples, and the results were in excellent accordance with those obtained using the standard enzyme-linked immunosorbent assay (ELISA) method. Thus, the magnetic nanoparticle-based assay format is a promising approach for clinical applications, and it could be further developed for the detection of other biomarkers in cancer diagnosis.
Abundant Genetic Variation + Strong Selection = Multivariate Genetic Constraints: A Geometric View of Adaptation

Evolutionary biology has struggled to explain the coexistence of two basic observations: Genetic variation is found in almost all traits in the presence of strong natural and sexual selection in natural populations. These two observations are in direct conflict as such selection should deplete genetic variation. Furthermore, the presence of genetic variation in a trait, and selection acting on that trait, is often not sufficient for the trait to respond to selection. Here, we bring together geometric perspectives on mutation, selection, and genetic variation and show how the perceived incompatibility between these two observations is a consequence of taking a trait-by-trait approach to the multivariate problem of genetic variation and selection. We conclude that the simultaneous presence of widespead genetic variation in, and strong selection on, individual traits indicates that substantial multivariate genetic constraints are likely to be present in natural populations.
# # # # # # # # # # # Interaction Testing For GenexEnvironment

It is challenging to detect gene-environment interactions in a genome-wide setting because of low statistical power and the heavy computational burden involved. Paré (Paré et al, 2010) proposed a novel method variance prioritization (VP) for prioritizing single nucleotide polymorphisms (SNPs) by exploiting the interaction effects on the variance of quantitative traits. The prioritization is achieved by comparing the variance of a quantitative trait conditioned on three possible genotypes using Levene’s test (Levene, 1960) for variance inequality. The variance prioritization procedure consists of two steps:
Fault Isolation Based on Decision-theoretic Troubleshooting Fault Isolation Based on Decision-theoretic Troubleshooting

A decision-theoretic approach for fault isolation in broadband networks is presented. Our approach considers faults due to software and hardware as well as performance degradation and connguration problems. Belief networks are used to represent the relationships among various network entities. During a trou-bleshooting session, the network manager iteratively derives a sequence of tests based on the conditional probabilities, computed from statistics gathered (via alarms and tests) about the state of the network, and the costs associated with testing entities. An online dynamic programming technique is used to get the optimal sequence of tests. A system prototype that was implemented based on data from the XUNET testbed is also described.
Passivity, global stabilization and disturbance attenuation of weakly minimum-phase nonlinear uncertain systems with applications to mechatronic systems

Passivity and its applications to mechatronic systems have been widely investigated and continuously improved for many years. This paper presents methodologies for adaptive global stabilization and disturbance attenuation of a class of weekly minimum-phase nonlinear uncertain systems, which can be either of nonlinear affine or of relative degree 1. Adaptive passivity-based control (PBC) methods are developed to achieve adaptive stabilization and disturbance attenuation for the systems with some unknown but constant parameters. Sufficient conditions and state regulations are established for showing the closed-loop system to be globally stable. The merit and performance of the proposed methods are exemplified by conducting several simulations on a 2-linked manipulator. The developed techniques may be of interest to professionals working in the field of nonlinear passive control and its applications.
Constraint 3D elastic model for the segmentation in cardiac MRI

In this paper a 3D elastic model for the segmentation of cardiac magnetic resonance imaging has been proposed and analyzed. Elastic models for segmentation usually involve minimization of internal and external energy. A problem we observed with standard internal and external energy is that the local or the global reached minima do not impose the external energy to be zero. To eliminate this difficulty, we propose introducing a constraint. The constraint problem is proved to be mathematically well posed, and a simple algorithm which avoids computing the Lagrange multiplier is provided. This algorithm is proved to be convergent. Finally the efficiency of the method is shown with numerical experiments