Miracle-dz/UniFAR-FTUs huggingface dataset:
Manipulating a synchronous or separatist group orientation to improve performance on a hidden profile task

Effective use of available information is a problem that plagues group decision-making tasks. Groups heavily favor shared information, or information that is known to all group members, which can lead to incorrect decisions and selection of inferior alternatives. However, groups may be less prone to overlooking unshared information if they are focused to value uniqueness and novel input from group members. The present research demonstrates that groups that value uniqueness, or a separatist orientation, correctly solved a hidden profile task more often than groups with a synchronous orientation, or groups that value similarity. Separatist groups repeated more unshared information than synchronous overall. Separatists also repeated more shared information than synchronous groups. Further, groups with a correct minority member also repeated more unshared information than groups with either a majority correct or no correct members. Results are discussed in terms of group focus and biases that affect the discussion of information.
Modeling Interaction in Information Retrieval (IR): A Review and Proposal.

The purpose is to critically examine traditional and interactive models that have emerged over the years in IR, particularly in relation to evaluation, and to propose an interactive IR model based on different levels in the interactive processes. The proposal is presented as work-in-progress. The traditional IR model was explicitly or implicitly adapted in majority of algorithmic works on IR, and it is the major model used in Text Retrieval Conference (TREC). Strengths and weaknesses of the traditional model are examined. The major weakness of that model is that it does not account for or incorporate IR interaction, which is the dominant feature of contemporary IR in practice. Several interactive IR models have been developed over the years; the cognitive model by Ingwersen and the episodes model by Belkin are examined. However, no leading and commonly accepted interactive IR model has emerged, particularly not in evaluation. A stratified interactive IR model is proposed here with suggestion that it has a potential to account for a variety of aspects in the processes involved in IR interaction. It is suggested that IR interaction may be decomposed into several levels that subtly affect each other. The paper concludes with general remarks on the state of IR interaction research.
Information Extraction in the Business Intelligence Context

Business Intelligence (BI) relies on corporate data to derive information for supporting strategic decisions. Source data internal to the corporation are used to assess productivity, lucrativeness, quality, etc, whereas external data are used to evaluate market share, expansion opportunities, competitiveness, etc. In a typical BI scenario, structured data, usually gathered from application databases, are integrated in Data Warehouses to support analytical tools. There is, however, a wealth of unstructured data which is harder to integrate but can provide valuable information: formal documents, reports, exchanged messages, and numerous websites on the internet. Information Extraction (IE) is one of the main players in harvesting the unstructured information embedded in digital documents. Researchers have developed a wide range of techniques to surface structured information from virtually all types of documents. Access to structured information enables richer analysis of data, which is the main goal of BI. This document describes research in IE and typical approaches to BI. This document is not intended as a survey on IE theory or techniques – for that we recommend the papers by Sarawagi [46] and Nadeau & Sekine [36]. Nor is the document intended to cover a broad range of BI issues, which are detailed in the books by Imhoff et al. [24] and Jarke et al. [28]. The objective of this document is to present typical approaches to IE and BI, to describe research that integrates the two areas, and to provide some insight on what may improve the applicability of IE techniques in BI scenarios. Section 2 presents IE research, analyzing techniques according to the type of input document, the dimensionality of the target extraction, and the variations on the typical IE workflow. Section 3 describes stablished BI technology and approaches to leverage documents in a BI scenario. It also suggests in which areas IE systems could be adapted to facilitate their use in BI tasks. Section 4 concludes the paper.
Towards Learning Coupled Representations for Cross-Lingual Information Retrieval

We explore the use of dictionary-based approaches for cross-lingual information retrieval tasks and propose a novel Coupled Dictionary Learning (CDL) algorithm to learn two separate representations simultaneously for documents in a parallel corpus alongside learning mappings from one representation to the other. We evaluate the performance of the proposed algorithm for the task of comparable document retrieval and compare with existing baselines.
Acute Hepatic Encephalopathy Presenting as Cortical Laminar Necrosis: Case Report

We report on a 55-year-old man with alcoholic liver cirrhosis who presented with status epilepticus. Laboratory analysis showed markedly elevated blood ammonia. Brain magnetic resonance imaging (MRI) showed widespread cortical signal changes with restricted diffusion, involving both temporo-fronto-parietal cortex, while the perirolandic regions and occipital cortex were uniquely spared. A follow-up brain MRI demonstrated diffuse cortical atrophy with increased signals on T1-weighted images in both the basal ganglia and temporal lobe cortex, representing cortical laminar necrosis. We suggest that the brain lesions, in our case, represent a consequence of toxic effect of ammonia.
Frequency of arrival-based interference localization using a single satellite

Intentional and unintentional interferences are an increasing threat for the satellite communications industry. In this paper, we aim to localize an interference with unknown location using frequency of arrival (FoA) technique by only relying on the measurements obtained through a single satellite. In each time instance, the satellite samples the interference and forwards it to the gateway to estimate its frequency. Since the satellite moves, each estimated frequency includes a Doppler shift, which is related to the location of the unknown interferer. The satellite's position, velocity, oscillator frequency, and the interference frequency are used at the gateway to build a location-related equation between the estimated frequency and the location of the unknown interference. Simultaneously with the interference signal, the satellite samples a reference signal to calibrate the estimated frequency and compensate for the mismatches between the available and real values of the satellite's position, velocity, and oscillator frequency. Multiple location- related equations obtained based on the FoA measurements, (at least two), along with the equation of the earth surface are used to localize the unknown interference. Simulations show that increasing the number of these equations, and the satellite velocity can improve the localization accuracy by 80% and 95%, respectively.
Overfitting in protein name recognition on biomedical literature and method of preventing it through use of transductive SVM

Machine learning methods have been used in research on protein name recognition. A classifier trained in a specific domain, however, could be overfit and so inflexible that it could be used only in that domain. We therefore developed a new corpus about breast cancer and investigated the flexibility of classifier trained on the GENIA (T. Ohta, 2002) corpus or the breast cancer corpus. To avoid overfitting we used the transductive support vector machine (SVM), and we evaluated the effect of transductive learning. We confirmed experimentally that the tranductive SVM prevented overfitting and yielded higher accuracies than the ordinary SVM did
Ensuring compatible interactions within component-based software systems

The interface definition of a component in a distributed system forms the contract between the component itself and its neighbouring components regarding the use of its services. In general, such a contract should cover the issues of service functionality, usage and quality. The interface definition languages (IDLs) used by commercial middleware standards such as CORBA primarily address the signature issues of such a contract, i.e., the forms and types of component or object services. Nothing is said about other aspects of the contract, including the way in which the component services are to be used. We introduce a framework and associated techniques that augment commercial IDLs with interaction protocol specifications and validate component interactions against such protocol specifications at run-time. In effect, the validation becomes a useful tool for testing whether or not the object services are used properly in a distributed system. Our approach has been implemented in the CORBA context, but can be readily applied to other IDL-based object/component systems.
Acute Toxicity and Gastroprotection Studies with a Newly Synthesized Steroid

Background Synthetic steroids, such as 9α-bromobeclomethasonedipropionate, have shown gastroprotective activity. For example, the potent glucocorticoid steroid, beclomethasone dipropionate, has been used for treatment of bowel ulcerations. The purpose of the present study was to evaluate the effect of a synthetic steroid, (20S)-22-acetoxymethyl-6β-methoxy-3α,5-dihydro-3′H-cyclopropa[3α,5]-5α-pregnane (AMDCP), on ethanol-induced gastric mucosa injuries in rats. Methodology/Principal Finding Rats were divided into 8 groups. The negative control and ethanol control groups were administered Tween 20 (10%v/v) orally. The reference control group, 20 mg/kg omeprazole (10% Tween 20, 5 mL/kg), was administrated orally. The experimental groups received 1, 5, 10, 15 or 20 mg/kg of the AMDCP compound (10% Tween 20, 5 mL/kg). After 60 min, Tween 20 and absolute ethanol was given orally (5 mL/kg) to the negative control group and to the rest of the groups, and the rats were sacrificed an hour later. The acidity of gastric content, gastric wall mucus and areas of mucosal lesions were assessed. In addition, histology and immunohistochemistry of the gastric wall were assessed. Prostaglandin E2 (PGE2) and malondialdehyde (MDA) content were also measured. The ethanol control group exhibited severe mucosal lesion compared with the experimental groups with fewer mucosal lesions along with a reduction of edema and leukocyte infiltration. Immunohistochemical staining of Hsp70 and Bax proteins showed over-expression and under-expression, respectively, in the experimental groups. The experimental groups also exhibited high levels of PGE2 as well as a reduced amount of MDA. AMDCP decreased the acidity and lipid peroxidation and increased the levels of antioxidant enzymes. Conclusion/Significance The current investigation evaluated the gastroprotective effects of AMDCP on ethanol-induced gastric mucosal lesions in rats. This study also suggests that AMDCP might be useful as a gastroprotective agent.
Randomization and Restarts in Proof Planning

Proof planning considers mathematical theorem proving as a planning problem. It has enabled the derivation of mathematical theorems that lay outside the scope of traditional logic-based theorem proving systems. One of its strengths comes from heuristic mathematical knowledge that restricts the search space and thereby facilitates the proving process for problems whose proofs belong in the restricted search space. But this may exclude solutions or restrict the kinds of proofs that can be found for a given problem. We take a different perspective and investigate problem classes for which little or no heuristic control knowledge is available and test the usage of randomization and restart techniques. Our approach to control in those mathematical domains is based on investigations on so-called heavy-tailed distributions (Gomes et al. 2000; 1998; 1998). Because of the non-standard nature of heavy-tailed cost distributions the controlled introduction of randomization into the search procedure and quick restarts of the randomized procedure can eliminate heavy-tailed behavior and can take advantage of short runs. To apply these techniques to the complicated domains of proof planning, the first task was to find problem classes for which proof planning exhibits an unpredictable run time behavior, i.e., with heavy-tailed cost distributions. Secondly, the experiments provided the basis for determining suitable cutoff values, i.e., the time interval after which a running proof attempt is interrupted and a new attempt is started. Finally, we designed a new control strategy which dramatically boosts the performance of our proof planner for a class of problems for which proof planning exhibits heavy-tailed cost behavior.
Vascular Factors Are Critical in Selective Neuronal Loss in an Animal Model of Impaired Oxidative Metabolism

Thiamine deficiency (TD) models the cellular and molecular mechanisms by which chronic oxidative deficits lead to death of select neurons in brain. Region- and cell-specific oxidative stress and vascular changes accompany the TD-induced neurodegeneration. The current studies analyzed the role of oxidative stress in initiating these events by testing the role of intercellular adhesion molecule-1 (ICAM-1) and endothelial nitric oxide synthase (eNOS) in the selective neuronal loss that begins in the submedial thalamic nucleus of mice. Oxidative stress to microvessels is known to induce eNOS and ICAM-1. TD increased ICAM-1 immunoreactivity in microvessels within the submedial nucleus and adjacent regions 1 day prior to the onset of neuronal loss. On subsequent days, the pattern of ICAM-1 induction overlapped that of neuronal loss, and of induction of the oxidative stress marker heme oxygenase-1 (HO-1). The intensity and extent of ICAM-1 and HO-1 induction progressively spread in parallel with the neuronal death in the thalamus. Targeted disruption of ICAM-1 or eNOS gene, but not the neuronal NOS gene, attenuated the TD-induced neurodegeneration and HO-1 induction. TD induced ICAM-1 in eNOS knockout mice, but did not induce eNOS in mice lacking ICAM-1. These results demonstrate that in TD, an ICAM-1-dependent pathway of eNOS induction leads to oxidative stress-mediated death of metabolically compromised neurons. Thus, TD provides a useful model to help elucidate the role of ICAM-1 and eNOS in the selective neuronal death in diseases in which oxidative stress is implicated.
Development of a lifestyle intervention using the MRC framework for diabetes prevention in people with impaired glucose regulation

Background We report development of a group-based lifestyle intervention, Let's Prevent, using the UK Medical Research Council (MRC) framework, and delivered by structured education to prevent type 2 diabetes mellitus (T2DM) in people with impaired glucose regulation (IGR) in a UK multi-ethnic population. Methods Diabetes Education and Self-Management for Ongoing and Newly Diagnosed (DESMOND) is the first national T2DM programme that meets National Institute for Health and Care Excellence criteria and formed the basis for Let's Prevent. An iterative cycle of initial development, piloting, collecting and collating qualitative and quantitative data, and reflection and modification, was used to inform and refine lifestyle intervention until it was fit for evaluation in a definitive randomized controlled trial (RCT). The programme encouraged IGR self-management using simple, non-technical language and visual aids. Results Qualitative and quantitative data suggested that intervention resulted in beneficial short-term behaviour change such as healthier eating patterns, improved health beliefs and greater participant motivation and empowerment. We also demonstrated that recruitment strategy and data collection methods were feasible for RCT implementation. Conclusions Let's Prevent was developed following successful application of MRC framework criteria and the subsequent RCT will determine whether it is feasible, reliable and transferable from research into a real-world NHS primary healthcare setting. Trial Registration ISRCTN80605705.
Local coherence in genetic interaction patterns reveals prevalent functional versatility

MOTIVATION Epistatic or genetic interactions, representing the effects of mutating one gene on the phenotypes caused by mutations in one or more distinct genes, can be very helpful for uncovering functional relationships between genes. Recently, the epistatic miniarray profiles (E-MAP) method has emerged as a powerful approach for identifying such interactions systematically. For E-MAP data analysis, hierarchical clustering is used to partition genes into groups on the basis of the similarity between their global interaction profiles, and the resulting descriptions assign each gene to only one group, thereby ignoring the multifunctional roles played by most genes. RESULTS Here, we present the original local coherence detection (LCD) algorithm for identifying groups of functionally related genes from E-MAP data in a manner that allows individual genes to be assigned to more than one functional group. This enables investigation of the pleiotropic nature of gene function. The performance of our algorithm is illustrated by applying it to two E-MAP datasets and an E-MAP-like in silico dataset for the yeast Saccharomyces cerevisiae. In addition to recapitulating the majority of the functional modules and many protein complexes reported previously, our algorithm uncovers many recently documented and novel multifunctional relationships between genes and gene groups. Our algorithm hence represents a valuable tool for uncovering new roles for genes with annotated functions and for mapping groups of genes and proteins into pathways.
Efficient Reconfigurable On-Chip Buses for FPGAs

This paper presents techniques for generating on-chip buses suitable for dynamically integrating hardware modules into an FPGA-based SoC by partial reconfiguration. The buses permit direct connections of master and slave modules to the bus in combination with a flexible fine-grained module placement and with minimized latency and area overheads. A test system will demonstrate a transfer rate of 800 MB/s while providing an extreme high placement flexibility.
Maternal Obesity, Overweight and Gestational Diabetes Affect the Offspring Neurodevelopment at 6 and 18 Months of Age – A Follow Up from the PREOBE Cohort

Background Brain development in fetal life and early infancy is critical to determine lifelong performance in various neuropsychological domains. Metabolic pathologies such as overweight, obesity, and gestational diabetes in pregnant women are prevalent and increasing risk factors that may adversely affect long-term brain development in their offspring. Objective The objective of this research was to investigate the influence of maternal metabolic pathologies on the neurodevelopment of the offspring at 6 and 18 months of life. Design This was a prospective case-control study of 331 mother- and child pairs from Granada, Spain. The mothers were included during pregnancy into four groups according to their pre-gestational body mass index and their gestational diabetes status; overweight (n:56), obese (n:64), gestational diabetic (n:79), and healthy normal weight controls (n:132). At 6 months and 18 months we assessed the children with the Bayley III scales of neurodevelopment. Results At 6 months (n=215), we found significant group differences in cognition composite language, and expressive language. Post hoc test revealed unexpectedly higher scores in the obese group compared to the normal weight group and a similar trend in overweight and diabetic group. The effects on language remained significant after adjusting for confounders with an adjusted odds ratio for a value above median in composite language score of 3.3 (95% CI: 1.1, 10.0; p=0.035) for children of obese mothers. At 18 month (n=197), the offspring born to obese mothers had lost five points in language composite scores and the previous differences in language and cognition was replaced by a suggestive trend of lower gross motor scores in the overweight, obese, and diabetic groups. Conclusions Infants of obese mothers had a temporary accelerated development of cognition and language, followed by a rapid deceleration until 18 months of age, particularly of language scores. This novel observation prompts further confirmative studies to explore possible placental and neurodevelopmental mechanisms involved.
A Vector Generalization of Costa's Entropy-Power Inequality With Applications

This paper considers an entropy-power inequality (EPI) of Costa and presents a natural vector generalization with a real positive semidefinite matrix parameter. The new inequality is proved using a perturbation approach via a fundamental relationship between the derivative of mutual information and the minimum mean-square error (MMSE) estimate in linear vector Gaussian channels. As an application, a new extremal entropy inequality is derived from the generalized Costa EPI and then used to establish the secrecy capacity regions of the degraded vector Gaussian broadcast channel with layered confidential messages.
Work in Progress : Scan Surveillance in Internet Networks

In recent years, many measurement studies have shown the ubiquity of scanning activities in the Internet and the growing sophistication of probing techniques that became more stealthy by stretching slowly over time or using spoofed source IP addresses. Scans are mainly generated by attackers trying to map the configuration of a target network and by computer worms trying to spread over the Internet. Although, the problem of scan detection has been given a lot of attention by network security researchers, current state-of-the-art methods still suffer from high percentage of false alarms or low ratio of scan detection. In this paper, we propose to detect changes in scanning patterns, by monitor variation of the distribution of scan features in a space spanned by IP source address, IP destination address, source port number, and destination port number. This gives insight on characteristics of scanning activities and exposes the presence of emerging scanning attacks and worms. For that, we propose to use an information theoretic-based approach to detect changes in distributions.
The sequential organization of movement is critical to the development of reaching: A neural dynamics account

We present a neuro-dynamic model of looking, reaching, and grasping movements in infants in three pre-reaching phases. We attribute the evolution from pre-reaches to their suppression and subsequent re-emergence reported in a longitudinal study of von Hofsten [1] to the development of the sequential organization of movements, through which a set of elementary movements (visual fixation, reaching, opening the hand) are coordinated in time. The spatial precision hypothesis, which has emerged from work on spatial, visual, and action working memory, characterizes developmental changes as a change from strongly input-driven to more strongly interaction-dominated neural dynamics. Applying this hypothesis to reaching, we propose that the intention to reach is increasingly able to suppress competing movement behaviors, enabling object-oriented reaches. We evaluate three versions of the model that capture the three phases reported by von Hofsten and illustrate the properties of the movement model in simulations and in demonstration on a NAO robot.