Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic association study for RSV bronchiolitis in infancy at the 5q31 cytokine cluster

Background: The pathophysiological basis of severe respiratory syncytial virus (RSV) bronchiolitis in infancy is poorly understood and has hindered vaccine development. Studies implicate the cell-mediated immune response in the pathogenesis of the disease. A recent twin study estimated a heritable contribution of 22% to RSV bronchiolitis. Genetic epidemiology provides a new approach to identifying important immune determinants of disease severity. Methods: A comprehensive high-density gene-region association study for severe RSV bronchiolitis in infancy at 5q31 across 11 genes including the Th2-cytokine cluster was performed. A haplotype tagging approach was used to analyse genetic variation at 113 single nucleotide polymorphisms (SNPs) in 780 independent cases and 1045 controls. The study had sufficient power to detect small effects, perform extensive haplotype analysis and analyse both a principal phenotype and a refined age-limited phenotype enriched for first-exposure RSV infection. Results: SNP associations were found at IL4 and a highly significant risk haplotype was identified across IL13 CNS-1 and IL4 (odds ratio 1.69, p<0.0001), present in both case-control and family-based analyses. All associations were strongest for a phenotype limited to <6 months of age, implicating this locus in primary RSV disease. The same risk haplotype has previously been shown to be associated with increased IL13 expression. Conclusions: A haplotype at IL13–1L4, which is associated with increased IL13 production, confers an increased risk of severe primary RSV bronchiolitis in early infancy. This study, together with previous studies implicating the same locus in atopic sensitisation, suggests that primary RSV bronchiolitis and atopy share a genetic contribution at the IL13–IL4 locus.
A conditional probability interpretation of Kanerva's sparse distributed memory

It is shown that P. Kanerva's sparse distributed memory (SDM) (Sparse Distributed Memories, Bradford Books/MIT Press, 1988) is a Monte Carlo approximation to a multidimensional conditional probability integral. The SDM will produce acceptable responses from a training set when this approximation is valid, that is, when the training set contains sufficient data to provide good estimates of the underlying joint probabilities and there are enough Monte Carlo samples to obtain an accurate estimate of the integral. This analysis makes clear that in order to construct, through examples, an analog device that will transform a set of inputs into a set of outputs using the SDM, care must be taken to match the training set data to the resources. In particular, ambiguities in amplitude space can arise in a manner similar to the way aliasing can corrupt samples of analog signals in the space and time domains if the sampling density is too low. This observation could very well apply to other learning systems. <<ETX>>
Character network analysis of Émile Zola’s Les Rougon-Macquart

In this work, we use network analysis methods to sketch a typology of fiction novels based on characters and their proximity in the narration. We construct character networks modelling the twenty novels composing Les Rougon-Macquart, written by Emile Zola. To categorise them, we rely on methods that track down major and minor characters relative to the character-systems. For that matter, we use centrality measures such as degree and eigenvector centrality. Eventually, with this analysis of a small corpus, we open the stage for a large-scale analysis of novels through their character networks.
Collective intelligence and bush fire spotting

Bush fires cause major damage each year in many areas of the world and the earlier that they can be detected the easier it is to minimize this damage. This paper describes a collective intelligence algorithm that performs localized rather than centralized control of a number of unmanned aerial vehicles (UAV) that can survey complex areas for fires, devoting attention in proportion to the user specified importance of each area. Simulation shows that not only is the algorithm able to perform this action successfully, it is also able to automatically adapt to a simulated malfunction in one of the UAVs.
Cell sites planning with minimized power consumption under cell load balancing constraint in LTE networks

The problem of cell sites planning in a given service area in LTE cellular networks is studied in this paper, the optimization objective of which is to minimize the power consumption of both users and cell sites under the constraint of cell load balancing. Non-uniform traffic distributions across the entire service area are considered. An efficient algorithm is proposed, which first works out a proper range of the optimal sites number, and then determines the cell sites locations for each number in the range by iteratively solving a convex problem to minimize the power consumption of both users and cell sites. The optimal cell sites number is the one with minimal power consumption and the locations are determined accordingly. An example scenario is presented to demonstrate the convergence and effectiveness of the proposed algorithm.
Modelling approaches for relating effects of change in river flow to populations of Atlantic salmon and brown trout

Modelling approaches for relating discharge to the biology of Atlantic salmon, Salmo salar L. , and brown trout, Salmo trutta L. , growing in rivers are reviewed. Process-based and empirical models are set within a common framework of input of water flow and output of characteristics of fish, such as growth and survival, which relate directly to population dynamics. A continuum is envisaged incorporating various contributions of process and empirical structure as practical and appropriate to specific goals. This framework is compared with, and shown to differ from, approaches whose output is in the form of quantity and form of habitat (or usable area) based on its frequency of use by fish, which then is assumed to have some relationship with fish performance. A simple conceptual modelling approach is also developed to relate water flow to fish population characteristics to assess the likelihood of simple relationships between flow and usable area thresholds. Basic predictions of the model are tested against empirical data from a long-term individual-based study of juvenile S. salar and resident brook trout, Salvelinus fontinalis (Mitchell), in West Brook, Massachusetts. For this system, growth rates of both species increased linearly with flow during spring, summer and autumn months and bore no relation to Q95 or wetted-width discontinuities. Winter is identified as a season during which water might be abstracted most safely, but cautiously given sparse knowledge of wild salmonid fish at this time of year. These results, together with the fundamental conceptual problems inherent in usable area-based approaches, suggest that models that relate directly to fish performance outcomes may be more robust as a basis for flow prescriptions. However, this utility will depend strongly on our ability to generalise from a limited set of empirical studies and to use the results of these studies of management actions to inform and improve future models.
Carotid artery stiffness and hemodynamic pulsatility during cognitive engagement in healthy adults: a pilot investigation.

BACKGROUND The matching of vascular supply to neuronal metabolic demand during cognitive engagement is known as neurovascular coupling (NVC). Arterial stiffness is a prominent determinant of pulsatility in the systemic circulation and may thus indirectly impact NVC. In this pilot investigation, we explored changes in carotid artery stiffness and cerebrovascular hemodynamic pulsatiltiy during cognitive engagement in healthy adults. METHODS Twenty-seven adults (age 39 ± 3 years, BMI 24 ± 1 kg/m(2)) underwent Doppler ultrasonography of the common carotid artery (CCA) combined with applanation tonometry to derive (i) CCA elastic modulus (Ep) and β-stiffness index; (ii) CCA flow pulsatility index (PI); (iii) CCA pulse pressure, (iv) CCA augmentation index (AIx). Cerebral PI was assessed using transcranial Doppler at the middle cerebral artery (MCA). All measures were made at rest and during an incongruent Stroop task. RESULTS CCA PI was reduced (1.75 ± 0.06 to 1.57 ± 0.06, P < 0.05) while MCA PI was unchanged (0.75 ± 0.02 to 0.75 ± 0.02, P > 0.05) during Stroop. Brachial pulse pressure increased during Stroop (43 ± 1 to 46 ± 1 mm Hg, P < 0.05) while CCA pulse pressure was unchanged (36 ± 1 to 35 ± 1 mm Hg, P > 0.05). Similarly, CCA Ep (54.5 ± 5.5 to 53.8 ± 4.9 kPa, P > 0.05) and β-stiffness index (4.4 ± 0.4 to 4.2 ± 0.3 aU, P > 0.05) were unchanged. CCA AIx increased (1 ± 4 to 13 ± 4%, P < 0.05). CONCLUSION Carotid pressure pulsatility is unaltered while carotid flow pulsatility is reduced during cognitive engagement. Carotid artery stiffness does not change suggesting that factors other than the dynamic elastic properties of the CCA buffer cerebrovascular hemodynamic pulsatility during cognitive engagement.
Evidence for a Fragile X Mental Retardation Protein-Mediated Translational Switch in Metabotropic Glutamate Receptor-Triggered Arc Translation and Long-Term Depression

Group 1 metabotropic glutamate receptor (mGluR)-stimulated protein synthesis and long-term synaptic depression (mGluR-LTD) are altered in the mouse model of fragile X syndrome, Fmr1 knock-out (KO) mice. Fmr1 encodes fragile X mental retardation protein (FMRP), a dendritic RNA binding protein that functions, in part, as a translational suppressor. It is unknown whether and how FMRP acutely regulates LTD and/or the rapid synthesis of new proteins required for LTD, such as the activity-regulated cytoskeletal-associated protein (Arc). The protein phosphatase PP2A dephosphorylates FMRP, which contributes to translational activation of some target mRNAs. Here, we report that PP2A and dephosphorylation of FMRP at S500 are required for an mGluR-induced, rapid (5 min) increase in dendritic Arc protein and LTD in rat and mouse hippocampal neurons. In Fmr1 KO neurons, basal, dendritic Arc protein levels and mGluR-LTD are enhanced, but mGluR-triggered Arc synthesis is absent. Lentiviral-mediated expression of wild-type FMRP in Fmr1 KO neurons suppresses basal dendritic Arc levels and mGluR-LTD, and restores rapid mGluR-triggered Arc synthesis. A phosphomimic of FMRP (S500D) suppresses steady-state dendritic Arc levels but does not rescue mGluR-induced Arc synthesis. A dephosphomimic of FMRP (S500A) neither suppresses dendritic Arc nor supports mGluR-induced Arc synthesis. Accordingly, S500D-FMRP expression in Fmr1 KO neurons suppresses mGluR-LTD, whereas S500A-FMRP has no effect. These data support a model in which phosphorylated FMRP functions to suppress steady-state translation of Arc and LTD. Upon mGluR activation of PP2A, FMRP is rapidly dephosphorylated, which contributes to rapid new synthesis of Arc and mGluR-LTD.
The Influence of Preference Learning on Complex Network Community under the Nash Equilibrium

We study the influence of preference learning on the community of complex network, on the basis of evolutionary game. First, we construct a model of complex network based on the evolutionary game, and we study the degree distribution and the average degree of the model, and according to whether the individual consider the Nash equilibrium when it choose its action, we study the community of the model. We can safely draw the conclusion that Nash equilibrium is necessary for individuals to choose actions when gaming with others.
Shared Cognitive Impairments and Aetiology in ADHD Symptoms and Reading Difficulties

Background Twin studies indicate that the frequent co-occurrence of attention deficit hyperactivity disorder (ADHD) symptoms and reading difficulties (RD) is largely due to shared genetic influences. Both disorders are associated with multiple cognitive impairments, but it remains unclear which cognitive impairments share the aetiological pathway, underlying the co-occurrence of the symptoms. We address this question using a sample of twins aged 7–10 and a range of cognitive measures previously associated with ADHD symptoms or RD. Methods We performed multivariate structural equation modelling analyses on parent and teacher ratings on the ADHD symptom domains of inattention and hyperactivity, parent ratings on RD, and cognitive data on response inhibition (commission errors, CE), reaction time variability (RTV), verbal short-term memory (STM), working memory (WM) and choice impulsivity, from a population sample of 1312 twins aged 7–10 years. Results Three cognitive processes showed significant phenotypic and genetic associations with both inattention symptoms and RD: RTV, verbal WM and STM. While STM captured only 11% of the shared genetic risk between inattention and RD, the estimates increased somewhat for WM (21%) and RTV (28%); yet most of the genetic sharing between inattention and RD remained unaccounted for in each case. Conclusion While response inhibition and choice impulsivity did not emerge as important cognitive processes underlying the co-occurrence between ADHD symptoms and RD, RTV and verbal memory processes separately showed significant phenotypic and genetic associations with both inattention symptoms and RD. Future studies employing longitudinal designs will be required to investigate the developmental pathways and direction of causality further.
The Mini Mental State Examination: Review of cutoff points adjusted for schooling in a large Southern Brazilian sample

The increase in life expectancy can influence the prevalence of dementias in the population. Instruments that evaluate cognitive functions such as the Mini Mental State Examination (MMSE) are necessary for the investigation of dementia. The supposition that patient score on the MMSE can be influenced by academic level points to the need for establishing cut-off values that take into account educational level. The aim of this study was to review MMSE cut-off values adjusted for schooling in a large southern Brazilian sample. Method Demographic data and MMSE scores of 968 subjects, of which 162 were dementia patients and 806 healthy participants, were analyzed. The sample was grouped according to education. The cut-off values were established by ROC Curve analysis. Results The total sample mean age was 70.6±7.3 years, and the mean years of education was 7.2±5.3. The cut-off score of 23 points (sensitivity=86%, specificity=83%) was observed as the optimal level to detect dementia on the MMSE instrument for the overall sample. Regarding level of schooling, the cut-off values were: 21 for the illiterate group (sensitivity=93%, specificity=82%), 22 for the low education group (sensitivity=87%, specificity=82%), 23 for the middle education group (sensitivity=86%, specificity=87%) and 24 for the high education group (sensitivity=81%, specificity=87%). Conclusions The cut-off values revealed by this analysis, and adjusted for level of schooling, can improve the clinical evaluation of cognitive deficits.
Generalized Multi-Constrained Path (G_MCP) QoS Routing Algorithm for Mobile Ad hoc Networks

In mobile ad hoc network, efficient routing protocol is required to perform route discovery and maintenance. These protocols can be classified into two main types which are proactive and reactive routing protocols. Most of them usually use the suboptimal path to reach destination without considering QoS parameters. This results in network congestion during high traffic load situation. Hence, many algorithms have been proposed to offer QoS routing to these protocols. However, most of them find the feasible path by using only one or two QoS metrics. This is not enough to support many applications with QoS guaranteed, especially multimedia applications since they have more stringent various QoS requirements. To provide QoS routing in ad hoc network based on such environment, we propose the effective algorithm called Generalized MCP (G_MCP) to find the feasible path based on proposed weighted Connectivity Index (combination of link connectivity and capacity) and non-linear cost (combination of multiple additive QoS metrics using non-linear function). We adopt the fall-back approach. That is, G_MCP will find the path from source to destination by considering weighted Connectivity Index first. If there is a tie, the path with least non-linear cost will be chosen. Based on this approach, G_MCP has the comparable time complexity with the Shortest-Widest Path algorithm. We construct the simulation in a number of scenarios based on proactive protocol called OLSR. According to the simulation results, it is obvious that G_MCP performances are superior than OLSR and Shortest-Widest Path algorithms in terms of throughput, packet delivery ratio, delay and success ratio. Therefore, it can be concluded that G_MCP is able to support various applications and be operated well in highly dynamic mobility environment
Speech and Language Disorders in Kenyan Children: Adapting Tools for Regions with Few Assessment Resources

This study sought to adapt a battery of Western speech and language assessment tools to a rural Kenyan setting. The tool was developed for children whose first language was KiGiryama, a Bantu language. A total of 539 Kenyan children (males=271, females=268, ethnicity=100% Kigiryama) were recruited. Data were initially collected from 52 children (pilot assessments), and then from a larger group of 487 children (152 cerebral malaria, 156 severe malaria and seizures, 179 unexposed). The language assessments were based upon the Content, Form and Use (C/F/U) model. The assessment was based upon the adapted versions of the Peabody Picture Vocabulary Test, Test for the Reception of Grammar, Renfrew Action Picture Test, Pragmatics Profile of Everyday Communication Skills in Children, Test of Word Finding and language specific tests of lexical semantics, higher level language. Preliminary measures of construct validity suggested that the theoretical assumptions behind the construction of the assessments were appropriate and re-test and inter-rater reliability scores were acceptable. These findings illustrate the potential to adapt Western speech and language assessments in other languages and settings, particularly those in which there is a paucity of standardised tools.
Assessing writing and collaboration in learning: Methodological issues

We describe the main tasks students usually complete when working in an e- learning platform, across five mean features that have to be taken into account in research efforts (writing-based activities, individual/collective level, knowledge/ pedagogy orientation, feedback, multiple stakeholders account). Ways to analyse and assist these tasks by (semi)-automatic assessments using NLP techniques is discussed. Two services aiming to assist writing-based tasks are presented along with their first validation.
Matching shapes with a reference point

For two given point sets, we present a very simple (almost trivial) algorithm to translate one set so that the Hausdorff distance between the two sets is not larger than a constant factor times the minimum Hausdorff distance which can be achieved in this way. The algorithm just matches the so-called Steiner points of the two sets. The focus of our paper is the general study of reference points (like the Steiner point) and their properties with respect to shape matching. For more general transformations than translations, our method eliminates several degrees of freedom from the problem and thus yields good matchings with improved time bounds.
One DBMS for all: the brawny few and the wimpy crowd

Shipments of smartphones and tablets with wimpy CPUs are outpacing brawny PC and server shipments by an ever-increasing margin. While high performance database systems have traditionally been optimized for brawny systems, wimpy systems have received only little attention; leading to poor performance and energy inefficiency on such systems. This demonstration presents HyPer, a high-performance hybrid OLTP&OLAP main memory database system that we optimized for both, brawny and wimpy systems. The efficient compilation of transactions and queries into efficient machine code allows for high performance, independent of the target platform. HyPer has a memory footprint of just a few megabytes, even though it supports the SQL-92 standard, a PL/SQL-like scripting language, and ACID-compliant transactions. It is the goal of this demonstration to showcase the same HyPer codebase running on (a) a wimpy ARM-based smartphone system and (b) a brawny x86-64-based server system. In particular, we run the TPC-C, TPC-H, and a combined CH-benCHmark and report performance and energy numbers. The demonstration further allows the interactive execution of arbitrary SQL queries and the visualization of optimized query plans.
Conceptual, Semantic and Information Models for Medicine

This paper presents the intensional requirements of the medical record. It suggests that at least four models are required in order to cover the complexity of the medical domain. It goes onto propose that description logics are more appropriate to the modelling of medicine information than conventional prescriptive semantic data models and propose a description logic capable of constrained generation of complex compositional concepts from elementary ones and their relationships. This formalism, named GRAIL, is described in detail as a representation for medical concepts, and is shown to be capable of integrating all the intensional and extensional requirements of a medical record. Experiences with GRAIL in use in a clinical workstation, PEN&PAD, and a large medical terminology server, part of the EU-funded project GALEN, are extensively described. The support requirements of distributed large-scale collaborative modelling for re-use, as required for GALEN, are discussed. Examples, both medical and non-medical, are given throughout.
Detection of heartbeats based on the Bayesian framework

The detection of heartbeat is an important and challenging issue for health care. This work proposes to estimate the QRS complex parameters based on the maximum-likelihood (ML) principle. To this goal, a new signal model and its Bayesian framework are studied. Detectors or estimators based on the Bayesian framework are considered to be optimal in the statistical signal processing point of view. To reduce the complexity of original method, its iterative counterpart is investigated by using the decomposition method. Detailed information of QRS complexes, including the starting point, duration, and period, can be derived by the proposed method for further medical diagnosis. Simulations using the benchmark MIT-BIH Arrhythmia database verify the advantages of the proposed approaches compared to traditional ones.