163 research outputs found
Preassociative aggregation functions
The classical property of associativity is very often considered in
aggregation function theory and fuzzy logic. In this paper we provide
axiomatizations of various classes of preassociative functions, where
preassociativity is a generalization of associativity recently introduced by
the authors. These axiomatizations are based on existing characterizations of
some noteworthy classes of associative operations, such as the class of
Acz\'elian semigroups and the class of t-norms.Comment: arXiv admin note: text overlap with arXiv:1309.730
ELMOD3-SH2D6 gene fusion as a possible co-star actor in autism spectrum disorder scenario
Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders characterized by high heritability. It is known that genetic factors contribute to ASD pathogenesis. In particular, copy number variants (CNVs) are involved in ASD susceptibility and can affect gene expression regulation. 2p11.2 microdeletions encompassing ELMOD3, CAPG and SH2D6 genes have been described in four unrelated ASD families. The present study revealed that this microdeletion is responsible for the production of a chimeric transcript generated from the fusion between ELMOD3 and SH2D6. The identified transcript showed significantly higher expression levels in subjects carrying the deletion compared to control subjects, suggesting that it is not subjected to nonsense-mediated decay and might encode for a chimeric protein. In conclusion, this study suggests the possible involvement of this gene fusion, together with the other previously identified variants, in ASD
An Empirical Study of Bots in Software Development -- Characteristics and Challenges from a Practitioner's Perspective
Software engineering bots - automated tools that handle tedious tasks - are
increasingly used by industrial and open source projects to improve developer
productivity. Current research in this area is held back by a lack of consensus
of what software engineering bots (DevBots) actually are, what characteristics
distinguish them from other tools, and what benefits and challenges are
associated with DevBot usage. In this paper we report on a mixed-method
empirical study of DevBot usage in industrial practice. We report on findings
from interviewing 21 and surveying a total of 111 developers. We identify three
different personas among DevBot users (focusing on autonomy, chat interfaces,
and "smartness"), each with different definitions of what a DevBot is, why
developers use them, and what they struggle with. We conclude that future
DevBot research should situate their work within our framework, to clearly
identify what type of bot the work targets, and what advantages practitioners
can expect. Further, we find that there currently is a lack of general purpose
"smart" bots that go beyond simple automation tools or chat interfaces. This is
problematic, as we have seen that such bots, if available, can have a
transformative effect on the projects that use them.Comment: To be published at the ACM Joint European Software Engineering
Conference and Symposium on the Foundations of Software Engineering
(ESEC/FSE
A genome-wide scan for common alleles affecting risk for autism
Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10−8. When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10−8 threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C
i-Rheo: Measuring the materials' linear viscoelastic properties “in a step”!
A new analytical technique for determining a materials' linear viscoelastic properties from a simple step-strain measurement is reported. The technique avoids the need for idealisation of real measurements. The technique involves evaluating the Fourier transforms of raw experimental data describing both the time-dependent stress and strain functions. A comparison with conventional linear oscillatory measurements for a diverse range of complex materials is made and the technique is shown to be superior to existing linear oscillatory measurements in all cases
Contribution of ultrarare variants in mTOR pathway genes to sporadic focal epilepsies
Objective: We investigated the contribution to sporadic focal epilepsies (FE) of ultrarare variants in genes coding for the components of complexes regulating mechanistic Target Of Rapamycin (mTOR)complex 1 (mTORC1). Methods: We collected genetic data of 121 Italian isolated FE cases and 512 controls by Whole Exome Sequencing (WES) and single-molecule Molecular Inversion Probes (smMIPs) targeting 10 genes of the GATOR1, GATOR2, and TSC complexes. We collapsed \u201cqualifying\u201d variants (ultrarare and predicted to be deleterious or loss of function) across the examined genes and sought to identify their enrichment in cases compared to controls. Results: We found eight qualifying variants in cases and nine in controls, demonstrating enrichment in FE patients (P = 0.006; exact unconditional test, one-tailed). Pathogenic variants were identified in DEPDC5 and TSC2, both major genes for Mendelian FE syndromes. Interpretation: Our findings support the contribution of ultrarare variants in genes in the mTOR pathway complexes GATOR and TSC to the risk of sporadic FE and a shared genetic basis between rare and common epilepsies. The identification of a monogenic etiology in isolated cases, most typically encountered in clinical practice, may offer to a broader community of patients the perspective of precision therapies directed by the underlying genetic cause
Homozygous microdeletion of exon 5 in ZNF277 in a girl with specific language impairment
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Individual common variants exert weak effects on the risk for autism spectrum disorders.
While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest
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