A probabilistic analysis of argument cogency

This paper offers a probabilistic treatment of the conditions for argument cogency as endorsed in informal logic: acceptability, relevance, and sufficiency. Treating a natural language argument as a reason-claim-complex, our analysis identifies content features of defeasible argument on which the RSA conditions depend, namely: change in the commitment to the reason, the reason’s sensitivity and selectivity to the claim, one’s prior commitment to the claim, and the contextually determined thresholds of acceptability for reasons and for claims. Results contrast with, and may indeed serve to correct, the informal understanding and applications of the RSA criteria concerning their conceptual dependence, their function as update-thresholds, and their status as obligatory rather than permissive norms, but also show how these formal and informal normative approachs can in fact align

Infant contributions to joint attention predict vocabulary development

Joint attention has long been accepted as constituting a privileged circumstance in which word learning prospers. Consequently research has investigated the role that maternal responsiveness to infant attention plays in predicting language outcomes. However there has been a recent expansion in research implicating similar predictive effects from individual differences in infant behaviours. Emerging from the foundations of such work comes an interesting question: do the relative contributions of the mother and infant to joint attention episodes impact upon language learning? In an attempt to address this, two joint attention behaviours were assessed as predictors of vocabulary attainment (as measured by OCDI Production Scores). These predictors were: mothers encouraging attention to an object given their infant was already attending to an object (maternal follow-in); and infants looking to an object given their mothers encouragement of attention to an object (infant follow-in). In a sample of 14-month old children (N=36) we compared the predictive power of these maternal and infant follow-in variables on concurrent and later language performance. Results using Growth Curve Analysis provided evidence that while both maternal follow-in and infant follow-in variables contributed to production scores, infant follow-in was a stronger predictor. Consequently it does appear to matter whose final contribution establishes joint attention episodes. Infants who more often follow-in into their mothers’ encouragement of attention have larger, and faster growing vocabularies between 14 and 18-months of age

MSSM Higgs bosons associated with high-pT jets at hadron colliders

The cross section for the production of the lightest neutral Higgs boson in association with a high-pT hadronic jet, calculated in the framework of the minimal supersymmetric standard model (MSSM), is presented. The expectations for the hadronic cross section at the Large Hadron Collider are discussed using reasonable kinematical cuts. In particular the contributions from superpartner loops to the cross section and their dependence on the parameters of the MSSM are investigated and found to be significant. Comparisons show that the production rate for h0 + jet in the MSSM can differ widely from the corresponding standard-model prediction.Comment: 20 page

Hadronic production of bottom-squark pairs with electroweak contributions

We present the complete computation of the tree-level and the next-to-leading order electroweak contributions to bottom-squark pair production at the LHC. The computation is performed within the minimal supersymmetric extension of the Standard Model. We discuss the numerical impact of these contributions in several supersymmetric scenarios.Comment: 33 pages, v2: preprint numbers correcte

Actinorhodopsin genes discovered diverse in freshwater habitats and among cultivated Actinobacteria

Microbial rhodopsins are membrane proteins that utilize a retinal chromophore to harvest sunlight for energetic and photosensory functions. Recently, a group of novel rhodopsin sequences named ‘actinorhodopsins’ (ActRs) was hypothesized to exist among uncultured planktonic Actinobacteria. ActRs were discovered by mining metagenomic data obtained during the Venter Institute’s Global Ocean Sampling expedition, from a hypersaline lagoon, two estuaries and a freshwater lake. On the basis of these findings, and many studies that show Actinobacteria are common inhabitants of lakes, we predicted that ActR genes would likely be present in other freshwater habitats and among the genomes of cultivated Actinobacteria. Using degenerate polymerase chain reaction primers, we discovered an ActR gene present in an actinobacterial isolate of the family Microbacteriaceae. Isolate MWH-Uga1 was cultivated prior to this study from a freshwater pond in Uganda and belongs to a group of Actinobacteria previously identified in freshwater ecosystems. ActR genes were also discovered present in numerous mixed cultures containing freshwater Actinobacteria and among environmental DNA samples obtained from three freshwater sources; a small woodland pond and the Laurentian Great Lakes Superior and Erie. An analysis of small subunit ribosomal RNA genes from metagenomic DNA samples harboring ActR genes suggests that organisms belonging to the acI lineage, an uncultured group of Actinobacteria commonly present in fresh waters, may utilize rhodopsins. The co-occurrence of an acI organism with a specific ActR variant in a mixed culture supports our hypothesis

Widening Access to Bayesian Problem Solving

Bayesian reasoning and decision making is widely considered normative because it minimizes prediction error in a coherent way. However, it is often difficult to apply Bayesian principles to complex real world problems, which typically have many unknowns and interconnected variables. Bayesian network modeling techniques make it possible to model such problems and obtain precise predictions about the causal impact that changing the value of one variable may have on the values of other variables connected to it. But Bayesian modeling is itself complex, and has until now remained largely inaccessible to lay people. In a large scale lab experiment, we provide proof of principle that a Bayesian network modeling tool, adapted to provide basic training and guidance on the modeling process to beginners without requiring knowledge of the mathematical machinery working behind the scenes, significantly helps lay people find normative Bayesian solutions to complex problems, compared to generic training on probabilistic reasoning. We discuss the implications of this finding for the use of Bayesian network software tools in applied contexts such as security, medical, forensic, economic or environmental decision making

Striatal dopamine D2 receptor binding of risperidone in schizophrenic patients as assessed by 123I-iodobenzamide SPECT: a comparative study with olanzapine

The aim of this investigation was to compare the degree of striatal dopamine-(D2) receptor blockade by two atypical antipsychotic drugs, risperidone and olanzapine. The percentage of D2 receptor occupancy during treatment was calculated by comparing the results of 123I-iodobenzamide SPECT with those from healthy control subjects. Twenty inpatients suffering from schizophrenia or schizoaffective psychosis according to DSM IV/ICD-10 criteria were treated with clinically recommended doses of risperidone and compared with 13 inpatients treated with up to 20 mg olanzapine. Neuroleptic dose and D2 receptor blockade correlated strongly for both risperidone (Pearson r = –0.86, p = 0.0001) and olanzapine (Pearson r = –0.77, p = 0.002). There was no significant difference between the D2 receptor occupancy of the two substances when given in the clinically recommended dose range (unpaired t-test, t= –0.112, p=0.911)