Search results for "Response"

showing 10 items of 4136 documents

Asymmetric Disulfanylbenzamides as Irreversible and Selective Inhibitors of Staphylococcus aureus Sortase A

2020

Abstract Staphylococcus aureus is one of the most frequent causes of nosocomial and community‐acquired infections, with drug‐resistant strains being responsible for tens of thousands of deaths per year. S. aureus sortase A inhibitors are designed to interfere with virulence determinants. We have identified disulfanylbenzamides as a new class of potent inhibitors against sortase A that act by covalent modification of the active‐site cysteine. A broad series of derivatives were synthesized to derive structure‐activity relationships (SAR). In vitro and in silico methods allowed the experimentally observed binding affinities and selectivities to be rationalized. The most active compounds were f…

Staphylococcus aureusmedicine.drug_classdrug designAntibioticsVirulenceMicrobial Sensitivity Testsmedicine.disease_cause01 natural sciencesBiochemistrybiofilmMicrobiology570 Life sciencesStructure-Activity RelationshipBacterial ProteinsAntibioticssortase ADrug DiscoverymedicineGeneral Pharmacology Toxicology and PharmaceuticsEnzyme InhibitorsCytotoxicityPharmacologyFull PaperDose-Response Relationship DrugMolecular Structure010405 organic chemistryChemistryOrganic ChemistryBiofilmFull PapersAminoacyltransferasesIn vitro0104 chemical sciencesAnti-Bacterial Agents010404 medicinal & biomolecular chemistryCysteine EndopeptidasesStaphylococcus aureusSortase Addc:540BenzamidesMolecular MedicineCysteine570 BiowissenschaftenChemmedchem
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Non-Gaussian probability density function of SDOF linear structures under wind actions

1998

Abstract Wind velocity is usually analytically described adding a static mean term to a zero mean fluctuation stationary process. The corresponding aerodynamic alongwind force acting on a single degree of freedom (SDOF) structure can be considered as a sum of three terms proportional to the mean wind velocity, to the product between mean and fluctuating part of the wind velocity and to the square power of the fluctuating wind velocity, respectively. The latter term, often neglected in the literature, is responsible for the non-Gaussian behaviour of the response. In this paper a method for the evaluation of the stationary probability density function of SDOF structures subjected to non-Gauss…

Stationary processStationary distributionSeries (mathematics)Renewable Energy Sustainability and the EnvironmentMechanical EngineeringGaussianMathematical analysisProbability density functionWind speedAerodynamic forcesymbols.namesakesymbolsSeries expansionCivil and Structural EngineeringMathematicsAlongwind response; Probability density function; Non-Gaussian stochastic analysis
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An association model for bivariate data with application to the anlysis of university students' success.

2015

The academic success of students is a priority for all universities. We analyze the students' success at university by considering their performance in terms of both ‘qualitative performance’, measured by their mean grade, and ‘quantitative performance’, measured by university credits accumulated. These data come from an Italian University and concern a cohort of students enrolled at the Faculty of Economics. To jointly model both the marginal relationships and the association structure with covariates, we fit a bivariate ordered logistic model by penalized maximum likelihood estimation. The penalty term we use allows us to smooth the association structure and enlarge the range of possible …

Statistics and Probability05 social sciencesBivariate analysisLogistic regression01 natural sciencesTerm (time)010104 statistics & probabilityGoodness of fitBivariate data0502 economics and businessStatisticsCovariateEconometricsRange (statistics)Settore SECS-S/05 - Statistica Sociale050207 economics0101 mathematicsStatistics Probability and UncertaintyAssociation (psychology)Mathematicsmodels for association students' performance bivariate ordinal response Dale's model maximum penalized likelihood estimation
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The Psychological Science Accelerator’s COVID-19 rapid-response dataset

2023

Funder: Amazon Web Services (AWS) Imagine Grant

Statistics and Probability223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore copingBF Psychology230 Affective NeuroscienceHealth Behaviorand demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73Message framingDiseasesLibrary and Information Sciences:Ciências Sociais::Psicologia [Domínio/Área Científica]geographical and cultural context characterizationHV Social pathology. Social and public welfare. CriminologypandemiatEducationa general questionnaire examining health prevention behaviors and COVID-19 experienceddc:150SDG 3 - Good Health and Well-beingRA0421 Public health. Hygiene. Preventive MedicineSurveys and QuestionnairesAdaptation PsychologicalyleiskartoituksetHumansPendienteHealth behaviorsPandemicsframingBehaviour Change and Well-beingEmotion regulationSelf-determination messagingand self-determination across a diverseCOVID-19kansainvälinen vertailuResearch dataComputer Science Applicationswhich can be merged with other time-sampled or geographic data.cognitive reappraisalsglobal sample obtained at the onset of the COVID-19 pandemicterveyskäyttäytyminenIn response to the COVID-19 pandemic/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_beingand autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental studyStatistics Probability and UncertaintyPeople’s healthtutkimusaineistosurvey-tutkimusDatasetInformation Systemsthe Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing
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Estimating person parameters via item response model and simple sum score in small samples with few polytomous items: A simulation study

2018

Background The Item Response Theory (IRT) is becoming increasingly popular for item analysis. Theoretical considerations and simulation studies suggest that parameter estimates will become precise only by utilizing many items in large samples. Method A simulation study focusing on a single scale was performed on data with (a) n = 40, 60, 80, 120, 200, 300, 500, and 900 cases utilizing (b) 4, 8, 16, or 32 items. The items were (c) symmetrically distributed vs. skew (skewness 0, 1, and 2). Item loadings were (d) homogeneous vs. heterogeneous. Item loadings were (e) low vs. high. Half of the items had (f) a correlated error or not. The number of answering categories (g) was four vs. five. A to…

Statistics and ProbabilityAnalysis of VarianceScale (ratio)EpidemiologyItem analysisSkewPolytomous Rasch modelMissing data01 natural sciences010104 statistics & probability03 medical and health sciences0302 clinical medicineSimple (abstract algebra)SkewnessSample SizeStatisticsItem response theoryHumansRegression AnalysisComputer Simulation030212 general & internal medicine0101 mathematicsCorrelation of DataMathematicsStatistics in Medicine
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Fast and universal estimation of latent variable models using extended variational approximations

2022

AbstractGeneralized linear latent variable models (GLLVMs) are a class of methods for analyzing multi-response data which has gained considerable popularity in recent years, e.g., in the analysis of multivariate abundance data in ecology. One of the main features of GLLVMs is their capacity to handle a variety of responses types, such as (overdispersed) counts, binomial and (semi-)continuous responses, and proportions data. On the other hand, the inclusion of unobserved latent variables poses a major computational challenge, as the resulting marginal likelihood function involves an intractable integral for non-normally distributed responses. This has spurred research into a number of approx…

Statistics and ProbabilityComputational Theory and Mathematicsmultivariate abundance datamuuttujatlaplace approximationmulti-response dataordinationStatistics Probability and Uncertaintyvariational approximationsgeneralized linear latent variable modelsestimointiTheoretical Computer ScienceStatistics and Computing
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Ranking Scientific Journals Via Latent Class Models for Polytomous Item Response Data

2015

Summary We propose a model-based strategy for ranking scientific journals starting from a set of observed bibliometric indicators that represent imperfect measures of the unobserved ‘value’ of a journal. After discretizing the available indicators, we estimate an extended latent class model for polytomous item response data and use the estimated model to cluster journals. We illustrate our approach by using the data from the Italian research evaluation exercise that was carried out for the period 2004–2010, focusing on the set of journals that are considered relevant for the subarea statistics and financial mathematics. Using four bibliometric indicators (IF, IF5, AIS and the h-index), some…

Statistics and ProbabilityEconomics and EconometricEconomics and EconometricsClass (set theory)Research evaluationClusteringSet (abstract data type)Valutazione della Qualità delle RicercaCovariateStatisticsEconometricsFinite mixture modelsCluster analysisFinite mixture modelMathematicsGraded response modelMathematical financeItem response theory modelsItem response theory modelProbability and statisticsLatent class modelRankingStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaValutazione della Qualità delle Ricerca; Clustering; Finite mixture models; Graded response model; Item response theory models; Research evaluation;Social Sciences (miscellaneous)Journal of the Royal Statistical Society Series A: Statistics in Society
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A heuristic method for estimating attribute importance by measuring choice time in a ranking task

2012

The evaluation of a product or service in terms of its attributes has been broadly studied in marketing, management and decision sciences. However, methods for finding important attributes have theoretical and practical limitations. The former are related to the selection of the most appropriate model; the latter are due to large number of variables that affect the specific experimental context. This study aims to present a new methodology that captures attribute preferences from a respondent and in particular, by using the choice time in a ranking task, it allows to indirectly obtain the importance weights for several tested attributes through a simple, fast and inexpensive procedure. More…

Statistics and ProbabilityEconomics and EconometricsService (systems architecture)HeuristicComputer scienceSettore SECS-S/02 - Statistica Per La Ricerca Sperimentale E TecnologicaVariable and attributeContext (language use)computer.software_genreTask (project management)RankingRespondentData miningStatistics Probability and UncertaintySettore SECS-S/01 - StatisticacomputerFinanceSelection (genetic algorithm)CHOICE TIME response time response latency attribute rating choice models
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Generalized Symmetry Models for Hypercubic Concordance Tables

2000

Summary Frequency data obtained classifying a sample of 'units' by the same categorical variable repeatedly over 'components', can be arranged in a hypercubic concordance table (h.c.t.). This kind of data naturally arises in a number of different areas such as longitudinal studies, studies using matched and clustered data, item-response analysis, agreement analysis. In spite of the substantial diversity of the mechanisms that can generate them, data arranged in a h.c.t. can all be analyzed via models of symmetry and quasi-symmetry, which exploit the special structure of the h.c.t. The paper extends the definition of such models to any dimension, introducing the class of generalized symmetry…

Statistics and ProbabilityLongitudinal dataItem-response analysiStructure (category theory)InferenceClass (philosophy)Statistical modelClusteringAgreementAlgebraGeneralized symmetry modelMatchingDimension (data warehouse)Statistical theoryStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaLikelihood functionCategorical variableAlgorithmMathematicsInternational Statistical Review / Revue Internationale de Statistique
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Power and Type I Error of the Mean and Covariance Structure Analysis Model for Detecting Differential Item Functioning in Graded Response Items.

2016

In this simulation study, we investigate the power and Type I error rate of a procedure based on the mean and covariance structure analysis (MACS) model in detecting differential item functioning (DIF) of graded response items with five response categories. The following factors were manipulated: type of DIF (uniform and non-uniform), DIF magnitude (low, medium and large), equality/inequality of latent trait distributions, sample size (100, 200, 400, and 800) and equality or inequality of the sample sizes across groups. The simulated test was made up of 10 items, of which only 1 contained DIF. One hundred replications were generated for each simulated condition. Results indicate that the MA…

Statistics and ProbabilityMultivariate analysisExperimental and Cognitive PsychologyGeneral MedicineCovarianceDifferential item functioningPower (physics)Distribution (mathematics)Arts and Humanities (miscellaneous)Sample size determinationStatisticsItem response theoryType I and type II errorsMathematicsMultivariate behavioral research
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