Search results for "Modelling"

showing 10 items of 1353 documents

On modelling and stability of axially moving viscoelastic materials

2013

mallintaminenpaperinvalmistusnumeeriset menetelmätpaper machinesviskositeettisolid mechanicsstabilitylineaariset mallitkimmoisuusmodellingcontinuum mechanicsvärähtelytout-of-plane vibrationslujuusoppivakavuusmatemaattiset mallitviscoelasticitypaperikoneetdynamiikka
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gllvm : Fast analysis of multivariate abundance data with generalized linear latent variable models in R

2019

1.There has been rapid development in tools for multivariate analysis based on fully specified statistical models or “joint models”. One approach attracting a lot of attention is generalized linear latent variable models (GLLVMs). However, software for fitting these models is typically slow and not practical for large datsets. 2.The R package gllvm offers relatively fast methods to fit GLLVMs via maximum likelihood, along with tools for model checking, visualization and inference. 3.The main advantage of the package over other implementations is speed e.g. being two orders of magnitude faster, and capable of handling thousands of response variables. These advances come from using variationa…

mallintaminenspecies interactionshigh-dimensional datamultivariate analysisvuorovaikutusmonimuuttujamenetelmätjoint modellingor-26dinationlajitmallit (mallintaminen)tilastolliset mallitekologia
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EXPERIMENTAL SEISMIC ANALYSIS OF MONUMENTS FOR RISK MITIGATION

2008

An experimental investigation, at the moment in progress, for the evaluation of the seismic vulnerability of a monumental structure and the effects of some reinforcement devices are presented. Referring to this monumental structure, that is a church, the authors obtained the dynamically identified analytical model and recognized that the drum-dome system was one of the macro-elements with highest risk. This result was obtained by analyzing the linear behaviour. In order to study the nonlinear behaviour, tests on reduced scale models were necessary. The models, with and without risk mitigation reinforcements, were subjected to seismic input with rising intensity in order to know the effects …

masonry churches drum-dome systems modelling retrofittingSettore ICAR/09 - Tecnica Delle Costruzioni
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Teachers' attitudes and self-efficacy on implementing inclusive education in Japan and Finland : A comparative study using multi-group structural equ…

2018

This study aims to explore relationships between teachers' attitudes, self-efficacy, and background variables regarding inclusive education by using a sample of 359 Japanese and 872 Finnish teachers. A multi-group structural equation modelling was conducted to find similarities and differences in how the background variables predict teachers' attitudes and self-efficacy. Experience in teaching students with disabilities had a positive effect on teachers' attitudes and self-efficacy in both countries. However, teachers' teaching career and the amount of inclusive education training affected them differently in Japan and Finland. The findings could be used to improve inclusive education train…

measurement invarianceosallistava opetusmulti-group structural equation modellinginclusive educationJapanimental disorderseducationinklusiivinen opetusSuomiasenteetopettajatbehavioral disciplines and activitiesomatoimisuus
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Data from: Transparency reduces predator detection in mimetic clearwing butterflies

2019

1. Predation is an important selective pressure and some prey have evolved conspicuous warning signals that advertise unpalatability (i.e. aposematism) as an antipredator defence. Conspicuous colour patterns have been shown effective as warning signals, by promoting predator learning and memory. Unexpectedly, some butterfly species from the unpalatable tribe Ithomiini possess transparent wings, a feature rare on land but common in water, known to reduce predator detection. 2. We tested if transparency of butterfly wings was associated with decreased detectability by predators, by comparing four butterfly species exhibiting different degrees of transparency, ranging from fully opaque to larg…

medicine and health careBrevioleria sebaHypothyris ninoniaexperimentaposematicLife SciencesMedicineCeratinia tutiaIthomia salapiavision modellingcrypsisIthomiini
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Data from: A mechanistic underpinning for sigmoid dose-dependent infection

2016

Theoretical models of environmentally transmitted diseases often assume that transmission is a constant process, which scales linearly with pathogen dose. Here we question the applicability of such an assumption and propose a sigmoidal form for the pathogens infectivity response. In our formulation, this response arises under two assumptions: 1) multiple invasion events are required for a successful pathogen infection and 2) the host invasion state is reversible. The first assumption reduces pathogen infection rates at low pathogen doses, while the second assumption, due to host immune function, leads to a saturating infection rate at high doses. The derived pathogen dose:infection rate -re…

medicine and health careepidemiological modellingGalleria mellonellaenvironmental transmissionMedicinepathogen transmissionLife sciencesSerratia marcescens
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Translating cross-lagged effects into incidence rates and risk ratios: The case of psychosocial safety climate and depression

2017

Longitudinal studies are the gold standard of empirical work and stress research whenever experiments are not plausible. Frequently, scales are used to assess risk factors and their consequences, and cross-lagged effects are estimated to determine possible risks. Methods to translate cross-lagged effects into risk ratios to facilitate risk assessment do not yet exist, which creates a divide between psychological and epidemiological work stress research. The aim of the present paper is to demonstrate how cross-lagged effects can be used to assess the risk ratio of different levels of psychosocial safety climate (PSC) in organisations, an important psychosocial risk for the development of dep…

medicine.medical_specialtyActuarial science05 social sciencesGold standard050401 social sciences methodscontinuous time modellingSafety climate0504 sociologycross-lagged effectsRelative riskCross laggedEnvironmental healthdepression0502 economics and businessEpidemiologymedicineincidence ratespsychosocial safety climatePsychologyRisk assessmentPsychosocialMonte Carlo simulation050203 business & managementApplied PsychologyDepression (differential diagnoses)Work & Stress
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Predicting survival after transarterial chemoembolization for hepatocellular carcinoma using a neural network: A Pilot Study.

2019

BACKGROUND AND AIMS Deciding when to repeat and when to stop transarterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC) can be difficult even for experienced investigators. Our aim was to develop a survival prediction model for such patients undergoing TACE using novel machine learning algorithms and to compare it to conventional prediction scores, ART, ABCR and SNACOR. METHODS For this retrospective analysis, 282 patients who underwent TACE for HCC at our tertiary referral centre between January 2005 and December 2017 were included in the final analysis. We built an artificial neural network (ANN) including all parameters used by the aforementioned risk scores a…

medicine.medical_specialtyCarcinoma Hepatocellular610 MedizinPilot Projects03 medical and health sciences0302 clinical medicine610 Medical sciencesmedicineHumansIn patientInternal validationChemoembolization TherapeuticRetrospective StudiesHepatologyArtificial neural networkbusiness.industryLiver NeoplasmsPatient survivalClinical routinemedicine.diseaseTreatment Outcome030220 oncology & carcinogenesisHepatocellular carcinoma030211 gastroenterology & hepatologyRadiologyNeural Networks ComputerbusinessArea under the roc curvePredictive modellingLiver international : official journal of the International Association for the Study of the LiverREFERENCES
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A mathematical model of cardiovascular dynamics for the diagnosis and prognosis of hemorrhagic shock

2020

Abstract A variety of mathematical models of the cardiovascular system have been suggested over several years in order to describe the time-course of a series of physiological variables (i.e. heart rate, cardiac output, arterial pressure) relevant for the compensation mechanisms to perturbations, such as severe haemorrhage. The current study provides a simple but realistic mathematical description of cardiovascular dynamics that may be useful in the assessment and prognosis of hemorrhagic shock. The present work proposes a first version of a differential-algebraic equations model, the model dynamical ODE model for haemorrhage (dODEg). The model consists of 10 differential and 14 algebraic e…

medicine.medical_specialtyCardiac outputMean arterial pressureShock HemorrhagicSettore ING-INF/01 - ElettronicaCardiovascular SystemGeneral Biochemistry Genetics and Molecular Biologycardiovascular dynamicshemorrhagic shockHeart RateInternal medicineHeart ratemedicineQuantitative assessmentAnimalsmathematical modellingCardiac OutputGeneral Environmental SciencePharmacologyGeneral Immunology and MicrobiologyMathematical modelbusiness.industryApplied MathematicsGeneral NeuroscienceSettore ING-IND/34 - Bioingegneria IndustrialeExperimental dataGeneral MedicineModels Theoreticalhemorrhagic shock;Blood pressureModeling and SimulationSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaHemorrhagic shockCardiologybusinessMathematical Medicine and Biology: A Journal of the IMA
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Enhanced prediction of hemoglobin concentration in a very large cohort of hemodialysis patients by means of deep recurrent neural networks.

2019

Erythropoiesis Stimulating Agents (ESAs) have become a standard anemia management tool for End Stage Renal Disease (ESRD) patients. However, dose optimization constitutes an extremely challenging task due to huge inter and intra-patient variability in the responses to ESA administration. Current data-based approaches to anemia control focus on learning accurate hemoglobin prediction models, which can be later utilized for testing competing treatment choices and choosing the optimal one. These methods, despite being proven effective in practice, present several shortcomings which this paper intends to tackle. Namely, they are limited to a small cohort of patients and, even then, they fail to…

medicine.medical_specialtyComputer scienceAnemiamedicine.medical_treatmentMedicine (miscellaneous)End stage renal diseaseTask (project management)03 medical and health sciencesHemoglobins0302 clinical medicineArtificial IntelligenceRenal DialysismedicineHumansProspective StudiesIntensive care medicine030304 developmental biology0303 health sciencesbusiness.industryDeep learningmedicine.diseaseRecurrent neural networkCohortHematinicsKidney Failure ChronicArtificial intelligenceHemodialysisNeural Networks Computerbusiness030217 neurology & neurosurgeryPredictive modellingArtificial intelligence in medicine
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