Search results for " predictive model"

showing 10 items of 17 documents

Predicting shifting sustainability trade-offs in marine finfish aquaculture under climate change

2018

Defining sustainability goals is a crucial but difficult task because it often involves the quantification of multiple interrelated and sometimes conflicting components. This complexity may be exacerbated by climate change, which will increase environmental vulnerability in aquaculture and potentially compromise the ability to meet the needs of a growing human population. Here, we developed an approach to inform sustainable aquaculture by quantifying spatio-temporal shifts in critical trade-offs between environmental costs and benefits using the time to reach the commercial size as a possible proxy of economic implications of aquaculture under climate change. Our results indicate that optim…

0106 biological sciencesTrade-offsSettore BIO/07 - EcologiaAquatic OrganismsConservation of Natural Resources010504 meteorology & atmospheric sciencesClimate ChangeMechanistic predictive modelsPopulationFisheriesClimate changeAquaculture01 natural sciencesAquaculture; Mechanistic predictive models; Mediterranean Sea; Regional climate models; Seabass; Trade-offs; Global and Planetary Change; Environmental Chemistry; Ecology; 2300Effects of global warmingseabaMediterranean SeaAnimalsHumansEnvironmental ChemistryEnvironmental impact assessmenteducationEnvironmental planning0105 earth and related environmental sciencesGeneral Environmental Scienceeducation.field_of_studyGlobal and Planetary Changemechanistic predictive modelEcology2300010604 marine biology & hydrobiologyregional climate modelFishesTemperatureNatural resourceSeabassSustainable managementSustainabilityBusinessGlobal and Planetary ChangeRegional climate models
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A laparoscopic risk-adjusted model to predict major complications after primary debulking surgery in ovarian cancer: A single-institution assessment

2016

Abstract Objective To develop and validate a simple adjusted laparoscopic score to predict major postoperative complications after primary debulking surgery (PDS) in advanced epithelial ovarian cancer (AEOC). Methods From January 2006 to June 2015, preoperative, intraoperative, and post-operative outcome data from patients undergoing staging laparoscopy (S-LPS) before receiving PDS (n=555) were prospectively collected in an electronic database and retrospectively analyzed. Major complications were defined as levels 3 to 5 of MSKCC classification. On the basis of a multivariate regression model, the score was developed using a random two-thirds of the population (n=370) and was validated on …

Adultmedicine.medical_specialtyPost-operative complicationsPopulationLaparoscopy; Ovarian cancer; Post-operative complications; Predictive model; Obstetrics and Gynecology; OncologyRisk AssessmentYoung Adult03 medical and health sciencesGynecologic Surgical ProceduresPostoperative Complications0302 clinical medicineOvarian cancerAscitesHumansMedicineMajor complicationLaparoscopy; Ovarian cancer; Post-operative complications; Predictive modelYoung adultLaparoscopyeducationAgedAged 80 and overOvarian Neoplasmseducation.field_of_studyModels Statistical030219 obstetrics & reproductive medicinemedicine.diagnostic_testbusiness.industryReproducibility of ResultsObstetrics and GynecologyMiddle Agedmedicine.diseaseDebulkingSurgerySettore MED/40 - GINECOLOGIA E OSTETRICIAItalyOncologyPredictive model030220 oncology & carcinogenesisFemaleLaparoscopymedicine.symptombusinessOvarian cancerRisk assessment
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Probabilité d'apparition d'un phénomène parasitaire et choix de modèles de régression logistique

2007

Epidemiological processes are now using spatial statistics and modelling tools. The main objective of most health risks studies consists in identifying potential contamination sources and factors capable of explaining their localization. Health data often prove binary (typically presence/absence) and specific methods such as binary logistic regression have to be used. This method's output consists in a probability for the pathogen of interest. A posterior classification of each sample is then conducted using a probability threshold. The method used to maximize this threshold is called the ROC curve which consists in giving a representation of the behaviour of the model and then to choose th…

Spatial epidemiology Binary logistic regression ROC curves Predictive modelling[SHS.GEO] Humanities and Social Sciences/Geography[SHS.GEO]Humanities and Social Sciences/GeographyÉpidémiologie spatiale Régression logistique binaire Courbes ROC Modélisation prédictive[ SHS.GEO ] Humanities and Social Sciences/Geography
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Development Of An Econometric Model Case Study: Romanian Classification System

2015

Abstract The purpose of the paper is to illustrate an econometric model used to predict the lean meat content in pig carcasses, based on the muscle thickness and back fat thickness measured by the means of an optical probe (OptiGrade PRO).The analysis goes through all steps involved in the development of the model: statement of theory, specification of the mathematical model, sampling and collection of data, estimation of the parameters of the chosen econometric model, tests of the hypothesis derived from the model and prediction equations. The data have been in a controlled experiment conducted by the Romanian Carcass Classification Commission in 2007. The purpose of the experiment was to …

EstimationStatement (computer science)HF5001-6182Social PsychologyInterviewComputer scienceEconomics Econometrics and Finance (miscellaneous)seurop systemSampling (statistics)Regression analysiseconometricsregression analysispredictive modelEconometric modelEconometricsBusiness Management and Accounting (miscellaneous)Normativemedia_common.cataloged_instanceBusinessEuropean unioneconometrics predictive model regression analysis SEUROP systemmedia_commonStudies in Business and Economics
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Clinical and biochemical determinants of the extent of liver steatosis in type 2 diabetes mellitus

2015

Objective Nonalcoholic fatty liver disease is very frequent in both type 2 diabetes mellitus (T2DM) and the metabolic syndrome (MS), which share clinical and metabolic characteristics. Whether and to which extent these characteristics can predict the degree of liver steatosis are not entirely clear. Patients and methods We determined liver fat (divided into four classes) by standard sonographic images, and clinical and biochemical variables, in 60 consecutive patients with T2DM and with features of the MS. We examined both simple and multiple correlations between the degree of liver steatosis and the variables measured. Results Increased liver fat (defined as >5% of liver mass) was detec…

Malenonalcoholic fatty liver diseasemedicine.medical_specialtytype 2 diabetes mellitusmedicine.medical_treatmentSettore MED/50 - Scienze Tecniche Mediche ApplicateGastroenterologyleptinliver steatosispredictive modelInsulin resistanceNon-alcoholic Fatty Liver DiseaseInternal medicineinsulin resistanceNonalcoholic fatty liver diseasemedicineHumansInsulinAdiposityAgedUltrasonographyvisceral adiposityGlycated HemoglobinMetabolic SyndromeSettore SECS-S/06 - Metodi mat. dell'economia e Scienze Attuariali e FinanziarieModels StatisticalAnthropometryHepatologybusiness.industryInsulinHemoglobin A1c; insulin resistance; leptin; liver steatosis; metabolic control; multiple regression analysis; nonalcoholic fatty liver disease; predictive model; type 2 diabetes mellitus; visceral adiposity;GastroenterologyType 2 Diabetes MellitusHemoglobin A1c; insulin resistance; leptin; liver steatosis; metabolic control; multiple regression analysis; nonalcoholic fatty liver disease; predictive model; type 2 diabetes mellitus; visceral adiposity; Gastroenterology; Hepatologymetabolic controlmultiple regression analysisMiddle AgedHepatologymedicine.diseaseEndocrinologyDiabetes Mellitus Type 2Hemoglobin A1cMetabolic control analysisFemaleWaist CircumferenceSteatosisMetabolic syndromebusinesshemoglobin A1c leptin liver steatosis metabolic control multiple regression analysis nonalcoholic fatty liver disease insulin resistance predictive model type 2 diabetes mellitus visceral adiposity
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Innovative tools to diagnose the impact of land use practices on soil microbial communities

2018

International audience; Preservation and sustainable use of soil biological communities represent major challenges in the current agroecological context. Indeed, most of soil ecosystem services results from biological functions particularly driven by taxonomic and functional assemblages of microbiological communities (i.e. nutrient cycling, soil aggregation, depollution, etc.). Consequently, soil microbial communities are logical candidates as effective indicators of soil quality and sustainability. But, good biological indicators must be associated with references that encompass an operating range of measured values that allow performing the desired diagnosis. Even if numerous studies have…

[SDE] Environmental Sciencessoil microbial indicatorssoil biological diagnosisstatistical predictive model[SDE]Environmental Sciences
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Forecasts on the development of hydrogen refuelling infrastructures in Portugal

2021

In Portugal, the transition to new forms of mobility has begun in recent years, but there are still obstacles to overcome. Currently, hybrid vehicles (PHEVs) are the most widespread and accepted by the community and that is probably due to range anxiety, having in fact the possibility of double charging (both through the thermal engine and the electric battery). Furthermore, it must be considered that in addition to electric vehicles, another valid alternative to mobility in the near future is the hydrogen vehicles one. These appear to be even more sustainable from the point of view of air emissions, but on the other hand the costs for the production of hydrogen are still too high. Then, th…

Range anxietybusiness.industryMarket trendEnvironmental economicsSettore ING-IND/32 - Convertitori Macchine E Azionamenti ElettriciDiscount pointsHydrogen vehicleMarket researchSettore ING-IND/31 - ElettrotecnicaSmart gridFuel cellsProduction (economics)BusinessElectric mobility Forecasting for FCEV Fuel cell vehicles Hydrogen Plug-in hybrid Predictive model Socio-technical transition
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Application of an interspecific competition model to predict the growth of Aeromonas hydrophyla on fish surfaces during refrigerated storage (Anwendu…

2007

The growth of Aeromonas hydrophila and the aerobic mesophilic plate count (APC) on gilthead seabream surfaces was evaluated during refrigerated storage (21 days). The related growth curves were compared with those obtained by a conventional third order predictive model obtaining a low agreement between observed and predicted data (Root Mean Squared Error = 1.77 for Aeromonas hydrophila and 0.64 for APC).The Lotka-Volterra interspecific competition model was used in order to calculate the degree of interaction between the two bacterial populations (beta_{Ah/APC} and beta_{APC/Ah}, respectively, the interspecific competition coefficients of APC on Aeromonas hydrophila and vice-versa). Afterwa…

Gilthead sea breamPredictive modelAeromonas hydrophila; Gilthead sea bream; Predictive model; Bacterial interspecific competition;Aeromonas hydrophila; Goldbrasse; Vorhersagemodell; Bakterielle KonkurrenzBacterial interspecific competitionBakterielle KonkurrenzGoldbrasseSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Aeromonas hydrophilaVorhersagemodell
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A bark beetle infestation predictive model based on satellite data in the frame of decision support system TANABBO

2020

The European spruce bark beetle Ips typographus L. causes significant economic losses in managed coniferous forests in Central and Northern Europe. New infestations either occur in previously undisturbed forest stands (i.e., spot initiation) or depend on proximity to previous years’ infestations (i.e., spot spreading). Early identification of newly infested trees over the forested landscape limits the effective control measures. Accurate forecasting of the spread of bark beetle infestation is crucial to plan efficient sanitation felling of infested trees and prevent further propagation of beetle-induced tree mortality. We created a predictive model of subsequent year spot initiation and spo…

0106 biological sciencesIps typographusDecision support systemBark beetlemedicine.disease_causeFelling01 natural sciencesgisbark beetle infestationSatellite dataInfestationmedicinelcsh:ForestryDigital elevation modelNature and Landscape ConservationkovakuoriaisetEcologybiologyForestryForestryNorway Spruce04 agricultural and veterinary sciencesVegetationspatial predictive modelbiology.organism_classificationGISroc curvemetsäekosysteemitGeographyROC Curvenorway spruce040103 agronomy & agriculture0401 agriculture forestry and fisherieslcsh:SD1-669.5010606 plant biology & botany
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Electric Mobility in Portugal: Current Situation and Forecasts for Fuel Cell Vehicles

2021

In recent years, the growing concern for air quality has led to the development of sustainable vehicles to replace conventional internal combustion engine (ICE) vehicles. Currently, the most widespread technology in Europe and Portugal is that of Battery Electric Vehicles (BEV) or plug‐in HEV (PHEV) electric cars, but hydrogen‐based transport has also shown significant growth in the commercialization of Fuel Cell Electric Vehicles (FCEV) and in the development of new infrastructural schemes. In the current panorama of EV, particular attention should be paid to hydrogen technology, i.e., FCEVs, which is potentially a valid alternative to BEVs and can also be hybrid (FCHEV) and plug‐in hybrid…

TechnologyControl and OptimizationPopulationEnergy Engineering and Power TechnologySocio‐technical transitionplug-in hybridSettore ING-IND/32 - Convertitori Macchine E Azionamenti Elettricifuel cell vehiclesCommercializationMarket segmentationsocio-technical transitionElectrical and Electronic EngineeringeducationEngineering (miscellaneous)Hydrogen infrastructureeducation.field_of_studyRenewable Energy Sustainability and the EnvironmentTechnological changeTElectric potential energyelectric mobility; fuel cell vehicles; plug-in hybrid; hydrogen; socio-technical transition; forecasting for FCEV; predictive modelBuilding and ConstructionEnvironmental economicsFuel cell vehicleSettore ING-IND/31 - ElettrotecnicaWork (electrical)Internal combustion enginePredictive modelElectric mobilityBusinessPlug‐in hybridEnergy (miscellaneous)Forecasting for FCEVHydrogenEnergies; Volume 14; Issue 23; Pages: 7945
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