Field crops represent one of the highest contributions to dietary metal exposure. The aim of this study was to develop specific regression models for the uptake of metals into various field crops and to compare the usability of other available models. We analysed samples of potato, hop, maize, barley, wheat, rape seed, and grass from 66 agricultural sites. The influence of measured soil concentrations and soil factors (pH, organic carbon, content of silt and clay) on the plant concentrations of Cd, Cr, Cu, Mo, Ni, Pb and Zn was evaluated. Bioconcentration factors (BCF) and plant-specific metal models (PSMM) developed from multivariate regressions were calculated. The explained variability of the models was from 19 to 64% and correlations between measured and predicted concentrations were between 0.43 and 0.90. The developed hop and rapeseed models are new in this field. Available models from literature showed inaccurate results, except for Cd; the modelling efficiency was mostly around zero. The use of interaction terms between parameters can significantly improve plant-specific models.

• Klíčová slova
• Field crops, Heavy metals, Linear regression, Plant uptake, Prediction models,
• MeSH
• Brassica rapa chemie   MeSH
• kontaminace potravin MeSH
• kukuřice setá chemie   MeSH
• látky znečišťující půdu analýza   MeSH
• monitorování životního prostředí metody   statistika a číselné údaje   MeSH
• multivariační analýza MeSH
• pšenice chemie   MeSH
• půda chemie   MeSH
• regresní analýza MeSH
• teoretické modely * MeSH
• těžké kovy analýza   MeSH
• zemědělské plodiny chemie   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Geografické názvy
• Česká republika MeSH
• Názvy látek
• látky znečišťující půdu MeSH
• půda MeSH
• těžké kovy MeSH

Recent evidence suggests that energy metabolism contributes to molecular mechanisms controlling stem cell identity. For example, human embryonic stem cells (hESCs) receive their metabolic energy mostly via glycolysis rather than mitochondrial oxidative phosphorylation. This suggests a connection of metabolic homeostasis to stemness. Nicotinamide adenine dinucleotide (NAD) is an important cellular redox carrier and a cofactor for various metabolic pathways, including glycolysis. Therefore, accurate determination of NAD cellular levels and dynamics is of growing importance for understanding the physiology of stem cells. Conventional analytic methods for the determination of metabolite levels rely on linear calibration curves. However, in actual practice many two-enzyme cycling assays, such as the assay systems used in this work, display prominently nonlinear behavior. Here we present a diaphorase/lactate dehydrogenase NAD cycling assay optimized for hESCs, together with a mechanism-based, nonlinear regression models for the determination of NAD(+), NADH, and total NAD. We also present experimental data on metabolic homeostasis of hESC under various physiological conditions. We show that NAD(+)/NADH ratio varies considerably with time in culture after routine change of medium, while the total NAD content undergoes relatively minor changes. In addition, we show that the NAD(+)/NADH ratio, as well as the total NAD levels, vary between stem cells and their differentiated counterparts. Importantly, the NAD(+)/NADH ratio was found to be substantially higher in hESC-derived fibroblasts versus hESCs. Overall, our nonlinear mathematical model is applicable to other enzymatic amplification systems.

• MeSH
• buněčné extrakty MeSH
• elektroforéza kapilární MeSH
• embryonální kmenové buňky metabolismus   MeSH
• kalibrace MeSH
• lidé MeSH
• NAD metabolismus   MeSH
• nelineární dynamika * MeSH
• oxaziny metabolismus   MeSH
• regresní analýza MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• buněčné extrakty MeSH
• NAD MeSH
• oxaziny MeSH
• resorufin MeSH Prohlížeč

Background concentrations of selected persistent organic pollutants (polychlorinated biphenyls, hexachlorobenzene, p,p'-DDT including metabolites) and polyaromatic hydrocarbons in soils of the Czech Republic were predicted in this study, and the main factors affecting their geographical distribution were identified. A database containing POP concentrations in 534 soil samples and the set of specific environmental predictors were used for development of a model based on regression trees. Selected predictors addressed specific conditions affecting a behavior of the individual groups of pollutants: a presence of primary and secondary sources, density of human settlement, geographical characteristics and climatic conditions, land use, land cover, and soil properties. The model explained a high portion of variability in relationship between the soil concentrations of selected organic pollutants and available predictors. A tree for hexachlorobenzene was the most successful with 76.2% of explained variability, followed by trees for polyaromatic hydrocarbons (71%), polychlorinated biphenyls (68.6%), and p,p'-DDT and metabolites (65.4%). The validation results confirmed that the model is stable, general and useful for prediction. The stochastic model applied in this study seems to be a promising tool capable of predicting the environmental distribution of organic pollutants.

• MeSH
• chemické modely MeSH
• DDT analýza   MeSH
• hexachlorbenzen analýza   MeSH
• látky znečišťující půdu analýza   MeSH
• lidé MeSH
• polychlorované bifenyly analýza   MeSH
• průmyslové fungicidy analýza   MeSH
• regresní analýza MeSH
• stochastické procesy * MeSH
• uhlík chemie   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Geografické názvy
• Česká republika MeSH
• Názvy látek
• DDT MeSH
• hexachlorbenzen MeSH
• látky znečišťující půdu MeSH
• polychlorované bifenyly MeSH
• průmyslové fungicidy MeSH
• uhlík MeSH

Land-use regression (LUR) models provide location and time specific estimates of exposure to air pollution and thereby improve the sensitivity of health effects models. However, they require pollutant concentrations at multiple locations along with land-use variables. Often, monitoring is performed over short durations using mobile monitoring with research-grade instruments. Low-cost PM monitors provide an alternative approach that increases the spatial and temporal resolution of the air quality data. LUR models were developed to predict hourly PM concentrations across a metropolitan area using PM concentrations measured simultaneously at multiple locations with low-cost monitors. Monitors were placed at 23 sites during the 2015/16 heating season. Monitors were externally calibrated using co-located measurements including a reference instrument (GRIMM particle spectrometer). LUR models for each hour of the day and weekdays/weekend days were developed using the deletion/substitution/addition algorithm. Coefficients of determination for hourly PM predictions ranged from 0.66 and 0.76 (average 0.7). The hourly-resolved LUR model results will be used in epidemiological studies to examine if and how quickly, increases in ambient PM concentrations trigger adverse health events by reducing the exposure misclassification that arises from using less time resolved exposure estimates.

• Klíčová slova
• Exposure assessment, Land-use regression, Low-cost monitors, PM(2.5),
• MeSH
• látky znečišťující vzduch * MeSH
• monitorování životního prostředí * přístrojové vybavení   metody   MeSH
• pevné částice MeSH
• roční období MeSH
• teoretické modely MeSH
• znečištění ovzduší * MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• látky znečišťující vzduch * MeSH
• pevné částice MeSH

The aims of this study were to create a regression model of the relationship between load and muscle power output and to determine an optimal load for maximum power output during a countermovement squat and a bench press. 55 males and 48 females performed power testing at 0, 10, 30, 50, 70, 90, and 100% of their individual one-repetition maximum (1-RM) in the countermovement squat and bench press exercises. Values for the maximum dynamic strength and load for each lift were used to develop a regression model in which the ratio of power was predicted from the ratio of the load for each type of lift. By optimizing the regression model, we predicted the optimal load for maximum muscle power. For the bench press and the countermovement squat, the mean optimal loads for maximum muscle output ranged from 50 to 70% of maximum dynamic strength. Optimal load in the acceleration phase of the upward movement of the two exercises appeared to be more important than over the full range of the movement. This model allows for specific determination of the optimal load for a pre-determined power output.

• MeSH
• biologické modely * MeSH
• dospělí MeSH
• fyzická vytrvalost fyziologie   MeSH
• kosterní svaly fyziologie   MeSH
• lidé MeSH
• počítačová simulace MeSH
• přenos energie fyziologie   MeSH
• regresní analýza MeSH
• statistické modely MeSH
• svalová kontrakce fyziologie   MeSH
• zatížení muskuloskeletálního systému fyziologie   MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Survival analysis is commonly conducted in medical and public health research to assess the association of an exposure or intervention with a hard end outcome such as mortality. The Cox (proportional hazards) regression model is probably the most popular statistical tool used in this context. However, when the exposure includes compositional covariables (that is, variables representing a relative makeup such as a nutritional or physical activity behaviour composition), some basic assumptions of the Cox regression model and associated significance tests are violated. Compositional variables involve an intrinsic interplay between one another which precludes results and conclusions based on considering them in isolation as is ordinarily done. In this work, we introduce a formulation of the Cox regression model in terms of log-ratio coordinates which suitably deals with the constraints of compositional covariates, facilitates the use of common statistical inference methods, and allows for scientifically meaningful interpretations. We illustrate its practical application to a public health problem: the estimation of the mortality hazard associated with the composition of daily activity behaviour (physical activity, sitting time and sleep) using data from the U.S. National Health and Nutrition Examination Survey (NHANES).

• Klíčová slova
• Cox regression, NHANES, Survival analysis, accelerometry, compositional data, physical activity, sedentary behaviour, time use,
• MeSH
• cvičení * MeSH
• proporcionální rizikové modely MeSH
• regresní analýza MeSH
• výživa - přehledy MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Modeling the interrelationships between the input parameters and outputs (responses) in any machining processes is essential to understand the process behavior and material removal mechanism. The developed models can also act as effective prediction tools in envisaging the tentative values of the responses for given sets of input parameters. In this paper, the application potentialities of nine different regression models, such as linear regression (LR), polynomial regression (PR), support vector regression (SVR), principal component regression (PCR), quantile regression, median regression, ridge regression, lasso regression and elastic net regression are explored in accurately predicting response values during turning and drilling operations of composite materials. Their prediction performance is also contrasted using four statistical metrics, i.e., mean absolute percentage error, root mean squared percentage error, root mean squared logarithmic error and root relative squared error. Based on the lower values of those metrics and Friedman rank and aligned rank tests, SVR emerges out as the best performing model, whereas the prediction performance of median regression is worst. The results of the Wilcoxon test based on the drilling dataset identify the existence of statistically significant differences between the performances of LR and PCR, and PR and median regression models.

• Klíčová slova
• composite material, drilling, model, regression, turning,
• Publikační typ
• časopisecké články MeSH

This research proposes an assessment and decision support model to use when a driver should be examined about their propensity for traffic accidents, based on an estimation of the driver's psychological traits. The proposed model was tested on a sample of 305 drivers. Each participant completed four psychological tests: the Barratt Impulsiveness Scale (BIS-11), the Aggressive Driving Behaviour Questionnaire (ADBQ), the Manchester Driver Attitude Questionnaire (DAQ) and the Questionnaire for Self-assessment of Driving Ability. In addition, participants completed an extensive demographic and driving survey. Various fuzzy inference systems were tested and each was defined using the well-known Wang-Mendel method for rule-base definition based on empirical data. For this purpose, a programming code was designed and utilized. Based on the obtained results, it was determined which combination of the considered psychological tests provides the best prediction of a driver's propensity for traffic accidents. The best of the considered fuzzy inference systems might be used as a decision support tool in various situations, such as in recruitment procedures for professional drivers. The validity of the proposed fuzzy approach was confirmed as its implementation provided better results than from statistics, in this case multiple regression analysis.

• Klíčová slova
• Traffic accidents, driving behaviour, fuzzy rules based on data, fuzzy systems, multiple regression, road safety,
• MeSH
• agrese MeSH
• bezpečnost MeSH
• dopravní nehody * MeSH
• dospělí MeSH
• fuzzy logika MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• postoj MeSH
• průzkumy a dotazníky MeSH
• psychologické modely * MeSH
• regresní analýza MeSH
• řízení motorových vozidel psychologie   MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

In this paper we demonstrate that fuzzy logic can provide a better tool for predicting recycling behaviour than the customarily used linear regression. To show this, we take a set of empirical data on recycling behaviour (N=664), which we randomly divide into two halves. The first half is used to estimate a linear regression model of recycling behaviour, and to develop a fuzzy logic model of recycling behaviour. As the first comparison, the fit of both models to the data included in estimation of the models (N=332) is evaluated. As the second comparison, predictive accuracy of both models for "new" cases (hold-out data not included in building the models, N=332) is assessed. In both cases, the fuzzy logic model significantly outperforms the regression model in terms of fit. To conclude, when accurate predictions of recycling and possibly other environmental behaviours are needed, fuzzy logic modelling seems to be a promising technique.

• Klíčová slova
• Empirical test, Fuzzy logic, Prediction, Recycling behaviour,
• MeSH
• fuzzy logika * MeSH
• lidé MeSH
• lineární modely * MeSH
• recyklace * statistika a číselné údaje   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

Kinetic models for removal of trichloroethylene, trichloromethane and tetrachloroethylene from water by zero-valent iron were tested. The dehalogenation reactions were modelled by first-order and power law models, pseudo-stationary models with a controlling surface reaction rate and non-stationary models without the assumption of rate controlling step. Regression analysis proved, that the first-order kinetic is not suitable for the modelling of chlorinated hydrocarbons dechlorination. On the other hand, power law models, Langmuir-Hinshelwood analogy models and general models of heterogeneous reactions are reliable for the kinetic description of dechlorination. In spite of an empirical or semi-empirical character, the power law models and models of controlling surface reaction rate can be recommended for the regression analysis owing to the their simple regression parameters interpretation.

• MeSH
• chemické modely * MeSH
• chlorované uhlovodíky chemie   MeSH
• čištění vody metody   MeSH
• kinetika MeSH
• regresní analýza MeSH
• železo chemie   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• srovnávací studie MeSH
• Názvy látek
• chlorované uhlovodíky MeSH
• železo MeSH