scholarly journals Calibration of the Dermal Advanced REACH Tool (dART) Mechanistic Model

2019 ◽  
Vol 63 (6) ◽  
pp. 637-650 ◽  
Author(s):  
Kevin McNally ◽  
Jean-Philippe Gorce ◽  
Henk A Goede ◽  
Jody Schinkel ◽  
Nick Warren
Keyword(s):  
Mass Transport ◽  
Mechanistic Model ◽  
Contextual Information ◽  
Measurement Data ◽  
Dermal Exposure ◽  
Transport Processes ◽  
Data Set ◽  
Mixed Effect ◽  
Model Estimate ◽  
Liquid Products

Abstract The dermal Advanced REACH Tool (dART) is a Tier 2 exposure modelling tool currently in development for estimating dermal exposure to the hands (mg min−1) for non-volatile liquid and solids-in-liquid products. The dART builds upon the existing ART framework and describes three mass transport processes [deposition (Dhands), direct emission and direct contact (Ehands), and contact transfer (Thands)] that may each contribute to dermal exposure. The mechanistic model that underpins the dART and its applicability domain has already been described in previous work. This paper describes the process of calibrating the mechanistic model such that the dimensionless score that results from encoding contextual information about a task into the determinants of the dART can be converted into a prediction of exposure (mg min−1). Furthermore, as a consequence of calibration, the uncertainty in a dART prediction may be quantified via a confidence interval. Thirty-six experimental studies were identified that satisfied the conditions of: (i) high-quality contextual information that was sufficient to confidently code the dART mechanistic model determinants; (ii) reliable exposure measurement data sets were available. From these studies, 40 exposure scenarios were subsequently developed. A non-linear log-normal mixed-effect model was fitted to the data set of Dhands,   Ehands, and    Thands scores and corresponding measurement data. The dART model was shown to be consistent with activities covering a broad range of tasks [spray applications, activities involving open liquid surfaces (e.g. dipping, mixing), handling of contaminated objects, spreading of liquid products, and transfer of products (e.g. pouring of liquid)]. Exposures resulting from a particular task were each dominated by one or two of the identified mass transport processes. As a consequence of calibration, an estimate of the uncertainty associated with a mechanistic model estimate is available. A 90% multiplicative interval is approximately a factor of six. This represents poorer overall precision than the (inhalation) ART model for dusts and vapours, although better than the ART model for mists. Considering the complexity of the conceptual model compared with the ART, the wide variety of exposure scenarios considered with differing dominant routes, and the particular challenges that result from the consideration of measurement data both above and beneath a protective glove, the precision of the calibrated dART mechanistic model is reasonable for well-documented exposure scenarios coded by experts. However, as the inputs to the model are based upon user judgement, in practical use, the reliability of predictions will be dependent upon both the competence of users and the quality of contextual information available on an exposure scenario.

scholarly journals Bridging Photosynthesis and Crop Yield Formation with a Mechanistic Model of Whole Plant Carbon Nitrogen Interaction

2020 ◽  
Author(s):  
Tian-Gen Chang ◽  
Xin-Guang Zhu
Keyword(s):  
Crop Yield ◽  
Genetic Manipulation ◽  
Mechanistic Model ◽  
Grain Filling ◽  
Transport Processes ◽  
Data Set ◽  
Whole Plant ◽  
Parameterized Model ◽  
Source Sink ◽  
Yield Formation

ABSTRACTCrop yield is co-determined by photosynthetic potential of source organs, and pattern of partitioning and utilization of photosynthate among sink organs. Although correlation between source sink relation and grain yield has been studied for a century, a quantitative understanding of the metabolic basis of source sink interaction is lacking. Here, we describe a mechanistic model of Whole plAnt Carbon Nitrogen Interaction (WACNI), enabling precise prediction of plant physiological dynamics during the grain filling period by reconstructing primary metabolic and biophysical processes in source, sink and transport organs. To get a specified range of parameters required to quantify the enzymatic kinetics in rice, a data set is established based on case studies and natural variation surveys in the past decades. The parameterized model quantitatively predicts plant carbon and nitrogen budget upon various scenarios, ranging from field management and environmental perturbation to genetic manipulation, thus enabling dissection of the precise role of such alterations in crop yield formation. Model simulations further reveal the importance of re-allocating activity of carbon/nitrogen metabolic and transport processes for a plant physiological ideotype to maximize crop yield.

scholarly journals Localization of Scattering Objects Using Neural Networks

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 11
Author(s):  
Domonkos Haffner ◽  
Ferenc Izsák
Keyword(s):  
Neural Networks ◽  
Plane Waves ◽  
Measurement Data ◽  
Scattered Wave ◽  
Training Data ◽  
Data Set ◽  
Main Compound ◽  
Incident Plane ◽  
The Neural Networks ◽  
Simulation Package

The localization of multiple scattering objects is performed while using scattered waves. An up-to-date approach: neural networks are used to estimate the corresponding locations. In the scattering phenomenon under investigation, we assume known incident plane waves, fully reflecting balls with known diameters and measurement data of the scattered wave on one fixed segment. The training data are constructed while using the simulation package μ-diff in Matlab. The structure of the neural networks, which are widely used for similar purposes, is further developed. A complex locally connected layer is the main compound of the proposed setup. With this and an appropriate preprocessing of the training data set, the number of parameters can be kept at a relatively low level. As a result, using a relatively large training data set, the unknown locations of the objects can be estimated effectively.

Harmonic Analysis on Low Quality Tidal Data

2014 ◽  
Author(s):  
Joost den Haan
Keyword(s):  
Harmonic Analysis ◽  
Three Dimensional ◽  
Measurement Data ◽  
Tidal Energy ◽  
Energy Yield ◽  
Profile Measurement ◽  
Current Profile ◽  
Tidal Power ◽  
Data Set ◽  
Tidal Forcing

The aim of the study is to devise a method to conservatively predict a tidal power generation based on relatively short current profile measurement data sets. Harmonic analysis on a low quality tidal current profile measurement data set only allowed for the reliable estimation of a limited number of constituents leading to a poor prediction of tidal energy yield. Two novel, but very different approaches were taken: firstly a quasi response function is formulated which combines the currents profiles into a single current. Secondly, a three dimensional vectorial tidal forcing model was developed aiming to support the harmonic analysis with upfront knowledge of the actual constituents. The response based approach allowed for a reasonable prediction. The vectorial tidal forcing model proved to be a viable start for a full featuring numerical model; even in its initial simplified form it could provide more insight than the conventional tidal potential models.

scholarly journals Effects of polar stratospheric clouds in the Nimbus 7 LIMS Version 6 data set

2016 ◽  
Vol 9 (7) ◽  
pp. 2927-2946 ◽  
Author(s):  
Ellis Remsberg ◽  
V. Lynn Harvey
Keyword(s):  
Stratospheric Aerosol ◽  
Transport Processes ◽  
The Arctic ◽  
Additional Parameter ◽  
Polar Stratospheric Clouds ◽  
Data Set ◽  
Screening Criteria ◽  
Temperature Thresholds ◽  
Level 3 ◽  
Stratospheric Clouds

Abstract. The historic Limb Infrared Monitor of the Stratosphere (LIMS) measurements of 1978–1979 from the Nimbus 7 satellite were re-processed with Version 6 (V6) algorithms and archived in 2002. The V6 data set employs updated radiance registration methods, improved spectroscopic line parameters, and a common vertical resolution for all retrieved parameters. Retrieved profiles are spaced about every 1.6° of latitude along orbits and include the additional parameter of geopotential height. Profiles of O3 are sensitive to perturbations from emissions of polar stratospheric clouds (PSCs). This work presents results of implementing a first-order screening for effects of PSCs using simple algorithms based on vertical gradients of the O3 mixing ratio. Their occurrences are compared with the co-located, retrieved temperatures and related to the temperature thresholds needed for saturation of H2O and/or HNO3 vapor onto PSC particles. Observed daily locations where the major PSC screening criteria are satisfied are validated against PSCs observed with the Stratospheric Aerosol Monitor (SAM) II experiment also on Nimbus 7. Remnants of emissions from PSCs are characterized for O3 and HNO3 following the screening. PSCs may also impart a warm bias in the co-located LIMS temperatures, but by no more than 1–2 K at the altitudes of where effects of PSCs are a maximum in the ozone; thus, no PSC screening was applied to the V6 temperatures. Minimum temperatures vary between 187 and 194 K and often occur 1 to 2 km above where PSC effects are first identified in the ozone (most often between about 21 and 28 hPa). Those temperature–pressure values are consistent with conditions for the existence of nitric acid trihydrate (NAT) mixtures and to a lesser extent of super-cooled ternary solution (STS) droplets. A local, temporary uptake of HNO3 vapor of order 1–3 ppbv is indicated during mid-January for the 550 K surface. Seven-month time series of the distributions of LIMS O3 and HNO3 are shown based on their gridded Level 3 data following the PSC screening. Zonal coefficients of both species are essentially free of effects from PSCs on the 550 K surface, based on their average values along PV contours and in terms of equivalent latitude. Remnants of PSCs are still present in O3 on the 450 K surface during mid-January. It is judged that the LIMS Level 3 data are of good quality for analyzing the larger-scale, stratospheric chemistry and transport processes during the Arctic winter of 1978–1979.

scholarly journals Dermal Advanced REACH Tool (dART)—Development of a Dermal Exposure Model for Low-Volatile Liquids

2019 ◽  
Vol 63 (6) ◽  
pp. 624-636 ◽  
Author(s):  
Henk A Goede ◽  
Kevin McNally ◽  
Jean-Philippe Gorce ◽  
Hans Marquart ◽  
Nick D Warren ◽  
...  
Keyword(s):  
Mechanistic Model ◽  
Predictive Ability ◽  
Field Studies ◽  
Dermal Exposure ◽  
Exposure Model ◽  
Sufficient Evidence ◽  
Software Platform ◽  
Related Factors ◽  
Direct Emission ◽  
Volatile Liquids

Abstract This article describes the development of a mechanistic model for underpinning the dermal Advanced REACH Tool (dART), an extension of the existing ART model and its software platform. It was developed for hand exposure to low volatile liquids (vapour pressure ≤ 10 Pa at 20°C) including solids-in-liquid products. The model is based on an existing conceptual dermal source-receptor model that has been integrated into the ART framework. A structured taxonomy of workplace activities referred to as activity classes are adopted from ART.  Three key processes involved in mass transport associated with dermal exposure are applied, i.e. deposition, direct emission and contact, and transfer. For deposition, the model adopts all the relevant modifying factors (MFs) applied in ART. In terms of direct emission and contact (e.g. splashes) and transfer (e.g. hand-surface contacts), the model defines independent principal MFs, i.e. substance-related factors, activity-related factors, localized- and dispersion control and exposed surface area of the hands. To address event-based exposures as much as possible, the model includes crucial events during an activity (e.g. hand immersions) and translates objective information on tools and equipment (manual or automated) to probable events (e.g. splashes) and worker behaviours (e.g. surface contacts). Based on an extensive review of peer-reviewed literature and unpublished field studies, multipliers were assigned to each determinant and provide an approximated (dimensionless) numerical value. In the absence of (sufficient) evidence, multipliers were assigned to determinants based on assumptions made during discussions by experts in the consortium. A worked example is presented to illustrate the calculation of hand exposure for a specific scenario. The dART model is not yet implemented in the ART software platform, and a robust validation of the model is necessary to determine its predictive ability. With advancing knowledge on dermal exposure and its determinants, this model will require periodic updates and refinements, in addition to further expansion of the applicability domain of the model.

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