Germination of Entomophthora aphidis resting spores under constant temperatures

1978 ◽  
Vol 56 (19) ◽  
pp. 2328-2333 ◽  
Author(s):  
Bijan Payandeh ◽  
D. M. MacLeod ◽  
D. R. Wallace
Keyword(s):  
Empirical Model ◽  
Modeling Approach ◽  
Wide Range ◽  
Resting Spores ◽  
Test Population ◽  
Good Germination

Germination tests at a wide range of constant temperatures show that the upper and lower thresholds for E. aphidis resting spores are about 3.5 and29.5 °C, respectively. Good germination was obtained over the range 10–22 °C with an optimum at about 16.5 °C. It is not known if spores exposed to temperatures above the optimum and failing to germinate are inactivated or killed. An empirical model is presented that describes the time–temperature–germination relationships of one test population. A similar modeling approach may be also applied to other spore populations.

scholarly journals Nutrition in Disguise: Effects of Food Neophobia, Healthy Eating Interests and Provision of Health Information on Liking and Perceptions of Nutrient-Dense Foods in Older Adults

Foods ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 60
Author(s):  
Olivia C. Romaniw ◽  
Ritika Rajpal ◽  
Alison M. Duncan ◽  
Heather H. Keller ◽  
Lisa M. Duizer
Keyword(s):  
Older Adults ◽  
Health Information ◽  
Residential Care ◽  
Healthy Eating ◽  
Food Neophobia ◽  
Older Consumers ◽  
Nutrient Density ◽  
Wide Range ◽  
Test Population ◽  
Hedonic Scale

Older adults (60+ years) are at higher risk of malnutrition. Improving the nutrient-density of their diets is important but presents challenges due to the introduction of new ingredients, liking implications and heterogeneity of older consumers. Ten nutrient-enhanced foods were evaluated for liking (9-point hedonic scale) and sensory perception (check-all-that-apply) by 71 older adults. Three foods were re-evaluated after participants were provided with information about their healthy ingredients and benefits. Participants were also segmented based on their degrees of food neophobia and interests in healthy eating, using questionnaires. The results showed that eight foods had adequate sensory appeal (overall hedonic score of ≥6) to be pursued for residential care menus. Segmentation based on food neophobia and healthy eating interests did not yield any meaningful differences between groups. The effect of health information on liking for the overall sample and subgroups was product-specific: liking scores only increased for the raspberry banana smoothie in the overall test population and higher healthy eating interest subgroup. Health information may lead to the experience of more positive attributes in some foods. Overall, eight foods that were tested could be accepted by a wide range of consumers and providing them with health information may further improve acceptance.

scholarly journals High Froude Number Experimental Investigation of the 2 DOF Behavior of a Multihull Float in Head Waves

2021 ◽  
Vol 6 (01) ◽  
pp. 1-20
Author(s):  
Paul Kerdraon ◽  
Boris Horel ◽  
Patrick Bot ◽  
Adrien Letourneur ◽  
David David Le Touzé
Keyword(s):  
High Performance ◽  
Good Representation ◽  
Prediction Program ◽  
Modeling Approach ◽  
Head Waves ◽  
Wide Range ◽  
Dynamic Velocity ◽  
Velocity Prediction ◽  
High Froude Number ◽  
Stability Issues

Dynamic Velocity Prediction Programs are taking an increasingly prominent role in high performance yacht design, as they allow to deal with seakeeping abilities and stability issues. Their validation is however often neglected for lack of time and data. This paper presents an experimental campaign carried out in the towing tank of the Ecole Centrale de Nantes, France, to validate the hull modeling in use in a previously presented Dynamic Velocity Prediction Program. Even though with foils, hulls are less frequently immersed, a reliable hull modeling is necessary to properly simulate the critical transient phases such as touchdowns and takeoffs. The model is a multihull float with a waterline length of 2.5 m. Measurements were made in head waves in both captive and semi-captive conditions (free to heave and pitch), with the model towed at constant yaw and speed. To get as close as possible to real sailing conditions, experiments were made at both zero and non-zero leeway angles, sweeping a wide range of speed values, with Froude numbers up to 1.2. Both linear and nonlinear wave conditions were studied in order to test the limits of the modeling approach, with wave steepness reaching up to 7% in captive conditions and 3.5% in semi-captive ones. The paper presents the design and methodology of the experiments, as well as comparisons of measured loads and motions with simulations. Loads are shown to be consistent, with a good representation of the sustained non-linearities. Pitch and heave motions depict an encouraging correlation which confirms that the modeling approach is valid.

Empirical Model of Operating Temperature and Pressure Effect towards Pure and Binary O2/ N2 Gas Permeability in Polysulfone Membrane

2018 ◽  
Vol 777 ◽  
pp. 238-244
Author(s):  
Serene Sow Mun Lock ◽  
Kok Keong Lau ◽  
Irene Sow Mei Lock ◽  
Azmi Mohd Shariff ◽  
Yin Fong Yeong ◽  
...  
Keyword(s):  
Empirical Model ◽  
Membrane Separation ◽  
Gas Permeability ◽  
Economic Assessment ◽  
Operating Conditions ◽  
Effect Of Temperature ◽  
Polysulfone Membrane ◽  
Wide Range ◽  
Temperature And Pressure ◽  
Membrane Permeance

Oxygen (O2) enriched air combustion via adaption of polymeric membranes has been proposed to be a feasible alternative to increase combustion proficiency while minimizing the emission of greenhouse gases into the atmosphere. Nonetheless, majority of techno-economic assessment on the O2 enriched combustion evolving membrane separation process are confined to assumption of constant membrane permeance. In reality, it is well known that membrane permeance is highly dependent upon the temperature and pressure to which it is operated. Therefore, in this work, an empirical model, which includes the effect of temperature and pressure to permeance, has been evaluated based on own experimental work using polysulfone membrane. The empirical model has been further validated with published experimental results. It is found that the model is able to provide an excellent characterization of the membrane permeance across a wide range of operating conditions for both pure and binary gas with determination coefficient of minimally 0.99.

scholarly journals Electricity Consumption Estimation of the Polymer Material Injection-Molding Manufacturing Process: Empirical Model and Application

Materials ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 1740 ◽  
Author(s):  
Ana Elduque ◽  
Daniel Elduque ◽  
Carmelo Pina ◽  
Isabel Clavería ◽  
Carlos Javierre
Keyword(s):  
Environmental Impact ◽  
Injection Molding ◽  
Empirical Model ◽  
Electricity Consumption ◽  
Injection Molding Process ◽  
Molding Process ◽  
Polymer Injection ◽  
Wide Range ◽  
Molded Parts ◽  
Polymer Injection Molding

Polymer injection-molding is one of the most used manufacturing processes for the production of plastic products. Its electricity consumption highly influences its cost as well as its environmental impact. Reducing these factors is one of the challenges that material science and production engineering face today. However, there is currently a lack of data regarding electricity consumption values for injection-molding, which leads to significant errors due to the inherent high variability of injection-molding and its configurations. In this paper, an empirical model is proposed to better estimate the electricity consumption and the environmental impact of the injection-molding process. This empirical model was created after measuring the electricity consumption of a wide range of parts. It provides a method to estimate both electricity consumption and environmental impact, taking into account characteristics of both the molded parts and the molding machine. A case study of an induction cooktop housing is presented, showing adequate accuracy of the empirical model and the importance of proper machine selection to reduce cost, electricity consumption, and environmental impact.

scholarly journals An empirical model to predict survival curve and relative biological effectiveness after helium and carbon ion irradiation based solely on the cell survival after photon irradiation

2020 ◽  
Author(s):  
David B. Flint ◽  
Scott J. Bright ◽  
Conor H. McFadden ◽  
Teruaki Konishi ◽  
Daisuke Ohsawa ◽  
...  
Keyword(s):  
Cell Survival ◽  
Cell Lines ◽  
Empirical Model ◽  
Linear Correlation ◽  
Relative Biological Effectiveness ◽  
Ion Irradiation ◽  
Survival Curve ◽  
Carbon Ion ◽  
Wide Range ◽  
Biological Effectiveness

ABSTRACTPurposeTo develop an empirical model to predict radiosensitivity and relative biological effectiveness (RBE) after helium (He) and carbon (C) ion irradiation with or without DNA repair inhibitors.MethodsWe characterized survival in eight human cancer cell lines exposed to 6 MV photons and to He- and C-ions with linear energy transfer (LET) values of 2.2-60.5 keV/μm to verify that the radiosensitivity parameters (D5%, D10%, D20%, D37%, D50% and SF2Gy) correlate linearly between photon and ion radiation with or without DNA-PKcs or ATR inhibitors. Then, we parameterized the LET response of the parameters governing these linear correlations up to LET values of 225 keV/μm using the data in the Particle Irradiation Data Ensemble (PIDE) v3.2 database, creating a model that predicts a cell’s ion radiosensitivity, RBE and ion survival curve for a given LET on the basis of the cell’s photon radiosensitivity. We then trained this model using the PIDE database as a training dataset, and validated it by predicting the radiosensitivity of the cell lines we exposed to He- and C- ions with LET ranging from 2.2-60.5 keV/μm.ResultsRadiosensitivity to ions depended linearly with radiosensitivity of photons in the range of investigated LET values and the slopes and intercepts of these linear relationships within the PIDE database vary exponentially and linearly, respectively. Our model predicted ion radiosensitivity (e.g., D10%) within 5.1–21.3%, RBED10% within 5.0-17.1%, and ion mean inactivation dose within 6.7-25.1% for He- and C-ion LET ranging from 2.2-60.5 keV/μm.ConclusionsRadiosensitivity to He- and C-ions depend linearly with radiosensitivity to photons and can be used to predict ion radiosensitivity, RBE and cell survival curves for clinically relevant LET values from 2.2–60.5 keV/μm, with or without drug treatment.SUMMARYWe present a new empirical model capable of predicting clonogenic cell survival of cell lines exposed to helium and carbon ion beams. Our model is based on an observed linear correlation between radiosensitivity to ions and photons across a wide range of LET values. This linear correlation can be used to predict ion RBE, radiosensitivity, and the cell survival curve for a given LET all based on a cell’s photon survival curve.

scholarly journals Improving the methodology for calculation of energy losses in axial turbine cascades

2021 ◽  
pp. 104-109
Author(s):  
М.Ю. Левенталь ◽  
Ю.М. Погодин ◽  
Ю.Р. Миронов
Keyword(s):  
Standard Deviation ◽  
Turbulence Model ◽  
Empirical Model ◽  
Turbulence Models ◽  
Operating Parameters ◽  
Cfd Analysis ◽  
Sample Standard Deviation ◽  
Rans Model ◽  
Wide Range ◽  
Turbine Cascades

Представлена оценка неопределенности прогнозирования потерь энергии в решетках профилей осевых турбин. В сравнении с экспериментальными данными рассмотрены эмпирическая модель ЦИАМ и метод CFD анализа в рамках RANS модели. Геометрические и режимные параметры решеток профилей варьируются в широком диапазоне. Результаты CFD расчета отличаются существенно в зависимости от модели турбулентности. Наименьшая неопределенность получена для модели рейнольдсовых напряжений RSM. Определено выборочное стандартное относительное отклонение для анализируемой базы данных. Применительно к CFD расчету данное отклонение составило 18,6%, применительно к эмпирической модели ЦИАМ 46,4%. Разработана эмпирическая модель коррекции потерь полученных по результатам CFD анализа с моделью турбулентности RSM. Корректирующая функция включает в себя геометрические и режимные параметры решеток и особенности течения в межлопаточном канале (всего 14 параметров). Использование разработанного подхода позволило снизить неопределённость прогнозирования потерь в 2 раза. В результате работы выборочное стандартное относительное отклонение предсказания потерь для рассматриваемой базы решеток профилей составило 9,3%. Estimation of the uncertainty in predicting profile losses using various models was performed. In comparison with the experimental data, empirical model of CIAM and method of CFD analysis are considered. RANS models are used. The geometric and operating parameters of the analyzed turbine cascades vary over a wide range. Turbulence models strongly influence loss prediction uncertainty. The smallest uncertainty was obtained using the RSM turbulence model. The sample standard deviation for the considered turbine cascades base was determined. The deviation for CFD analysis is 18.6%. For the empirical model of CIAM the deviation is 46.4%. The new empirical model has been created to correct the results of calculating losses according to the RANS model using the RSM turbulence model. The corrective function takes into account the influence of the geometric and operating parameters of the turbine cascades and the features of the airfoil flow (14 parameters in total). The developed approach allows reducing the uncertainty in the estimation of losses according to the RANS model by 2 times. As a result, the sample standard deviation in the prediction of losses is 9.3% for the considered turbine cascades base.

scholarly journals Hybrid Modeling for Simultaneous Prediction of Flux, Rejection Factor and Concentration in Two-Component Crossflow Ultrafiltration

Processes ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 1625
Author(s):  
Maximilian Krippl ◽  
Ignasi Bofarull-Manzano ◽  
Mark Duerkop ◽  
Astrid Dürauer
Keyword(s):  
Film Theory ◽  
Hybrid Models ◽  
Mechanistic Modeling ◽  
Time Resolved ◽  
Process Stage ◽  
Modeling Approach ◽  
Crossflow Ultrafiltration ◽  
Wide Range ◽  
Rejection Factor ◽  
The Impact

Ultrafiltration is a powerful method used in virtually every pharmaceutical bioprocess. Depending on the process stage, the product-to-impurity ratio differs. The impact of impurities on the process depends on various factors. Solely mechanistic models are currently not sufficient to entirely describe these complex interactions. We have established two hybrid models for predicting the flux evolution, the protein rejection factor and two components’ concentration during crossflow ultrafiltration. The hybrid models were compared to the standard mechanistic modeling approach based on the stagnant film theory. The hybrid models accurately predicted the flux and concentration over a wide range of process parameters and product-to-impurity ratios based on a minimum set of training experiments. Incorporating both components into the modeling approach was essential to yielding precise results. The stagnant film model exhibited larger errors and no predictions regarding the impurity could be made, since it is based on the main product only. Further, the developed hybrid models exhibit excellent interpolation properties and enable both multi-step ahead flux predictions as well as time-resolved impurity forecasts, which is considered to be a critical quality attribute in many bioprocesses. Therefore, the developed hybrid models present the basis for next generation bioprocessing when implemented as soft sensors for real-time monitoring of processes.

Modal Emissions Modeling: A Physical Approach

1996 ◽  
Vol 1520 (1) ◽  
pp. 81-88 ◽  
Author(s):  
Matthew Barth ◽  
Feng An ◽  
Joseph Norbeck ◽  
Marc Ross
Keyword(s):  
Intelligent Transportation Systems ◽  
Transportation Systems ◽  
Control Measures ◽  
Mobile Source ◽  
Alternative Fuel Vehicles ◽  
Modeling Approach ◽  
Emissions Modeling ◽  
Vehicle Operation ◽  
Wide Range ◽  
Emission Models

Mobile source emission models currently used by state and federal agencies (e.g., Environmental Protection Agency's MOBILE and California Air Resources Board's EMFAC) are often inadequate for analyzing the emissions impact of various transportation control measures, intelligent transportation systems, alternative fuel vehicles, and more sophisticated inspection/maintenance programs contained in most state air quality management plans. These emission models are based on the assumption that vehicle running exhaust emissions can be represented as integrated values for a specific driving cycle, and then later adjusted by speed correction factors. What is needed in addition to these “regional-type” mobile source models is an emissions model that considers at a more fundamental level the modal operation of a vehicle (i.e., emissions that directly relate to vehicle operating modes such as idle, steady-state cruise, various levels of acceleration/deceleration, and so forth). A new modal-emissions modeling approach that is deterministic and based on analytical functions that describe the physical phenomena associated with vehicle operation and emissions productions is presented. This model relies on highly time-resolved emissions and vehicle operation data that must be collected from a wide range of vehicles of varying emission control technologies. Current emission modeling techniques are discussed and the modeling approach and implementation plan for a new, three-year NCHRP Project entitled “Development of a Modal Emissions Model” are described.

scholarly journals Computational simulation of flocculent sedimentation based on experimental results

2012 ◽  
Vol 65 (6) ◽  
pp. 1007-1013 ◽  
Author(s):  
Mafeni S. Ramatsoma ◽  
Evans M. N. Chirwa
Keyword(s):  
Empirical Model ◽  
Mechanistic Model ◽  
Computational Simulation ◽  
Data Sets ◽  
Random Errors ◽  
Wide Range ◽  
Model Predictions ◽  
Sedimentation Basins ◽  
Semi Empirical ◽  
Better Than

Computerised interpolation algorithms as well as the empirical model for analysing the flocculent settling data were developed. A mechanistic semi-empirical model developed from fundamental physical principles of a falling particle in a viscous fluid was tested against actual flocculation column data. The accuracy of the mechanistic model was evaluated using the sum of the squared errors between the interpolated values (real values) and the model predictions. Its fitting capabilities were compared with Özer's model using nine flocculent data sets of which four were obtained from literature and the rest were actual data from the performed experiments. The developed model consistently simulated the flocculation behaviour of particles in settling columns better than Özer's model in eight of the nine data sets considered. It is recommended that the model's performance be further compared with other models like the Rule based and San's model. The errors due to the use of interpolated values when determining the performance of the empirical models need to be investigated. Furthermore, a three-way rather than two-way interpolation should now be achievable using the interpolation algorithm developed in this study thereby reducing the effects of interpolation bias. The above work opens the way to full automation of design of flocculation sedimentation basins and other gravitational particle separation systems which at present are designed manually and are susceptible to a wide range of human and random errors.

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