A biphasic model of limb venous compliance: a comparison with linear and exponential models

2003 ◽  
Vol 95 (3) ◽  
pp. 1207-1215 ◽  
Author(s):  
Marcelo R. Risk ◽  
Vasilios Lirofonis ◽  
Ricardo L. Armentano ◽  
Roy Freeman
Keyword(s):  
Low Pressure ◽  
Coefficient Of Determination ◽  
Linear Modeling ◽  
Venous Compliance ◽  
Exponential Models ◽  
Biphasic Model ◽  
Venous Circulation ◽  
Compliance Curve ◽  
The Mean ◽  
Low Pressures

Compliance is not linear within the physiological range of pressures, and linear modeling may not describe venous physiology adequately. Forearm and calf venous compliance were assessed in nine subjects. Venous compliance was modeled by using a biphasic model with high- and low-pressure linear phases separated by a breakpoint. This model was compared with a linear model and several exponential models. The biphasic, linear, and two-parameter exponential models best represented the data. The mean coefficient of determination for the biphasic model was greater than for the linear and exponential models in the calf (biphasic 0.94 ± 0.04, exponential 0.81 ± 0.16, P = not significant; and linear 0.54 ± 0.05, P < 0.05) and forearm (biphasic 0.83 ± 0.17, exponential 0.79 ± 0.15, P = not significant; and linear 0.51 ± 0.06, P < 0.05). The breakpoint pressure in the biphasic model was higher in the calf than the forearm, 34.4 ± 3.9 vs. 29.1 ± 4.5 mmHg, P < 0.05. A biphasic model can describe limb venous compliance and delineate differences in venous physiology at high and low pressures. The steep low-pressure phase of the compliance curve extends to higher pressures in the calf than in the forearm, thereby enlarging the range of pressures over which hemodynamic regulation by the calf venous circulation occurs.

scholarly journals Modeling of Lake Malombe Annual Fish Landings and Catch per Unit Effort (CPUE)

Forecasting ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 39-55
Author(s):  
Rodgers Makwinja ◽  
Seyoum Mengistou ◽  
Emmanuel Kaunda ◽  
Tena Alemiew ◽  
Titus Bandulo Phiri ◽  
...  
Keyword(s):  
Time Series ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Series Data ◽  
Efficiency Coefficient ◽  
Arima Models ◽  
Catch Per Unit Effort ◽  
Annual Fish ◽  
Unit Effort ◽  
The Mean

Forecasting, using time series data, has become the most relevant and effective tool for fisheries stock assessment. Autoregressive integrated moving average (ARIMA) modeling has been commonly used to predict the general trend for fish landings with increased reliability and precision. In this paper, ARIMA models were applied to predict Lake Malombe annual fish landings and catch per unit effort (CPUE). The annual fish landings and CPUE trends were first observed and both were non-stationary. The first-order differencing was applied to transform the non-stationary data into stationary. Autocorrelation functions (AC), partial autocorrelation function (PAC), Akaike information criterion (AIC), Bayesian information criterion (BIC), square root of the mean square error (RMSE), the mean absolute error (MAE), percentage standard error of prediction (SEP), average relative variance (ARV), Gaussian maximum likelihood estimation (GMLE) algorithm, efficiency coefficient (E2), coefficient of determination (R2), and persistent index (PI) were estimated, which led to the identification and construction of ARIMA models, suitable in explaining the time series and forecasting. According to the measures of forecasting accuracy, the best forecasting models for fish landings and CPUE were ARIMA (0,1,1) and ARIMA (0,1,0). These models had the lowest values AIC, BIC, RMSE, MAE, SEP, ARV. The models further displayed the highest values of GMLE, PI, R2, and E2. The “auto. arima ()” command in R version 3.6.3 further displayed ARIMA (0,1,1) and ARIMA (0,1,0) as the best. The selected models satisfactorily forecasted the fish landings of 2725.243 metric tons and CPUE of 0.097 kg/h by 2024.

scholarly journals IndoorPlant: A Model for Intelligent Services in Indoor Agriculture Based on Context Histories

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1631
Author(s):  
Bruno Guilherme Martini ◽  
Gilson Augusto Helfer ◽  
Jorge Luis Victória Barbosa ◽  
Regina Célia Espinosa Modolo ◽  
Marcio Rosa da Silva ◽  
...  
Keyword(s):  
Technology Acceptance ◽  
Mean Square Error ◽  
Ease Of Use ◽  
Coefficient Of Determination ◽  
Square Root ◽  
Mean Square ◽  
Use Context ◽  
The Mean ◽  
Acceptance Model ◽  
The Internet Of Things

The application of ubiquitous computing has increased in recent years, especially due to the development of technologies such as mobile computing, more accurate sensors, and specific protocols for the Internet of Things (IoT). One of the trends in this area of research is the use of context awareness. In agriculture, the context involves the environment, for example, the conditions found inside a greenhouse. Recently, a series of studies have proposed the use of sensors to monitor production and/or the use of cameras to obtain information about cultivation, providing data, reminders, and alerts to farmers. This article proposes a computational model for indoor agriculture called IndoorPlant. The model uses the analysis of context histories to provide intelligent generic services, such as predicting productivity, indicating problems that cultivation may suffer, and giving suggestions for improvements in greenhouse parameters. IndoorPlant was tested in three scenarios of the daily life of farmers with hydroponic production data that were obtained during seven months of cultivation of radicchio, lettuce, and arugula. Finally, the article presents the results obtained through intelligent services that use context histories. The scenarios used services to recommend improvements in cultivation, profiles and, finally, prediction of the cultivation time of radicchio, lettuce, and arugula using the partial least squares (PLS) regression technique. The prediction results were relevant since the following values were obtained: 0.96 (R2, coefficient of determination), 1.06 (RMSEC, square root of the mean square error of calibration), and 1.94 (RMSECV, square root of the mean square error of cross validation) for radicchio; 0.95 (R2), 1.37 (RMSEC), and 3.31 (RMSECV) for lettuce; 0.93 (R2), 1.10 (RMSEC), and 1.89 (RMSECV) for arugula. Eight farmers with different functions on the farm filled out a survey based on the technology acceptance model (TAM). The results showed 92% acceptance regarding utility and 98% acceptance for ease of use.

Experiments on the flow of heat in liquid helium below 0.7 °K

1958 ◽  
Vol 246 (1246) ◽  
pp. 390-405 ◽  
Keyword(s):  
Thermal Conductivity ◽  
Liquid Helium ◽  
Free Path ◽  
Empirical Relation ◽  
Mean Free Path ◽  
Series Of Experiments ◽  
The Mean ◽  
Set Up ◽  
Low Pressures ◽  
Measured Thermal Conductivity

A series of experiments has been performed to study the steady flow of heat in liquid helium in tubes of diameter 0.05 to 1.0 cm at temperatures between 0.25 and 0.7 °K. The results are interpreted in terms of the flow of a gas of phonons, in which the mean free path λ varies with temperature, and may be either greater or less than the diameter of the tube d . When λ ≫ d the flow is limited by the scattering of the phonons at the walls, and the effect of the surface has been studied, but when λ ≪ d viscous flow is set up in which the measured thermal conductivity is increased above that for wall scattering. This behaviour is very similar to that observed in the flow of gases at low pressures, and by applying kinetic theory to the problem it can be shown that the mean free path of the phonons characterizing viscosity can be expressed by the empirical relation λ = 3.8 x 10 -3 T -4.3 cm. This result is inconsistent with the temperature dependence of λ as T -9 predicted theoretically by Landau & Khalatnikov (1949).

Highly Loaded Low-Pressure Turbine: Design, Numerical, and Experimental Analysis

2010 ◽  
Author(s):  
J. T. Schmitz ◽  
S. C. Morris ◽  
R. Ma ◽  
T. C. Corke ◽  
J. P. Clark ◽  
...  
Keyword(s):  
High Speed ◽  
Numerical Solutions ◽  
Pressure Ratio ◽  
Low Pressure ◽  
Boundary Layer Transition ◽  
Layer Transition ◽  
Free Stream Turbulence ◽  
Low Pressure Turbine ◽  
The Mean ◽  
Highly Loaded

The performance and detailed flow physics of a highly loaded, transonic, low-pressure turbine stage has been investigated numerically and experimentally. The mean rotor Zweifel coefficient was 1.35, with dh/U2 = 2.8, and a total pressure ratio of 1.75. The aerodynamic design was based on recent developments in boundary layer transition modeling. Steady and unsteady numerical solutions were used to design the blade geometry as well as to predict the design and off-design performance. Measurements were acquired in a recently developed, high-speed, rotating turbine facility. The nozzle-vane only and full stage characteristics were measured with varied mass flow, Reynolds number, and free-stream turbulence. The efficiency calculated from torque at the design speed and pressure ratio of the turbine was found to be 90.6%. This compared favorably to the mean line target value of 90.5%. This paper will describe the measurements and numerical solutions in detail for both design and off-design conditions.

Large Cryogenic Storage of Hydrogen in Carbon Nanotubes at Low Pressures

2001 ◽  
Vol 706 ◽  
Author(s):  
B. K. Pradhan ◽  
A. Harutyunyan ◽  
D. Stojkovic ◽  
P. Zhang ◽  
M. W. Cole ◽  
...  
Keyword(s):  
Carbon Nanotubes ◽  
Zero Point ◽  
Isosteric Heat ◽  
Low Pressure ◽  
Quantum Mechanical ◽  
Strong Adsorption ◽  
Point Motion ◽  
Post Synthesis ◽  
Walled Carbon Nanotubes ◽  
Low Pressures

AbstractWe report (6 wt %) storage of H2 at T=77 K in processed bundles of single-walled carbon nanotubes at P=2 atmospheres. The hydrogen storage isotherms are completely reversible. D2 isotherms confirm this anomalous low-pressure adsorption and further reveal the effects of quantum mechanical zero point motion. We propose that our post-synthesis treatment of the sample not only improves access for hydrogen to the central pores within individual nanotubes, but also may create a roughened tube surface with an enhanced binding energy for hydrogen. Such an enhancement is needed to understand the strong adsorption at low pressure. We obtain an experimental isosteric heat qst=125 ± 5 meV for processed SWNT materials.

scholarly journals Kinetics of drying of basil leaves (Ocimum basilicum L.) in the infrared

2012 ◽  
Vol 16 (12) ◽  
pp. 1346-1352 ◽  
Author(s):  
Renata C. dos Reis ◽  
Ivano A. Devilla ◽  
Diego P. R. Ascheri ◽  
Ana C. O. Servulo ◽  
Athina B. M. Souza
Keyword(s):  
Experimental Data ◽  
Ocimum Basilicum ◽  
Coefficient Of Determination ◽  
Chisquare Test ◽  
The Mean ◽  
Drying Curves ◽  
The One ◽  
Increasing Temperature ◽  
Air Circulation ◽  
Kinetics Of

The objective of this paper was to model the drying curves of the leaves of basil (Ocimum basilicum L.) in the infrared at temperatures of 50, 60, 70 and 80 ºC and to evaluate the influence of drying temperature on the color of dried leaves. Drying was conducted in infrared dryer with temperature and greenhouse air circulation. Experimental data were fitted to eight mathematical models. The magnitude of the coefficient of determination (R²), the mean relative error (P), the estimated mean error (SE) and chisquare test (χ2) were used to verify the degree of fitness of the models. From the study it was concluded that: a) the behavior of the drying curves of basil leaves was similar to most agricultural products, the drying times in the infrared were less than the drying times in an oven with air circulation, b) the mathematical drying model proposed by Midilli et al. (2002) was the one which best adjusted to the experimental data, c) the diffusion coefficient ranged from 9.10 x 10-12 to 2.92 x 10-11 m² s-1 and d) the color of the samples was highly influenced by drying, becoming darker due to loss of chlorophyll with increasing temperature.

scholarly journals Reconsidering the ‘Decline’ of Dental Student Empathy within the Course in Latin America

2017 ◽  
Vol 30 (11) ◽  
pp. 775 ◽  
Author(s):  
Víctor Patricio Díaz-Narváez ◽  
Ana María Erazo Coronado ◽  
Jorge Luis Bilbao ◽  
Farith González ◽  
Mariela Padilla ◽  
...  
Keyword(s):  
Latin America ◽  
Dental Students ◽  
Coefficient Of Determination ◽  
Dental Student ◽  
Cross Sectional ◽  
The Mean ◽  
Physician Empathy ◽  
Dental Schools ◽  
Academic Year ◽  
Made In

Introduction: The controversy over the presence of empathic decline within the course in students of medicine, dentistry and health sciences in general, has not fully been studied. This controversy could be partially solved if massive studies of empathy levels are made in similar cultural, social and economic contexts.Material and Methods: Empathy levels within the course were studied in eighteen dental schools from six countries in Latin America (2013). The mean of the empathy levels were used to study the behavior between first and fifth academic years. The values of empathy levels within the course were observed by applying the Jefferson Scale of Physician Empathy, the Spanish version. All these studies were cross-sectional. The value of means observed, were subjected to regression studies and further adjustment curves were obtained and the coefficient of determination were calculated.Results: Six different models of behavior were observed, which found that five of them suffer empathic decline within the course, but with different final results: in some the decline persists until the fifth academic year and in others, this decline ‘recovers’ persistently until the fifth academic year. The sixth model is characterized by a constant and persistent increase of levels of empathy within the course until the last academic year.Discussion: There are six different models for the behavior of means of levels of empathy within the course evaluated by a common methodology in eighteen dental schools from six countries of Latin America. These findings support the existence of variability of empathic response and a comprehensive approach is needed to find the causes that give rise to this variability.Conclusion: In dental students of Latin America, there is variability in the behavior of the distribution in means between the academic years of the dentistry schools examined in this study.

scholarly journals Neural Model for the Prediction of Volume Losses in the Aging Process of Rums

2020 ◽  
Vol 29 (54) ◽  
pp. e10514
Author(s):  
Beatriz García-Castellanos ◽  
Osney Pérez-Ones ◽  
Lourdes Zumalacárregui-de-Cárdenas ◽  
Idania Blanco-Carvajal ◽  
Luis Eduardo López-de-la-Maza
Keyword(s):  
Aging Time ◽  
Aging Process ◽  
Neural Model ◽  
Correlation Factor ◽  
Coefficient Of Determination ◽  
Training Algorithms ◽  
The Neural Network ◽  
Aging Conditions ◽  
The Mean ◽  
Input Variables

The rum aging process shows volume losses, called wastage. The numerical operation variables: product, boardwalk, horizontal and vertical positions, date, volume, alcoholic degree, temperature, humidity and aging time, recorded in databases, contain valuable information to study the process. MATLAB 2017 software was used to estimate volume losses. In the modeling of the rum aging process, the multilayer perceptron neuronal network with one and two hidden layers was used, varying the number of neurons in these between 4 and 10. The Levenberg-Marquadt (LM) and Bayesian training algorithms were compared (Bay) The increase in 6 consecutive iterations of the validation error and 1,000 as the maximum number of training cycles were the criteria used to stop the training. The input variables to the network were: numerical month, volume, temperature, humidity, initial alcoholic degree and aging time, while the output variable was wastage. 546 pairs of input/output data were processed. The statistical Friedman and Wilcoxon tests were performed to select the best neural architecture according to the mean square error (MSE) criteria. The selected topology has a 6-4-4-1 structure, with an MSE of 2.1∙10-3 and a correlation factor (R) with experimental data of 0.9898. The neural network obtained was used to simulate thirteen initial aging conditions that were not used for training and validation, detecting a coefficient of determination (R2) of 0.9961.

scholarly journals Alometric Model for Estimation of Leaf Area of Garcinia brasiliensis Mart. Through Non-destructive Method

2019 ◽  
Vol 11 (10) ◽  
pp. 154
Author(s):  
Vinicius de Souza Oliveira ◽  
Cássio Francisco Moreira de Carvalho ◽  
Juliany Morosini França ◽  
Flávia Barreto Pinto ◽  
Karina Tiemi Hassuda dos Santos ◽  
...  
Keyword(s):  
Leaf Area ◽  
Linear Equations ◽  
Absolute Error ◽  
Coefficient Of Determination ◽  
Maximum Width ◽  
Linear Dimensions ◽  
Length Width ◽  
Independent Variable ◽  
The Mean ◽  
Non Destructive

The objective of the present study was to test and establish mathematical models to estimate the leaf area of Garcinia brasiliensis Mart. through linear dimensions of the length, width and product of both measurements. In this way, 500 leaves of trees with age between 4 and 6 years were collected from all the cardinal points of the plant in the municipality of S&atilde;o Mateus, North of the State of Esp&iacute;rito Santo, Brazil. The length (L) along the main midrib, the maximum width (W), the product of the length with the width (LW) and the observed leaf area (OLA) were obtained for all leaves. From these measurements were adjusted linear equations of first degree, quadratic and power, in which OLA was used as dependent variable as function of L, W and LW as independent variable. For the validation, the values of L, W and LW of 100 random leaves were substituted in the equations generated in the modeling, thus obtaining the estimated leaf area (ELA). The values of the means of ELA and OLA were tested by Student&rsquo;s t test 5% of probability. The mean absolute error (MAE), root mean square error (RMSE) and Willmott&rsquo;s index d for all proposed models were also determined. The choice of the best model was based on the non significant values in the comparison of the means of ELA and OLA, values of MAE and RMSE closer to zero and value of the index d and coefficient of determination (R2) close to unity. The equation that best estimates leaf area of Garcinia brasiliensis Mart. in a way non-destructive is the power model represented by por ELA = 0.7470(LW)0.9842 and R2 = 0.9949.

scholarly journals Central and Peripheral Obesity on Severity Knee Osteoarthritis

2021 ◽  
Vol 1 (3) ◽  
pp. 64
Author(s):  
Refangga Lova Nusantara Efendi ◽  
Zulfachmi Wahab ◽  
M. Riza Setiawan
Keyword(s):  
Knee Osteoarthritis ◽  
Sampling Method ◽  
Simple Random Sampling ◽  
Statistical Test ◽  
Coefficient Of Determination ◽  
Mean Deviation ◽  
Cross Sectional ◽  
Linear Pattern ◽  
Different Types ◽  
The Mean

Background: Obesity can affect severity of knee osteoarthritis sufferers. Several studies have examined relationship between obesity and osteoarthritis, but no one has examined the different types of obesity on osteoarthritis, therefore, researchers wanted to know differences of central and peripheral obesity on severity osteoarthritis.Methods: A retrospective studi, with cross-sectional, simple random sampling method, conducted between 1 August 2014 and 30 September 2014 in Semarang City. Samples people > 50 years old. Data were analyzed by rank Spearman and Anova correlation.Results: In this study, 45.7% (n = 32) reported severe osteoarthritis. The results of the statistical test obtained p1 = 0,000 (reject Ho). The correlation coefficient (r) is 0.857 (strong), and the linear pattern is positive. The coefficient of determination (r2) is obtained (0.857) 2 = 0.73 = 73%. And 37.1% (N = 26) reported being obese. p2 = 0.043 (reject Ho). The mean deviation (MD) was 0.048 (not significant) between central obesity and peripheral obesity.Conclusion: Obesity affects severity of knee osteoarthritis. The greater body mass index, greater severity of knee osteoarthritis. 73% of severity of knee osteoarthritis is influenced by obesity, but there is no significant effect between central and peripheral obesity on the occurrence of knee osteoarthritis.

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