scholarly journals Live above- and belowground biomass of a Mozambican evergreen forest: a comparison of estimates based on regression equations and biomass expansion factors

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
Tarquinio Mateus Magalhães
Keyword(s):  
Belowground Biomass ◽  
Evergreen Forest ◽  
Regression Equations ◽  
Biomass Expansion Factors

scholarly journals Allometric Relationships for Estimation of Above-Ground Biomass in Young Turkey Oak (Quercus cerris L.) Stands in Albania

2018 ◽  
Vol 14 (1) ◽  
pp. 65-81 ◽  
Author(s):  
Erion Istrefi ◽  
Elvin Toromani ◽  
Nehat Çollaku
Keyword(s):  
Aboveground Biomass ◽  
National Forest Inventory ◽  
Carbon Accounting ◽  
Leaf Biomass ◽  
Regression Equations ◽  
Allometric Relationships ◽  
Study Objective ◽  
Biomass Expansion Factors ◽  
Model Efficiency ◽  
Dependence Relationship

Abstract The study objective was the determination of allometric relationships to estimate aboveground biomass in young Q. cerris stands growing in various sites in Albania. The equations described here are developed for Q. cerris forest stands managed as coppice. The total aboveground biomass of sampled trees varied from 10.67 to 19.71 kg with a stem diameter at 1.3 m (DBH) from 7.65 to 9.7 cm, and height from 5.26 to 7.6 m. Stem biomass comprised, on average, 69.6 %, while branch biomass was 24.3 %, and leaf biomass,6% on the total aboveground biomass of the sampled oak trees. Total aboveground biomass was predicted with the highest accuracy from linear and non-linear regression equations. Total aboveground biomass and the biomass of tree compartments were predicted with a notable accuracy from DBH where the allometric model efficiency exceeded 93%. Biomass expansion factors (BEFs) showed a stronger dependency on diameter at breast height and a weaker relationship with age. The age-dependence relationship found in our study was closely related to site productivity. The variability in aboveground biomass among sampled sites indicated that local site conditions cause this difference. These new equations for Q.cerris might be applicable in the framework of the Albanian National Forest Inventory for estimation of carbon accounting from forest ecosystems and will contribute to the sustainable management of oak forests.

scholarly journals Visualization and simulation of structural dynamics of natural broad-leaved evergreen forest at Xuan Son national park

2018 ◽  
Vol 40 (4) ◽  
Author(s):  
Nguyen Tien Dung
Keyword(s):  
National Park ◽  
Evergreen Forest ◽  
Permanent Plots ◽  
Regression Equations ◽  
Natural Death ◽  
Text File ◽  
Tree Diameter ◽  
Tree Number ◽  
Visualization And Simulation ◽  
Simulation Scheme

This research was conducted at Xuan Son National Park, the data was collected on 03 permanent plots, the area of each permanent plot is 1 ha. The data collection has been conducted in the period from 2012 to 2018. The trees are classified into diameter categories of 5 cm starting from 10 cm. The structural simulation model consists of two groups of system elements including: state elements (number of trees categorized by diameter size), intermediate elements (tree density, entering and outgoing tree number of diameter categories, number of died trees of different diameter categories, number of regenerating trees). The processes of forest dynamics (regeneration of trees, change of tree number and natural death of diameter categories) were simulated through an simulation scheme in MM&S Software. The interaction is defined through regression equations: Correlation between the number of regenerating trees and the number of existing trees (R-N0), correlation between the number of diameter-category-changing trees and the number of trees at particular diameter category (Ok-Nk), correlation between the number of died trees and the number of trees at particular diameter category (Mk-Nk). The suitable regression equations (that are selected based on the results of statistic analysis) were input into the model in the simulation diagram in MM&S Software. The model in the simulation diagram has been ran, the graph was created from the results of model running to show the tendencies of the change of the tree diameter categories in time and to see the correlation between the changes of the tree diameter categories of the system. The model was exported from the simulation diagram into text file for illustration. 

Computer Assistance in the Clinical Investigation of Pulmonary Function Studies

1973 ◽  
Vol 12 (02) ◽  
pp. 102-107 ◽  
Author(s):  
D. J. Protti ◽  
Nancy Craven ◽  
A. Naimark ◽  
R. M. Cherniack
Keyword(s):  
Information System ◽  
Pulmonary Function ◽  
Additional Data ◽  
Normal Values ◽  
Clinical Investigation ◽  
Regression Equations ◽  
Beneficial Effects ◽  
Computer Assistance ◽  
Manual Methods

A previously described comprehensive respiratory information system (CRIS) has been changed to introduce new spirometric tests which are sensitive to minor abnormalities, revise on the basis of additional data the regression equations which define normal values to various parameters of pulmonary function and refine the system’s interpretation scheme. The beneficial effects of transferring the system from a large IBM 360/65 to a small CDC 1700 are presented. An analysis of the costs of processing routine pulmonary function studies reveals that a 40°/o saving is realized when a computer is used in comparison to the use of the usual manual methods.

Studying the factors of regional insurance market development using the correlation and regression analysis

2020 ◽  
Vol 26 (7) ◽  
pp. 1610-1630
Author(s):  
E.L. Prokop'eva
Keyword(s):  
Regression Analysis ◽  
Federal District ◽  
Insurance Market ◽  
Market Development ◽  
Insurance Markets ◽  
Regression Equations ◽  
Factors Affecting ◽  
Correlation And Regression Analysis ◽  
Country Level ◽  
Inverse Effect

Subject. The article investigates and quantifies factors of insurance markets functioning in Russian regions, and reveals possibilities to manage them. Objectives. The purpose of the study is to substantiate regional factors that determine the specifics of regional insurance market development; to quantify them to increase the efficiency of regional insurance. Methods. The study draws on statistical methods, functional analysis, algorithm development, correlation and regression analysis. Results. I calculated coefficients of pair and multiple correlation with the indicators of insurance markets in the context of the subjects of the Russian Federation, and composed regression equations. Based on the analysis, I determined the algorithm for inverse effect of the insurance market on the economic, social, fiscal and environmental performance of the region, offered appropriate measures aimed at developing the economic potential of the region and its social sphere. Conclusions. The paper considers the case of the Republic of Khakassia, one of depressed subjects in the Siberian Federal District. The developed models can be used for other regions of Russia, given the geographical and economic features of development. The findings may help generate regional strategies for socio-economic development at the country level. The scientific contribution and the novelty of the work consist of systematizing and quantifying the factors affecting the insurance mechanisms of regional markets, and assessing the inverse effect of insurance mechanisms on integrated development of the region.

Investigation of the effect of the constructive and mode parametres of a combined rocker on the power of the drive of the working bodies

2019 ◽  
pp. 82-85
Author(s):  
Pavel Ivanovich Pavlov ◽  
Viktor Vladislavovich Korsak ◽  
Aleksandr Olegovich Vezirov ◽  
Dmitriy Vadimovich Mukhin
Keyword(s):  
Operating Parameters ◽  
Regression Equations ◽  
Drive Power ◽  
Minimum Value ◽  
Working Bodies

The regression equations and graphical dependencies are obtained, which describe the influence of design and operating parameters on the drive power of the working bodies. The value of the design and operating parameters in which the power required to drive the working bodies, will have a minimum value  are experimentally determined.

County-level USA: No Robust Relationship between Geoclimatic Variables and Cognitive Ability

2020 ◽  
Author(s):  
Bryan J Pesta ◽  
John Fuerst ◽  
Emil O. W. Kirkegaard
Keyword(s):  
Cognitive Ability ◽  
Climate Models ◽  
Cold Weather ◽  
Regression Equations ◽  
County Level ◽  
Spatial Lag ◽  
Average Temperature ◽  
Wrong Direction ◽  
Race Ethnicity ◽  
Demographic Covariates

Using a sample of ~3,100 U.S. counties, we tested geoclimatic explanations for why cognitive ability varies across geography. These models posit that geoclimatic factors will strongly predict cognitive ability across geography, even when a variety of common controls appear in the regression equations. Our results generally do not support UV radiation (UVR) based or other geoclimatic models. Specifically, although UVR alone predicted cognitive ability at the U.S. county-level (β = -.33), its validity was markedly reduced in the presence of climatic and demographic covariates (β = -.16), and was reduced even further with a spatial lag (β = -.10). For climate models, average temperature remained a significant predictor in the regression equation containing a spatial lag (β = .35). However, the effect was in the wrong direction relative to typical cold weather hypotheses. Moreover, when we ran the analyses separately by race/ethnicity, no consistent pattern appeared in the models containing the spatial lag. Analyses of gap sizes across counties were also generally inconsistent with predictions from the UVR model. Instead, results seemed to provide support for compositional models.

Multilayer Polymeric Nano composite Membrane for Oxygen Separation

2019 ◽  
Vol 1 (2) ◽  
pp. 1-11
Author(s):  
Gobi Nallathambi ◽  
Hazel Dhinakaran
Keyword(s):  
Polymer Concentration ◽  
Sio2 Nanoparticles ◽  
Air Separation ◽  
Regression Equations ◽  
Permeate Flux ◽  
Nano Composite ◽  
Box Behnken Design ◽  
Oxygen Selectivity ◽  
Multilayer Membrane ◽  
Spun Fiber

Air separation is a process of separating primary components from the atmospheric air. Development of membrane technologies plays a key role in air separation. Multi-layer polymeric nanocomposite membranes have been developed by a novel technique using Polyacrylonitrile (PAN) and cellulose acetate (CA) along with nano silica particles (SiO2) to obtain a higher oxygen selectivity and permeability. For the construction of the multilayer membrane, the Box-Behnken design has been used by employing three independent variables namely PAN Electro spinning time, the SiO2 percentage in the PAN polymer and CA/PEG polymer concentration. The developed membranes have been characterized for its surface morphology and physical properties. Along with the analysis of compound desirability, the results were also subject to statistical analysis in order to form regression equations. The electro spun fiber diameter increases along with the concentration of SiO2 nanoparticles and the range is from 50 nm to 400 nm. Moreover, the maximum pore size on the surface of the membrane lies between 200 to 400 nm whereas the maximum percentage of oxygen purity obtained is 48 with the permeate flux of 5.45 cm3/cm2/min.

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