scholarly journals Modeling the Soil Response to Rainstorms after Wildfire and Prescribed Fire in Mediterranean Forests

Climate ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 150
Author(s):  
Manuel Esteban Lucas-Borja ◽  
Giuseppe Bombino ◽  
Bruno Gianmarco Carrà ◽  
Daniela D’Agostino ◽  
Pietro Denisi ◽  
...  
Keyword(s):  
Linear Regression ◽  
Prescribed Fire ◽  
Linear Equations ◽  
Model Performance ◽  
Fire Risk ◽  
Mediterranean Forests ◽  
Regression Equations ◽  
Soil Response ◽  
Runoff Volume ◽  
Scs Cn

The use of the Soil Conservation Service-curve number (SCS-CN) model for runoff predictions after rainstorms in fire-affected forests in the Mediterranean climate is quite scarce and limited to the watershed scale. To validate the applicability of this model in this environment, this study has evaluated the runoff prediction capacity of the SCS-CN model after storms at the plot scale in two pine forests of Central-Eastern Spain, affected by wildfire (with or without straw mulching) or prescribed fire and in unburned soils. The model performance has been compared to the predictions of linear regression equations between rainfall depth and runoff volume. The runoff volume was simulated with reliability by the linear regression only for the unburned soil (coefficient of Nash and Sutcliffe E = 0.73–0.89). Conversely, the SCS-CN model was more accurate for burned soils (E = 0.81–0.97), also when mulching was applied (E = 0.96). The performance of this model was very satisfactory in predicting the maximum runoff. Very low values of CNs and initial abstraction were required to predict the particular hydrology of the experimental areas. Moreover, the post-fire hydrological “window-of-disturbance” could be reproduced only by increasing the CN for the storms immediately after the wildfire. This study indicates that, in Mediterranean forests subject to the fire risk, the simple linear equations are feasible to predict runoff after low-intensity storms, while the SCS-CN model is advisable when runoff predictions are needed to control the flooding risk.

scholarly journals Modelling the Event-Based Hydrological Response of Mediterranean Forests to Prescribed Fire and Soil Mulching with Fern Using the Curve Number, Horton and USLE-Family (Universal Soil Loss Equation) Models

Land ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1166
Author(s):  
Bruno Gianmarco Carra ◽  
Giuseppe Bombino ◽  
Manuel Esteban Lucas-Borja ◽  
Pietro Denisi ◽  
Pedro Antonio Plaza-Álvarez ◽  
...  
Keyword(s):  
Prescribed Fire ◽  
Soil Loss ◽  
Overland Flow ◽  
Curve Number ◽  
Soil Conditions ◽  
Mediterranean Forests ◽  
Hydrological Response ◽  
Infiltration Excess ◽  
Runoff And Soil Loss ◽  
Scs Cn

The SCS-CN, Horton, and USLE-family models are widely used to predict and control runoff and erosion in forest ecosystems. However, in the literature there is no evidence of their use in Mediterranean forests subjected to prescribed fire and soil mulching. To fill this gap, this study evaluates the prediction capability for runoff and soil loss of the SCS-CN, Horton, MUSLE, and USLE-M models in three forests (pine, chestnut, and oak) in Southern Italy. The investigation was carried out at plot and event scales throughout one year, after a prescribed fire and post-fire soil mulching with fern. The SCS-CN and USLE-M models were accurate in predicting runoff volume and soil loss, respectively. In contrast, poor predictions of the modelled hydrological variables were provided by the models in unburned plots, and by the Horton and MUSLE models for all soil conditions. This inaccuracy may have been due to the fact that the runoff and erosion generation mechanisms were saturation-excess and rainsplash, while the Horton and MUSLE models better simulate infiltration-excess and overland flow processes, respectively. For the SCS-CN and USLE-M models, calibration was needed to obtain accurate predictions of surface runoff and soil loss; furthermore, different CNs and C factors must be input throughout the year to simulate the variability of the hydrological response of soil after fire. After calibration, two sets of CNs and C-factor values were suggested for applications of the SCS-CN and USLE-M models, after prescribed fire and fern mulching in Mediterranean forests. Once validated in a wider range of environmental contexts, these models may support land managers in controlling the hydrology of Mediterranean forests that are prone to wildfire risks.

SINGLE-FACTOR LINEAR REGRESSION MODEL OF HODGKIN’S LYMPHOMA IN ADOLESCENTS

2017 ◽  
Vol 63 (2) ◽  
pp. 320-325
Author(s):  
Svetlana Kuleva ◽  
Svetlana Ivanova ◽  
Andrey Karitskiy ◽  
Darya Zvyagintseva
Keyword(s):  
Radiation Therapy ◽  
Linear Regression ◽  
Predictive Factors ◽  
Hodgkin’S Lymphoma ◽  
Risk Group ◽  
Hodgkin's Lymphoma ◽  
Regression Equations ◽  
Single Factor ◽  
Number Of Cycles ◽  
Selection Of

With the use of regression and dispersion analyzes conducted in this study it was possible to identify predictive factors that significantly worsen the prognosis of Hodgkin’s lymphoma in adolescents however constructed regression equations did not pass the quality assessment of the models, which did not allow them to be used for the construction of point and interval predictions. In a cohort of patients enrolled in the study a risk-adapted treatment program based on the risk group for stratification was conducted. Negative aspects of the results of our study could be related to the already selected volume of the program for these patients. In turn our analysis proves the validity of the selection of therapeutic loads (a number of cycles of polychemotherapy, doses of radiation therapy) depending on the risk group, into which the adolescent is stratified.

scholarly journals Using the Landsat Burned Area Products to Derive Fire History Relevant for Fire Management and Conservation in the State of Florida, Southeastern USA

Fire ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 26
Author(s):  
Casey Teske ◽  
Melanie K. Vanderhoof ◽  
Todd J. Hawbaker ◽  
Joe Noble ◽  
John Kevin Hiers
Keyword(s):  
Prescribed Fire ◽  
Spatial Data ◽  
Fire History ◽  
Fire Management ◽  
Fire Behavior ◽  
Fire Risk ◽  
Behavior Modeling ◽  
Burned Area ◽  
Burned Areas ◽  
Burn Probability

Development of comprehensive spatially explicit fire occurrence data remains one of the most critical needs for fire managers globally, and especially for conservation across the southeastern United States. Not only are many endangered species and ecosystems in that region reliant on frequent fire, but fire risk analysis, prescribed fire planning, and fire behavior modeling are sensitive to fire history due to the long growing season and high vegetation productivity. Spatial data that map burned areas over time provide critical information for evaluating management successes. However, existing fire data have undocumented shortcomings that limit their use when detailing the effectiveness of fire management at state and regional scales. Here, we assessed information in existing fire datasets for Florida and the Landsat Burned Area products based on input from the fire management community. We considered the potential of different datasets to track the spatial extents of fires and derive fire history metrics (e.g., time since last burn, fire frequency, and seasonality). We found that burned areas generated by applying a 90% threshold to the Landsat burn probability product matched patterns recorded and observed by fire managers at three pilot areas. We then created fire history metrics for the entire state from the modified Landsat Burned Area product. Finally, to show their potential application for conservation management, we compared fire history metrics across ownerships for natural pinelands, where prescribed fire is frequently applied. Implications of this effort include increased awareness around conservation and fire management planning efforts and an extension of derivative products regionally or globally.

Methodology of Estimation of Fire Separation Distances between Construction Facilities by Calculation

2020 ◽  
Vol 1006 ◽  
pp. 93-100
Author(s):  
Vadym Nizhnyk ◽  
Yurii Feshchuk ◽  
Volodymyr Borovykov
Keyword(s):  
Mathematical Model ◽  
Heat Flux ◽  
Linear Regression ◽  
Ignition Temperature ◽  
Oil Products ◽  
Regression Equations ◽  
Fire Load ◽  
Literary Sources ◽  
Tabular Method

Based on analysis of appropriate literary sources we established that estimation of fire separation distances was based of two criteria: heat flux and temperature. We proposed to use “ignition temperature of materials” as principal criterion when determining fire separation distances between adjacent construction facilities. Based on the results derived while performing complete factorial we created mathematical model to describe trend of changing fire separation distances depending on caloric power of fire load (Q), openings factor of the external enclosing structures (k) and duration of irradiation (t); moreover, its adequacy was confirmed. Based on linear regression equations we substantiated calculation and tabular method for the determination of fire separation distances for a facility being irradiated which contains combustible or otherwise non-combustible façade and a facility where liquid oil products turn. We developed and proposed general methodology for estimation of fire separation distances between construction facilities by calculation.

scholarly journals PENGARUH TINGKAT PENDIDIKAN, MOTIVASI, DAN KOMPENSASI TERHADAP KINERJA PEGAWAI DI BRI CABANG SEMARANG AHMAD YANI

2019 ◽  
Vol 11 (02) ◽  
pp. 31-47
Author(s):  
Sopi Sopi ◽  
Zumrotun Nafi'ah
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Industrial Revolution ◽  
Employee Performance ◽  
Science And Technology ◽  
Regression Equations ◽  
Linear Regression Equation ◽  
Improve Performance ◽  
Independent Variables ◽  
Life Education

Education, motivation and compensation are important things that can improve performance. This study aims to explain whether there is an influence of education, motivation and compensation on employee performance. So that through the results of this study it is expected to be a reference for leaders in managing the organization. In this study there are three independent variables namely education, motivation and compensation and one dependent variable is employee performance. At present it is in the era of industrial revolution 4.0, which is marked by; big data / giant data, internet of think, labor knowledge, and long life education. Since the beginning of the life of mankind to an infinite period, it is largely determined by the mastery of science and technology. Science and technology can not be separated from the progress of education level. Education is the base of all changes both individually, as well as countries. Employee performance is determined by the education that is owned, as high as education, the higher the performance and vice versa. The population in this study are BRI CAB employees, SEMARANG A-YANI, 60 people and all of them are sampled. The results of the analysis using SPSS 23 program statistical tools obtained multiple linear regression equation Y = 0.505 X1 + 0.175 X2 + 0.408 X3 The results of multiple linear regression equations show that there is a positive and significant influence between education on employee performance at BRI CAB. A YANI SEMARANG (t count test 6.314> t table 0.05), motivation towards employee performance at BRI CAB. A YANI SEMARANG (tcount 2,160> t table 0,05), and compensation for employee performance at BRI CAB. A YANI SEMARANG (t test 5.108> ttable 0.05). While together (simultaneously) the influence of education, motivation and compensation has an effect on and significant on the performance of employees at BRI CAB. A YANI SEMARANG (count = 44,692> ftabel = 0.05). The influence of the two research variables is very strong with a correlation value of 69.0% for employee performance at BRI CAB. A YANI SEMARANG is influenced by the motivation and compensation education of the remaining 31.0% of the employees' performance at BRI CAB. A YANI SEMARANG is influenced by other variables that affect employee performance.

scholarly journals PENGARUH LINGKUNGAN KERJA DAN KOMPENSASI TERHADAP KINERJA PEGAWAI PADA DINAS PENDIDIKAN, PEMUDA DAN OLAHRAGA KABUPATEN MAJENE

2020 ◽  
Vol 9 (2) ◽  
pp. 121
Author(s):  
Sri Indira Hartawati ◽  
Meutia A Sahur
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Work Environment ◽  
Employee Performance ◽  
Linear Regression Analysis ◽  
Youth Sports ◽  
Multiple Linear Regression Analysis ◽  
Department Of Education ◽  
Test Reliability ◽  
Regression Equations

<p><em>This research was conducted at the Department of Education, Youth and Sports of Majene Regency with the title The Effect of Work Environment and Compensation on Employee Performance. The formulation of the problem used by researchers is How the influence of the Work Environment on Employee Performance at the Education and Youth Sports Office of Majene Regency, How the influence of Compensation on Employee Performance at the Education and Youth Sports Office of Majene Regency, which variables have more influence on Employee Performance at the Education and Youth Office Majene District Sports. The research method, namely the population and sample used in this study were all employees of the Department of Education and Youth Sports of Majene Regency, which amounted to about 50 people, while the analysis method used the Validity Test, Reliability Test, Multiple Linear Regression Analysis This analysis was used to determine how much influence it had. independent variables, namely: compensation (X1), and work environment (X2) on the dependent variable, namely Employee Performance (Y). Multiple linear regression equations, Partial Significance Test (t test) and Simultaneous Test (F test). The results obtained from this study are the work environment has a significant effect on employee performance at the Department of Education and Youth Sports of Majene Regency, compensation has an effect on employee performance at the Education and Youth Sports Office of Majene Regency. and the work environment has a more dominant influence on employee performance at the Department of Education and Youth Sport, Majene Regency.</em></p><p><strong><em>Keywords: </em></strong><em>Work Environment, Compensation, Employee Performance</em></p>

scholarly journals The Laba Per Saham, Rasio Hutang, Pengembalian Atas Aset dan Suku Bunga Terhadap Nilai Perusahaan Wholesale

2021 ◽  
Vol 4 (1) ◽  
pp. 648-661
Author(s):  
Elise Elise ◽  
Mariska Sisilia ◽  
Rina Yustito S ◽  
Cherria Halim
Keyword(s):  
Linear Regression ◽  
Interest Rates ◽  
Firm Value ◽  
Research Method ◽  
Sampling Method ◽  
Regression Equations ◽  
Debt Ratio ◽  
Analysis Model ◽  
Return On Assets ◽  
Earnings Per Share

This study aims to determine the effect of earnings per share, debt ratio, return on assets and interest rates on firm value in whosale companies listed on the IDX in 2014-2018. This research was conducted using an associative research method and a quantitative approach. 17 companies as samples were taken using purposive sampling method. The analysis model uses multiple linear regression equations. The result of the research is that earning per share has no effect on firm value at Whosale companies listed on the IDX. The debt ratio does not affect the firm value of Whosale companies listed on the IDX. Returns on assets have an effect on firm value at Whosale companies listed on the IDX. Interest rates do not affect the firm value of Whosale companies listed on the IDX. Earnings per share, debt ratio, return on assets and interest rates have an effect on firm value at Whosale companies listed on the IDX.

scholarly journals Pengaruh Pelatihan Dan Pengembangan Terhadap Kinerja Karyawan Departemen Produksi Pada PT. Kaltim Diamond Coal Site Loa Gagak Kutai Kartanegara

2021 ◽  
Vol 9 (2) ◽  
pp. 170
Author(s):  
Wijayanti Wijayanti Wijayanti
Keyword(s):  
Data Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Employee Performance ◽  
Training And Development ◽  
Test Reliability ◽  
Regression Equations ◽  
Production Department ◽  
Data Analysis Technique ◽  
Analysis Technique

The results of the analysis using multiple linear regression equations show the following regression equation: Y = 5.622 + 0.488 (X1) + 0.329 (X2). Data collection techniques are based on the source, including primary data through observation, interviews, questionnaires or questionnaires, and include documentation. Secondary data, among others, by searching for literature in the form of previous research journals, and textbooks that are related to the variables to be studied. The data analysis technique used the validity test, reliability test, and classical assumption test. As for the data analysis technique method using Multiple Linear Regression, Correlation Analysis, Analysis of Determination (R2), hypothesis testing using the F test, T test and variable test which have the most influence. The results showed that the Training (X1) and Development (X2) variables simultaneously had a significant effect on the Employee Performance (Y) of the Production Department of PT. Kaltim Diamond Coal Site Loa Gagak Kutai Kartanegara.“The results of multiple linear regression tests simultaneously found that the Training and Development variables had a significant effect on the Employee Performance of the Production Department“at PT. Kaltim Diamond Coal Site Loa Gagak”Kutai Kartanegara.”The results of”the multiple linear regression test partially found that training and development had a significant influence on the performance of the production department“employees at PT. Kaltim Diamond Coal Site Loa Gagak Kutai Kartanegara”. The results of the most influential variable test, it is known that the training variable is the variable that has the most dominant influence on the Employee Performance of the Production Department at PT. Kaltim Diamond Coal Site Loa Gagak Kutai Kartanegara.

scholarly journals . Reflection of individual typological properties in the tremorogram (Predicting the indicators of Rusalov’s test according to the indicators of the tremorogram)

2021 ◽  
Vol 11 (5) ◽  
pp. 213-222
Author(s):  
B. A. Lobasyuk ◽  
L. N. Akimova ◽  
A. N. Stoyanov ◽  
A. V. Zamkovaya
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Regression Coefficients ◽  
Regression Equations ◽  
Target Feature ◽  
Left Hand ◽  
Right Hand ◽  
Postural Load ◽  
Significant Regression ◽  
The Right

Rationale for choosing. An increase in physiological tremor (Tr) in emotionally saturated situations is reflected not only in fiction, but also in scientific literature. In other words, tremors and emotional responses are interconnected. Purpose. To investigate the reflection of individual-typological properties in a tremorogram using V. M. Rusalov’s mathematical modeling. Material and methods. Tr was recorded using a linear transducer. Tr was recorded under postural load (arms extended forward). The sensor was alternately placed on the outstretched right and left arms in front of oneself, under conditions of “eyes open” (operative rest). The analysis of the tremorogram (TrG) files was carried out after the end of the study using the "Analist - 2" software according to the half - period analysis algorithm. To study the individual psychological characteristics of the personality, we used the method of determining the properties of the temperament by V.M. Rusalov. Each of the many indicators of Rusalov’s test selected in the analysis was considered as a target feature (Y-s), and the amplitudes and frequencies of TrG were considered as influencing variables (sets of X - s) and multiple linear regression equations of the form were built: The parameters of the amplitude and frequency of EEG rhythms were used as Xs. Own research. In multiple regression analysis of the influence of TrG indices of the right hand on the indices of Rusalov’s test, 12 statistically significant regression coefficients were determined, and 11 statistically significant regression coefficients for the left hand. After obtaining the diagnostic equations of multiple linear regression, describing the influence of TrG indicators on the indicators of Rusalov’s test, an attempt was made, using these equations, to obtain the indicators of Rusalov’s test, using the tremor indicators. On average, the% discrepancy between the determined and predicted indicators was 97.42% for the right hand, and 101.98 for the left. Conclusions. 1. With the use of diagnostic equation, it was possible to predict the indicators of psychological testing according to Rusalov’s test by the indicators of tremor of the right and left hands.2. Influence of Rusalov’s test indicators on TrG indicators were less in modulus than the influence of TrG indicators on the indicators of Rusalov’s  test, i.e. did not participate in the control of the mechanisms of TrG generation.3. The results obtained indicate that tremor indicators contain information about the subject-activity and communicative aspects of temperament according to V. M. Rusalov.

scholarly journals ATTITUDES AND PRO-ENVIRONMENTAL BEHAVIOURS: DETERMINING FACTOR OF PERSONALITY AND LIFESTYLE

2020 ◽  
Vol 18 (11) ◽  
Author(s):  
Aisyah Abu Bakar ◽  
Mariana Mohamed Osman ◽  
Mizan Hitam
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Equations ◽  
Well Being ◽  
Multiple Correlation ◽  
Limited Evidence ◽  
Environmental Behaviour ◽  
Environmental Destruction ◽  
Determining Factor ◽  
Environmental Behaviours

Sustainability in well-being embodies the interconnecting course of how various systems influence each other. The more strongly individuals subscribe to values beyond their immediate interests, that is, prosocial, collectivistic and biospheric values, the more likely they are to engage in environmental behaviour. Issue: Existing research has limited evidence on specific values of Malaysian’s personality and lifestyle (PL) that have significant impact on attitude and proenvironmental behaviour (AP). Purpose: This paper aims to verify the statistical predictability of AP based on PL. Approach: Multiple Correlation and Multiple Linear Regression were carried out to assess linear associations and parameters of linear equations to predict AP components based on PL items. Findings: AP components were moderately predictable by some of the PL items. Specifically, ‘ Urging media to raise environmental awareness ’ and ‘being mindful about environmental destruction’ were the two strongest predictors of AP.

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