A study about the linearity of trends between extreme and mean temperatures in Argentina

2021 ◽  
Author(s):  
Solange Suli ◽  
Matilde Rusticucci ◽  
Soledad Collazo
Keyword(s):  
Linear Regression ◽  
Linear Relationship ◽  
Statistical Significance ◽  
Coefficient Of Determination ◽  
Maximum Temperature ◽  
Mean Temperature ◽  
Change In The Mean ◽  
The Mean ◽  
Student’S T ◽  
Cold Extremes

<p>Small variations in the mean state of the atmosphere can cause large changes in the frequency of extreme events. In order to deepen and extend previous results in time, in this work we analyzed the linear relationship between extreme and mean temperature (Τ) on a climate change scale in Argentina. Two monthly extreme indices, cold nights (TN10) and warm days (TX90), were calculated based on the quality-controlled daily minimum and maximum temperature data provided by the Argentine National Meteorological Service from 58 conventional weather stations located over Argentina in the 1977–2017 period. Subsequently, we evaluated the relationship between the linear trends of extremes and mean temperature on a seasonal basis (JFM, AMJ, JAS, and OND). Student's T-test was performed to analyze their statistical significance at 5%. Firstly, positive (negative) and significant linear regressions were found between TX90 (TN10) trends and mean temperature trends for the four studied seasons. Therefore, an increase in the Τ-trend maintains a linear relationship with significant increase (decrease) of warm days (cold nights). Moreover, we found that JFM was the one with the highest coefficient of determination (0.602 for hot extremes and 0.511 for cold extremes), implying that 60.2% (51.1%) of the TX90 (TN10) trend could be explained as a function of the Τ-trend by a linear regression. In addition, in the JFM (OND) quarter, the TX90 index increased by 7.02 (6.02) % of days each with a 1 ºC increase in the mean temperature. Likewise, the TN10 index decreased by 4.94 (and 4.99) % of days from a 1ºC increase in the mean temperature for the JFM (AMJ) quarter. Finally, it is worthwhile to highlight the uneven behavior between hot and cold extremes and the mean temperature. Specifically, it was observed that the slopes of the linear regression calculated for the TX90 index and Τ presented a higher absolute value than those registered for the TN10 index and Τ. Therefore, a change in the mean temperature affects hot extremes to a greater extent than cold ones in Argentina.</p>

THE TEMPERATURES OF SURFACE FIRES IN JACK PINE BARREN: I. THE VARIATION IN TEMPERATURE WITH TIME

1966 ◽  
Vol 44 (10) ◽  
pp. 1285-1292 ◽  
Author(s):  
David W. Smith ◽  
John H. Sparling
Keyword(s):  
Jack Pine ◽  
Maximum Temperature ◽  
Surface Fires ◽  
Mean Temperature ◽  
The Mean ◽  
Maximum Temperatures

The temperatures of 18 fires in an open jack pine barren near Timmins, Ontario, have been recorded. The maximum temperature recorded was 545 °C, although in other determinations fire temperatures in excess of 1000 °C were reached. The mean temperature of all fires was 340.6 ± 133.2 °C. Three fires at 230, 345, and 545 °C were considered in detail.The maximum temperature of a fire was normally recorded at heights of 5 cm or 10 cm above the surface. Maximum temperatures of hotter fires usually occurred at greater heights than cooler ones. Duration and the temperature ("intensity") of the fire are important aspects of fire studies.

scholarly journals Comparison of Methods for Harvest Prediction in ‘Gigante’ Cactus Pear

2019 ◽  
Vol 11 (14) ◽  
pp. 216 ◽  
Author(s):  
Bruno V. C. Guimarães ◽  
Sérgio L. R. Donato ◽  
Ignacio Aspiazú ◽  
Alcinei M. Azevedo ◽  
Abner J. de Carvalho
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Regression Models ◽  
Coefficient Of Determination ◽  
Cactus Pear ◽  
Federal Institute ◽  
The Mean ◽  
Artificial Neural

Behavior analysis and plant expression are the answers the researcher needs to construct predictive models that minimize the effects of the uncertainties of field production. The objective of this study was to compare the simple and multiple linear regression methods and the artificial neural networks to allow the maximum security in the prediction of harvest in ‘Gigante’ cactus pear. The uniformity test was conducted at the Federal Institute of Bahia, Campus Guanambi, Bahia, Brazil, coordinates 14°13′30″ S, 42°46′53″ W and altitude of 525 m. At 930 days after planting, we evaluated 384 basic units, in which were measured the following variables: plant height (PH); cladode length (CL), width (CW) and thickness (CT); cladode number (CN); total cladode area (TCA); cladode area (CA) and cladode yield (Y). For the comparison between the artificial neural networks (ANN) and regression models (single and multiple-SLR and MLR), we considered the mean prediction error (MPE), the mean quadratic error (MQE), the mean square of deviation (MSD) and the coefficient of determination (R2).The values estimated by the ANN 7-5-1 showed the best proximity to the data obtained in field conditions, followed by ANN 6-2-1, MLR (TCA and CT), SLR (TCA) and SLR (CN). In this way, the ANN models with the topologies 7-2-1 and 6-2-1, MLR with the variables total cladode area and cladode thickness and SLR with the isolated descriptors total cladode area and cladode number, explain 85.1; 81.5; 76.3; 74.09 and 65.87%, respectively, of the yield variation. The ANNs were more efficient at predicting the yield of the ‘Gigante’ cactus pear when compared to the simple and multiple linear regression models.

scholarly journals Caregiver Burden and Disability in Somatoform Disorder: An Exploratory Study

2020 ◽  
pp. 025371762095756
Author(s):  
Esther Chinneimawi ◽  
Padmavathi Nagarajan ◽  
Vikas Menon
Keyword(s):  
Caregiver Burden ◽  
Somatoform Disorders ◽  
Statistical Significance ◽  
International Classification Of Diseases ◽  
Somatoform Disorder ◽  
Chi Square ◽  
Disability Score ◽  
Chi Square Test ◽  
The Mean ◽  
Student’S T

Background: Very few Indian studies have explored disability among patients with somatoform disorder and the burden experienced by their caregivers. We aimed to assess the levels of disability among patients with somatoform disorder and the levels of burden among their caregivers and compare these parameters against patients with schizophrenia. Methods: Participants included adults with a diagnosis of somatoform disorders (F45.0–F 45.9) ( n = 28) or schizophrenia (F20.0–F20.9) ( n = 28) diagnosed as per the International Classification of Diseases, Tenth Revision ( ICD-10), clinical descriptions, and diagnostic guidelines, as well as their caregivers. The WHO Disability Assessment Schedule 2.0 and Family Burden Interview Schedule were used to assess patient disability and caregiver burden, respectively. Independent Student’s t-test or chi-square test was used to compare relevant sociodemographic and clinical parameters. Results: Out of 56 patients, the mean (±SD) age of the sample was 38.6 (±10.5) years. Females constituted a slender majority of the sample ( n = 29, 51.8%). The mean disability score of patients with somatoform disorders was slightly higher (83.6 ±20.9) than that of patients with schizophrenia (82.3 ±16.7). Similarly, the mean burden score of caregivers of patients with somatoform disorders was nominally higher (18.96 ±9.9) than that of caregivers of patients with schizophrenia (15.7 ±9.7). Neither of these differences approached statistical significance (P > 0.05). Conclusion: Patients with somatoform disorders experience considerable levels of disability, and their caregivers go through various levels of burden in their daily life that is comparable to schizophrenia.

scholarly journals The Effect of Different Shades, Voltages and Increment Thickness on the Polymerization Depth of a Microhybrid Composite

2012 ◽  
Vol 2 (2) ◽  
pp. 52-56
Author(s):  
Farhan Raza Khan ◽  
Muhammad Hasan ◽  
Syed Iqbal Azam
Keyword(s):  
Composite Material ◽  
Linear Regression ◽  
Developing World ◽  
Dental Composite ◽  
P Value ◽  
Depth Of Cure ◽  
Variable Voltage ◽  
The Mean ◽  
Student’S T ◽  
Student’S T Test

ABSTRACT Aim Electric fluctuations in the developing world are common and may affect dental composite curing. We determined the effect of variable voltage and increasing thickness of different shades of composite on its depth-of-cure. Materials and methods ISO scrapping method was used on 14 commonly used shades of Esthet-X HD composites. Student's t-test and ANOVA were applied to compare the mean depth-of-cure and a linear regression model was developed using variables voltage (180 V and 220 V), material thickness (2, 4 and 6 mm) and shades (n = 14). Results The mean curing depth of samples was significantly reduced at 180 volts compared to 220 volts (p-value <0.002). At thickness of 2 mm, all samples were fully cured but when it was raised to 4 mm, the depth-of-cure reduced to 1.86 mm ± 0.06; while at 6 mm thickness, it reached to 1.96 mm ± 0.06 (p-value < 0.001). Conclusion Around 82% variation in the depth-of-cure is explained by voltage, thickness and shade of composite material (p-value <0.001). Clinical significance Electric fluctuations are prevalent in the developing world and thus poor voltage flow is responsible for dental composite's inadequate polymerization. How to cite this article Khan FR, Hasan M, Azam SI. The Effect of Different Shades, Voltages and Increment Thickness on the Polymerization Depth of a Microhybrid Composite. Int J Prosthodont Restor Dent 2012;2(2):52-56.

scholarly journals Time Series Analysis of Temperature and Rainfall Data of Dhaka Division

2017 ◽  
Vol 65 (2) ◽  
pp. 119-123
Author(s):  
Khadija Khatun ◽  
MA Samad ◽  
Md Bazlur Rashid
Keyword(s):  
Climatic Factors ◽  
Statistical Significance ◽  
Rainfall Data ◽  
Maximum Temperature ◽  
Total Rainfall ◽  
Annual Average ◽  
Mean Temperature ◽  
Average Maximum ◽  
Annual Total ◽  
Level Of Significance

In this paper, thirty five years’ (1981-2015) temperature and rainfall data have been studied to detect the recent trends in temperature and rainfall over Dhaka division of Bangladesh. Data of climatic factors such as annual average maximum temperature (MAXT), minimum temperature (MINT), mean temperature (MEANT), monsoon total rainfall (MTR) and annual total rainfall (ATR) have been analyzed. Sen’s non-parametric estimator of slope has been frequently used to estimate the magnitude of trend, whose statistical significance is assessed by the Mann–Kendall test. For this purpose, data from four meteorological stations (Dhaka, Mymensingh, Tangail and Faridpur) have been used. It is observed that annual average maximum, minimum and mean temperature of the study area are increasing at the rates 0.0170C/year, 0.0090C/year and 0.0130C/year respectively and the upward trend is statistically stable with 10% level of significance. On the other hand, monsoon total rainfall and annual total rainfall are decreasing at the rates of 4.94 mm/year and 16.11mm/year respectively where the downward trend of MTR is insignificant but the trend of ATR is significant with 10% level of significance. Dhaka Univ. J. Sci. 65(2): 119-123, 2017 (July)

scholarly journals Linear regression of sampling distributions of the mean

2021 ◽  
Author(s):  
David J Torres ◽  
Ana Vasilic ◽  
Jose Pacheco
Keyword(s):  
Linear Regression ◽  
Differential Expression ◽  
Clustering Algorithm ◽  
Distance Measure ◽  
Regression Coefficients ◽  
Coefficient Of Determination ◽  
Individual Data ◽  
Sampling Distributions ◽  
The Mean ◽  
Hierarchical Clustering Algorithm

AbstractWe show that the simple and multiple linear regression coefficients and the coefficient of determination R2 computed from sampling distributions of the mean (with or without replacement) are equal to the regression coefficients and coefficient of determination computed with individual data. Moreover, the standard error of estimate is reduced by the square root of the group size for sampling distributions of the mean. The result has applications when formulating a distance measure between two genes in a hierarchical clustering algorithm. We show that the Pearson R coefficient can measure how differential expression in one gene correlates with differential expression in a second gene.

scholarly journals Analysis of Long Term Temperature Trend for Madhya Pradesh, India (1901-2005)

2017 ◽  
Vol 12 (1) ◽  
pp. 68-79
Author(s):  
Rituraj Shukla ◽  
Deepak Khare ◽  
Priti Tiwari ◽  
Prabhash Mishra ◽  
Sakshi Gupta
Keyword(s):  
Time Series ◽  
Temperature Time Series ◽  
Madhya Pradesh ◽  
Maximum Temperature ◽  
Significance Level ◽  
Monotonic Trend ◽  
Mean Temperature ◽  
The Mean ◽  
The Impact ◽  
Temperature Time

The paper examines the impact of climatic change on the mean temperature time series for Pre-monsoon (Mar-May), Monsoon (Jun-Sept), Post-monsoon (Oct-Nov), winter (Dec-Feb) and Annual (Jan-Dec) at 45 stations in the state of Madhya Pradesh, India. Impact detection is accomplished by using the Mann-Kendall method to find out the monotonic trend and Sen’s slope is method is to identify the grandeur of trend for the period 1901 to 2005 (105 years). Prior to the trend analysis prominence of eloquent lag-1 serial correlation are eradicated from data by the pre-whitening method. In addition, shift year change has also been examined in the study using Pettitt’s test. From 45 stations, most of the station show symbolic hike trend at 5% significance level in the mean temperature time series for Madhya Pradesh region. During peak summer months the maximum temperature touches 40°C in the entire Madhya Pradesh. The magnitudes of annual increase in temperature in the majority of the stations are about 0.01°C.The analysis in the present study indicated that the change point year of the significant upward shift changes was 1963 for annual mean temperature time series, which can be very useful for water resources planners in the study area. The finding of the study provides more insights and inputs for the better understanding of regional temperature and shift behavior in the study area.

Natural temperature regimes for loggerhead and green turtle nests in the eastern Mediterranean

1998 ◽  
Vol 76 (4) ◽  
pp. 723-729 ◽  
Author(s):  
Y Kaska ◽  
R Downie ◽  
R Tippett ◽  
R W Furness
Keyword(s):  
Sex Ratio ◽  
Incubation Period ◽  
Green Turtle ◽  
Eastern Mediterranean ◽  
Loggerhead Turtle ◽  
Chelonia Mydas ◽  
Maximum Temperature ◽  
Diel Cycles ◽  
Mean Temperature ◽  
The Mean

Temperatures of green turtle (Chelonia mydas) and loggerhead turtle (Caretta caretta) nests on the beaches of northern Cyprus and Turkey were examined. Electronic continuous-temperature recorders programmed by computer were placed at the top, middle, and bottom of the nests. The sex of 3-7 hatchlings from each level was determined from gonadal histology. The maximum temperature increase during the incubation period was 9.6oC for both species. The mean temperature during the middle third of the incubation period is a good indicator of the sex ratio of the clutch. The percentage of female embryos increased with temperature, 50% being female at 29°C. The mean temperature over the entire incubation period is not a good indicator of sex ratio but can be used to predict the duration of incubation period. The temperature differences within the clutch were larger in loggerhead than in green turtle nests. Eggs at the top of the nest experienced generally warmer (up to 1.4°C) conditions than eggs at the bottom of the same nest, and this caused variation in sex ratio within nests. Over all nests, the sex ratio (percent female) of hatchlings was 91% at the top, 83% at the middle, and 69% at the bottom. There was considerable interbeach thermal variation. Marked diel cycles of up to 1.5°C were detected in loggerhead turtle nests but not in the deeper nests of green turtles.

Summer Temperature and All-cause Mortality from 2006 to 2015 for Smart City Jaipur, India

2021 ◽  
pp. 097206342110116
Author(s):  
Suresh K. Rathi ◽  
P. R. Sodani ◽  
Suresh Joshi
Keyword(s):  
Relative Humidity ◽  
Urban Population ◽  
Extreme Heat ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Mean Temperature ◽  
All Cause Mortality ◽  
The Mean

A considerable association between temperature and all-cause mortality has been documented in various studies. Further insights can be obtained from studying the impact of temperature and heat index (HI) for Jaipur city’s all-cause mortality. The objective of this work was to assess the association between the extreme heat (daily maximum temperature, daily minimum temperature, daily mean temperature, relative humidity and HI) and all-cause mortality for summer months (March to June) from 2006 to 2015 for urban population of Jaipur. For summer months, we collected the data on various temperature and all-cause mortality parameters for at least 10 years. The student’s t-test and ANOVA were used to analyse variations in mean temperature, maximum temperature and HI. The Pearson correlation coefficient was used to study the relationship between ambient heat and lag time effect all-cause mortality. A total of 75,571 deaths (all-cause mortality) for 1,203 summer days (2006–2015) were analysed in relation to temperature and relative humidity. The mean daily all-cause mortality has been estimated at 62.8 ± 15.2 for the study period. There is a significant increase of 39% per day all-cause mortality at the maximum temperature of 45 °C and above. However only 10% rise per day all-cause mortality for extreme danger days (HI > 54 °C). The mean daily all-cause mortality shows a significant association with daily maximum temperature ( F = 34.6, P < .0001) and HI (discomfort index) from caution to extreme danger risk days ( F = 5.0, P < .0019). The lag effect of extreme heat on all-cause mortality for the study period (2006 to 2015) was at a peak period on the same day of the maximum temperature ( r = 0.245 at P < .01) but continues up to four days. The study concludes that the effect of ambient heat on all-cause mortality increase is clearly evident (rise of 39% deaths/day). Accordingly, focus should be put on developing adaptation measures against ambient heat. This analysis may satisfy policy makers’ needs. Extreme heat-related mortality needs further study to reduce adverse effects on health among Jaipur’s urban population.

scholarly journals Evaluation of a Technique for Radar Identification of Large Hail across the Upper Midwest and Central Plains of the United States

2007 ◽  
Vol 22 (2) ◽  
pp. 244-254 ◽  
Author(s):  
Rodney A. Donavon ◽  
Karl A. Jungbluth
Keyword(s):  
United States ◽  
Linear Regression ◽  
Linear Relationship ◽  
Radar Data ◽  
The United States ◽  
Probability Of Detection ◽  
Coefficient Of Determination ◽  
Event Time ◽  
Severe Thunderstorms ◽  
Melting Level

Abstract Radar data were analyzed for severe thunderstorms that produced severe hail (&gt;19 mm diameter) across the central and northern plains of the United States during the 2001–04 convective seasons. Results showed a strongly linear relationship between the 50-dBZ echo height and the height of the melting level—so strong that a severe hail warning methodology was successfully deployed at the National Weather Service Warning and Forecast Offices in North Dakota and Iowa. Specifically, for each of 183 severe hailstorms, the 50-dBZ echo height near the hail event time was plotted against the depth of the environmental melting level. Linear regression revealed a coefficient of determination of 0.86, which suggested a strong linear relationship between the 50-dBZ echo height and the melting-level depth for the severe hail producing storms. As the height of the melting level increased, the expected 50-dBZ echo height increased. A severe warning criterion for large hail was based on the 10th percentile from the linear regression, producing a probability of detection of 90% and a false alarm rate of 22%. Additional analysis found that the 50-dBZ echo-height technique performs very well for weakly to moderately sheared thunderstorm environments. However, for strongly sheared, supercell-type environments, signatures such as weak-echo regions and three-body scatter spikes led to more rapid severe thunderstorm detection in many cases.

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