016 Associations between Circadian Melatonin and Temperature Amplitudes during Constant Routine

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A8-A8
Author(s):  
Katrina Rodheim ◽  
Christoper Jung ◽  
Kenneth Wright
Keyword(s):  
Individual Differences ◽  
Regression Models ◽  
Signal To Noise Ratio ◽  
Large Individual ◽  
Linear Regression Models ◽  
Harmonic Model ◽  
Circadian Phase ◽  
Best Fitting ◽  
Harmonic Regression ◽  
Best Fit

Abstract Introduction Circadian amplitude measures the strength or robustness of a rhythm and changes in amplitude may have implications for health. Large individual differences in melatonin amplitude are recognized. Here we aimed to determine the strength of relationships between melatonin and the core body (CBT) and distal-proximal skin temperature gradient (DPG) amplitudes during a constant routine protocol. Additionally, we determined the best fitting harmonic model for the DPG circadian rhythm. Methods 17 young healthy adults [13 males (22.3±3.9yr;mean±SD)] completed a 28-hr constant routine protocol after maintaining 8h habitual sleep schedules for one week at home. Endogenous circadian amplitudes of melatonin and CBT were fit with standard three- and dual-harmonic linear regression models, respectively. The DPG amplitude was analyzed with both dual and three-harmonic regression models to determine which model produced the best fit. Results The DPG was best fit by a three-harmonic regression model with significantly lower standard deviation and higher signal-to-noise ratio compared to the 2-harmonic model (both p<0.05) as well as by visualization of the fitted curves. Melatonin, CBT and DPG amplitudes were not found to be associated with each other during constant routine (all r<0.37; all p>0.10). Conclusion While it is common for melatonin and body temperature circadian phase estimates to be used interchangeably, non-significant findings for associations between circadian amplitudes of melatonin, CBT and DPG indicate that these markers may not provide similar information about circadian amplitude. Further, research is needed to explore possible associations between individual differences in melatonin, CBT and DPG amplitudes with other physiological and behavioral outcomes to determine which measure(s) of circadian amplitude may be functionally relevant. Support (if any) NIH R01 HL081761

scholarly journals Assessment of spline functions for estimating growth curve parameters of FUNAABAlpha chickens

2020 ◽  
Vol 46 (5) ◽  
Author(s):  
H. A. Bashiru ◽  
S. O. Oseni ◽  
L. A. Omadime
Keyword(s):  
Regression Models ◽  
Selection Criteria ◽  
Goodness Of Fit ◽  
Information Criterion ◽  
Regression Coefficients ◽  
Spline Functions ◽  
Linear Regression Models ◽  
Male And Female ◽  
Spline Models ◽  
Best Fit

The objective of this study was to fit four spline linear regression models to describe the growth of FUNAAB-Alpha Chickens (FAC). Body weight records of 300 FAC raised from day old till the 20th week were used to fit spline models of 3 (SP3), 4 (SP4), 5 (SP5) and 6 knots (SP6) using the REG procedure of SAS®. The data were first plotted to determine the most appropriate location of knots and they were placed at 4th, 10 th and 16 th week of age for SP3; 4th, 8th, 12th and 16th week for SP4; 4th, 7th, 10th, 14th and 18th week for SP5 and 3rd, 6th, 9th, 12th, 15 th and 18 th week for SP6, respectively. The hatch weight predicted by SP3 was observed to be highest while SP6 predicted the lowest hatch weight for male and female FAC. Regression coefficients ranged from -38.47 to 47.46 and -39.40 to 40.47 for the male and female, respectively. For all the models, the highest magnitude of these coefficients were estimated at early ages after hatching (at 3 to 10 weeks of age). Based on Bayesian Information Criterion (BIC) and Akaike Information Criterion (AIC) as the goodness-of-fit selection criteria, SP3 had the lowest value for AIC and BIC for male FAC while SP4 had the lowest value of AIC and BIC for the female FAC. It was concluded that spline models of lower knots (SP3 and SP4) were the best fit to describe the growth of male and female FAC respectively, and that growth rate at early stages of life of FAC may be good predictors of later growth performance.

scholarly journals Seasonal Variability of Snow Density in the Spanish Pyrenees

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1598
Author(s):  
Eduardo Lastrada ◽  
Guillermo Cobos ◽  
Julio Garzón-Roca ◽  
F. Javier Torrijo
Keyword(s):  
Regression Models ◽  
Water Resource Management ◽  
Snow Water Equivalent ◽  
Linear Regression Models ◽  
Snow Density ◽  
Spanish Pyrenees ◽  
Snow Water ◽  
Best Fitting ◽  
The Impact ◽  
Annual Time

Spanish latitudes and meteorological conditions cause the snow phenomena to mainly take place in mountainous areas, playing a key role in water resource management, with the Pyrenees as one of the most important and best monitored areas. Based on the most significant dataset of snow density (SDEN) in the Spanish Pyrenees for on-site manual samples and automatic measurements, in this study, single and multiple linear regression models are evaluated that relate SDEN with intra-annual time dependence and other drivers such as the seasonal accumulated precipitation, 7-day average temperatures, snow depth (SD) and elevation. The seasonal accumulated precipitation presented a more dominant influence than daily precipitation, usually being the second most dominant SDEN driver, followed by temperature. Average temperatures showed the best fitting to SDEN. The results showed similar densification rates ranging widely from 0.7 × 103 kg/L/day to 2 × 103 kg/L/day without showing a spatial pattern. The densification rate for the set of manual samples was set to 1.2 kg/L/day, very similar to the set of automatic measurements (1.3 kg/L/day). The results increase knowledge on SDEN in the Pyrenees. The SDEN regression models that are given in this work may allow us, in the future, to estimate SDEN, and consequently Snow Water Equivalent (SWE), using an economical and extensive SD and meteorological network, although the high spatial variability that has been found must be regarded. Estimating a relationship between SDEN and several climate drivers enables us to take into account the impact of climate variability on SDEN.

scholarly journals Models to estimate longitudinal compressive strength of Brazilian hardwood based on apparent density

BioResources ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. 1373-1381
Author(s):  
Francisco Antonio Rocco Lahr ◽  
Felipe Nascimento Arroyo ◽  
Edson Fernando Castanheira Rodrigues ◽  
João Paulo Boff Almeida ◽  
Vinicius Borges de Moura Aquino ◽  
...  
Keyword(s):  
Compressive Strength ◽  
Apparent Density ◽  
Regression Models ◽  
Physical And Mechanical Properties ◽  
Natural Material ◽  
Linear Regression Models ◽  
Linear Polynomial ◽  
Best Fit ◽  
Brazilian Standard ◽  
Large Research

As wood is an orthotropic and natural material, there are several properties required for its use in civil construction. The apparent density has been used to estimate physical and mechanical properties of wood, as it is easy to determine experimentally, unlike other determinations, which involve the use of equipment available only in large research centers. Using the Brazilian standard ABNT NBR 7190 and linear and non-linear regression models, this research aimed to evaluate their accuracy in estimating the compressive strength parallel to the fibers (fc0) as well as their characteristic value (fc0,k). This study considered 72 tropical wood species from native forests that were divided into the 4 strength classes of this standard. For the set formed by all species, the linear polynomial model was the best fit, resulting in a determination coefficient of just over 70%.

scholarly journals Suprathreshold perceptual decisions constrain models of confidence

2021 ◽  
Author(s):  
Shannon M Locke ◽  
Michael S Landy ◽  
Pascal Mamassian
Keyword(s):  
Signal To Noise Ratio ◽  
Point Estimate ◽  
Probability Metrics ◽  
Evidence Strength ◽  
Discrimination Criterion ◽  
Best Fitting ◽  
Complex Decision ◽  
The Mean ◽  
Sensory Uncertainty ◽  
Best Fit

Perceptual confidence is an important internal signal about the certainty of our decisions and there is a substantial debate on how it is computed. We highlight three confidence metric types from the literature: observers either use 1) the full probability distribution to compute probability correct (Probability metrics), 2) point estimates from the perceptual decision process to estimate uncertainty (Evidence-Strength metrics), or 3) heuristic confidence from stimulus-based cues to uncertainty (Heuristic metrics). These metrics are rarely tested against one another, so we examined models of all three types on a suprathreshold spatial discrimination task. Observers were shown a cloud of dots sampled from a dot generating distribution and judged if the mean of the distribution was left or right of centre. In addition to varying the horizontal position of the mean, there were two sensory uncertainty manipulations: the number of dots sampled and the spread of the generating distribution. After every two perceptual decisions, observers made a confidence forced-choice judgement whether they were more confident in the first or second decision. Model results showed that observers were on average best-fit by a Heuristic model that used dot cloud position, spread, and number of dots as cues. However, almost half of the observers were best-fit by an Evidence-Strength model that uses the distance between the discrimination criterion and a point estimate, scaled according to sensory uncertainty, to compute confidence. This signal-to-noise ratio model outperformed the standard unscaled distance from criterion model favoured by many researchers and suggests that this latter simple model may not be suitable for mixed-difficulty designs. An accidental repetition of some sessions also allowed for the measurement of confidence agreement for identical pairs of stimuli. This N-pass analysis revealed that human observers were more consistent than their best-fitting model would predict, indicating there are still aspects of confidence that are not captured by our model. As such, we propose confidence agreement as a useful technique for computational studies of confidence. Taken together, these findings highlight the idiosyncratic nature of confidence computations for complex decision contexts and the need to consider different potential metrics and transformations in the confidence computation.

scholarly journals Model-based Informal Inference

2017 ◽  
Vol 6 (5) ◽  
pp. 140
Author(s):  
Theodosia Prodromou
Keyword(s):  
Linear Regression ◽  
Instructional Practices ◽  
Linear Model ◽  
Regression Models ◽  
Linear Models ◽  
Linear Regression Models ◽  
Journal Paper ◽  
Support Students ◽  
Best Fit ◽  
Informal Inference

Following recent scholarly interest in teaching informal linear regression models, this study looks at teachers’ reasoning about informal lines of best fit and their role in pedagogy. The case results presented in this journal paper provide insights into the reasoning used when developing a simple informal linear model to best fit the available data. This study also suggests potential in specific aspects of bidirectional modelling to help foster the development of robust knowledge of the logic of inference for those investigating and coordinating relations between models developed during modelling exercises and informal inferences based on these models. These insights can inform refinement of instructional practices using simple linear models to support students’ learning of statistical inference, both formal and informal.

scholarly journals Extra-Curricular Activities and Well-Being: Results From a Survey of Undergraduate University Students During COVID-19 Lockdown Restrictions

2021 ◽  
Vol 12 ◽  
Author(s):  
Rachael Finnerty ◽  
Sara A. Marshall ◽  
Constance Imbault ◽  
Laurel J. Trainor
Keyword(s):  
Individual Differences ◽  
University Students ◽  
Well Being ◽  
Musical Instrument ◽  
Large Individual ◽  
Linear Regression Models ◽  
University Campuses ◽  
Extra Curricular Activities ◽  
Song Writing ◽  
The Individual

Participation in extra-curricular activities has been found to associate with increased well-being. Here we investigated in a survey (n = 786) what activities university students at a Canadian university engaged in during the stressful COVID-19 pandemic lockdown in April, 2020, which coincided with a novel online exam period, and how these activities related to perceived well-being, anxiety (STAI-S), social aspects of activities, and personality. Sixty-five percentage of students scored in the high anxiety category of the STAI-S, an alarming statistic given that only 24% had reached out for professional supports. This is consistent with reports that current supports on university campuses are inadequate. Listening to music (92%) and watching movies/series (92%) were engaged in most frequently, followed by socializing virtually (89%) and engaging in social media (85%). The activities students rated as most helpful to their well-being were somewhat different, with outdoor exercise rated highest, followed by socializing virtually and listening to music. While all activities were rated as beneficial, those with a social component tended to have high ratings, consistent with students attempting to replace lost social interactions. Linear regression models found few associations between STAI-S scores and other measures, likely because of large individual differences and lack of a pre-pandemic baseline needed to assess changes in anxiety. The importance of individual differences was evident in that those higher in conscientiousness or extraversion or emotional stability were more likely to engage in exercise, while those higher in openness to experience were more likely to engage in journaling, playing a musical instrument, or singing, with a trend for higher engagement in song writing. Individual differences were also evident in that equal numbers of students gave positive and negative comments related to their well-being during the pandemic. The individual differences uncovered here suggest that having a variety of proactive interventions would likely reach more students. Indeed, 52% indicated an interest in online group music therapy, 48% in art therapy and 40% in verbal therapy, despite music and art therapies being virtually non-existent on campuses. In sum, the findings highlight the importance of choice in extra-curricular activities and therapies that support well-being.

FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

2018 ◽  
Vol 23 (1) ◽  
pp. 60-71
Author(s):  
Wigiyanti Masodah
Keyword(s):  
Interest Rate ◽  
Linear Regression ◽  
Interest Rates ◽  
Regression Models ◽  
Linear Regression Models ◽  
Negative Impacts ◽  
Main Activity ◽  
The Impact ◽  
The Given ◽  
Multiple Linear Regression Models

Offering credit is the main activity of a Bank. There are some considerations when a bank offers credit, that includes Interest Rates, Inflation, and NPL. This study aims to find out the impact of Variable Interest Rates, Inflation variables and NPL variables on credit disbursed. The object in this study is state-owned banks. The method of analysis in this study uses multiple linear regression models. The results of the study have shown that Interest Rates and NPL gave some negative impacts on the given credit. Meanwhile, Inflation variable does not have a significant effect on credit given. Keywords: Interest Rate, Inflation, NPL, offered Credit.

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