One model fits all

Author(s):  
Spiros Chadoulos ◽  
Iordanis Koutsopoulos ◽  
George C. Polyzos
Keyword(s):  
2020 ◽  
Vol 32 (4) ◽  
pp. 165-175 ◽  
Author(s):  
Leman Pınar Tosun ◽  
Ezgi Kaşdarma

Abstract. In the current study we examined a psychological mechanism linking Facebook use to depression. A survey was conducted with 319 undergraduates about their passive Facebook use, their frequency of making upward social comparisons on Facebook, the emotions evoked through these comparisons, and their levels of depression. Half of the participants were given questions about the Facebook comparisons they made with their close friends, while the other half were given questions about the Facebook comparisons they made with acquaintances. Analysis of the whole sample revealed that upward Facebook comparison elicited assimilative emotions (inspiration, optimism, and admiration) more than contrastive emotions did (envy and resentment). A path model was developed in which passive use of Facebook predicted the frequency of making upward social comparisons, and, in turn, the frequency of making upward Facebook comparisons predicted depression through two routes: one through contrastive emotions and other through assimilative emotions. The results suggested that the model fits the data. As expected, the frequency of upward Facebook comparisons was associated with the increases in frequency of both contrastive and assimilative emotions, and the associations of these two types of emotions with depression were in opposite directions: Depression increased as the frequency of contrastive emotions increased, and it decreased as the frequency of assimilative emotions increased. The strength of the latter aforementioned association was stronger when the comparison targets were acquaintances rather than close friends.


1999 ◽  
Vol 519 (2) ◽  
pp. 834-843 ◽  
Author(s):  
J. Davy Kirkpatrick ◽  
France Allard ◽  
Tom Bida ◽  
Ben Zuckerman ◽  
E. E. Becklin ◽  
...  

2021 ◽  
Author(s):  
Sigurd M⊘lster Galaasen ◽  
Alfonso Irarrazabal

Abstract This paper studies the determinants of R&D heterogeneity and the economic impact of R&D subsidies. We estimate a Schumpeterian growth model featuring firms with heterogeneous innovation efficiencies. The model fits well the R&D investment distribution, and the frequency and relative size of R&D performers. Using the model we study the impact of a Norwegian R&D reform targeting firms with R&D spending below a certain threshold. The size-dependent subsidy increases aggregate R&D investment by 11.7%, but reduces growth and welfare. In contrast, a uniform subsidy stimulates investment, growth and welfare.


Forests ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 234
Author(s):  
Linda Flade ◽  
Christopher Hopkinson ◽  
Laura Chasmer

In this follow-on study on aboveground biomass of shrubs and short-stature trees, we provide plant component aboveground biomass (herein ‘AGB’) as well as plant component AGB allometric models for five common boreal shrub and four common boreal short-stature tree genera/species. The analyzed plant components consist of stem, branch, and leaf organs. We found similar ratios of component biomass to total AGB for stems, branches, and leaves amongst shrubs and deciduous tree genera/species across the southern Northwest Territories, while the evergreen Picea genus differed in the biomass allocation to aboveground plant organs compared to the deciduous genera/species. Shrub component AGB allometric models were derived using the three-dimensional variable volume as predictor, determined as the sum of line-intercept cover, upper foliage width, and maximum height above ground. Tree component AGB was modeled using the cross-sectional area of the stem diameter as predictor variable, measured at 0.30 m along the stem length. For shrub component AGB, we achieved better model fits for stem biomass (60.33 g ≤ RMSE ≤ 163.59 g; 0.651 ≤ R2 ≤ 0.885) compared to leaf biomass (12.62 g ≤ RMSE ≤ 35.04 g; 0.380 ≤ R2 ≤ 0.735), as has been reported by others. For short-stature trees, leaf biomass predictions resulted in similar model fits (18.21 g ≤ RMSE ≤ 70.0 g; 0.702 ≤ R2 ≤ 0.882) compared to branch biomass (6.88 g ≤ RMSE ≤ 45.08 g; 0.736 ≤ R2 ≤ 0.923) and only slightly better model fits for stem biomass (30.87 g ≤ RMSE ≤ 11.72 g; 0.887 ≤ R2 ≤ 0.960), which suggests that leaf AGB of short-stature trees (<4.5 m) can be more accurately predicted using cross-sectional area as opposed to diameter at breast height for tall-stature trees. Our multi-species shrub and short-stature tree allometric models showed promising results for predicting plant component AGB, which can be utilized for remote sensing applications where plant functional types cannot always be distinguished. This study provides critical information on plant AGB allocation as well as component AGB modeling, required for understanding boreal AGB and aboveground carbon pools within the dynamic and rapidly changing Taiga Plains and Taiga Shield ecozones. In addition, the structural information and component AGB equations are important for integrating shrubs and short-stature tree AGB into carbon accounting strategies in order to improve our understanding of the rapidly changing boreal ecosystem function.


2004 ◽  
Vol 1695 (1-3) ◽  
pp. 215-223 ◽  
Author(s):  
Christian Hirsch ◽  
Ernst Jarosch ◽  
Thomas Sommer ◽  
Dieter H. Wolf

1977 ◽  
Vol 47 (8) ◽  
pp. 545-551
Author(s):  
N. S. Kambo ◽  
K. R. Salhotra ◽  
A. Singh

A probabilistic model for the tuft-breakage process has been proposed by Kambo and Aziz. Estimation of the parameters and the application of the model are demonstrated in this study. The parameters of the model are estimated by a linearization method. To do this, two modes of tuft breakage have been studied to determine which one is better suited to explain the observed data. The results show that the model fits very well to the data on tuft breakage for two types of cotton.


1996 ◽  
pp. 95-96
Author(s):  
Yu. A. Kovalev ◽  
A. B. Berlin ◽  
N. A. Nizelskij ◽  
Y. Y. Kovalev ◽  
S. V. Babak
Keyword(s):  

2011 ◽  
pp. 2850-2865
Author(s):  
Murray E. Jennex ◽  
Lorne Olfman

This article proposes a framework for assessing knowledge management system (KMS) success models. The framework uses three criteria: how well the model fits actual KMS success factors, the degree to which the model has a theoretical foundation, and if the model can be used for both types of KMSs. The framework is then applied to four KMS success models found in the literature and is determined to be a useful framework for assessing KMS success models.


2019 ◽  
Vol 49 (03) ◽  
pp. 555-590 ◽  
Author(s):  
Andrew J.G. Cairns ◽  
Malene Kallestrup-Lamb ◽  
Carsten Rosenskjold ◽  
David Blake ◽  
Kevin Dowd

AbstractWe introduce a new modelling framework to explain socio-economic differences in mortality in terms of an affluence index that combines information on individual wealth and income. The model is illustrated using data on older Danish males over the period 1985–2012 reported in the Statistics Denmark national register database. The model fits the historical mortality data well, captures their key features, generates smoothed death rates that allow us to work with a larger number of sub-groups than has previously been considered feasible, and has plausible projection properties.


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