LASER COUPLING TO NUCLEI VIA COLLECTIVE ELECTRONIC OSCILLATIONS—A SIMPLE HEURISTIC MODEL STUDY

1988 ◽  
pp. 707-712
Author(s):  
JOHNDALE C. SOLEM ◽  
LAWRENCE C. BLEDENHARN
2020 ◽  
Author(s):  
Fook Hou Lee

ABSTRACTThis paper presents a simple heuristic model for COVID 19 spreading. The model is based on a propagation unit of time. The state of the epidemic at the end of the time unit is then related to that at the start through recurrence relationships. By propagating these relationships over the required number of time units, a projection can be made over time. The model is readily implemented on a spreadsheet and is therefore potentially widely accessible. It can serve as a useful tool for scenario planning and forecasting not just for an entire population, but also for a specific community within a population.


2006 ◽  
Vol 15 (5) ◽  
pp. 763-777
Author(s):  
José A. Blanco ◽  
David W. Gillingham ◽  
John H. Lewko

Author(s):  
DAVID FORTUNATO ◽  
NICK C. N. LIN ◽  
RANDOLPH T. STEVENSON ◽  
MATHIAS WESSEL TROMBORG

Abstract Coalition governance divides policy-making influence across multiple parties, making it challenging for voters to accurately attribute responsibility for outcomes. We argue that many voters overcome this challenge by inferring parties’ policy-making influence using a simple heuristic model that integrates a number of readily available and cheaply obtained informational cues about parties (e.g., their roles in government and legislative seat shares)—while ignoring other cues that, while predictive of real-world influence, are not suitable for heuristic inference (e.g., median party status and bargaining power). Using original data from seven surveys in five countries, we show that voters’ attributions of parties’ policy-making influence are consistent with our proposed inferential strategy. Our findings suggest that while voters certainly have blind spots that cause them to misattribute policy responsibility in some situations, their attributions are generally sensible and consistent with the academic research on multiparty policy making.


2009 ◽  
Vol 36 (1/2/3) ◽  
pp. 287 ◽  
Author(s):  
Salvatore Barbaro ◽  
Angelo Bonanno ◽  
Maria Letizia Boscia ◽  
Gianfranco Rizzo ◽  
Salvatore Aronica

2020 ◽  
Author(s):  
Bishwajit Bhattacharjee

AbstractA simple heuristic model for spread of COVID-19 infections in India is presented and compared with reported data up to April 10, 2020. Spread of infection is considered to be initiating from infected individuals and spread is assumed to take place in a compounding manner. Some of the data needed are taken from readily available sources in the web. The possible progress is then estimated based on model presented and possible scenarios are highlighted.


1993 ◽  
Vol 37 (2) ◽  
pp. 145-159 ◽  
Author(s):  
W.J. Kimmerer ◽  
S.V. Smith ◽  
J.T. Hollibaugh

2014 ◽  
Vol 35 (3) ◽  
pp. 144-157 ◽  
Author(s):  
Martin Bäckström ◽  
Fredrik Björklund

The difference between evaluatively loaded and evaluatively neutralized five-factor inventory items was used to create new variables, one for each factor in the five-factor model. Study 1 showed that these variables can be represented in terms of a general evaluative factor which is related to social desirability measures and indicated that the factor may equally well be represented as separate from the Big Five as superordinate to them. Study 2 revealed an evaluative factor in self-ratings and peer ratings of the Big Five, but the evaluative factor in self-reports did not correlate with such a factor in ratings by peers. In Study 3 the evaluative factor contributed above the Big Five in predicting work performance, indicating a substance component. The results are discussed in relation to measurement issues and self-serving biases.


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