scholarly journals Seasonal patterns of ecological uniqueness of anuran metacommunities along different ecoregions in Western Brazil

PLoS ONE ◽  
2020 ◽  
Vol 15 (9) ◽  
pp. e0239874
Author(s):  
Karoline Ceron ◽  
Diego J. Santana ◽  
Francisco Valente-Neto
Crisis ◽  
2014 ◽  
Vol 35 (1) ◽  
pp. 5-9 ◽  
Author(s):  
Daniel Hideki Bando ◽  
Fernando Madalena Volpe

Background: In light of the few reports from intertropical latitudes and their conflicting results, we aimed to replicate and update the investigation of seasonal patterns of suicide occurrences in the city of São Paulo, Brazil. Methods: Data relating to male and female suicides were extracted from the Mortality Information Enhancement Program (PRO-AIM), the official health statistics of the municipality of São Paulo. Seasonality was assessed by studying distribution of suicides over time using cosinor analyses. Results: There were 6,916 registered suicides (76.7% men), with an average of 39.0 ± 7.0 observed suicides per month. For the total sample and for both sexes, cosinor analysis estimated a significant seasonal pattern. For the total sample and for males suicide peaked in November (late spring) with a trough in May–June (late autumn). For females, the estimated peak occurred in January, and the trough in June–July. Conclusions: A seasonal pattern of suicides was found for both males and females, peaking in spring/summer and dipping in fall/winter. The scarcity of reports from intertropical latitudes warrants promoting more studies in this area.


1988 ◽  
Vol 9 (01) ◽  
pp. 85-88
Author(s):  
K. Srinivasan ◽  
N. K. Krishnakumar ◽  
P. R. Ramachander ◽  
G. S. P. Rao

Author(s):  
Andrew Foster ◽  
Hao Huang ◽  
Mohammad R. Narimani ◽  
Laura Homiller ◽  
Katherine Davis ◽  
...  

2021 ◽  
Vol 5 (1) ◽  
pp. 4
Author(s):  
Ruggero Sainaghi ◽  
Rodolfo Baggio

This paper explores the scaling (size) effect in the seasonal patterns, a proxy for competitive threats, of Airbnb’s host providers, with the aim of understanding possible similarities and differences. This explorative study uses the city of Milan (Italy) as a case and daily occupancy data from Airbnb listings for four completed years (2015–2018). A mutual information-based technique was applied to assess possible synchronizations in the seasonal patterns. Empirical findings show progressive dissimilarities when moving from single to multiple listings, thus indicating a differentiation correlated to the presence of managed listings. There are fewer differences during the seasonal periods more centered around leisure clients and they are higher when considering business travelers. The evidence supports the scaling effect and its ability to reduce the competitive threat among different hosts.


2021 ◽  
Vol 55 (1) ◽  
Author(s):  
Christian Hutter

AbstractThis paper exploits big data on online activity from the job exchange of the German Federal Employment Agency and its internal placement-software to generate measures for search activity of employers and job seekers and—as a novel feature—for placement activity of employment agencies. In addition, the average search perimeter in the job seekers’ search profiles can be measured. The data are used to estimate the behaviour of the search and placement activities during the business and labour market cycle and their seasonal patterns. The results show that the search activities of firms and employment agencies are procyclical. By contrast, job seekers’ search intensity shows a countercyclical pattern, at least before the COVID-19 crisis.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Mikołaj Kamiński ◽  
Matylda Kręgielska-Narożna ◽  
Paweł Bogdański

Abstract Background Detection of the seasonal patterns of healthy and unhealthy behavior could be helpful for designing individual and population health interventions programs. This study investigates the seasonal variation in sales of common types of products in Poland and Polish Google queries related to healthy behavior. Methods Data of index sales from a large Polish retail store franchise, from January 2014 to August 2019, has been analyzed. The commercial data included twelve types of products. The interest of Google users was investigated using Google Trends statistics for the same period for six lifestyle-related topics. The seasonality was checked using time series analysis. Results Six of the consumer goods (dairy, ready-made meals, salty snacks, meats, beer, and cigarettes) were most commonly purchased in summer months, four (processed fish, food fats, wine, and alcohol 30%+) in December, and two (bread and sweets) in October. The lowest sales indexes were observed mostly in February. The interest in four topics that have been analyzed (“Diet,” “Dietitian,” “Weight loss,” and “Gym”), was highest in January, while interest in “Dietary supplements” was high in February, and “Running” in May. The search volume of the Google topics were the lowest in December. Conclusion The purchase of food, drinks, and cigarettes, and the interest in information regarding different components of a healthy lifestyle has seasonal variation. New Year and Lent might be good periods to encourage healthy behavior. The motivation may decrease in summer and during Christmas.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Hirofumi Hashimoto ◽  
Weile Wang ◽  
Jennifer L. Dungan ◽  
Shuang Li ◽  
Andrew R. Michaelis ◽  
...  

AbstractAssessing the seasonal patterns of the Amazon rainforests has been difficult because of the paucity of ground observations and persistent cloud cover over these forests obscuring optical remote sensing observations. Here, we use data from a new generation of geostationary satellites that carry the Advanced Baseline Imager (ABI) to study the Amazon canopy. ABI is similar to the widely used polar orbiting sensor, the Moderate Resolution Imaging Spectroradiometer (MODIS), but provides observations every 10–15 min. Our analysis of NDVI data collected over the Amazon during 2018–19 shows that ABI provides 21–35 times more cloud-free observations in a month than MODIS. The analyses show statistically significant changes in seasonality over 85% of Amazon forest pixels, an area about three times greater than previously reported using MODIS data. Though additional work is needed in converting the observed changes in seasonality into meaningful changes in canopy dynamics, our results highlight the potential of the new generation geostationary satellites to help us better understand tropical ecosystems, which has been a challenge with only polar orbiting satellites.


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