Climate of the Reformation: droughts and anomalous weather in the 1500s-1510s in Europe

2020 ◽  
Author(s):  
Andrea Kiss ◽  
Mariano Barriendos ◽  
Rudolf Brázdil ◽  
Chantal Camenisch ◽  
Silvia Enzi ◽  
...  
Keyword(s):  
Western Europe ◽  
Weather Conditions ◽  
Temporal Analysis ◽  
Economic Consequences ◽  
Economic Factors ◽  
Documentary Evidence ◽  
The Reformation ◽  
Rapid Spread ◽  
Spatial Temporal Analysis ◽  
Socio Economic Factors

<p>In the 1500s-1510s an unusually high number of significant droughts in Central and Western, and partly in Southern Europe; the years 1502-1504, 1506-1507, 1513-1514 and 1516-1518 were dry particularly in Central and Western Europe. Droughts, interspersed with wet years marked even by significant floods and other weather-related extremes, and frequent hard winters were mainly responsible for the reduced or poor crop and hay harvests in multiple years. These circumstances, in combination with other socio-economic factors, contributed to the increased social tension of the period, manifesting itself in major peasant uprisings, and might have acted as a catalyst in the timing and rapid spread of the Reformation.</p><p>The first part of the presentation is concentrated on the reconstruction and spatial-temporal analysis of the droughts (and hard winters) using documentary evidence – in comparison with the tree-ring based hydroclimate reconstruction (OWDA: Cook et al. 2015) and the multiproxy-based reconstruction of Central European precipitation (Pauling et al. 2006).</p><p>The most significant groups of socio-economic consequences are analysed in the second part of the presentation, with special emphasis on discussing the possible cumulative effects of the anomalous weather conditions during the period on the ongoing transformation of the late-medieval society and economy and the Reformation itself.</p>

scholarly journals Fourier Analysis for Demand Forecasting in a Fashion Company

10.5772/56839 ◽  
2013 ◽  
Vol 5 ◽  
pp. 30 ◽  
Author(s):  
Andrea Fumi ◽  
Arianna Pepe ◽  
Laura Scarabotti ◽  
Massimiliano M. Schiraldi
Keyword(s):  
Moving Average ◽  
Demand Forecasting ◽  
Fourier Method ◽  
Weather Conditions ◽  
Economic Factors ◽  
Fast Fourier Transform Algorithm ◽  
Fashion Industry ◽  
Forecasting Method ◽  
Short Lifecycle ◽  
Socio Economic Factors

In the fashion industry, demand forecasting is particularly complex: companies operate with a large variety of short lifecycle products, deeply influenced by seasonal sales, promotional events, weather conditions, advertising and marketing campaigns, on top of festivities and socio-economic factors. At the same time, shelf-out-of-stock phenomena must be avoided at all costs. Given the strong seasonal nature of the products that characterize the fashion sector, this paper aims to highlight how the Fourier method can represent an easy and more effective forecasting method compared to other widespread heuristics normally used. For this purpose, a comparison between the fast Fourier transform algorithm and another two techniques based on moving average and exponential smoothing was carried out on a set of 4-year historical sales data of a €60+ million turnover medium- to large-sized Italian fashion company, which operates in the women's textiles apparel and clothing sectors. The entire analysis was performed on a common spreadsheet, in order to demonstrate that accurate results exploiting advanced numerical computation techniques can be carried out without necessarily using expensive software.

scholarly journals ANALYSIS OF THE ECONOMIC SITUATION IN WESTERN EUROPE

2021 ◽  
pp. 106-110
Author(s):  
L. M. Rubaeva ◽  
A. A. Datieva
Keyword(s):  
Comparative Analysis ◽  
Social Development ◽  
Western Europe ◽  
Developed Countries ◽  
Economic Situation ◽  
Economic Factors ◽  
The United Kingdom ◽  
Macroeconomic Indicators ◽  
The Relationship ◽  
Socio Economic Factors

The article considers the issue of achieving the most stable socio-economic situation in the countries of Western Europe. The paper highlights socio-economic factors that characterize states with a developed economic system. The authors make a comparative analysis of the macroeconomic indicators of countries with a developed socio-economic situation: Germany, France and the United Kingdom. The study notes the relationship between the sectors of the economy that have allowed developed countries to achieve the greatest results at present time. Based on the study, the authors identify the main provisions that stimulate the economic and social development of the considered states.

scholarly journals Logit analysis of socio-economic factors influencing people to become fishermen in the central region of Ghana

2011 ◽  
Vol 56 (1) ◽  
pp. 55-64 ◽  
Author(s):  
Henry Acquah ◽  
Isaac Abunyuwah
Keyword(s):  
Central Region ◽  
Weather Conditions ◽  
Structured Interview ◽  
Economic Factors ◽  
Logit Analysis ◽  
Access To Credit ◽  
The People ◽  
Study Results ◽  
Credit Lack ◽  
Socio Economic Factors

This study analyzes the socio-economic factors that influence people?s decision to become fishermen in the central region of Ghana. Using a well structured interview schedule, a random sample of 98 people from Elmina in the central region of Ghana was selected for the study. Results from the descriptive statistics analysis of respondents identified fishing as a family business, minimum skills requirement and ready market for fish demand as factors that motivated majority of the people into fishing. Lack of storage facilities, access to credit, lack of government assistance and unpredictable changes in weather conditions on sea were the main constraints to fishing activities. Results from the logistic regression model indicated that household size and access to credit were significant factors that positively influenced people?s decision to become fishermen. The regression analysis further revealed that engaging in other income generating activity and being educated significantly reduces the probability to start fishing business.

scholarly journals Analysis of lockdown perception in the United States during the COVID-19 pandemic

2021 ◽  
Author(s):  
Francesco Vincenzo Surano ◽  
Maurizio Porfiri ◽  
Alessandro Rizzo
Keyword(s):  
United States ◽  
Temporal Analysis ◽  
The United States ◽  
Economic Effects ◽  
Economic Factors ◽  
Political Orientations ◽  
Containment Measures ◽  
Spatio Temporal ◽  
Different Parts ◽  
Socio Economic Factors

AbstractContainment measures have been applied throughout the world to halt the COVID-19 pandemic. In the United States, several forms of lockdown have been adopted in different parts of the country, leading to heterogeneous epidemiological, social, and economic effects. Here, we present a spatio-temporal analysis of a Twitter dataset comprising 1.3 million geo-localized Tweets about lockdown, from January to May 2020. Through sentiment analysis, we classified Tweets as expressing positive or negative emotions about lockdown, demonstrating a change in perception during the course of the pandemic modulated by socio-economic factors. A transfer entropy analysis of the time series of Tweets unveiled that the emotions in different parts of the country did not evolve independently. Rather, they were mediated by spatial interactions, which were also related to socio-ecomomic factors and, arguably, to political orientations. This study constitutes a first, necessary step toward isolating the mechanisms underlying the acceptance of public health interventions from highly resolved online datasets.

scholarly journals Multi-Temporal Analysis of Forest Fire Probability Using Socio-Economic and Environmental Variables

2019 ◽  
Vol 11 (1) ◽  
pp. 86 ◽  
Author(s):  
Sea Jin Kim ◽  
Chul-Hee Lim ◽  
Gang Sun Kim ◽  
Jongyeol Lee ◽  
Tobias Geiger ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Random Forest ◽  
South Korea ◽  
Human Activity ◽  
Forest Fire ◽  
Roc Curve ◽  
Temporal Analysis ◽  
Economic Factors ◽  
Multi Temporal ◽  
Socio Economic Factors

As most of the forest fires in South Korea are related to human activity, socio-economic factors are critical in estimating their probability. To estimate and analyze how human activity is influencing forest fire probability, this study considered not only environmental factors such as precipitation, elevation, topographic wetness index, and forest type, but also socio-economic factors such as population density and distance from urban area. The machine learning Maximum Entropy (Maxent) and Random Forest models were used to predict and analyze the spatial distribution of forest fire probability in South Korea. The model performance was evaluated using the receiver operating characteristic (ROC) curve method, and models’ outputs were compared based on the area under the ROC curve (AUC). In addition, a multi-temporal analysis was conducted to determine the relationships between forest fire probability and socio-economic or environmental changes from the 1980s to the 2000s. The analysis revealed that the spatial distribution was concentrated in or around cities, and the probability had a strong correlation with variables related to human activity and accessibility over the decades. The AUC values for validation were higher in the Random Forest result compared to the Maxent result throughout the decades. Our findings can be useful for developing preventive measures for forest fire risk reduction considering socio-economic development and environmental conditions.

DINAMIKA KELOMPOK TANI ANUGERAH MOLLO DI DESA NETPALA KECAMATAN MOLLO UTARA KABUPATEN TIMOR TENGAH SELATAN

2020 ◽  
Vol 21 (1) ◽  
pp. 71-80
Author(s):  
Tanggu Dedo Yeremias ◽  
Ernantje Hendrik ◽  
Ignatius Sinu
Keyword(s):  
Formal Education ◽  
Secondary Data ◽  
Nonparametric Test ◽  
Primary Data ◽  
Economic Factors ◽  
Dynamic Level ◽  
South Central ◽  
Group Members ◽  
Relationship Of ◽  
Socio Economic Factors

ABSTRACT This research has been carried out in the Anugerah Mollo Farmer Group, in Netpala Village, North Mollo District, South Central Timor Regency, starting in March - April 2019. This study aims to determine: (1) The dynamic level of the Anugerah Mollo Farmer Group in Netpala Village, North Mollo District, South Central Timor Regency, (2) Relationship between Socio-economic factors of farmer group members and the level of dynamics of the Anugerah Mollo Farmer Group in Netpala Village, North Mollo District, South Central Timor Regency. Determination of the location of the study carried out intentionally (purposive sampling) The type of data collected is primary data obtained from direct interviews with respondents guided by the questionnaire, while secondary data is obtained from the relevant agencies. To find out the first purpose of the data analyzed using a Likert scale, to find out the second purpose of the data analyzed using the Sperman Rank statistical Nonparametric test. The results of this study indicate that: (1) The level of dynamism of the Anugerah Mollo Farmer Group in Netpala Village, North Mollo District, South Central Timor Regency, is in the very dynamic category of 84%, (2) The relationship of socio-economic factors is only one of the five variables that are significantly related namely land area with a coefficient of rs 0.278 and t = 1.782 count greater than t table 1.699 (p> 0.05), while other social factors such as age, formal education, number of family dependents, and experience of farming show no significant relationship with the level of dynamism of Anugerah Mollo Farmers Group in Netpala Village.

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