scholarly journals Nutritional Management of The Transhumant Sheep and Goat in Greece

2020 ◽  
Vol 2 (4) ◽  
Author(s):  
Anna Siasiou ◽  
Ioannis Mitsopoulos ◽  
Konstantinos Galanopoulos ◽  
Vasiliki Lagka
Keyword(s):  
Natural Resources ◽  
Production System ◽  
Parametric Analysis ◽  
Farming System ◽  
Nutritional Management ◽  
Dairy Sheep ◽  
Mediterranean Countries ◽  
Extensive Farming ◽  
Goat Farming ◽  
Non Parametric

In Mediterranean countries dairy sheep and goat farming is based on grazing even though production system can vary from extensive, where nutrition is based on the exploitation of natural resources, to intensive, where nutrition can be a combination of grazing and parallel supplementation of feed.  Transhumance is an extensive farming system where herds are moved to uplands in order to exploit the mountainous rangelands. Purpose of this paper was to study the nutritional management of transhumant sheep and goat herds in Greece. Non parametric analysis was performed to a sample of 551 transhumant herds. The results revealed differences of the nutritional management performed between different species and breeds of the reared animals. More specifically nutrition of goats and indigenous mountainous breeds was based mainly on grazing even to lowlands while nutrition of sheep and improved dairy breeds tended to be more integrated with combination of grazing to supplementation of feed.     

Evaluating the Performance of Hedge Fund Strategies: A Non-Parametric Analysis

2015 ◽  
Author(s):  
Alessandra Canepa ◽  
Maria O. Gonzalez ◽  
Frank S. Skinner
Keyword(s):  
Parametric Analysis ◽  
Hedge Fund ◽  
Non Parametric

Het Hoge Kempen ruraal-industrieel transitielandschap

2019 ◽  
Vol 4 (3) ◽  
pp. 194-207
Author(s):  
PIET GELEYNS
Keyword(s):  
Large Scale ◽  
Western Europe ◽  
Farming System ◽  
Small Scale ◽  
Coal Miners ◽  
Garden Cities ◽  
World Heritage List ◽  
The World ◽  
Outstanding Universal Value ◽  
Extensive Farming

The Hoge Kempen rural industrial transition landscape: a layered landscape of Outstanding Universal Value? Up until the beginning of the 20th century, the eastern part of the Belgian province of Limburg was a sparsely populated and not very productive part of the country. The dominating heathland was maintained with sheep, which were an essential part of a small-scale extensive farming system. This all changed when coal was discovered in 1901. Seven large coalmines were established in a few decades, each one employing thousands of coal-miners. This also meant that entire new garden cities were built, to house the coal-miners and their families. The confrontation between the small-scale traditional land-use and the new large-scale industrial developments defines the landscape up to today. The scale and the force of the turnover are considered unprecedented for Western Europe, which is why it is being presented by Belgium for inclusion in the World Heritage List.

scholarly journals Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data

2017 ◽  
Vol 14 (2) ◽  
Author(s):  
Qihua Tan ◽  
Mads Thomassen ◽  
Mark Burton ◽  
Kristian Fredløv Mose ◽  
Klaus Ejner Andersen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Correlation Coefficient ◽  
Parametric Analysis ◽  
Time Course ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Microarray Time Course ◽  
Time Course Data ◽  
Generalized Correlation ◽  
Non Parametric

AbstractModeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.

Non-Parametric Analysis of Covariance

Biometrics ◽  
1995 ◽  
Vol 51 (3) ◽  
pp. 920 ◽  
Author(s):  
Stuart G. Young ◽  
Adrian W. Bowman
Keyword(s):  
Parametric Analysis ◽  
Analysis Of Covariance ◽  
Non Parametric
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