The present study proposes a methodology to identify spatial patterns in airborne radioactive particles in Europe. The methodology is based on transforming the activity concentrations in the set of stations for each month (monthly index), due to the tightly spaced sampling intervals (daily to monthly), in combination with hierarchical and non-hierarchical clustering approaches, due to the lack of a priori knowledge of the number of clusters to be created. Three different hierarchical cluster methodologies are explored to set the optimal number of clusters necessary to initialize the non-hierarchical one (k-means). To evaluate this methodology, cosmogenic beryllium-7 ((7)Be) data, collected between 2007 and 2010 at 19 sampling stations in European Union (EU) countries and stored in the Radioactivity Environmental Monitoring (REM) database, are used. This methodology yields a solution with three distinguishable clusters (south, central and north), each with a different evolution of the (7)Be monthly index. Clear differences between monthly indices are shown in both intensity and time trends, following a latitudinal distribution of the sampling stations. This cluster result is evaluated performing ANOVA analysis, considering the original (7)Be activity concentrations grouped in each cluster. The statistical results (among clusters and sampling stations within clusters) confirm the spatial distribution of (7)Be in Europe, and, hence, reinforce the use of this methodology. Finally, the impact of tropopause height on this grouping is successfully tested, suggesting its influence on the spatial distribution of (7)Be in Europe. For airborne radioactive particles the analysis gave valuable results that improve knowledge of these atmospheric compounds in Europe. Hence, this work addresses a methodology to a grouping of airborne sampling stations, 1) allowing a better understanding of the distribution of (7)Be activity concentrations in the EU, and 2) serving as a basis for further investigation of the heterogeneity of airborne radioactivity concentrations in Europe.
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http://dx.doi.org/10.1016/j.jenvrad.2016.02.006 | DOI Listing |
Plant Dis
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LSU AgCenter, Plant Pathology and Crop Physiology, Baton Rouge, Louisiana, United States.
In July 2023, panicle and leaf blight-like symptoms were observed from the rice () variety, PVL03, in research field plots in Louisiana (Rayne, LA 70578, USA; 30.21330⁰ N, 92.37309⁰ W).
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Group for Medical Entomology, Centre of Excellence for Food- and Vector-Borne Zoonoses, Institute for Medical Research, National Institute of Republic of Serbia, University of Belgrade, Belgrade, Serbia.
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January 2025
Michigan State University, Dept. Plant, Soil and Microbial Sciences, 105 CIPS, East Lansing, Michigan, United States, 48910;
Grape downy mildew, caused by poses a threat to grape cultivation globally. Early detection of fungicide resistance is critical for effective management. This study aimed to assess the prevalence and distribution of mutations associated with resistance to Quinone oxide inhibitors (QoI, FRAC 11), Quinone inside inhibitors (QiIs, FRAC 21, cyazofamid), Carboxylic acid amides (CAA, FRAC 41), and Quinone inside and outside inhibitor, stigmatellin binding mode (QioSI, FRAC 45, ametoctradin) in populations in the eastern United States and Canada; and evaluate whether these mutations are linked to fungicide resistance correlate with specific clades.
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Department of Medicine & Pharmacology, Texas A & M University, College Station, TX 77843, United States.
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January 2025
Zhanjiang Experimental Station, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang, 524013, China.
Background: The Leizhou Black Goat (LZBG), a prominent breed in tropical China's meat goat industry, frequently exhibits inherent muscle atrophy and malnutrition-related traits. Particularly, muscles critical for support, such as the legs, often display severe symptoms. This study aimed to investigate the differential genes and signaling pathways influencing muscle development and atrophy across various muscle locations in LZBG from a muscular atrophy-affected family.
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