scholarly journals КЛАСТЕРНИЙ АНАЛІЗ УРОЖАЙНОСТІ СОРТІВ ТА ГІБРИДІВ РІПАКУ ОЗИМОГО В РІЗНИХ АГРОКЛІМАТИЧНИХ ЗОНАХ УКРАЇНИ

2017 ◽  
pp. 7-12
Author(s):  
А. В. Мельник ◽  
О. І. Присяжнюк ◽  
І. Л. Бондарчук
Keyword(s):  
Cluster Analysis ◽  
Central Region ◽  
High Performance ◽  
Winter Period ◽  
Western Region ◽  
Eastern Region ◽  
Winter Rape ◽  
Climatic Zones ◽  
Climatic Regions ◽  
Current Selection

Обґрунтовано використання кластерного аналізу для підбору сортів та гібридів ріпаку озимого сучасної селекції. Дослідження проводились у 2013–2015 рр. у чотирьох різних агрокліматичних регіонах України. За вирощування в господарствах різних сортів та гібридів потрібно уникати підбору для центрального регіону Клеопатра, ПР44В30, ДК Секвоя, Демерка та ПР45Д05. Для господарств південного регіону небажаним є поєднання двох груп сортів, а саме: Клеопатра, Черемош, НК Октан та ПР45Д05 або ж: Снігова королева, Джампер, Сітро, Демерка, Абакус, Белана, ПР44В30, ДК Секвоя та ДК Секюр. Для західного регіону близькими за продуктивністю в розрізі років досліджень є Клеопатра, ДК Секюр, НК Октан, ПР45Д06, ДК Секвоя та Сітро, а для східного регіону  відповідно: Клеопатра, ПР44В30, ДК Секюр, Снігова королева та Сітро. Тобто сорти та гібриди з різних груп кластерів можна висівати в умовах одного господарства, а от в межах однієї групи кластерів – небажано. The application of cluster analysis for the assortment of winter rape varieties and hybrids of current selection has been grounded. The research was conducted in 2013–2015 in four different agro-climatic regions of Ukraine. To get a stable and high performance of winter rape under the conditions of major agro-climatic zones of cultivation we need to adhere to the principles of production saturation with different varieties and hybrids to reduce the risk of loss of crops in the autumn–winter period and harvest shortfall due to the unfavorable factors of environment. For the farm cultivation of different varieties and hybrids, we should avoid selecting for the central region Cleopatra PR44V30, DK Sequoia, and Demerka and PR45D05. For the farms of southern region, it is undesirable to combine two groups of varieties, namely Cleopatra, Cheremosh, NK Oktan and PR45D05 or Snow Queen, Jumper, Sitro, Demerka, Abakus, Belana, PR44V30, DK and DK Sequoia and DK Sekyur. For the western region Cleopatra, DK Sekyur, NK Oktan, PR45D05, DK Sequoia and Sitro are similar in performance in terms of years of the research, and for the eastern region, there are the following varieties of Cleopatra, PR44V30, DK Sekyur, Snow Queen and Sitro. We mean the varieties and hybrids with different groups of clusters can be sown under the conditions of one farm, but within the same group of clusters, it is undesirable.

scholarly journals Evaluation of some effectiveness elements of the pig breeding industry in Bulgaria, through cluster analysis

2019 ◽  
Vol 35 (1) ◽  
pp. 25-33
Author(s):  
Ivelina Zapryanova
Keyword(s):  
Cluster Analysis ◽  
Central Region ◽  
Western Region ◽  
North Central Region ◽  
North Central ◽  
The North ◽  
South Central ◽  
North Eastern ◽  
Central Regions ◽  
North Western

An evaluation was made of the effectiveness elements of the pig breeding industry in Bulgaria in the period 2001-2016, through cluster analysis. The studied period was divided in 3 subperiods, each one with three similar groups (clusters). Through application of cluster analysis, the proximity of the different administration regions in the country was defined in accordance with certain indicators of the pig breeding effectiveness. It was found that in the first cluster for the period 2001-2006 fall North-Western and South-Western region. The North-Eastern and North-Central region form the second cluster. The South-Eastern and South-Central region fall mainly into the third cluster. In the first cluster for the period 2007-2011, the North-Western, South-Western and South-Central regions have a priority with the lowest number of sold animals. The North-Eastern and the North-Central region, forming a third cluster, remain with the highest effectiveness of the pig farming. After the end of 2013 an aggregation of the sector began. For the period 2012-2016, the second cluster is formed from three regions - North-Western, South-Western, and South-Central in 2013.

scholarly journals The Age, Sex, and Geographical Distribution of Self-Reported Asthma Triggers on Children With Asthma in China

2021 ◽  
Vol 9 ◽  
Author(s):  
Changhao Zhang ◽  
Yan Kong ◽  
Kunling Shen
Keyword(s):  
Air Pollution ◽  
Geographical Distribution ◽  
Central Region ◽  
Tobacco Smoke ◽  
Action Plan ◽  
Western Region ◽  
Eastern Region ◽  
Allergen Sensitization ◽  
Children With Asthma ◽  
Asthma Triggers

Background: Asthma can be exacerbated by many triggers, and the heterogeneity of asthma triggers is clear among children with asthma. This study describes asthma triggers using a large-scale electronic dataset from the smartphone-based Chinese Children's Asthma Action Plan (CCAAP) app and aims to examine the difference in asthma triggers among different subgroups of children with asthma.Methods: Data from the smartphone-based CCAAP app between February 22, 2017, and November 23, 2020, were reviewed, and children with asthma who reported their asthma triggers were enrolled. Eight common asthma triggers were listed in the software: upper respiratory infection (URI), allergen sensitization, exercise, emotional disturbances, pungent odors, air pollution/smog, weather change, and tobacco smoke. We compared the incidence of asthma triggers among different subgroups (<6 years vs. 6–17 years; boy vs. girl; eastern region vs. central region vs. western region).Results: We enrolled 6,835 patients with self-reported asthma triggers. When compared by sex, boys had a higher proportion of exercise-triggered asthma than girls (boys vs. girls, 22.5 vs. 19.7%, p < 0.05). The proportion of patients <6 years of age with URI-triggered asthma was higher than that of patients 6–17 years of age (<6 vs. 6–17 years, 80.9 vs. 74.9%, p < 0.001). Patients 6–17 years of age were more likely than patients <6 years of age to report five of the asthma triggers: allergen sensitization (<6 vs. 6–17 years, 26.6 vs. 35.8%, p < 0.001), exercise (<6 vs. 6–17 years, 19.3 vs. 23.7%, p < 0.001), pungent odors (<6 vs. 6–17 years, 8.8 vs. 12.7%, p < 0.001), air pollution/smog (<6 vs. 6–17 years, 9.4 vs. 16.2%, p < 0.001), and tobacco smoke (<6 vs. 6–17 years, 3.5 vs. 5.3%, p < 0.001). In subgroups based on geographical distribution, asthma triggering of allergen sensitization was reported to be the most common in patients from the eastern region (eastern region vs. central region vs. western region, 35.0 vs. 24.6 vs. 28.0%, p < 0.001). Exercise-triggered asthma was found to be the most prevalent among patients from the central region (eastern region vs. central region vs. western region, 21.6 vs. 24.8 vs. 20.4%, p < 0.05). However, the proportion of patients with air pollution/smog as an asthma trigger was the lowest among those from the western region (eastern region vs. central region vs. western region, 14.1 vs. 14.1 vs. 10.8%, p < 0.05).Conclusion: Children with asthma present different types of asthma triggers, both allergenic and nonallergenic. Age, sex, and geographical distribution affect specific asthma triggers. Preventive measures can be implemented based on a patient's specific asthma trigger.

scholarly journals Study on the Impact of Industrial Informatization on Economic Growth

2021 ◽  
Vol 251 ◽  
pp. 01113
Author(s):  
Jingying Zhu
Keyword(s):  
Economic Growth ◽  
Regression Model ◽  
Central Region ◽  
Positive Impact ◽  
Western Region ◽  
Eastern Region ◽  
Regional Heterogeneity ◽  
East Central ◽  
The Western Region ◽  
The Impact

Based on the basic regression model, this paper analyzes the impact of industrial informatization on China’s economic growth. The research shows that industrial informatization has a significant positive impact on China’s economic growth. Then, considering the significant differences in the development of industrial informatization in different regions of China, the paper further explores the regional heterogeneity of industrial informatization on economic growth. The results show that there are significant differences in the impact of industrial informatization on economic growth in the three major regions of East, Central and West. That is, industrial informatization has the strongest effect on promoting economic growth in the eastern region, followed by the central region, and industrial informatization has the weakest effect on promoting economic growth in the western region.

Delineation of climatic regions in Maine

1992 ◽  
Vol 22 (6) ◽  
pp. 801-811 ◽  
Author(s):  
R.D. Briggs ◽  
R.C. Lemin Jr.
Keyword(s):  
Cluster Analysis ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Multivariate Analyses ◽  
The State ◽  
Climatic Zones ◽  
Climatic Regions ◽  
Weather Stations ◽  
Components Analysis ◽  
Component Scores

As part of a project to develop a productivity-oriented site classification system for spruce and fir in Maine, multivariate analyses of meteorological data were used to partition the state into homogeneous climatic zones. Data were obtained for 63 weather stations reporting both temperature and precipitation in Maine during the period 1954–1983. Monthly means were computed for each variable over the period of record and summarized by four 3-month seasons. Eighty-two percent of the variation in the 37 variables was accounted for by the first three principal components. Cluster analysis identified eight homogeneous groups of weather stations. Results from the principal components analysis were spatially extrapolated across the state using stepwise regression to define the relationship between the first two principal components and the location variables latitude, longitude, and elevation. Principal component scores were predicted across the state along a grid composed of township line intersections. The Triangulated Irregular Network of ARCINFO, a geographic information system software package, was used to spatially summarize the predicted component scores into climagraphic maps. The combined results from cluster analysis and spatial extrapolation of the principal components analysis suggested the presence of four broad climatic regions, which were further subdivided into nine climatic zones. Overlap among the four regions and nine zones was evaluated with a jackknifed classification of a linear discriminant function. Ninety-four percent of the weather stations were correctly classified by climatic region, whereas 76% were correctly classified by climatic zone. The high degree of correspondence between climatic zones and biophysical regions reinforced results of the multivariate analyses.

Research on the Development of China’s Emission Reduction Based on Low Carbon Economy

2014 ◽  
Vol 962-965 ◽  
pp. 2381-2385 ◽  
Author(s):  
Ni Sha Jia ◽  
Yong Hui Han ◽  
Bo Hu
Keyword(s):  
Social Development ◽  
Central Region ◽  
Emission Reduction ◽  
Middle Level ◽  
Forecasting Model ◽  
Western Region ◽  
Eastern Region ◽  
Low Carbon ◽  
Low Carbon Economy ◽  
Carbon Economy

This paper built up a forecasting model for CO2 emission and calcutaled the CO2 emissions of 30 provinces (cities) in China. It’s been found that the CO2 emission amount varies greatly in different provinces (cities). We find that the capacity of energy conservation and emmision reduction of eastern region is best, the western region is in the middle level, while the central region is not good enough. Based on the above, this paper proposed concrete suggestions on energy saving and emission reduction.They are not only in line the national policies but also have took consideration of the economic and social development of different areas.

scholarly journals BIODIVERSITY, DISTRIBUTION, AND ABUNDANCE OF THE TROPICAL ANGUILLID EELS IN THE INDONESIAN WATERS

2008 ◽  
Vol 33 (2) ◽  
pp. 129-137 ◽  
Author(s):  
Hagi Yulia Sugeha ◽  
Sasanti Retno Suharti ◽  
Sam Wouthuyzen ◽  
Kurnaen Sumadhiharga
Keyword(s):  
Central Region ◽  
Western Region ◽  
Eastern Region ◽  
Genetic Analyses ◽  
Tropical Estuaries ◽  
Glass Eel ◽  
Indonesian Archipelago ◽  
Migration Mechanism ◽  
The Western Region ◽  
Inshore Migration

In order to understand biodiversity, distribution, and abundance among the tropical anguillid eels in the Indonesian waters, inshore migration mechanism of the juvenile anguillid eel (glass eel) to the estuaries of western, central, and eastern region of Indonesian waters were examined using both morphology and genetic analyses. A total of 9 species/sub species of anguillid eels (Anguilla bicolor bicolor, A. nebulosa nebulosa, A. bicolor pacifica, A. interioris, A. borneensis, A. celebesensis, A. marinorata, A. obscura and A. megastoma) were recognized to recruit at the mouth of 15 rivers through Indonesian archipelago. Species/subspecies diversity and distribution of recruiting juveniles differs in the estuaries of each region. In the western region that represented by estuary of Krueng Aceh, Batang Antokan, Air Kertaun, Cibaliung, Citanduy, Progo, and Pacitan Rivers, three species and sub species (A. bicolor bicolor, A. nebulosa nebulosa and A. bicolor pacifica) were found. In the central region that represented by estuary of Mahakam, Palu, Dumoga, Poigar, Bone, and Poso Rivers, five species and sub species (A. borneensis, A. celebesensis, A. marinorata, A. bicolor pacilica and A. interioris) were found. In the eastern region that represented by estuary of Akelamo and Pami Rivers, four species (A. marinorata, A. interioris, A. obscura and A. megastoma) were found. During the 6 months investigation from May to October 2005, abundance of the juveniles was higher in the central region compared with western and eastern regions. These results were suggested that inshore migration mechanism of tropical anguillid eels recruiting in tropical estuaries of Indonesian waters differs among regions.

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