573 research outputs found

    Unconventional critical scaling of magnetization in uranium ferromagnetic superconductors UGe2_2 and URhGe

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    We report a dc magnetization study of the critical phenomenon around the ferromagnetic transition temperature T_C in high-quality single crystals of uranium ferromagnetic superconductors UGe2 and URhGe. The critical exponents, beta for the temperature dependence of the magnetization below T_C, gamma for the magnetic susceptibility, and delta for the magnetic isothermal at T_C have been determined with a modified Arrott plot, a Kouvel-Fisher plot, and the scaling analysis. Magnetization in the ferromagnetic state has strong uniaxial magnetic anisotropy in the two compounds. However, the universality class of the critical phenomena do not belong to the three dimensional (3D) Ising system. Although the values of beta in UGe2 and URhGe are close to those in the 3D magnets, the values of gamma are close to unity, that expected from the mean field theory. Similar critical exponents have been reported previously for the 3D Ising ferromagnet UIr where superconductivity appears under high pressure. The critical behavior may be limited to a very narrow Ginzburg critical region of 1 mK because of the strong itinerant character of the 5f electrons in the ferromagnetic superconductor UCoGe where the mean field behavior of the magnetization has been reported. The unconventional critical scaling of magnetization in UGe2, URhGe and UIr cannot be explained via previous approaches to critical phenomena. The ferromagnetic correlation between the 5f electrons differs from that in the 3D Ising system and this difference may be a key point for the understanding of the ferromagnetism where superconductivity emerges.Comment: 8 pages, 5 figure

    Comparing technical efficiency of organic and conventional coffee farms in Nepal using data envelopment analysis (DEA) approach

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    Data Envelopment Analysis (DEA) approach used to estimate technical efficiency and followed by regressing the technical efficiency scores to farm specific characters under tobit regression model. Primary data was collected from random samples of 240 (120 from each) coffee famers. Mean technical efficiency score was 0.89 and 0.83 in organic and conventional coffee farming respectively. Farms operating under CRS, DRS and IRS were 31.67, 3.83 and 37.5% respectively in organic coffee and 29.17, 25 and 45.83% respectively in conventional farming areas. Tobit regression showed the variation in technical efficiency was related education, farm experience and training/extension services and excess to credit.Production frontier, Resource use, Technical efficiency, Organic, Altitude, Productivity Analysis,

    Analysis of Technical Efficiency of Small-Scale Rice Farmers in Indonesia

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    In this study, we analyzed the performance of small-scale rice farmers who used hand tractors in Jember Regency, Indonesia. Data were collected from 144 small-scale rice farmers in six districts through the use of a questionnaire in September 2015. The Data Envelopment AnalysisSlack-Based Model (DEA-SBM) was used to calculate the technical efficiency of small-scale rice farmers based on seven inputs and one output by determining Overall Technical Efficiency (OTE), Pure Technical Efficiency (PTE), and Scale Efficiency (SE). The results showed that out of 144 small-scale rice farmers, only nine farmers and 14 farmers were evaluated as strongly efficient and weakly efficient, respectively, while the rest were categorized as inefficient. The average values for OTE, PTE, and SE were 0.41, 0.63, and 0.61, respectively. The observed inefficiency was because of both poor input utilization (managerial inefficiency) and failure to operate at an optimal scale (scale inefficiency). Such analysis of technical efficiency can encourage small-scale rice farmers to enhance their performance and profitability

    Applications of the new Remote Sensing Method to the Forest Biomass Estimation

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    For accurate measurement of forest biomass in the Akazawa Forest Reserve, this study analyzed texture measures derived from GeoEye-1 satellite data using the individual tree crown (ITC) method. On this basis, canopy area, tree tops and tree species of individual trees were delineated. Canopy area was used to calculate the DBH of trees in canopy layer based on canopy-DBH curve in this stand. In this study, the estimation models, between DBH and height, and between canopy area and DBH were developed by linear regression using forest survey data. Then according to the results of satellite data interpreted the biomass of every tree was calculated by biomass expansion factor (BEF). This method was verified against the survey data from old–growth Chamaecyparis obtusa stand composed of various cover types. For Chamaecyparis obtusa, the accuracy of biomass estimation was higher than 84%. However, the accuracy of Chamaecyparis pisifera was less than 60%, because some Chamaecyparis pisifera trees were misidentified as Chamaecyparis obtusa, and canopy area of Chamaecyparis pisifera was underestimated in the high-density stand. For Thujopsis dolabrata, the accuracy ranged from 22.4 % to 78.9%, and from 63.4% to 84.6% for broad-leaved trees, because many of them were understory. These results indicated that estimation of old-growth forest biomass based on high resolution satellite data, might be validated for estimating biomass at the individual tree level improved by developing and applying forest stratum–specific models with the ITC-survey data as a bridging reference in addition to spectral information. This approach is useful for biomass estimation whether is used to calculate biomass of individual tree or forest.ArticleThe International Journal of Sciences. 2(8):1-13 (2013)journal articl
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