5,873 research outputs found

    DETERMINANTS OF PART-TIME FARMING AND ITS EFFECT ON FARM PRODUCTIVITY AND EFFICIENCY

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    Little attention has been given in the agricultural economics literature to the impact of off-farm work on farm productivity and efficiency. More knowledge about what determines part-time farming and whether farm productivity and efficiency are affected by part-time farming could help policy makers introduce better targeted rural development policies. This paper aims to fill the above-mentioned gaps by first analysing factors that influence the choice of off-farm work; and then examining how off-farm work influences productivity and technical efficiency at the farm level. An unbalanced panel data set from 1991 to 2005 from Norwegian grain farms is used for this purpose. The results show that the likelihood of off-farm work and the share of time allocated to it increase with increasing age (up to 39 years), and with low relative yields (compared to others farms in the surrounding area/region). The level of support payments is not significantly associated with the extent of off-farm work. Large-scale farms and single farmers tend to have a lower likelihood of off-farm work. Average technical efficiency was found to be 79%. Farmers with low variability in farm revenue were found to be more technically efficient than farmers with high revenue variability. We did not find any evidence of off-farm work share affecting farm productivity − the predicted off-farm work share was not statistically significant. In other words, we did not find any systematic difference in farm productivity and technical efficiency between part-time and full-time farmers.off-farm work, productivity, efficiency, unobserved heterogeneity, panel data, Farm Management,

    Electrical Conductivity for Evaluating Fabric and Mechanical Behavior of Granular Soils

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    In this study, an auto-compensation conductivity measurement system has been developed. This system is expected to offer a possible means for describing the granular soil fabric and mechanical behaviors. A series of cyclic triaxial compression, extension, and unloading tests with resistance measurement were performed. The correlation between granular soil friction angle φ, and vertical formation factor, Fv under maximum shear stress ratio has been studied. The test results have shown that the electrical conductivity could be used to evaluate the fabric behavior during the process of loading. The fabric ellipsoid function, which has been used to simulate the orientation strength for sedimentation granular soil, was described

    Finite-Size Scaling in Two-dimensional Continuum Percolation Models

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    We test the universal finite-size scaling of the cluster mass order parameter in two-dimensional (2D) isotropic and directed continuum percolation models below the percolation threshold by computer simulations. We found that the simulation data in the 2D continuum models obey the same scaling expression of mass M to sample size L as generally accepted for isotropic lattice problems, but with a positive sign of the slope in the ln-ln plot of M versus L. Another interesting aspect of the finite-size 2D models is also suggested by plotting the normalized mass in 2D continuum and lattice bond percolation models, versus an effective percolation parameter, independently of the system structure (i.e. lattice or continuum) and of the possible directions allowed for percolation (i.e. isotropic or directed) in regions close to the percolation thresholds. Our study is the first attempt to map the scaling behaviour of the mass for both lattice and continuum model systems into one curve.Comment: 9 pages, Revtex, 2 PostScript figure

    Formal Model Engineering for Embedded Systems Using Real-Time Maude

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    This paper motivates why Real-Time Maude should be well suited to provide a formal semantics and formal analysis capabilities to modeling languages for embedded systems. One can then use the code generation facilities of the tools for the modeling languages to automatically synthesize Real-Time Maude verification models from design models, enabling a formal model engineering process that combines the convenience of modeling using an informal but intuitive modeling language with formal verification. We give a brief overview six fairly different modeling formalisms for which Real-Time Maude has provided the formal semantics and (possibly) formal analysis. These models include behavioral subsets of the avionics modeling standard AADL, Ptolemy II discrete-event models, two EMF-based timed model transformation systems, and a modeling language for handset software.Comment: In Proceedings AMMSE 2011, arXiv:1106.596

    Mosquitoes Collected In South And East Kalimantan

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    Pengumpulan nyamuk dalam waktu singkat di sembilan tempat di Kalimantan Timur dan Selatan menghasilkan 57 species dari 11 genera. Species yang terbanyak dikumpulkan ialah dari genus Culex 27 percent Mansonia 16 percent. Anopheles 16 percent, Aedes 12 percent, Armigeres 7 percent, Mimomia 7 percent, Uranotaenia 7 percent, Hodgesia. Tripteroides, Heizmania dan Culiseta masing-masing 2 percent

    Ground-Penetrating Radar Theory and Application of Thin-Bed Offset-Dependent Reflectivity

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    Offset-dependent reflectivity or amplitude-variationwith- offset (AVO) analysis of ground-penetrating radar (GPR) data may improve the resolution of subsurface dielectric permittivity estimates. A horizontally stratified medium has a limiting layer thickness below which thin-bed AVO analysis is necessary. For a typical GPR signal, this limit is approximately 0.75 of the characteristic wavelength of the signal. Our approach to modeling the GPR thin-bed response is a broadband, frequency-dependent computation that utilizes an analytical solution to the three-interface reflectivity and is easy to implement for either transverse electric (TE) or transverse magnetic (TM) polarizations. The AVO curves for TE and TM modes differ significantly. In some cases, constraining the interpretation using both TE and TM data is critical. In two field examples taken from contaminated-site characterization data, we find quantitative thin-bed modeling agrees with the GPR field data and available characterization data
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