902 resultados para Extended rank likelihood
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Factor markets are a central issue in analyses of farm development and of agricultural sector vitality. Among the different production factors, land is one of the most studied. Several studies seek to estimate the effect of government policy payments on land value or land rental prices. The studies mostly agree that government payments and other types of policy support are significant in explaining land prices and account for a large share of them. In October 2011, the European Commission published a new policy proposal for the common agricultural policy (CAP) up to 2020. The proposed regulation includes a shift from historical to regional payments. The objective of this paper is to provide an ex ante analysis of the impact of the new CAP policy instruments on the land market. In particular, the effect of the regionalisation of payments in Italy is examined. The analysis is based on the use of a mathematical programming model to simulate the changes in land demand for a farm in Emilia Romagna. The results highlight the relevance of the new policy mechanism in determining a change in land demand. Yet the effect is highly dependent on initial ownership of entitlements under the historical payment scheme.
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Aim: Familial Hypercholesterolemia (FH) is a common autosomal dominant disorder, caused by mutations in genes involved in cholesterol’s clearance (LDLR, APOB, PCSK 9). Clinical diagnosis is usually based on high total cholesterol or LDL-C levels and family history of premature coronary heart disease. Using an extended lipid profile of paediatric dyslipidemic patients, we aim to identify biomarkers for a better diagnosis of FH in clinical settings.
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This study was carried out to detect differences in locomotion and feeding behavior in lame (group L; n = 41; gait score ≥ 2.5) and non-lame (group C; n = 12; gait score ≤ 2) multiparous Holstein cows in a cross-sectional study design. A model for automatic lameness detection was created, using data from accelerometers attached to the hind limbs and noseband sensors attached to the head. Each cow's gait was videotaped and scored on a 5-point scale before and after a period of 3 consecutive days of behavioral data recording. The mean value of 3 independent experienced observers was taken as a definite gait score and considered to be the gold standard. For statistical analysis, data from the noseband sensor and one of two accelerometers per cow (randomly selected) of 2 out of 3 randomly selected days was used. For comparison between group L and group C, the T-test, the Aspin-Welch Test and the Wilcoxon Test were used. The sensitivity and specificity for lameness detection was determined with logistic regression and ROC-analysis. Group L compared to group C had significantly lower eating and ruminating time, fewer eating chews, ruminating chews and ruminating boluses, longer lying time and lying bout duration, lower standing time, fewer standing and walking bouts, fewer, slower and shorter strides and a lower walking speed. The model considering the number of standing bouts and walking speed was the best predictor of cows being lame with a sensitivity of 90.2% and specificity of 91.7%. Sensitivity and specificity of the lameness detection model were considered to be very high, even without the use of halter data. It was concluded that under the conditions of the study farm, accelerometer data were suitable for accurately distinguishing between lame and non-lame dairy cows, even in cases of slight lameness with a gait score of 2.5.
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At head of title: 93d Congress, 1st session, Senate, Executive report ; no. 93-16.
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Federal Highway Administration, Office of Safety and Traffic Operations, Washington, D.C.
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Mode of access: Internet.
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"July 1955."
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Mode of access: Internet.
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"This report was prepared for the Unemployment Insurance Service, U.S. Department of Labor under Contract Number 99-7-0805-04-138-01 with Mathematica Policy Research, Inc. The authors of this report are John L. Czajka, Sharon K. Long and Walter Nicholson ..."
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Mode of access: Internet.
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Transportation Department, Office of Systems Engineering, Washington, D.C.