The Dynamics of Agricultural Productivity and Industrial Transformation in Transition Countries

Relying on the frontier production approach, we investigated the performance of the agricultural sector in 28 transition countries and its changes over time, especially focusing on the dynamics of productivity changes and the effects of reform policy. Our findings are: (i) Asian and CEE transition countries performed better than CIS countries, while the performance improvement of CEE countries seems to be more prominent compared to that of Asian and CIS countries; (ii) The productivity growth is mainly attributable to the technical progress, particularly in CEE countries; (iii) Reform policy and industrial transformation seems to have positive effects on the performance of agricultural sector and its changes; (iv) The initial conditions do matter.transition countries, efficiency, productivity, directional distance function, agricultural reform, initial condition, industrial transformation, Productivity Analysis,

Legendrian singular links and singular connected sums

We study Legendrian singular links up to contact isotopy. Using a special property of the singular points, we define the singular connected sum of Legendrian singular links. This concept is a generalization of the connected sum and can be interpreted as a tangle replacement, which provides a way to classify Legendrian singular links. Moreover, we investigate several phenomena only occur in the Legendrian setup

An overview of the Daya Bay Reactor Neutrino Experiment

The Daya Bay Reactor Neutrino Experiment discovered an unexpectedly large neutrino oscillation related to the mixing angle $\theta_{13}$ in 2012. This finding paved the way to the next generation of neutrino oscillation experiments. In this article, we review the history, featured design, and scientific results of Daya Bay. Prospects of the experiment are also described.Comment: 18 pages, 5 figures. An overview to appear in the Special Issue on neutrino oscillations of Nuclear Physics

The Dynamics of Productivity Changes in Agricultural Sector of Transition Countries

Relying on frontier production approach (e.g., Luenberger's shortage function), we investigated the performance of agricultural sector in transition countries and its changes over time, especially focusing on the dynamics of productivity changes. We found that; (i) CEE countries have improved their performance during the sample period whereas CIS have not; (ii) productivity changes in the last decade was attributable to the technical progress; (iii) overall performance was decelerated for the second 5-year sub-period (1997-2001) in both regions; (iv) agricultural reform has positive effects on the productivity and its components especially in CEE countries.transition countries, productivity, directional distance function, agricultural reform, Productivity Analysis,

Amortising the Cost of Mutation Based Fault Localisation using Statistical Inference

Mutation analysis can effectively capture the dependency between source code and test results. This has been exploited by Mutation Based Fault Localisation (MBFL) techniques. However, MBFL techniques suffer from the need to expend the high cost of mutation analysis after the observation of failures, which may present a challenge for its practical adoption. We introduce SIMFL (Statistical Inference for Mutation-based Fault Localisation), an MBFL technique that allows users to perform the mutation analysis in advance against an earlier version of the system. SIMFL uses mutants as artificial faults and aims to learn the failure patterns among test cases against different locations of mutations. Once a failure is observed, SIMFL requires either almost no or very small additional cost for analysis, depending on the used inference model. An empirical evaluation of SIMFL using 355 faults in Defects4J shows that SIMFL can successfully localise up to 103 faults at the top, and 152 faults within the top five, on par with state-of-the-art alternatives. The cost of mutation analysis can be further reduced by mutation sampling: SIMFL retains over 80% of its localisation accuracy at the top rank when using only 10% of generated mutants, compared to results obtained without sampling