Theoretical analyses of testing efficiency in long-term breeding of poplar

The major goal for long-term poplar breeding can be formulated as maximizing annual progress in Group Merit Gain at a given annual budget （GMG/Y＊）. To evaluate different breeding scenarios, a deterministic simulator BREEDING CYCLE ANALYZER covering the most important aspects （gain, cost, time, technique, and gene diversity） of a full breeding cycle was used. The breeding strategies considered was based on pairwise crossing of the selected breeding population and balanced within family selection for the next breeding population. A main scenario and a number of alternative scenarios within these constraints were evaluated using estimates of the best available inputs for poplars. In focus was a comparison between three different testing scenarios for selecting the parents mated to create future breeding generations, thus selecting based on phenotype, clone test or progeny test. For the main scenario, the highest GMG/Y, and the optimal selection age for clone, phenotype and progeny strategies were 0.7480 %, 0.6989% and 0.4675%; 7, 6, and 11 years respectively. Clone test was best except when heritability was high, plant price was high or total budget was low; phenotype strategy was the second except for the case of extremely low narrow-sense heritability, for which the progeny strategy was a little more efficient than phenotype strategy. GMG/Y was markedly affected by narrow-sense heritability, additive variance at mature age, rotation age, plant-dependent cost, total budget and the time needed to produce the test plants, while diversity loss and recombination cost had rather weak effect on GMG/Y. Short rotation age and cheap testing cost favoured all three testing strategies. Comparably short rotation age, low plant-dependent cost and high total budget seem to promote early selection for progeny strategy.

A new method for improving efficiency of protocol testing

Traditional solutions have encountered some bottleneck in improving the efficiency of protocol testing.A novel method that records the test sequence dynamically is proposed.Three dynamically reordering algorithms are brought forward in line with different fault conditions.The impact of the new method of testing efficiency is also presented.Simulation results demonstrate that the proposed solution is better than the traditional ones in terms of testing efficiency.

Flexible,efficient,and accurate tests for epidemics

Group testing involves discovering a small subset of distinguished subjects from a large population while efficiently reducing the total number of tests.It has been widely used for industrial testing,information technology,and biology,especially epidemic screening.Tests,in reality,are noisy for the presence of false outcomes.Some tests are accurate but time-consuming,while others are cheaper but less accurate.Exactly which test to use is constrained by various considerations,such as availability,cost,accuracy,and efficiency.In this paper,we propose flexible,efficient,and accurate tests(FEATs).FEATs are based on group testing with simple but careful designs by incorporating ideas such as close contact cliques and repeated tests.FEATs could dramatically improve the efficiency or accuracy of existing tests.For example,for accurate but slow tests,the FEAT can improve efficiency multiple times without compromising accuracy.On the other hand,for fast but inaccurate tests,the FEAT can sharply reduce the false-negative rate(FNR)and significantly increase efficiency.Theoretical justifications are provided.We point out some scenarios where the FEAT can be effectively employed.