摘要：Owing to rapid advances in the next-generation sequencing technology, the cost of DNA sequencing has been reduced by over several orders of magnitude. However, genomic sequencing of individuals at the population scale is still restricted to a few model species due to the huge challenge of constructing libraries for thousands of samples. Meanwhile, pooled sequencing provides a cost-effective alternative to sequencing individuals separately, which could vastly reduce the time and cost for DNA library preparation. Technological improvements, together with the broad range of biological research questions that require large sample sizes, mean that pooled sequencing will continue to complement the sequencing of individual genomes and become increasingly important in the foreseeable future. However, simply mixing samples together for sequencing makes it impossible to identify reads that belongs to each sample. Barcoding technology could help to solve this problem, nonetheless, currently, barcoding every sample is costly especially for large-scale samples. An alternative to barcoding is combinatorial pooled sequencing which employs pooling pattern rather than short DNA barcodes to encode each sample. In combinatorial pooled sequencing, samples are mixed into few pools according to a carefully designed pooling strategy which allows the sequencing data to be decoded to identify the reads that belongs to the sample that are unique or rare in the population. In this review, we mainly survey the experiment design and decoding procedure for the combinatorial pooled sequencing applied in rare variant and rare haplotype carriers screening, complex genome assembling and single individual haplotyping.

摘要：Interwell connectivities are fundamental parameters required to manage waterfloods in oil reservoirs. Data-driven models, such as the capacitance-resistance model （CRM）, are fast tools to estimate these parameters from time-correlations of input （injection rates） and output （production rates） signals. Noise and structure of the input time-series impose limits on the information that can be extracted from a given data-set. This work uses the CRM to study general prescriptions for the design of input signals that enhance the information content of injection/production data in the estimation of well-to-well interactions. Numerical schemes and general features of the optimal input signal strategy are derived for this problem.

摘要：The paper is devoted to the elastostatic calibration of industrial robots, which is used for precise machining of large-dimensional parts made of composite materials. In this technological process, the interaction between the robot and the workpiece causes essential elastic deflections of the manipulator components that should be compensated by the robot controller using relevant elastostatic model of this mechanism. To estimate parameters of this model, an advanced calibration technique is applied that is based on the non-linear experiment design theory, which is adopted for this particular application. In contrast to previous works, it is proposed a concept of the user-defined test-pose, which is used to evaluate the calibration experiments quality. In the frame of this concept, the related optimization problem is defined and numerical routines are developed, which allow generating optimal set of manipulator configurations and corresponding forces/torques for a given number of the calibration experiments. Some specific kinematic constraints are also taken into account, which insure feasibility of calibration experiments for the obtained configurations and allow avoiding collision between the robotic manipulator and the measurement equipment. The efficiency of the developed technique is illustrated by an application example that deals with elastostatic calibration of the serial manipulator used for robot-based machining.