A consensus-based ensemble approach to improve transcriptome assembly

Background Systems-level analyses, such as differential gene expression analysis, co-expression analysis, and metabolic pathway reconstruction, depend on the accuracy of the transcriptome. Multiple tools exist to perform transcriptome assembly from RNAseq data. However, assembling high quality transcriptomes is still not a trivial problem. This is especially the case for non-model organisms where adequate reference genomes are often not available. Different methods produce different transcriptome models and there is no easy way to determine which are more accurate. Furthermore, having alternative-splicing events exacerbates such difficult assembly problems. While benchmarking transcriptome assemblies is critical, this is also not trivial due to the general lack of true reference transcriptomes. Results In this study, we first provide a pipeline to generate a set of the simulated benchmark transcriptome and corresponding RNAseq data. Using the simulated benchmarking datasets, we compared the performance of various transcriptome assembly approaches including both de novo and genome-guided methods. The results showed that the assembly performance deteriorates significantly when alternative transcripts (isoforms) exist or for genome-guided methods when the reference is not available from the same genome. To improve the transcriptome assembly performance, leveraging the overlapping predictions between different assemblies, we present a new consensus-based ensemble transcriptome assembly approach, ConSemble. Conclusions Without using a reference genome, ConSemble using four de novo assemblers achieved an accuracy up to twice as high as any de novo assemblers we compared. When a reference genome is available, ConSemble using four genome-guided assemblies removed many incorrectly assembled contigs with minimal impact on correctly assembled contigs, achieving higher precision and accuracy than individual genome-guided methods. Furthermore, ConSemble using de novo assemblers matched or exceeded the best performing genome-guided assemblers even when the transcriptomes included isoforms. We thus demonstrated that the ConSemble consensus strategy both for de novo and genome-guided assemblers can improve transcriptome assembly. The RNAseq simulation pipeline, the benchmark transcriptome datasets, and the script to perform the ConSemble assembly are all freely available from: http://bioinfolab.unl.edu/emlab/consemble/.

New Forms of Communities? The Constitution and Performance of Audiences in Digital Theater during the COVID-19 Pandemic

The Covid-19 pandemic plunged many theaters around the world into a temporary crisis and favored the rise of digital theater forms. This article investigates how the reception of theater changes in the digital space and, above all, how audiences as a social dimension of theatrical performances must first be constituted separately there. Based on performance analysis of the digital theater productions Homecoming and Sterben from Germany, the significance of the digital infrastructure for the assembly, performance, and action repertoires of these theater audiences is discussed. The author examines how audiences can be formed into different temporal communities in the digital space. These temporal communities are characterized by hybridity and have the potential to enable intense theatrical encounters across spatial boundaries.

Grain-Scale Anisotropic Analysis of Steady-State Creep in Oligocrystalline SAC Solder Joints

Heterogeneous integration is leading to unprecedented miniaturization of solder joints, often with thousands of joints within a single package. The thermomechanical behavior of such SAC solder joints is critically important to assembly performance and reliability, but can be difficult to predict due to the significant joint-to-joint variability caused by the stochastic variability of the arrangement of a few highly-anisotropic grains in each joint. This study relies on grain-scale testing to characterize the mechanical behavior of such oligocrystalline solder joints, while a grain-scale modeling approach has been developed to assess the effect of microstructure that lacks statistical homogeneity. The contribution of the grain boundaries is modeled with isotropic cohesive elements and identified by an inverse iterative method that extracts material properties by comparing simulation with experimental measurements. The properties are extracted from the results of one test and validated by verifying reasonable agreement with test results from a different specimen. Equivalent creep strain heterogeneity within the same specimen and between different specimens are compared to assess typical variability due to the variability of microstructure.

Analysis of Assembly Tolerance Based on Assembly Constraint Information Model

Mechanical products are composed of two or more parts. The geometric tolerance and dimensional tolerance of each feature in part will affect the assembly performance of the product, which are accumulated and propagated between assembly fit and parts. In this paper, through the secondary development of CAD software, the B-rep model of parts is obtained. The model information is decomposed and simplified based on geometric features to obtain the key information of parts in the assembly process, simplify the operation, and improve the accuracy. Through a directed graph network, the transmission model of assembly error information based on geometrical and dimensional tolerances (GD&T) on the surface of parts is established. Combined with the error transfer characteristics of different geometric surfaces and different error sources, guided by the breadth-first search algorithm and the shortest path theory, the search and establishment of a three-dimensional assembly chain are realized. Finally, the three-dimensional chain is simulated by the Monte Carlo method. The calculation results are compared with the error range obtained by the traditional method to prove the effectiveness of the method.

Can Assembly Performance and Work Environment be Jointly Optimized? An Example Discreet Event Simulation Study

Can Assembly Performance and Work Environment be Jointly Optimized? An Example Discreet Event Simulation Study

Can Assembly Performance and Work Environment be Jointly Optimized? An Example Discreet Event Simulation Study

Can Assembly Performance and Work Environment be Jointly Optimized? An Example Discreet Event Simulation Study

Research Status, Key Technology and Its Application Prospect of Complex Products Assembly Quality Control and Prediction Based on Digital Twin

In order to solve the problem of unmeasurable assembly performance of complex product, the digital twin-driven assembly quality control and prediction of complex product is studied by means of cyber-physical fusion in the assembly workshop. The connotation of digital twin intelligent assembly is introduced, the current research status of complex product assembly quality is compared and analyzed, and three main key technologies for the assembly quality control of complex product are proposed: (1) multidimensional, multi-scale, multidisciplinary modeling and simulating of digital twin-driven assembly; (2) multi-source heterogeneous data collection, sensing and fusion for assembly processes; (3) data-driven decision making, feedback and optimization technology. Finally, the application of digital twin technology in the field of assembly quality control of complex product is prospected.