The design and manufacturing process account for approximately 60–80% of a product’s lifecycle carbon emissions, making them critical junctures for achieving low-carbon transformation across multiple industrial sectors [...]

The design for the remanufacturing process (DFRP) is a key part of remanufacturing, which directly affects the cost, performance, and carbon emission of used product remanufacturing. However, used parts have various failure forms and defects, which make it hard to rapidly generate the remanufacturing process scheme for simultaneously satisfying remanufacturing requirements regarding cost, performance, and carbon emissions. This causes remanufactured products to lose their energy-saving and emission-reduction benefits. To this end, this paper proposes an integrated design method for the used product remanufacturing process based on the multi-objective optimization model. Firstly, an integrated DFRP framework is constructed, including design information acquisition, the virtual model construction of DFRP solutions, and the multi-objective optimization of the remanufacturing process scheme. Then, the design matrix, sensitivity analysis, and least squares are applied to construct the mapping models between performance, carbon emissions, cost, and remanufacturing process parameters. Meanwhile, a DFRP multi-objective optimization model with performance, carbon emission, and cost as the design objectives is established, and a teaching–learning based adaptive optimization algorithm is employed to solve the optimization model to acquire a DFRP solution satisfying the target information. Finally, the feasibility of the method is verified by the DFRP of the turbine blade as an example. The results show that the optimized remanufacturing process parameters reduce carbon emissions by 11.7% and remanufacturing cost by USD 0.052 compared with the original process parameters, and also improve the tensile strength of the turbine blades, which also indicates that the DFPR method can effectively achieve energy saving and emission reduction and ensure the performance of the remanufactured products. This can greatly reduce the carbon emission credits of the large-scale remanufacturing industry and promote the global industry’s sustainable development; meanwhile, this study is useful for remanufacturing companies and provides remanufacturing process design methodology support.

Optimizing tolerance allocation is crucial for balancing cost and performance in the remanufacturing of used electromechanical products. However, the traditional remanufacturing model of “individual part precision restoration + secondary machining trial assembly” lacks an integrated approach to tolerance planning in the design and manufacturing stages, leading to excessive fluctuations in cost and quality. To address this issue, a remanufacturing value-based tolerance allocation method is proposed, integrating remanufacturing value into the tolerance allocation process. First, a remanufacturing value quantification and evaluation indicator system was established at the failure surface layer (i.e., the remanufacturing processing surface) at the design stage and comprehensively considers the used part quality and enterprise processing capabilities. Quantification methods for each indicator were developed, and a comprehensive weighting strategy combining subjective enterprise standards and objective return quality adopted. Then, a multi-objective optimization model for remanufacturing tolerance allocation was established, targeting remanufacturing cost, quality loss, process stability, and corrected by the failure surface value. Finally, the beetle antennae search (BAS) algorithm was employed to determine the optimal solution. A case study on a used gearbox demonstrated that the proposed method significantly improves cost, quality loss, and process stability compared to the traditional remanufacturing approaches.

Assessing the remanufacturability of used parts is a crucial basis for determining their value and optimal utilization methods. Due to the uncertain quality of used parts and the varying processing capacity of enterprises, coupled with the continuous expansion of the scale of the remanufacturing industry, the traditional weighted-analysis model, which considers all indicators at the same level, is inefficient for decision-making. In order to evaluate the remanufacturability of used parts more efficiently, a decision tree-based method is proposed, which hierarchically processes the evaluation criteria to enhance decision-making efficiency and adaptability. First, using a data platform, the remaining value of used parts reflected in the failure degree is analyzed and predicted, with the aid of artificial neural networks and the Weibull model, providing an initial remanufacturability assessment. Then, remanufacturability is assessed sequentially from the technical, economic, and environmental feasibility aspects, based on the enterprise’s processing capabilities. Finally, the effectiveness of the proposed method is validated through a case study on the remanufacturing of used blades.

This file contains descriptions of all of the bioinformatic analyses used in the paper.

Distribution of allele fraction of inherited and somatic variants before and after filtering. This figure is similar to Fig. 4a, but includes a plotting of all somatic variants before filtering (black), which contains a large number of false positive errors.

The following file contains Tables S1-12. The contents of these tables are referenced through the manuscript and contain the basis for the results summarized in the paper. The list of tables is as follows: S1. CNV. This table contains all the copy number gains and losses identified in the CTCs. S2. SNV. This table contains all of the somatic SNVs identified in the CTCs. S3. Indel. This table contains all of the somatic insertions and deletions identified in the CTCs. S4. NA12877 somatic. This table contains all of the somatic SNVs identified in NA12877. S5. Allele fraction. This table contains allele fraction calculations and compartment number filtering calculations. S6. Sanger and Miseq. This table contains all of the Sanger sequencing and Miseq validation for the 77 somatic SNVs validated in this study. S7. Mutational spectrum. This table contains the mutation spectrum analysis and the comparison of the CTC mutation spectrum to other tumor types. S8. Non-coding annotation. This table contains a list of potentially important somatic noncoding variants. S9. Splicing. This table contains somatic splicing variants. S10. MHC-II. This table contains the potential somatic coding changes which would result in MHC-II binding antigens. S11. Two hit. This table contains genes with two potential inactivating variants, this can include inherited and somatic variants. S12. Phasing. This table contains phased somatic and/or inherited variants that potentially inactivate a gene through a compound heterozygous mechanism.

To reduce the remanufacturing cost and improve product quality and processing stability of the remanufacturing of Waste Electromechanical Products（WEMP）,an optimization method of remanufacturing tolerance for WEMP with process condition constraint was proposed.In this method, the characteristics of process condition constraint in tolerance design optimization for remanufacturing of WEMP were analyzed, and a four-level tolerance distribution system was constructed from tolerance design stage to manufacturing stage.Based on the design targets such as assembly accuracy and enterprise processing capability, a multi-objective optimization model of remanufacturing tolerance in design stage was established by taking production cost, quality loss, process capability in manufacture stage as the objectives.The modified method of the model was proposed based on the uncertainty precision to improve the rationality, and the Beetle Antennae Search Algorithm（BAS） was used to optimized the model.A used gearbox was taken as an example to illustrate the validity and practicality of the proposed method.The results showed that the proposed method was effective in optimization the remanufacturing tolerance of WEMP.

Copy number analysis based on read coverage in all batches. Read data is plotted starting from Chr1 and ending at ChrX. Each sample is labeled on the right side of the plot. All CTC samples identify chr1q amplification, and chr13 and chr16q losses.

Mutational spectrum of CTCs. The percent of particular base changes (labeled on the right of the figure) for different sets of mutations from CTCs, NA12877, and breast cancer from TCGA (BRCA) data are shown. Founder mutations and mutations found in 5 cells have a pattern very similar to that seen in breast cancer.

The uncertainty failure of the used part leads the complexity selection of remanufacturing processes. The different remanufacturing process combinations among used parts of used products also make the formulation of tolerance schemes more difficult. It is hard to guarantee the optimality of process-tolerance schemes by traditional serial production modes in general, in which tolerance design is followed by process formulation. In order to generate the optimal remanufacturing scheme of process and tolerance for used products, an optimization method to integrate designs of process-tolerance (IDP-T) based on fault features was presented. In this work, the failure description set of used parts was constructed by combining the attribute characteristics and failure characteristics. Case-based reasoning (CBR) was first utilized to generate the feasible remanufacturing process plans of used parts. Then, based on the feasible process plans, the factors of cost, quality loss, closed-loop accuracy and machining ability of remanufacturing were comprehensively considered to construct the optimization model of IDP-T. The Beetle Antennae Search algorithm (BAS) was used for the optimal alternative selection. Finally, a used gearbox was taken as an example to illustrate the validity and practicality of the proposed method. The results showed that the proposed method was effective in the optimization of IDP-T for remanufacturing.

：The reassembly strategy of used components is an important factor affecting the cost of remanufacturing of used mechanical equipment.The uncertainty of the reuse strategy and the complexity coupling relationship between used components, make the optimization of the reassembly strategy more complex, and affect the multi-life cycle cost of product.A research on the reassembly strategy of used mechanical equipment components based on non-cooperative game is proposed, the multi-objective optimization model of reassembly strategy with cost and balance of residual service life is transformed into a non-cooperative game (NCG) model and a mapping relationship is formed.The cost and balance of residual service life of different reassembly Strategies are taken as non-cooperative game parties, fuzzy cluster analysis is used to form the strategic attribution of two players in the game, and the utility matrix is formed by combining the utility function of the players.The optimal reassembly strategy is obtained through the Nash equilibrium analysis of the utility matrix, to improve the short comes of previous methods which depend on experience or linear weighted.A used lathe C6132 is taken as an example, to validate the feasibility and effectiveness of the proposed method.

The maximum concurrent flow problem (MCFP) is a multicommodity flow problem in which every pair of vertices can send and receive flow concurrently. The objective of MCFP is to find a maximum throughput and the flow corresponding to the throughput under a set of capacity constraints. We present an improved version of the Flow Deviation Method for the maximum concurrent flow problem, which was first presented by Daniel Bienstock and Olga Raskina in 2000. The algorithm is based on linear programming formulation involving Frank-Wolfe procedure and minimum-cost flow problem. The correctness of the algorithm is strictly proved and the performance is evaluated under several networks of different sizes.

NDN naturally supports multicast better than the traditional Internet, and multicast plays an important role in NDN. Most researchs on multicast routing algorithms are focused on cost optimization without taking node cache into account. This paper constructs a mathematical model for joint optimization of delay and cost, which is more flexible in describing NDN than adding delay as a constraint to the model. Then, the heuristic multicast algorithm considering node cache for this model is proposed. Last, we analyze the delay performance of the algorithm by comparing it with the exact Algorithm and the classical STMPH algorithm.

Abstract Much effort has been dedicated to developing circulating tumor cells (CTC) as a noninvasive cancer biopsy, but with limited success as yet. In this study, we combine a method for isolation of highly pure CTCs using immunomagnetic enrichment/fluorescence-activated cell sorting with advanced whole genome sequencing (WGS), based on long fragment read technology, to illustrate the utility of an accurate, comprehensive, phased, and quantitative genomic analysis platform for CTCs. Whole genomes of 34 CTCs from a patient with metastatic breast cancer were analyzed as 3,072 barcoded subgenomic compartments of long DNA. WGS resulted in a read coverage of 23× per cell and an ensemble call rate of >95%. These barcoded reads enabled accurate detection of somatic mutations present in as few as 12% of CTCs. We found in CTCs a total of 2,766 somatic single-nucleotide variants and 543 indels and multi-base substitutions, 23 of which altered amino acid sequences. Another 16,961 somatic single nucleotide variant and 8,408 indels and multi-base substitutions, 77 of which were nonsynonymous, were detected with varying degrees of prevalence across the 34 CTCs. On the basis of our whole genome data of mutations found in all CTCs, we identified driver mutations and the tissue of origin of these cells, suggesting personalized combination therapies beyond the scope of most gene panels. Taken together, our results show how advanced WGS of CTCs can lead to high-resolution analyses of cancers that can reliably guide personalized therapy. Cancer Res; 77(16); 4530–41. ©2017 AACR.

Patients of infraorbital nerve injury often appear in the sensory abnormalities of corresponding position, such as numbness or pain. We present a case with numbness of the left cheek because of the injury. The patient were treated by endoscopic assisted on the left infraorbital nerve decompression through the approach of the canine fossa. The symptom shows improvement after the operation. The patient feels numbness significantly ease on 4 months after the operation.

Background There is a rapidly increasing amount of de novo genome assembly using next-generation sequencing (NGS) short reads; however, several big challenges remain to be overcome in order for this to be efficient and accurate. SOAPdenovo has been successfully applied to assemble many published genomes, but it still needs improvement in continuity, accuracy and coverage, especially in repeat regions. Findings To overcome these challenges, we have developed its successor, SOAPdenovo2, which has the advantage of a new algorithm design that reduces memory consumption in graph construction, resolves more repeat regions in contig assembly, increases coverage and length in scaffold construction, improves gap closing, and optimizes for large genome. Conclusions Benchmark using the Assemblathon1 and GAGE datasets showed that SOAPdenovo2 greatly surpasses its predecessor SOAPdenovo and is competitive to other assemblers on both assembly length and accuracy. We also provide an updated assembly version of the 2008 Asian (YH) genome using SOAPdenovo2. Here, the contig and scaffold N50 of the YH genome were ~20.9 kbp and ~22 Mbp, respectively, which is 3-fold and 50-fold longer than the first published version. The genome coverage increased from 81.16% to 93.91%, and memory consumption was ~2/3 lower during the point of largest memory consumption.

Background: With the fast development of next generation sequencing technologies, increasing numbers of genomes are being de novo sequenced and assembled. However, most are in fragmental and incomplete draft status, and thus it is often difficult to know the accurate genome size and repeat content. Furthermore, many genomes are highly repetitive or heterozygous, posing problems to current assemblers utilizing short reads. Therefore, it is necessary to develop efficient assembly-independent methods for accurate estimation of these genomic characteristics. Results: Here we present a framework for modeling the distribution of k-mer frequency from sequencing data and estimating the genomic characteristics such as genome size, repeat structure and heterozygous rate. By introducing novel techniques of k-mer individuals, float precision estimation, and proper treatment of sequencing error and coverage bias, the estimation accuracy of our method is significantly improved over existing methods. We also studied how the various genomic and sequencing characteristics affect the estimation accuracy using simulated sequencing data, and discussed the limitations on applying our method to real sequencing data. Conclusion: Based on this research, we show that the k-mer frequency analysis can be used as a general and assembly-independent method for estimating genomic characteristics, which can improve our understanding of a species genome, help design the sequencing strategy of genome projects, and guide the development of assembly algorithms. The programs developed in this research are written using C/C++, and freely accessible at Github URL (this https URL) or BGI ftp ( this ftp URL).