Identification of Sequence Specificity of 5‐Methylcytosine Oxidation by Tet1 Protein with High‐Throughput Sequencing

Tet (ten‐eleven translocation) family proteins have the ability to oxidize 5‐methylcytosine (mC) to 5‐hydroxymethylcytosine (hmC), 5‐formylcytosine (fC), and 5‐carboxycytosine (caC). However, the oxidation reaction of Tet is not understood completely. Evaluation of genomic‐level epigenetic changes by Tet protein requires unbiased identification of the highly selective oxidation sites. In this study, we used high‐throughput sequencing to investigate the sequence specificity of mC oxidation by Tet1. A 6.6×10⁴‐member mC‐containing random DNA‐sequence library was constructed. The library was subjected to Tet‐reactive pulldown followed by high‐throughput sequencing. Analysis of the obtained sequence data identified the Tet1‐reactive sequences. We identified mCpG as a highly reactive sequence of Tet1 protein.     

GA-based synthesis approach for machining scheme selection and operation sequencing optimization for prismatic parts

To obtain global and near-global optimal process plans based on the combinations of different machining schemes selected from each feature, a genetic algorithm-based synthesis approach for machining scheme selection and operation sequencing optimization is proposed. The memberships derived from the fuzzy logic neural network (FL-NN), which contains the membership function of each machining operation to batch size, are presented to determine the priorities of alternative machining operations for each feature. After all alternative machining schemes for each feature are generated, their memberships are obtained by calculation. The proposed approach contains the outer iteration and nested genetic algorithm (GA). In an outer iteration, one machining scheme for each feature is selected by using the roulette wheel approach or highest membership approach in terms of its membership first, and then the corresponding operation precedence constraints are generated automatically. These constraints, which can be modified freely in different outer iterations, are then used in a constraints adjustment algorithm to ensure the feasibility of process plan candidates generated in GA. After that, GA obtains an optimal process plan candidate. At last, the global and near-global optimal process plans are obtained by comparing the optimal process plan candidates in the whole outer iteration. The proposed approach is experimentally validated through a case study.     

Grouping PCBs with Minimum Feeder Changes

In printed circuit board (PCB) assembly, the majority of electronic components are inserted by high-speed placement machines. Although the efficient utilization of the machinery is important for a manufacturer, it is hard to fully realize in high-mix low-volume production environments. On the machine level, the component setup strategy adopted by the manufacturer has a significant impact on the overall production efficiency. Usually, the setup strategy is formulated as a part type grouping problem or a minimum setup problem. In this article, we consider a hybridization of these two problems for the single machine case: The object function to be minimized includes a weighted sum of the number of part type groups (giving the number of setup occasions) and the number of feeder changeovers. We present algorithms for the problem and compare their efficiency.     

Minimizing total flow time on a single flexible machine

In this study, we address a job sequencing and tool switching problem arising in flexible manufacturing systems. We consider the single machine problem of minimizing total flow time. We prove that the problem is NP-hard in the strong sense and show that the tool switching problem is polynomially solvable for a given sequence.We propose a branch-and-bound algorithm whose efficiency is improved by precedence relations and several lower and upper bounding techniques. Our computational results reveal that the branch and bound approach produces optimal solutions in reasonable times for moderate sized problems. Our upper bounds produce very satisfactory solutions; therefore they can be an attractive alternative to solve larger sized problems.     

Joint admission,production sequencing,and production rate control for a two-class make-to-order manufacturing system

Today's manufacturing industry faces a number of challenges related to the rapid delivery of products with a high degree of variety. Striking a balance between the effectiveness in capacity utilization and the rapidness in order-fulfillment is a substantial challenge for manufacturing companies. This work aims to provide a theoretical basis from which to address this practical question. To this end, we address the problem of coordinating the admission, production sequencing, and production rate controls for a two-class make-to-order manufacturing system. Formulating the problem as a Markov decision process model, we identify the structural properties of optimal control policies under both discounted and average profit criteria. We show that the cμ rule is optimal for production sequencing and the optimal admission and production rate control policies can be characterized by the state-dependent threshold levels, provided that the production times are not associated with customer class. We also show that the optimal production rates are monotone in the system state, as in the case of a single class queueing system, and that the lower priority class can be preferred to the higher priority class in order admission under a certain condition on the system parameters. Our numerical study demonstrates that a considerable economic benefit can be achieved if the production rate is dynamically controlled between the minimum and maximum rates rather than fixed to the mean rate of these values. Finally, we present a heuristic policy that is described by linear switching functions for the control of order admission and a selection rule for the control of production rate. We compare the performance of our heuristic to the optimal policy using a numerical experiment, revealing that the heuristic provides near optimal solutions to test example problems and is robust to the system parameters.     

Impact of salinity on treatment of saline wastewater by sequencing batch biofilm reactor process

High salinity industrial wastewater is difficult to treat using biological treatment system because of the high concentrations of salt.The potential of a sequencing batch biofilm reactor （SBBR） process in treating synthetic high salinity wastewater was evaluated at laboratory scale during a 110-day operation.The reactor was operated in a 12 h cycle,and each cycle consisted of 0.25 h influent addition,8 h aeration,3 h anoxic reaction,0.5 h sedimentation and 0.25 h effluent withdrawal.Gradual increase in salinity gradient was applied during the acclimatization period.The acclimated SBBR system was demonstrated to be an effective process to remove organic compounds and ammonia nitrogen under high salinity conditions with chemical oxygen demand （COD） and ammonia nitrogen （NH3-N） removal efficiencies of 88% and 80%,respectively.The microscopic examination indicated that rather than rotifers or vorticella,the zoogloea,filamentous fungus mingled with a small quantity of swimming infusorians were dominant bacteria in SBBR system.The removal efficiencies close to 80% in COD and 75% in NH3-N were achieved at an organic loading rate （OLR） of 0.96 kg COD/（m3·d）,pH of 7.0,salinity of 14 g/L and NH3-N of 30 mg/L.     

屠宰过程中猪胴体表面及环境的细菌菌相分析

应用传统培养方法结合高通量测序技术分析屠宰分割过程中猪胴体表面微生物污染情况，并对屠宰车间刀具和分割车间接触面进行细菌菌落计数，以确定屠宰分割过程中的关键污染环节。结果表明：测序共得到881 458 个有效序列，864 个可操作分类单元，样品共注释到了22 门、33 纲、79 目、162 科、382 属和613 种的微生物信息。变形菌门（Proteobacteria）、拟杆菌门（Bacteroidota）和厚壁菌门（Firmicutes）为优势菌门，不动杆菌属（Acinetobacter）和气单胞菌属（Aeromonas）为主要的优势菌属。屠宰分割过程中群落多样性的排序为放血＞脱毛＞分割＞开膛＞冲淋＞冷却，冷却环节胴体表面的微生物多样性最低，分割后有所增加，表明分割是关键污染环节。传统微生物计数与测序的结果一致，从脱毛到冷却环节，猪胴体表面各类微生物数量呈下降趋势，分割后显著上升；分割车间各接触面菌落总数平均为6.11（lg（CFU/cm2）），高于屠宰车间刀具（平均为4.86（lg（CFU/cm2））），表明分割车间各接触面是关键污染源，进一步证明猪胴体分割环节为关键污染环节。     

Novel nuclear barcode regions for the identification of flatfish species

The development of an efficient seafood traceability framework is crucial for the management of sustainable fisheries and the monitoring of potential substitution fraud across the food chain. Recent studies have shown the potential of DNA barcoding methods in this framework, with most of the efforts focusing on using mitochondrial targets such as the cytochrome oxidase 1 and cytochrome b genes. In this article, we show the identification of novel targets in the nuclear genome, and their associated primers, to be used for the efficient identification of flatfishes of the Pleuronectidae family. In addition, different in silico methods are described to generate a dataset of barcode reference sequences from the ever-growing wealth of publicly available sequence information, replacing, where possible, labour-intensive laboratory work. The short amplicon lengths render the analysis of these new barcode target regions ideally suited to next-generation sequencing techniques, allowing characterisation of multiple fish species in mixed and processed samples. Their location in the nucleus also improves currently used methods by allowing the identification of hybrid individuals.     

Assessing the Accuracy of Quantitative Molecular Microbial Profiling

The application of high-throughput sequencing in profiling microbial communities is providing an unprecedented ability to investigate microbiomes. Such studies typically apply one of two methods: amplicon sequencing using PCR to target a conserved orthologous sequence (typically the 16S ribosomal RNA gene) or whole (meta)genome sequencing (WGS). Both methods have been used to catalog the microbial taxa present in a sample and quantify their respective abundances. However, a comparison of the inherent precision or bias of the different sequencing approaches has not been performed. We previously developed a metagenomic control material (MCM) to investigate error when performing different sequencing strategies. Amplicon sequencing using four different primer strategies and two 16S rRNA regions was examined (Roche 454 Junior) and compared to WGS (Illumina HiSeq). All sequencing methods generally performed comparably and in good agreement with organism specific digital PCR (dPCR); WGS notably demonstrated very high precision. Where discrepancies between relative abundances occurred they tended to differ by less than twofold. Our findings suggest that when alternative sequencing approaches are used for microbial molecular profiling they can perform with good reproducibility, but care should be taken when comparing small differences between distinct methods. This work provides a foundation for future work comparing relative differences between samples and the impact of extraction methods. We also highlight the value of control materials when conducting microbial profiling studies to benchmark methods and set appropriate thresholds.