Equipment selection and task assignment for multiproduct assembly system design

A multiproduct assembly system produces a family of similar products, where the assembly of each product entails an ordered set of tasks. An assembly system consists of a sequence of workstations. For each workstation, we assign a subset of the assembly tasks to be performed at the workstation and select the type of assembly equipment or resource to be used by the workstation. The assembly of each product requires a visit to each workstation in the fixed sequence. The problem of system design is to find the system that is capable of producing all the products in the desired volumes at minimum cost. The system cost includes the fixed capital costs for the assembly equipment and tools and the variable operating costs for the various workstations. We present and illustrate an optimization procedure that assigns tasks to workstations and selects assembly equipment for each workstation.     

Decision support for clinical laboratory capacity planning

The design of a decision support system for capacity planning in clinical laboratories is discussed. The DSS supports decisions concerning the following questions: how should the laboratory be divided into job shops (departments/sections), how should staff be assigned to workstations and how should samples be assigned to workstations for testing. The decision support system contains modules for supporting decisions at the overall laboratory level (concerning the division of the laboratory into job shops) and for supporting decisions at the job shop level (assignment of staff to workstations and sample scheduling). Experiments with these modules are described showing both the functionality and the validity.     

Optimal dispatching of multipriority jobs to two heterogeneous workstations

The general problem scenario of this paper is the following: Jobs of various priorities, stationed in a common storage area, are waiting to be dispatched to two non-identical workstations. Any of the waiting jobs can be accessed from the storage at any given time. Each job can be processed on either of the workstations, but once a job has been assigned it may not be preempted. By job priority it is meant that a higher priority job has disptach preference over a lower priority job. The processing time of a job on a given workstation is assumed to be random, the distribution being dependent on the job type and the configuration of the workstation. Specifically, the first problem studied considers only two classes of jobs: (1) “hot” jobs, whose processing is to be expedited and thus have the higher dispatch priority, and (2) “routine” jobs which may be assigned to an available workstation only if the workstation has been rejected by all “hot” jobs. The processing times are assumed to be exponentially distributed with means depending on the job class and workstation. We assume that, on the average, one workstation is faster than the other with regard to processing any job. The dispatching objective for each job class is to minimize its expected flowtime. It is shown that threshold dispatching policies are optimal for this problem. That is, the faster processor should be utilized whenever possible, and for each class there exists an explicit threshold such that when the number of jobs of that class in the buffer exceeds this threshold then a job of that class is dispatched to the slower processor, otherwise these jobs wait for the faster processor to become available. For the higher priority jobs, this threshold is shown to be a function only of the various processing rates of the two workstations. For the lower priority jobs, the threshold also depends on the number of higher priority jobs in the buffer. The results is extended to a system with n priority classes. Again, it is shown that when the processing times are exponentially distributed with different rates and the dispatching objective for each class is to minimize its expected flowtime, the optimal dispatching policies are of threshold type. Explicit thresholds are easily derived.     

High-throughput SNP genotyping

Whole genome approaches using single nucleotide polymorphism (SNP) markers have the potential to transform complex disease genetics and expedite pharmacogenetics research. This has led to a requirement for high-throughput SNP genotyping platforms. Development of a successful high-throughput genotyping platform depends on coupling reliable assay chemistry with an appropriate detection system to maximise efficiency with respect to accuracy, speed and cost. Current technology platforms are able to deliver throughputs in excess of 100 000 genotypes per day, with an accuracy of >99%, at a cost of 20-30 cents per genotype. In order to meet the demands of the coming years, however, genotyping platforms need to deliver throughputs in the order of one million genotypes per day at a cost of only a few cents per genotype. In addition, DNA template requirements must be minimised such that hundreds of thousands of SNPs can be interrogated using a relatively small amount of genomic DNA. As such, it is predicted that the next generation of high-throughput genotyping platforms will exploit large-scale multiplex reactions and solid phase assay detection systems.     

An intrinsic timer that controls cell-cycle withdrawal in cultured cardiac myocytes

Developing cardiac myocytes divide a limited number of times before they stop and terminally differentiate, but the mechanism that stops their division is unknown. To help study the stopping mechanism, we defined conditions under which embryonic rat cardiac myocytes cultured in serum-free medium proliferate and exit the cell cycle on a schedule that closely resembles that seen in vivo. The culture medium contains FGF-1 and FGF-2, which stimulate cell proliferation, and thyroid hormone, which seems to be necessary for stable cell-cycle exit. Time-lapse video recording shows that the cells within a clone tend to divide a similar number of times before they stop, whereas cells in different clones divide a variable number of times before they stop. Cells cultured at 33 degrees C divide more slowly but stop dividing at around the same time as cells cultured at 37 degrees C, having undergone fewer divisions. Together, these findings suggest that an intrinsic timer helps control when cardiac myocytes withdraw from the cell cycle and that the timer does not operate by simply counting cell divisions. We provide evidence that the cyclin-dependent kinase inhibitors p18 and p27 may be part of the timer and that thyroid hormone may help developing cardiac myocytes stably withdraw from the cell cycle.     

Performance Evaluation of Flexible Manufacturing Systems with Finite Local Buffers: Fixed and Dynamic Routings

This article evaluates the performance of flexible manufacturing systems with finite local buffers and fixed or dynamic routing rules, and addresses the optimal design or system configuration problem of maximizing the system throughput. The costs include machine cost, part (or pallet) cost, and local buffers cost. First, the system throughputs and their behaviors are considered with both queueing network analysis and simulation, and it is shown for a fixed routing model that the system throughput in the case of finite local buffers is greater than in the case of infinite local buffers. For a fixed versus dynamic routing rule, it is also found that the throughput in the former case can be close to the one in the latter case by changing the setting parameters. Next, the design problems of maximizing the system throughput are considered numerically for fixed and dynamic routing cases. Then, it is seen that better combination of design variables is a class of the monotonicity in local buffers, service rates, and routing probabilities.     

Modeling and design optimization of asynchronous flexible assembly systems with statistical process control and repair

This article presents the implementation of hybrid procedures involving the use of analytical performance evaluation techniques, discrete event simulation, and Monte Carlo optimization methods for the stochastic design optimization of asynchronous flexible assembly systems (AFASs) with statistical process control (SPC) and repair loops. AFASs are extremely complex and difficult to analyze in that such systems are subject to starvation and blocking effects, random jam occurrences at workstations, and splitting and merging of the assembly flow due to repair loops. Hence, an integrated approach simultaneously analyzing the interactions between product quality and optimal/near optimal system design is pursued. In the analytical analysis stage, a model based on GI/G/1 queueing network theory is used. In the Monte Carlo optimization stage, two alternative stochastic optimization approaches, namely, heuristic versions of stochastic quasigradient and simulated annealing algorithms, are implemented and compared in terms of their capabilities of solving complex AFAS design problems. The hybrid procedures presented appear to perform reasonably well in designing AFASs to reach a target production rate.     

Middleware support for many-task computing

Many-task computing aims to bridge the gap between two computing paradigms, high throughput computing and high performance computing. Many-task computing denotes high-performance computations comprising multiple distinct activities, coupled via file system operations. The aggregate number of tasks, quantity of computing, and volumes of data may be extremely large. Traditional techniques found in production systems in the scientific community to support many-task computing do not scale to today’s largest systems, due to issues in local resource manager scalability and granularity, efficient utilization of the raw hardware, long wait queue times, and shared/parallel file system contention and scalability. To address these limitations, we adopted a “top-down” approach to building a middleware called Falkon, to support the most demanding many-task computing applications at the largest scales. Falkon (Fast and Light-weight tasK executiON framework) integrates (1) multi-level scheduling to enable dynamic resource provisioning and minimize wait queue times, (2) a streamlined task dispatcher able to achieve orders-of-magnitude higher task dispatch rates than conventional schedulers, and (3) data diffusion which performs data caching and uses a data-aware scheduler to co-locate computational and storage resources. Micro-benchmarks have shown Falkon to achieve over 15K+ tasks/s throughputs, scale to hundreds of thousands of processors and to millions of queued tasks, and execute billions of tasks per day. Data diffusion has also shown to improve applications scalability and performance, with its ability to achieve hundreds of Gb/s I/O rates on modest sized clusters, with Tb/s I/O rates on the horizon. Falkon has shown orders of magnitude improvements in performance and scalability than traditional approaches to resource management across many diverse workloads and applications at scales of billions of tasks on hundreds of thousands of processors across clusters, specialized systems, Grids, and supercomputers. Falkon’s performance and scalability have enabled a new class of applications called Many-Task Computing to operate at previously so-believed impossible scales with high efficiency.     

A Multi-stage Representation of Cell Proliferation as a Markov Process

The stochastic simulation algorithm commonly known as Gillespie’s algorithm (originally derived for modelling well-mixed systems of chemical reactions) is now used ubiquitously in the modelling of biological processes in which stochastic effects play an important role. In well-mixed scenarios at the sub-cellular level it is often reasonable to assume that times between successive reaction/interaction events are exponentially distributed and can be appropriately modelled as a Markov process and hence simulated by the Gillespie algorithm. However, Gillespie’s algorithm is routinely applied to model biological systems for which it was never intended. In particular, processes in which cell proliferation is important (e.g. embryonic development, cancer formation) should not be simulated naively using the Gillespie algorithm since the history-dependent nature of the cell cycle breaks the Markov process. The variance in experimentally measured cell cycle times is far less than in an exponential cell cycle time distribution with the same mean.Here we suggest a method of modelling the cell cycle that restores the memoryless property to the system and is therefore consistent with simulation via the Gillespie algorithm. By breaking the cell cycle into a number of independent exponentially distributed stages, we can restore the Markov property at the same time as more accurately approximating the appropriate cell cycle time distributions. The consequences of our revised mathematical model are explored analytically as far as possible. We demonstrate the importance of employing the correct cell cycle time distribution by recapitulating the results from two models incorporating cellular proliferation (one spatial and one non-spatial) and demonstrating that changing the cell cycle time distribution makes quantitative and qualitative differences to the outcome of the models. Our adaptation will allow modellers and experimentalists alike to appropriately represent cellular proliferation—vital to the accurate modelling of many biological processes—whilst still being able to take advantage of the power and efficiency of the popular Gillespie algorithm.     

Dwell time symmetry in random walks and molecular motors

The statistics of steps and dwell times in reversible molecular motors differ from those of cycle completion in enzyme kinetics. The reason is that a step is only one of several transitions in the mechanochemical cycle. As a result, theoretical results for cycle completion in enzyme kinetics do not apply to stepping data. To allow correct parameter estimation, and to guide data analysis and experiment design, a theoretical treatment is needed that takes this observation into account. In this article, we model the distribution of dwell times and number of forward and backward steps using first passage processes, based on the assumption that forward and backward steps correspond to different directions of the same transition. We extend recent results for systems with a single cycle and consider the full dwell time distributions as well as models with multiple pathways, detectable substeps, and detachments. Our main results are a symmetry relation for the dwell time distributions in reversible motors, and a relation between certain relative step frequencies and the free energy per cycle. We demonstrate our results by analyzing recent stepping data for a bacterial flagellar motor, and discuss the implications for the efficiency and reversibility of the force-generating subunits.     

Analysis of flexible manufacturing systems with distinct repeated visits: DrQ

This article examines the performance effects caused by repeated part visits at the workstations of a flexible manufacturing system (FMS). Such repeated part visits to the same workstations are commonly associated with fixture changes for machining complex parts, reclamping, and remounting or reorienting them. Since each of the repeated visits to a workstation may require different processing requirements, the resulting queueing network does not have a product form solution. We therefore develop an approximate mean value analysis model for performance evaluation of an FMS that may produce multiple part types with distinct repeated visits. We provide numerical examples and validate the accuracy of our solution algorithm against simulation. These examples show that the proposed model produces accurate throughput and utilization predictions with minimal computational efforts. These examples reveal that increasing the total pallet population may result in a reduction of the aggregate throughput, and that the FMS's performance could be more sensitive to the mix of pallets and part routes than to the total number of pallets. Our model will be of use, in particular, when managers wish to control individual operations (e.g., to adjust individual operation times to achieve economic savings in tool wear and breakage costs) or to investigate the performance implications of route changes due to alternate assignments of particular manufacturing tasks to certain workstations.     

Combinatorial metabolic pathway assembly approaches and toolkits for modular assembly

Synthetic Biology is a rapidly growing interdisciplinary field that is primarily built upon foundational advances in molecular biology combined with engineering design principles such as modularity and interoperability. The field considers living systems as programmable at the genetic level and has been defined by the development of new platform technologies and methodological advances. A key concept driving the field is the Design-Build-Test-Learn cycle which provides a systematic framework for building new biological systems. One major application area for synthetic biology is biosynthetic pathway engineering that requires the modular assembly of different genetic regulatory elements and biosynthetic enzymes. In this review we provide an overview of modular DNA assembly and describe and compare the plethora of in vitro and in vivo assembly methods for combinatorial pathway engineering. Considerations for part design and methods for enzyme balancing are also presented, and we briefly discuss alternatives to intracellular pathway assembly including microbial consortia and cell-free systems for biosynthesis. Finally, we describe computational tools and automation for pathway design and assembly and argue that a deeper understanding of the many different variables of genetic design, pathway regulation and cellular metabolism will allow more predictive pathway design and engineering.     

The Min system and nucleoid occlusion are not required for identifying the division site in Bacillus subtilis but ensure its efficient utilization

Precise temporal and spatial control of cell division is essential for progeny survival. The current general view is that precise positioning of the division site at midcell in rod-shaped bacteria is a result of the combined action of the Min system and nucleoid (chromosome) occlusion. Both systems prevent assembly of the cytokinetic Z ring at inappropriate places in the cell, restricting Z rings to the correct site at midcell. Here we show that in the bacterium Bacillus subtilis Z rings are positioned precisely at midcell in the complete absence of both these systems, revealing the existence of a mechanism independent of Min and nucleoid occlusion that identifies midcell in this organism. We further show that Z ring assembly at midcell is delayed in the absence of Min and Noc proteins, while at the same time FtsZ accumulates at other potential division sites. This suggests that a major role for Min and Noc is to ensure efficient utilization of the midcell division site by preventing Z ring assembly at potential division sites, including the cell poles. Our data lead us to propose a model in which spatial regulation of division in B. subtilis involves identification of the division site at midcell that requires Min and nucleoid occlusion to ensure efficient Z ring assembly there and only there, at the right time in the cell cycle.     

The role of temperature and dispersal in moss-microarthropod community assembly after a catastrophic event

There is a clear crisis in the maintenance of biodiversity. It has been generated by a multitude of factors, notably habitat loss, now compounded by the effects of climate change. Predicted changes in climate include increased severity and frequency of extreme climatic events. To manage landscapes, an understanding of the processes that allow recovery from these extreme events is required. Understanding these landscape-scale processes of community assembly and disassembly is hindered by the large scales at which they operate. Model systems provide a means of studying landscape scale processes at tractable scales. Here, we assess the combined effects of temperature and habitat-patch isolation on assembly of naturally diverse moss microarthropod communities after a high-temperature event. We show that community assembly depends on temperature and on degree of habitat isolation. Heated communities were heavily dominated in abundance by two species, one of them relatively large. The resulting size-structure is unlike that seen in the field. Community composition in habitat fragments appears also to have been influenced by the source pool of recolonizing fauna. Our results highlight the value of dispersal in disturbed landscapes and the potential for habitat connectivity to buffer communities from the effects of climate change.     

生物节律基因period3的研究进展

昼夜节律是所有真核生物和部分原核生物的基本特征,一组节律表达的生物钟基因形成24 h周期振荡的自主调节转录-翻译反馈回路。period（per）基因家族是生物钟反馈回路中重要组成成分,per3基因是period基因家族成员之一。人类的per3基因定位于染色体1p36,其编码区第18外显子中含有一个灵长类特有的串联重复序列（variable number tandem repeat,VNTR）。该VNTR包含一簇理论上的磷酸化位点,能影响PER3蛋白的磷酸化降解,影响PER3蛋白的功能。近年研究发现,per3基因多态性与睡眠结构、睡眠紊乱发病年龄、睡眠剥夺后次日清晨执行能力等密切相关。     

Cell cycle control of higher-order chromatin assembly around naked DNA in vitro.

We have developed an in vitro system in which higher-order chromatin structures are assembled around naked DNAs in a cell cycle-dependent manner. Membrane-free soluble extracts specific to interphase and mitotic states were prepared from Xenopus eggs. When high molecular weight DNA is incubated with interphase extracts, fluffy chromatin-like structures are assembled. In contrast, mitotic extracts produce highly condensed chromosome-like structures. Immunofluorescence studies show that a monoclonal antibody MPM-2, which recognizes a class of mitosis-specific phosphoproteins, stains the "core" or "axis" of condensed mitotic chromatin but not interphase chromatin. By adding mitotic extracts, interphase chromatin structures are synchronously converted into the condensed state. The increasingly condensed state of chromatin correlates with the appearance and structural rearrangements of the MPM-2-stained structures. These results suggest that mitosis-specific phosphoproteins recognized by MPM-2 may be directly involved in the assembly of the chromosome scaffold-like structures and chromatin condensation. Although both extracts promote nucleosome assembly at the same rate, topoisomerase II (topo II) activity is four to five times higher in mitotic extracts compared with interphase extracts. The addition of a topo II inhibitor VM-26 into mitotic assembly mixtures disturbs the organization of the MPM-2-stained structures and affects the final stage of chromatin condensation. This in vitro system should be useful for identifying cis- and trans-acting elements responsible for higher-order chromatin assembly and its structural changes in the cell cycle.