Fundamental bottlenecks in the application of continuous bioprocesses.

Continuous culture is applied mainly as a research tool and much less as a production process. Fundamental bottlenecks in continuous culture are discussed to help shed light on this apparent contradiction. Based on a discussion of technical, process related, and economic/market bottlenecks it is concluded that the often mentioned productivity argument in favor of continuous processing is much too simple. The optimal choice of a process mode is determined by a full understanding of the equipment and production plant factors and of the economic/market factors. Very often the resulting choice will be the fed batch and/or the cell retention process mode which is characterized by low growth rates. Therefore more research towards product formation at low growth rates (less than 0.05 h-1) is needed.     

Comprehensive assessment of the l-lysine production process from fermentation of sugarcane molasses

l-Lysine is an essential amino acid that can be produced by chemical processes from fossil raw materials, as well as by microbial fermentation, the latter being a more efficient and environmentally friendly procedure. In this work, the production process of l-lysine-HCl is studied using a systematic approach based on modeling and simulation, which supports decision making in the early stage of process design. The study considers two analysis stages: first, the dynamic analysis of the fermentation reactor, where the conversion of sugars from sugarcane molasses to l-lysine with a strain of Corynebacterium glutamicum is carried out. In this stage, the operation mode (either batch or fed batch) and operating conditions of the fermentation reactor are defined to reach the maximum technical criteria. Afterwards, the second analysis stage relates to the industrial production process of l-lysine-HCl, where the fermentation reactor, upstream processing, and downstream processing are included. In this stage, the influence of key parameters on the overall process performance is scrutinized through the evaluation of several technical, economic, and environmental criteria, to determine a profitable and sustainable design of the l-lysine production process. The main results show how the operating conditions, process design, and selection of evaluation criteria can influence in the conceptual design. The best plant design shows maximum product yield (0.31 g l-lysine/g glucose) and productivity (1.99 g/L/h), achieving 26.5% return on investment (ROI) with a payback period (PBP) of 3.8 years, decreasing water and energy consumption, and with a low potential environmental impact (PEI) index.

     

Time-Based Competition in Multistage Manufacturing: Stream-of-Variation Analysis (SOVA) Methodology—Review

Frequency of model change and the vast amounts of time and cost required to make a changeover, also called time-based competition, has become a characteristic feature of modern manufacturing and new product development in automotive, aerospace, and other industries. This paper discusses the concept of time-based competition in manufacturing and design based on a review of on-going research related to stream-of-variation (SOVA or SoV) methodology. The SOVA methodology focuses on the development of modeling, analysis, and control of dimensional variation in complex multistage assembly processes (MAP) such as the automotive, aerospace, appliance, and electronics industries. The presented methodology can help in eliminating costly trial-and-error fine-tuning of new-product assembly processes attributable to unforeseen dimensional errors throughout the assembly process from design through ramp-up and production. Implemented during the product design phase, the method will produce math-based predictions of potential downstream assembly problems, based on evaluations of the design and a large array of process variables. By integrating product and process design in a pre-production simulation, SOVA can head off individual assembly errors that contribute to an accumulating set of dimensional variations, which ultimately result in out-of-tolerance parts and products. Once in the ramp-up stage of production, SOVA will be able to compare predicted misalignments with actual measurements to determine the degree of mismatch in the assemblies, diagnose the root causes of errors, isolate the sources from other assembly steps, and then, on the basis of the SOVA model and product measurements, recommend solutions.     

Design-to-Manufacturing Information Management for Electronics Assembly

This paper addresses design to manufacturing (DTM) for electronics assembly from several different perspectives. First, a working definition for DTM is proposed, and the distinction is made between DTM and the more commonly known design for manufacturability. Following an overview of surface mount technology assembly processes, DTM information management is introduced in terms of its data requirements and underlying decision and planning problems. Evaluation criteria are discussed, and specific requirements for a state-of-the-art DTM system are highlighted. The experiences of one Motorola factory are presented in a brief case study, which covers process mapping, system design and benchmarking, and installation and configuration activities. Benefits of an efficient DTM sytem are discussed in terms of the improvements in production time, engineering time, and product or process quality. Finally, a summary of future trends for DTM is given.     

Design of metabolic feed controllers: application to high-density fermentations of Pichia pastoris

High-density cultures of the methylotrophic yeast Pichia pastoris were found to exhibit oscillatory metabolic behavior when fed methanol under closed-loop operations using a dissolved oxygen-based bioreactor feed controller (DOstat). This behavior, if left unattended, led to the irreversible loss of culture productivity, 1 to 2 days after growth on methanol commenced, presumably through the accumulation of incompletely oxidized intermediates. To provide insights into how fermentation operation conditions and strain variations might contribute to this phenomenon a theoretical study was initiated. In this article, a simple mathematical model of the closed-loop DOstat is developed and analyzed with the goal of deriving theoretical stability criteria applicable to the design of metabolic feed controllers during high-cell-density fermentations. The model consists of a system of differential, integral, and algebraic equations describing the biological process and the components of the standard proportional-integral (PI) feedback controller. Inputs into the process model include metabolic pathway information, oxidative metabolism stoichiometry, and substrate uptake kinetics. Frequency-response analysis and the Bode stability criterion are applied to derive controller stability criteria with particular emphasis on elucidating the role(s) that model parameters, both biological and operational, have on system stability. The results of this analysis are used to construct a closed-loop fermentation-operating diagram relating fermentation operating parameters to the oxidative capacity of the culture. The utility of this analysis is demonstrated through the application of the results to the design and stabilization of the DOstat during high-density fermentations of P. pastoris growing on methanol or glycerol. From this analysis, it is possible to conclude that, when the rate of oxygen transfer approaches in magnitude the rate of oxygen utilization, the potential for controller destabilization is greatest. Under these conditions, the region of parameter space associated with stable controller operations is further constrained. Because the only system-specific experimental inputs into the model are the routinely measured residual substrate and dissolved oxygen concentrations, the framework presented should provide simple and practical theoretical guidelines relevant to the design of similar industrial fermentation feed controllers independent of the specifics of the biological system at hand.     

Ecological indicators: Imperative to sustainable forest management

Sustainable forest management (SFM) deals with ecologically sound practices that maintain the forest ecosystem integrity, productivity, resilience and biodiversity. Ecological sustainability ensures continuing function of ecosystems which are considered as ecological life support system. Several attempts have been made world over to develop criteria and indicators, which are specific to various forestry conditions and recognized as appropriate tools for assessing and monitoring progress towards sustainable forest management. In India, the process for measuring forest sustainability has started by evolving national level set of Criteria and indicators in the form of Bhopal–India process. The Bhopal–India process specifies 8 criteria and 43 indicators. The first 4 criteria pertain exclusively to ecology with 21 related indicators. Thus, nearly half of the criteria and indicators pertain to ecological dimensions that largely govern sustainability of forests. Rest of the criteria of the base set pertains to economic and social aspects with related indicators. This provides holistic approach of monitoring the forest resources.     

Membrane Phospholipid Redistribution in Cytokinesis： A Theoretical Model

In cell mitosis, cytokinesis is a major deformation process, during which the site of the contractile ring is determined by the biochemical stimulus from asters of the mitotic apparatus, actin and myosin assembly is related to the motion of membrane phospholipids, and local distribution and arrangement of the microfilament cytoskeleton are different at different cytokinesis stages. Based on the Zinemanas-Nir model, a new model is proposed in this study to simulate the entire process by coupling the biochemical stimulus with the mechanical actions. There were three assumptions in this model： the movements of phospholipid proteins are driven by gradients of biochemical stimulus on the membrane surface; the local assembly of actin and myosin filament depends on the amount of phospholipid proteins at the same location; and the surface tension includes membrane tensions due to both the passive deformation of the membrane and the active contraction of actin filament, which is determined by microfilament redistribution and rearrangement. This model could explain the dynamic movement of microfilaments during cytokinesis and predict cell deformation. The calculated results from this model demonstrated that the reorientation of phospholipid proteins and the redistribution and reorientation of microfilaments may play a crucial role in cell division. This model may better represent the cytokinesis process by the introduction of biochemical stimulus.     

A modular approach to situation identification of the dynamics of bacterial populations synthesizing poly-β-hydroxybutyrate

Biotechnological processes involving bacteria are strongly nonlinear. Therefore, both their productivity and the final product quality may be considerably improved by applying appropriate control strategies to modulate behavior of the bacteria during transitional states. This requires advance identification of indicative signals by off-line investigation (i.e. experimental analysis) and on-line monitoring, (i.e. real time evaluation). A modular scheme is presented for doing this, which incorporates an Extended Kalman Filter and a prediction filter. If this is based on a suitable process-feature vector, which must be chosen in advance, the system can provide sufficient information to trigger appropriate feedback signals. Thus, it can provide a key element in modular situation control, allowing continuously periodic process management. In this publication the individual modules involved, and their assembly into an integrated system are described. Potential problems concerning selection of the feature vector, and experimental results are also discussed.     

蛋白质预算：合成生物学的成本标尺

合成生物学以创建人工生命体系为目的.实践中人们希望人工生命体系具有更强的生产能力、转化能力、环境适应与监测能力,从而获得更优质的生产方式.生命体系的优化涉及到多层次的调控网络,而根本上还是对细胞中蛋白质的含量、定位、活性的控制.在蛋白质表达水平上进行控制是合成生物学元件设计、模块组装以及适配性研究最核心的手段.类似于工厂中的成本计算,合成生物学创建的人工生命体系(人工细胞工厂)以蛋白质预算为依据.优化蛋白质预算的研究策略已经成功应用于合成生物学研究实践中.     

A method of intelligent recommendation using task ontology

This study proposed a method of developing an intelligent recommendation system for automotive parts assembly. The proposed system will display the detailed information and the list components which make up the relevant part that an user wants through the database using the ontology when selecting an automotive part that an user intends to learn or to be guided of. This study is to design task ontology based on Hierarchical Taxonomy so as to achieve productivity enhancement, cost reduction and outcome improvement through recommendations based on intelligence and personalization depending on the worker’s present situation or context of task in charge when assembly of automotive parts is conducted. For this, composing elements of an engine and upper/lower relationships were expressed using hierarchical structure Taxonomy. The intelligent recommendation system for parts is offered to users through determining the automatic recommendation order between parts using the weights. This study has experimented the principles of the recommendation system and the method of setting the weights by setting two scenarios.     

Assessment of the Automobile Assembly Paint Process for Energy, Environmental, and Economic Improvement

A coat of paint adds considerable value to an automobile. In addition to consuming up to 60% of the energy needed by automobile assembly plants, however, the painting process also creates both economic and environmental impacts. This study investigated the degree of cost and environmental impact improvement that can be expected when modifications are considered for existing paint processes through heat integration. In order to accomplish this goal, a mathematical model was created to describe the energy use, costs, and environmental impacts from energy consumption in an automobile assembly painting facility. The model agrees with measured energy consumption data for process heating and electricity demand to within about 15% for one Michigan truck facility from which model input parameters were obtained. Thermal pinch analysis determined an energy conservation target of 58% of paint process energy demand. A heat exchanger network optimization study was conducted in order to determine how closely the network design could achieve this target. The resulting heat exchanger network design was profitable based on a discounted cash flow analysis and may achieve reductions in total corporate energy consumption of up to 16% if implemented corporatewide at a major automobile manufacturer.     

A method for assessing work productivity and flexibility in livestock farms

Changes affecting livestock farming systems have made farm work a central concern for both the sector and for farmers themselves. Increased pressure on farms to be competitive and productive together with farmers' demand for greater autonomy, holidays or time to spend on private activities and the family converge to underline the two key dimensions of work - productivity and flexibility - required for the assessment of work organization. This paper proposes a method called the QuaeWork (QUAlification and Evaluation of Work in livestock farms) to assess work productivity and flexibility on a farm, and its use to identify how livestock management can contribute to work organization on dairy farms. The QuaeWork method was set up through an iterative process combining surveys conducted with farmers in two regions of France, discussions with different experts and literature review. The QuaeWork was applied on a sample of seven dairy farms in the southern Massif Central in France to identify patterns of how livestock management contributes to work organization. The QuaeWork was used to analyse work organization over the year through a systemic approach to the farm, integrating interactions between herd and land management, workforce composition, equipment facilities and combinations of activities through a characterization of 'who does what, when and for how long'. The criteria for assessing work productivity were work duration (routine work, seasonal work) and work efficiency (per livestock unit or hectare of utilized agricultural area). The criteria for assessing work flexibility were room for manoeuvre and adjustments to internal and external events. The three main patterns of livestock management practices to work organization were identified. In pattern-1, farmers used indoor stable feeding practices with delegated work, with moderate room for manoeuvre and efficiency. In pattern-3, farmers used simplified milking, reproduction and breeding practices to seasonalize work and make it efficient with consistent room for manoeuvre. The method suggests social sustainability criteria to assess work productivity and flexibility, which are important for making reasoned decisions on livestock farm changes, especially innovations. Researchers could usefully exploit the QuaeWork to integrate work objectives (productivity, flexibility) into technical and economic goals.     

Simulations Show that Virus Assembly and Budding Are Facilitated by Membrane Microdomains

For many viruses, assembly and budding occur simultaneously during virion formation. Understanding the mechanisms underlying this process could promote biomedical efforts to block viral propagation and enable use of capsids in nanomaterials applications. To this end, we have performed molecular dynamics simulations on a coarse-grained model that describes virus assembly on a fluctuating lipid membrane. Our simulations show that the membrane can promote association of adsorbed subunits through dimensional reduction, but it also introduces thermodynamic and kinetic effects that can inhibit complete assembly. We find several mechanisms by which membrane microdomains, such as lipid rafts, reduce these effects, and thus, enhance assembly. We show how these predicted mechanisms can be experimentally tested. Furthermore, the simulations demonstrate that assembly and budding depend crucially on the system dynamics via multiple timescales related to membrane deformation, protein diffusion, association, and adsorption onto the membrane.     

Exhaustive analysis of the modular structure of the spliceosomal assembly network: a petri net approach

Spliceosomes are macro-complexes involving hundreds of proteins with many functional interactions. Spliceosome assembly belongs to the key processes that enable splicing of mRNA and modulate alternative splicing. A detailed list of factors involved in spliceosomal reactions has been assorted over the past decade, but, their functional interplay is often unknown and most of the present biological models cover only parts of the complete assembly process. It is a challenging task to build a computational model that integrates dispersed knowledge and combines a multitude of reaction schemes proposed earlier.Because for most reactions involved in spliceosome assembly kinetic parameters are not available, we propose a discrete modeling using Petri nets, through which we are enabled to get insights into the system's behavior via computation of structural and dynamic properties. In this paper, we compile and examine reactions from experimental reports that contribute to a functional spliceosome. All these reactions form a network, which describes the inventory and conditions necessary to perform the splicing process. The analysis is mainly based on system invariants. Transition invariants (T-invariants) can be interpreted as signaling routes through the network. Due to the huge number of T-invariants that arise with increasing network size and complexity, maximal common transition sets (MCTS) and T-clusters were used for further analysis. Additionally, we introduce a false color map representation, which allows a quick survey of network modules and the visual detection of single reactions or reaction sequences, which participate in more than one signaling route. We designed a structured model of spliceosome assembly, which combines the demands on a platform that i) can display involved factors and concurrent processes, ii) offers the possibility to run computational methods for knowledge extraction, and iii) is successively extendable as new insights into spliceosome function are reported by experimental reports. The network consists of 161 transitions (reactions) and 140 places (reactants). All reactions are part of at least one of the 71 T-invariants. These T-invariants define pathways, which are in good agreement with the current knowledge and known hypotheses on reaction sequences during spliceosome assembly, hence contributing to a functional spliceosome. We demonstrate that present knowledge, in particular of the initial part of the assembly process, describes parallelism and interaction of signaling routes, which indicate functional redundancy and reflect the dependency of spliceosome assembly initiation on different cellular conditions. The complexity of the network is further increased by two switches, which introduce alternative routes during A-complex formation in early spliceosome assembly and upon transition from the B-complex to the C-complex. By compiling known reactions into a complete network, the combinatorial nature of invariant computation leads to pathways that have previously not been described as connected routes, although their constituents were known. T-clusters divide the network into modules, which we interpret as building blocks in spliceosome maturation. We conclude that Petri net representations of large biological networks and system invariants, are well-suited as a means for validating the integration of experimental knowledge into a consistent model. Based on this network model, the design of further experiments is facilitated.     

Sources of carbon productivity change: A decomposition and disaggregation analysis based on global Luenberger productivity indicator and endogenous directional distance function

The measurement of carbon productivity makes the effort of global climate change mitigation accountable and helps to formulate policies and prioritize actions for economic growth, energy conservation, and carbon emissions control. Previous studies arbitrarily predetermined the directions of directional distance function in calculating the carbon productivity indicator, and the traditional carbon productivity indicator itself is not capable of identifying the contribution of different energy driven carbon emissions in carbon productivity change. Through utilizing an endogenous directional distance function selecting approach and a global productivity index, this paper proposes a global Luenberger carbon productivity indicator for computing carbon productivity change. This carbon productivity indicator can be further decomposed into three components that respectively identify the best practice gap change, pure efficiency change, and scale efficiency change. Moreover, the carbon productivity indicator is shown as a combination of individual carbon emissions productivity indicators that account for the contribution of different fossil fuel driven carbon emissions (i.e. coal driven CO₂, oil driven CO₂, and natural gas driven CO₂) toward the carbon productivity change. Our carbon productivity indicator is employed to measure and decompose the carbon productivity changes of 37 major carbon emitting countries and regions over 1995–2009. The main findings include: (i) endogenous directions identifying the largest improvement potentials are noticeably different from exogenous directions in estimating the inefficiencies of undesirable outputs. (ii) Carbon productivity indicator calculated with the consideration of emission structure provides a more significant estimation on productivity change. (iii) The aggregated carbon productivity and the specific energy driven carbon productivities significantly improve over our study period which are primarily attributed to technical progress. (iv) Empirical results imply that policies focused on researching and developing energy utilization and carbon control technologies might not be enough; it is also essential to encourage technical efficiency catching-up and economic scale management.     

How to Deal with Resource Productivity

Resource productivity enhancement stands at the center of tackling issues on environmental pollution and resource scarcity. Identifying influential socioeconomic factors should be the first step in establishing and improving resource management policy. This study compares and analyzes data from multiple countries to construct a resource productivity simulation model. The socioeconomic factors and their characteristic patterns are discussed in detail. The results demonstrate that the major factors influencing resource productivity include income level, population density, economic structure, energy structure, and raw material trade. Among these factors, the three most important are income level, population density, and economic structure. The influencing patterns can be summarized as follows: (1) Resource productivity increases with increasing income levels. (2) Countries with high population density are inclined to demonstrate high resource productivity. (3) The economic structure shows a biphase influence on resource productivity, that is, during industrialization, decreased agricultural activity and increased industrial activity lead to higher resource productivity. On the other hand, after industrialization, decreasing industrial activity and an expanding service sector become the major impetus of resource productivity enhancement. (4) Raw material export demonstrates a negative effect on resource productivity. Countries that depend heavily on raw material export show a unique resource productivity evolution pattern. For these countries, relatively high resource productivity in low income phases and relatively low resource productivity in high income phases show only small increases in resource efficiency and economic growth. Finally, insights from the study are transformed into suggestions for sustainable resource management and resource productivity enhancement.     

Application of model discriminating experimental design for modeling and development of a fermentative fed-batch L-valine production process

A model discriminating experimental design approach for fed-batch processes has been developed and applied to the fermentative production of L-valine by a genetically modified Corynebacterium glutamicum strain possessing multiple auxotrophies as an example. Being faced with the typical situation of uncertain model information based on preliminary experiments, model discriminating design was successfully applied to improve discrimination between five competing models. Within the same modeling and experimental design framework, also the planning of an optimized production process with respect to the total volumetric productivity is shown. Simulation results were experimentally affirmed, yielding an increased total volumetric productivity of 6.2 mM L-valine per hour. However, also so far unknown metabolic mechanisms were observed in the optimized process, underlining the importance of process optimization during modeling to avoid problems of extreme extrapolation of model predictions during the final process optimization.     

Species assembly in model ecosystems, II: Results of the assembly process

In the companion paper of this set (Capitán and Cuesta, 2010) we have developed a full analytical treatment of the model of species assembly introduced in Capitán et al. (2009). This model is based on the construction of an assembly graph containing all viable configurations of the community, and the definition of a Markov chain whose transitions are the transformations of communities by new species invasions. In the present paper we provide an exhaustive numerical analysis of the model, describing the average time to the recurrent state, the statistics of avalanches, and the dependence of the results on the amount of available resource. Our results are based on the fact that the Markov chain provides an asymptotic probability distribution for the recurrent states, which can be used to obtain averages of observables as well as the time variation of these magnitudes during succession, in an exact manner. Since the absorption times into the recurrent set are found to be comparable to the size of the system, the end state is quickly reached (in units of the invasion time). Thus, the final ecosystem can be regarded as a fluctuating complex system where species are continually replaced by newcomers without ever leaving the set of recurrent patterns. The assembly graph is dominated by pathways in which most invasions are accepted, triggering small extinction avalanches. Through the assembly process, communities become less resilient (e.g., have a higher return time to equilibrium) but become more robust in terms of resistance against new invasions.