Modeling and Implementation of Cattle/Beef Supply Chain Traceability Using a Distributed RFID-Based Framework in China.

PubMed

Liang, Wanjie; Cao, Jing; Fan, Yan; Zhu, Kefeng; Dai, Qiwei

2015-01-01

In recent years, traceability systems have been developed as effective tools for improving the transparency of supply chains, thereby guaranteeing the quality and safety of food products. In this study, we proposed a cattle/beef supply chain traceability model and a traceability system based on radio frequency identification (RFID) technology and the EPCglobal network. First of all, the transformations of traceability units were defined and analyzed throughout the cattle/beef chain. Secondly, we described the internal and external traceability information acquisition, transformation, and transmission processes throughout the beef supply chain in detail, and explained a methodology for modeling traceability information using the electronic product code information service (EPCIS) framework. Then, the traceability system was implemented based on Fosstrak and FreePastry software packages, and animal ear tag code and electronic product code (EPC) were employed to identify traceability units. Finally, a cattle/beef supply chain included breeding business, slaughter and processing business, distribution business and sales outlet was used as a case study to evaluate the beef supply chain traceability system. The results demonstrated that the major advantages of the traceability system are the effective sharing of information among business and the gapless traceability of the cattle/beef supply chain.

Modeling and Implementation of Cattle/Beef Supply Chain Traceability Using a Distributed RFID-Based Framework in China

PubMed Central

Liang, Wanjie; Cao, Jing; Fan, Yan; Zhu, Kefeng; Dai, Qiwei

2015-01-01

In recent years, traceability systems have been developed as effective tools for improving the transparency of supply chains, thereby guaranteeing the quality and safety of food products. In this study, we proposed a cattle/beef supply chain traceability model and a traceability system based on radio frequency identification (RFID) technology and the EPCglobal network. First of all, the transformations of traceability units were defined and analyzed throughout the cattle/beef chain. Secondly, we described the internal and external traceability information acquisition, transformation, and transmission processes throughout the beef supply chain in detail, and explained a methodology for modeling traceability information using the electronic product code information service (EPCIS) framework. Then, the traceability system was implemented based on Fosstrak and FreePastry software packages, and animal ear tag code and electronic product code (EPC) were employed to identify traceability units. Finally, a cattle/beef supply chain included breeding business, slaughter and processing business, distribution business and sales outlet was used as a case study to evaluate the beef supply chain traceability system. The results demonstrated that the major advantages of the traceability system are the effective sharing of information among business and the gapless traceability of the cattle/beef supply chain. PMID:26431340

Optimal design of supply chain network under uncertainty environment using hybrid analytical and simulation modeling approach

NASA Astrophysics Data System (ADS)

Chiadamrong, N.; Piyathanavong, V.

2017-12-01

Models that aim to optimize the design of supply chain networks have gained more interest in the supply chain literature. Mixed-integer linear programming and discrete-event simulation are widely used for such an optimization problem. We present a hybrid approach to support decisions for supply chain network design using a combination of analytical and discrete-event simulation models. The proposed approach is based on iterative procedures until the difference between subsequent solutions satisfies the pre-determined termination criteria. The effectiveness of proposed approach is illustrated by an example, which shows closer to optimal results with much faster solving time than the results obtained from the conventional simulation-based optimization model. The efficacy of this proposed hybrid approach is promising and can be applied as a powerful tool in designing a real supply chain network. It also provides the possibility to model and solve more realistic problems, which incorporate dynamism and uncertainty.

Invited commentary: Lost in estimation--searching for alternatives to markov chains to fit complex Bayesian models.

PubMed

Molitor, John

2012-03-01

Bayesian methods have seen an increase in popularity in a wide variety of scientific fields, including epidemiology. One of the main reasons for their widespread application is the power of the Markov chain Monte Carlo (MCMC) techniques generally used to fit these models. As a result, researchers often implicitly associate Bayesian models with MCMC estimation procedures. However, Bayesian models do not always require Markov-chain-based methods for parameter estimation. This is important, as MCMC estimation methods, while generally quite powerful, are complex and computationally expensive and suffer from convergence problems related to the manner in which they generate correlated samples used to estimate probability distributions for parameters of interest. In this issue of the Journal, Cole et al. (Am J Epidemiol. 2012;175(5):368-375) present an interesting paper that discusses non-Markov-chain-based approaches to fitting Bayesian models. These methods, though limited, can overcome some of the problems associated with MCMC techniques and promise to provide simpler approaches to fitting Bayesian models. Applied researchers will find these estimation approaches intuitively appealing and will gain a deeper understanding of Bayesian models through their use. However, readers should be aware that other non-Markov-chain-based methods are currently in active development and have been widely published in other fields.

Learning In networks

NASA Technical Reports Server (NTRS)

Buntine, Wray L.

1995-01-01

Intelligent systems require software incorporating probabilistic reasoning, and often times learning. Networks provide a framework and methodology for creating this kind of software. This paper introduces network models based on chain graphs with deterministic nodes. Chain graphs are defined as a hierarchical combination of Bayesian and Markov networks. To model learning, plates on chain graphs are introduced to model independent samples. The paper concludes by discussing various operations that can be performed on chain graphs with plates as a simplification process or to generate learning algorithms.

Biokinetic food chain modeling of waterborne selenium pulses into aquatic food chains: Implications for water quality criteria.

PubMed

DeForest, David K; Pargee, Suzanne; Claytor, Carrie; Canton, Steven P; Brix, Kevin V

2016-04-01

We evaluated the use of biokinetic models to predict selenium (Se) bioaccumulation into model food chains after short-term pulses of selenate or selenite into water. Both periphyton- and phytoplankton-based food chains were modeled, with Se trophically transferred to invertebrates and then to fish. Whole-body fish Se concentrations were predicted based on 1) the background waterborne Se concentration, 2) the magnitude of the Se pulse, and 3) the duration of the Se pulse. The models were used to evaluate whether the US Environmental Protection Agency's (USEPA's) existing acute Se criteria and their recently proposed intermittent Se criteria would be protective of a whole-body fish Se tissue-based criterion of 8.1 μg g(-1) dry wt. Based on a background waterborne Se concentration of 1 μg L(-1) and pulse durations of 1 d and 4 d, the Se pulse concentrations predicted to result in a whole-body fish Se concentration of 8.1 μg g(-1) dry wt in the most conservative model food chains were 144 and 35 μg L(-1), respectively, for selenate and 57 and 16 μg L(-1), respectively, for selenite. These concentrations fall within the range of various acute Se criteria recommended by the USEPA based on direct waterborne toxicity, suggesting that these criteria may not always be protective against bioaccumulation-based toxicity that could occur after short-term pulses. Regarding the USEPA's draft intermittent Se criteria, the biokinetic modeling indicates that they may be overly protective for selenate pulses but potentially underprotective for selenite pulses. Predictions of whole-body fish Se concentrations were highly dependent on whether the food chain was periphyton- or phytoplankton-based, because the latter had much greater Se uptake rate constants. Overall, biokinetic modeling provides an approach for developing acute Se criteria that are protective against bioaccumulation-based toxicity after trophic transfer, and it is also a useful tool for evaluating averaging periods for chronic Se criteria. © 2015 SETAC.

Modelling a flows in supply chain with analytical models: Case of a chemical industry

NASA Astrophysics Data System (ADS)

Benhida, Khalid; Azougagh, Yassine; Elfezazi, Said

2016-02-01

This study is interested on the modelling of the logistics flows in a supply chain composed on a production sites and a logistics platform. The contribution of this research is to develop an analytical model (integrated linear programming model), based on a case study of a real company operating in the phosphate field, considering a various constraints in this supply chain to resolve the planning problems for a better decision-making. The objectives of this model is to determine and define the optimal quantities of different products to route, to and from the various entities in the supply chain studied.

Predicting the stability of nanodevices

NASA Astrophysics Data System (ADS)

Lin, Z. Z.; Yu, W. F.; Wang, Y.; Ning, X. J.

2011-05-01

A simple model based on the statistics of single atoms is developed to predict the stability or lifetime of nanodevices without empirical parameters. Under certain conditions, the model produces the Arrhenius law and the Meyer-Neldel compensation rule. Compared with the classical molecular-dynamics simulations for predicting the stability of monatomic carbon chain at high temperature, the model is proved to be much more accurate than the transition state theory. Based on the ab initio calculation of the static potential, the model can give out a corrected lifetime of monatomic carbon and gold chains at higher temperature, and predict that the monatomic chains are very stable at room temperature.

Research on manufacturing service behavior modeling based on block chain theory

NASA Astrophysics Data System (ADS)

Zhao, Gang; Zhang, Guangli; Liu, Ming; Yu, Shuqin; Liu, Yali; Zhang, Xu

2018-04-01

According to the attribute characteristics of processing craft, the manufacturing service behavior is divided into service attribute, basic attribute, process attribute, resource attribute. The attribute information model of manufacturing service is established. The manufacturing service behavior information is successfully divided into public and private domain. Additionally, the block chain technology is introduced, and the information model of manufacturing service based on block chain principle is established, which solves the problem of sharing and secreting information of processing behavior, and ensures that data is not tampered with. Based on the key pairing verification relationship, the selective publishing mechanism for manufacturing information is established, achieving the traceability of product data, guarantying the quality of processing quality.

Chains are more flexible under tension

PubMed Central

Carrillo, Jan-Michael Y.; Rubinstein, Michael

2010-01-01

The mechanical response of networks, gels, and brush layers is a manifestation of the elastic properties of the individual macromolecules. Furthermore, the elastic response of macromolecules to an applied force is the foundation of the single-molecule force spectroscopy techniques. The two main classes of models describing chain elasticity include the worm-like and freely-jointed chain models. The selection between these two classes of models is based on the assumptions about chain flexibility. In many experimental situations the choice is not clear and a model describing the crossover between these two limiting classes is therefore in high demand. We are proposing a unified chain deformation model which describes the force-deformation curve in terms of the chain bending constant K and bond length b. This model demonstrates that the worm-like and freely-jointed chain models correspond to two different regimes of polymer deformation and the crossover between these two regimes depends on the chain bending rigidity and the magnitude of the applied force. Polymer chains with bending constant K>1 behave as a worm-like chain under tension in the interval of the applied forces f ≤ KkBT/b and as a freely-jointed chain for f ≥ KkBT/b (kB is the Boltzmann constant and T is the absolute temperature). The proposed crossover expression for chain deformation is in excellent agreement with the results of the molecular dynamics simulations of chain deformation and single-molecule deformation experiments of biological and synthetic macromolecules. PMID:21415940

Research of Trust Chain of Operating System

NASA Astrophysics Data System (ADS)

Li, Hongjiao; Tian, Xiuxia

Trust chain is one of the key technologies in designing secure operating system based on TC technology. Constructions of trust chain and trust models are analyzed. Future works in these directions are discussed.

Molecular modeling of calmodulin: a comparison with crystallographic data

NASA Technical Reports Server (NTRS)

McDonald, J. J.; Rein, R.

1989-01-01

Two methods of side-chain placement on a modeled protein have been examined. Two molecular models of calmodulin were constructed that differ in the treatment of side chains prior to optimization of the molecule. A virtual bond analysis program developed by Purisima and Scheraga was used to determine the backbone conformation based on 2.2 angstroms resolution C alpha coordinates for the molecules. In the first model, side chains were initially constructed in an extended conformation. In the second model, a conformational grid search technique was employed. Calcium ions were treated explicitly during energy optimization using CHARMM. The models are compared to a recently published refined crystal structure of calmodulin. The results indicate that the initial choices for side-chains, but also significant effects on the main-chain conformation and supersecondary structure. The conformational differences are discussed. Analysis of these and other methods makes possible the formulation of a methodology for more appropriate side-chain placement in modeled proteins.

Cloud Computing Value Chains: Understanding Businesses and Value Creation in the Cloud

NASA Astrophysics Data System (ADS)

Mohammed, Ashraf Bany; Altmann, Jörn; Hwang, Junseok

Based on the promising developments in Cloud Computing technologies in recent years, commercial computing resource services (e.g. Amazon EC2) or software-as-a-service offerings (e.g. Salesforce. com) came into existence. However, the relatively weak business exploitation, participation, and adoption of other Cloud Computing services remain the main challenges. The vague value structures seem to be hindering business adoption and the creation of sustainable business models around its technology. Using an extensive analyze of existing Cloud business models, Cloud services, stakeholder relations, market configurations and value structures, this Chapter develops a reference model for value chains in the Cloud. Although this model is theoretically based on porter's value chain theory, the proposed Cloud value chain model is upgraded to fit the diversity of business service scenarios in the Cloud computing markets. Using this model, different service scenarios are explained. Our findings suggest new services, business opportunities, and policy practices for realizing more adoption and value creation paths in the Cloud.

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics.

PubMed

Wu, Xiao-Lin; Sun, Chuanyu; Beissinger, Timothy M; Rosa, Guilherme Jm; Weigel, Kent A; Gatti, Natalia de Leon; Gianola, Daniel

2012-09-25

Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel computing can overcome the bottlenecks that can arise from series computing. Hence, a major goal of the present study is to bridge the gap to high-performance Bayesian computation in the context of animal breeding and genetics. Parallel Monte Carlo Markov chain algorithms and strategies are described in the context of animal breeding and genetics. Parallel Monte Carlo algorithms are introduced as a starting point including their applications to computing single-parameter and certain multiple-parameter models. Then, two basic approaches for parallel Markov chain Monte Carlo are described: one aims at parallelization within a single chain; the other is based on running multiple chains, yet some variants are discussed as well. Features and strategies of the parallel Markov chain Monte Carlo are illustrated using real data, including a large beef cattle dataset with 50K SNP genotypes. Parallel Markov chain Monte Carlo algorithms are useful for computing complex Bayesian models, which does not only lead to a dramatic speedup in computing but can also be used to optimize model parameters in complex Bayesian models. Hence, we anticipate that use of parallel Markov chain Monte Carlo will have a profound impact on revolutionizing the computational tools for genomic selection programs.

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics

PubMed Central

2012-01-01

Background Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel computing can overcome the bottlenecks that can arise from series computing. Hence, a major goal of the present study is to bridge the gap to high-performance Bayesian computation in the context of animal breeding and genetics. Results Parallel Monte Carlo Markov chain algorithms and strategies are described in the context of animal breeding and genetics. Parallel Monte Carlo algorithms are introduced as a starting point including their applications to computing single-parameter and certain multiple-parameter models. Then, two basic approaches for parallel Markov chain Monte Carlo are described: one aims at parallelization within a single chain; the other is based on running multiple chains, yet some variants are discussed as well. Features and strategies of the parallel Markov chain Monte Carlo are illustrated using real data, including a large beef cattle dataset with 50K SNP genotypes. Conclusions Parallel Markov chain Monte Carlo algorithms are useful for computing complex Bayesian models, which does not only lead to a dramatic speedup in computing but can also be used to optimize model parameters in complex Bayesian models. Hence, we anticipate that use of parallel Markov chain Monte Carlo will have a profound impact on revolutionizing the computational tools for genomic selection programs. PMID:23009363

Chemical supply chain modeling for analysis of homeland security events

DOE PAGES

Ehlen, Mark A.; Sun, Amy C.; Pepple, Mark A.; ...

2013-09-06

The potential impacts of man-made and natural disasters on chemical plants, complexes, and supply chains are of great importance to homeland security. To be able to estimate these impacts, we developed an agent-based chemical supply chain model that includes: chemical plants with enterprise operations such as purchasing, production scheduling, and inventories; merchant chemical markets, and multi-modal chemical shipments. Large-scale simulations of chemical-plant activities and supply chain interactions, running on desktop computers, are used to estimate the scope and duration of disruptive-event impacts, and overall system resilience, based on the extent to which individual chemical plants can adjust their internal operationsmore » (e.g., production mixes and levels) versus their external interactions (market sales and purchases, and transportation routes and modes). As a result, to illustrate how the model estimates the impacts of a hurricane disruption, a simple example model centered on 1,4-butanediol is presented.« less

Developing a suitable model for supplier selection based on supply chain risks: an empirical study from Iranian pharmaceutical companies.

PubMed

Mehralian, Gholamhossein; Rajabzadeh Gatari, Ali; Morakabati, Mohadese; Vatanpour, Hossein

2012-01-01

The supply chain represents the critical link between the development of new product and the market in pharmaceutical industry. Over the years, improvements made in supply chain operations have focused largely on ways to reduce cost and gain efficiencies in scale. In addition, powerful regulatory and market forces have provided new incentives for pharmaceutical firms to basically rethink the way they produce and distribute products, and also to re-imagine the role of the supply chain in driving strategic growth, brand differentiation and economic value in the health continuum. The purpose of this paper is to formulate basic factors involved in risk analysis of pharmaceutical industry, and also determine the effective factors involved in suppliers selection and their priorities. This paper is based on the results of literature review, experts' opinion acquisition, statistical analysis and also using MADM models on data gathered from distributed questionnaires. The model consists of the following steps and components: first factors involved in to supply chain risks are determined. Based on them a framework is considered. According the result of statistical analysis and MADM models the risk factors are formulated. The paper determines the main components and influenceial factors involving in the supply chain risks. Results showed that delivery risk can make an important contribution to mitigate the risk of pharmaceutical industry.

Developing a Suitable Model for Supplier Selection Based on Supply Chain Risks: An Empirical Study from Iranian Pharmaceutical Companies

PubMed Central

Mehralian, Gholamhossein; Rajabzadeh Gatari, Ali; Morakabati, Mohadese; Vatanpour, Hossein

2012-01-01

The supply chain represents the critical link between the development of new product and the market in pharmaceutical industry. Over the years, improvements made in supply chain operations have focused largely on ways to reduce cost and gain efficiencies in scale. In addition, powerful regulatory and market forces have provided new incentives for pharmaceutical firms to basically rethink the way they produce and distribute products, and also to re-imagine the role of the supply chain in driving strategic growth, brand differentiation and economic value in the health continuum. The purpose of this paper is to formulate basic factors involved in risk analysis of pharmaceutical industry, and also determine the effective factors involved in suppliers selection and their priorities. This paper is based on the results of literature review, experts’ opinion acquisition, statistical analysis and also using MADM models on data gathered from distributed questionnaires. The model consists of the following steps and components: first factors involved in to supply chain risks are determined. Based on them a framework is considered. According the result of statistical analysis and MADM models the risk factors are formulated. The paper determines the main components and influenceial factors involving in the supply chain risks. Results showed that delivery risk can make an important contribution to mitigate the risk of pharmaceutical industry. PMID:24250442

Chain-Based Communication in Cylindrical Underwater Wireless Sensor Networks

PubMed Central

Javaid, Nadeem; Jafri, Mohsin Raza; Khan, Zahoor Ali; Alrajeh, Nabil; Imran, Muhammad; Vasilakos, Athanasios

2015-01-01

Appropriate network design is very significant for Underwater Wireless Sensor Networks (UWSNs). Application-oriented UWSNs are planned to achieve certain objectives. Therefore, there is always a demand for efficient data routing schemes, which can fulfill certain requirements of application-oriented UWSNs. These networks can be of any shape, i.e., rectangular, cylindrical or square. In this paper, we propose chain-based routing schemes for application-oriented cylindrical networks and also formulate mathematical models to find a global optimum path for data transmission. In the first scheme, we devise four interconnected chains of sensor nodes to perform data communication. In the second scheme, we propose routing scheme in which two chains of sensor nodes are interconnected, whereas in third scheme single-chain based routing is done in cylindrical networks. After finding local optimum paths in separate chains, we find global optimum paths through their interconnection. Moreover, we develop a computational model for the analysis of end-to-end delay. We compare the performance of the above three proposed schemes with that of Power Efficient Gathering System in Sensor Information Systems (PEGASIS) and Congestion adjusted PEGASIS (C-PEGASIS). Simulation results show that our proposed 4-chain based scheme performs better than the other selected schemes in terms of network lifetime, end-to-end delay, path loss, transmission loss, and packet sending rate. PMID:25658394

Supply chain analysis of e-tailing versus retailing operation - a case study

NASA Astrophysics Data System (ADS)

Kumar, Sameer; Tiffany, Maryellen; Vaidya, Salil

2016-07-01

The swift growth of e-commerce or e-tailing as a consumer retail channel has made it a serious competitor to traditional retail channels and is changing consumers' purchasing behaviour. The purpose of this case study, based on Target and Amazon.com, is to analyse the attributes of traditional retailing, e-tailing, and hybrid supply chain models to form conclusions about the feasibility of an idealised supply chain model for the future. An integrated and generalised modelling framework is used that incorporates Six Sigma - define, measure, analyse, improve, control methodology leveraging various tools, including process flow maps, cause and effect diagram, performance efficiency metrics, failure mode and effects analysis (FMEA), and Monte Carlo simulation. Based on this analysis and research, the conclusion is that the idealised supply chain of the future may evolve into a hybrid supply chain, which includes both e-tail and retail channels. The main recommendations from this study include assessing the risks of migrating to such a hybrid supply chain and to leverage the recommended actions provided in the hybrid FMEA. To facilitate more effective and mature processes, this study can guide researchers in exhaustive empirical evaluations of hybrid supply chains, gather experiences and lessons learned for practitioners.

Scale-Dependent Stiffness and Internal Tension of a Model Brush Polymer

NASA Astrophysics Data System (ADS)

Berezney, John P.; Marciel, Amanda B.; Schroeder, Charles M.; Saleh, Omar A.

2017-09-01

Bottle-brush polymers exhibit closely grafted side chains that interact by steric repulsion, thereby causing stiffening of the main polymer chain. We use single-molecule elasticity measurements of model brush polymers to quantify this effect. We find that stiffening is only significant on long length scales, with the main chain retaining flexibility on short scales. From the elasticity data, we extract an estimate of the internal tension generated by side-chain repulsion; this estimate is consistent with the predictions of blob-based scaling theories.

Modeling relief demands in an emergency supply chain system under large-scale disasters based on a queuing network.

PubMed

He, Xinhua; Hu, Wenfa

2014-01-01

This paper presents a multiple-rescue model for an emergency supply chain system under uncertainties in large-scale affected area of disasters. The proposed methodology takes into consideration that the rescue demands caused by a large-scale disaster are scattered in several locations; the servers are arranged in multiple echelons (resource depots, distribution centers, and rescue center sites) located in different places but are coordinated within one emergency supply chain system; depending on the types of rescue demands, one or more distinct servers dispatch emergency resources in different vehicle routes, and emergency rescue services queue in multiple rescue-demand locations. This emergency system is modeled as a minimal queuing response time model of location and allocation. A solution to this complex mathematical problem is developed based on genetic algorithm. Finally, a case study of an emergency supply chain system operating in Shanghai is discussed. The results demonstrate the robustness and applicability of the proposed model.

Modeling Relief Demands in an Emergency Supply Chain System under Large-Scale Disasters Based on a Queuing Network

PubMed Central

He, Xinhua

2014-01-01

This paper presents a multiple-rescue model for an emergency supply chain system under uncertainties in large-scale affected area of disasters. The proposed methodology takes into consideration that the rescue demands caused by a large-scale disaster are scattered in several locations; the servers are arranged in multiple echelons (resource depots, distribution centers, and rescue center sites) located in different places but are coordinated within one emergency supply chain system; depending on the types of rescue demands, one or more distinct servers dispatch emergency resources in different vehicle routes, and emergency rescue services queue in multiple rescue-demand locations. This emergency system is modeled as a minimal queuing response time model of location and allocation. A solution to this complex mathematical problem is developed based on genetic algorithm. Finally, a case study of an emergency supply chain system operating in Shanghai is discussed. The results demonstrate the robustness and applicability of the proposed model. PMID:24688367

Quality tracing in meat supply chains

PubMed Central

Mack, Miriam; Dittmer, Patrick; Veigt, Marius; Kus, Mehmet; Nehmiz, Ulfert; Kreyenschmidt, Judith

2014-01-01

The aim of this study was the development of a quality tracing model for vacuum-packed lamb that is applicable in different meat supply chains. Based on the development of relevant sensory parameters, the predictive model was developed by combining a linear primary model and the Arrhenius model as the secondary model. Then a process analysis was conducted to define general requirements for the implementation of the temperature-based model into a meat supply chain. The required hardware and software for continuous temperature monitoring were developed in order to use the model under practical conditions. Further on a decision support tool was elaborated in order to use the model as an effective tool in combination with the temperature monitoring equipment for the improvement of quality and storage management within the meat logistics network. Over the long term, this overall procedure will support the reduction of food waste and will improve the resources efficiency of food production. PMID:24797136

Quality tracing in meat supply chains.

PubMed

Mack, Miriam; Dittmer, Patrick; Veigt, Marius; Kus, Mehmet; Nehmiz, Ulfert; Kreyenschmidt, Judith

2014-06-13

The aim of this study was the development of a quality tracing model for vacuum-packed lamb that is applicable in different meat supply chains. Based on the development of relevant sensory parameters, the predictive model was developed by combining a linear primary model and the Arrhenius model as the secondary model. Then a process analysis was conducted to define general requirements for the implementation of the temperature-based model into a meat supply chain. The required hardware and software for continuous temperature monitoring were developed in order to use the model under practical conditions. Further on a decision support tool was elaborated in order to use the model as an effective tool in combination with the temperature monitoring equipment for the improvement of quality and storage management within the meat logistics network. Over the long term, this overall procedure will support the reduction of food waste and will improve the resources efficiency of food production.

A mixed integer linear programming model for operational planning of a biodiesel supply chain network from used cooking oil

NASA Astrophysics Data System (ADS)

Jonrinaldi, Hadiguna, Rika Ampuh; Salastino, Rades

2017-11-01

Environmental consciousness has paid many attention nowadays. It is not only about how to recycle, remanufacture or reuse used end products but it is also how to optimize the operations of the reverse system. A previous research has proposed a design of reverse supply chain of biodiesel network from used cooking oil. However, the research focused on the design of the supply chain strategy not the operations of the supply chain. It only decided how to design the structure of the supply chain in the next few years, and the process of each stage will be conducted in the supply chain system in general. The supply chain system has not considered operational policies to be conducted by the companies in the supply chain. Companies need a policy for each stage of the supply chain operations to be conducted so as to produce the optimal supply chain system, including how to use all the resources that have been designed in order to achieve the objectives of the supply chain system. Therefore, this paper proposes a model to optimize the operational planning of a biodiesel supply chain network from used cooking oil. A mixed integer linear programming is developed to model the operational planning of biodiesel supply chain in order to minimize the total operational cost of the supply chain. Based on the implementation of the model developed, the total operational cost of the biodiesel supply chain incurred by the system is less than the total operational cost of supply chain based on the previous research during seven days of operational planning about amount of 2,743,470.00 or 0.186%. Production costs contributed to 74.6 % of total operational cost and the cost of purchasing the used cooking oil contributed to 24.1 % of total operational cost. So, the system should pay more attention to these two aspects as changes in the value of these aspects will cause significant effects to the change in the total operational cost of the supply chain.

An Overview of Markov Chain Methods for the Study of Stage-Sequential Developmental Processes

ERIC Educational Resources Information Center

Kapland, David

2008-01-01

This article presents an overview of quantitative methodologies for the study of stage-sequential development based on extensions of Markov chain modeling. Four methods are presented that exemplify the flexibility of this approach: the manifest Markov model, the latent Markov model, latent transition analysis, and the mixture latent Markov model.…

Dynamic modeling and optimal joint torque coordination of advanced robotic systems

NASA Astrophysics Data System (ADS)

Kang, Hee-Jun

The development is documented of an efficient dynamic modeling algorithm and the subsequent optimal joint input load coordination of advanced robotic systems for industrial application. A closed-form dynamic modeling algorithm for the general closed-chain robotic linkage systems is presented. The algorithm is based on the transfer of system dependence from a set of open chain Lagrangian coordinates to any desired system generalized coordinate set of the closed-chain. Three different techniques for evaluation of the kinematic closed chain constraints allow the representation of the dynamic modeling parameters in terms of system generalized coordinates and have no restriction with regard to kinematic redundancy. The total computational requirement of the closed-chain system model is largely dependent on the computation required for the dynamic model of an open kinematic chain. In order to improve computational efficiency, modification of an existing open-chain KIC based dynamic formulation is made by the introduction of the generalized augmented body concept. This algorithm allows a 44 pct. computational saving over the current optimized one (O(N4), 5995 when N = 6). As means of resolving redundancies in advanced robotic systems, local joint torque optimization is applied for effectively using actuator power while avoiding joint torque limits. The stability problem in local joint torque optimization schemes is eliminated by using fictitious dissipating forces which act in the necessary null space. The performance index representing the global torque norm is shown to be satisfactory. In addition, the resulting joint motion trajectory becomes conservative, after a transient stage, for repetitive cyclic end-effector trajectories. The effectiveness of the null space damping method is shown. The modular robot, which is built of well defined structural modules from a finite-size inventory and is controlled by one general computer system, is another class of evolving, highly versatile, advanced robotic systems. Therefore, finally, a module based dynamic modeling algorithm is presented for the dynamic coordination of such reconfigurable modular robotic systems. A user interactive module based manipulator analysis program (MBMAP) has been coded in C language running on 4D/70 Silicon Graphics.

Diy Geospatial Web Service Chains: Geochaining Make it Easy

NASA Astrophysics Data System (ADS)

Wu, H.; You, L.; Gui, Z.

2011-08-01

It is a great challenge for beginners to create, deploy and utilize a Geospatial Web Service Chain (GWSC). People in Computer Science are usually not familiar with geospatial domain knowledge. Geospatial practitioners may lack the knowledge about web services and service chains. The end users may lack both. However, integrated visual editing interfaces, validation tools, and oneclick deployment wizards may help to lower the learning curve and improve modelling skills so beginners will have a better experience. GeoChaining is a GWSC modelling tool designed and developed based on these ideas. GeoChaining integrates visual editing, validation, deployment, execution etc. into a unified platform. By employing a Virtual Globe, users can intuitively visualize raw data and results produced by GeoChaining. All of these features allow users to easily start using GWSC, regardless of their professional background and computer skills. Further, GeoChaining supports GWSC model reuse, meaning that an entire GWSC model created or even a specific part can be directly reused in a new model. This greatly improves the efficiency of creating a new GWSC, and also contributes to the sharing and interoperability of GWSC.

Protein structure modeling for CASP10 by multiple layers of global optimization.

PubMed

Joo, Keehyoung; Lee, Juyong; Sim, Sangjin; Lee, Sun Young; Lee, Kiho; Heo, Seungryong; Lee, In-Ho; Lee, Sung Jong; Lee, Jooyoung

2014-02-01

In the template-based modeling (TBM) category of CASP10 experiment, we introduced a new protocol called protein modeling system (PMS) to generate accurate protein structures in terms of side-chains as well as backbone trace. In the new protocol, a global optimization algorithm, called conformational space annealing (CSA), is applied to the three layers of TBM procedure: multiple sequence-structure alignment, 3D chain building, and side-chain re-modeling. For 3D chain building, we developed a new energy function which includes new distance restraint terms of Lorentzian type (derived from multiple templates), and new energy terms that combine (physical) energy terms such as dynamic fragment assembly (DFA) energy, DFIRE statistical potential energy, hydrogen bonding term, etc. These physical energy terms are expected to guide the structure modeling especially for loop regions where no template structures are available. In addition, we developed a new quality assessment method based on random forest machine learning algorithm to screen templates, multiple alignments, and final models. For TBM targets of CASP10, we find that, due to the combination of three stages of CSA global optimizations and quality assessment, the modeling accuracy of PMS improves at each additional stage of the protocol. It is especially noteworthy that the side-chains of the final PMS models are far more accurate than the models in the intermediate steps. Copyright © 2013 Wiley Periodicals, Inc.

Future supply chains enabled by continuous processing--opportunities and challenges. May 20-21, 2014 Continuous Manufacturing Symposium.

PubMed

Srai, Jagjit Singh; Badman, Clive; Krumme, Markus; Futran, Mauricio; Johnston, Craig

2015-03-01

This paper examines the opportunities and challenges facing the pharmaceutical industry in moving to a primarily "continuous processing"-based supply chain. The current predominantly "large batch" and centralized manufacturing system designed for the "blockbuster" drug has driven a slow-paced, inventory heavy operating model that is increasingly regarded as inflexible and unsustainable. Indeed, new markets and the rapidly evolving technology landscape will drive more product variety, shorter product life-cycles, and smaller drug volumes, which will exacerbate an already unsustainable economic model. Future supply chains will be required to enhance affordability and availability for patients and healthcare providers alike despite the increased product complexity. In this more challenging supply scenario, we examine the potential for a more pull driven, near real-time demand-based supply chain, utilizing continuous processing where appropriate as a key element of a more "flow-through" operating model. In this discussion paper on future supply chain models underpinned by developments in the continuous manufacture of pharmaceuticals, we have set out; The significant opportunities to moving to a supply chain flow-through operating model, with substantial opportunities in inventory reduction, lead-time to patient, and radically different product assurance/stability regimes. Scenarios for decentralized production models producing a greater variety of products with enhanced volume flexibility. Production, supply, and value chain footprints that are radically different from today's monolithic and centralized batch manufacturing operations. Clinical trial and drug product development cost savings that support more rapid scale-up and market entry models with early involvement of SC designers within New Product Development. The major supply chain and industrial transformational challenges that need to be addressed. The paper recognizes that although current batch operational performance in pharma is far from optimal and not necessarily an appropriate end-state benchmark for batch technology, the adoption of continuous supply chain operating models underpinned by continuous production processing, as full or hybrid solutions in selected product supply chains, can support industry transformations to deliver right-first-time quality at substantially lower inventory profiles. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

An Extended Petri-Net Based Approach for Supply Chain Process Enactment in Resource-Centric Web Service Environment

NASA Astrophysics Data System (ADS)

Wang, Xiaodong; Zhang, Xiaoyu; Cai, Hongming; Xu, Boyi

Enacting a supply-chain process involves variant partners and different IT systems. REST receives increasing attention for distributed systems with loosely coupled resources. Nevertheless, resource model incompatibilities and conflicts prevent effective process modeling and deployment in resource-centric Web service environment. In this paper, a Petri-net based framework for supply-chain process integration is proposed. A resource meta-model is constructed to represent the basic information of resources. Then based on resource meta-model, XML schemas and documents are derived, which represent resources and their states in Petri-net. Thereafter, XML-net, a high level Petri-net, is employed for modeling control and data flow of process. From process model in XML-net, RESTful services and choreography descriptions are deduced. Therefore, unified resource representation and RESTful services description are proposed for cross-system integration in a more effective way. A case study is given to illustrate the approach and the desirable features of the approach are discussed.

Governance on the Drug Supply Chain via Gcoin Blockchain.

PubMed

Tseng, Jen-Hung; Liao, Yen-Chih; Chong, Bin; Liao, Shih-Wei

2018-05-23

As a trust machine, blockchain was recently introduced to the public to provide an immutable, consensus based and transparent system in the Fintech field. However, there are ongoing efforts to apply blockchain to other fields where trust and value are essential. In this paper, we suggest Gcoin blockchain as the base of the data flow of drugs to create transparent drug transaction data. Additionally, the regulation model of the drug supply chain could be altered from the inspection and examination only model to the surveillance net model, and every unit that is involved in the drug supply chain would be able to participate simultaneously to prevent counterfeit drugs and to protect public health, including patients.

Analog modeling of Worm-Like Chain molecules using macroscopic beads-on-a-string.

PubMed

Tricard, Simon; Feinstein, Efraim; Shepherd, Robert F; Reches, Meital; Snyder, Phillip W; Bandarage, Dileni C; Prentiss, Mara; Whitesides, George M

2012-07-07

This paper describes an empirical model of polymer dynamics, based on the agitation of millimeter-sized polymeric beads. Although the interactions between the particles in the macroscopic model and those between the monomers of molecular-scale polymers are fundamentally different, both systems follow the Worm-Like Chain theory.

Fuzzy Markov random fields versus chains for multispectral image segmentation.

PubMed

Salzenstein, Fabien; Collet, Christophe

2006-11-01

This paper deals with a comparison of recent statistical models based on fuzzy Markov random fields and chains for multispectral image segmentation. The fuzzy scheme takes into account discrete and continuous classes which model the imprecision of the hidden data. In this framework, we assume the dependence between bands and we express the general model for the covariance matrix. A fuzzy Markov chain model is developed in an unsupervised way. This method is compared with the fuzzy Markovian field model previously proposed by one of the authors. The segmentation task is processed with Bayesian tools, such as the well-known MPM (Mode of Posterior Marginals) criterion. Our goal is to compare the robustness and rapidity for both methods (fuzzy Markov fields versus fuzzy Markov chains). Indeed, such fuzzy-based procedures seem to be a good answer, e.g., for astronomical observations when the patterns present diffuse structures. Moreover, these approaches allow us to process missing data in one or several spectral bands which correspond to specific situations in astronomy. To validate both models, we perform and compare the segmentation on synthetic images and raw multispectral astronomical data.

Reasons for Staying: A Test of the Chain of Response Model among Community-College Students. AIR 2001 Annual Forum Paper.

ERIC Educational Resources Information Center

Salomonson, Kristen; Moss, Brian G.; Hill, H. Leon

This paper uses the Chain of Response Model (CRM) to help explain retention in the community college population. In the CRM, the student's decision to remain at an educational institution is not an isolated act, but rather the result of a complex chain of responses based on her/his cognitive evaluation of the present situation. The authors applied…

Simple model of inhibition of chain-branching combustion processes

NASA Astrophysics Data System (ADS)

Babushok, Valeri I.; Gubernov, Vladimir V.; Minaev, Sergei S.; Miroshnichenko, Taisia P.

2017-11-01

A simple kinetic model has been suggested to describe the inhibition and extinction of flame propagation in reaction systems with chain-branching reactions typical for hydrocarbon systems. The model is based on the generalised model of the combustion process with chain-branching reaction combined with the one-stage reaction describing the thermal mode of flame propagation with the addition of inhibition reaction steps. Inhibitor addition suppresses the radical overshoot in flame and leads to the change of reaction mode from the chain-branching reaction to a thermal mode of flame propagation. With the increase of inhibitor the transition of chain-branching mode of reaction to the reaction with straight-chains (non-branching chain reaction) is observed. The inhibition part of the model includes a block of three reactions to describe the influence of the inhibitor. The heat losses are incorporated into the model via Newton cooling. The flame extinction is the result of the decreased heat release of inhibited reaction processes and the suppression of radical overshoot with the further decrease of the reaction rate due to the temperature decrease and mixture dilution. A comparison of the results of modelling laminar premixed methane/air flames inhibited by potassium bicarbonate (gas phase model, detailed kinetic model) with the results obtained using the suggested simple model is presented. The calculations with the detailed kinetic model demonstrate the following modes of combustion process: (1) flame propagation with chain-branching reaction (with radical overshoot, inhibitor addition decreases the radical overshoot down to the equilibrium level); (2) saturation of chemical influence of inhibitor, and (3) transition to thermal mode of flame propagation (non-branching chain mode of reaction). The suggested simple kinetic model qualitatively reproduces the modes of flame propagation with the addition of the inhibitor observed using detailed kinetic models.

Housing Value Projection Model Related to Educational Planning: The Feasibility of a New Methodology. Final Report.

ERIC Educational Resources Information Center

Helbock, Richard W.; Marker, Gordon

This study concerns the feasibility of a Markov chain model for projecting housing values and racial mixes. Such projections could be used in planning the layout of school districts to achieve desired levels of socioeconomic heterogeneity. Based upon the concepts and assumptions underlying a Markov chain model, it is concluded that such a model is…

The Seven Challenges for Transitioning into a Bio-based Circular Economy in the Agri-food Sector.

PubMed

Borrello, Massimiliano; Lombardi, Alessia; Pascucci, Stefano; Cembalo, Luigi

2016-01-01

Closed-loop agri-food supply chains have a high potential to reduce environmental and economic costs resulting from food waste disposal. This paper illustrates an alternative to the traditional supply chain of bread based on the principles of a circular economy. Six circular interactions among seven actors (grain farmers, bread producers, retailers, compostable packaging manufacturers, insect breeders, livestock farmers, consumers) of the circular filière are created in order to achieve the goal of "zero waste". In the model, two radical technological innovations are considered: insects used as animal feed and polylactic acid compostable packaging. The main challenges for the implementation of the new supply chain are identified. Finally, some recent patents related to bread sustainable production, investigated in the current paper, are considered. Recommendations are given to academics and practitioners interested in the bio-based circular economy model approach for transforming agri-food supply chains.

Predicting the Performance of Chain Saw Machines Based on Shore Scleroscope Hardness

NASA Astrophysics Data System (ADS)

Tumac, Deniz

2014-03-01

Shore hardness has been used to estimate several physical and mechanical properties of rocks over the last few decades. However, the number of researches correlating Shore hardness with rock cutting performance is quite limited. Also, rather limited researches have been carried out on predicting the performance of chain saw machines. This study differs from the previous investigations in the way that Shore hardness values (SH1, SH2, and deformation coefficient) are used to determine the field performance of chain saw machines. The measured Shore hardness values are correlated with the physical and mechanical properties of natural stone samples, cutting parameters (normal force, cutting force, and specific energy) obtained from linear cutting tests in unrelieved cutting mode, and areal net cutting rate of chain saw machines. Two empirical models developed previously are improved for the prediction of the areal net cutting rate of chain saw machines. The first model is based on a revised chain saw penetration index, which uses SH1, machine weight, and useful arm cutting depth as predictors. The second model is based on the power consumed for only cutting the stone, arm thickness, and specific energy as a function of the deformation coefficient. While cutting force has a strong relationship with Shore hardness values, the normal force has a weak or moderate correlation. Uniaxial compressive strength, Cerchar abrasivity index, and density can also be predicted by Shore hardness values.

Performance analysis of Supply Chain Management with Supply Chain Operation reference model

NASA Astrophysics Data System (ADS)

Hasibuan, Abdurrozzaq; Arfah, Mahrani; Parinduri, Luthfi; Hernawati, Tri; Suliawati; Harahap, Bonar; Rahmah Sibuea, Siti; Krianto Sulaiman, Oris; purwadi, Adi

2018-04-01

This research was conducted at PT. Shamrock Manufacturing Corpora, the company is required to think creatively to implement competition strategy by producing goods/services that are more qualified, cheaper. Therefore, it is necessary to measure the performance of Supply Chain Management in order to improve the competitiveness. Therefore, the company is required to optimize its production output to meet the export quality standard. This research begins with the creation of initial dimensions based on Supply Chain Management process, ie Plan, Source, Make, Delivery, and Return with hierarchy based on Supply Chain Reference Operation that is Reliability, Responsiveness, Agility, Cost, and Asset. Key Performance Indicator identification becomes a benchmark in performance measurement whereas Snorm De Boer normalization serves to equalize Key Performance Indicator value. Analiytical Hierarchy Process is done to assist in determining priority criteria. Measurement of Supply Chain Management performance at PT. Shamrock Manufacturing Corpora produces SC. Responsiveness (0.649) has higher weight (priority) than other alternatives. The result of performance analysis using Supply Chain Reference Operation model of Supply Chain Management performance at PT. Shamrock Manufacturing Corpora looks good because its monitoring system between 50-100 is good.

Supply Chain Engineering and the Use of a Supporting Knowledge Management Application

NASA Astrophysics Data System (ADS)

Laakmann, Frank

The future competition in markets will happen between logistics networks and no longer between enterprises. A new approach for supporting the engineering of logistics networks is developed by this research as a part of the Collaborative Research Centre (SFB) 559: "Modeling of Large Networks in Logistics" at the University of Dortmund together with the Fraunhofer-Institute of Material Flow and Logistics founded by Deutsche Forschungsgemeinschaft (DFG). Based on a reference model for logistics processes, the process chain model, a guideline for logistics engineers is developed to manage the different types of design tasks of logistics networks. The technical background of this solution is a collaborative knowledge management application. This paper will introduce how new Internet-based technologies support supply chain design projects.

Future Supply Chains Enabled by Continuous Processing-Opportunities Challenges May 20-21 2014 Continuous Manufacturing Symposium.

PubMed

Srai, Jagjit Singh; Badman, Clive; Krumme, Markus; Futran, Mauricio; Johnston, Craig

2015-03-01

This paper examines the opportunities and challenges facing the pharmaceutical industry in moving to a primarily "continuous processing"-based supply chain. The current predominantly "large batch" and centralized manufacturing system designed for the "blockbuster" drug has driven a slow-paced, inventory heavy operating model that is increasingly regarded as inflexible and unsustainable. Indeed, new markets and the rapidly evolving technology landscape will drive more product variety, shorter product life-cycles, and smaller drug volumes, which will exacerbate an already unsustainable economic model. Future supply chains will be required to enhance affordability and availability for patients and healthcare providers alike despite the increased product complexity. In this more challenging supply scenario, we examine the potential for a more pull driven, near real-time demand-based supply chain, utilizing continuous processing where appropriate as a key element of a more "flow-through" operating model. In this discussion paper on future supply chain models underpinned by developments in the continuous manufacture of pharmaceuticals, we have set out; The paper recognizes that although current batch operational performance in pharma is far from optimal and not necessarily an appropriate end-state benchmark for batch technology, the adoption of continuous supply chain operating models underpinned by continuous production processing, as full or hybrid solutions in selected product supply chains, can support industry transformations to deliver right-first-time quality at substantially lower inventory profiles. © 2015 The Authors. Journal of Pharmaceutical Sciences published by Wiley Periodicals, Inc. and the American Pharmacists Association. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

A Looping-Based Model for Quenching Repression

PubMed Central

Pollak, Yaroslav; Goldberg, Sarah; Amit, Roee

2017-01-01

We model the regulatory role of proteins bound to looped DNA using a simulation in which dsDNA is represented as a self-avoiding chain, and proteins as spherical protrusions. We simulate long self-avoiding chains using a sequential importance sampling Monte-Carlo algorithm, and compute the probabilities for chain looping with and without a protrusion. We find that a protrusion near one of the chain’s termini reduces the probability of looping, even for chains much longer than the protrusion–chain-terminus distance. This effect increases with protrusion size, and decreases with protrusion-terminus distance. The reduced probability of looping can be explained via an eclipse-like model, which provides a novel inhibitory mechanism. We test the eclipse model on two possible transcription-factor occupancy states of the D. melanogaster eve 3/7 enhancer, and show that it provides a possible explanation for the experimentally-observed eve stripe 3 and 7 expression patterns. PMID:28085884

A New Activity-Based Financial Cost Management Method

NASA Astrophysics Data System (ADS)

Qingge, Zhang

The standard activity-based financial cost management model is a new model of financial cost management, which is on the basis of the standard cost system and the activity-based cost and integrates the advantages of the two. It is a new model of financial cost management with more accurate and more adequate cost information by taking the R&D expenses as the accounting starting point and after-sale service expenses as the terminal point and covering the whole producing and operating process and the whole activities chain and value chain aiming at serving the internal management and decision.

A Case Study Using Modeling and Simulation to Predict Logistics Supply Chain Issues

NASA Technical Reports Server (NTRS)

Tucker, David A.

2007-01-01

Optimization of critical supply chains to deliver thousands of parts, materials, sub-assemblies, and vehicle structures as needed is vital to the success of the Constellation Program. Thorough analysis needs to be performed on the integrated supply chain processes to plan, source, make, deliver, and return critical items efficiently. Process modeling provides simulation technology-based, predictive solutions for supply chain problems which enable decision makers to reduce costs, accelerate cycle time and improve business performance. For example, United Space Alliance, LLC utilized this approach in late 2006 to build simulation models that recreated shuttle orbiter thruster failures and predicted the potential impact of thruster removals on logistics spare assets. The main objective was the early identification of possible problems in providing thruster spares for the remainder of the Shuttle Flight Manifest. After extensive analysis the model results were used to quantify potential problems and led to improvement actions in the supply chain. Similarly the proper modeling and analysis of Constellation parts, materials, operations, and information flows will help ensure the efficiency of the critical logistics supply chains and the overall success of the program.

A new paradigm for the molecular basis of rubber elasticity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hanson, David E.; Barber, John L.

The molecular basis for rubber elasticity is arguably the oldest and one of the most important questions in the field of polymer physics. The theoretical investigation of rubber elasticity began in earnest almost a century ago with the development of analytic thermodynamic models, based on simple, highly-symmetric configurations of so-called Gaussian chains, i.e. polymer chains that obey Markov statistics. Numerous theories have been proposed over the past 90 years based on the ansatz that the elastic force for individual network chains arises from the entropy change associated with the distribution of end-to-end distances of a free polymer chain. There aremore » serious philosophical objections to this assumption and others, such as the assumption that all network nodes undergo affine motion and that all of the network chains have the same length. Recently, a new paradigm for elasticity in rubber networks has been proposed that is based on mechanisms that originate at the molecular level. Using conventional statistical mechanics analyses, quantum chemistry, and molecular dynamics simulations, the fundamental entropic and enthalpic chain extension forces for polyisoprene (natural rubber) have been determined, along with estimates for the basic force constants. Concurrently, the complex morphology of natural rubber networks (the joint probability density distributions that relate the chain end-to-end distance to its contour length) has also been captured in a numerical model. When molecular chain forces are merged with the network structure in this model, it is possible to study the mechanical response to tensile and compressive strains of a representative volume element of a polymer network. As strain is imposed on a network, pathways of connected taut chains, that completely span the network along strain axis, emerge. Although these chains represent only a few percent of the total, they account for nearly all of the elastic stress at high strain. Here we provide a brief review of previous elasticity theories and their deficiencies, and present a new paradigm with an emphasis on experimental comparisons.« less

A new paradigm for the molecular basis of rubber elasticity

DOE PAGES

Hanson, David E.; Barber, John L.

2015-02-19

The molecular basis for rubber elasticity is arguably the oldest and one of the most important questions in the field of polymer physics. The theoretical investigation of rubber elasticity began in earnest almost a century ago with the development of analytic thermodynamic models, based on simple, highly-symmetric configurations of so-called Gaussian chains, i.e. polymer chains that obey Markov statistics. Numerous theories have been proposed over the past 90 years based on the ansatz that the elastic force for individual network chains arises from the entropy change associated with the distribution of end-to-end distances of a free polymer chain. There aremore » serious philosophical objections to this assumption and others, such as the assumption that all network nodes undergo affine motion and that all of the network chains have the same length. Recently, a new paradigm for elasticity in rubber networks has been proposed that is based on mechanisms that originate at the molecular level. Using conventional statistical mechanics analyses, quantum chemistry, and molecular dynamics simulations, the fundamental entropic and enthalpic chain extension forces for polyisoprene (natural rubber) have been determined, along with estimates for the basic force constants. Concurrently, the complex morphology of natural rubber networks (the joint probability density distributions that relate the chain end-to-end distance to its contour length) has also been captured in a numerical model. When molecular chain forces are merged with the network structure in this model, it is possible to study the mechanical response to tensile and compressive strains of a representative volume element of a polymer network. As strain is imposed on a network, pathways of connected taut chains, that completely span the network along strain axis, emerge. Although these chains represent only a few percent of the total, they account for nearly all of the elastic stress at high strain. Here we provide a brief review of previous elasticity theories and their deficiencies, and present a new paradigm with an emphasis on experimental comparisons.« less

A Framework of Multi Objectives Negotiation for Dynamic Supply Chain Model

NASA Astrophysics Data System (ADS)

Chai, Jia Yee; Sakaguchi, Tatsuhiko; Shirase, Keiichi

Trends of globalization and advances in Information Technology (IT) have created opportunity in collaborative manufacturing across national borders. A dynamic supply chain utilizes these advances to enable more flexibility in business cooperation. This research proposes a concurrent decision making framework for a three echelons dynamic supply chain model. The dynamic supply chain is formed by autonomous negotiation among agents based on multi agents approach. Instead of generating negotiation aspects (such as amount, price and due date) arbitrary, this framework proposes to utilize the information available at operational level of an organization in order to generate realistic negotiation aspect. The effectiveness of the proposed model is demonstrated by various case studies.

Stochastic entangled chain dynamics of dense polymer solutions.

PubMed

Kivotides, Demosthenes; Wilkin, S Louise; Theofanous, Theo G

2010-10-14

We propose an adjustable-parameter-free, entangled chain dynamics model of dense polymer solutions. The model includes the self-consistent dynamics of molecular chains and solvent by describing the former via coarse-grained polymer dynamics that incorporate hydrodynamic interaction effects, and the latter via the forced Stokes equation. Real chain elasticity is modeled via the inclusion of a Pincus regime in the polymer's force-extension curve. Excluded volume effects are taken into account via the combined action of coarse-grained intermolecular potentials and explicit geometric tracking of chain entanglements. We demonstrate that entanglements are responsible for a new (compared to phantom chain dynamics), slow relaxation mode whose characteristic time scale agrees very well with experiment. Similarly good agreement between theory and experiment is also obtained for the equilibrium chain size. We develop methods for the solution of the model in periodic flow domains and apply them to the computation of entangled polymer solutions in equilibrium. We show that the number of entanglements Π agrees well with the number of entanglements expected on the basis of tube theory, satisfactorily reproducing the latter's scaling of Π with the polymer volume fraction φ. Our model predicts diminishing chain size with concentration, thus vindicating Flory's suggestion of excluded volume effects screening in dense solutions. The predicted scaling of chain size with φ is consistent with the heuristic, Flory theory based value.

Future Supply Chains Enabled by Continuous Processing—Opportunities and Challenges. May 20–21, 2014 Continuous Manufacturing Symposium

PubMed Central

Srai, Jagjit Singh; Badman, Clive; Krumme, Markus; Futran, Mauricio; Johnston, Craig

2015-01-01

This paper examines the opportunities and challenges facing the pharmaceutical industry in moving to a primarily “continuous processing”-based supply chain. The current predominantly “large batch” and centralized manufacturing system designed for the “blockbuster” drug has driven a slow-paced, inventory heavy operating model that is increasingly regarded as inflexible and unsustainable. Indeed, new markets and the rapidly evolving technology landscape will drive more product variety, shorter product life-cycles, and smaller drug volumes, which will exacerbate an already unsustainable economic model. Future supply chains will be required to enhance affordability and availability for patients and healthcare providers alike despite the increased product complexity. In this more challenging supply scenario, we examine the potential for a more pull driven, near real-time demand-based supply chain, utilizing continuous processing where appropriate as a key element of a more “flow-through” operating model. In this discussion paper on future supply chain models underpinned by developments in the continuous manufacture of pharmaceuticals, we have set out; The significant opportunities to moving to a supply chain flow-through operating model, with substantial opportunities in inventory reduction, lead-time to patient, and radically different product assurance/stability regimes. Scenarios for decentralized production models producing a greater variety of products with enhanced volume flexibility. Production, supply, and value chain footprints that are radically different from today's monolithic and centralized batch manufacturing operations. Clinical trial and drug product development cost savings that support more rapid scale-up and market entry models with early involvement of SC designers within New Product Development. The major supply chain and industrial transformational challenges that need to be addressed. The paper recognizes that although current batch operational performance in pharma is far from optimal and not necessarily an appropriate end-state benchmark for batch technology, the adoption of continuous supply chain operating models underpinned by continuous production processing, as full or hybrid solutions in selected product supply chains, can support industry transformations to deliver right-first-time quality at substantially lower inventory profiles. © 2015 The Authors. Journal of Pharmaceutical Sciences published by Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 104:840–849, 2015 PMID:25631279

Model Development of Cold Chains for Fresh Fruits and Vegetables Distribution: A Case Study in Bali Province

NASA Astrophysics Data System (ADS)

Waisnawa, I. N. G. S.; Santosa, I. D. M. C.; Sunu, I. P. W.; Wirajati, IGAB

2018-01-01

In developing countries such as Indonesia, as much as 40% of total vegetables and fruits production becomes waste because of lack refrigeration. This condition also contributes a food crisis problem besides other factor such as, climate change and number of population. Cold chain system that will be modelled in this study is for vegetables and fruits and refrigeration system as the main devices. In future, this system will play an important role for the food crisis solution where fresh food can be distributed very well with significant low waste. The fresh food also can be kept with good quality and hygienist (bacteria contaminated). Cold Chain model will be designed using refrigeration components including, pre cooling chiller, cold room, and truck refrigeration. This study will be conducted by survey and observation di around Bali Province focus on vegetables and fruits production center. Interviews and questionnaire will be also done to get some information about the conventional distribution obstacles and problem. Distribution mapping will be developed and created. The data base of the storage characteristic of the fruits and vegetable also collected through experiment and secondary data. Depend on the mapping and data base can be developed a cold chain model that has the best performance application. The model will be can directly apply in Bali to get eligible cold chain in Bali. The cold chain model will be compared with the conventional distribution system using ALCC/LCC method and also others factor and will be weighted to get better results.

Negotiation-based Order Lot-Sizing Approach for Two-tier Supply Chain

NASA Astrophysics Data System (ADS)

Chao, Yuan; Lin, Hao Wen; Chen, Xili; Murata, Tomohiro

This paper focuses on a negotiation based collaborative planning process for the determination of order lot-size over multi-period planning, and confined to a two-tier supply chain scenario. The aim is to study how negotiation based planning processes would be used to refine locally preferred ordering patterns, which would consequently affect the overall performance of the supply chain in terms of costs and service level. Minimal information exchanges in the form of mathematical models are suggested to represent the local preferences and used to support the negotiation processes.

Dependence of Ion Dynamics on the Polymer Chain Length in Poly(ethylene oxide)-Based Polymer Electrolytes.

PubMed

Chattoraj, Joyjit; Knappe, Marisa; Heuer, Andreas

2015-06-04

It is known from experiments that in the polymer electrolyte system, which contains poly(ethylene oxide) chains (PEO), lithium-cations (Li(+)), and bis(trifluoromethanesulfonyl)imide-anions (TFSI(-)), the cation and the anion diffusion and the ionic conductivity exhibit a similar chain-length dependence: with increasing chain length, they start dropping steadily, and later, they saturate to constant values. These results are surprising because Li-cations are strongly correlated with the polymer chains, whereas TFSI-anions do not have such bonding. To understand this phenomenon, we perform molecular dynamics simulations of this system for four different polymer chain lengths. The diffusion results obtained from our simulations display excellent agreement with the experimental data. The cation transport model based on the Rouse dynamics can successfully quantify the Li-diffusion results, which correlates Li diffusion with the polymer center-of-mass motion and the polymer segmental motion. The ionic conductivity as a function of the chain length is then estimated based on the chain-length-dependent ion diffusion, which shows a temperature-dependent deviation for short chain lengths. We argue that in the first regime, counterion correlations modify the conductivity, whereas for the long chains, the system behaves as a strong electrolyte.

Stability of ecological industry chain: an entropy model approach.

PubMed

Wang, Qingsong; Qiu, Shishou; Yuan, Xueliang; Zuo, Jian; Cao, Dayong; Hong, Jinglan; Zhang, Jian; Dong, Yong; Zheng, Ying

2016-07-01

A novel methodology is proposed in this study to examine the stability of ecological industry chain network based on entropy theory. This methodology is developed according to the associated dissipative structure characteristics, i.e., complexity, openness, and nonlinear. As defined in the methodology, network organization is the object while the main focus is the identification of core enterprises and core industry chains. It is proposed that the chain network should be established around the core enterprise while supplementation to the core industry chain helps to improve system stability, which is verified quantitatively. Relational entropy model can be used to identify core enterprise and core eco-industry chain. It could determine the core of the network organization and core eco-industry chain through the link form and direction of node enterprises. Similarly, the conductive mechanism of different node enterprises can be examined quantitatively despite the absence of key data. Structural entropy model can be employed to solve the problem of order degree for network organization. Results showed that the stability of the entire system could be enhanced by the supplemented chain around the core enterprise in eco-industry chain network organization. As a result, the sustainability of the entire system could be further improved.

SCOR based key success factors in cooking oil supply chain buyers perspective in Padang City

NASA Astrophysics Data System (ADS)

Zahara, Fatimah; Hadiguna, Rika Ampuh

2017-11-01

Supply chain of cooking oil is a network of companies from palm oil as raw material to retailers which work to create the value and deliver products into the end consumers. This paper is aimed to study key success factors based on consumer's perspective as the last stage in the supply chain. Consumers who are examined in this study are restaurants management or owners. Restaurant is the biggest consumption of cooking oil. The factors is studied based on Supply Chain Operation Reference (SCOR) version 10.0. Factors used are formulated based on the third-level metrics of SCOR Model. Factors are analyzed using factors analysis. This study found factors which become key success factors in managing supply chain of cooking oil encompass reliability, responsiveness and agility. Key success factors can be applied by governments as policy making and cooking oil companies as formulation of the distribution strategies.

A framework for the computer-aided planning and optimisation of manufacturing processes for components with functional graded properties

NASA Astrophysics Data System (ADS)

Biermann, D.; Gausemeier, J.; Heim, H.-P.; Hess, S.; Petersen, M.; Ries, A.; Wagner, T.

2014-05-01

In this contribution a framework for the computer-aided planning and optimisation of functional graded components is presented. The framework is divided into three modules - the "Component Description", the "Expert System" for the synthetisation of several process chains and the "Modelling and Process Chain Optimisation". The Component Description module enhances a standard computer-aided design (CAD) model by a voxel-based representation of the graded properties. The Expert System synthesises process steps stored in the knowledge base to generate several alternative process chains. Each process chain is capable of producing components according to the enhanced CAD model and usually consists of a sequence of heating-, cooling-, and forming processes. The dependencies between the component and the applied manufacturing processes as well as between the processes themselves need to be considered. The Expert System utilises an ontology for that purpose. The ontology represents all dependencies in a structured way and connects the information of the knowledge base via relations. The third module performs the evaluation of the generated process chains. To accomplish this, the parameters of each process are optimised with respect to the component specification, whereby the result of the best parameterisation is used as representative value. Finally, the process chain which is capable of manufacturing a functionally graded component in an optimal way regarding to the property distributions of the component description is presented by means of a dedicated specification technique.

Interplanetary Supply Chain Risk Management

NASA Technical Reports Server (NTRS)

Galluzzi, Michael C.

2018-01-01

Emphasis on KSC ground processing operations, reduced spares up-mass lift requirements and campaign-level flexible path perspective for space systems support as Regolith-based ISM is achieved by; Network modeling for sequencing space logistics and in-space logistics nodal positioning to include feedstock. Economic modeling to assess ISM 3D printing adaption and supply chain risk.

Population pharmacokinetics of recombinant coagulation factor VIII-SingleChain in patients with severe hemophilia A.

PubMed

Zhang, Y; Roberts, J; Tortorici, M; Veldman, A; St Ledger, K; Feussner, A; Sidhu, J

2017-06-01

Essentials rVIII-SingleChain is a unique recombinant factor VIII (FVIII) molecule. A population pharmacokinetic model was based on FVIII activity of severe hemophilia A patients. The model was used to simulate factor VIII activity-time profiles for various dosing scenarios. The model supports prolonged dosing of rVIII-SingleChain with intervals of up to twice per week. Background Single-chain recombinant coagulation factor VIII (rVIII-SingleChain) is a unique recombinant coagulation factor VIII molecule. Objectives To: (i) characterize the population pharmacokinetics (PK) of rVIII-SingleChain in patients with severe hemophilia A; (ii) identify correlates of variability in rVIII-SingleChain PK; and (iii) simulate various dosing scenarios of rVIII-SingleChain. Patients/Methods A population PK model was developed, based on FVIII activity levels of 130 patients with severe hemophilia A (n = 91 for ≥ 12-65 years; n = 39 for < 12 years) who had participated in a single-dose PK investigation with rVIII-SingleChain 50 IU kg -1 . PK sampling was performed for up to 96 h. Results A two-compartment population PK model with first-order elimination adequately described FVIII activity. Body weight and predose level of von Willebrand factor were significant covariates on clearance, and body weight was a significant covariate on the central distribution volume. Simulations using the model with various dosing scenarios estimated that > 85% and > 93% of patients were predicted to maintain FVIII activity level above 1 IU dL -1 , at all times with three-times-weekly dosing (given on days 0, 2, and 4.5) at the lowest (20 IU kg -1 ) and highest (50 IU kg -1 ) doses, respectively. For twice weekly dosing (days 0 and 3.5) of 50 IU kg -1 rVIII-SingleChain, 62-80% of patients across all ages were predicted to maintain a FVIII activity level above 1 IU dL -1 at day 7. Conclusions The population PK model adequately characterized rVIII-SingleChain PK, and the model can be utilized to simulate FVIII activity-time profiles for various dosing scenarios. © 2017 The Authors. Journal of Thrombosis and Haemostasis published by Wiley Periodicals, Inc. on behalf of International Society on Thrombosis and Haemostasis.

Robust optimization on sustainable biodiesel supply chain produced from waste cooking oil under price uncertainty.

PubMed

Zhang, Yong; Jiang, Yunjian

2017-02-01

Waste cooking oil (WCO)-for-biodiesel conversion is regarded as the "waste-to-wealthy" industry. This paper addresses the design of a WCO-for-biodiesel supply chain at both strategic and tactical levels. The supply chain of this problem is studied, which is based on a typical mode of the waste collection (from restaurants' kitchen) and conversion in the cities. The supply chain comprises three stakeholders: WCO supplier, integrated bio-refinery and demand zone. Three key problems should be addressed for the optimal design of the supply chain: (1) the number, sizes and locations of bio-refinery; (2) the sites and amount of WCO collected; (3) the transportation plans of WCO and biodiesel. A robust mixed integer linear model with muti-objective (economic, environmental and social objectives) is proposed for these problems. Finally, a large-scale practical case study is adopted based on Suzhou, a city in the east of China, to verify the proposed models. Copyright © 2016 Elsevier Ltd. All rights reserved.

Large scale shell model study of the evolution of mixed-symmetry states in chains of nuclei around 132Sn

NASA Astrophysics Data System (ADS)

Lo Iudice, N.; Bianco, D.; Andreozzi, F.; Porrino, A.; Knapp, F.

2012-10-01

Large scale shell model calculations based on a new diagonalization algorithm are performed in order to investigate the mixed symmetry states in chains of nuclei in the proximity of N=82. The resulting spectra and transitions are in agreement with the experiments and consistent with the scheme provided by the interacting boson model.

Model-based Clustering of Categorical Time Series with Multinomial Logit Classification

NASA Astrophysics Data System (ADS)

Frühwirth-Schnatter, Sylvia; Pamminger, Christoph; Winter-Ebmer, Rudolf; Weber, Andrea

2010-09-01

A common problem in many areas of applied statistics is to identify groups of similar time series in a panel of time series. However, distance-based clustering methods cannot easily be extended to time series data, where an appropriate distance-measure is rather difficult to define, particularly for discrete-valued time series. Markov chain clustering, proposed by Pamminger and Frühwirth-Schnatter [6], is an approach for clustering discrete-valued time series obtained by observing a categorical variable with several states. This model-based clustering method is based on finite mixtures of first-order time-homogeneous Markov chain models. In order to further explain group membership we present an extension to the approach of Pamminger and Frühwirth-Schnatter [6] by formulating a probabilistic model for the latent group indicators within the Bayesian classification rule by using a multinomial logit model. The parameters are estimated for a fixed number of clusters within a Bayesian framework using an Markov chain Monte Carlo (MCMC) sampling scheme representing a (full) Gibbs-type sampler which involves only draws from standard distributions. Finally, an application to a panel of Austrian wage mobility data is presented which leads to an interesting segmentation of the Austrian labour market.

Simple Physics-Based Analytical Formulas for the Potentials of Mean Force of the Interaction of Amino Acid Side Chains in Water. VII. Charged-Hydrophobic/Polar and Polar-Hydrophobic/Polar Side Chains.

PubMed

Makowski, Mariusz; Liwo, Adam; Scheraga, Harold A

2017-01-19

The physics-based potentials of side-chain-side-chain interactions corresponding to pairs composed of charged and polar, polar and polar, charged and hydrophobic, and hydrophobic and hydrophobic side chains have been determined. A total of 144 four-dimensional potentials of mean force (PMFs) of all possible pairs of molecules modeling these pairs were determined by umbrella-sampling molecular dynamics simulations in explicit water as functions of distance and orientation, and the analytical expressions were then fitted to the PMFs. Depending on the type of interacting sites, the analytical approximation to the PMF is a sum of terms corresponding to van der Waals interactions and cavity-creation involving the nonpolar sections of the side chains and van der Waals, cavity-creation, and electrostatic (charge-dipole or dipole-dipole) interaction energies and polarization energies involving the charged or polar sections of the side chains. The model used in this work reproduces all features of the interacting pairs. The UNited RESidue force field with the new side-chain-side-chain interaction potentials was preliminarily tested with the N-terminal part of the B-domain of staphylococcal protein A (PDBL 1BDD ; a three-α-helix bundle) and UPF0291 protein YnzC from Bacillus subtilis (PDB: 2HEP ; an α-helical hairpin).

A coupled two-dimensional main chain torsional potential for protein dynamics: generation and implementation.

PubMed

Li, Yongxiu; Gao, Ya; Zhang, Xuqiang; Wang, Xingyu; Mou, Lirong; Duan, Lili; He, Xiao; Mei, Ye; Zhang, John Z H

2013-09-01

Main chain torsions of alanine dipeptide are parameterized into coupled 2-dimensional Fourier expansions based on quantum mechanical (QM) calculations at M06 2X/aug-cc-pvtz//HF/6-31G** level. Solvation effect is considered by employing polarizable continuum model. Utilization of the M06 2X functional leads to precise potential energy surface that is comparable to or even better than MP2 level, but with much less computational demand. Parameterization of the 2D expansions is against the full main chain torsion space instead of just a few low energy conformations. This procedure is similar to that for the development of AMBER03 force field, except unique weighting factor was assigned to all the grid points. To avoid inconsistency between quantum mechanical calculations and molecular modeling, the model peptide is further optimized at molecular mechanics level with main chain dihedral angles fixed before the calculation of the conformational energy on molecular mechanical level at each grid point, during which generalized Born model is employed. Difference in solvation models at quantum mechanics and molecular mechanics levels makes this parameterization procedure less straightforward. All force field parameters other than main chain torsions are taken from existing AMBER force field. With this new main chain torsion terms, we have studied the main chain dihedral distributions of ALA dipeptide and pentapeptide in aqueous solution. The results demonstrate that 2D main chain torsion is effective in delineating the energy variation associated with rotations along main chain dihedrals. This work is an implication for the necessity of more accurate description of main chain torsions in the future development of ab initio force field and it also raises a challenge to the development of quantum mechanical methods, especially the quantum mechanical solvation models.

A multistage stochastic programming model for a multi-period strategic expansion of biofuel supply chain under evolving uncertainties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xie, Fei; Huang, Yongxi

Here, we develop a multistage, stochastic mixed-integer model to support biofuel supply chain expansion under evolving uncertainties. By utilizing the block-separable recourse property, we reformulate the multistage program in an equivalent two-stage program and solve it using an enhanced nested decomposition method with maximal non-dominated cuts. We conduct extensive numerical experiments and demonstrate the application of the model and algorithm in a case study based on the South Carolina settings. The value of multistage stochastic programming method is also explored by comparing the model solution with the counterparts of an expected value based deterministic model and a two-stage stochastic model.

A multistage stochastic programming model for a multi-period strategic expansion of biofuel supply chain under evolving uncertainties

DOE PAGES

Xie, Fei; Huang, Yongxi

2018-02-04

Here, we develop a multistage, stochastic mixed-integer model to support biofuel supply chain expansion under evolving uncertainties. By utilizing the block-separable recourse property, we reformulate the multistage program in an equivalent two-stage program and solve it using an enhanced nested decomposition method with maximal non-dominated cuts. We conduct extensive numerical experiments and demonstrate the application of the model and algorithm in a case study based on the South Carolina settings. The value of multistage stochastic programming method is also explored by comparing the model solution with the counterparts of an expected value based deterministic model and a two-stage stochastic model.

Developing a model for agile supply: an empirical study from Iranian pharmaceutical supply chain.

PubMed

Rajabzadeh Ghatari, Ali; Mehralian, Gholamhossein; Zarenezhad, Forouzandeh; Rasekh, Hamid Reza

2013-01-01

Agility is the fundamental characteristic of a supply chain needed for survival in turbulent markets, where environmental forces create additional uncertainty resulting in higher risk in the supply chain management. In addition, agility helps providing the right product, at the right time to the consumer. The main goal of this research is therefore to promote supplier selection in pharmaceutical industry according to the formative basic factors. Moreover, this paper can configure its supply network to achieve the agile supply chain. The present article analyzes the supply part of supply chain based on SCOR model, used to assess agile supply chains by highlighting their specific characteristics and applicability in providing the active pharmaceutical ingredient (API). This methodology provides an analytical modeling; the model enables potential suppliers to be assessed against the multiple criteria using both quantitative and qualitative measures. In addition, for making priority of critical factors, TOPSIS algorithm has been used as a common technique of MADM model. Finally, several factors such as delivery speed, planning and reorder segmentation, trust development and material quantity adjustment are identified and prioritized as critical factors for being agile in supply of API.

Developing a Model for Agile Supply: an Empirical Study from Iranian Pharmaceutical Supply Chain

PubMed Central

Rajabzadeh Ghatari, Ali; Mehralian, Gholamhossein; Zarenezhad, Forouzandeh; Rasekh, Hamid Reza

2013-01-01

Agility is the fundamental characteristic of a supply chain needed for survival in turbulent markets, where environmental forces create additional uncertainty resulting in higher risk in the supply chain management. In addition, agility helps providing the right product, at the right time to the consumer. The main goal of this research is therefore to promote supplier selection in pharmaceutical industry according to the formative basic factors. Moreover, this paper can configure its supply network to achieve the agile supply chain. The present article analyzes the supply part of supply chain based on SCOR model, used to assess agile supply chains by highlighting their specific characteristics and applicability in providing the active pharmaceutical ingredient (API). This methodology provides an analytical modeling; the model enables potential suppliers to be assessed against the multiple criteria using both quantitative and qualitative measures. In addition, for making priority of critical factors, TOPSIS algorithm has been used as a common technique of MADM model. Finally, several factors such as delivery speed, planning and reorder segmentation, trust development and material quantity adjustment are identified and prioritized as critical factors for being agile in supply of API. PMID:24250689

A conceptual mitigation model for asymmetric information of supply chain in seaweed cultivation

NASA Astrophysics Data System (ADS)

Teniwut, Wellem A.; Betaubun, Kamilius D.; Marimin; Djatna, Taufik

2017-10-01

Seaweed cultivation has a better advantage over other fisheries activity in terms of easiness on conducting the production and multiplier effect on coastal community welfare. The effect of seaweed farming on the prosperity of coastal community in Southeast Maluku started to take place in 2008, although in 2012 either number of production and workforce is declining rapidly. By solving this problem, this article also provided with identifying and analyzing the supply chain of seaweed cultivation in Southeast Maluku. Based on this analysis we have found that one of the main reasons of declining seaweed production and the number seaweed farmers was asymmetric information that occurred on seaweed supply chain in Southeast Maluku. The component of asymmetric risk was the quality of the seeds, price, information and technology and the knowledge of actual market of seaweed, especially by seaweed farmers. Therefore, it is essential to make a conceptual model on mitigation of asymmetric information on the supply chain of seaweed production. We proposed a conceptual model based on four perspectives, first was goal, criteria and sub-criteria, actor and the solution to mitigate asymmetric information supply chain on seaweed cultivation.

Template based protein structure modeling by global optimization in CASP11.

PubMed

Joo, Keehyoung; Joung, InSuk; Lee, Sun Young; Kim, Jong Yun; Cheng, Qianyi; Manavalan, Balachandran; Joung, Jong Young; Heo, Seungryong; Lee, Juyong; Nam, Mikyung; Lee, In-Ho; Lee, Sung Jong; Lee, Jooyoung

2016-09-01

For the template-based modeling (TBM) of CASP11 targets, we have developed three new protein modeling protocols (nns for server prediction and LEE and LEER for human prediction) by improving upon our previous CASP protocols (CASP7 through CASP10). We applied the powerful global optimization method of conformational space annealing to three stages of optimization, including multiple sequence-structure alignment, three-dimensional (3D) chain building, and side-chain remodeling. For more successful fold recognition, a new alignment method called CRFalign was developed. It can incorporate sensitive positional and environmental dependence in alignment scores as well as strong nonlinear correlations among various features. Modifications and adjustments were made to the form of the energy function and weight parameters pertaining to the chain building procedure. For the side-chain remodeling step, residue-type dependence was introduced to the cutoff value that determines the entry of a rotamer to the side-chain modeling library. The improved performance of the nns server method is attributed to successful fold recognition achieved by combining several methods including CRFalign and to the current modeling formulation that can incorporate native-like structural aspects present in multiple templates. The LEE protocol is identical to the nns one except that CASP11-released server models are used as templates. The success of LEE in utilizing CASP11 server models indicates that proper template screening and template clustering assisted by appropriate cluster ranking promises a new direction to enhance protein 3D modeling. Proteins 2016; 84(Suppl 1):221-232. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Relating MBSE to Spacecraft Development: A NASA Pathfinder

NASA Technical Reports Server (NTRS)

Othon, Bill

2016-01-01

The NASA Engineering and Safety Center (NESC) has sponsored a Pathfinder Study to investigate how Model Based Systems Engineering (MBSE) and Model Based Engineering (MBE) techniques can be applied by NASA spacecraft development projects. The objectives of this Pathfinder Study included analyzing both the products of the modeling activity, as well as the process and tool chain through which the spacecraft design activities are executed. Several aspects of MBSE methodology and process were explored. Adoption and consistent use of the MBSE methodology within an existing development environment can be difficult. The Pathfinder Team evaluated the possibility that an "MBSE Template" could be developed as both a teaching tool as well as a baseline from which future NASA projects could leverage. Elements of this template include spacecraft system component libraries, data dictionaries and ontology specifications, as well as software services that do work on the models themselves. The Pathfinder Study also evaluated the tool chain aspects of development. Two chains were considered: 1. The Development tool chain, through which SysML model development was performed and controlled, and 2. The Analysis tool chain, through which both static and dynamic system analysis is performed. Of particular interest was the ability to exchange data between SysML and other engineering tools such as CAD and Dynamic Simulation tools. For this study, the team selected a Mars Lander vehicle as the element to be designed. The paper will discuss what system models were developed, how data was captured and exchanged, and what analyses were conducted.

Residue-Specific Side-Chain Polymorphisms via Particle Belief Propagation.

PubMed

Ghoraie, Laleh Soltan; Burkowski, Forbes; Li, Shuai Cheng; Zhu, Mu

2014-01-01

Protein side chains populate diverse conformational ensembles in crystals. Despite much evidence that there is widespread conformational polymorphism in protein side chains, most of the X-ray crystallography data are modeled by single conformations in the Protein Data Bank. The ability to extract or to predict these conformational polymorphisms is of crucial importance, as it facilitates deeper understanding of protein dynamics and functionality. In this paper, we describe a computational strategy capable of predicting side-chain polymorphisms. Our approach extends a particular class of algorithms for side-chain prediction by modeling the side-chain dihedral angles more appropriately as continuous rather than discrete variables. Employing a new inferential technique known as particle belief propagation, we predict residue-specific distributions that encode information about side-chain polymorphisms. Our predicted polymorphisms are in relatively close agreement with results from a state-of-the-art approach based on X-ray crystallography data, which characterizes the conformational polymorphisms of side chains using electron density information, and has successfully discovered previously unmodeled conformations.

Side-chain mobility in the folded state of Myoglobin

NASA Astrophysics Data System (ADS)

Lammert, Heiko; Onuchic, Jose

We study the accessibility of alternative side-chain rotamer configurations in the native state of Myoglobin, using an all-atom structure-based model. From long, unbiased simulation trajectories we determine occupancies of rotameric states and also estimate configurational and vibrational entropies. Direct sampling of the full native-state dynamics, enabled by the simple model, reveals facilitation of side-chain motions by backbone dynamics. Correlations between different dihedral angles are quantified and prove to be weak. We confirm global trends in the mobilities of side-chains, following burial and also the chemical character of residues. Surface residues loose little configurational entropy upon folding; side-chains contribute significantly to the entropy of the folded state. Mobilities of buried side-chains vary strongly with temperature. At ambient temperature, individual side-chains in the core of the protein gain substantial access to alternative rotamers, with occupancies that are likely observable experimentally. Finally, the dynamics of buried side-chains may be linked to the internal pockets, available to ligand gas molecules in Myoglobin.

Evaluation of Supply Chain Efficiency Based on a Novel Network of Data Envelopment Analysis Model

NASA Astrophysics Data System (ADS)

Fu, Li Fang; Meng, Jun; Liu, Ying

2015-12-01

Performance evaluation of supply chain (SC) is a vital topic in SC management and inherently complex problems with multilayered internal linkages and activities of multiple entities. Recently, various Network Data Envelopment Analysis (NDEA) models, which opened the “black box” of conventional DEA, were developed and applied to evaluate the complex SC with a multilayer network structure. However, most of them are input or output oriented models which cannot take into consideration the nonproportional changes of inputs and outputs simultaneously. This paper extends the Slack-based measure (SBM) model to a nonradial, nonoriented network model named as U-NSBM with the presence of undesirable outputs in the SC. A numerical example is presented to demonstrate the applicability of the model in quantifying the efficiency and ranking the supply chain performance. By comparing with the CCR and U-SBM models, it is shown that the proposed model has higher distinguishing ability and gives feasible solution in the presence of undesirable outputs. Meanwhile, it provides more insights for decision makers about the source of inefficiency as well as the guidance to improve the SC performance.

Modified allocation capacitated planning model in blood supply chain management

NASA Astrophysics Data System (ADS)

Mansur, A.; Vanany, I.; Arvitrida, N. I.

2018-04-01

Blood supply chain management (BSCM) is a complex process management that involves many cooperating stakeholders. BSCM involves four echelon processes, which are blood collection or procurement, production, inventory, and distribution. This research develops an optimization model of blood distribution planning. The efficiency of decentralization and centralization policies in a blood distribution chain are compared, by optimizing the amount of blood delivered from a blood center to a blood bank. This model is developed based on allocation problem of capacitated planning model. At the first stage, the capacity and the cost of transportation are considered to create an initial capacitated planning model. Then, the inventory holding and shortage costs are added to the model. These additional parameters of inventory costs lead the model to be more realistic and accurate.

Variable context Markov chains for HIV protease cleavage site prediction.

PubMed

Oğul, Hasan

2009-06-01

Deciphering the knowledge of HIV protease specificity and developing computational tools for detecting its cleavage sites in protein polypeptide chain are very desirable for designing efficient and specific chemical inhibitors to prevent acquired immunodeficiency syndrome. In this study, we developed a generative model based on a generalization of variable order Markov chains (VOMC) for peptide sequences and adapted the model for prediction of their cleavability by certain proteases. The new method, called variable context Markov chains (VCMC), attempts to identify the context equivalence based on the evolutionary similarities between individual amino acids. It was applied for HIV-1 protease cleavage site prediction problem and shown to outperform existing methods in terms of prediction accuracy on a common dataset. In general, the method is a promising tool for prediction of cleavage sites of all proteases and encouraged to be used for any kind of peptide classification problem as well.

Direct observation of single flexible polymers using single stranded DNA†

PubMed Central

Brockman, Christopher; Kim, Sun Ju

2012-01-01

Over the last 15 years, double stranded DNA (dsDNA) has been used as a model polymeric system for nearly all single polymer dynamics studies. However, dsDNA is a semiflexible polymer with markedly different molecular properties compared to flexible chains, including synthetic organic polymers. In this work, we report a new system for single polymer studies of flexible chains based on single stranded DNA (ssDNA). We developed a method to synthesize ssDNA for fluorescence microscopy based on rolling circle replication, which generates long strands (>65 kb) of ssDNA containing “designer” sequences, thereby preventing intramolecular base pair interactions. Polymers are synthesized to contain amine-modified bases randomly distributed along the backbone, which enables uniform labelling of polymer chains with a fluorescent dye to facilitate fluorescence microscopy and imaging. Using this approach, we synthesized ssDNA chains with long contour lengths (>30 μm) and relatively low dye loading ratios (~1 dye per 100 bases). In addition, we used epifluorescence microscopy to image single ssDNA polymer molecules stretching in flow in a microfluidic device. Overall, we anticipate that ssDNA will serve as a useful model system to probe the dynamics of polymeric materials at the molecular level. PMID:22956981

Analyzing the Critical Supply Chain For Unmanned Aircraft Systems

DTIC Science & Technology

2017-03-23

with a decision support tool that facilitates interdiction strategy planning. Overall, the different models developed in the study provide modeling...allow adaptation to different levels of fidelity of the supply chain, based on the user’s mission objectives and available data. A House of Quality...priorities are unknown or incorrect. 1.7 Implications The models presented in this research can be utilized from two different perspectives of

Contingent approach to Internet-based supply network integration

NASA Astrophysics Data System (ADS)

Ho, Jessica; Boughton, Nick; Kehoe, Dennis; Michaelides, Zenon

2001-10-01

The Internet is playing an increasingly important role in enhancing the operations of supply networks as many organizations begin to recognize the benefits of Internet- enabled supply arrangements. However, the developments and applications to-date do not extend significantly beyond the dyadic model, whereas the real advantages are to be made with the external and network models to support a coordinated and collaborative based approach. The DOMAIN research group at the University of Liverpool is currently defining new Internet- enabled approaches to enable greater collaboration across supply chains. Different e-business models and tools are focusing on different applications. Using inappropriate e- business models, tools or techniques will bring negative results instead of benefits to all the tiers in the supply network. Thus there are a number of issues to be considered before addressing Internet based supply network integration, in particular an understanding of supply chain management, the emergent business models and evaluating the effects of deploying e-business to the supply network or a particular tier. It is important to utilize a contingent approach to selecting the right e-business model to meet the specific supply chain requirements. This paper addresses the issues and provides a case study on the indirect materials supply networks.

Understanding the General Packing Rearrangements Required for Successful Template Based Modeling of Protein Structure from a CASP Experiment

PubMed Central

Day, Ryan; Joo, Hyun; Chavan, Archana; Lennox, Kristin P.; Chen, Ann; Dahl, David B.; Vannucci, Marina; Tsai, Jerry W.

2012-01-01

As an alternative to the common template based protein structure prediction methods based on main-chain position, a novel side-chain centric approach has been developed. Together with a Bayesian loop modeling procedure and a combination scoring function, the Stone Soup algorithm was applied to the CASP9 set of template based modeling targets. Although the method did not generate as large of perturbations to the template structures as necessary, the analysis of the results gives unique insights into the differences in packing between the target structures and their templates. Considerable variation in packing is found between target and template structures even when the structures are close, and this variation is found due to 2 and 3 body packing interactions. Outside the inherent restrictions in packing representation of the PDB, the first steps in correctly defining those regions of variable packing have been mapped primarily to local interactions, as the packing at the secondary and tertiary structure are largely conserved. Of the scoring functions used, a loop scoring function based on water structure exhibited some promise for discrimination. These results present a clear structural path for further development of a side-chain centered approach to template based modeling. PMID:23266765

Understanding the general packing rearrangements required for successful template based modeling of protein structure from a CASP experiment.

PubMed

Day, Ryan; Joo, Hyun; Chavan, Archana C; Lennox, Kristin P; Chen, Y Ann; Dahl, David B; Vannucci, Marina; Tsai, Jerry W

2013-02-01

As an alternative to the common template based protein structure prediction methods based on main-chain position, a novel side-chain centric approach has been developed. Together with a Bayesian loop modeling procedure and a combination scoring function, the Stone Soup algorithm was applied to the CASP9 set of template based modeling targets. Although the method did not generate as large of perturbations to the template structures as necessary, the analysis of the results gives unique insights into the differences in packing between the target structures and their templates. Considerable variation in packing is found between target and template structures even when the structures are close, and this variation is found due to 2 and 3 body packing interactions. Outside the inherent restrictions in packing representation of the PDB, the first steps in correctly defining those regions of variable packing have been mapped primarily to local interactions, as the packing at the secondary and tertiary structure are largely conserved. Of the scoring functions used, a loop scoring function based on water structure exhibited some promise for discrimination. These results present a clear structural path for further development of a side-chain centered approach to template based modeling. Copyright © 2012 Elsevier Ltd. All rights reserved.

Optimizing decentralized production-distribution planning problem in a multi-period supply chain network under uncertainty

NASA Astrophysics Data System (ADS)

Nourifar, Raheleh; Mahdavi, Iraj; Mahdavi-Amiri, Nezam; Paydar, Mohammad Mahdi

2017-09-01

Decentralized supply chain management is found to be significantly relevant in today's competitive markets. Production and distribution planning is posed as an important optimization problem in supply chain networks. Here, we propose a multi-period decentralized supply chain network model with uncertainty. The imprecision related to uncertain parameters like demand and price of the final product is appropriated with stochastic and fuzzy numbers. We provide mathematical formulation of the problem as a bi-level mixed integer linear programming model. Due to problem's convolution, a structure to solve is developed that incorporates a novel heuristic algorithm based on Kth-best algorithm, fuzzy approach and chance constraint approach. Ultimately, a numerical example is constructed and worked through to demonstrate applicability of the optimization model. A sensitivity analysis is also made.

Time-based analysis of the apheresis platelet supply chain in England.

PubMed

Wilding, R; Cotton, S; Dobbin, J; Chapman, J; Yates, N

2011-10-01

During 2009/2010 loss of platelets within NHS Blood and Transplant (NHSBT) due to time expiry was 9.3%. Hospitals remain reluctant to hold stocks of platelets due to the poor shelf life at issue. The purpose of this study was to identify areas for time compression in the apheresis platelet supply chain to extend the shelf life available for hospitals and reduce wastage in NHSBT. This was done within the context of NHSBT reconfiguring their supply chain and moving towards a consolidated and centralised approach. Time based process mapping was applied to identify value and non-value adding time in two manufacturing models. A large amount of the non-value adding time in the apheresis platelet supply chain is due to transportation and waiting for the next process in the manufacturing process to take place. Time based process mapping provides an effective 'lens' for supply chain professionals to identify opportunities for improvement in the platelet supply chain. © 2011 The Author(s). Vox Sanguinis © 2011 International Society of Blood Transfusion.

Modeling of plug-in electric vehicle travel patterns and charging load based on trip chain generation

NASA Astrophysics Data System (ADS)

Wang, Dai; Gao, Junyu; Li, Pan; Wang, Bin; Zhang, Cong; Saxena, Samveg

2017-08-01

Modeling PEV travel and charging behavior is the key to estimate the charging demand and further explore the potential of providing grid services. This paper presents a stochastic simulation methodology to generate itineraries and charging load profiles for a population of PEVs based on real-world vehicle driving data. In order to describe the sequence of daily travel activities, we use the trip chain model which contains the detailed information of each trip, namely start time, end time, trip distance, start location and end location. A trip chain generation method is developed based on the Naive Bayes model to generate a large number of trips which are temporally and spatially coupled. We apply the proposed methodology to investigate the multi-location charging loads in three different scenarios. Simulation results show that home charging can meet the energy demand of the majority of PEVs in an average condition. In addition, we calculate the lower bound of charging load peak on the premise of lowest charging cost. The results are instructive for the design and construction of charging facilities to avoid excessive infrastructure.

A Split-Path Schema-Based RFID Data Storage Model in Supply Chain Management

PubMed Central

Fan, Hua; Wu, Quanyuan; Lin, Yisong; Zhang, Jianfeng

2013-01-01

In modern supply chain management systems, Radio Frequency IDentification (RFID) technology has become an indispensable sensor technology and massive RFID data sets are expected to become commonplace. More and more space and time are needed to store and process such huge amounts of RFID data, and there is an increasing realization that the existing approaches cannot satisfy the requirements of RFID data management. In this paper, we present a split-path schema-based RFID data storage model. With a data separation mechanism, the massive RFID data produced in supply chain management systems can be stored and processed more efficiently. Then a tree structure-based path splitting approach is proposed to intelligently and automatically split the movement paths of products. Furthermore, based on the proposed new storage model, we design the relational schema to store the path information and time information of tags, and some typical query templates and SQL statements are defined. Finally, we conduct various experiments to measure the effect and performance of our model and demonstrate that it performs significantly better than the baseline approach in both the data expression and path-oriented RFID data query performance. PMID:23645112

Buckling of paramagnetic chains in soft gels

NASA Astrophysics Data System (ADS)

Huang, Shilin; Pessot, Giorgio; Cremer, Peet; Weeber, Rudolf; Holm, Christian; Nowak, Johannes; Odenbach, Stefan; Menzel, Andreas M.; Auernhammer, Günter K.

We study the magneto-elastic coupling behavior of paramagnetic chains in soft polymer gels exposed to external magnetic fields. To this end, a laser scanning confocal microscope is used to observe the morphology of the paramagnetic chains together with the deformation field of the surrounding gel network. The paramagnetic chains in soft polymer gels show rich morphological shape changes under oblique magnetic fields, in particular a pronounced buckling deformation. The details of the resulting morphological shapes depend on the length of the chain, the strength of the external magnetic field, and the modulus of the gel. Based on the observation that the magnetic chains are strongly coupled to the surrounding polymer network, a simplified model is developed to describe their buckling behavior. A coarse-grained molecular dynamics simulation model featuring an increased matrix stiffness on the surfaces of the particles leads to morphologies in agreement with the experimentally observed buckling effects.

Theory and simulation of the dynamics, deformation, and breakup of a chain of superparamagnetic beads under a rotating magnetic field

NASA Astrophysics Data System (ADS)

Vázquez-Quesada, A.; Franke, T.; Ellero, M.

2017-03-01

In this work, an analytical model for the behavior of superparamagnetic chains under the effect of a rotating magnetic field is presented. It is postulated that the relevant mechanisms for describing the shape and breakup of the chains into smaller fragments are the induced dipole-dipole magnetic force on the external beads, their translational and rotational drag forces, and the tangential lubrication between particles. Under this assumption, the characteristic S-shape of the chain can be qualitatively understood. Furthermore, based on a straight chain approximation, a novel analytical expression for the critical frequency for the chain breakup is obtained. In order to validate the model, the analytical expressions are compared with full three-dimensional smoothed particle hydrodynamics simulations of magnetic beads showing excellent agreement. Comparison with previous theoretical results and experimental data is also reported.

A Unified Framework for Complex Networks with Degree Trichotomy Based on Markov Chains.

PubMed

Hui, David Shui Wing; Chen, Yi-Chao; Zhang, Gong; Wu, Weijie; Chen, Guanrong; Lui, John C S; Li, Yingtao

2017-06-16

This paper establishes a Markov chain model as a unified framework for describing the evolution processes in complex networks. The unique feature of the proposed model is its capability in addressing the formation mechanism that can reflect the "trichotomy" observed in degree distributions, based on which closed-form solutions can be derived. Important special cases of the proposed unified framework are those classical models, including Poisson, Exponential, Power-law distributed networks. Both simulation and experimental results demonstrate a good match of the proposed model with real datasets, showing its superiority over the classical models. Implications of the model to various applications including citation analysis, online social networks, and vehicular networks design, are also discussed in the paper.

Dynamic Models and Coordination Analysis of Reverse Supply Chain with Remanufacturing

NASA Astrophysics Data System (ADS)

Yan, Nina

In this paper, we establish a reverse chain system with one manufacturer and one retailer under demand uncertainties. Distinguishing between the recycling process of the retailer and the remanufacturing process of the manufacturer, we formulate a two-stage dynamic model for reverse supply chain based on remanufacturing. Using buyback contract as coordination mechanism and applying dynamic programming the optimal decision problems for each stage are analyzed. It concluded that the reverse supply chain system could be coordinated under the given condition. Finally, we carry out numerical calculations to analyze the expected profits for the manufacturer and the retailer under different recovery rates and recovery prices and the outcomes validate the theoretical analyses.

Toward tailoring Majorana bound states in artificially constructed magnetic atom chains on elemental superconductors

PubMed Central

Thorwart, Michael

2018-01-01

Realizing Majorana bound states (MBS) in condensed matter systems is a key challenge on the way toward topological quantum computing. As a promising platform, one-dimensional magnetic chains on conventional superconductors were theoretically predicted to host MBS at the chain ends. We demonstrate a novel approach to design of model-type atomic-scale systems for studying MBS using single-atom manipulation techniques. Our artificially constructed atomic Fe chains on a Re surface exhibit spin spiral states and a remarkable enhancement of the local density of states at zero energy being strongly localized at the chain ends. Moreover, the zero-energy modes at the chain ends are shown to emerge and become stabilized with increasing chain length. Tight-binding model calculations based on parameters obtained from ab initio calculations corroborate that the system resides in the topological phase. Our work opens new pathways to design MBS in atomic-scale hybrid structures as a basis for fault-tolerant topological quantum computing. PMID:29756034

Toward tailoring Majorana bound states in artificially constructed magnetic atom chains on elemental superconductors.

PubMed

Kim, Howon; Palacio-Morales, Alexandra; Posske, Thore; Rózsa, Levente; Palotás, Krisztián; Szunyogh, László; Thorwart, Michael; Wiesendanger, Roland

2018-05-01

Realizing Majorana bound states (MBS) in condensed matter systems is a key challenge on the way toward topological quantum computing. As a promising platform, one-dimensional magnetic chains on conventional superconductors were theoretically predicted to host MBS at the chain ends. We demonstrate a novel approach to design of model-type atomic-scale systems for studying MBS using single-atom manipulation techniques. Our artificially constructed atomic Fe chains on a Re surface exhibit spin spiral states and a remarkable enhancement of the local density of states at zero energy being strongly localized at the chain ends. Moreover, the zero-energy modes at the chain ends are shown to emerge and become stabilized with increasing chain length. Tight-binding model calculations based on parameters obtained from ab initio calculations corroborate that the system resides in the topological phase. Our work opens new pathways to design MBS in atomic-scale hybrid structures as a basis for fault-tolerant topological quantum computing.

Dynamics of global supply chain and electric power networks: Models, pricing analysis, and computations

NASA Astrophysics Data System (ADS)

Matsypura, Dmytro

In this dissertation, I develop a new theoretical framework for the modeling, pricing analysis, and computation of solutions to electric power supply chains with power generators, suppliers, transmission service providers, and the inclusion of consumer demands. In particular, I advocate the application of finite-dimensional variational inequality theory, projected dynamical systems theory, game theory, network theory, and other tools that have been recently proposed for the modeling and analysis of supply chain networks (cf. Nagurney (2006)) to electric power markets. This dissertation contributes to the extant literature on the modeling, analysis, and solution of supply chain networks, including global supply chains, in general, and electric power supply chains, in particular, in the following ways. It develops a theoretical framework for modeling, pricing analysis, and computation of electric power flows/transactions in electric power systems using the rationale for supply chain analysis. The models developed include both static and dynamic ones. The dissertation also adds a new dimension to the methodology of the theory of projected dynamical systems by proving that, irrespective of the speeds of adjustment, the equilibrium of the system remains the same. Finally, I include alternative fuel suppliers, along with their behavior into the supply chain modeling and analysis framework. This dissertation has strong practical implications. In an era in which technology and globalization, coupled with increasing risk and uncertainty, complicate electricity demand and supply within and between nations, the successful management of electric power systems and pricing become increasingly pressing topics with relevance not only for economic prosperity but also national security. This dissertation addresses such related topics by providing models, pricing tools, and algorithms for decentralized electric power supply chains. This dissertation is based heavily on the following coauthored papers: Nagurney, Cruz, and Matsypura (2003), Nagurney and Matsypura (2004, 2005, 2006), Matsypura and Nagurney (2005), Matsypura, Nagurney, and Liu (2006).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ehlen, Mark A.; Sun, Amy C.; Pepple, Mark A.

The potential impacts of man-made and natural disasters on chemical plants, complexes, and supply chains are of great importance to homeland security. To be able to estimate these impacts, we developed an agent-based chemical supply chain model that includes: chemical plants with enterprise operations such as purchasing, production scheduling, and inventories; merchant chemical markets, and multi-modal chemical shipments. Large-scale simulations of chemical-plant activities and supply chain interactions, running on desktop computers, are used to estimate the scope and duration of disruptive-event impacts, and overall system resilience, based on the extent to which individual chemical plants can adjust their internal operationsmore » (e.g., production mixes and levels) versus their external interactions (market sales and purchases, and transportation routes and modes). As a result, to illustrate how the model estimates the impacts of a hurricane disruption, a simple example model centered on 1,4-butanediol is presented.« less

Biomass supply chain optimisation for Organosolv-based biorefineries.

PubMed

Giarola, Sara; Patel, Mayank; Shah, Nilay

2014-05-01

This work aims at providing a Mixed Integer Linear Programming modelling framework to help define planning strategies for the development of sustainable biorefineries. The up-scaling of an Organosolv biorefinery was addressed via optimisation of the whole system economics. Three real world case studies were addressed to show the high-level flexibility and wide applicability of the tool to model different biomass typologies (i.e. forest fellings, cereal residues and energy crops) and supply strategies. Model outcomes have revealed how supply chain optimisation techniques could help shed light on the development of sustainable biorefineries. Feedstock quality, quantity, temporal and geographical availability are crucial to determine biorefinery location and the cost-efficient way to supply the feedstock to the plant. Storage costs are relevant for biorefineries based on cereal stubble, while wood supply chains present dominant pretreatment operations costs. Copyright © 2014 Elsevier Ltd. All rights reserved.

Antibody side chain conformations are position-dependent.

PubMed

Leem, Jinwoo; Georges, Guy; Shi, Jiye; Deane, Charlotte M

2018-04-01

Side chain prediction is an integral component of computational antibody design and structure prediction. Current antibody modelling tools use backbone-dependent rotamer libraries with conformations taken from general proteins. Here we present our antibody-specific rotamer library, where rotamers are binned according to their immunogenetics (IMGT) position, rather than their local backbone geometry. We find that for some amino acid types at certain positions, only a restricted number of side chain conformations are ever observed. Using this information, we are able to reduce the breadth of the rotamer sampling space. Based on our rotamer library, we built a side chain predictor, position-dependent antibody rotamer swapper (PEARS). On a blind test set of 95 antibody model structures, PEARS had the highest average χ 1 and χ1+2 accuracy (78.7% and 64.8%) compared to three leading backbone-dependent side chain predictors. Our use of IMGT position, rather than backbone ϕ/ψ, meant that PEARS was more robust to errors in the backbone of the model structure. PEARS also achieved the lowest number of side chain-side chain clashes. PEARS is freely available as a web application at http://opig.stats.ox.ac.uk/webapps/pears. © 2018 Wiley Periodicals, Inc.

Side-chain conformational space analysis (SCSA): A multi conformation-based QSAR approach for modeling and prediction of protein-peptide binding affinities

NASA Astrophysics Data System (ADS)

Zhou, Peng; Chen, Xiang; Shang, Zhicai

2009-03-01

In this article, the concept of multi conformation-based quantitative structure-activity relationship (MCB-QSAR) is proposed, and based upon that, we describe a new approach called the side-chain conformational space analysis (SCSA) to model and predict protein-peptide binding affinities. In SCSA, multi-conformations (rather than traditional single-conformation) have received much attention, and the statistical average information on multi-conformations of side chains is determined using self-consistent mean field theory based upon side chain rotamer library. Thereby, enthalpy contributions (including electrostatic, steric, hydrophobic interaction and hydrogen bond) and conformational entropy effects to the binding are investigated in terms of occurrence probability of residue rotamers. Then, SCSA was applied into the dataset of 419 HLA-A*0201 binding peptides, and nonbonding contributions of each position in peptide ligands are well determined. For the peptides, the hydrogen bond and electrostatic interactions of the two ends are essential to the binding specificity, van der Waals and hydrophobic interactions of all the positions ensure strong binding affinity, and the loss of conformational entropy at anchor positions partially counteracts other favorable nonbonding effects.

Life cycle cost optimization of biofuel supply chains under uncertainties based on interval linear programming.

PubMed

Ren, Jingzheng; Dong, Liang; Sun, Lu; Goodsite, Michael Evan; Tan, Shiyu; Dong, Lichun

2015-01-01

The aim of this work was to develop a model for optimizing the life cycle cost of biofuel supply chain under uncertainties. Multiple agriculture zones, multiple transportation modes for the transport of grain and biofuel, multiple biofuel plants, and multiple market centers were considered in this model, and the price of the resources, the yield of grain and the market demands were regarded as interval numbers instead of constants. An interval linear programming was developed, and a method for solving interval linear programming was presented. An illustrative case was studied by the proposed model, and the results showed that the proposed model is feasible for designing biofuel supply chain under uncertainties. Copyright © 2015 Elsevier Ltd. All rights reserved.

A big-data model for multi-modal public transportation with application to macroscopic control and optimisation

NASA Astrophysics Data System (ADS)

Faizrahnemoon, Mahsa; Schlote, Arieh; Maggi, Lorenzo; Crisostomi, Emanuele; Shorten, Robert

2015-11-01

This paper describes a Markov-chain-based approach to modelling multi-modal transportation networks. An advantage of the model is the ability to accommodate complex dynamics and handle huge amounts of data. The transition matrix of the Markov chain is built and the model is validated using the data extracted from a traffic simulator. A realistic test-case using multi-modal data from the city of London is given to further support the ability of the proposed methodology to handle big quantities of data. Then, we use the Markov chain as a control tool to improve the overall efficiency of a transportation network, and some practical examples are described to illustrate the potentials of the approach.

Mathematical model of the loan portfolio dynamics in the form of Markov chain considering the process of new customers attraction

NASA Astrophysics Data System (ADS)

Bozhalkina, Yana

2017-12-01

Mathematical model of the loan portfolio structure change in the form of Markov chain is explored. This model considers in one scheme both the process of customers attraction, their selection based on the credit score, and loans repayment. The model describes the structure and volume of the loan portfolio dynamics, which allows to make medium-term forecasts of profitability and risk. Within the model corrective actions of bank management in order to increase lending volumes or to reduce the risk are formalized.

Sustainable Supplier Performance Evaluation and Selection with Neofuzzy TOPSIS Method

PubMed Central

Chaharsooghi, S. K.; Ashrafi, Mehdi

2014-01-01

Supplier selection plays an important role in the supply chain management and traditional criteria such as price, quality, and flexibility are considered for supplier performance evaluation in researches. In recent years sustainability has received more attention in the supply chain management literature with triple bottom line (TBL) describing the sustainability in supply chain management with social, environmental, and economic initiatives. This paper explores sustainability in supply chain management and examines the problem of identifying a new model for supplier selection based on extended model of TBL approach in supply chain by presenting fuzzy multicriteria method. Linguistic values of experts' subjective preferences are expressed with fuzzy numbers and Neofuzzy TOPSIS is proposed for finding the best solution of supplier selection problem. Numerical results show that the proposed model is efficient for integrating sustainability in supplier selection problem. The importance of using complimentary aspects of sustainability and Neofuzzy TOPSIS concept in sustainable supplier selection process is shown with sensitivity analysis. PMID:27379267

Optimization of Location-Routing Problem for Cold Chain Logistics Considering Carbon Footprint.

PubMed

Wang, Songyi; Tao, Fengming; Shi, Yuhe

2018-01-06

In order to solve the optimization problem of logistics distribution system for fresh food, this paper provides a low-carbon and environmental protection point of view, based on the characteristics of perishable products, and combines with the overall optimization idea of cold chain logistics distribution network, where the green and low-carbon location-routing problem (LRP) model in cold chain logistics is developed with the minimum total costs as the objective function, which includes carbon emission costs. A hybrid genetic algorithm with heuristic rules is designed to solve the model, and an example is used to verify the effectiveness of the algorithm. Furthermore, the simulation results obtained by a practical numerical example show the applicability of the model while provide green and environmentally friendly location-distribution schemes for the cold chain logistics enterprise. Finally, carbon tax policies are introduced to analyze the impact of carbon tax on the total costs and carbon emissions, which proves that carbon tax policy can effectively reduce carbon dioxide emissions in cold chain logistics network.

Sustainable Supplier Performance Evaluation and Selection with Neofuzzy TOPSIS Method.

PubMed

Chaharsooghi, S K; Ashrafi, Mehdi

2014-01-01

Supplier selection plays an important role in the supply chain management and traditional criteria such as price, quality, and flexibility are considered for supplier performance evaluation in researches. In recent years sustainability has received more attention in the supply chain management literature with triple bottom line (TBL) describing the sustainability in supply chain management with social, environmental, and economic initiatives. This paper explores sustainability in supply chain management and examines the problem of identifying a new model for supplier selection based on extended model of TBL approach in supply chain by presenting fuzzy multicriteria method. Linguistic values of experts' subjective preferences are expressed with fuzzy numbers and Neofuzzy TOPSIS is proposed for finding the best solution of supplier selection problem. Numerical results show that the proposed model is efficient for integrating sustainability in supplier selection problem. The importance of using complimentary aspects of sustainability and Neofuzzy TOPSIS concept in sustainable supplier selection process is shown with sensitivity analysis.

A design of strategic alliance based on value chain of surveying and mapping enterprises in China

NASA Astrophysics Data System (ADS)

Duan, Hong; Huang, Xianfeng

2007-06-01

In this paper, we use value chain and strategic alliance theories to analyzing the surveying and mapping Industry and enterprises. The value chain of surveying and mapping enterprises is highly-contacted but split by administrative interference, the enterprises are common small scale. According to the above things, we consider that establishing a nonequity- Holding strategic alliance based on value chain is an available way, it can not only let the enterprises share the superior resources in different sectors of the whole value chain each other but avoid offending the interests of related administrative departments, by this way, the surveying and mapping enterprises gain development respectively and totally. Then, we give the method to building up the strategic alliance model through parting the value chain and the using advantage of companies in different value chain sectors. Finally, we analyze the internal rule of strategic alliance and prove it is a suitable way to realize the development of surveying and mapping enterprises through game theory.

A new ChainMail approach for real-time soft tissue simulation.

PubMed

Zhang, Jinao; Zhong, Yongmin; Smith, Julian; Gu, Chengfan

2016-07-03

This paper presents a new ChainMail method for real-time soft tissue simulation. This method enables the use of different material properties for chain elements to accommodate various materials. Based on the ChainMail bounding region, a new time-saving scheme is developed to improve computational efficiency for isotropic materials. The proposed method also conserves volume and strain energy. Experimental results demonstrate that the proposed ChainMail method can not only accommodate isotropic, anisotropic and heterogeneous materials but also model incompressibility and relaxation behaviors of soft tissues. Further, the proposed method can achieve real-time computational performance.

Stackelberg Game of Buyback Policy in Supply Chain with a Risk-Averse Retailer and a Risk-Averse Supplier Based on CVaR

PubMed Central

Zhou, Yanju; Chen, Qian; Chen, Xiaohong; Wang, Zongrun

2014-01-01

This paper considers a decentralized supply chain in which a single supplier sells a perishable product to a single retailer facing uncertain demand. We assume that the supplier and the retailer are both risk averse and utilize Conditional Value at Risk (CVaR), a risk measure method which is popularized in financial risk management, to estimate their risk attitude. We establish a buyback policy model based on Stackelberg game theory under considering supply chain members' risk preference and get the expressions of the supplier's optimal repurchase price and the retailer's optimal order quantity which are compared with those under risk neutral case. Finally, a numerical example is applied to simulate that model and prove related conclusions. PMID:25247605

Stackelberg game of buyback policy in supply chain with a risk-averse retailer and a risk-averse supplier based on CVaR.

PubMed

Zhou, Yanju; Chen, Qian; Chen, Xiaohong; Wang, Zongrun

2014-01-01

This paper considers a decentralized supply chain in which a single supplier sells a perishable product to a single retailer facing uncertain demand. We assume that the supplier and the retailer are both risk averse and utilize Conditional Value at Risk (CVaR), a risk measure method which is popularized in financial risk management, to estimate their risk attitude. We establish a buyback policy model based on Stackelberg game theory under considering supply chain members' risk preference and get the expressions of the supplier's optimal repurchase price and the retailer's optimal order quantity which are compared with those under risk neutral case. Finally, a numerical example is applied to simulate that model and prove related conclusions.

Room temperature ionic liquids: A simple model. Effect of chain length and size of intermolecular potential on critical temperature.

PubMed

Chapela, Gustavo A; Guzmán, Orlando; Díaz-Herrera, Enrique; del Río, Fernando

2015-04-21

A model of a room temperature ionic liquid can be represented as an ion attached to an aliphatic chain mixed with a counter ion. The simple model used in this work is based on a short rigid tangent square well chain with an ion, represented by a hard sphere interacting with a Yukawa potential at the head of the chain, mixed with a counter ion represented as well by a hard sphere interacting with a Yukawa potential of the opposite sign. The length of the chain and the depth of the intermolecular forces are investigated in order to understand which of these factors are responsible for the lowering of the critical temperature. It is the large difference between the ionic and the dispersion potentials which explains this lowering of the critical temperature. Calculation of liquid-vapor equilibrium orthobaric curves is used to estimate the critical points of the model. Vapor pressures are used to obtain an estimate of the triple point of the different models in order to calculate the span of temperatures where they remain a liquid. Surface tensions and interfacial thicknesses are also reported.

Antiresonance induced spin-polarized current generation

NASA Astrophysics Data System (ADS)

Yin, Sun; Min, Wen-Jing; Gao, Kun; Xie, Shi-Jie; Liu, De-Sheng

2011-12-01

According to the one-dimensional antiresonance effect (Wang X R, Wang Y and Sun Z Z 2003 Phys. Rev. B 65 193402), we propose a possible spin-polarized current generation device. Our proposed model consists of one chain and an impurity coupling to the chain. The energy level of the impurity can be occupied by an electron with a specific spin, and the electron with such a spin is blocked because of the antiresonance effect. Based on this phenomenon our model can generate the spin-polarized current flowing through the chain due to different polarization rates. On the other hand, the device can also be used to measure the generated spin accumulation. Our model is feasible with today's technology.

On the thermodynamic and kinetic investigations of a [c2]daisy chain polymer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hmadeh, Mohamad; Fang, Lei; Trabolsi, Ali

2010-01-01

We report a variety of [c2]daisy chain molecules which undergo quantitative, efficient, and fully reversible molecular movements upon the addition of base/acid in organic solvents. Such externally triggered molecular movements can induce the contraction and extension of the [c2]daisy chain molecule as a whole. A linear polymer of such a bistable [c2]daisy chain exerts similar types of movements and can be looked upon as a candidate for the development of artificial muscles. The spectrophotometric investigations of both the monomeric and polymeric bistable [c2]daisy chains, as well as the corresponding model compounds, were performed in MeCN at room temperature, in ordermore » to obtain the thermodynamic parameters for these mechanically interlocked molecules. Based on their spectrophotometric and thermodynamic characteristics, kinetic analysis of the acid/base-induced contraction and extension of the [c2]daisy chain monomer and polymer were conducted by employing a stopped-flow technique. These kinetic data suggest that the rates of contraction and extension for these [c2]daisy chain molecules are determined by the thermodynamic stabilities of the corresponding kinetic intermediates. Faster switching rates for both the contraction and extension processes of the polymeric [c2]daisy chain were observed when compared to those of its monomeric counterpart. These kinetic and thermodynamic investigations on [c2]daisy chain-based muscle-like compounds provide important information for those seeking an understanding of the mechanisms of actuation in mechanically interlocked macromolecules.« less

Research on the performance evaluation of agricultural products supply chain integrated operation

NASA Astrophysics Data System (ADS)

Jiang, Jiake; Wang, Xifu; Liu, Yang

2017-04-01

The agricultural product supply chain integrated operation can ensure the quality and efficiency of agricultural products, and achieve the optimal goal of low cost and high service. This paper establishes a performance evaluation index system of agricultural products supply chain integration operation based on the development status of agricultural products and SCOR, BSC and KPI model. And then, we constructing rough set theory and BP neural network comprehensive evaluation model with the aid of Rosetta and MATLAB tools and the case study is about the development of agricultural products integrated supply chain in Jing-Jin-Ji region. And finally, we obtain the corresponding performance results, and give some improvement measures and management recommendations to the managers.

Kepler Uniform Modeling of KOIs: MCMC Notes for Data Release 25

NASA Technical Reports Server (NTRS)

Hoffman, Kelsey L.; Rowe, Jason F.

2017-01-01

This document describes data products related to the reported planetary parameters and uncertainties for the Kepler Objects of Interest (KOIs) based on a Markov-Chain-Monte-Carlo (MCMC) analysis. Reported parameters, uncertainties and data products can be found at the NASA Exoplanet Archive . The codes used for this data analysis are available on the Github website (Rowe 2016). The relevant paper for details of the calculations is Rowe et al. (2015). The main differences between the model fits discussed here and those in the DR24 catalogue are that the DR25 light curves were used in the analysis, our processing of the MAST light curves took into account different data flags, the number of chains calculated was doubled to 200 000, and the parameters which are reported are based on a damped least-squares fit, instead of the median value from the Markov chain or the chain with the lowest 2 as reported in the past.

An all-atom structure-based potential for proteins: bridging minimal models with all-atom empirical forcefields.

PubMed

Whitford, Paul C; Noel, Jeffrey K; Gosavi, Shachi; Schug, Alexander; Sanbonmatsu, Kevin Y; Onuchic, José N

2009-05-01

Protein dynamics take place on many time and length scales. Coarse-grained structure-based (Go) models utilize the funneled energy landscape theory of protein folding to provide an understanding of both long time and long length scale dynamics. All-atom empirical forcefields with explicit solvent can elucidate our understanding of short time dynamics with high energetic and structural resolution. Thus, structure-based models with atomic details included can be used to bridge our understanding between these two approaches. We report on the robustness of folding mechanisms in one such all-atom model. Results for the B domain of Protein A, the SH3 domain of C-Src Kinase, and Chymotrypsin Inhibitor 2 are reported. The interplay between side chain packing and backbone folding is explored. We also compare this model to a C(alpha) structure-based model and an all-atom empirical forcefield. Key findings include: (1) backbone collapse is accompanied by partial side chain packing in a cooperative transition and residual side chain packing occurs gradually with decreasing temperature, (2) folding mechanisms are robust to variations of the energetic parameters, (3) protein folding free-energy barriers can be manipulated through parametric modifications, (4) the global folding mechanisms in a C(alpha) model and the all-atom model agree, although differences can be attributed to energetic heterogeneity in the all-atom model, and (5) proline residues have significant effects on folding mechanisms, independent of isomerization effects. Because this structure-based model has atomic resolution, this work lays the foundation for future studies to probe the contributions of specific energetic factors on protein folding and function.

An All-atom Structure-Based Potential for Proteins: Bridging Minimal Models with All-atom Empirical Forcefields

PubMed Central

Whitford, Paul C.; Noel, Jeffrey K.; Gosavi, Shachi; Schug, Alexander; Sanbonmatsu, Kevin Y.; Onuchic, José N.

2012-01-01

Protein dynamics take place on many time and length scales. Coarse-grained structure-based (Gō) models utilize the funneled energy landscape theory of protein folding to provide an understanding of both long time and long length scale dynamics. All-atom empirical forcefields with explicit solvent can elucidate our understanding of short time dynamics with high energetic and structural resolution. Thus, structure-based models with atomic details included can be used to bridge our understanding between these two approaches. We report on the robustness of folding mechanisms in one such all-atom model. Results for the B domain of Protein A, the SH3 domain of C-Src Kinase and Chymotrypsin Inhibitor 2 are reported. The interplay between side chain packing and backbone folding is explored. We also compare this model to a Cα structure-based model and an all-atom empirical forcefield. Key findings include 1) backbone collapse is accompanied by partial side chain packing in a cooperative transition and residual side chain packing occurs gradually with decreasing temperature 2) folding mechanisms are robust to variations of the energetic parameters 3) protein folding free energy barriers can be manipulated through parametric modifications 4) the global folding mechanisms in a Cα model and the all-atom model agree, although differences can be attributed to energetic heterogeneity in the all-atom model 5) proline residues have significant effects on folding mechanisms, independent of isomerization effects. Since this structure-based model has atomic resolution, this work lays the foundation for future studies to probe the contributions of specific energetic factors on protein folding and function. PMID:18837035

A discrete scattering series representation for lattice embedded models of chain cyclization

NASA Astrophysics Data System (ADS)

Fraser, Simon J.; Winnik, Mitchell A.

1980-01-01

In this paper we develop a lattice based model of chain cyclization in the presence of a set of occupied sites V in the lattice. We show that within the approximation of a Markovian chain propagator the effect of V on the partition function for the system can be written as a time-ordered exponential series in which V behaves like a scattering potential and chainlength is the timelike parameter. The discrete and finite nature of this model allows us to obtain rigorous upper and lower bounds to the series limit. We adapt these formulas to calculation of the partition functions and cyclization probabilities of terminally and globally cyclizing chains. Two classes of cyclization are considered: in the first model the target set H may be visited repeatedly (the Markovian model); in the second case vertices in H may be visited at most once(the non-Markovian or taboo model). This formulation depends on two fundamental combinatorial structures, namely the inclusion-exclusion principle and the set of subsets of a set. We have tried to interpret these abstract structures with physical analogies throughout the paper.

Sense and Respond Logistics: Integrating Prediction, Responsiveness, and Control Capabilities

DTIC Science & Technology

2006-01-01

logistics SAR sense and respond SCM Supply Chain Management SCN Supply Chain Network SIDA sense, interpret, decide, act SOS source of supply TCN...commodity supply chain management ( SCM ), will have WS- SCMs that focus on integrating information for a particular MDS. 8 In the remainder of this...developed applications of ABMs for SCM .21 Applications of Agents and Agent-Based Modeling Agents have been used in telecommunications, e-commerce

Density functional theory-based simulations of sum frequency generation spectra involving methyl stretching vibrations: effect of the molecular model on the deduced molecular orientation and comparison with an analytical approach.

PubMed

Cecchet, F; Lis, D; Caudano, Y; Mani, A A; Peremans, A; Champagne, B; Guthmuller, J

2012-03-28

The knowledge of the first hyperpolarizability tensor elements of molecular groups is crucial for a quantitative interpretation of the sum frequency generation (SFG) activity of thin organic films at interfaces. Here, the SFG response of the terminal methyl group of a dodecanethiol (DDT) monolayer has been interpreted on the basis of calculations performed at the density functional theory (DFT) level of approximation. In particular, DFT calculations have been carried out on three classes of models for the aliphatic chains. The first class of models consists of aliphatic chains, containing from 3 to 12 carbon atoms, in which only one methyl group can freely vibrate, while the rest of the chain is frozen by a strong overweight of its C and H atoms. This enables us to localize the probed vibrational modes on the methyl group. In the second class, only one methyl group is frozen, while the entire remaining chain is allowed to vibrate. This enables us to analyse the influence of the aliphatic chain on the methyl stretching vibrations. Finally, the dodecanethiol (DDT) molecule is considered, for which the effects of two dielectrics, i.e. n-hexane and n-dodecane, are investigated. Moreover, DDT calculations are also carried out by using different exchange-correlation (XC) functionals in order to assess the DFT approximations. Using the DFT IR vectors and Raman tensors, the SFG spectrum of DDT has been simulated and the orientation of the methyl group has then been deduced and compared with that obtained using an analytical approach based on a bond additivity model. This analysis shows that when using DFT molecular properties, the predicted orientation of the terminal methyl group tends to converge as a function of the alkyl chain length and that the effects of the chain as well as of the dielectric environment are small. Instead, a more significant difference is observed when comparing the DFT-based results with those obtained from the analytical approach, thus indicating the importance of a quantum chemical description of the hyperpolarizability tensor elements of the methyl group. © 2012 IOP Publishing Ltd

Dissolution of covalent adaptable network polymers in organic solvent

NASA Astrophysics Data System (ADS)

Yu, Kai; Yang, Hua; Dao, Binh H.; Shi, Qian; Yakacki, Christopher M.

2017-12-01

It was recently reported that thermosetting polymers can be fully dissolved in a proper organic solvent utilizing a bond-exchange reaction (BER), where small molecules diffuse into the polymer, break the long polymer chains into short segments, and eventually dissolve the network when sufficient solvent is provided. The solvent-assisted dissolution approach was applied to fully recycle thermosets and their fiber composites. This paper presents the first multi-scale modeling framework to predict the dissolution kinetics and mechanics of thermosets in organic solvent. The model connects the micro-scale network dynamics with macro-scale material properties: in the micro-scale, a model is developed based on the kinetics of BERs to describe the cleavage rate of polymer chains and evolution of chain segment length during the dissolution. The micro-scale model is then fed into a continuum-level model with considerations of the transportation of solvent molecules and chain segments in the system. The model shows good prediction on conversion rate of functional groups, degradation of network mechanical properties, and dissolution rate of thermosets during the dissolution. It identifies the underlying kinetic factors governing the dissolution process, and reveals the influence of different material and processing variables on the dissolution process, such as time, temperature, catalyst concentration, and chain length between cross-links.

Source term evaluation model for high-level radioactive waste repository with decay chain build-up.

PubMed

Chopra, Manish; Sunny, Faby; Oza, R B

2016-09-18

A source term model based on two-component leach flux concept is developed for a high-level radioactive waste repository. The long-lived radionuclides associated with high-level waste may give rise to the build-up of activity because of radioactive decay chains. The ingrowths of progeny are incorporated in the model using Bateman decay chain build-up equations. The model is applied to different radionuclides present in the high-level radioactive waste, which form a part of decay chains (4n to 4n + 3 series), and the activity of the parent and daughter radionuclides leaching out of the waste matrix is estimated. Two cases are considered: one when only parent is present initially in the waste and another where daughters are also initially present in the waste matrix. The incorporation of in situ production of daughter radionuclides in the source is important to carry out realistic estimates. It is shown that the inclusion of decay chain build-up is essential to avoid underestimation of the radiological impact assessment of the repository. The model can be a useful tool for evaluating the source term of the radionuclide transport models used for the radiological impact assessment of high-level radioactive waste repositories.

Model-based extended quaternion Kalman filter to inertial orientation tracking of arbitrary kinematic chains.

PubMed

Szczęsna, Agnieszka; Pruszowski, Przemysław

2016-01-01

Inertial orientation tracking is still an area of active research, especially in the context of out-door, real-time, human motion capture. Existing systems either propose loosely coupled tracking approaches where each segment is considered independently, taking the resulting drawbacks into account, or tightly coupled solutions that are limited to a fixed chain with few segments. Such solutions have no flexibility to change the skeleton structure, are dedicated to a specific set of joints, and have high computational complexity. This paper describes the proposal of a new model-based extended quaternion Kalman filter that allows for estimation of orientation based on outputs from the inertial measurements unit sensors. The filter considers interdependencies resulting from the construction of the kinematic chain so that the orientation estimation is more accurate. The proposed solution is a universal filter that does not predetermine the degree of freedom at the connections between segments of the model. To validation the motion of 3-segments single link pendulum captured by optical motion capture system is used. The next step in the research will be to use this method for inertial motion capture with a human skeleton model.

Linear viscoelasticity of a single semiflexible polymer with internal friction.

PubMed

Hiraiwa, Tetsuya; Ohta, Takao

2010-07-28

The linear viscoelastic behaviors of single semiflexible chains with internal friction are studied based on the wormlike-chain model. It is shown that the frequency dependence of the complex compliance in the high frequency limit is the same as that of the Voigt model. This asymptotic behavior appears also for the Rouse model with internal friction. We derive the characteristic times for both the high frequency limit and the low frequency limit and compare the results with those obtained by Khatri et al.

Modeling qRT-PCR dynamics with application to cancer biomarker quantification.

PubMed

Chervoneva, Inna; Freydin, Boris; Hyslop, Terry; Waldman, Scott A

2017-01-01

Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is widely used for molecular diagnostics and evaluating prognosis in cancer. The utility of mRNA expression biomarkers relies heavily on the accuracy and precision of quantification, which is still challenging for low abundance transcripts. The critical step for quantification is accurate estimation of efficiency needed for computing a relative qRT-PCR expression. We propose a new approach to estimating qRT-PCR efficiency based on modeling dynamics of polymerase chain reaction amplification. In contrast, only models for fluorescence intensity as a function of polymerase chain reaction cycle have been used so far for quantification. The dynamics of qRT-PCR efficiency is modeled using an ordinary differential equation model, and the fitted ordinary differential equation model is used to obtain effective polymerase chain reaction efficiency estimates needed for efficiency-adjusted quantification. The proposed new qRT-PCR efficiency estimates were used to quantify GUCY2C (Guanylate Cyclase 2C) mRNA expression in the blood of colorectal cancer patients. Time to recurrence and GUCY2C expression ratios were analyzed in a joint model for survival and longitudinal outcomes. The joint model with GUCY2C quantified using the proposed polymerase chain reaction efficiency estimates provided clinically meaningful results for association between time to recurrence and longitudinal trends in GUCY2C expression.

Document Ranking Based upon Markov Chains.

ERIC Educational Resources Information Center

Danilowicz, Czeslaw; Balinski, Jaroslaw

2001-01-01

Considers how the order of documents in information retrieval responses are determined and introduces a method that uses a probabilistic model of a document set where documents are regarded as states of a Markov chain and where transition probabilities are directly proportional to similarities between documents. (Author/LRW)

ChainMail based neural dynamics modeling of soft tissue deformation for surgical simulation.

PubMed

Zhang, Jinao; Zhong, Yongmin; Smith, Julian; Gu, Chengfan

2017-07-20

Realistic and real-time modeling and simulation of soft tissue deformation is a fundamental research issue in the field of surgical simulation. In this paper, a novel cellular neural network approach is presented for modeling and simulation of soft tissue deformation by combining neural dynamics of cellular neural network with ChainMail mechanism. The proposed method formulates the problem of elastic deformation into cellular neural network activities to avoid the complex computation of elasticity. The local position adjustments of ChainMail are incorporated into the cellular neural network as the local connectivity of cells, through which the dynamic behaviors of soft tissue deformation are transformed into the neural dynamics of cellular neural network. Experiments demonstrate that the proposed neural network approach is capable of modeling the soft tissues' nonlinear deformation and typical mechanical behaviors. The proposed method not only improves ChainMail's linear deformation with the nonlinear characteristics of neural dynamics but also enables the cellular neural network to follow the principle of continuum mechanics to simulate soft tissue deformation.

Competence-Based Approach in Value Chain Processes

NASA Astrophysics Data System (ADS)

Azevedo, Rodrigo Cambiaghi; D'Amours, Sophie; Rönnqvist, Mikael

There is a gap between competence theory and value chain processes frameworks. While individually considered as core elements in contemporary management thinking, the integration of the two concepts is still lacking. We claim that this integration would allow for the development of more robust business models by structuring value chain activities around aspects such as capabilities and skills, as well as individual and organizational knowledge. In this context, the objective of this article is to reduce this gap and consequently open a field for further improvements of value chain processes frameworks.

Sampling rare fluctuations of discrete-time Markov chains

NASA Astrophysics Data System (ADS)

Whitelam, Stephen

2018-03-01

We describe a simple method that can be used to sample the rare fluctuations of discrete-time Markov chains. We focus on the case of Markov chains with well-defined steady-state measures, and derive expressions for the large-deviation rate functions (and upper bounds on such functions) for dynamical quantities extensive in the length of the Markov chain. We illustrate the method using a series of simple examples, and use it to study the fluctuations of a lattice-based model of active matter that can undergo motility-induced phase separation.

Sampling rare fluctuations of discrete-time Markov chains.

PubMed

Whitelam, Stephen

2018-03-01

We describe a simple method that can be used to sample the rare fluctuations of discrete-time Markov chains. We focus on the case of Markov chains with well-defined steady-state measures, and derive expressions for the large-deviation rate functions (and upper bounds on such functions) for dynamical quantities extensive in the length of the Markov chain. We illustrate the method using a series of simple examples, and use it to study the fluctuations of a lattice-based model of active matter that can undergo motility-induced phase separation.

Utilization of two web-based continuing education courses evaluated by Markov chain model.

PubMed

Tian, Hao; Lin, Jin-Mann S; Reeves, William C

2012-01-01

To evaluate the web structure of two web-based continuing education courses, identify problems and assess the effects of web site modifications. Markov chain models were built from 2008 web usage data to evaluate the courses' web structure and navigation patterns. The web site was then modified to resolve identified design issues and the improvement in user activity over the subsequent 12 months was quantitatively evaluated. Web navigation paths were collected between 2008 and 2010. The probability of navigating from one web page to another was analyzed. The continuing education courses' sequential structure design was clearly reflected in the resulting actual web usage models, and none of the skip transitions provided was heavily used. The web navigation patterns of the two different continuing education courses were similar. Two possible design flaws were identified and fixed in only one of the two courses. Over the following 12 months, the drop-out rate in the modified course significantly decreased from 41% to 35%, but remained unchanged in the unmodified course. The web improvement effects were further verified via a second-order Markov chain model. The results imply that differences in web content have less impact than web structure design on how learners navigate through continuing education courses. Evaluation of user navigation can help identify web design flaws and guide modifications. This study showed that Markov chain models provide a valuable tool to evaluate web-based education courses. Both the results and techniques in this study would be very useful for public health education and research specialists.

Utilization of two web-based continuing education courses evaluated by Markov chain model

PubMed Central

Lin, Jin-Mann S; Reeves, William C

2011-01-01

Objectives To evaluate the web structure of two web-based continuing education courses, identify problems and assess the effects of web site modifications. Design Markov chain models were built from 2008 web usage data to evaluate the courses' web structure and navigation patterns. The web site was then modified to resolve identified design issues and the improvement in user activity over the subsequent 12 months was quantitatively evaluated. Measurements Web navigation paths were collected between 2008 and 2010. The probability of navigating from one web page to another was analyzed. Results The continuing education courses' sequential structure design was clearly reflected in the resulting actual web usage models, and none of the skip transitions provided was heavily used. The web navigation patterns of the two different continuing education courses were similar. Two possible design flaws were identified and fixed in only one of the two courses. Over the following 12 months, the drop-out rate in the modified course significantly decreased from 41% to 35%, but remained unchanged in the unmodified course. The web improvement effects were further verified via a second-order Markov chain model. Conclusions The results imply that differences in web content have less impact than web structure design on how learners navigate through continuing education courses. Evaluation of user navigation can help identify web design flaws and guide modifications. This study showed that Markov chain models provide a valuable tool to evaluate web-based education courses. Both the results and techniques in this study would be very useful for public health education and research specialists. PMID:21976027

Implementation of system dynamic simulation method to optimize profit in supply chain network of vegetable product

NASA Astrophysics Data System (ADS)

Tama, I. P.; Akbar, Z.; Eunike, A.

2018-04-01

Vegetables are categorized as a perishable product, which is a product with short lifespan thus requires proper handling and planning to reduce losses caused by the short lifespan. In order to reduce the losses, coordination among the players in the supply chain is required. On the other hand, the decision in the supply chain of vegetables and other farming products in the traditional market of developing country is independent among the players. This research is conducted by using System Dynamic Simulation method to develop model and scenario by coordinating the supply quantity amongst players in the supply chain. The scenarios are developed based on newsboy inventory model. This study aims to compare scenarios combining tiers involved in coordination program. The result shows that coordination in supply chain increases total supply chain profit, although there will always be players who experienced decrements in profit. The scenario of coordination among the farmer, the distributor, and the wholesaler resulted in the highest increase in total supply chain profit compared to other coordination scenarios, with an increased value of 10.49%.

Cloud point phenomena for POE-type nonionic surfactants in a model room temperature ionic liquid.

PubMed

Inoue, Tohru; Misono, Takeshi

2008-10-15

The cloud point phenomenon has been investigated for the solutions of polyoxyethylene (POE)-type nonionic surfactants (C(12)E(5), C(12)E(6), C(12)E(7), C(10)E(6), and C(14)E(6)) in 1-butyl-3-methylimidazolium tetrafluoroborate (bmimBF(4)), a typical room temperature ionic liquid (RTIL). The cloud point, T(c), increases with the elongation of the POE chain, while decreases with the increase in the hydrocarbon chain length. This demonstrates that the solvophilicity/solvophobicity of the surfactants in RTIL comes from POE chain/hydrocarbon chain. When compared with an aqueous system, the chain length dependence of T(c) is larger for the RTIL system regarding both POE and hydrocarbon chains; in particular, hydrocarbon chain length affects T(c) much more strongly in the RTIL system than in equivalent aqueous systems. In a similar fashion to the much-studied aqueous systems, the micellar growth is also observed in this RTIL solvent as the temperature approaches T(c). The cloud point curves have been analyzed using a Flory-Huggins-type model based on phase separation in polymer solutions.

Evaluating approaches to find exon chains based on long reads.

PubMed

Kuosmanen, Anna; Norri, Tuukka; Mäkinen, Veli

2018-05-01

Transcript prediction can be modeled as a graph problem where exons are modeled as nodes and reads spanning two or more exons are modeled as exon chains. Pacific Biosciences third-generation sequencing technology produces significantly longer reads than earlier second-generation sequencing technologies, which gives valuable information about longer exon chains in a graph. However, with the high error rates of third-generation sequencing, aligning long reads correctly around the splice sites is a challenging task. Incorrect alignments lead to spurious nodes and arcs in the graph, which in turn lead to incorrect transcript predictions. We survey several approaches to find the exon chains corresponding to long reads in a splicing graph, and experimentally study the performance of these methods using simulated data to allow for sensitivity/precision analysis. Our experiments show that short reads from second-generation sequencing can be used to significantly improve exon chain correctness either by error-correcting the long reads before splicing graph creation, or by using them to create a splicing graph on which the long-read alignments are then projected. We also study the memory and time consumption of various modules, and show that accurate exon chains lead to significantly increased transcript prediction accuracy. The simulated data and in-house scripts used for this article are available at http://www.cs.helsinki.fi/group/gsa/exon-chains/exon-chains-bib.tar.bz2.

Phytosphingosine, sphingosine and dihydrosphingosine ceramides in model skin lipid membranes: permeability and biophysics.

PubMed

Školová, Barbora; Kováčik, Andrej; Tesař, Ondřej; Opálka, Lukáš; Vávrová, Kateřina

2017-05-01

Ceramides based on phytosphingosine, sphingosine and dihydrosphingosine are essential constituents of the skin lipid barrier that protects the body from excessive water loss. The roles of the individual ceramide subclasses in regulating skin permeability and the reasons for C4-hydroxylation of these sphingolipids are not completely understood. We investigated the chain length-dependent effects of dihydroceramides, sphingosine ceramides (with C4-unsaturation) and phytoceramides (with C4-hydroxyl) on the permeability, lipid organization and thermotropic behavior of model stratum corneum lipid membranes composed of ceramide/lignoceric acid/cholesterol/cholesteryl sulfate. Phytoceramides with very long C24 acyl chains increased the permeability of the model lipid membranes compared to dihydroceramides or sphingosine ceramides with the same chain lengths. Either unsaturation or C4-hydroxylation of dihydroceramides induced chain length-dependent increases in membrane permeability. Infrared spectroscopy showed that C4-hydroxylation of the sphingoid base decreased the relative ratio of orthorhombic chain packing in the membrane and lowered the miscibility of C24 phytoceramide with lignoceric acid. The phase separation in phytoceramide membranes was confirmed by X-ray diffraction. In contrast, phytoceramides formed strong hydrogen bonds and highly thermostable domains. Thus, the large heterogeneity in ceramide structures and in their aggregation mechanisms may confer resistance towards the heterogeneous external stressors that are constantly faced by the skin barrier. Copyright © 2017 Elsevier B.V. All rights reserved.

Capillarity theory for the fly-casting mechanism

PubMed Central

Trizac, Emmanuel; Levy, Yaakov; Wolynes, Peter G.

2010-01-01

Biomolecular folding and function are often coupled. During molecular recognition events, one of the binding partners may transiently or partially unfold, allowing more rapid access to a binding site. We describe a simple model for this fly-casting mechanism based on the capillarity approximation and polymer chain statistics. The model shows that fly casting is most effective when the protein unfolding barrier is small and the part of the chain which extends toward the target is relatively rigid. These features are often seen in known examples of fly casting in protein–DNA binding. Simulations of protein–DNA binding based on well-funneled native-topology models with electrostatic forces confirm the trends of the analytical theory. PMID:20133683

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rongle Zhang; Jie Chang; Yuanyuan Xu

A new kinetic model of the Fischer-Tropsch synthesis (FTS) is proposed to describe the non-Anderson-Schulz-Flory (ASF) product distribution. The model is based on the double-polymerization monomers hypothesis, in which the surface C{sub 2}{asterisk} species acts as a chain-growth monomer in the light-product range, while C{sub 1}{asterisk} species acts as a chain-growth monomer in the heavy-product range. The detailed kinetic model in the Langmuir-Hinshelwood-Hougen-Watson type based on the elementary reactions is derived for FTS and the water-gas-shift reaction. Kinetic model candidates are evaluated by minimization of multiresponse objective functions with a genetic algorithm approach. The model of hydrocarbon product distribution ismore » consistent with experimental data (

Comparison of particular logistic models' adoption in the Czech Republic

NASA Astrophysics Data System (ADS)

Vrbová, Petra; Cempírek, Václav

2016-12-01

Managing inventory is considered as one of the most challenging tasks facing supply chain managers and specialists. Decisions related to inventory locations along with level of inventory kept throughout the supply chain have a fundamental impact on the response time, service level, delivery lead-time and the total cost of the supply chain. The main objective of this paper is to identify and analyse the share of a particular logistic model adopted in the Czech Republic (Consignment stock, Buffer stock, Safety stock) and also compare their usage and adoption according to different industries. This paper also aims to specify possible reasons of particular logistic model preferences in comparison to the others. The analysis is based on quantitative survey held in the Czech Republic.

Dark Solitons in FPU Lattice Chain

NASA Astrophysics Data System (ADS)

Wang, Deng-Long; Yang, Ru-Shu; Yang, You-Tian

2007-11-01

Based on multiple scales method, we study the nonlinear properties of a new Fermi-Pasta-Ulam lattice model analytically. It is found that the lattice chain exhibits a novel nonlinear elementary excitation, i.e. a dark soliton. Moreover, the modulation depth of dark soliton is increasing as the anharmonic parameter increases.

Hybrid lattice gas simulations of flow through porous media

NASA Astrophysics Data System (ADS)

Becklehimer, Jeffrey Lynn

1997-10-01

This study introduces a suite of models designed to investigate transport phenomena in simulated porous media such as rigid or quenched sediment and clay-like deformable environments. This is achieved by using a variety of techniques that are borrowed from the field of statistical physics. These techniques include percolation, lattice gas, and cellular automata. A percolation-based model is used to study a porous medium by using rods and chains of various shapes and sizes to model the porous media formed by sediments. This is further extended to model clay-like deformable media by interacting heavy sediment particles. An interacting lattice gas computer simulation model based on the Metropolis algorithm is used to study the transport properties of fluid particles and permeability of a porous sediment. Finally, a hybrid lattice gas model is introduced by combining the Metropolis Monte Carlo method with a direct simulation which involves the collision rules as in cellular automata. This model is then used to study shock propagation in a fluid filled porous medium. This study is then extended to study shock propagation through in a fluid filled elastic porous medium. Several interesting and new results were obtained. These results show that for rigid chain percolation the percolation threshold shows a dependence on the chain length of pc~ Lc-1/2 and the jamming coverage decreases with the chain length as Lc- 1/3. For the random SAW-like chains the percolation threshold decays with the chain length as Lc- 0.01 and the jamming coverage as Lc-1/3. The fluid flow model shows that permeability depends nonmonotonically on the concentration of the fluid. For some fluids at a fixed porosity, the permeability increases on increasing the bias until a certain value Bc above which it decreases. Also, it was found that a shock propagates in a drift-like fashion when in a rigid porous medium when the porosity is high; low porosity damps out the shock front very quickly. For a shock propagating in a clay-like porous medium an unusually super-fast power-law behavior is observed for the RMS displacements of the fluid and clay particles.

Manned and Unmanned Aircraft Effectiveness in Fast Attack Craft / Fast Inshore Attack Craft ASUW Kill Chain Execution

DTIC Science & Technology

2016-09-01

par. 4) Based on a RED projected size of 22.16 m, a sample calculation for the unadjusted single shot probability of kill for HELLFIRE missiles is...framework based on intelligent objects (SIMIO) environment to model a fast attack craft/fast inshore attack craft anti-surface warfare expanded kill chain...concept of operation efficiency. Based on the operational environment, low cost and less capable unmanned aircraft provide an alternative to the

Charge transport properties of DNA aperiodic molecule: The role of interbase hopping in Watson-Crick base pair

NASA Astrophysics Data System (ADS)

Sinurat, E. N.; Yudiarsah, E.

2017-07-01

The charge transport properties of DNA aperiodic molecule has been studied by considering various interbase hopping parameter on Watson-Crick base pair. 32 base pairs long double-stranded DNA aperiodic model with sequence GCTAGTACGTGACGTAGCTAGGATATGCCTGA on one chain and its complement on the other chain is used. Transfer matrix method has been used to calculate transmission probabilities, for determining I-V characteristic using Landauer Büttiker formula. DNA molecule is modeled using tight binding hamiltonian combined with the theory of Slater-Koster. The result show, the increment of Watson-Crick hopping value leads to the transmission probabilities and current of DNA aperiodic molecule increases.

Pricing Models for Dual-channel Reverse Supply Chain Considering Regional Differences under “Internet Recycling” Mode in China

NASA Astrophysics Data System (ADS)

Wu, Di; Li, Peng; Chen, Juhong

2018-01-01

In recent years, the Internet technology has been deeply influencing recycling industry to make it more intelligent and interconnected. However, most existing papers on “Internet Recycling” neglected the problem of pricing strategy under online and offline channels for different levels of recyclers. Moreover, the effect of regional differences has been emphasized a lot in dual-channel forward supply chain, but recycling field has seldom been concerned about it. In this paper, a recycling system consisting of one recycling center and several third-party recyclers (TPR) was investigated based on traditional mode and dual-channel mode. The dual-channel reverse supply chain model is transformed from traditional mode by the introduction of online channel. It involves two recycling modes, as recycling centre for online recovery and “Recycling center+TPR” for offline recovery. By establishing pricing strategies based on Stackelberg game model, the impacts of regional differences were analysed. Finally, numerical analysis was given to illustrate the effectiveness of the pricing mechanisms and strategies.

Research on Duplication Dynamics and Evolutionary Stable of Reverse Supply Chain

NASA Astrophysics Data System (ADS)

Huizhong, Dong; Hongli, Song

An evolutionary game model of Reverse Supply Chain(RSC) is established based on duplication dynamics function and evolutionary stable strategy. Using the model framework, this paper provides insights into a deeper understanding on how each supplier make strategic decision independently in reverse supply chain to determine their performance. The main conclusion is as follow: Under the market mechanism, not unless the extra income derived from the implementation of RSC exceeds zero point would the suppliers implement RSC strategy. When those suppliers are passive to RSC, the effective solution is that the government takes macro-control measures, for example, to force those suppliers implement RSC through punishment mechanism.

Application of a transmission model to estimate performance objectives for Salmonella in the broiler supply chain.

PubMed

van der Fels-Klerx, H J; Tromp, S; Rijgersberg, H; van Asselt, E D

2008-11-30

The aim of the present study was to demonstrate how Performance Objectives (POs) for Salmonella at various points in the broiler supply chain can be estimated, starting from pre-set levels of the PO in finished products. The estimations were performed using an analytical transmission model, based on prevalence data collected throughout the chain in The Netherlands. In the baseline (current) situation, the end PO was set at 2.5% of the finished products (at end of processing) being contaminated with Salmonella. Scenario analyses were performed by reducing this baseline end PO to 1.5% and 0.5%. The results showed the end PO could be reduced by spreading the POs over the various stages of the broiler supply chain. Sensitivity analyses were performed by changing the values of the model parameters. Results indicated that, in general, decreasing Salmonella contamination between points in the chain is more effective in reducing the baseline PO than increasing the reduction of the pathogen, implying contamination should be prevented rather than treated. Application of both approaches at the same time showed to be most effective in reducing the end PO, especially at the abattoir and during processing. The modelling approach of this study proved to be useful to estimate the implications for preceding stages of the chain by setting a PO at the end of the chain as well as to evaluate the effectiveness of potential interventions in reducing the end PO. The model estimations may support policy-makers in their decision-making process with regard to microbiological food safety.

Optimization of Location–Routing Problem for Cold Chain Logistics Considering Carbon Footprint

PubMed Central

Wang, Songyi; Tao, Fengming; Shi, Yuhe

2018-01-01

In order to solve the optimization problem of logistics distribution system for fresh food, this paper provides a low-carbon and environmental protection point of view, based on the characteristics of perishable products, and combines with the overall optimization idea of cold chain logistics distribution network, where the green and low-carbon location–routing problem (LRP) model in cold chain logistics is developed with the minimum total costs as the objective function, which includes carbon emission costs. A hybrid genetic algorithm with heuristic rules is designed to solve the model, and an example is used to verify the effectiveness of the algorithm. Furthermore, the simulation results obtained by a practical numerical example show the applicability of the model while provide green and environmentally friendly location-distribution schemes for the cold chain logistics enterprise. Finally, carbon tax policies are introduced to analyze the impact of carbon tax on the total costs and carbon emissions, which proves that carbon tax policy can effectively reduce carbon dioxide emissions in cold chain logistics network. PMID:29316639

Entanglement Theories: Packing vs. Percolation

NASA Astrophysics Data System (ADS)

Wool, Richard

2007-03-01

There are two emergent theories of polymer entanglements, the Packing Model (Fetters, Lohse, Graessley, Milner, Whitten, ˜'98) and the Percolation Model (Wool ˜'93). The Packing model suggests that the entanglement molecular weight Me is determined by Me = K p^3, where the packing length parameter p = V/R^2 in which V is the volume of the chain (V=M/ρNa), R is the end-to end vector of the chain, and K 357 ρNa, is an empirical constant. The Percolation model states that an entanglement network develops when the number of chains per unit area σ, intersecting any load bearing plane, is equal to 3 times the number of chain segments (1/a cross-section), such that when 3aσ =1 at the percolation threshold, Me 31 MjC∞, in which Mj is the step molecular weight and C∞ is the characteristic ratio. There are no fitting parameters in the Percolation model. The Packing model predicts that Me decreases rapidly with chain stiffness, as Me˜1/C∞^3, while the Percolation model predicts that Me increases with C∞, as Me˜C∞. The Percolation model was found to be the correct model based on computer simulations (M. Bulacu et al) and a re-analysis of the Packing model experimental data. The Packing model can be derived from the Percolation model, but not visa versa, and reveals a surprising accidental relation between C∞ and Mj in the front factor K. This result significantly impacts the interpretation of the dynamics of rheology and fracture of entangled polymers.

Protein structure modeling and refinement by global optimization in CASP12.

PubMed

Hong, Seung Hwan; Joung, InSuk; Flores-Canales, Jose C; Manavalan, Balachandran; Cheng, Qianyi; Heo, Seungryong; Kim, Jong Yun; Lee, Sun Young; Nam, Mikyung; Joo, Keehyoung; Lee, In-Ho; Lee, Sung Jong; Lee, Jooyoung

2018-03-01

For protein structure modeling in the CASP12 experiment, we have developed a new protocol based on our previous CASP11 approach. The global optimization method of conformational space annealing (CSA) was applied to 3 stages of modeling: multiple sequence-structure alignment, three-dimensional (3D) chain building, and side-chain re-modeling. For better template selection and model selection, we updated our model quality assessment (QA) method with the newly developed SVMQA (support vector machine for quality assessment). For 3D chain building, we updated our energy function by including restraints generated from predicted residue-residue contacts. New energy terms for the predicted secondary structure and predicted solvent accessible surface area were also introduced. For difficult targets, we proposed a new method, LEEab, where the template term played a less significant role than it did in LEE, complemented by increased contributions from other terms such as the predicted contact term. For TBM (template-based modeling) targets, LEE performed better than LEEab, but for FM targets, LEEab was better. For model refinement, we modified our CASP11 molecular dynamics (MD) based protocol by using explicit solvents and tuning down restraint weights. Refinement results from MD simulations that used a new augmented statistical energy term in the force field were quite promising. Finally, when using inaccurate information (such as the predicted contacts), it was important to use the Lorentzian function for which the maximal penalty arising from wrong information is always bounded. © 2017 Wiley Periodicals, Inc.

Disease Compass- a navigation system for disease knowledge based on ontology and linked data techniques.

PubMed

Kozaki, Kouji; Yamagata, Yuki; Mizoguchi, Riichiro; Imai, Takeshi; Ohe, Kazuhiko

2017-06-19

Medical ontologies are expected to contribute to the effective use of medical information resources that store considerable amount of data. In this study, we focused on disease ontology because the complicated mechanisms of diseases are related to concepts across various medical domains. The authors developed a River Flow Model (RFM) of diseases, which captures diseases as the causal chains of abnormal states. It represents causes of diseases, disease progression, and downstream consequences of diseases, which is compliant with the intuition of medical experts. In this paper, we discuss a fact repository for causal chains of disease based on the disease ontology. It could be a valuable knowledge base for advanced medical information systems. We developed the fact repository for causal chains of diseases based on our disease ontology and abnormality ontology. This section summarizes these two ontologies. It is developed as linked data so that information scientists can access it using SPARQL queries through an Resource Description Framework (RDF) model for causal chain of diseases. We designed the RDF model as an implementation of the RFM for the fact repository based on the ontological definitions of the RFM. 1554 diseases and 7080 abnormal states in six major clinical areas, which are extracted from the disease ontology, are published as linked data (RDF) with SPARQL endpoint (accessible API). Furthermore, the authors developed Disease Compass, a navigation system for disease knowledge. Disease Compass can browse the causal chains of a disease and obtain related information, including abnormal states, through two web services that provide general information from linked data, such as DBpedia, and 3D anatomical images. Disease Compass can provide a complete picture of disease-associated processes in such a way that fits with a clinician's understanding of diseases. Therefore, it supports user exploration of disease knowledge with access to pertinent information from a variety of sources.

Markov Chain-Like Quantum Biological Modeling of Mutations, Aging, and Evolution.

PubMed

Djordjevic, Ivan B

2015-08-24

Recent evidence suggests that quantum mechanics is relevant in photosynthesis, magnetoreception, enzymatic catalytic reactions, olfactory reception, photoreception, genetics, electron-transfer in proteins, and evolution; to mention few. In our recent paper published in Life, we have derived the operator-sum representation of a biological channel based on codon basekets, and determined the quantum channel model suitable for study of the quantum biological channel capacity. However, this model is essentially memoryless and it is not able to properly model the propagation of mutation errors in time, the process of aging, and evolution of genetic information through generations. To solve for these problems, we propose novel quantum mechanical models to accurately describe the process of creation spontaneous, induced, and adaptive mutations and their propagation in time. Different biological channel models with memory, proposed in this paper, include: (i) Markovian classical model, (ii) Markovian-like quantum model, and (iii) hybrid quantum-classical model. We then apply these models in a study of aging and evolution of quantum biological channel capacity through generations. We also discuss key differences of these models with respect to a multilevel symmetric channel-based Markovian model and a Kimura model-based Markovian process. These models are quite general and applicable to many open problems in biology, not only biological channel capacity, which is the main focus of the paper. We will show that the famous quantum Master equation approach, commonly used to describe different biological processes, is just the first-order approximation of the proposed quantum Markov chain-like model, when the observation interval tends to zero. One of the important implications of this model is that the aging phenotype becomes determined by different underlying transition probabilities in both programmed and random (damage) Markov chain-like models of aging, which are mutually coupled.

Markov Chain-Like Quantum Biological Modeling of Mutations, Aging, and Evolution

PubMed Central

Djordjevic, Ivan B.

2015-01-01

Recent evidence suggests that quantum mechanics is relevant in photosynthesis, magnetoreception, enzymatic catalytic reactions, olfactory reception, photoreception, genetics, electron-transfer in proteins, and evolution; to mention few. In our recent paper published in Life, we have derived the operator-sum representation of a biological channel based on codon basekets, and determined the quantum channel model suitable for study of the quantum biological channel capacity. However, this model is essentially memoryless and it is not able to properly model the propagation of mutation errors in time, the process of aging, and evolution of genetic information through generations. To solve for these problems, we propose novel quantum mechanical models to accurately describe the process of creation spontaneous, induced, and adaptive mutations and their propagation in time. Different biological channel models with memory, proposed in this paper, include: (i) Markovian classical model, (ii) Markovian-like quantum model, and (iii) hybrid quantum-classical model. We then apply these models in a study of aging and evolution of quantum biological channel capacity through generations. We also discuss key differences of these models with respect to a multilevel symmetric channel-based Markovian model and a Kimura model-based Markovian process. These models are quite general and applicable to many open problems in biology, not only biological channel capacity, which is the main focus of the paper. We will show that the famous quantum Master equation approach, commonly used to describe different biological processes, is just the first-order approximation of the proposed quantum Markov chain-like model, when the observation interval tends to zero. One of the important implications of this model is that the aging phenotype becomes determined by different underlying transition probabilities in both programmed and random (damage) Markov chain-like models of aging, which are mutually coupled. PMID:26305258

An IT-enabled supply chain model: a simulation study

NASA Astrophysics Data System (ADS)

Cannella, Salvatore; Framinan, Jose M.; Barbosa-Póvoa, Ana

2014-11-01

During the last decades, supply chain collaboration practices and the underlying enabling technologies have evolved from the classical electronic data interchange (EDI) approach to a web-based and radio frequency identification (RFID)-enabled collaboration. In this field, most of the literature has focused on the study of optimal parameters for reducing the total cost of suppliers, by adopting operational research (OR) techniques. Herein we are interested in showing that the considered information technology (IT)-enabled structure is resilient, that is, it works well across a reasonably broad range of parameter settings. By adopting a methodological approach based on system dynamics, we study a multi-tier collaborative supply chain. Results show that the IT-enabled supply chain improves operational performance and customer service level. Nonetheless, benefits for geographically dispersed networks are of minor entity.

Micromechanics-based magneto-elastic constitutive modeling of particulate composites

NASA Astrophysics Data System (ADS)

Yin, Huiming

Modified Green's functions are derived for three situations: a magnetic field caused by a local magnetization, a displacement field caused by a local body force and a displacement field caused by a local prescribed eigenstrain. Based on these functions, an explicit solution is derived for two magnetic particles embedded in the infinite medium under external magnetic and mechanical loading. A general solution for numerable magnetic particles embedded in an infinite domain is then provided in integral form. Two-phase composites containing spherical magnetic particles of the same size are considered for three kinds of microstructures. With chain-structured composites, particle interactions in the same chain are considered and a transversely isotropic effective elasticity is obtained. For periodic composites, an eight-particle interaction model is developed and provides a cubic symmetric effective elasticity. In the random composite, pair-wise particle interactions are integrated from all possible positions and an isotropic effective property is reached. This method is further extended to functionally graded composites. Magneto-mechanical behavior is studied for the chain-structured composite and the random composite. Effective magnetic permeability, effective magnetostriction and field-dependent effective elasticity are investigated. It is seen that the chain-structured composite is more sensitive to the magnetic field than the random composite; a composite consisting of only 5% of chain-structured particles can provide a larger magnetostriction and a larger change of effective elasticity than an equivalent composite consisting of 30% of random dispersed particles. Moreover, the effective shear modulus of the chain-structured composite rapidly increases with the magnetic field, while that for the random composite decreases. An effective hyperelastic constitutive model is further developed for a magnetostrictive particle-filled elastomer, which is sampled by using a network of body-centered cubic lattices of particles connected by macromolecular chains. The proposed hyperelastic model is able to characterize overall nonlinear elastic stress-stretch relations of the composites under general three-dimensional loading. It is seen that the effective strain energy density is proportional to the length of stretched chains in unit volume and volume fraction of particles.

Functionalizing graphene by embedded boron clusters

NASA Astrophysics Data System (ADS)

Quandt, Alexander; Özdoğan, Cem; Kunstmann, Jens; Fehske, Holger

2008-08-01

We present a model system that might serve as a blueprint for the controlled layout of graphene based nanodevices. The systems consists of chains of B7 clusters implanted in a graphene matrix, where the boron clusters are not directly connected. We show that the graphene matrix easily accepts these alternating B7-C6 chains and that the implanted boron components may dramatically modify the electronic properties of graphene based nanomaterials. This suggests a functionalization of graphene nanomaterials, where the semiconducting properties might be supplemented by parts of the graphene matrix itself, but the basic wiring will be provided by alternating chains of implanted boron clusters that connect these areas.

Mitigation of short-term disturbance negative impacts in the agent-based model of a production companies network

NASA Astrophysics Data System (ADS)

Shevchuk, G. K.; Berg, D. B.; Zvereva, O. M.; Medvedeva, M. A.

2017-11-01

This article is devoted to the study of a supply chain disturbance impact on manufacturing volumes in a production system network. Each network agent's product can be used as a resource by other system agents (manufacturers). A supply chain disturbance can lead to operating cease of the entire network. Authors suggest using of short-term partial resources reservation to mitigate negative consequences of such disturbances. An agent-based model with a reservation algorithm compatible with strategies for resource procurement in terms of financial constraints was engineered. This model works in accordance with the static input-output Leontief 's model. The results can be used for choosing the ways of system's stability improving, and protecting it from various disturbances and imbalance.

Network Security Risk Assessment System Based on Attack Graph and Markov Chain

NASA Astrophysics Data System (ADS)

Sun, Fuxiong; Pi, Juntao; Lv, Jin; Cao, Tian

2017-10-01

Network security risk assessment technology can be found in advance of the network problems and related vulnerabilities, it has become an important means to solve the problem of network security. Based on attack graph and Markov chain, this paper provides a Network Security Risk Assessment Model (NSRAM). Based on the network infiltration tests, NSRAM generates the attack graph by the breadth traversal algorithm. Combines with the international standard CVSS, the attack probability of atomic nodes are counted, and then the attack transition probabilities of ones are calculated by Markov chain. NSRAM selects the optimal attack path after comprehensive measurement to assessment network security risk. The simulation results show that NSRAM can reflect the actual situation of network security objectively.

Molecular dynamics simulations of theoretical cellulose nanotube models.

PubMed

Uto, Takuya; Kodama, Yuta; Miyata, Tatsuhiko; Yui, Toshifumi

2018-06-15

Nanotubes are remarkable nanoscale architectures for a wide range of potential applications. In the present paper, we report a molecular dynamics (MD) study of the theoretical cellulose nanotube (CelNT) models to evaluate their dynamic behavior in solution (either chloroform or benzene). Based on the one-quarter chain staggering relationship, we constructed six CelNT models by combining the two chain polarities (parallel (P) and antiparallel (AP)) and three symmetry operations (helical right (H R ), helical left (H L ), and rotation (R)) to generate a circular arrangement of molecular chains. Among the four models that retained the tubular form (P-H R , P-H L , P-R, and AP-R), the P-R and AP-R models have the lowest steric energies in benzene and chloroform, respectively. The structural features of the CelNT models were characterized in terms of the hydroxymethyl group conformation and intermolecular hydrogen bonds. Solvent structuring more clearly occurred with benzene than chloroform, suggesting that the CelNT models may disperse in benzene. Copyright © 2018 Elsevier Ltd. All rights reserved.

Covariate adjustment of event histories estimated from Markov chains: the additive approach.

PubMed

Aalen, O O; Borgan, O; Fekjaer, H

2001-12-01

Markov chain models are frequently used for studying event histories that include transitions between several states. An empirical transition matrix for nonhomogeneous Markov chains has previously been developed, including a detailed statistical theory based on counting processes and martingales. In this article, we show how to estimate transition probabilities dependent on covariates. This technique may, e.g., be used for making estimates of individual prognosis in epidemiological or clinical studies. The covariates are included through nonparametric additive models on the transition intensities of the Markov chain. The additive model allows for estimation of covariate-dependent transition intensities, and again a detailed theory exists based on counting processes. The martingale setting now allows for a very natural combination of the empirical transition matrix and the additive model, resulting in estimates that can be expressed as stochastic integrals, and hence their properties are easily evaluated. Two medical examples will be given. In the first example, we study how the lung cancer mortality of uranium miners depends on smoking and radon exposure. In the second example, we study how the probability of being in response depends on patient group and prophylactic treatment for leukemia patients who have had a bone marrow transplantation. A program in R and S-PLUS that can carry out the analyses described here has been developed and is freely available on the Internet.

Modelling and analysis of workflow for lean supply chains

NASA Astrophysics Data System (ADS)

Ma, Jinping; Wang, Kanliang; Xu, Lida

2011-11-01

Cross-organisational workflow systems are a component of enterprise information systems which support collaborative business process among organisations in supply chain. Currently, the majority of workflow systems is developed in perspectives of information modelling without considering actual requirements of supply chain management. In this article, we focus on the modelling and analysis of the cross-organisational workflow systems in the context of lean supply chain (LSC) using Petri nets. First, the article describes the assumed conditions of cross-organisation workflow net according to the idea of LSC and then discusses the standardisation of collaborating business process between organisations in the context of LSC. Second, the concept of labelled time Petri nets (LTPNs) is defined through combining labelled Petri nets with time Petri nets, and the concept of labelled time workflow nets (LTWNs) is also defined based on LTPNs. Cross-organisational labelled time workflow nets (CLTWNs) is then defined based on LTWNs. Third, the article proposes the notion of OR-silent CLTWNS and a verifying approach to the soundness of LTWNs and CLTWNs. Finally, this article illustrates how to use the proposed method by a simple example. The purpose of this research is to establish a formal method of modelling and analysis of workflow systems for LSC. This study initiates a new perspective of research on cross-organisational workflow management and promotes operation management of LSC in real world settings.

Bayesian parameter inference for stochastic biochemical network models using particle Markov chain Monte Carlo

PubMed Central

Golightly, Andrew; Wilkinson, Darren J.

2011-01-01

Computational systems biology is concerned with the development of detailed mechanistic models of biological processes. Such models are often stochastic and analytically intractable, containing uncertain parameters that must be estimated from time course data. In this article, we consider the task of inferring the parameters of a stochastic kinetic model defined as a Markov (jump) process. Inference for the parameters of complex nonlinear multivariate stochastic process models is a challenging problem, but we find here that algorithms based on particle Markov chain Monte Carlo turn out to be a very effective computationally intensive approach to the problem. Approximations to the inferential model based on stochastic differential equations (SDEs) are considered, as well as improvements to the inference scheme that exploit the SDE structure. We apply the methodology to a Lotka–Volterra system and a prokaryotic auto-regulatory network. PMID:23226583

Risk assessment of supply chain for pharmaceutical excipients with AHP-fuzzy comprehensive evaluation.

PubMed

Li, Maozhong; Du, Yunai; Wang, Qiyue; Sun, Chunmeng; Ling, Xiang; Yu, Boyang; Tu, Jiasheng; Xiong, Yerong

2016-01-01

As the essential components in formulations, pharmaceutical excipients directly affect the safety, efficacy, and stability of drugs. Recently, safety incidents of pharmaceutical excipients posing seriously threats to the patients highlight the necessity of controlling the potential risks. Hence, it is indispensable for the industry to establish an effective risk assessment system of supply chain. In this study, an AHP-fuzzy comprehensive evaluation model was developed based on the analytic hierarchy process and fuzzy mathematical theory, which quantitatively assessed the risks of supply chain. Taking polysorbate 80 as the example for model analysis, it was concluded that polysorbate 80 for injection use is a high-risk ingredient in the supply chain compared to that for oral use to achieve safety application in clinic, thus measures should be taken to control and minimize those risks.

Risk assessment of supply chain for pharmaceutical excipients with AHP-fuzzy comprehensive evaluation.

PubMed

Li, Maozhong; Du, Yunai; Wang, Qiyue; Sun, Chunmeng; Ling, Xiang; Yu, Boyang; Tu, Jiasheng; Xiong, Yerong

2016-04-01

As the essential components in formulations, pharmaceutical excipients directly affect the safety, efficacy, and stability of drugs. Recently, safety incidents of pharmaceutical excipients posing seriously threats to the patients highlight the necessity of controlling the potential risks. Hence, it is indispensable for the industry to establish an effective risk assessment system of supply chain. In this study, an AHP-fuzzy comprehensive evaluation model was developed based on the analytic hierarchy process and fuzzy mathematical theory, which quantitatively assessed the risks of supply chain. Taking polysorbate 80 as the example for model analysis, it was concluded that polysorbate 80 for injection use is a high-risk ingredient in the supply chain compared to that for oral use to achieve safety application in clinic, thus measures should be taken to control and minimize those risks.

Land transportation model for supply chain manufacturing industries

NASA Astrophysics Data System (ADS)

Kurniawan, Fajar

2017-12-01

Supply chain is a system that integrates production, inventory, distribution and information processes for increasing productivity and minimize costs. Transportation is an important part of the supply chain system, especially for supporting the material distribution process, work in process products and final products. In fact, Jakarta as the distribution center of manufacturing industries for the industrial area. Transportation system has a large influences on the implementation of supply chain process efficiency. The main problem faced in Jakarta is traffic jam that will affect on the time of distribution. Based on the system dynamic model, there are several scenarios that can provide solutions to minimize timing of distribution that will effect on the cost such as the construction of ports approaching industrial areas other than Tanjung Priok, widening road facilities, development of railways system, and the development of distribution center.

Marker-based reconstruction of the kinematics of a chain of segments: a new method that incorporates joint kinematic constraints.

PubMed

Klous, Miriam; Klous, Sander

2010-07-01

The aim of skin-marker-based motion analysis is to reconstruct the motion of a kinematical model from noisy measured motion of skin markers. Existing kinematic models for reconstruction of chains of segments can be divided into two categories: analytical methods that do not take joint constraints into account and numerical global optimization methods that do take joint constraints into account but require numerical optimization of a large number of degrees of freedom, especially when the number of segments increases. In this study, a new and largely analytical method for a chain of rigid bodies is presented, interconnected in spherical joints (chain-method). In this method, the number of generalized coordinates to be determined through numerical optimization is three, irrespective of the number of segments. This new method is compared with the analytical method of Veldpaus et al. [1988, "A Least-Squares Algorithm for the Equiform Transformation From Spatial Marker Co-Ordinates," J. Biomech., 21, pp. 45-54] (Veldpaus-method, a method of the first category) and the numerical global optimization method of Lu and O'Connor [1999, "Bone Position Estimation From Skin-Marker Co-Ordinates Using Global Optimization With Joint Constraints," J. Biomech., 32, pp. 129-134] (Lu-method, a method of the second category) regarding the effects of continuous noise simulating skin movement artifacts and regarding systematic errors in joint constraints. The study is based on simulated data to allow a comparison of the results of the different algorithms with true (noise- and error-free) marker locations. Results indicate a clear trend that accuracy for the chain-method is higher than the Veldpaus-method and similar to the Lu-method. Because large parts of the equations in the chain-method can be solved analytically, the speed of convergence in this method is substantially higher than in the Lu-method. With only three segments, the average number of required iterations with the chain-method is 3.0+/-0.2 times lower than with the Lu-method when skin movement artifacts are simulated by applying a continuous noise model. When simulating systematic errors in joint constraints, the number of iterations for the chain-method was almost a factor 5 lower than the number of iterations for the Lu-method. However, the Lu-method performs slightly better than the chain-method. The RMSD value between the reconstructed and actual marker positions is approximately 57% of the systematic error on the joint center positions for the Lu-method compared with 59% for the chain-method.

Markov Chain Ontology Analysis (MCOA)

PubMed Central

2012-01-01

Background Biomedical ontologies have become an increasingly critical lens through which researchers analyze the genomic, clinical and bibliographic data that fuels scientific research. Of particular relevance are methods, such as enrichment analysis, that quantify the importance of ontology classes relative to a collection of domain data. Current analytical techniques, however, remain limited in their ability to handle many important types of structural complexity encountered in real biological systems including class overlaps, continuously valued data, inter-instance relationships, non-hierarchical relationships between classes, semantic distance and sparse data. Results In this paper, we describe a methodology called Markov Chain Ontology Analysis (MCOA) and illustrate its use through a MCOA-based enrichment analysis application based on a generative model of gene activation. MCOA models the classes in an ontology, the instances from an associated dataset and all directional inter-class, class-to-instance and inter-instance relationships as a single finite ergodic Markov chain. The adjusted transition probability matrix for this Markov chain enables the calculation of eigenvector values that quantify the importance of each ontology class relative to other classes and the associated data set members. On both controlled Gene Ontology (GO) data sets created with Escherichia coli, Drosophila melanogaster and Homo sapiens annotations and real gene expression data extracted from the Gene Expression Omnibus (GEO), the MCOA enrichment analysis approach provides the best performance of comparable state-of-the-art methods. Conclusion A methodology based on Markov chain models and network analytic metrics can help detect the relevant signal within large, highly interdependent and noisy data sets and, for applications such as enrichment analysis, has been shown to generate superior performance on both real and simulated data relative to existing state-of-the-art approaches. PMID:22300537

Markov Chain Ontology Analysis (MCOA).

PubMed

Frost, H Robert; McCray, Alexa T

2012-02-03

Biomedical ontologies have become an increasingly critical lens through which researchers analyze the genomic, clinical and bibliographic data that fuels scientific research. Of particular relevance are methods, such as enrichment analysis, that quantify the importance of ontology classes relative to a collection of domain data. Current analytical techniques, however, remain limited in their ability to handle many important types of structural complexity encountered in real biological systems including class overlaps, continuously valued data, inter-instance relationships, non-hierarchical relationships between classes, semantic distance and sparse data. In this paper, we describe a methodology called Markov Chain Ontology Analysis (MCOA) and illustrate its use through a MCOA-based enrichment analysis application based on a generative model of gene activation. MCOA models the classes in an ontology, the instances from an associated dataset and all directional inter-class, class-to-instance and inter-instance relationships as a single finite ergodic Markov chain. The adjusted transition probability matrix for this Markov chain enables the calculation of eigenvector values that quantify the importance of each ontology class relative to other classes and the associated data set members. On both controlled Gene Ontology (GO) data sets created with Escherichia coli, Drosophila melanogaster and Homo sapiens annotations and real gene expression data extracted from the Gene Expression Omnibus (GEO), the MCOA enrichment analysis approach provides the best performance of comparable state-of-the-art methods. A methodology based on Markov chain models and network analytic metrics can help detect the relevant signal within large, highly interdependent and noisy data sets and, for applications such as enrichment analysis, has been shown to generate superior performance on both real and simulated data relative to existing state-of-the-art approaches.

A descriptive model of resting-state networks using Markov chains.

PubMed

Xie, H; Pal, R; Mitra, S

2016-08-01

Resting-state functional connectivity (RSFC) studies considering pairwise linear correlations have attracted great interests while the underlying functional network structure still remains poorly understood. To further our understanding of RSFC, this paper presents an analysis of the resting-state networks (RSNs) based on the steady-state distributions and provides a novel angle to investigate the RSFC of multiple functional nodes. This paper evaluates the consistency of two networks based on the Hellinger distance between the steady-state distributions of the inferred Markov chain models. The results show that generated steady-state distributions of default mode network have higher consistency across subjects than random nodes from various RSNs.

Geometric modelling of the contact point between the bushing and sprocket in chain drives

NASA Astrophysics Data System (ADS)

Saulescu, R.; Velicu, R.; Lates, M.

2017-02-01

An important problem of the bush chains dynamics is represented by the calculus of the normal and transversal forces on all the contacts; these forces are producing vibrations in the chain and due to this, the chain is affected by the wear. One aspect of that dynamics is referring directly on the sprockets geometry and on the bushing and sprocket contact. The paper presents a calculus method for the contact angle between the bushing and the sprocket; this angle is a variable one depending on the bushing’s number being in contact (i) and on the specific elongation of the chain (x) due to the functioning of it. Based on the presented calculus model, a comparative analysis is proposed for these factors by using sprockets with different teeth numbers and different specific elongations of the chain. The results of the numerical simulations allow the dissemination of recommendations regarding the contact angle’s evolution, from the beginning to the end of the contact and regarding the influence of the chain’s specific elongations on the out of use of it.

Monte Carlo simulation and equation of state for flexible charged hard-sphere chain fluids: polyampholyte and polyelectrolyte solutions.

PubMed

Jiang, Hao; Adidharma, Hertanto

2014-11-07

The thermodynamic modeling of flexible charged hard-sphere chains representing polyampholyte or polyelectrolyte molecules in solution is considered. The excess Helmholtz energy and osmotic coefficients of solutions containing short polyampholyte and the osmotic coefficients of solutions containing short polyelectrolytes are determined by performing canonical and isobaric-isothermal Monte Carlo simulations. A new equation of state based on the thermodynamic perturbation theory is also proposed for flexible charged hard-sphere chains. For the modeling of such chains, the use of solely the structure information of monomer fluid for calculating the chain contribution is found to be insufficient and more detailed structure information must therefore be considered. Two approaches, i.e., the dimer and dimer-monomer approaches, are explored to obtain the contribution of the chain formation to the Helmholtz energy. By comparing with the simulation results, the equation of state with either the dimer or dimer-monomer approach accurately predicts the excess Helmholtz energy and osmotic coefficients of polyampholyte and polyelectrolyte solutions except at very low density. It also well captures the effect of temperature on the thermodynamic properties of these solutions.

Design and analysis of the Gemini chain system in dual clutch transmission of automobile

NASA Astrophysics Data System (ADS)

Cheng, Yabing; Guo, Haitao; Fu, Zhenming; Wan, Nen; Li, Lei; Wang, Yang

2015-01-01

Chain drive system is widely used in the conditions of high-speed, overload, variable speed and load. Many studies are focused on the meshing theory and wear characteristics of chain drive system, but system design, analysis, and noise characteristics of the chain drive system are weak. System design and noise characteristic are studied for a new type Gemini chain of dual-clutch automatic transmission. Based on the meshing theory of silent chain, the design parameters of the Gemini chain system are calculated and the mathematical models and dynamic analysis models of the Gemini chain system are established. Dynamic characteristics of the Gemini chain system is simulated and the contact force of plate and pin, plate and sprockets, the chain tension forces, the transmission error and the stress of plates and pins are analyzed. According to the simulation results of the Gemini chain system, the noise experiment about system is carried out. The noise values are tested at different speed and load and spectral characteristics are analyzed. The results of simulation and experimental show that the contact forces of plate and pin, plate and sprockets are smaller than the allowable stress values, the chain tension force is less than ultimate tension and transmission error is limited in 1.2%. The noise values can meet the requirements of industrial design, and it is proved that the design and analysis method of the Gemini chain system is scientific and feasible. The design and test system is built from analysis to test of Gemini chain system. This research presented will provide a corresponding theoretical guidance for the design and dynamic characteristics and noise characteristics of chain drive system.

Integrated supply chain design for commodity chemicals production via woody biomass fast pyrolysis and upgrading.

PubMed

Zhang, Yanan; Hu, Guiping; Brown, Robert C

2014-04-01

This study investigates the optimal supply chain design for commodity chemicals (BTX, etc.) production via woody biomass fast pyrolysis and hydroprocessing pathway. The locations and capacities of distributed preprocessing hubs and integrated biorefinery facilities are optimized with a mixed integer linear programming model. In this integrated supply chain system, decisions on the biomass chipping methods (roadside chipping vs. facility chipping) are also explored. The economic objective of the supply chain model is to maximize the profit for a 20-year chemicals production system. In addition to the economic objective, the model also incorporates an environmental objective of minimizing life cycle greenhouse gas emissions, analyzing the trade-off between the economic and environmental considerations. The capital cost, operating cost, and revenues for the biorefinery facilities are based on techno-economic analysis, and the proposed approach is illustrated through a case study of Minnesota, with Minneapolis-St. Paul serving as the chemicals distribution hub. Copyright © 2014 Elsevier Ltd. All rights reserved.

Analysing biomass torrefaction supply chain costs.

PubMed

Svanberg, Martin; Olofsson, Ingemar; Flodén, Jonas; Nordin, Anders

2013-08-01

The objective of the present work was to develop a techno-economic system model to evaluate how logistics and production parameters affect the torrefaction supply chain costs under Swedish conditions. The model consists of four sub-models: (1) supply system, (2) a complete energy and mass balance of drying, torrefaction and densification, (3) investment and operating costs of a green field, stand-alone torrefaction pellet plant, and (4) distribution system to the gate of an end user. The results show that the torrefaction supply chain reaps significant economies of scale up to a plant size of about 150-200 kiloton dry substance per year (ktonDS/year), for which the total supply chain costs accounts to 31.8 euro per megawatt hour based on lower heating value (€/MWhLHV). Important parameters affecting total cost are amount of available biomass, biomass premium, logistics equipment, biomass moisture content, drying technology, torrefaction mass yield and torrefaction plant capital expenditures (CAPEX). Copyright © 2013 Elsevier Ltd. All rights reserved.

The Bethe ansatz

NASA Astrophysics Data System (ADS)

Levkovich-Maslyuk, Fedor

2016-08-01

We give a pedagogical introduction to the Bethe ansatz techniques in integrable QFTs and spin chains. We first discuss and motivate the general framework of asymptotic Bethe ansatz for the spectrum of integrable QFTs in large volume, based on the exact S-matrix. Then we illustrate this method in several concrete theories. The first case we study is the SU(2) chiral Gross-Neveu model. We derive the Bethe equations via algebraic Bethe ansatz, solving in the process the Heisenberg XXX spin chain. We discuss this famous spin chain model in some detail, covering in particular the coordinate Bethe ansatz, some properties of Bethe states, and the classical scaling limit leading to finite-gap equations. Then we proceed to the more involved SU(3) chiral Gross-Neveu model and derive the Bethe equations using nested algebraic Bethe ansatz to solve the arising SU(3) spin chain. Finally we show how a method similar to the Bethe ansatz works in a completely different setting, namely for the 1D oscillator in quantum mechanics.

Long charged macromolecule in an entropic trap with rough surfaces.

PubMed

Mamasakhlisov, Yevgeni Sh; Hayryan, Shura; Hu, Chin-Kun

2012-11-01

The kinetics of the flux of a charged macromolecular solution through an environment of changing geometry with wide and constricted regions is investigated analytically. A model device consisting of alternating deep and shallow slits known as an "entropic trap" is used to represent the environment. The flux is supported by the external electrostatic field. The "wormlike chain" model is used for the macromolecule (dsDNA in the present study). The chain entropy in both the deep and the shallow slits, the work by the electric field, and the energy of the elastic bending of the chain are taken into account accurately. Based on the calculated free energy, the kinetics and the scaling behavior of the chain escaping from the entropic trap are studied. We find that the escape process occurs in two kinetic stages with different time scales and discuss the possible influence of the surface roughness. The scope of the accuracy of the proposed model is discussed.

Automated main-chain model building by template matching and iterative fragment extension.

PubMed

Terwilliger, Thomas C

2003-01-01

An algorithm for the automated macromolecular model building of polypeptide backbones is described. The procedure is hierarchical. In the initial stages, many overlapping polypeptide fragments are built. In subsequent stages, the fragments are extended and then connected. Identification of the locations of helical and beta-strand regions is carried out by FFT-based template matching. Fragment libraries of helices and beta-strands from refined protein structures are then positioned at the potential locations of helices and strands and the longest segments that fit the electron-density map are chosen. The helices and strands are then extended using fragment libraries consisting of sequences three amino acids long derived from refined protein structures. The resulting segments of polypeptide chain are then connected by choosing those which overlap at two or more C(alpha) positions. The fully automated procedure has been implemented in RESOLVE and is capable of model building at resolutions as low as 3.5 A. The algorithm is useful for building a preliminary main-chain model that can serve as a basis for refinement and side-chain addition.

Ultrafast exciton migration in an HJ-aggregate: Potential surfaces and quantum dynamics

NASA Astrophysics Data System (ADS)

Binder, Robert; Polkehn, Matthias; Ma, Tianji; Burghardt, Irene

2017-01-01

Quantum dynamical and electronic structure calculations are combined to investigate the mechanism of exciton migration in an oligothiophene HJ aggregate, i.e., a combination of oligomer chains (J-type aggregates) and stacked aggregates of such chains (H-type aggregates). To this end, a Frenkel exciton model is parametrized by a recently introduced procedure [Binder et al., J. Chem. Phys. 141, 014101 (2014)] which uses oligomer excited-state calculations to perform an exact, point-wise mapping of coupled potential energy surfaces to an effective Frenkel model. Based upon this parametrization, the Multi-Layer Multi-Configuration Time-Dependent Hartree (ML-MCTDH) method is employed to investigate ultrafast dynamics of exciton transfer in a small, asymmetric HJ aggregate model composed of 30 sites and 30 active modes. For a partially delocalized initial condition, it is shown that a torsional defect confines the trapped initial exciton, and planarization induces an ultrafast resonant transition between an HJ-aggregated segment and a covalently bound "dangling chain" end. This model is a minimal realization of experimentally investigated mixed systems exhibiting ultrafast exciton transfer between aggregated, highly planarized chains and neighboring disordered segments.

Precise side-chain conformation analysis of L-phenylalanine in α-helical polypeptide by quantum-chemical calculation and 13C CP-MAS NMR measurement

NASA Astrophysics Data System (ADS)

Niimura, Subaru; Suzuki, Junya; Kurosu, Hiromichi; Yamanobe, Takeshi; Shoji, Akira

2010-04-01

To clarify the positive role of side-chain conformation in the stability of protein secondary structure (main-chain conformation), we successfully calculated the optimization structure of a well-defined α-helical octadecapeptide composed of L-alanine (Ala) and L-phenylalanine (Phe) residues, H-(Ala) 8-Phe-(Ala) 9-OH, based on the molecular orbital calculation with density functional theory (DFT/B3LYP/6-31G(d)). From the total energy and the precise secondary structural parameters such as main-chain dihedral angles and hydrogen-bond parameters of the optimized structure, we confirmed that the conformational stability of an α-helix is affected dominantly by the side-chain conformation ( χ1) of the Phe residue in this system: model A ( T form: around 180° of χ1) is most stable in α-helix and model B ( G + form: around -60° of χ1) is next stable, but model C ( G - form: around 60° of χ1) is less stable. In addition, we demonstrate that the stable conformation of poly( L-phenylalanine) is an α-helix with the side-chain T form, by comparison of the carbonyl 13C chemical shift measured by 13C CP-MAS NMR and the calculated one.

Structure of flexible and semiflexible polyelectrolyte chains in confined spaces of slit micro/nanochannels.

PubMed

Jeon, Jonggu; Chun, Myung-Suk

2007-04-21

Understanding the behavior of a polyelectrolyte in confined spaces has direct relevance in design and manipulation of microfluidic devices, as well as transport in living organisms. In this paper, a coarse-grained model of anionic semiflexible polyelectrolyte is applied, and its structure and dynamics are fully examined with Brownian dynamics (BD) simulations both in bulk solution and under confinement between two negatively charged parallel plates. The modeling is based on the nonlinear bead-spring discretization of a continuous chain with additional long-range electrostatic, Lennard-Jones, and hydrodynamic interactions between pairs of beads. The authors also consider the steric and electrostatic interactions between the bead and the confining wall. Relevant model parameters are determined from experimental rheology data on the anionic polysaccharide xanthan reported previously. For comparison, both flexible and semiflexible models are developed accompanying zero and finite intrinsic persistence lengths, respectively. The conformational changes of the polyelectrolyte chain induced by confinements and their dependence on the screening effect of the electrolyte solution are faithfully characterized with BD simulations. Depending on the intrinsic rigidity and the medium ionic strength, the polyelectrolyte can be classified as flexible, semiflexible, or rigid. Confined flexible and semiflexible chains exhibit a nonmonotonic variation in size, as measured by the radius of gyration and end-to-end distance, with changing slit width. For the semiflexible chain, this is coupled to the variations in long-range bond vector correlation. The rigid chain, realized at low ionic strength, does not have minima in size but exhibits a sigmoidal transition. The size of confined semiflexible and rigid polyelectrolytes can be well described by the wormlike chain model once the electrostatic effects are taken into account by the persistence length measured at long length scale.

The knowledge-value chain: A conceptual framework for knowledge translation in health.

PubMed

Landry, Réjean; Amara, Nabil; Pablos-Mendes, Ariel; Shademani, Ramesh; Gold, Irving

2006-08-01

This article briefly discusses knowledge translation and lists the problems associated with it. Then it uses knowledge-management literature to develop and propose a knowledge-value chain framework in order to provide an integrated conceptual model of knowledge management and application in public health organizations. The knowledge-value chain is a non-linear concept and is based on the management of five dyadic capabilities: mapping and acquisition, creation and destruction, integration and sharing/transfer, replication and protection, and performance and innovation.

The knowledge-value chain: A conceptual framework for knowledge translation in health.

PubMed Central

Landry, Réjean; Amara, Nabil; Pablos-Mendes, Ariel; Shademani, Ramesh; Gold, Irving

2006-01-01

This article briefly discusses knowledge translation and lists the problems associated with it. Then it uses knowledge-management literature to develop and propose a knowledge-value chain framework in order to provide an integrated conceptual model of knowledge management and application in public health organizations. The knowledge-value chain is a non-linear concept and is based on the management of five dyadic capabilities: mapping and acquisition, creation and destruction, integration and sharing/transfer, replication and protection, and performance and innovation. PMID:16917645

Spectrum, symmetries, and dynamics of Heisenberg spin-1/2 chains

NASA Astrophysics Data System (ADS)

Joel, Kira; Kollmar, Davida; Santos, Lea

2013-03-01

Quantum spin chains are prototype quantum many-body systems. They are employed in the description of various complex physical phenomena. Here we provide an introduction to the subject by focusing on the time evolution of Heisenberg spin-1/2 chains with couplings between nearest-neighbor sites only. We study how the anisotropy parameter and the symmetries of the model affect its time evolution. Our predictions are based on the analysis of the eigenvalues and eigenstates of the system and then confirmed with actual numerical results.

Z n clock models and chains of so(n)2 non-Abelian anyons: symmetries, integrable points and low energy properties

NASA Astrophysics Data System (ADS)

Finch, Peter E.; Flohr, Michael; Frahm, Holger

2018-02-01

We study two families of quantum models which have been used previously to investigate the effect of topological symmetries in one-dimensional correlated matter. Various striking similarities are observed between certain {Z}n quantum clock models, spin chains generalizing the Ising model, and chains of non-Abelian anyons constructed from the so(n)2 fusion category for odd n, both subject to periodic boundary conditions. In spite of the differences between these two types of quantum chains, e.g. their Hilbert spaces being spanned by tensor products of local spin states or fusion paths of anyons, the symmetries of the lattice models are shown to be closely related. Furthermore, under a suitable mapping between the parameters describing the interaction between spins and anyons the respective Hamiltonians share part of their energy spectrum (although their degeneracies may differ). This spin-anyon correspondence can be extended by fine-tuning of the coupling constants leading to exactly solvable models. We show that the algebraic structures underlying the integrability of the clock models and the anyon chain are the same. For n  =  3,5,7 we perform an extensive finite size study—both numerical and based on the exact solution—of these models to map out their ground state phase diagram and to identify the effective field theories describing their low energy behaviour. We observe that the continuum limit at the integrable points can be described by rational conformal field theories with extended symmetry algebras which can be related to the discrete ones of the lattice models.

Biofuel supply chain, market, and policy analysis

NASA Astrophysics Data System (ADS)

Zhang, Leilei

Renewable fuel is receiving an increasing attention as a substitute for fossil based energy. The US Department of Energy (DOE) has employed increasing effort on promoting the advanced biofuel productions. Although the advanced biofuel remains at its early stage, it is expected to play an important role in climate policy in the future in the transportation sector. This dissertation studies the emerging biofuel supply chain and markets by analyzing the production cost, and the outcomes of the biofuel market, including blended fuel market price and quantity, biofuel contract price and quantity, profitability of each stakeholder (farmers, biofuel producers, biofuel blenders) in the market. I also address government policy impacts on the emerging biofuel market. The dissertation is composed with three parts, each in a paper format. The first part studies the supply chain of emerging biofuel industry. Two optimization-based models are built to determine the number of facilities to deploy, facility locations, facility capacities, and operational planning within facilities. Cost analyses have been conducted under a variety of biofuel demand scenarios. It is my intention that this model will shed light on biofuel supply chain design considering operational planning under uncertain demand situations. The second part of the dissertation work focuses on analyzing the interaction between the key stakeholders along the supply chain. A bottom-up equilibrium model is built for the emerging biofuel market to study the competition in the advanced biofuel market, explicitly formulating the interactions between farmers, biofuel producers, blenders, and consumers. The model simulates the profit maximization of multiple market entities by incorporating their competitive decisions in farmers' land allocation, biomass transportation, biofuel production, and biofuel blending. As such, the equilibrium model is capable of and appropriate for policy analysis, especially for those policies that have complex ramifications and result in sophisticate interactions among multiple stakeholders. The third part of the dissertation investigates the impacts of flexible fuel vehicles (FFVs) market penetration levels on the market outcomes, including cellulosic biofuel production and price, blended fuel market price, and profitability of each stakeholder in the biofuel supply chain for imperfectly competitive biofuel markets. In this paper, I investigate the penetration levels of FFVs by incorporating the substitution among different fuels in blended fuel demand functions through "cross price elasticity" in a bottom-up equilibrium model framework. The complementarity based problem is solved by a Taylor expansion-based iterative procedure. At each step of the iteration, the highly nonlinear complementarity problems with constant elasticity of demand functions are linearized into linear complimentarity problems and solved until it converges. This model can be applied to investigate the interaction between the stakeholders in the biofuel market, and to assist decision making for both cellulosic biofuel investors and government.

Shadowing of non-transversal heteroclinic chains

NASA Astrophysics Data System (ADS)

Delshams, Amadeu; Simon, Adrià; Zgliczyński, Piotr

2018-03-01

We present a new result about the shadowing of non-transversal chain of heteroclinic connections based on the idea of dropping dimensions. We illustrate this new mechanism with several examples. As an application we discuss this mechanism in a simplification of a toy model system derived by Colliander et al. in the context of cubic defocusing nonlinear Schrödinger equation.

A fuzzy MICMAC analysis for improving supply chain performance of basic vaccines in developing countries.

PubMed

Chandra, Dheeraj; Kumar, Dinesh

2018-03-01

In recent years, demand to improve child immunization coverage globally, and the development of the latest vaccines and technology has made the vaccine market very complex. The rise in such complexities often gives birth to numerous issues in the vaccine supply chain, which are the primary cause of its poor performance. Figuring out the cause of the performance problem can help you decide how to address it. The goal of the present study is to identify and analyze important issues in the supply chain of basic vaccines required for child immunization in the developing countries. Twenty-five key issues as various factors of the vaccine supply chain have been presented in this paper. Fuzzy MICMAC analysis has been carried out to classify the factors based on their driving and dependence power and to develop a hierarchy based model. Further, the findings have been discussed with the field experts to identify the critical factors. Three factors: better demand forecast, communication between the supply chain members, and proper planning and scheduling have been identified as the critical factors of vaccine supply chain. These factors should be given special care to improve vaccine supply chain performance.

Cost-effectiveness analysis of an early-initiated, continuous chain of rehabilitation after severe traumatic brain injury.

PubMed

Andelic, Nada; Ye, Jiajia; Tornas, Sveinung; Roe, Cecilie; Lu, Juan; Bautz-Holter, Erik; Moger, Tron; Sigurdardottir, Solrun; Schanke, Anne-Kristine; Aas, Eline

2014-07-15

The aim of this study is to estimate the long-term cost-effectiveness of two different rehabilitation trajectories after severe traumatic brain injury (sTBI). A decision tree model compared hospitalization costs, health effects, and incremental cost-effectiveness ratios (ICER) of a continuous chain versus a broken chain of rehabilitation. The expected costs were estimated by the reimbursement system using diagnosis-related group and based on point estimates of the Disability Rating Scale (DRS); the health effects were measured by means of area under the curve (AUC). The incremental health benefit was estimated as the difference in the AUCs between the chains. Lower values on the DRS scale indicate better health; thus, smaller AUCs were preferred. The modeled population was a cohort of 59 patients with sTBI (30 in continuous chain; 29 in broken chain) with 6-weeks, 1-year, and 5-year post-injury follow-ups. Regarding the DRS estimates, 5-year AUCs were 19.40 (continuous chain) and 23.46 (broken chain). Across 5 years, the continuous chain of rehabilitation had lower costs and better health effects. By replacing the broken chain with the continuous chain, NOK 37.000 could be saved and 4.06 DRS points gained. By means of probabilistic sensitivity analysis, the majority of ICER estimates (67% of the Monte Carlo simulations) indicated that a continuous chain of rehabilitation was less costly and more effective. These findings indicate that the trajectory of continuous rehabilitation represents a dominant strategy in that it reduces costs and improves outcomes after sTBI under reasonable assumptions.

Voltage dependency of transmission probability of aperiodic DNA molecule

NASA Astrophysics Data System (ADS)

Wiliyanti, V.; Yudiarsah, E.

2017-07-01

Characteristics of electron transports in aperiodic DNA molecules have been studied. Double stranded DNA model with the sequences of bases, GCTAGTACGTGACGTAGCTAGGATATGCCTGA, in one chain and its complements on the other chains has been used. Tight binding Hamiltonian is used to model DNA molecules. In the model, we consider that on-site energy of the basis has a linearly dependency on the applied electric field. Slater-Koster scheme is used to model electron hopping constant between bases. The transmission probability of electron from one electrode to the next electrode is calculated using a transfer matrix technique and scattering matrix method simultaneously. The results show that, generally, higher voltage gives a slightly larger value of the transmission probability. The applied voltage seems to shift extended states to lower energy. Meanwhile, the value of the transmission increases with twisting motion frequency increment.

Process modeling and supply chain design for advanced biofuel production based on bio-oil gasification

NASA Astrophysics Data System (ADS)

Li, Qi

As a potential substitute for petroleum-based fuel, second generation biofuels are playing an increasingly important role due to their economic, environmental, and social benefits. With the rapid development of biofuel industry, there has been an increasing literature on the techno-economic analysis and supply chain design for biofuel production based on a variety of production pathways. A recently proposed production pathway of advanced biofuel is to convert biomass to bio-oil at widely distributed small-scale fast pyrolysis plants, then gasify the bio-oil to syngas and upgrade the syngas to transportation fuels in centralized biorefinery. This thesis aims to investigate two types of assessments on this bio-oil gasification pathway: techno-economic analysis based on process modeling and literature data; supply chain design with a focus on optimal decisions for number of facilities to build, facility capacities and logistic decisions considering uncertainties. A detailed process modeling with corn stover as feedstock and liquid fuels as the final products is presented. Techno-economic analysis of the bio-oil gasification pathway is also discussed to assess the economic feasibility. Some preliminary results show a capital investment of 438 million dollar and minimum fuel selling price (MSP) of $5.6 per gallon of gasoline equivalent. The sensitivity analysis finds that MSP is most sensitive to internal rate of return (IRR), biomass feedstock cost, and fixed capital cost. A two-stage stochastic programming is formulated to solve the supply chain design problem considering uncertainties in biomass availability, technology advancement, and biofuel price. The first-stage makes the capital investment decisions including the locations and capacities of the decentralized fast pyrolysis plants and the centralized biorefinery while the second-stage determines the biomass and biofuel flows. The numerical results and case study illustrate that considering uncertainties can be pivotal in this supply chain design and optimization problem. Also, farmers' participation has a significant effect on the decision making process.

FTIR spectroscopic characterization of polyurethane-urea model hard segments (PUUMHS) based on three diamine chain extenders

NASA Astrophysics Data System (ADS)

Zhang, Shijie; Ren, Zhiyong; He, Suqing; Zhu, Yan; Zhu, Chengshen

2007-01-01

Six polyurethane-urea model hard segments (PUUMHS) were prepared by a solution method based, respectively, on two isocyanates: 4,4'-methylene-diphenyl-diisocyanate (MDI), 4,4'-methylene-dicyclohexyl diisocyanate (HMDI) and three amine chain extenders: ethylene diamine (EDA), methylene-bis-ortho-chloroaniline (MOCA), 2,4-diamino-3,5-dimethylsuphylchlorobenzene (DDSCB). FTIR was used to study their spectroscopic characterization. The main FTIR bands of the six samples were assigned and compared. It was found that most of N-H and C dbnd O are H-bonded in these PUUMHS. However, the N-H in three MDI based PUUMHS is all in the stronger H-bond state than that in their corresponding HMDI based while the C dbnd O in three HMDI based PUUMHS is all in the stronger H-bond state than that in their corresponding MDI based, respectively. In addition, the order of the H-bond strength in HMDI based PUUMHS is MOCA, DDSCB and EDA whether according to νN sbnd H or νC dbnd O band wavenumbers, which is, however, different from that in MDI based PUUMHS. Moreover, the HMDI based PUUMHS shows obvious double amide III bands while the MDI based has only prominent one. The results are discussed according mainly to the different characteristics of the three chain extenders as well as the structure difference between MDI and HMDI.

A manufacturing quality assessment model based-on two stages interval type-2 fuzzy logic

NASA Astrophysics Data System (ADS)

Purnomo, Muhammad Ridwan Andi; Helmi Shintya Dewi, Intan

2016-01-01

This paper presents the development of an assessment models for manufacturing quality using Interval Type-2 Fuzzy Logic (IT2-FL). The proposed model is developed based on one of building block in sustainable supply chain management (SSCM), which is benefit of SCM, and focuses more on quality. The proposed model can be used to predict the quality level of production chain in a company. The quality of production will affect to the quality of product. Practically, quality of production is unique for every type of production system. Hence, experts opinion will play major role in developing the assessment model. The model will become more complicated when the data contains ambiguity and uncertainty. In this study, IT2-FL is used to model the ambiguity and uncertainty. A case study taken from a company in Yogyakarta shows that the proposed manufacturing quality assessment model can work well in determining the quality level of production.

What are we missing? Scope 3 greenhouse gas emissions accounting in the metals and minerals industry

NASA Astrophysics Data System (ADS)

Greene, Suzanne E.

2018-05-01

Metal and mineral companies have significant greenhouse gas emissions in their upstream and downstream value chains due to outsourced extraction, beneficiation and transportation activities, depending on a firm's business model. While many companies move towards more transparent reporting of corporate greenhouse gas emissions, value chain emissions remain difficult to capture, particularly in the global supply chain. Incomplete reports make it difficult for companies to track emissions reductions goals or implement sustainable supply chain improvements, especially for commodity products that form the base of many other sector's value chains. Using voluntarily-reported CDP data, this paper sheds light on hotspots in value chain emissions for individual metal and mineral companies, and for the sector as a whole. The state of value chain emissions reporting for the industry is discussed in general, with a focus on where emissions could potentially be underestimated and how estimates could be improved.

Degree of polymerization of glucan chains shapes the structure fluctuations and melting thermodynamics of a cellulose microfibril.

PubMed

Chang, Rakwoo; Gross, Adam S; Chu, Jhih-Wei

2012-07-19

A Staggered LATtice (SLAT) model is developed for modeling cellulose microfibrils. The simple representation of molecular packing and interactions employed in SLAT allows simulations of structure fluctuations and phase transition of cellulose microfibrils at sufficiently long and large scales for comparison with experiments. Glucan chains in the microfibril are modeled as connected monomers, each corresponding to a cellobiose subunit, and the surrounding space around the cellulose is composed of solvent cells. Interaction parameters of monomer-monomer interactions were parametrized based on the results of atomistic molecular dynamics simulations. The monomer-solvent interaction was optimized to give a melting temperature of ∼695 K for the 36-glucan chain model cellulose microfibril, which is consistent with the estimation based on experimental data. Monte Carlo simulations of the SLAT model also capture experimentally measured X-ray diffraction patterns of cellulose as a function of temperature, including the region of melting transition, as well as predict the highly flexible regions in the microfibril. Beyond the diameter of ∼3 nm, we found that melting temperature of the cellulose microfibril is not significantly shifted by changing the thickness. On the other hand, a slight decrease in the degree of polymerization of glucan chains is shown to enhance structure fluctuations through the ends of glucan chains, i.e., the defect sites, and thereby significantly reduce the melting temperature. Analysis of the sizes, densities, and lifetimes of defect structures in the microfibril indicates a significant extent of fluctuations on the surfaces even at room temperature and that defect statistics are strong but distinct functions of temperature and solvent quality. The SLAT model is the first of its kind for simulating cellulosic materials, and this work shows that it can be used to incorporate information obtained from atomistic simulations and experimental data to enable the aforementioned findings through computation.

Developing strategic planning of green supply chain in refinery CPO company

NASA Astrophysics Data System (ADS)

Hidayati, J.; Mumtaz, G.; Hasibuan, S.

2018-02-01

We are conducted a research at the company of the manufacturing CPO into cooking oil, margarine and materials of oleochemical industries. Today palm oil based industries are facing global challenges related to environmental issues. To against these challenges, it is necessary to have an environmentally friendly supply chain. However, the limited resource owned by the company requires the integrated environmental strategy with the company’s business strategy. The model is developed based on management orientation towards external pressure, internal key resources and competitive advantage that can be obtained as the decision factor. The decision-making method used is Analytical Network Process (ANP). The results obtained institutional pressure becomes the criterion with the greatest influence on green supply chain initiatives and sub criteria of customer desires and stakeholder integration having the most significant influence on green supply chain initiatives. There are five green alternative initiatives that can be done: green product design, greening upstream, greening production, greening downstream and greening post use. For green supply chain initiative, greening upstream is the best priority.

Distribution of Base Pair Alternations in a Periodic DNA Chain: Application of Pólya Counting to a Physical System

NASA Astrophysics Data System (ADS)

Hillebrand, Malcolm; Paterson-Jones, Guy; Kalosakas, George; Skokos, Charalampos

2018-03-01

In modeling DNA chains, the number of alternations between Adenine-Thymine (AT) and Guanine-Cytosine (GC) base pairs can be considered as a measure of the heterogeneity of the chain, which in turn could affect its dynamics. A probability distribution function of the number of these alternations is derived for circular or periodic DNA. Since there are several symmetries to account for in the periodic chain, necklace counting methods are used. In particular, Polya's Enumeration Theorem is extended for the case of a group action that preserves partitioned necklaces. This, along with the treatment of generating functions as formal power series, allows for the direct calculation of the number of possible necklaces with a given number of AT base pairs, GC base pairs and alternations. The theoretically obtained probability distribution functions of the number of alternations are accurately reproduced by Monte Carlo simulations and fitted by Gaussians. The effect of the number of base pairs on the characteristics of these distributions is also discussed, as well as the effect of the ratios of the numbers of AT and GC base pairs.

A methodology and supply chain management inspired reference ontology for modeling healthcare teams.

PubMed

Kuziemsky, Craig E; Yazdi, Sara

2011-01-01

Numerous studies and strategic plans are advocating more team based healthcare delivery that is facilitated by information and communication technologies (ICTs). However before we can design ICTs to support teams we need a solid conceptual model of team processes and a methodology for using such a model in healthcare settings. This paper draws upon success in the supply chain management domain to develop a reference ontology of healthcare teams and a methodology for modeling teams to instantiate the ontology in specific settings. This research can help us understand how teams function and how we can design ICTs to support teams.

Fibroblast Growth Factor-based Signaling through Synthetic Heparan Sulfate Blocks Copolymers Studied Using High Cell Density Three-dimensional Cell Printing*

PubMed Central

Sterner, Eric; Masuko, Sayaka; Li, Guoyun; Li, Lingyun; Green, Dixy E.; Otto, Nigel J.; Xu, Yongmei; DeAngelis, Paul L.; Liu, Jian; Dordick, Jonathan S.; Linhardt, Robert J.

2014-01-01

Four well-defined heparan sulfate (HS) block copolymers containing S-domains (high sulfo group content) placed adjacent to N-domains (low sulfo group content) were chemoenzymatically synthesized and characterized. The domain lengths in these HS block co-polymers were ∼40 saccharide units. Microtiter 96-well and three-dimensional cell-based microarray assays utilizing murine immortalized bone marrow (BaF3) cells were developed to evaluate the activity of these HS block co-polymers. Each recombinant BaF3 cell line expresses only a single type of fibroblast growth factor receptor (FGFR) but produces neither HS nor fibroblast growth factors (FGFs). In the presence of different FGFs, BaF3 cell proliferation showed clear differences for the four HS block co-polymers examined. These data were used to examine the two proposed signaling models, the symmetric FGF2-HS2-FGFR2 ternary complex model and the asymmetric FGF2-HS1-FGFR2 ternary complex model. In the symmetric FGF2-HS2-FGFR2 model, two acidic HS chains bind in a basic canyon located on the top face of the FGF2-FGFR2 protein complex. In this model the S-domains at the non-reducing ends of the two HS proteoglycan chains are proposed to interact with the FGF2-FGFR2 protein complex. In contrast, in the asymmetric FGF2-HS1-FGFR2 model, a single HS chain interacts with the FGF2-FGFR2 protein complex through a single S-domain that can be located at any position within an HS chain. Our data comparing a series of synthetically prepared HS block copolymers support a preference for the symmetric FGF2-HS2-FGFR2 ternary complex model. PMID:24563485

Polymer-induced forces at interfaces

NASA Astrophysics Data System (ADS)

Rangarajan, Murali

This dissertation concerns studies of forces generated by confined and physisorbed flexible polymers using lattice mean-field theories, and those generated by confined and clamped semiflexible polymers modeled as slender elastic rods. Lattice mean-field theories have been used in understanding and predicting the behavior of polymeric interfacial systems. In order to efficiently tailor such systems for various applications of interest, one has to understand the forces generated in the interface due to the polymer molecules. The present work examines the abilities and limitations of lattice mean-field theories in predicting the structure of physisorbed polymer layers and the resultant forces. Within the lattice mean-field theory, a definition of normal force of compression as the negative derivative of the partition-function-based excess free energy with surface separation gives misleading results because the theory does not explicitly account for the normal stresses involved in the system. Correct expressions for normal and tangential forces are obtained from a continuum-mechanics-based formulation. Preliminary comparisons with lattice Monte Carlo simulations show that mean-field theories fail to predict significant attractive forces when the surfaces are undersaturated, as one would expect. The corrections to the excluded volume (non-reversal chains) and the mean-field (anisotropic field) approximations improve the predictions of layer structure, but not the forces. Bending of semiflexible polymer chains (elastic rods) is considered for two boundary conditions---where the chain is hinged on both ends and where the chain is clamped on one end and hinged on the other. For the former case, the compressive forces and chain shapes obtained are consistent with the inflexional elastica published by Love. For the latter, multiple and higher-order solutions are observed for the hinged-end position for a given force. Preliminary studies are conducted on actin-based motility of Listeria monocytogenes by treating actin filaments as elastic rods, using the actoclampin model. The results show qualitative agreement with calculations where the filaments are modeled as Hookean springs. The feasibility of the actoclampin model to address long length-scale rotation of Listeria during actin-based motility is addressed.

Bayesian seismic tomography by parallel interacting Markov chains

NASA Astrophysics Data System (ADS)

Gesret, Alexandrine; Bottero, Alexis; Romary, Thomas; Noble, Mark; Desassis, Nicolas

2014-05-01

The velocity field estimated by first arrival traveltime tomography is commonly used as a starting point for further seismological, mineralogical, tectonic or similar analysis. In order to interpret quantitatively the results, the tomography uncertainty values as well as their spatial distribution are required. The estimated velocity model is obtained through inverse modeling by minimizing an objective function that compares observed and computed traveltimes. This step is often performed by gradient-based optimization algorithms. The major drawback of such local optimization schemes, beyond the possibility of being trapped in a local minimum, is that they do not account for the multiple possible solutions of the inverse problem. They are therefore unable to assess the uncertainties linked to the solution. Within a Bayesian (probabilistic) framework, solving the tomography inverse problem aims at estimating the posterior probability density function of velocity model using a global sampling algorithm. Markov chains Monte-Carlo (MCMC) methods are known to produce samples of virtually any distribution. In such a Bayesian inversion, the total number of simulations we can afford is highly related to the computational cost of the forward model. Although fast algorithms have been recently developed for computing first arrival traveltimes of seismic waves, the complete browsing of the posterior distribution of velocity model is hardly performed, especially when it is high dimensional and/or multimodal. In the latter case, the chain may even stay stuck in one of the modes. In order to improve the mixing properties of classical single MCMC, we propose to make interact several Markov chains at different temperatures. This method can make efficient use of large CPU clusters, without increasing the global computational cost with respect to classical MCMC and is therefore particularly suited for Bayesian inversion. The exchanges between the chains allow a precise sampling of the high probability zones of the model space while avoiding the chains to end stuck in a probability maximum. This approach supplies thus a robust way to analyze the tomography imaging uncertainties. The interacting MCMC approach is illustrated on two synthetic examples of tomography of calibration shots such as encountered in induced microseismic studies. On the second application, a wavelet based model parameterization is presented that allows to significantly reduce the dimension of the problem, making thus the algorithm efficient even for a complex velocity model.

Real time markerless motion tracking using linked kinematic chains

DOEpatents

Luck, Jason P [Arvada, CO; Small, Daniel E [Albuquerque, NM

2007-08-14

A markerless method is described for tracking the motion of subjects in a three dimensional environment using a model based on linked kinematic chains. The invention is suitable for tracking robotic, animal or human subjects in real-time using a single computer with inexpensive video equipment, and does not require the use of markers or specialized clothing. A simple model of rigid linked segments is constructed of the subject and tracked using three dimensional volumetric data collected by a multiple camera video imaging system. A physics based method is then used to compute forces to align the model with subsequent volumetric data sets in real-time. The method is able to handle occlusion of segments and accommodates joint limits, velocity constraints, and collision constraints and provides for error recovery. The method further provides for elimination of singularities in Jacobian based calculations, which has been problematic in alternative methods.

Solution-Phase Conformation and Dynamics of Conjugated Isoindigo-Based Donor–Acceptor Polymer Single Chains

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Franklin L.; Farimani, Amir Barati; Gu, Kevin L.

Conjugated polymers are the key material in thin-film organic optoelectronic devices due to the versatility of these molecules combined with their semiconducting properties. A molecular-scale understanding of conjugated polymers is important to the optimization of the thin-film morphology. We examine the solution-phase behavior of conjugated isoindigo-based donor–acceptor polymer single chains of various chain lengths using atomistic molecular dynamics simulations. Our simulations elucidate the transition from a rod-like to a coil-like conformation from an analysis of normal modes and persistence length. In addition, we find another transition based on the solvent environment, contrasting the coil-like conformation in a good solvent withmore » a globule-like conformation in a poor solvent. Altogether, our results provide valuable insights into the transition between conformational regimes for conjugated polymers as a function of both the chain length and the solvent environment, which will help to accurately parametrize higher level models.« less

Solution-Phase Conformation and Dynamics of Conjugated Isoindigo-Based Donor–Acceptor Polymer Single Chains

DOE PAGES

Lee, Franklin L.; Farimani, Amir Barati; Gu, Kevin L.; ...

2017-10-25

Conjugated polymers are the key material in thin-film organic optoelectronic devices due to the versatility of these molecules combined with their semiconducting properties. A molecular-scale understanding of conjugated polymers is important to the optimization of the thin-film morphology. We examine the solution-phase behavior of conjugated isoindigo-based donor–acceptor polymer single chains of various chain lengths using atomistic molecular dynamics simulations. Our simulations elucidate the transition from a rod-like to a coil-like conformation from an analysis of normal modes and persistence length. In addition, we find another transition based on the solvent environment, contrasting the coil-like conformation in a good solvent withmore » a globule-like conformation in a poor solvent. Altogether, our results provide valuable insights into the transition between conformational regimes for conjugated polymers as a function of both the chain length and the solvent environment, which will help to accurately parametrize higher level models.« less

The Complex Economic System of Supply Chain Financing

NASA Astrophysics Data System (ADS)

Zhang, Lili; Yan, Guangle

Supply Chain Financing (SCF) refers to a series of innovative and complicated financial services based on supply chain. The SCF set-up is a complex system, where the supply chain management and Small and Medium Enterprises (SMEs) financing services interpenetrate systematically. This paper establishes the organization structure of SCF System, and presents two financing models respectively, with or without the participation of the third-party logistic provider (3PL). Using Information Economics and Game Theory, the interrelationship among diverse economic sectors is analyzed, and the economic mechanism of development and existent for SCF system is demonstrated. New thoughts and approaches to solve SMEs financing problem are given.

Bushes of vibrational modes for Fermi-Pasta-Ulam chains

NASA Astrophysics Data System (ADS)

Chechin, G. M.; Novikova, N. V.; Abramenko, A. A.

2002-06-01

Some exact solutions and multimode invariant submanifolds were found for the Fermi-Pasta-Ulam (FPU)- β model by Poggi and Ruffo [Physica D 103 (1997) 251]. In the present paper we demonstrate how results of such a type can be obtained for an arbitraryN-particle chain with periodic boundary conditions with the aid of our group-theoretical approach [Physica D 117 (1998) 43] based on the concept of bushes of normal modes in mechanical systems with discrete symmetry. The integro-differential equation describing the FPU- α dynamics in the modal space is derived. The loss of stability of the bushes of modes for the FPU- α model, in particular, for the limiting case N→∞ for the dynamical regime with displacement pattern having period twice the lattice spacing ( π-mode) is studied. Our results for the FPU- α chain are compared with those by Poggi and Ruffo for the FPU- β chain.

Testing for context-dependence in a processing chain interaction among detritus-feeding aquatic insects

PubMed Central

DAUGHERTY, MATTHEW P.; JULIANO, STEVEN A.

2008-01-01

Scirtid beetles may benefit mosquitoes Ochlerotatus triseriatus (Say) by consuming whole leaves and leaving behind fine particles required by mosquito larvae. Such interactions based on the sequential use of a resource that occurs in multiple forms are known as processing chains.Models of processing chains predict that interactions can vary from commensal (0, +) to amensal (0, −), depending on how quickly resource is processed in the absence of consumers.The scirtid-O. triseriatus system was used to test the prediction derived from processing chain models that, as consumer-independent processing increases, scirtids benefit mosquitoes less. Consumer-independent processing rate was manipulated by using different leaf species that vary in decay rate, or by physically crushing a single leaf type to different degrees.Although scirtids increased the production of fine particles, the effects of scirtids on mosquitoes were weak and were not dependent on consumer-independent processing rate.In the leaf manipulation experiment, a correlation between scirtid feeding and consumer-independent processing was detected. Numerical simulations suggest that such a correlation may eliminate shifts from commensal to amensal at equilibrium; because mosquito populations are typically not at equilibrium, however, this correlation may not be important.There was evidence that mosquitoes affected scirtids negatively, which is inconsistent with the structure of processing chain interactions in models. Processing chain models need to incorporate more detail on the biology of scirtids and O. triseriatus, especially alternative mechanisms of interaction, if they are to describe scirtid-O. triseriatus dynamics accurately. PMID:19060960

Fitmunk: improving protein structures by accurate, automatic modeling of side-chain conformations.

PubMed

Porebski, Przemyslaw Jerzy; Cymborowski, Marcin; Pasenkiewicz-Gierula, Marta; Minor, Wladek

2016-02-01

Improvements in crystallographic hardware and software have allowed automated structure-solution pipelines to approach a near-`one-click' experience for the initial determination of macromolecular structures. However, in many cases the resulting initial model requires a laborious, iterative process of refinement and validation. A new method has been developed for the automatic modeling of side-chain conformations that takes advantage of rotamer-prediction methods in a crystallographic context. The algorithm, which is based on deterministic dead-end elimination (DEE) theory, uses new dense conformer libraries and a hybrid energy function derived from experimental data and prior information about rotamer frequencies to find the optimal conformation of each side chain. In contrast to existing methods, which incorporate the electron-density term into protein-modeling frameworks, the proposed algorithm is designed to take advantage of the highly discriminatory nature of electron-density maps. This method has been implemented in the program Fitmunk, which uses extensive conformational sampling. This improves the accuracy of the modeling and makes it a versatile tool for crystallographic model building, refinement and validation. Fitmunk was extensively tested on over 115 new structures, as well as a subset of 1100 structures from the PDB. It is demonstrated that the ability of Fitmunk to model more than 95% of side chains accurately is beneficial for improving the quality of crystallographic protein models, especially at medium and low resolutions. Fitmunk can be used for model validation of existing structures and as a tool to assess whether side chains are modeled optimally or could be better fitted into electron density. Fitmunk is available as a web service at http://kniahini.med.virginia.edu/fitmunk/server/ or at http://fitmunk.bitbucket.org/.

Sequence-Based Discovery Demonstrates That Fixed Light Chain Human Transgenic Rats Produce a Diverse Repertoire of Antigen-Specific Antibodies.

PubMed

Harris, Katherine E; Aldred, Shelley Force; Davison, Laura M; Ogana, Heather Anne N; Boudreau, Andrew; Brüggemann, Marianne; Osborn, Michael; Ma, Biao; Buelow, Benjamin; Clarke, Starlynn C; Dang, Kevin H; Iyer, Suhasini; Jorgensen, Brett; Pham, Duy T; Pratap, Payal P; Rangaswamy, Udaya S; Schellenberger, Ute; van Schooten, Wim C; Ugamraj, Harshad S; Vafa, Omid; Buelow, Roland; Trinklein, Nathan D

2018-01-01

We created a novel transgenic rat that expresses human antibodies comprising a diverse repertoire of heavy chains with a single common rearranged kappa light chain (IgKV3-15-JK1). This fixed light chain animal, called OmniFlic, presents a unique system for human therapeutic antibody discovery and a model to study heavy chain repertoire diversity in the context of a constant light chain. The purpose of this study was to analyze heavy chain variable gene usage, clonotype diversity, and to describe the sequence characteristics of antigen-specific monoclonal antibodies (mAbs) isolated from immunized OmniFlic animals. Using next-generation sequencing antibody repertoire analysis, we measured heavy chain variable gene usage and the diversity of clonotypes present in the lymph node germinal centers of 75 OmniFlic rats immunized with 9 different protein antigens. Furthermore, we expressed 2,560 unique heavy chain sequences sampled from a diverse set of clonotypes as fixed light chain antibody proteins and measured their binding to antigen by ELISA. Finally, we measured patterns and overall levels of somatic hypermutation in the full B-cell repertoire and in the 2,560 mAbs tested for binding. The results demonstrate that OmniFlic animals produce an abundance of antigen-specific antibodies with heavy chain clonotype diversity that is similar to what has been described with unrestricted light chain use in mammals. In addition, we show that sequence-based discovery is a highly effective and efficient way to identify a large number of diverse monoclonal antibodies to a protein target of interest.

A mathematical/physics carbon emission reduction strategy for building supply chain network based on carbon tax policy

NASA Astrophysics Data System (ADS)

Li, Xueying; Peng, Ying; Zhang, Jing

2017-03-01

Under the background of a low carbon economy, this paper examines the impact of carbon tax policy on supply chain network emission reduction. The integer linear programming method is used to establish a supply chain network emission reduction such a model considers the cost of CO2 emissions, and analyses the impact of different carbon price on cost and carbon emissions in supply chains. The results show that the implementation of a carbon tax policy can reduce CO2 emissions in building supply chain, but the increase in carbon price does not produce a reduction effect, and may bring financial burden to the enterprise. This paper presents a reasonable carbon price range and provides decision makers with strategies towards realizing a low carbon building supply chain in an economical manner.

Discrete-Choice Modeling Of Non-Working Women’s Trip-Chaining Activity Based

NASA Astrophysics Data System (ADS)

Hayati, Amelia; Pradono; Purboyo, Heru; Maryati, Sri

2018-05-01

Start The urban developments of technology and economics are now changing the lifestyles of the urban societies. It is also changing their travel demand to meet their movement needs. Nowadays, urban women, especially in Bandung, West Java, have a high demand for their daily travel and tend to increase. They have the ease of accessibility to personal modes of transportation and freedom to go anywhere to meet their personal and family needs. This also happens to non-working women or as housewives in the city of Bandung. More than 50% of women’s mobility is outside the home, in the term of trip-chaining, from leaving to returning home in one day. It is based on their complex activities in order to meet the needs of family and home care. While less than 60% of male’s mobility is outdoors, it is a simple trip-chaining or only has a single trip. The trip-chaining has significant differences between non-working women and working-men. This illustrates the pattern of Mom and Dad’s mobility in a family with an activity-based approach for the same purpose, i.e. family welfare. This study explains how complex the trip-chaining of non-working urban women and as housewives, with an activity-based approach done outdoors in a week. Socio-economic and household demographic variables serve as the basis for measuring the independent variables affecting family welfare, as well as the variables of type, time and duration of activities performed by unemployed housewives. This study aims to examine the interrelationships between activity variables, especially the time of activity and travel, and socio-economic of household variables that can generate the complexity of women’s daily travel. Discrete Choice Modeling developed by Ben-Akiva, Chandra Bhat, etc., is used in this study to illustrate the relationship between activity and socio-economic demographic variables based on primary survey data in Bandung, West Java for 466 unemployed housewives. The results of the regression, by Seemingly Unrelated Regression approach methods, showed the interrelationship between all variables, including the complexity of trip chaining of housewives based on their daily activities. The type of mandatory and discretionary activities, and the duration of activities performed during the dismissal in the series of trip chains conducted are intended for the fulfillment of the welfare of all family member.

Structure-preserving model reduction of large-scale logistics networks. Applications for supply chains

NASA Astrophysics Data System (ADS)

Scholz-Reiter, B.; Wirth, F.; Dashkovskiy, S.; Makuschewitz, T.; Schönlein, M.; Kosmykov, M.

2011-12-01

We investigate the problem of model reduction with a view to large-scale logistics networks, specifically supply chains. Such networks are modeled by means of graphs, which describe the structure of material flow. An aim of the proposed model reduction procedure is to preserve important features within the network. As a new methodology we introduce the LogRank as a measure for the importance of locations, which is based on the structure of the flows within the network. We argue that these properties reflect relative importance of locations. Based on the LogRank we identify subgraphs of the network that can be neglected or aggregated. The effect of this is discussed for a few motifs. Using this approach we present a meta algorithm for structure-preserving model reduction that can be adapted to different mathematical modeling frameworks. The capabilities of the approach are demonstrated with a test case, where a logistics network is modeled as a Jackson network, i.e., a particular type of queueing network.

An improvement in the calculation of the efficiency of oxidative phosphorylation and rate of energy dissipation in mitochondria

NASA Astrophysics Data System (ADS)

Ghafuri, Mohazabeh; Golfar, Bahareh; Nosrati, Mohsen; Hoseinkhani, Saman

2014-12-01

The process of ATP production is one of the most vital processes in living cells which happens with a high efficiency. Thermodynamic evaluation of this process and the factors involved in oxidative phosphorylation can provide a valuable guide for increasing the energy production efficiency in research and industry. Although energy transduction has been studied qualitatively in several researches, there are only few brief reviews based on mathematical models on this subject. In our previous work, we suggested a mathematical model for ATP production based on non-equilibrium thermodynamic principles. In the present study, based on the new discoveries on the respiratory chain of animal mitochondria, Golfar's model has been used to generate improved results for the efficiency of oxidative phosphorylation and the rate of energy loss. The results calculated from the modified coefficients for the proton pumps of the respiratory chain enzymes are closer to the experimental results and validate the model.

Measurement-based quantum teleportation on finite AKLT chains

NASA Astrophysics Data System (ADS)

Fujii, Akihiko; Feder, David

In the measurement-based model of quantum computation, universal quantum operations are effected by making repeated local measurements on resource states which contain suitable entanglement. Resource states include two-dimensional cluster states and the ground state of the Affleck-Kennedy-Lieb-Tasaki (AKLT) state on the honeycomb lattice. Recent studies suggest that measurements on one-dimensional systems in the Haldane phase teleport perfect single-qubit gates in the correlation space, protected by the underlying symmetry. As laboratory realizations of symmetry-protected states will necessarily be finite, we investigate the potential for quantum gate teleportation in finite chains of a bilinear-biquadratic Hamiltonian which is a generalization of the AKLT model representing the full Haldane phase.

Expert systems for automated maintenance of a Mars oxygen production system

NASA Technical Reports Server (NTRS)

Ash, Robert L.; Huang, Jen-Kuang; Ho, Ming-Tsang

1989-01-01

A prototype expert system was developed for maintaining autonomous operation of a Mars oxygen production system. Normal operation conditions and failure modes according to certain desired criteria are tested and identified. Several schemes for failure detection and isolation using forward chaining, backward chaining, knowledge-based and rule-based are devised to perform several housekeeping functions. These functions include self-health checkout, an emergency shut down program, fault detection and conventional control activities. An effort was made to derive the dynamic model of the system using Bond-Graph technique in order to develop the model-based failure detection and isolation scheme by estimation method. Finally, computer simulations and experimental results demonstrated the feasibility of the expert system and a preliminary reliability analysis for the oxygen production system is also provided.

Evaluating the green practice of food service supply chain management based on fuzzy DEMATEL-ANP model

NASA Astrophysics Data System (ADS)

Li, Xiaoying; Zhu, Qinghua

2017-01-01

The question on how to evaluate a company's green practice has recently become a key strategic consideration for the food service supply chain management. This paper proposed a novel hybrid model that combines a fuzzy Decision Making Trial And Evaluation Laboratory(DEMATEL) and Analysis Network Process(ANP) methods, which developed the green restaurant criteria and demonstrated the complicated relations among various criteria to help the food service operation to better analyze the real-world situation and determine the different weight value of the criteria .The analysis of the evaluation of green practices will help the food service operation to be clear about the key measures of green practice to improve supply chain management.

Derivation of stiffness matrix in constitutive modeling of magnetorheological elastomer

NASA Astrophysics Data System (ADS)

Leng, D.; Sun, L.; Sun, J.; Lin, Y.

2013-02-01

Magnetorheological elastomers (MREs) are a class of smart materials whose mechanical properties change instantly by the application of a magnetic field. Based on the specially orthotropic, transversely isotropic stress-strain relationships and effective permeability model, the stiffness matrix of constitutive equations for deformable chain-like MRE is considered. To valid the components of shear modulus in this stiffness matrix, the magnetic-structural simulations with finite element method (FEM) are presented. An acceptable agreement is illustrated between analytical equations and numerical simulations. For the specified magnetic field, sphere particle radius, distance between adjacent particles in chains and volume fractions of ferrous particles, this constitutive equation is effective to engineering application to estimate the elastic behaviour of chain-like MRE in an external magnetic field.

Towards a physics-based multiscale modelling of the electro-mechanical coupling in electro-active polymers.

PubMed

Cohen, Noy; Menzel, Andreas; deBotton, Gal

2016-02-01

Owing to the increasing number of industrial applications of electro-active polymers (EAPs), there is a growing need for electromechanical models which accurately capture their behaviour. To this end, we compare the predicted behaviour of EAPs undergoing homogeneous deformations according to three electromechanical models. The first model is a phenomenological continuum-based model composed of the mechanical Gent model and a linear relationship between the electric field and the polarization. The electrical and the mechanical responses according to the second model are based on the physical structure of the polymer chain network. The third model incorporates a neo-Hookean mechanical response and a physically motivated microstructurally based long-chains model for the electrical behaviour. In the microstructural-motivated models, the integration from the microscopic to the macroscopic levels is accomplished by the micro-sphere technique. Four types of homogeneous boundary conditions are considered and the behaviours determined according to the three models are compared. For the microstructurally motivated models, these analyses are performed and compared with the widely used phenomenological model for the first time. Some of the aspects revealed in this investigation, such as the dependence of the intensity of the polarization field on the deformation, highlight the need for an in-depth investigation of the relationships between the structure and the behaviours of the EAPs at the microscopic level and their overall macroscopic response.

Commanding an Air Force Squadron

DTIC Science & Technology

1993-12-01

I The M ission ...................................... 3 The People ...................................... 5 The Chain of Command...of Air Force squadron commanders. By so doing, it serves as an explanatory text to allied officers, as a model for leadership studies, and as a...personnel, meeting the chain of command above him, and understanding the role of other units on the base. The Mission Lt Col John Bell, chief of the wing

Evaluating Augmented Reality to Complete a Chain Task for Elementary Students with Autism

ERIC Educational Resources Information Center

Cihak, David F.; Moore, Eric J.; Wright, Rachel E.; McMahon, Don D.; Gibbons, Melinda M.; Smith, Cate

2016-01-01

The purpose of this study was to examine the effects of augmented reality to teach a chain task to three elementary-age students with autism spectrum disorders (ASDs). Augmented reality blends digital information within the real world. This study used a marker-based augmented reality picture prompt to trigger a video model clip of a student…

Share2Quit: Web-Based Peer-Driven Referrals for Smoking Cessation

PubMed Central

2013-01-01

Background Smoking is the number one preventable cause of death in the United States. Effective Web-assisted tobacco interventions are often underutilized and require new and innovative engagement approaches. Web-based peer-driven chain referrals successfully used outside health care have the potential for increasing the reach of Internet interventions. Objective The objective of our study was to describe the protocol for the development and testing of proactive Web-based chain-referral tools for increasing the access to Decide2Quit.org, a Web-assisted tobacco intervention system. Methods We will build and refine proactive chain-referral tools, including email and Facebook referrals. In addition, we will implement respondent-driven sampling (RDS), a controlled chain-referral sampling technique designed to remove inherent biases in chain referrals and obtain a representative sample. We will begin our chain referrals with an initial recruitment of former and current smokers as seeds (initial participants) who will be trained to refer current smokers from their social network using the developed tools. In turn, these newly referred smokers will also be provided the tools to refer other smokers from their social networks. We will model predictors of referral success using sample weights from the RDS to estimate the success of the system in the targeted population. Results This protocol describes the evaluation of proactive Web-based chain-referral tools, which can be used in tobacco interventions to increase the access to hard-to-reach populations, for promoting smoking cessation. Conclusions Share2Quit represents an innovative advancement by capitalizing on naturally occurring technology trends to recruit smokers to Web-assisted tobacco interventions. PMID:24067329

Quantitative microbial risk assessment for Escherichia coli O157:H7, Salmonella enterica, and Listeria monocytogenes in leafy green vegetables consumed at salad bars, based on modeling supply chain logistics.

PubMed

Tromp, S O; Rijgersberg, H; Franz, E

2010-10-01

Quantitative microbial risk assessments do not usually account for the planning and ordering mechanisms (logistics) of a food supply chain. These mechanisms and consumer demand determine the storage and delay times of products. The aim of this study was to quantitatively assess the difference between simulating supply chain logistics (MOD) and assuming fixed storage times (FIX) in microbial risk estimation for the supply chain of fresh-cut leafy green vegetables destined for working-canteen salad bars. The results of the FIX model were previously published (E. Franz, S. O. Tromp, H. Rijgersberg, and H. J. van der Fels-Klerx, J. Food Prot. 73:274-285, 2010). Pathogen growth was modeled using stochastic discrete-event simulation of the applied logistics concept. The public health effects were assessed by conducting an exposure assessment and risk characterization. The relative growths of Escherichia coli O157 (17%) and Salmonella enterica (15%) were identical in the MOD and FIX models. In contrast, the relative growth of Listeria monocytogenes was considerably higher in the MOD model (1,156%) than in the FIX model (194%). The probability of L. monocytogenes infection in The Netherlands was higher in the MOD model (5.18×10(-8)) than in the FIX model (1.23×10(-8)). The risk of listeriosis-induced fetal mortality in the perinatal population increased from 1.24×10(-4) (FIX) to 1.66×10(-4) (MOD). Modeling the probabilistic nature of supply chain logistics is of additional value for microbial risk assessments regarding psychrotrophic pathogens in food products for which time and temperature are the postharvest preventive measures in guaranteeing food safety.

Quasi-Block Copolymers Based on a General Polymeric Chain Stopper.

PubMed

Sanguramath, Rajashekharayya A; Nealey, Paul F; Shenhar, Roy

2016-07-11

Quasi-block copolymers (q-BCPs) are block copolymers consisting of conventional and supramolecular blocks, in which the conventional block is end-terminated by a functionality that interacts with the supramolecular monomer (a "chain stopper" functionality). A new design of q-BCPs based on a general polymeric chain stopper, which consists of polystyrene end-terminated with a sulfonate group (PS-SO3 Li), is described. Through viscosity measurements and a detailed diffusion-ordered NMR spectroscopy study, it is shown that PS-SO3 Li can effectively cap two types of model supramolecular monomers to form q-BCPs in solution. Furthermore, differential scanning calorimetry data and structural characterization of thin films by scanning force microscopy suggests the existence of the q-BCP architecture in the melt. The new design considerably simplifies the synthesis of polymeric chain stoppers; thus promoting the utilization of q-BCPs as smart, nanostructured materials. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Improving the leakage current of polyimide-based resistive memory by tuning the molecular chain stack of the polyimide film

NASA Astrophysics Data System (ADS)

Wu, Chi-Chang; Hsiao, Yu-Ping; You, Hsin-Chiang; Lin, Guan-Wei; Kao, Min-Fang; Manga, Yankuba B.; Yang, Wen-Luh

2018-02-01

We have developed an organic-based resistive random access memory (ReRAM) by using spin-coated polyimide (PI) as the resistive layer. In this study, the chain distance and number of chain stacks of PI molecules are investigated. We employed different solid contents of polyamic acid (PAA) to synthesize various PI films, which served as the resistive layer of ReRAM, the electrical performance of which was evaluated. By tuning the PAA solid content, the intermolecular interaction energy of the PI films is changed without altering the molecular structure. Our results show that the leakage current in the high-resistance state and the memory window of the PI-based ReRAM can be substantially improved using this technique. The superior properties of the PI-based ReRAM are ascribed to fewer molecular chain stacks in the PI films when the PAA solid content is decreased, hence suppressing the leakage current. In addition, a device retention time of more than 107 s can be achieved using this technique. Finally, the conduction mechanism in the PI-based ReRAM was analyzed using hopping and conduction models.

Soliton Analysis in Complex Molecular Systems: A Zig-Zag Chain

NASA Astrophysics Data System (ADS)

Christiansen, P. L.; Savin, A. V.; Zolotaryuk, A. V.

1997-06-01

A simple numerical method for seeking solitary wavesolutions of a permanent profile in molecular systems of big complexity is presented. The method is essentially based on the minimization of a finite-dimensional function which is chosen under an appropriate discretization of time derivatives in equations of motion. In the present paper, it is applied to a zig-zag chain backbone of coupled particles, each of which has twodegrees of freedom (longitudinal and transverse). Both topological and nontopological soliton solutions are treated for this chain when it is (i) subjected to a two-dimensional periodic substrate potential or (ii) considered as an isolated object, respectively. In the first case, which may be considered as a zig-zag generalization of the Frenkel-Kontorova chain model, two types of kink solutions with different topological charges, describing vacancies of one or two atoms (I- or II-kinks) and defects with excess one or two atoms in the chain (I- or II-antikinks), have been found. The second case (isolated chain) is a generalization of the well-known Fermi-Pasta-Ulam chain model, which takes into account transverse degrees of freedom of the chain molecules. Two types of stable nontopological soliton solutions which describe either (i) a supersonic solitary wave of longitudinal stretching accompanied by transverse slendering or (ii) supersonic pulses of longitudinal compression propagating together with localized transverse thickening (bulge) have been obtained.

Monte Carlo simulation and equation of state for flexible charged hard-sphere chain fluids: Polyampholyte and polyelectrolyte solutions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Hao; Adidharma, Hertanto, E-mail: adidharm@uwyo.edu

The thermodynamic modeling of flexible charged hard-sphere chains representing polyampholyte or polyelectrolyte molecules in solution is considered. The excess Helmholtz energy and osmotic coefficients of solutions containing short polyampholyte and the osmotic coefficients of solutions containing short polyelectrolytes are determined by performing canonical and isobaric-isothermal Monte Carlo simulations. A new equation of state based on the thermodynamic perturbation theory is also proposed for flexible charged hard-sphere chains. For the modeling of such chains, the use of solely the structure information of monomer fluid for calculating the chain contribution is found to be insufficient and more detailed structure information must thereforemore » be considered. Two approaches, i.e., the dimer and dimer-monomer approaches, are explored to obtain the contribution of the chain formation to the Helmholtz energy. By comparing with the simulation results, the equation of state with either the dimer or dimer-monomer approach accurately predicts the excess Helmholtz energy and osmotic coefficients of polyampholyte and polyelectrolyte solutions except at very low density. It also well captures the effect of temperature on the thermodynamic properties of these solutions.« less

Bayesian analysis of physiologically based toxicokinetic and toxicodynamic models.

PubMed

Hack, C Eric

2006-04-17

Physiologically based toxicokinetic (PBTK) and toxicodynamic (TD) models of bromate in animals and humans would improve our ability to accurately estimate the toxic doses in humans based on available animal studies. These mathematical models are often highly parameterized and must be calibrated in order for the model predictions of internal dose to adequately fit the experimentally measured doses. Highly parameterized models are difficult to calibrate and it is difficult to obtain accurate estimates of uncertainty or variability in model parameters with commonly used frequentist calibration methods, such as maximum likelihood estimation (MLE) or least squared error approaches. The Bayesian approach called Markov chain Monte Carlo (MCMC) analysis can be used to successfully calibrate these complex models. Prior knowledge about the biological system and associated model parameters is easily incorporated in this approach in the form of prior parameter distributions, and the distributions are refined or updated using experimental data to generate posterior distributions of parameter estimates. The goal of this paper is to give the non-mathematician a brief description of the Bayesian approach and Markov chain Monte Carlo analysis, how this technique is used in risk assessment, and the issues associated with this approach.

Multiscale approach for the construction of equilibrated all-atom models of a poly(ethylene glycol)-based hydrogel

PubMed Central

Li, Xianfeng; Murthy, N. Sanjeeva; Becker, Matthew L.; Latour, Robert A.

2016-01-01

A multiscale modeling approach is presented for the efficient construction of an equilibrated all-atom model of a cross-linked poly(ethylene glycol) (PEG)-based hydrogel using the all-atom polymer consistent force field (PCFF). The final equilibrated all-atom model was built with a systematic simulation toolset consisting of three consecutive parts: (1) building a global cross-linked PEG-chain network at experimentally determined cross-link density using an on-lattice Monte Carlo method based on the bond fluctuation model, (2) recovering the local molecular structure of the network by transitioning from the lattice model to an off-lattice coarse-grained (CG) model parameterized from PCFF, followed by equilibration using high performance molecular dynamics methods, and (3) recovering the atomistic structure of the network by reverse mapping from the equilibrated CG structure, hydrating the structure with explicitly represented water, followed by final equilibration using PCFF parameterization. The developed three-stage modeling approach has application to a wide range of other complex macromolecular hydrogel systems, including the integration of peptide, protein, and/or drug molecules as side-chains within the hydrogel network for the incorporation of bioactivity for tissue engineering, regenerative medicine, and drug delivery applications. PMID:27013229

Remarks towards the spectrum of the Heisenberg spin chain type models

NASA Astrophysics Data System (ADS)

Burdík, Č.; Fuksa, J.; Isaev, A. P.; Krivonos, S. O.; Navrátil, O.

2015-05-01

The integrable close and open chain models can be formulated in terms of generators of the Hecke algebras. In this review paper, we describe in detail the Bethe ansatz for the XXX and the XXZ integrable close chain models. We find the Bethe vectors for two-component and inhomogeneous models. We also find the Bethe vectors for the fermionic realization of the integrable XXX and XXZ close chain models by means of the algebraic and coordinate Bethe ansatz. Special modification of the XXZ closed spin chain model ("small polaron model") is considered. Finally, we discuss some questions relating to the general open Hecke chain models.

Modelling the bioaccumulation of persistent organic pollutants in agricultural food chains for regulatory exposure assessment.

PubMed

Takaki, Koki; Wade, Andrew J; Collins, Chris D

2017-02-01

New models for estimating bioaccumulation of persistent organic pollutants in the agricultural food chain were developed using recent improvements to plant uptake and cattle transfer models. One model named AgriSim was based on K OW regressions of bioaccumulation in plants and cattle, while the other was a steady-state mechanistic model, AgriCom. The two developed models and European Union System for the Evaluation of Substances (EUSES), as a benchmark, were applied to four reported food chain (soil/air-grass-cow-milk) scenarios to evaluate the performance of each model simulation against the observed data. The four scenarios considered were as follows: (1) polluted soil and air, (2) polluted soil, (3) highly polluted soil surface and polluted subsurface and (4) polluted soil and air at different mountain elevations. AgriCom reproduced observed milk bioaccumulation well for all four scenarios, as did AgriSim for scenarios 1 and 2, but EUSES only did this for scenario 1. The main causes of the deviation for EUSES and AgriSim were the lack of the soil-air-plant pathway and the ambient air-plant pathway, respectively. Based on the results, it is recommended that soil-air-plant and ambient air-plant pathway should be calculated separately and the K OW regression of transfer factor to milk used in EUSES be avoided. AgriCom satisfied the recommendations that led to the low residual errors between the simulated and the observed bioaccumulation in agricultural food chain for the four scenarios considered. It is therefore recommended that this model should be incorporated into regulatory exposure assessment tools. The model uncertainty of the three models should be noted since the simulated concentration in milk from 5th to 95th percentile of the uncertainty analysis often varied over two orders of magnitude. Using a measured value of soil organic carbon content was effective to reduce this uncertainty by one order of magnitude.

Alignment-free Transcriptomic and Metatranscriptomic Comparison Using Sequencing Signatures with Variable Length Markov Chains.

PubMed

Liao, Weinan; Ren, Jie; Wang, Kun; Wang, Shun; Zeng, Feng; Wang, Ying; Sun, Fengzhu

2016-11-23

The comparison between microbial sequencing data is critical to understand the dynamics of microbial communities. The alignment-based tools analyzing metagenomic datasets require reference sequences and read alignments. The available alignment-free dissimilarity approaches model the background sequences with Fixed Order Markov Chain (FOMC) yielding promising results for the comparison of microbial communities. However, in FOMC, the number of parameters grows exponentially with the increase of the order of Markov Chain (MC). Under a fixed high order of MC, the parameters might not be accurately estimated owing to the limitation of sequencing depth. In our study, we investigate an alternative to FOMC to model background sequences with the data-driven Variable Length Markov Chain (VLMC) in metatranscriptomic data. The VLMC originally designed for long sequences was extended to apply to high-throughput sequencing reads and the strategies to estimate the corresponding parameters were developed. The flexible number of parameters in VLMC avoids estimating the vast number of parameters of high-order MC under limited sequencing depth. Different from the manual selection in FOMC, VLMC determines the MC order adaptively. Several beta diversity measures based on VLMC were applied to compare the bacterial RNA-Seq and metatranscriptomic datasets. Experiments show that VLMC outperforms FOMC to model the background sequences in transcriptomic and metatranscriptomic samples. A software pipeline is available at https://d2vlmc.codeplex.com.

Landscaping the structures of GAVI country vaccine supply chains and testing the effects of radical redesign.

PubMed

Lee, Bruce Y; Connor, Diana L; Wateska, Angela R; Norman, Bryan A; Rajgopal, Jayant; Cakouros, Brigid E; Chen, Sheng-I; Claypool, Erin G; Haidari, Leila A; Karir, Veena; Leonard, Jim; Mueller, Leslie E; Paul, Proma; Schmitz, Michelle M; Welling, Joel S; Weng, Yu-Ting; Brown, Shawn T

2015-08-26

Many of the world's vaccine supply chains do not adequately provide vaccines, prompting several questions: how are vaccine supply chains currently structured, are these structures closely tailored to individual countries, and should these supply chains be radically redesigned? We segmented the 57 GAVI-eligible countries' vaccine supply chains based on their structure/morphology, analyzed whether these segments correlated with differences in country characteristics, and then utilized HERMES to develop a detailed simulation model of three sample countries' supply chains and explore the cost and impact of various alternative structures. The majority of supply chains (34 of 57) consist of four levels, despite serving a wide diversity of geographical areas and population sizes. These four-level supply chains loosely fall into three clusters [(1) 18 countries relatively more bottom-heavy, i.e., many more storage locations lower in the supply chain, (2) seven with relatively more storage locations in both top and lower levels, and (3) nine comparatively more top-heavy] which do not correlate closely with any of the country characteristics considered. For all three cluster types, our HERMES modeling found that simplified systems (a central location shipping directly to immunization locations with a limited number of Hubs in between) resulted in lower operating costs. A standard four-tier design template may have been followed for most countries and raises the possibility that simpler and more tailored designs may be warranted. Copyright © 2015 Elsevier Ltd. All rights reserved.

Finite size induces crossover temperature in growing spin chains

NASA Astrophysics Data System (ADS)

Sienkiewicz, Julian; Suchecki, Krzysztof; Hołyst, Janusz A.

2014-01-01

We introduce a growing one-dimensional quenched spin model that bases on asymmetrical one-side Ising interactions in the presence of external field. Numerical simulations and analytical calculations based on Markov chain theory show that when the external field is smaller than the exchange coupling constant J there is a nonmonotonous dependence of the mean magnetization on the temperature in a finite system. The crossover temperature Tc corresponding to the maximal magnetization decays with system size, approximately as the inverse of the Lambert W function. The observed phenomenon can be understood as an interplay between the thermal fluctuations and the presence of the first cluster determined by initial conditions. The effect exists also when spins are not quenched but fully thermalized after the attachment to the chain. By performing tests on real data we conceive the model is in part suitable for a qualitative description of online emotional discussions arranged in a chronological order, where a spin in every node conveys emotional valence of a subsequent post.

Finite size induces crossover temperature in growing spin chains.

PubMed

Sienkiewicz, Julian; Suchecki, Krzysztof; Hołyst, Janusz A

2014-01-01

We introduce a growing one-dimensional quenched spin model that bases on asymmetrical one-side Ising interactions in the presence of external field. Numerical simulations and analytical calculations based on Markov chain theory show that when the external field is smaller than the exchange coupling constant J there is a nonmonotonous dependence of the mean magnetization on the temperature in a finite system. The crossover temperature Tc corresponding to the maximal magnetization decays with system size, approximately as the inverse of the Lambert W function. The observed phenomenon can be understood as an interplay between the thermal fluctuations and the presence of the first cluster determined by initial conditions. The effect exists also when spins are not quenched but fully thermalized after the attachment to the chain. By performing tests on real data we conceive the model is in part suitable for a qualitative description of online emotional discussions arranged in a chronological order, where a spin in every node conveys emotional valence of a subsequent post.

Correction of erroneously packed protein's side chains in the NMR structure based on ab initio chemical shift calculations.

PubMed

Zhu, Tong; Zhang, John Z H; He, Xiao

2014-09-14

In this work, protein side chain (1)H chemical shifts are used as probes to detect and correct side-chain packing errors in protein's NMR structures through structural refinement. By applying the automated fragmentation quantum mechanics/molecular mechanics (AF-QM/MM) method for ab initio calculation of chemical shifts, incorrect side chain packing was detected in the NMR structures of the Pin1 WW domain. The NMR structure is then refined by using molecular dynamics simulation and the polarized protein-specific charge (PPC) model. The computationally refined structure of the Pin1 WW domain is in excellent agreement with the corresponding X-ray structure. In particular, the use of the PPC model yields a more accurate structure than that using the standard (nonpolarizable) force field. For comparison, some of the widely used empirical models for chemical shift calculations are unable to correctly describe the relationship between the particular proton chemical shift and protein structures. The AF-QM/MM method can be used as a powerful tool for protein NMR structure validation and structural flaw detection.

Chain-Wise Generalization of Road Networks Using Model Selection

NASA Astrophysics Data System (ADS)

Bulatov, D.; Wenzel, S.; Häufel, G.; Meidow, J.

2017-05-01

Streets are essential entities of urban terrain and their automatized extraction from airborne sensor data is cumbersome because of a complex interplay of geometric, topological and semantic aspects. Given a binary image, representing the road class, centerlines of road segments are extracted by means of skeletonization. The focus of this paper lies in a well-reasoned representation of these segments by means of geometric primitives, such as straight line segments as well as circle and ellipse arcs. We propose the fusion of raw segments based on similarity criteria; the output of this process are the so-called chains which better match to the intuitive perception of what a street is. Further, we propose a two-step approach for chain-wise generalization. First, the chain is pre-segmented using circlePeucker and finally, model selection is used to decide whether two neighboring segments should be fused to a new geometric entity. Thereby, we consider both variance-covariance analysis of residuals and model complexity. The results on a complex data-set with many traffic roundabouts indicate the benefits of the proposed procedure.

Modeling side-chains using molecular dynamics improve recognition of binding region in CAPRI targets.

PubMed

Camacho, Carlos J

2005-08-01

The CAPRI-II experiment added an extra level of complexity to the problem of predicting protein-protein interactions by including 5 targets for which participants had to build or complete the 3-dimensional (3D) structure of either the receptor or ligand based on the structure of a close homolog. In this article, we describe how modeling key side-chains using molecular dynamics (MD) in explicit solvent improved the recognition of the binding region of a free energy- based computational docking method. In particular, we show that MD is able to predict with relatively high accuracy the rotamer conformation of the anchor side-chains important for molecular recognition as suggested by Rajamani et al. (Proc Natl Acad Sci USA 2004;101:11287-11292). As expected, the conformations are some of the most common rotamers for the given residue, while latch side-chains that undergo induced fit upon binding are forced into less common conformations. Using these models as starting conformations in conjunction with the rigid-body docking server ClusPro and the flexible docking algorithm SmoothDock, we produced valuable predictions for 6 of the 9 targets in CAPRI-II, missing only the 3 targets that underwent significant structural rearrangements upon binding. We also show that our free energy- based scoring function, consisting of the sum of van der Waals, Coulombic electrostatic with a distance-dependent dielectric, and desolvation free energy successfully discriminates the nativelike conformation of our submitted predictions. The latter emphasizes the critical role that thermodynamics plays on our methodology, and validates the generality of the algorithm to predict protein interactions.

3D printed soft parallel actuator

NASA Astrophysics Data System (ADS)

Zolfagharian, Ali; Kouzani, Abbas Z.; Khoo, Sui Yang; Noshadi, Amin; Kaynak, Akif

2018-04-01

This paper presents a 3-dimensional (3D) printed soft parallel contactless actuator for the first time. The actuator involves an electro-responsive parallel mechanism made of two segments namely active chain and passive chain both 3D printed. The active chain is attached to the ground from one end and constitutes two actuator links made of responsive hydrogel. The passive chain, on the other hand, is attached to the active chain from one end and consists of two rigid links made of polymer. The actuator links are printed using an extrusion-based 3D-Bioplotter with polyelectrolyte hydrogel as printer ink. The rigid links are also printed by a 3D fused deposition modelling (FDM) printer with acrylonitrile butadiene styrene (ABS) as print material. The kinematics model of the soft parallel actuator is derived via transformation matrices notations to simulate and determine the workspace of the actuator. The printed soft parallel actuator is then immersed into NaOH solution with specific voltage applied to it via two contactless electrodes. The experimental data is then collected and used to develop a parametric model to estimate the end-effector position and regulate kinematics model in response to specific input voltage over time. It is observed that the electroactive actuator demonstrates expected behaviour according to the simulation of its kinematics model. The use of 3D printing for the fabrication of parallel soft actuators opens a new chapter in manufacturing sophisticated soft actuators with high dexterity and mechanical robustness for biomedical applications such as cell manipulation and drug release.

Multi-chain Markov chain Monte Carlo methods for computationally expensive models

NASA Astrophysics Data System (ADS)

Huang, M.; Ray, J.; Ren, H.; Hou, Z.; Bao, J.

2017-12-01

Markov chain Monte Carlo (MCMC) methods are used to infer model parameters from observational data. The parameters are inferred as probability densities, thus capturing estimation error due to sparsity of the data, and the shortcomings of the model. Multiple communicating chains executing the MCMC method have the potential to explore the parameter space better, and conceivably accelerate the convergence to the final distribution. We present results from tests conducted with the multi-chain method to show how the acceleration occurs i.e., for loose convergence tolerances, the multiple chains do not make much of a difference. The ensemble of chains also seems to have the ability to accelerate the convergence of a few chains that might start from suboptimal starting points. Finally, we show the performance of the chains in the estimation of O(10) parameters using computationally expensive forward models such as the Community Land Model, where the sampling burden is distributed over multiple chains.

A 2-D process-based model for suspended sediment dynamics: A first step towards ecological modeling

USGS Publications Warehouse

Achete, F. M.; van der Wegen, M.; Roelvink, D.; Jaffe, B.

2015-01-01

In estuaries suspended sediment concentration (SSC) is one of the most important contributors to turbidity, which influences habitat conditions and ecological functions of the system. Sediment dynamics differs depending on sediment supply and hydrodynamic forcing conditions that vary over space and over time. A robust sediment transport model is a first step in developing a chain of models enabling simulations of contaminants, phytoplankton and habitat conditions. This works aims to determine turbidity levels in the complex-geometry delta of the San Francisco estuary using a process-based approach (Delft3D Flexible Mesh software). Our approach includes a detailed calibration against measured SSC levels, a sensitivity analysis on model parameters and the determination of a yearly sediment budget as well as an assessment of model results in terms of turbidity levels for a single year, water year (WY) 2011. Model results show that our process-based approach is a valuable tool in assessing sediment dynamics and their related ecological parameters over a range of spatial and temporal scales. The model may act as the base model for a chain of ecological models assessing the impact of climate change and management scenarios. Here we present a modeling approach that, with limited data, produces reliable predictions and can be useful for estuaries without a large amount of processes data.

A 2-D process-based model for suspended sediment dynamics: a first step towards ecological modeling

NASA Astrophysics Data System (ADS)

Achete, F. M.; van der Wegen, M.; Roelvink, D.; Jaffe, B.

2015-06-01

In estuaries suspended sediment concentration (SSC) is one of the most important contributors to turbidity, which influences habitat conditions and ecological functions of the system. Sediment dynamics differs depending on sediment supply and hydrodynamic forcing conditions that vary over space and over time. A robust sediment transport model is a first step in developing a chain of models enabling simulations of contaminants, phytoplankton and habitat conditions. This works aims to determine turbidity levels in the complex-geometry delta of the San Francisco estuary using a process-based approach (Delft3D Flexible Mesh software). Our approach includes a detailed calibration against measured SSC levels, a sensitivity analysis on model parameters and the determination of a yearly sediment budget as well as an assessment of model results in terms of turbidity levels for a single year, water year (WY) 2011. Model results show that our process-based approach is a valuable tool in assessing sediment dynamics and their related ecological parameters over a range of spatial and temporal scales. The model may act as the base model for a chain of ecological models assessing the impact of climate change and management scenarios. Here we present a modeling approach that, with limited data, produces reliable predictions and can be useful for estuaries without a large amount of processes data.

Simulation of economic agents interaction in a trade chain

NASA Astrophysics Data System (ADS)

Gimanova, I. A.; Dulesov, A. S.; Litvin, N. V.

2017-01-01

The mathematical model of economic agents interaction is offered in the work. It allowsconsidering the change of price and sales volumesin dynamics according to the process of purchase and sale in the single-product market of the trade and intermediary network. The description of data-flow processes is based on the use of the continuous dynamic market model. The application of ordinary differential equations during the simulation allows one to define areas of coefficients - characteristics of agents - and to investigate their interaction in a chain on stability.

Confinement dynamics of a semiflexible chain inside nano-spheres

NASA Astrophysics Data System (ADS)

Fathizadeh, A.; Heidari, Maziar; Eslami-Mossallam, B.; Ejtehadi, M. R.

2013-07-01

We study the conformations of a semiflexible chain, confined in nano-scaled spherical cavities, under two distinct processes of confinement. Radial contraction and packaging are employed as two confining procedures. The former method is performed by gradually decreasing the diameter of a spherical shell which envelopes a confined chain. The latter procedure is carried out by injecting the chain inside a spherical shell through a hole on the shell surface. The chain is modeled with a rigid body molecular dynamics simulation and its parameters are adjusted to DNA base-pair elasticity. Directional order parameter is employed to analyze and compare the confined chain and the conformations of the chain for two different sizes of the spheres are studied in both procedures. It is shown that for the confined chains in the sphere sizes of our study, they appear in spiral or tennis-ball structures, and the tennis-ball structure is more likely to be observed in more compact confinements. Our results also show that the dynamical procedure of confinement and the rate of the confinement are influential parameters of the structure of the chain inside spherical cavities.

Linear-algebraic bath transformation for simulating complex open quantum systems

DOE PAGES

Huh, Joonsuk; Mostame, Sarah; Fujita, Takatoshi; ...

2014-12-02

In studying open quantum systems, the environment is often approximated as a collection of non-interacting harmonic oscillators, a configuration also known as the star-bath model. It is also well known that the star-bath can be transformed into a nearest-neighbor interacting chain of oscillators. The chain-bath model has been widely used in renormalization group approaches. The transformation can be obtained by recursion relations or orthogonal polynomials. Based on a simple linear algebraic approach, we propose a bath partition strategy to reduce the system-bath coupling strength. As a result, the non-interacting star-bath is transformed into a set of weakly coupled multiple parallelmore » chains. Furthermore, the transformed bath model allows complex problems to be practically implemented on quantum simulators, and it can also be employed in various numerical simulations of open quantum dynamics.« less

Building Quantitative Hydrologic Storylines from Process-based Models for Managing Water Resources in the U.S. Under Climate-changed Futures

NASA Astrophysics Data System (ADS)

Arnold, J.; Gutmann, E. D.; Clark, M. P.; Nijssen, B.; Vano, J. A.; Addor, N.; Wood, A.; Newman, A. J.; Mizukami, N.; Brekke, L. D.; Rasmussen, R.; Mendoza, P. A.

2016-12-01

Climate change narratives for water-resource applications must represent the change signals contextualized by hydroclimatic process variability and uncertainty at multiple scales. Building narratives of plausible change includes assessing uncertainties across GCM structure, internal climate variability, climate downscaling methods, and hydrologic models. Work with this linked modeling chain has dealt mostly with GCM sampling directed separately to either model fidelity (does the model correctly reproduce the physical processes in the world?) or sensitivity (of different model responses to CO2 forcings) or diversity (of model type, structure, and complexity). This leaves unaddressed any interactions among those measures and with other components in the modeling chain used to identify water-resource vulnerabilities to specific climate threats. However, time-sensitive, real-world vulnerability studies typically cannot accommodate a full uncertainty ensemble across the whole modeling chain, so a gap has opened between current scientific knowledge and most routine applications for climate-changed hydrology. To close that gap, the US Army Corps of Engineers, the Bureau of Reclamation, and the National Center for Atmospheric Research are working on techniques to subsample uncertainties objectively across modeling chain components and to integrate results into quantitative hydrologic storylines of climate-changed futures. Importantly, these quantitative storylines are not drawn from a small sample of models or components. Rather, they stem from the more comprehensive characterization of the full uncertainty space for each component. Equally important from the perspective of water-resource practitioners, these quantitative hydrologic storylines are anchored in actual design and operations decisions potentially affected by climate change. This talk will describe part of our work characterizing variability and uncertainty across modeling chain components and their interactions using newly developed observational data, models and model outputs, and post-processing tools for making the resulting quantitative storylines most useful in practical hydrology applications.

Extraction of business relationships in supply networks using statistical learning theory.

PubMed

Zuo, Yi; Kajikawa, Yuya; Mori, Junichiro

2016-06-01

Supply chain management represents one of the most important scientific streams of operations research. The supply of energy, materials, products, and services involves millions of transactions conducted among national and local business enterprises. To deliver efficient and effective support for supply chain design and management, structural analyses and predictive models of customer-supplier relationships are expected to clarify current enterprise business conditions and to help enterprises identify innovative business partners for future success. This article presents the outcomes of a recent structural investigation concerning a supply network in the central area of Japan. We investigated the effectiveness of statistical learning theory to express the individual differences of a supply chain of enterprises within a certain business community using social network analysis. In the experiments, we employ support vector machine to train a customer-supplier relationship model on one of the main communities extracted from a supply network in the central area of Japan. The prediction results reveal an F-value of approximately 70% when the model is built by using network-based features, and an F-value of approximately 77% when the model is built by using attribute-based features. When we build the model based on both, F-values are improved to approximately 82%. The results of this research can help to dispel the implicit design space concerning customer-supplier relationships, which can be explored and refined from detailed topological information provided by network structures rather than from traditional and attribute-related enterprise profiles. We also investigate and discuss differences in the predictive accuracy of the model for different sizes of enterprises and types of business communities.

Bayesian clustering of DNA sequences using Markov chains and a stochastic partition model.

PubMed

Jääskinen, Väinö; Parkkinen, Ville; Cheng, Lu; Corander, Jukka

2014-02-01

In many biological applications it is necessary to cluster DNA sequences into groups that represent underlying organismal units, such as named species or genera. In metagenomics this grouping needs typically to be achieved on the basis of relatively short sequences which contain different types of errors, making the use of a statistical modeling approach desirable. Here we introduce a novel method for this purpose by developing a stochastic partition model that clusters Markov chains of a given order. The model is based on a Dirichlet process prior and we use conjugate priors for the Markov chain parameters which enables an analytical expression for comparing the marginal likelihoods of any two partitions. To find a good candidate for the posterior mode in the partition space, we use a hybrid computational approach which combines the EM-algorithm with a greedy search. This is demonstrated to be faster and yield highly accurate results compared to earlier suggested clustering methods for the metagenomics application. Our model is fairly generic and could also be used for clustering of other types of sequence data for which Markov chains provide a reasonable way to compress information, as illustrated by experiments on shotgun sequence type data from an Escherichia coli strain.

Predicting side-chain conformations of methionine using a hard-sphere model with stereochemical constraints

NASA Astrophysics Data System (ADS)

Virrueta, A.; Gaines, J.; O'Hern, C. S.; Regan, L.

2015-03-01

Current research in the O'Hern and Regan laboratories focuses on the development of hard-sphere models with stereochemical constraints for protein structure prediction as an alternative to molecular dynamics methods that utilize knowledge-based corrections in their force-fields. Beginning with simple hydrophobic dipeptides like valine, leucine, and isoleucine, we have shown that our model is able to reproduce the side-chain dihedral angle distributions derived from sets of high-resolution protein crystal structures. However, methionine remains an exception - our model yields a chi-3 side-chain dihedral angle distribution that is relatively uniform from 60 to 300 degrees, while the observed distribution displays peaks at 60, 180, and 300 degrees. Our goal is to resolve this discrepancy by considering clashes with neighboring residues, and averaging the reduced distribution of allowable methionine structures taken from a set of crystallized proteins. We will also re-evaluate the electron density maps from which these protein structures are derived to ensure that the methionines and their local environments are correctly modeled. This work will ultimately serve as a tool for computing side-chain entropy and protein stability. A. V. is supported by an NSF Graduate Research Fellowship and a Ford Foundation Fellowship. J. G. is supported by NIH training Grant NIH-5T15LM007056-28.

Configuration of the magnetosome chain: a natural magnetic nanoarchitecture.

PubMed

Orue, I; Marcano, L; Bender, P; García-Prieto, A; Valencia, S; Mawass, M A; Gil-Cartón, D; Alba Venero, D; Honecker, D; García-Arribas, A; Fernández Barquín, L; Muela, A; Fdez-Gubieda, M L

2018-04-26

Magnetospirillum gryphiswaldense is a microorganism with the ability to biomineralize magnetite nanoparticles, called magnetosomes, and arrange them into a chain that behaves like a magnetic compass. Rather than straight lines, magnetosome chains are slightly bent, as evidenced by electron cryotomography. Our experimental and theoretical results suggest that due to the competition between the magnetocrystalline and shape anisotropies, the effective magnetic moment of individual magnetosomes is tilted out of the [111] crystallographic easy axis of magnetite. This tilt does not affect the direction of the chain net magnetic moment, which remains along the [111] axis, but explains the arrangement of magnetosomes in helical-like shaped chains. Indeed, we demonstrate that the chain shape can be reproduced by considering an interplay between the magnetic dipolar interactions between magnetosomes, ruled by the orientation of the magnetosome magnetic moment, and a lipid/protein-based mechanism, modeled as an elastic recovery force exerted on the magnetosomes.

An ``Alternating-Curvature'' Model for the Nanometer-scale Structure of the Nafion Ionomer, Based on Backbone Properties Detected by NMR

NASA Astrophysics Data System (ADS)

Schmidt-Rohr, Klaus; Chen, Q.

2006-03-01

The perfluorinated ionomer, Nafion, which consists of a (-CF2-)n backbone and charged side branches, is useful as a proton exchange membrane in H2/O2 fuel cells. A modified model of the nanometer-scale structure of hydrated Nafion will be presented. It features hydrated ionic clusters familiar from some previous models, but is based most prominently on pronounced backbone rigidity between branch points and limited orientational correlation of local chain axes. These features have been revealed by solid-state NMR measurements, which take advantage of fast rotations of the backbones around their local axes. The resulting alternating curvature of the backbones towards the hydrated clusters also better satisfies the requirement of dense space filling in solids. Simulations based on this ``alternating curvature'' model reproduce orientational correlation data from NMR, as well as scattering features such as the ionomer peak and the I(q) ˜ 1/q power law at small q values, which can be attributed to modulated cylinders resulting from the chain stiffness. The shortcomings of previous models, including Gierke's cluster model and more recent lamellar or bundle models, in matching all requirements imposed by the experimental data will be discussed.

Study of fracture and stress-induced morphological instabilities in polymeric materials

NASA Astrophysics Data System (ADS)

Sabouri-Ghomi, Mohsen

We study the phenomena of fracture in polymers at the molecular and continuum level. At a molecular level, we study the failure of polymer/polymer interfaces. Our main focus is on a specific mode of failure known as chain pull-out fracture, which is common to weak adhesive junctions, and polymer blends and mixtures. In the case of the interface between incompatible polymers, reinforcement is achieved by adding a block copolymer to the interface. We introduce a microscopic model based on Brownian dynamics to investigate the effect of the polymerization index N, of the block connector chain, on fracture toughness of such reinforced polymeric junctions. We consider the mushroom regime, where connector chains are grafted with low surface density, for the case of large pulling velocity. We find that for short chains the interface fracture toughness depends linearly on the polymerization index N of the connector chains, while for longer chains the dependence becomes N 3/2. We propose a scaling argument, based on the geometry of the initial configuration, that accounts for both short and long chains and the crossover between them. At the continuum level, we study the pattern selection mechanism of finger-like crack growth phenomena in gradient driven growth problems in general, and the structure of stress-induced morphological instabilities in crazing of polymer glasses in particular. We simulate solidification in a narrow channel through the use of a phase-field model with an adaptive grid. By tuning a dimensionless parameter, the Peclet number, we show a continuous crossover from a free dendrite at high Peclet numbers to anisotropic viscous fingering at low Peclet numbers. At low Peclet numbers we find good agreement between our results, theoretical predictions, and experiment, providing the first quantitative test of solvability theory for anisotropic viscous fingers. For high undercoolings, we find new phenomena, a solid forger which satisfies stability and thermodynamic criterion. We further provide an analytical form for the shape of these fingers, based on local models of solidification, which fits our numerical results from simulation. Later we study the growth of crazes in polymer glasses by deriving the equations of motion of plastic flow at the craze tip, and the steady-state velocity profile of this flow. By developing a phenomenological model, we solve the full time-dependent equations of motion of this highly non-linear phenomena. Our simulation produces the steady-state cellular pattern observed in experiments. We further show that polymer glasses with lower yield stress produce cellular patterns with sharper tips and more cells, indicating instabilities with smaller wavelengths.

Model-based confirmation of alternative substrates of mitochondrial electron transport chain.

PubMed

Kleessen, Sabrina; Araújo, Wagner L; Fernie, Alisdair R; Nikoloski, Zoran

2012-03-30

Discrimination of metabolic models based on high throughput metabolomics data, reflecting various internal and external perturbations, is essential for identifying the components that contribute to the emerging behavior of metabolic processes. Here, we investigate 12 different models of the mitochondrial electron transport chain (ETC) in Arabidopsis thaliana during dark-induced senescence in order to elucidate the alternative substrates to this metabolic pathway. Our findings demonstrate that the coupling of the proposed computational approach, based on dynamic flux balance analysis, with time-resolved metabolomics data results in model-based confirmations of the hypotheses that, during dark-induced senescence in Arabidopsis, (i) under conditions where the main substrate for the ETC are not fully available, isovaleryl-CoA dehydrogenase and 2-hydroxyglutarate dehydrogenase are able to donate electrons to the ETC, (ii) phytanoyl-CoA does not act even as an indirect substrate of the electron transfer flavoprotein/electron-transfer flavoprotein:ubiquinone oxidoreductase complex, and (iii) the mitochondrial γ-aminobutyric acid transporter has functional significance in maintaining mitochondrial metabolism. Our study provides a basic framework for future in silico studies of alternative pathways in mitochondrial metabolism under extended darkness whereby the role of its components can be computationally discriminated based on available molecular profile data.

Simple Model of Sickle Hemoglobin

NASA Astrophysics Data System (ADS)

Shiryayev, Andrey; Li, Xiaofei; Gunton, James

2006-03-01

A microscopic model is proposed for the interactions between sickle hemoglobin molecules based on information from the protein data bank. A Monte Carlo simulation of a simplified two patch model is carried out, with the goal of understanding fiber formation. A gradual transition from monomers to one dimensional chains is observed as one varies the density of molecules at fixed temperature, somewhat similar to the transition from monomers to polymer fibers in sickle hemoglobin molecules in solution. An observed competition between chain formation and crystallization for the model is also discussed. The results of the simulation of the equation of state are shown to be in excellent agreement with a theory for a model of globular proteins, for the case of two interacting sites.

Under-reported data analysis with INAR-hidden Markov chains.

PubMed

Fernández-Fontelo, Amanda; Cabaña, Alejandra; Puig, Pedro; Moriña, David

2016-11-20

In this work, we deal with correlated under-reported data through INAR(1)-hidden Markov chain models. These models are very flexible and can be identified through its autocorrelation function, which has a very simple form. A naïve method of parameter estimation is proposed, jointly with the maximum likelihood method based on a revised version of the forward algorithm. The most-probable unobserved time series is reconstructed by means of the Viterbi algorithm. Several examples of application in the field of public health are discussed illustrating the utility of the models. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Notes from the field: the economic value chain in disease management organizations.

PubMed

Fetterolf, Donald

2006-12-01

The disease management (DM) "value chain" is composed of a linear series of steps that include operational milestones in the development of knowledge, each stage evolving from the preceding one. As an adaptation of Michael Porter's "value chain" model, the process flow in DM moves along the following path: (1) data/information technology, (2) information generation, (3) analysis, (4) assessment/recommendations, (5) actionable customer plan, and (6) program assessment/reassessment. Each of these stages is managed as a major line of product operations within a DM company or health plan. Metrics around each of the key production variables create benchmark milestones, ongoing management insight into program effectiveness, and potential drivers for activity-based cost accounting pricing models. The value chain process must remain robust from early entry of data and information into the system, through the final presentation and recommendations for our clients if the program is to be effective. For individuals involved in the evaluation or review of DM programs, this framework is an excellent method to visualize the key components and sequence in the process. The value chain model is an excellent way to establish the value of a formal DM program and to create a consultancy relationship with a client involved in purchasing these complex services.

Stochastic model of template-directed elongation processes in biology.

PubMed

Schilstra, Maria J; Nehaniv, Chrystopher L

2010-10-01

We present a novel modular, stochastic model for biological template-based linear chain elongation processes. In this model, elongation complexes (ECs; DNA polymerase, RNA polymerase, or ribosomes associated with nascent chains) that span a finite number of template units step along the template, one after another, with semaphore constructs preventing overtaking. The central elongation module is readily extended with modules that represent initiation and termination processes. The model was used to explore the effect of EC span on motor velocity and dispersion, and the effect of initiation activator and repressor binding kinetics on the overall elongation dynamics. The results demonstrate that (1) motors that move smoothly are able to travel at a greater velocity and closer together than motors that move more erratically, and (2) the rate at which completed chains are released is proportional to the occupancy or vacancy of activator or repressor binding sites only when initiation or activator/repressor dissociation is slow in comparison with elongation. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

An open Markov chain scheme model for a credit consumption portfolio fed by ARIMA and SARMA processes

NASA Astrophysics Data System (ADS)

Esquível, Manuel L.; Fernandes, José Moniz; Guerreiro, Gracinda R.

2016-06-01

We introduce a schematic formalism for the time evolution of a random population entering some set of classes and such that each member of the population evolves among these classes according to a scheme based on a Markov chain model. We consider that the flow of incoming members is modeled by a time series and we detail the time series structure of the elements in each of the classes. We present a practical application to data from a credit portfolio of a Cape Verdian bank; after modeling the entering population in two different ways - namely as an ARIMA process and as a deterministic sigmoid type trend plus a SARMA process for the residues - we simulate the behavior of the population and compare the results. We get that the second method is more accurate in describing the behavior of the populations when compared to the observed values in a direct simulation of the Markov chain.

Process and data fragmentation-oriented enterprise network integration with collaboration modelling and collaboration agents

NASA Astrophysics Data System (ADS)

Li, Qing; Wang, Ze-yuan; Cao, Zhi-chao; Du, Rui-yang; Luo, Hao

2015-08-01

With the process of globalisation and the development of management models and information technology, enterprise cooperation and collaboration has developed from intra-enterprise integration, outsourcing and inter-enterprise integration, and supply chain management, to virtual enterprises and enterprise networks. Some midfielder enterprises begin to serve for different supply chains. Therefore, they combine related supply chains into a complex enterprise network. The main challenges for enterprise network's integration and collaboration are business process and data fragmentation beyond organisational boundaries. This paper reviews the requirements of enterprise network's integration and collaboration, as well as the development of new information technologies. Based on service-oriented architecture (SOA), collaboration modelling and collaboration agents are introduced to solve problems of collaborative management for service convergence under the condition of process and data fragmentation. A model-driven methodology is developed to design and deploy the integrating framework. An industrial experiment is designed and implemented to illustrate the usage of developed technologies in this paper.

Network Polymers Formed Under Nonideal Conditions.

DTIC Science & Technology

1986-12-01

the system or the limited ability of the statistical model to account for stochastic correlations. The viscosity of the reacting system was measured as...based on competing reactions (ring, chain) and employs equilibrium chain statistics . The work thus far has been limited to single cycle growth on an...polymerizations, because a large number of differential equations must be solved. The Makovian approach (sometimes referred to as the statistical or

Adapting Poisson-Boltzmann to the self-consistent mean field theory: Application to protein side-chain modeling

NASA Astrophysics Data System (ADS)

Koehl, Patrice; Orland, Henri; Delarue, Marc

2011-08-01

We present an extension of the self-consistent mean field theory for protein side-chain modeling in which solvation effects are included based on the Poisson-Boltzmann (PB) theory. In this approach, the protein is represented with multiple copies of its side chains. Each copy is assigned a weight that is refined iteratively based on the mean field energy generated by the rest of the protein, until self-consistency is reached. At each cycle, the variational free energy of the multi-copy system is computed; this free energy includes the internal energy of the protein that accounts for vdW and electrostatics interactions and a solvation free energy term that is computed using the PB equation. The method converges in only a few cycles and takes only minutes of central processing unit time on a commodity personal computer. The predicted conformation of each residue is then set to be its copy with the highest weight after convergence. We have tested this method on a database of hundred highly refined NMR structures to circumvent the problems of crystal packing inherent to x-ray structures. The use of the PB-derived solvation free energy significantly improves prediction accuracy for surface side chains. For example, the prediction accuracies for χ1 for surface cysteine, serine, and threonine residues improve from 68%, 35%, and 43% to 80%, 53%, and 57%, respectively. A comparison with other side-chain prediction algorithms demonstrates that our approach is consistently better in predicting the conformations of exposed side chains.

Nonlinear ball chain waveguides for acoustic emission and ultrasound sensing of ablation

NASA Astrophysics Data System (ADS)

Pearson, Stephen H.

Harsh environment acoustic emission and ultrasonic wave sensing applications often benefit from placing the sensor in a remote and more benign physical location by using waveguides to transmit elastic waves between the structural location under test and the transducer. Waveguides are normally designed to have high fidelity over broad frequency ranges to minimize distortion -- often difficult to achieve in practice. This thesis reports on an examination of using nonlinear ball chain waveguides for the transmission of acoustic emission and ultrasonic waves for the monitoring of thermal protection systems undergoing severe heat loading, leading to ablation and similar processes. Experiments test the nonlinear propagation of solitary, harmonic and mixed harmonic elastic waves through a copper tube filled with steel and elastomer balls and various other waveguides. Triangulation of pencil lead breaks occurs on a steel plate. Data are collected concerning the usage of linear waveguides and a water-cooled linear waveguide. Data are collected from a second water-cooled waveguide monitoring Atmospheric Reentry Materials in UVM's Inductively-Coupled Plasma Torch Facility. The motion of the particles in the dimer waveguides is linearly modeled with a three ball and spring chain model and the results are compared per particle. A theoretical nonlinear model is presented which is capable of exactly modeling the motion of the dimer chains. The shape of the waveform propagating through the dimer chain is modeled in a sonic vacuum. Mechanical pulses of varying time widths and amplitudes are launched into one end of the ball chain waveguide and observed at the other end in both time and frequency domains. Similarly, harmonic and mixed harmonic mechanical loads are applied to one end of the waveguide. Balls of different materials are analyzed and discriminated into categories. A copper tube packed with six steel particles, nine steel or marble particles and a longer copper tube packed with 17 steel particles are studied with a frequency sweep. The deformation experienced by a single steel particle in the dimer chain is approximated. Steel ball waveguides and steel rods are fitted with piezoelectric sensors to monitor the force at different points inside the waveguide during testing. The corresponding frequency responses, including intermodulation products, are compared based on amplitude and preloads. A nonlinear mechanical model describes the motion of the dimer chains in a vacuum. Based on the results of these studies it is anticipated that a nonlinear waveguide will be designed, built, and tested as a possible replacement for the high-fidelity waveguides presently being used in an Inductively Coupled Plasma Torch facility for high heat flux thermal protection system testing. The design is intended to accentuate acoustic emission signals of interest, while suppressing other forms of elastic wave noise.

Compression induced phase transition of nematic brush: A mean-field theory study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang, Jiuzhou; Zhang, Xinghua, E-mail: zhangxh@bjtu.edu.cn; Yan, Dadong, E-mail: yandd@bnu.edu.cn

2015-11-28

Responsive behavior of polymer brush to the external compression is one of the most important characters for its application. For the flexible polymer brush, in the case of low grafting density, which is widely studied by the Gaussian chain model based theory, the compression leads to a uniform deformation of the chain. However, in the case of high grafting density, the brush becomes anisotropic and the nematic phase will be formed. The normal compression tends to destroy the nematic order, which leads to a complex responsive behaviors. Under weak compression, chains in the nematic brush are buckled, and the bendingmore » energy and Onsager interaction give rise to the elasticity. Under deep compression, the responsive behaviors of the nematic polymer brush depend on the chain rigidity. For the compressed rigid polymer brush, the chains incline to re-orientate randomly to maximize the orientational entropy and its nematic order is destroyed. For the compressed flexible polymer brush, the chains incline to fold back to keep the nematic order. A buckling-folding transition takes place during the compressing process. For the compressed semiflexible brush, the chains are collectively tilted to a certain direction, which leads to the breaking of the rotational symmetry in the lateral plane. These responsive behaviors of nematic brush relate to the properties of highly frustrated worm-like chain, which is hard to be studied by the traditional self-consistent field theory due to the difficulty to solve the modified diffusion equation. To overcome this difficulty, a single chain in mean-field theory incorporating Monte Carlo simulation and mean-field theory for the worm-like chain model is developed in present work. This method shows high performance for entire region of chain rigidity in the confined condition.« less

Model-Based Engineering for Supply Chain Risk Management

DTIC Science & Technology

2015-09-30

Privacy, 2009 [19] Julien Delange Wheel Brake System Example using AADL; Feiler, Peter; Hansson, Jörgen; de Niz, Dionisio; & Wrage, Lutz. System ...University Software Engineering Institute Abstract—Expanded use of commercial components has increased the complexity of system assurance...verification. Model- based engineering (MBE) offers a means to design, develop, analyze, and maintain a complex system architecture. Architecture Analysis

Self-consistent field theory and numerical scheme for calculating the phase diagram of wormlike diblock copolymers

NASA Astrophysics Data System (ADS)

Jiang, Ying; Chen, Jeff Z. Y.

2013-10-01

This paper concerns establishing a theoretical basis and numerical scheme for studying the phase behavior of AB diblock copolymers made of wormlike chains. The general idea of a self-consistent field theory is the combination of the mean-field approach together with a statistical weight that describes the configurational properties of a polymer chain. In recent years, this approach has been extensively used for structural prediction of block copolymers, based on the Gaussian-model description of a polymer chain. The wormlike-chain model has played an important role in the description of polymer systems, covering the semiflexible-to-rod crossover of the polymer properties and the highly stretching regime, which the Gaussian-chain model has difficulties to describe. Although the idea of developing a self-consistent field theory for wormlike chains could be traced back to early development in polymer physics, the solution of such a theory has been limited due to technical difficulties. In particular, a challenge has been to develop a numerical algorithm enabling the calculation of the phase diagram containing three-dimensional structures for wormlike AB diblock copolymers. This paper describes a computational algorithm that combines a number of numerical tricks, which can be used for such a calculation. A phase diagram covering major parameter areas was constructed for the wormlike-chain system and reported by us, where the ratio between the total length and the persistence length of a constituent polymer is suggested as another tuning parameter for the microphase-separated structures; all detailed technical issues are carefully addressed in the current paper.

System Dynamics Modeling for Supply Chain Information Sharing

NASA Astrophysics Data System (ADS)

Feng, Yang

In this paper, we try to use the method of system dynamics to model supply chain information sharing. Firstly, we determine the model boundaries, establish system dynamics model of supply chain before information sharing, analyze the model's simulation results under different changed parameters and suggest improvement proposal. Then, we establish system dynamics model of supply chain information sharing and make comparison and analysis on the two model's simulation results, to show the importance of information sharing in supply chain management. We wish that all these simulations would provide scientific supports for enterprise decision-making.

Transportation and dynamic networks: Models, theory, and applications to supply chains, electric power, and financial networks

NASA Astrophysics Data System (ADS)

Liu, Zugang

Network systems, including transportation and logistic systems, electric power generation and distribution networks as well as financial networks, provide the critical infrastructure for the functioning of our societies and economies. The understanding of the dynamic behavior of such systems is also crucial to national security and prosperity. The identification of new connections between distinct network systems is the inspiration for the research in this dissertation. In particular, I answer two questions raised by Beckmann, McGuire, and Winsten (1956) and Copeland (1952) over half a century ago, which are, respectively, how are electric power flows related to transportation flows and does money flow like water or electricity? In addition, in this dissertation, I achieve the following: (1) I establish the relationships between transportation networks and three other classes of complex network systems: supply chain networks, electric power generation and transmission networks, and financial networks with intermediation. The establishment of such connections provides novel theoretical insights as well as new pricing mechanisms, and efficient computational methods. (2) I develop new modeling frameworks based on evolutionary variational inequality theory that capture the dynamics of such network systems in terms of the time-varying flows and incurred costs, prices, and, where applicable, profits. This dissertation studies the dynamics of such network systems by addressing both internal competition and/or cooperation, and external changes, such as varying costs and demands. (3) I focus, in depth, on electric power supply chains. By exploiting the relationships between transportation networks and electric power supply chains, I develop a large-scale network model that integrates electric power supply chains and fuel supply markets. The model captures both the economic transactions as well as the physical transmission constraints. The model is then applied to the New England electric power supply chain consisting of 6 states, 5 fuel types, 82 power generators, with a total of 573 generating units, and 10 demand markets. The empirical case study demonstrates that the regional electricity prices simulated by the model match very well the actual electricity prices in New England. I also utilize the model to study interactions between electric power supply chains and energy fuel markets.

Effect of Molecular Flexibility upon Ice Adhesion Shear Strength

NASA Technical Reports Server (NTRS)

Smith, Joseph G.; Wohl, Christopher J.; Kreeger, Richard E.; Palacios, Jose; Knuth, Taylor; Hadley, Kevin

2016-01-01

Ice formation on aircraft surfaces effects aircraft performance by increasing weight and drag leading to loss of lift. Current active alleviation strategies involve pneumatic boots, heated surfaces, and usage of glycol based de-icing fluids. Mitigation or reduction of in-flight icing by means of a passive approach may enable retention of aircraft capabilities, i.e., no reduction in lift, while reducing the aircraft weight and mechanical complexity. Under a NASA Aeronautics Research Institute Seedling activity, the effect of end group functionality and chain length upon ice adhesion shear strength (IASS) was evaluated with the results indicating that chemical functionality and chain length (i.e. molecular flexibility) affected IASS. Based on experimental and modeling results, diamine monomers incorporating molecular flexibility as either a side chain or in between diamine functionalities were prepared, incorporated into epoxy resins that were subsequently used to fabricate coatings on aluminum substrates, and tested in a simulated icing environment. The IASS was found to be lower when molecular flexibility was incorporated in the polymer chain as opposed to a side chain.

Energy transfer in PPV-based conjugated polymers: a defocused widefield fluorescence microscopy study.

PubMed

Hooley, E N; Tilley, A J; White, J M; Ghiggino, K P; Bell, T D M

2014-04-21

Both pendant and main chain conjugated MEH-PPV based polymers have been studied at the level of single chains using confocal and widefield fluorescence microscopy techniques. In particular, defocused widefield fluorescence is applied to reveal the extent of energy transfer in these polymers by identifying whether they act as single emitters. For main chain conjugated MEH-PPV, molecular weight and the surrounding matrix play a primary role in determining energy transport processes and whether single emitter behaviour is observed. Surprisingly in polymers with a saturated backbone but containing the same pendant MEH-PPV oligomer on each repeating unit, intra-chain energy transfer to a single emitter is also apparent. The results imply there is chromophore heterogeneity that can facilitate energy funneling to the emitting site. Both main chain conjugated and pendant MEH-PPV polymers exhibit changes in orientation of the emission dipole during a fluorescence trajectory of many seconds, whereas a model MEH-PPV oligomer does not. The results suggest that, in the polymers, the nature of the emitting chromophores can change during the time trajectory.

Studies of biaxial mechanical properties and nonlinear finite element modeling of skin.

PubMed

Shang, Xituan; Yen, Michael R T; Gaber, M Waleed

2010-06-01

The objective of this research is to conduct mechanical property studies of skin from two individual but potentially connected aspects. One is to determine the mechanical properties of the skin experimentally by biaxial tests, and the other is to use the finite element method to model the skin properties. Dynamic biaxial tests were performed on 16 pieces of abdominal skin specimen from rats. Typical biaxial stress-strain responses show that skin possesses anisotropy, nonlinearity and hysteresis. To describe the stress-strain relationship in forms of strain energy function, the material constants of each specimen were obtained and the results show a high correlation between theory and experiments. Based on the experimental results, a finite element model of skin was built to model the skin's special properties including anisotropy and nonlinearity. This model was based on Arruda and Boyce's eight-chain model and Bischoff et al.'s finite element model of skin. The simulation results show that the isotropic, nonlinear eight-chain model could predict the skin's anisotropic and nonlinear responses to biaxial loading by the presence of an anisotropic prestress state.

Functionalizing graphene by embedded boron clusters

NASA Astrophysics Data System (ADS)

Quandt, Alexander; Kunstmann, Jens; Ozdogan, Cem; Fehske, Holger

2010-03-01

We present results from an ab initio study of B7 clusters implanted into graphene [1,2]. Our model system consists of an alternating chain of quasiplanar B7 clusters. We show that graphene easily accepts these alternating B7-C6 chains and that the implanted boron components may dramatically modify the electronic properties. This suggests that our model system might serve as a blueprint for the controlled layout of graphene based nanodevices, where the semiconducting properties are supplemented by parts of the graphene matrix itself, and the basic metallic wiring is provided by alternating chains of implanted boron clusters. [1] A. Quandt, C. "Ozdogan, J. Kunstmann, and H. Fehske, Nanotechnology 19, 335707 (2008). [2] A. Quandt, C. "Ozdogan, J. Kunstmann, and H. Fehske, phys. stat. solidi (b) 245, 2077 (2008).

A molecular-field-based similarity study of non-nucleoside HIV-1 reverse transcriptase inhibitors

NASA Astrophysics Data System (ADS)

Mestres, Jordi; Rohrer, Douglas C.; Maggiora, Gerald M.

1999-01-01

This article describes a molecular-field-based similarity method for aligning molecules by matching their steric and electrostatic fields and an application of the method to the alignment of three structurally diverse non-nucleoside HIV-1 reverse transcriptase inhibitors. A brief description of the method, as implemented in the program MIMIC, is presented, including a discussion of pairwise and multi-molecule similarity-based matching. The application provides an example that illustrates how relative binding orientations of molecules can be determined in the absence of detailed structural information on their target protein. In the particular system studied here, availability of the X-ray crystal structures of the respective ligand-protein complexes provides a means for constructing an 'experimental model' of the relative binding orientations of the three inhibitors. The experimental model is derived by using MIMIC to align the steric fields of the three protein P66 subunit main chains, producing an overlay with a 1.41 Å average rms distance between the corresponding Cα's in the three chains. The inter-chain residue similarities for the backbone structures show that the main-chain conformations are conserved in the region of the inhibitor-binding site, with the major deviations located primarily in the 'finger' and RNase H regions. The resulting inhibitor structure overlay provides an experimental-based model that can be used to evaluate the quality of the direct a priori inhibitor alignment obtained using MIMIC. It is found that the 'best' pairwise alignments do not always correspond to the experimental model alignments. Therefore, simply combining the best pairwise alignments will not necessarily produce the optimal multi-molecule alignment. However, the best simultaneous three-molecule alignment was found to reproduce the experimental inhibitor alignment model. A pairwise consistency index has been derived which gauges the quality of combining the pairwise alignments and aids in efficiently forming the optimal multi-molecule alignment analysis. Two post-alignment procedures are described that provide information on feature-based and field-based pharmacophoric patterns. The former corresponds to traditional pharmacophore models and is derived from the contribution of individual atoms to the total similarity. The latter is based on molecular regions rather than atoms and is constructed by computing the percent contribution to the similarity of individual points in a regular lattice surrounding the molecules, which when contoured and colored visually depict regions of highly conserved similarity. A discussion of how the information provided by each of the procedures is useful in drug design is also presented.

Regional climate models reduce biases of global models and project smaller European summer warming

NASA Astrophysics Data System (ADS)

Soerland, S.; Schar, C.; Lüthi, D.; Kjellstrom, E.

2017-12-01

The assessment of regional climate change and the associated planning of adaptation and response strategies are often based on complex model chains. Typically, these model chains employ global and regional climate models (GCMs and RCMs), as well as one or several impact models. It is a common belief that the errors in such model chains behave approximately additive, thus the uncertainty should increase with each modeling step. If this hypothesis were true, the application of RCMs would not lead to any intrinsic improvement (beyond higher-resolution detail) of the GCM results. Here, we investigate the bias patterns (offset during the historical period against observations) and climate change signals of two RCMs that have downscaled a comprehensive set of GCMs following the EURO-CORDEX framework. The two RCMs reduce the biases of the driving GCMs, reduce the spread and modify the amplitude of the GCM projected climate change signal. The GCM projected summer warming at the end of the century is substantially reduced by both RCMs. These results are important, as the projected summer warming and its likely impact on the water cycle are among the most serious concerns regarding European climate change.

Swelling of biological and semiflexible polyelectrolytes.

PubMed

Dobrynin, Andrey V; Carrillo, Jan-Michael Y

2009-10-21

We have developed a theoretical model of swelling of semiflexible (biological) polyelectrolytes in salt solutions. Our approach is based on separation of length scales which allowed us to split a chain's electrostatic energy into two parts that describe local and remote electrostatic interactions along the polymer backbone. The local part takes into account interactions between charged monomers that are separated by distances along the polymer backbone shorter than the chain's persistence length. These electrostatic interactions renormalize chain persistence length. The second part includes electrostatic interactions between remote charged pairs along the polymer backbone located at distances larger than the chain persistence length. These interactions are responsible for chain swelling. In the framework of this approach we calculated effective chain persistence length and chain size as a function of the Debye screening length, chain degree of ionization, bare persistence length and chain degree of polymerization. Our crossover expression for the effective chain's persistence length is in good quantitative agreement with the experimental data on DNA. We have been able to fit experimental datasets by using two adjustable parameters: DNA ionization degree (α = 0.15-0.17) and a bare persistence length (l(p) = 40-44 nm).

A Strategy Combining Higher Energy C-Trap Dissociation with Neutral Loss- and Product Ion-Based MSn Acquisition for Global Profiling and Structure Annotation of Fatty Acids Conjugates

NASA Astrophysics Data System (ADS)

Bi, Qi-rui; Hou, Jin-jun; Yang, Min; Shen, Yao; Qi, Peng; Feng, Rui-hong; Dai, Zhuo; Yan, Bing-peng; Wang, Jian-wei; Shi, Xiao-jian; Wu, Wan-ying; Guo, De-an

2017-03-01

Fatty acids conjugates (FACs) are ubiquitous but found in trace amounts in the natural world. They are composed of multiple unknown substructures and side chains. Thus, FACs are difficult to be analyzed by traditional mass spectrometric methods. In this study, an integrated strategy was developed to global profiling and targeted structure annotation of FACs in complex matrix by LTQ Orbitrap. Dicarboxylic acid conjugated bufotoxins (DACBs) in Venenum bufonis (VB) were used as model compounds. The new strategy (abbreviated as HPNA) combined higher-energy C-trap dissociation (HCD) with product ion- (PI), neutral loss- (NL) based MSn (n ≥ 3) acquisition in both positive-ion mode and negative-ion mode. Several advantages are presented. First, various side chains were found under HCD in negative-ion mode, which included both known and unknown side chains. Second, DACBs with multiple side chains were simultaneously detected in one run. Compared with traditional quadrupole-based mass method, it greatly increased analysis throughput. Third, the fragment ions of side chain and steroids substructure could be obtained by PI- and NL-based MSn acquisition, respectively, which greatly increased the accuracy of the structure annotation of DACBs. In all, 78 DACBs have been discovered, of which 68 were new compounds; 25 types of substructure formulas and seven dicarboxylic acid side chains were found, especially five new side chains, including two saturated dicarboxylic acids [(azelaic acid (C9) and sebacic acid (C10)] and three unsaturated dicarboxylic acids (u-C8, u-C9, and u-C10). All these results greatly enriched the structures of DACBs in VB.

Operational applications of a process-based runoff generation module on the Swiss Plateau and Prealps

NASA Astrophysics Data System (ADS)

Horat, Christoph; Antonetti, Manuel; Wernli, Heini; Zappa, Massimiliano

2017-04-01

Flash floods evolve rapidly during and after heavy precipitation events and represent a risk for society, especially in mountainous areas. Knowledge on meteorological variables and their temporal development is often not sufficient to predict their occurrence. Therefore, information about the state of the hydrological system derived from hydrological models is used. These models rely however on strong simplifying assumptions and need therefore to be calibrated. This prevents their application on catchments, where no runoff data is available. Here we present a flash-flood forecasting chain including: (i) a nowcasting product which combines radar and rain gauge rainfall data (CombiPrecip), (ii) meteorological data from numerical weather prediction models at currently finest available resolution (COSMO-1, COSMO-E), (iii) operationally available soil moisture estimations from the PREVAH hydrological model, and (iv) a process-based runoff generation module with no need for calibration (RGM-PRO). This last component uses information on the spatial distribution of dominant runoff processes (DRPs) which can be derived with different mapping approaches, and is parameterised a priori based on expert knowledge. First, we compared the performance of RGM-PRO with the one of a traditional conceptual runoff generation module for several events on Swiss Emme catchment, as well as on their nested catchments. Different DRP-maps are furthermore tested to evaluate the sensitivity of the forecasting chain to the mapping approaches. Then, we benchmarked the new forecasting chain with the traditional chain used on the Swiss Verzasca catchment. The results show that RGM-PRO performs similarly or even better than the traditional calibrated conceptual module on the investigated catchments. The use of strongly simplified DRP mapping approaches still leads to satisfying results, due mainly to the fact that the largest uncertainty source is represented by the meteorological input data. On the Verzasca catchment, RGM-PRO outperformed the traditional forecast chain in terms of mean absolute error, independently from the lead time and threshold quantile, whereas the Brier Skill Score did not show any clear preference. Probabilistic input data led generally to better results compared with those obtained with deterministic forecasts.

Fragment-based modelling of single stranded RNA bound to RNA recognition motif containing proteins

PubMed Central

de Beauchene, Isaure Chauvot; de Vries, Sjoerd J.; Zacharias, Martin

2016-01-01

Abstract Protein-RNA complexes are important for many biological processes. However, structural modeling of such complexes is hampered by the high flexibility of RNA. Particularly challenging is the docking of single-stranded RNA (ssRNA). We have developed a fragment-based approach to model the structure of ssRNA bound to a protein, based on only the protein structure, the RNA sequence and conserved contacts. The conformational diversity of each RNA fragment is sampled by an exhaustive library of trinucleotides extracted from all known experimental protein–RNA complexes. The method was applied to ssRNA with up to 12 nucleotides which bind to dimers of the RNA recognition motifs (RRMs), a highly abundant eukaryotic RNA-binding domain. The fragment based docking allows a precise de novo atomic modeling of protein-bound ssRNA chains. On a benchmark of seven experimental ssRNA–RRM complexes, near-native models (with a mean heavy-atom deviation of <3 Å from experiment) were generated for six out of seven bound RNA chains, and even more precise models (deviation < 2 Å) were obtained for five out of seven cases, a significant improvement compared to the state of the art. The method is not restricted to RRMs but was also successfully applied to Pumilio RNA binding proteins. PMID:27131381

Low temperature scanning tunneling microscopy of metallic and organic nanostructures

NASA Astrophysics Data System (ADS)

Fölsch, Stefan

2006-03-01

Low temperature scanning tunneling microscopy (LT-STM) is capable of both characterizing and manipulating atomic-scale structures at surfaces. It thus provides a powerful experimental tool to gain fundamental insight into how electronic properties evolve when controlling size, geometry, and composition of nanometric model systems at the level of single atoms and molecules. The experiments discussed in this talk employ a Cu(111) surface onto which perfect nanostructures are assembled from native adatoms and organic molecules. Using single Cu adatoms as building blocks, we obtain zero-, one-, and two-dimensional quantum objects (corresponding to the discrete adatom, monatomic adatom chains, and compact adatom assemblies) with intriguing electronic properties. Depending on the structure shape and the number of incorporated atoms we observe the formation of characteristic quantum levels which merge into the sp-derived Shockley surface state in the limit of extended 2D islands; this state exists on many surfaces, such as Cu(111). Our results reveal the natural linkage between this traditional surface property, the quantum confinement in compact adatom structures, and the quasi-atomic state associated with the single adatom. In a second step, we study the interaction of pentacene (C22H14) with Cu adatom chains serving as model quantum wires. We find that STM-based manipulation is capable of connecting single molecules to the chain ends in a defined way, and that the molecule-chain interaction shifts the chain-localized quantum states to higher binding energies. The present system provides an instructive model case to study single organic molecules interacting with metallic nanostructures. The microscopic nature of such composite structures is of importance for any future molecular-based device realization since it determines the contact conductance between the molecular unit and its metal ''contact pad''.

On-ground characterization of the Euclid's CCD273-based readout chain

NASA Astrophysics Data System (ADS)

Szafraniec, Magdalena; Azzollini, R.; Cropper, M.; Pottinger, S.; Khalil, A.; Hailey, M.; Hu, D.; Plana, C.; Cutts, A.; Hunt, T.; Kohley, R.; Walton, D.; Theobald, C.; Sharples, R.; Schmoll, J.; Ferrando, P.

2016-07-01

Euclid is a medium class European Space Agency mission scheduled for launch in 2020. The goal of the survey is to examine the nature of Dark Matter and Dark Energy in the Universe. One of the cosmological probes used to analyze Euclid's data, the weak lensing technique, measures the distortions of galaxy shapes and this requires very accurate knowledge of the system point spread function (PSF). Therefore, to ensure that the galaxy shape is not affected, the detector chain of the telescope's VISible Instrument (VIS) needs to meet specific performance performance requirements. Each of the 12 VIS readout chains consisting of 3 CCDs, readout electronics (ROE) and a power supply unit (RPSU) will undergo a rigorous on-ground testing to ensure that these requirements are met. This paper reports on the current status of the warm and cold testing of the VIS Engineering Model readout chain. Additionally, an early insight to the commissioning of the Flight Model calibration facility and program is provided.

Effect of magnetic dipolar interactions on nanoparticle heating efficiency: Implications for cancer hyperthermia

PubMed Central

Branquinho, Luis C.; Carrião, Marcus S.; Costa, Anderson S.; Zufelato, Nicholas; Sousa, Marcelo H.; Miotto, Ronei; Ivkov, Robert; Bakuzis, Andris F.

2013-01-01

Nanostructured magnetic systems have many applications, including potential use in cancer therapy deriving from their ability to heat in alternating magnetic fields. In this work we explore the influence of particle chain formation on the normalized heating properties, or specific loss power (SLP) of both low- (spherical) and high- (parallelepiped) anisotropy ferrite-based magnetic fluids. Analysis of ferromagnetic resonance (FMR) data shows that high particle concentrations correlate with increasing chain length producing decreasing SLP. Monte Carlo simulations corroborate the FMR results. We propose a theoretical model describing dipole interactions valid for the linear response regime to explain the observed trends. This model predicts optimum particle sizes for hyperthermia to about 30% smaller than those previously predicted, depending on the nanoparticle parameters and chain size. Also, optimum chain lengths depended on nanoparticle surface-to-surface distance. Our results might have important implications to cancer treatment and could motivate new strategies to optimize magnetic hyperthermia. PMID:24096272

A hydrodynamic microchip for formation of continuous cell chains

NASA Astrophysics Data System (ADS)

Khoshmanesh, Khashayar; Zhang, Wei; Tang, Shi-Yang; Nasabi, Mahyar; Soffe, Rebecca; Tovar-Lopez, Francisco J.; Rajadas, Jayakumar; Mitchell, Arnan

2014-05-01

Here, we demonstrate the unique features of a hydrodynamic based microchip for creating continuous chains of model yeast cells. The system consists of a disk shaped microfluidic structure, containing narrow orifices that connect the main channel to an array of spoke channels. Negative pressure provided by a syringe pump draws fluid from the main channel through the narrow orifices. After cleaning process, a thin layer of water is left between the glass substrate and the polydimethylsiloxane microchip, enabling leakage beneath the channel walls. A mechanical clamp is used to adjust the operation of the microchip. Relaxing the clamp allows leakage of liquid beneath the walls in a controllable fashion, leading to formation of a long cell chain evenly distributed along the channel wall. The unique features of the microchip are demonstrated by creating long chains of yeast cells and model 15 μm polystyrene particles along the side wall and analysing the hydrogen peroxide induced death of patterned cells.

Energy exchange and transition to localization in the asymmetric Fermi-Pasta-Ulam oscillatory chain

NASA Astrophysics Data System (ADS)

Smirnov, Valeri V.; Shepelev, Denis S.; Manevitch, Leonid I.

2013-01-01

A finite (periodic) FPU chain is chosen as a convenient model for investigating the energy exchange phenomenon in nonlinear oscillatory systems. As we have recently shown, this phenomenon may occur as a consequence of the resonant interaction between high-frequency nonlinear normal modes. This interaction determines both the complete energy exchange between different parts of the chain and the transition to energy localization in an excited group of particles. In the paper, we demonstrate that this mechanism can exist in realistic (asymmetric) models of atomic or molecular oscillatory chains. Also, we study the resonant interaction of conjugated nonlinear normal modes and prove a possibility of linearization of the equations of motion. The theoretical constructions developed in this paper are based on the concepts of "effective particles" and Limiting Phase Trajectories. In particular, an analytical description of energy exchange between the "effective particles" in the terms of non-smooth functions is presented. The analytical results are confirmed with numerical simulations.

Interaction between glycosaminoglycans and immunoglobulin light chains.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, X.; Myatt, E.; Lykos, P.

1997-01-01

Amyloidosis is a pathological process in which normally soluble proteins polymerize to form insoluble fibrils (amyloid). Amyloid formation is found in a number of diseases, including Alzheimer's disease, adult-onset diabetes, and light-chain-associated amyloidosis. No pharmaceutical methods currently exist to prevent this process or to remove the fibrils from tissue. The search for treatment and prevention methods is hampered by a limited understanding of the biophysical basis of amyloid formation. Glycosaminoglycans (GAGs) are long, unbranched heteropolysaccharides composed of repeating disaccharide subunits and are known to associate with amyloid fibrils. The interaction of amyloid-associated free light chains with GAGs was tested bymore » both size-exclusion high-performance liquid chromatography and sodium dodecyl sulfate-polyacrylamide gel electrophoresis experiments. The results indicated that heparin 16 000 and chondroitin sulfate B and C precipitated both human intact light chains and recombinant light chain variable domains. Although all light chains interacted with heparin, the strongest interactions were obtained with proteins that had formed amyloid. Molecular modeling indicated the possibility of interaction between heparin and the conserved saddle like surface of the light chain dimer opposite the complementarity-determining segments that form part of the antigen-binding site of a functional antibody. This suggestion might offer a new path to block the aggregation of amyloid-associated light chain proteins, by design of antagonists based on properties of GAG binding. A hexasaccharide was modeled as the basis for a possible antagonist.« less

Branching, Chain Scission, and Solution Stability of Worm-Like Micelles

NASA Astrophysics Data System (ADS)

Beaucage, Greg; Vogtt, Karsten; Jiang, Hanqui

As salt is added to a simple micelle solution such as SDS or SLES, the zero shear rate specific viscosity rises rapidly followed by a maximum and decay. The rapid rise in viscosity is associated with formation of elliptical and extended chain worm-like micelles, WLMs. Entanglement of these long chain micelles leads to the viscoelastic behavior we associate with shampoo and body wash. The plateau and drop in viscosity at high salt concentrations is caused by a special type of topological branching where the branch points have no energy penalty to motion along the chain according to Cates theory. These have some similarity to catenane crosslinks. Predictive dynamic theories for WLMs rely on structural details; the diameter, persistence length, contour length, branch length, segment length between branch points, and mesh size. Further, since the contour length and other large scale features are in kinetic equilibrium, with frequent chain breakage and formation, the thermodynamics of these long chain structures are of interest both in terms of chain scission as well as in terms of the stability of the colloidal solution as a whole. Recent structural studies of WLMs using static neutron scattering based on new scattering models will be presented demonstrating that these input parameters for dynamic models of complex topological systems are quantitatively and directly available. In this context it is important to consider a comparison between dynamic features, for instance entanglement, and their static analogs, chain overlap.

Chain stiffness, salt valency, and concentration influences on titration curves of polyelectrolytes: Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Carnal, Fabrice; Stoll, Serge

2011-01-01

Monte Carlo simulations have been used to study two different models of a weak linear polyelectrolyte surrounded by explicit counterions and salt particles: (i) a rigid rod and (ii) a flexible chain. We focused on the influence of the pH, chain stiffness, salt concentration, and valency on the polyelectrolyte titration process and conformational properties. It is shown that chain acid-base properties and conformational properties are strongly modified when multivalent salt concentration variation ranges below the charge equivalence. Increasing chain stiffness allows to minimize intramolecular electrostatic monomer interactions hence improving the deprotonation process. The presence of di and trivalent salt cations clearly promotes the chain degree of ionization but has only a limited effect at very low salt concentration ranges. Moreover, folded structures of fully charged chains are only observed when multivalent salt at a concentration equal or above charge equivalence is considered. Long-range electrostatic potential is found to influence the distribution of charges along and around the polyelectrolyte backbones hence resulting in a higher degree of ionization and a lower attraction of counterions and salt particles at the chain extremities.

Chain stiffness, salt valency, and concentration influences on titration curves of polyelectrolytes: Monte Carlo simulations.

PubMed

Carnal, Fabrice; Stoll, Serge

2011-01-28

Monte Carlo simulations have been used to study two different models of a weak linear polyelectrolyte surrounded by explicit counterions and salt particles: (i) a rigid rod and (ii) a flexible chain. We focused on the influence of the pH, chain stiffness, salt concentration, and valency on the polyelectrolyte titration process and conformational properties. It is shown that chain acid-base properties and conformational properties are strongly modified when multivalent salt concentration variation ranges below the charge equivalence. Increasing chain stiffness allows to minimize intramolecular electrostatic monomer interactions hence improving the deprotonation process. The presence of di and trivalent salt cations clearly promotes the chain degree of ionization but has only a limited effect at very low salt concentration ranges. Moreover, folded structures of fully charged chains are only observed when multivalent salt at a concentration equal or above charge equivalence is considered. Long-range electrostatic potential is found to influence the distribution of charges along and around the polyelectrolyte backbones hence resulting in a higher degree of ionization and a lower attraction of counterions and salt particles at the chain extremities.

Power-law creep behavior of a semiflexible chain.

PubMed

Majumdar, Arnab; Suki, Béla; Rosenblatt, Noah; Alencar, Adriano M; Stamenović, Dimitrije

2008-10-01

Rheological properties of adherent cells are essential for their physiological functions, and microrheological measurements on living cells have shown that their viscoelastic responses follow a weak power law over a wide range of time scales. This power law is also influenced by mechanical prestress borne by the cytoskeleton, suggesting that cytoskeletal prestress determines the cell's viscoelasticity, but the biophysical origins of this behavior are largely unknown. We have recently developed a stochastic two-dimensional model of an elastically joined chain that links the power-law rheology to the prestress. Here we use a similar approach to study the creep response of a prestressed three-dimensional elastically jointed chain as a viscoelastic model of semiflexible polymers that comprise the prestressed cytoskeletal lattice. Using a Monte Carlo based algorithm, we show that numerical simulations of the chain's creep behavior closely correspond to the behavior observed experimentally in living cells. The power-law creep behavior results from a finite-speed propagation of free energy from the chain's end points toward the center of the chain in response to an externally applied stretching force. The property that links the power law to the prestress is the chain's stiffening with increasing prestress, which originates from entropic and enthalpic contributions. These results indicate that the essential features of cellular rheology can be explained by the viscoelastic behaviors of individual semiflexible polymers of the cytoskeleton.

Mesoscopic modeling for nucleic acid chain dynamics

PubMed Central

Sales-Pardo, M.; Guimerà, R.; Moreira, A. A.; Widom, J.; Amaral, L. A. N.

2007-01-01

To gain a deeper insight into cellular processes such as transcription and translation, one needs to uncover the mechanisms controlling the configurational changes of nucleic acids. As a step toward this aim, we present here a mesoscopic-level computational model that provides a new window into nucleic acid dynamics. We model a single-stranded nucleic as a polymer chain whose monomers are the nucleosides. Each monomer comprises a bead representing the sugar molecule and a pin representing the base. The bead-pin complex can rotate about the backbone of the chain. We consider pairwise stacking and hydrogen-bonding interactions. We use a modified Monte Carlo dynamics that splits the dynamics into translational bead motion and rotational pin motion. By performing a number of tests, we first show that our model is physically sound. We then focus on a study of the kinetics of a DNA hairpin—a single-stranded molecule comprising two complementary segments joined by a noncomplementary loop—studied experimentally. We find that results from our simulations agree with experimental observations, demonstrating that our model is a suitable tool for the investigation of the hybridization of single strands. PMID:16089566

Applying STAMP in Accident Analysis

NASA Technical Reports Server (NTRS)

Leveson, Nancy; Daouk, Mirna; Dulac, Nicolas; Marais, Karen

2003-01-01

Accident models play a critical role in accident investigation and analysis. Most traditional models are based on an underlying chain of events. These models, however, have serious limitations when used for complex, socio-technical systems. Previously, Leveson proposed a new accident model (STAMP) based on system theory. In STAMP, the basic concept is not an event but a constraint. This paper shows how STAMP can be applied to accident analysis using three different views or models of the accident process and proposes a notation for describing this process.

Classification of customer lifetime value models using Markov chain

NASA Astrophysics Data System (ADS)

Permana, Dony; Pasaribu, Udjianna S.; Indratno, Sapto W.; Suprayogi

2017-10-01

A firm’s potential reward in future time from a customer can be determined by customer lifetime value (CLV). There are some mathematic methods to calculate it. One method is using Markov chain stochastic model. Here, a customer is assumed through some states. Transition inter the states follow Markovian properties. If we are given some states for a customer and the relationships inter states, then we can make some Markov models to describe the properties of the customer. As Markov models, CLV is defined as a vector contains CLV for a customer in the first state. In this paper we make a classification of Markov Models to calculate CLV. Start from two states of customer model, we make develop in many states models. The development a model is based on weaknesses in previous model. Some last models can be expected to describe how real characters of customers in a firm.

Multi-objective design of fuzzy logic controller in supply chain

NASA Astrophysics Data System (ADS)

Ghane, Mahdi; Tarokh, Mohammad Jafar

2012-08-01

Unlike commonly used methods, in this paper, we have introduced a new approach for designing fuzzy controllers. In this approach, we have simultaneously optimized both objective functions of a supply chain over a two-dimensional space. Then, we have obtained a spectrum of optimized points, each of which represents a set of optimal parameters which can be chosen by the manager according to the importance of objective functions. Our used supply chain model is a member of inventory and order-based production control system family, a generalization of the periodic review which is termed `Order-Up-To policy.' An auto rule maker, based on non-dominated sorting genetic algorithm-II, has been applied to the experimental initial fuzzy rules. According to performance measurement, our results indicate the efficiency of the proposed approach.

Higher-order automatic differentiation of mathematical functions

NASA Astrophysics Data System (ADS)

Charpentier, Isabelle; Dal Cappello, Claude

2015-04-01

Functions of mathematical physics such as the Bessel functions, the Chebyshev polynomials, the Gauss hypergeometric function and so forth, have practical applications in many scientific domains. On the one hand, differentiation formulas provided in reference books apply to real or complex variables. These do not account for the chain rule. On the other hand, based on the chain rule, the automatic differentiation has become a natural tool in numerical modeling. Nevertheless automatic differentiation tools do not deal with the numerous mathematical functions. This paper describes formulas and provides codes for the higher-order automatic differentiation of mathematical functions. The first method is based on Faà di Bruno's formula that generalizes the chain rule. The second one makes use of the second order differential equation they satisfy. Both methods are exemplified with the aforementioned functions.

Removing the regional level from the Niger vaccine supply chain.

PubMed

Assi, Tina-Marie; Brown, Shawn T; Kone, Souleymane; Norman, Bryan A; Djibo, Ali; Connor, Diana L; Wateska, Angela R; Rajgopal, Jayant; Slayton, Rachel B; Lee, Bruce Y

2013-06-10

Since many of the world's vaccine supply chains contain multiple levels, the question remains of whether removing a level could bring efficiencies. We utilized HERMES to generate a detailed discrete-event simulation model of Niger's vaccine supply chain and compared the current four-tier (central, regional, district, and integrated health center levels) with a modified three-tier structure (removing the regional level). Different scenarios explored various accompanying shipping policies and frequencies. Removing the regional level and implementing a collection-based shipping policy from the district stores increases vaccine availability from a mean of 70-100% when districts could collect vaccines at least weekly. Alternatively, implementing a delivery-based shipping policy from the central store monthly in three-route and eight-route scenarios only increases vaccine availability to 87%. Restricting central-to district vaccine shipments to a quarterly schedule for three-route and eight-route scenarios reduces vaccine availability to 49%. The collection-based shipping policy from district stores reduces supply chain logistics cost per dose administered from US$0.14 at baseline to US$0.13 after removing the regional level. Removing the regional level from Niger's vaccine supply chain can substantially improve vaccine availability as long as certain concomitant adjustments to shipping policies and frequencies are implemented. Copyright © 2013 Elsevier Ltd. All rights reserved.

Removing the Regional Level from the Niger Vaccine Supply Chain

PubMed Central

Assi, Tina-Marie; Brown, Shawn T.; Kone, Souleymane; Norman, Bryan A.; Djibo, Ali; Connor, Diana L.; Wateska, Angela R.; Rajgopal, Jayant; Slayton, Rachel B.; Lee, Bruce Y.

2013-01-01

Objective Since many of the world’s vaccine supply chains contain multiple levels, the question remains of whether removing a level could bring efficiencies. Methods We utilized HERMES to generate a detailed discrete-event simulation model of Niger’s vaccine supply chain and compare the current four-tier (central, regional, district and integrated health center levels) with a modified three-tier structure (removing the regional level). Different scenarios explored various accompanying shipping policies and frequencies. Findings Removing the regional level and implementing a collection-based shipping policy from the district stores increases vaccine availability from a mean of 70% to 100% when districts could collect vaccines at least weekly. Alternatively, implementing a delivery-based shipping policy from the central store monthly in three-route and eight-route scenarios only increases vaccine availability to 87%. Restricting central-to district vaccine shipments to a quarterly schedule for three-route and eight-route scenarios reduces vaccine availability to 49%. The collection-based shipping policy from district stores reduces supply chain logistics cost per dose administered from US$0.14 at baseline to US$0.13 after removing the regional level. Conclusion Removing the regional level from Niger’s vaccine supply chain can substantially improve vaccine availability as long as certain concomitant adjustments to shipping policies and frequencies are implemented. PMID:23602666

Bond Graph Modeling of Chemiosmotic Biomolecular Energy Transduction.

PubMed

Gawthrop, Peter J

2017-04-01

Engineering systems modeling and analysis based on the bond graph approach has been applied to biomolecular systems. In this context, the notion of a Faraday-equivalent chemical potential is introduced which allows chemical potential to be expressed in an analogous manner to electrical volts thus allowing engineering intuition to be applied to biomolecular systems. Redox reactions, and their representation by half-reactions, are key components of biological systems which involve both electrical and chemical domains. A bond graph interpretation of redox reactions is given which combines bond graphs with the Faraday-equivalent chemical potential. This approach is particularly relevant when the biomolecular system implements chemoelectrical transduction - for example chemiosmosis within the key metabolic pathway of mitochondria: oxidative phosphorylation. An alternative way of implementing computational modularity using bond graphs is introduced and used to give a physically based model of the mitochondrial electron transport chain To illustrate the overall approach, this model is analyzed using the Faraday-equivalent chemical potential approach and engineering intuition is used to guide affinity equalisation: a energy based analysis of the mitochondrial electron transport chain.

Numerical methods in Markov chain modeling

NASA Technical Reports Server (NTRS)

Philippe, Bernard; Saad, Youcef; Stewart, William J.

1989-01-01

Several methods for computing stationary probability distributions of Markov chains are described and compared. The main linear algebra problem consists of computing an eigenvector of a sparse, usually nonsymmetric, matrix associated with a known eigenvalue. It can also be cast as a problem of solving a homogeneous singular linear system. Several methods based on combinations of Krylov subspace techniques are presented. The performance of these methods on some realistic problems are compared.

Agent Based Modeling and Simulation Framework for Supply Chain Risk Management

DTIC Science & Technology

2012-03-01

Christopher and Peck 2004) macroeconomic , policy, competition, and resource (Ghoshal 1987) value chain, operational, event, and recurring (Shi 2004...clustering algorithms in agent logic to protect company privacy ( da Silva et al. 2006), aggregation of domain context in agent data analysis logic (Xiang...Operational Availability ( OA ) for FMC and PMC. 75 Mission Capable (MICAP) Hours is the measure of total time (in a month) consumable or reparable

Agile supply chain capabilities: emerging patterns as a determinant of competitive objectives

NASA Astrophysics Data System (ADS)

Yusuf, Yahaya Y.; Adeleye, E. O.; Sivayoganathan, K.

2001-10-01

Turbulent change caused by factors such as changing customer and technological requirements threatens manufacturers through lower product life cycles, profits and bleak survival prospects. Therefore, several companies are stressing flexibility and agility in order to respond, real time, to the unique needs of customers and markets. However, the resource competencies required are often difficult to mobilise and retain by single companies. It is therefore imperative for companies to co-operate and leverage complementary competencies. To this end, legally separate and spatially distributed companies are becoming integrated through Internet-based technologies. The paper reviews emerging patterns in supply chain integration. It also explores the relationship between the emerging patterns and attainment of competitive objectives. The results reported in the paper are based on data from a survey by questionnaire. The survey involved 600 companies in the UK, as part of a larger study of agile manufacturing. The study was driven by a conceptual model, which relates supply chain practices to competitive objectives. The analysis involves the use of factor analysis to reduce research variables to a few principal components. Subsequently, multiple regression was conducted to study the relationship amongst the reduced variables. The results validate the proposed conceptual model and lend credence to current thinking that supply chain integration is a vital tool for competitive advantage.

Environmental Management Competitive Pressure Effect on SME Environmental Innovation Activities: A Green Supply Chain Perspective

NASA Astrophysics Data System (ADS)

Rashid, A. A.; Sidek, A. A.; Suffian, S. A.; Daud, M. R. C.

2018-01-01

The idea of assimilating green supply chain is to integrate and establish environmental management into the supply chain practices. The study aims to explore how environmental management competitive pressure influences a SME company in Malaysia to incorporate green supply chain integration, which is an efficient platform to develop environmental innovation. This study further advances green supply chain management research in Malaysia by using the method of quantitative analysis to analyze the model developed which data will be collected based on a sample of SMEs in Malaysia in manufacturing sector. The model developed in this study illustrates how environmental management competitive pressure from main competitors affects three fundamental dimensions of green supply chain integration. The research findings suggest that environmental management competitive pressure is a vital driving force for a SME company to incorporate internal and external collaboration in developing green product innovation. From the analysis conducted, the study strongly demonstrated that the best way for a company to counteract competitor’s environmental management success is to first implement strong internal green product development process then move to incorporate external environmental management innovation between their suppliers and customers. The findings also show that internal integration of green product innovation fully mediates the relationship of environmental management competitive pressure and the external integration of green product innovation.

Propagating synchrony in feed-forward networks

PubMed Central

Jahnke, Sven; Memmesheimer, Raoul-Martin; Timme, Marc

2013-01-01

Coordinated patterns of precisely timed action potentials (spikes) emerge in a variety of neural circuits but their dynamical origin is still not well understood. One hypothesis states that synchronous activity propagating through feed-forward chains of groups of neurons (synfire chains) may dynamically generate such spike patterns. Additionally, synfire chains offer the possibility to enable reliable signal transmission. So far, mostly densely connected chains, often with all-to-all connectivity between groups, have been theoretically and computationally studied. Yet, such prominent feed-forward structures have not been observed experimentally. Here we analytically and numerically investigate under which conditions diluted feed-forward chains may exhibit synchrony propagation. In addition to conventional linear input summation, we study the impact of non-linear, non-additive summation accounting for the effect of fast dendritic spikes. The non-linearities promote synchronous inputs to generate precisely timed spikes. We identify how non-additive coupling relaxes the conditions on connectivity such that it enables synchrony propagation at connectivities substantially lower than required for linearly coupled chains. Although the analytical treatment is based on a simple leaky integrate-and-fire neuron model, we show how to generalize our methods to biologically more detailed neuron models and verify our results by numerical simulations with, e.g., Hodgkin Huxley type neurons. PMID:24298251

A non-affine micro-macro approach to strain-crystallizing rubber-like materials

NASA Astrophysics Data System (ADS)

Rastak, Reza; Linder, Christian

2018-02-01

Crystallization can occur in rubber materials at large strains due to a phenomenon called strain-induced crystallization. We propose a multi-scale polymer network model to capture this process in rubber-like materials. At the microscopic scale, we present a chain formulation by studying the thermodynamic behavior of a polymer chain and its crystallization mechanism inside a stretching polymer network. The chain model accounts for the thermodynamics of crystallization and presents a rate-dependent evolution law for crystallization based on the gradient of the free energy with respect to the crystallinity variables to ensures the dissipation is always non-negative. The multiscale framework allows the anisotropic crystallization of rubber which has been observed experimentally. Two different approaches for formulating the orientational distribution of crystallinity are studied. In the first approach, the algorithm tracks the crystallization at a finite number of orientations. In contrast, the continuous distribution describes the crystallization for all polymer chain orientations and describes its evolution with only a few distribution parameters. To connect the deformation of the micro with that of the macro scale, our model combines the recently developed maximal advance path constraint with the principal of minimum average free energy, resulting in a non-affine deformation model for polymer chains. Various aspects of the proposed model are validated by existing experimental results, including the stress response, crystallinity evolution during loading and unloading, crystallinity distribution, and the rotation of the principal crystallization direction. As a case study, we simulate the formation of crystalline regions around a pre-existing notch in a 3D rubber block and we compare the results with experimental data.

Improved packing of protein side chains with parallel ant colonies.

PubMed

Quan, Lijun; Lü, Qiang; Li, Haiou; Xia, Xiaoyan; Wu, Hongjie

2014-01-01

The accurate packing of protein side chains is important for many computational biology problems, such as ab initio protein structure prediction, homology modelling, and protein design and ligand docking applications. Many of existing solutions are modelled as a computational optimisation problem. As well as the design of search algorithms, most solutions suffer from an inaccurate energy function for judging whether a prediction is good or bad. Even if the search has found the lowest energy, there is no certainty of obtaining the protein structures with correct side chains. We present a side-chain modelling method, pacoPacker, which uses a parallel ant colony optimisation strategy based on sharing a single pheromone matrix. This parallel approach combines different sources of energy functions and generates protein side-chain conformations with the lowest energies jointly determined by the various energy functions. We further optimised the selected rotamers to construct subrotamer by rotamer minimisation, which reasonably improved the discreteness of the rotamer library. We focused on improving the accuracy of side-chain conformation prediction. For a testing set of 442 proteins, 87.19% of X1 and 77.11% of X12 angles were predicted correctly within 40° of the X-ray positions. We compared the accuracy of pacoPacker with state-of-the-art methods, such as CIS-RR and SCWRL4. We analysed the results from different perspectives, in terms of protein chain and individual residues. In this comprehensive benchmark testing, 51.5% of proteins within a length of 400 amino acids predicted by pacoPacker were superior to the results of CIS-RR and SCWRL4 simultaneously. Finally, we also showed the advantage of using the subrotamers strategy. All results confirmed that our parallel approach is competitive to state-of-the-art solutions for packing side chains. This parallel approach combines various sources of searching intelligence and energy functions to pack protein side chains. It provides a frame-work for combining different inaccuracy/usefulness objective functions by designing parallel heuristic search algorithms.

Metaheuristic simulation optimisation for the stochastic multi-retailer supply chain

NASA Astrophysics Data System (ADS)

Omar, Marina; Mustaffa, Noorfa Haszlinna H.; Othman, Siti Norsyahida

2013-04-01

Supply Chain Management (SCM) is an important activity in all producing facilities and in many organizations to enable vendors, manufacturers and suppliers to interact gainfully and plan optimally their flow of goods and services. A simulation optimization approach has been widely used in research nowadays on finding the best solution for decision-making process in Supply Chain Management (SCM) that generally faced a complexity with large sources of uncertainty and various decision factors. Metahueristic method is the most popular simulation optimization approach. However, very few researches have applied this approach in optimizing the simulation model for supply chains. Thus, this paper interested in evaluating the performance of metahueristic method for stochastic supply chains in determining the best flexible inventory replenishment parameters that minimize the total operating cost. The simulation optimization model is proposed based on the Bees algorithm (BA) which has been widely applied in engineering application such as training neural networks for pattern recognition. BA is a new member of meta-heuristics. BA tries to model natural behavior of honey bees in food foraging. Honey bees use several mechanisms like waggle dance to optimally locate food sources and to search new ones. This makes them a good candidate for developing new algorithms for solving optimization problems. This model considers an outbound centralised distribution system consisting of one supplier and 3 identical retailers and is assumed to be independent and identically distributed with unlimited supply capacity at supplier.

Spin canting in a Dy-based single-chain magnet with dominant next-nearest-neighbor antiferromagnetic interactions

NASA Astrophysics Data System (ADS)

Bernot, K.; Luzon, J.; Caneschi, A.; Gatteschi, D.; Sessoli, R.; Bogani, L.; Vindigni, A.; Rettori, A.; Pini, M. G.

2009-04-01

We investigate theoretically and experimentally the static magnetic properties of single crystals of the molecular-based single-chain magnet of formula [Dy(hfac)3NIT(C6H4OPh)]∞ comprising alternating Dy3+ and organic radicals. The magnetic molar susceptibility χM displays a strong angular variation for sample rotations around two directions perpendicular to the chain axis. A peculiar inversion between maxima and minima in the angular dependence of χM occurs on increasing temperature. Using information regarding the monomeric building block as well as an ab initio estimation of the magnetic anisotropy of the Dy3+ ion, this “anisotropy-inversion” phenomenon can be assigned to weak one-dimensional ferromagnetism along the chain axis. This indicates that antiferromagnetic next-nearest-neighbor interactions between Dy3+ ions dominate, despite the large Dy-Dy separation, over the nearest-neighbor interactions between the radicals and the Dy3+ ions. Measurements of the field dependence of the magnetization, both along and perpendicularly to the chain, and of the angular dependence of χM in a strong magnetic field confirm such an interpretation. Transfer-matrix simulations of the experimental measurements are performed using a classical one-dimensional spin model with antiferromagnetic Heisenberg exchange interaction and noncollinear uniaxial single-ion anisotropies favoring a canted antiferromagnetic spin arrangement, with a net magnetic moment along the chain axis. The fine agreement obtained with experimental data provides estimates of the Hamiltonian parameters, essential for further study of the dynamics of rare-earth-based molecular chains.

Polymer Chain Conformation and Dynamical Confinement in a Model One-Component Nanocomposite

NASA Astrophysics Data System (ADS)

Mark, C.; Holderer, O.; Allgaier, J.; Hübner, E.; Pyckhout-Hintzen, W.; Zamponi, M.; Radulescu, A.; Feoktystov, A.; Monkenbusch, M.; Jalarvo, N.; Richter, D.

2017-07-01

We report a neutron-scattering investigation on the structure and dynamics of a single-component nanocomposite based on SiO2 particles that were grafted with polyisoprene chains at the entanglement limit. By skillful labeling, we access both the monomer density in the corona as well as the conformation of the grafted chains. While the corona profile follows a r-1 power law, the conformation of a grafted chain is identical to that of a chain in a reference melt, implying a high mutual penetration of the coronas from different particles. The brush crowding leads to topological confinement of the chain dynamics: (i) At local scales, the segmental dynamics is unchanged compared to the reference melt, while (ii) at the scale of the chain, the dynamics appears to be slowed down; (iii) by performing a mode analysis in terms of end-fixed Rouse chains, the slower dynamics is tracked to topological confinement within the cone spanned by the adjacent grafts; (iv) by adding 50% matrix chains, the topological confinement sensed by the grafted chain is lifted partially and the apparent chain motion is accelerated. We observe a crossover from pure Rouse motion at short times to topological confined motion beyond the time when the segmental mean squared displacement has reached the distance to the next graft.

Acidic-basic properties of three alanine-based peptides containing acidic and basic side chains: comparison between theory and experiment.

PubMed

Makowska, Joanna; Bagińska, Katarzyna; Liwo, Adam; Chmurzyński, Lech; Scheraga, Harold A

2008-01-01

The purpose of this work was to evaluate the effect of the nature of the ionizable end groups, and the solvent, on their acid-base properties in alanine-based peptides. Hence, the acid-base properties of three alanine-based peptides: Ac-KK-(A)(7)-KK-NH(2) (KAK), Ac-OO-(A)(7)-DD-NH(2) (OAD), Ac-KK-(A)(7)-EE-NH(2) (KAE), where A, D, E, K, and O denote alanine, aspartic acid, glutamic acid, lysine, and ornithine, respectively, were determined in water and in methanol by potentiometry. With the availability of these data, the ability of two theoretical methods to simulate pH-metric titration of those peptides was assessed: (i) the electrostatically driven Monte Carlo method with the ECEPP/3 force field and the Poisson-Boltzmann approach to compute solvation energy (EDMC/PB/pH), and (ii) the molecular dynamics method with the AMBER force field and the Generalized Born model (MD/GB/pH). For OAD and KAE, pK(a1) and pK(a2) correspond to the acidic side chains. For all three compounds in both solvents, the pK(a1) value is remarkably lower than the pK(a) of a compound modeling the respective isolated side chain, which can be explained by the influence of the electrostatic field from positively charged ornithine or lysine side chains. The experimental titration curves are reproduced well by the MD/GB/pH approach, the agreement being better if restraints derived from NMR measurements are incorporated in the conformational search. Poorer agreement is achieved by the EDMC/PB/pH method.

Construction typification as the tool for optimizing the functioning of a robotized manufacturing system

NASA Astrophysics Data System (ADS)

Gwiazda, A.; Banas, W.; Sekala, A.; Foit, K.; Hryniewicz, P.; Kost, G.

2015-11-01

Process of workcell designing is limited by different constructional requirements. They are related to technological parameters of manufactured element, to specifications of purchased elements of a workcell and to technical characteristics of a workcell scene. This shows the complexity of the design-constructional process itself. The results of such approach are individually designed workcell suitable to the specific location and specific production cycle. Changing this parameters one must rebuild the whole configuration of a workcell. Taking into consideration this it is important to elaborate the base of typical elements of a robot kinematic chain that could be used as the tool for building Virtual modelling of kinematic chains of industrial robots requires several preparatory phase. Firstly, it is important to create a database element, which will be models of industrial robot arms. These models could be described as functional primitives that represent elements between components of the kinematic pairs and structural members of industrial robots. A database with following elements is created: the base kinematic pairs, the base robot structural elements, the base of the robot work scenes. The first of these databases includes kinematic pairs being the key component of the manipulator actuator modules. Accordingly, as mentioned previously, it includes the first stage rotary pair of fifth stage. This type of kinematic pairs was chosen due to the fact that it occurs most frequently in the structures of industrial robots. Second base consists of structural robot elements therefore it allows for the conversion of schematic structures of kinematic chains in the structural elements of the arm of industrial robots. It contains, inter alia, the structural elements such as base, stiff members - simple or angular units. They allow converting recorded schematic three-dimensional elements. Last database is a database of scenes. It includes elements of both simple and complex: simple models of technological equipment, conveyors models, models of the obstacles and like that. Using these elements it could be formed various production spaces (robotized workcells), in which it is possible to virtually track the operation of an industrial robot arm modelled in the system.

Appraisal of jump distributions in ensemble-based sampling algorithms

NASA Astrophysics Data System (ADS)

Dejanic, Sanda; Scheidegger, Andreas; Rieckermann, Jörg; Albert, Carlo

2017-04-01

Sampling Bayesian posteriors of model parameters is often required for making model-based probabilistic predictions. For complex environmental models, standard Monte Carlo Markov Chain (MCMC) methods are often infeasible because they require too many sequential model runs. Therefore, we focused on ensemble methods that use many Markov chains in parallel, since they can be run on modern cluster architectures. Little is known about how to choose the best performing sampler, for a given application. A poor choice can lead to an inappropriate representation of posterior knowledge. We assessed two different jump moves, the stretch and the differential evolution move, underlying, respectively, the software packages EMCEE and DREAM, which are popular in different scientific communities. For the assessment, we used analytical posteriors with features as they often occur in real posteriors, namely high dimensionality, strong non-linear correlations or multimodality. For posteriors with non-linear features, standard convergence diagnostics based on sample means can be insufficient. Therefore, we resorted to an entropy-based convergence measure. We assessed the samplers by means of their convergence speed, robustness and effective sample sizes. For posteriors with strongly non-linear features, we found that the stretch move outperforms the differential evolution move, w.r.t. all three aspects.

Literature review of organic matter transport from marshes

NASA Technical Reports Server (NTRS)

Dow, D. D.

1982-01-01

A conceptual model for estimating a transport coefficient for the movement of nonliving organic matter from wetlands to the adjacent embayments was developed in a manner that makes it compatible with the Earth Resources Laboratory's Productive Capacity Model. The model, which envisages detritus movement from wetland pixels to the nearest land-water boundary followed by movement within the water column from tidal creeks to the adjacent embayment, can be transposed to deal with only the interaction between tidal water and the marsh or to estimate the transport from embayments to the adjacent coastal waters. The outwelling hypothesis postulated wetlands as supporting coastal fisheries either by exporting nutrients, such as inorganic nitrogen, which stimulated the plankton-based grazing food chain in the water column, or through the export of dissolved and particulate organic carbon which provided a benthic, detritus-based food web which provides the food source for the grazing food chain in a more indirect fashion.

Investigation of reliability indicators of information analysis systems based on Markov’s absorbing chain model

NASA Astrophysics Data System (ADS)

Gilmanshin, I. R.; Kirpichnikov, A. P.

2017-09-01

In the result of study of the algorithm of the functioning of the early detection module of excessive losses, it is proven the ability to model it by using absorbing Markov chains. The particular interest is in the study of probability characteristics of early detection module functioning algorithm of losses in order to identify the relationship of indicators of reliability of individual elements, or the probability of occurrence of certain events and the likelihood of transmission of reliable information. The identified relations during the analysis allow to set thresholds reliability characteristics of the system components.

Mathematical supply-chain modelling: Product analysis of cost and time

NASA Astrophysics Data System (ADS)

Easters, D. J.

2014-03-01

Establishing a mathematical supply-chain model is a proposition that has received attention due to its inherent benefits of evolving global supply-chain efficiencies. This paper discusses the prevailing relationships found within apparel supply-chain environments, and contemplates the complex issues indicated for constituting a mathematical model. Principal results identified within the data suggest, that the multifarious nature of global supply-chain activities require a degree of simplification in order to fully dilate the necessary factors which affect, each sub-section of the chain. Subsequently, the research findings allowed the division of supply-chain components into sub-sections, which amassed a coherent method of product development activity. Concurrently, the supply-chain model was found to allow systematic mathematical formulae analysis, of cost and time, within the multiple contexts of each subsection encountered. The paper indicates the supply-chain model structure, the mathematics, and considers how product analysis of cost and time can improve the comprehension of product lifecycle management.

Ionizable side chains at catalytic active sites of enzymes.

PubMed

Jimenez-Morales, David; Liang, Jie; Eisenberg, Bob

2012-05-01

Catalytic active sites of enzymes of known structure can be well defined by a modern program of computational geometry. The CASTp program was used to define and measure the volume of the catalytic active sites of 573 enzymes in the Catalytic Site Atlas database. The active sites are identified as catalytic because the amino acids they contain are known to participate in the chemical reaction catalyzed by the enzyme. Acid and base side chains are reliable markers of catalytic active sites. The catalytic active sites have 4 acid and 5 base side chains, in an average volume of 1,072 Å(3). The number density of acid side chains is 8.3 M (in chemical units); the number density of basic side chains is 10.6 M. The catalytic active site of these enzymes is an unusual electrostatic and steric environment in which side chains and reactants are crowded together in a mixture more like an ionic liquid than an ideal infinitely dilute solution. The electrostatics and crowding of reactants and side chains seems likely to be important for catalytic function. In three types of analogous ion channels, simulation of crowded charges accounts for the main properties of selectivity measured in a wide range of solutions and concentrations. It seems wise to use mathematics designed to study interacting complex fluids when making models of the catalytic active sites of enzymes.

Ionizable Side Chains at Catalytic Active Sites of Enzymes

PubMed Central

Jimenez-Morales, David; Liang, Jie

2012-01-01

Catalytic active sites of enzymes of known structure can be well defined by a modern program of computational geometry. The CASTp program was used to define and measure the volume of the catalytic active sites of 573 enzymes in the Catalytic Site Atlas database. The active sites are identified as catalytic because the amino acids they contain are known to participate in the chemical reaction catalyzed by the enzyme. Acid and base side chains are reliable markers of catalytic active sites. The catalytic active sites have 4 acid and 5 base side chains, in an average volume of 1072 Å3. The number density of acid side chains is 8.3 M (in chemical units); the number density of basic side chains is 10.6 M. The catalytic active site of these enzymes is an unusual electrostatic and steric environment in which side chains and reactants are crowded together in a mixture more like an ionic liquid than an ideal infinitely dilute solution. The electrostatics and crowding of reactants and side chains seems likely to be important for catalytic function. In three types of analogous ion channels, simulation of crowded charges accounts for the main properties of selectivity measured in a wide range of solutions and concentrations. It seems wise to use mathematics designed to study interacting complex fluids when making models of the catalytic active sites of enzymes. PMID:22484856

A temperature-dependent coarse-grained model for the thermoresponsive polymer poly(N-isopropylacrylamide).

PubMed

Abbott, Lauren J; Stevens, Mark J

2015-12-28

A coarse-grained (CG) model is developed for the thermoresponsive polymer poly(N-isopropylacrylamide) (PNIPAM), using a hybrid top-down and bottom-up approach. Nonbonded parameters are fit to experimental thermodynamic data following the procedures of the SDK (Shinoda, DeVane, and Klein) CG force field, with minor adjustments to provide better agreement with radial distribution functions from atomistic simulations. Bonded parameters are fit to probability distributions from atomistic simulations using multi-centered Gaussian-based potentials. The temperature-dependent potentials derived for the PNIPAM CG model in this work properly capture the coil-globule transition of PNIPAM single chains and yield a chain-length dependence consistent with atomistic simulations.

Hamiltonian dynamics of thermostated systems: two-temperature heat-conducting phi4 chains.

PubMed

Hoover, Wm G; Hoover, Carol G

2007-04-28

We consider and compare four Hamiltonian formulations of thermostated mechanics, three of them kinetic, and the other one configurational. Though all four approaches "work" at equilibrium, their application to many-body nonequilibrium simulations can fail to provide a proper flow of heat. All the Hamiltonian formulations considered here are applied to the same prototypical two-temperature "phi4" model of a heat-conducting chain. This model incorporates nearest-neighbor Hooke's-Law interactions plus a quartic tethering potential. Physically correct results, obtained with the isokinetic Gaussian and Nose-Hoover thermostats, are compared with two other Hamiltonian results. The latter results, based on constrained Hamiltonian thermostats, fail to model correctly the flow of heat.

Embryo as an active granular fluid: stress-coordinated cellular constriction chains

NASA Astrophysics Data System (ADS)

Gao, Guo-Jie Jason; Holcomb, Michael C.; Thomas, Jeffrey H.; Blawzdziewicz, Jerzy

2016-10-01

Mechanical stress plays an intricate role in gene expression in individual cells and sculpting of developing tissues. However, systematic methods of studying how mechanical stress and feedback help to harmonize cellular activities within a tissue have yet to be developed. Motivated by our observation of the cellular constriction chains (CCCs) during the initial phase of ventral furrow formation in the Drosophila melanogaster embryo, we propose an active granular fluid (AGF) model that provides valuable insights into cellular coordination in the apical constriction process. In our model, cells are treated as circular particles connected by a predefined force network, and they undergo a random constriction process in which the particle constriction probability P is a function of the stress exerted on the particle by its neighbors. We find that when P favors tensile stress, constricted particles tend to form chain-like structures. In contrast, constricted particles tend to form compact clusters when P favors compression. A remarkable similarity of constricted-particle chains and CCCs observed in vivo provides indirect evidence that tensile-stress feedback coordinates the apical constriction activity. Our particle-based AGF model will be useful in analyzing mechanical feedback effects in a wide variety of morphogenesis and organogenesis phenomena.

Expert systems for automated maintenance of a Mars oxygen production system

NASA Astrophysics Data System (ADS)

Huang, Jen-Kuang; Ho, Ming-Tsang; Ash, Robert L.

1992-08-01

Application of expert system concepts to a breadboard Mars oxygen processor unit have been studied and tested. The research was directed toward developing the methodology required to enable autonomous operation and control of these simple chemical processors at Mars. Failure detection and isolation was the key area of concern, and schemes using forward chaining, backward chaining, knowledge-based expert systems, and rule-based expert systems were examined. Tests and simulations were conducted that investigated self-health checkout, emergency shutdown, and fault detection, in addition to normal control activities. A dynamic system model was developed using the Bond-Graph technique. The dynamic model agreed well with tests involving sudden reductions in throughput. However, nonlinear effects were observed during tests that incorporated step function increases in flow variables. Computer simulations and experiments have demonstrated the feasibility of expert systems utilizing rule-based diagnosis and decision-making algorithms.

Integration within the Felsenstein equation for improved Markov chain Monte Carlo methods in population genetics

PubMed Central

Hey, Jody; Nielsen, Rasmus

2007-01-01

In 1988, Felsenstein described a framework for assessing the likelihood of a genetic data set in which all of the possible genealogical histories of the data are considered, each in proportion to their probability. Although not analytically solvable, several approaches, including Markov chain Monte Carlo methods, have been developed to find approximate solutions. Here, we describe an approach in which Markov chain Monte Carlo simulations are used to integrate over the space of genealogies, whereas other parameters are integrated out analytically. The result is an approximation to the full joint posterior density of the model parameters. For many purposes, this function can be treated as a likelihood, thereby permitting likelihood-based analyses, including likelihood ratio tests of nested models. Several examples, including an application to the divergence of chimpanzee subspecies, are provided. PMID:17301231

Vapour-liquid interfacial properties of square-well chains from density functional theory and Monte Carlo simulation.

PubMed

Martínez-Ruiz, Francisco José; Blas, Felipe J; Moreno-Ventas Bravo, A Ignacio; Míguez, José Manuel; MacDowell, Luis G

2017-05-17

The statistical associating fluid theory for attractive potentials of variable range (SAFT-VR) density functional theory (DFT) developed by [Gloor et al., J. Chem. Phys., 2004, 121, 12740-12759] is used to predict the interfacial behaviour of molecules modelled as fully-flexible square-well chains formed from tangentially-bonded monomers of diameter σ and potential range λ = 1.5σ. Four different model systems, comprising 4, 8, 12, and 16 monomers per molecule, are considered. In addition to that, we also compute a number of interfacial properties of molecular chains from direct simulation of the vapour-liquid interface. The simulations are performed in the canonical ensemble, and the vapour-liquid interfacial tension is evaluated using the wandering interface (WIM) method, a technique based on the thermodynamic definition of surface tension. Apart from surface tension, we also obtain density profiles, coexistence densities, vapour pressures, and critical temperature and density, paying particular attention to the effect of the chain length on these properties. According to our results, the main effect of increasing the chain length (at fixed temperature) is to sharpen the vapour-liquid interface and to increase the width of the biphasic coexistence region. As a result, the interfacial thickness decreases and the surface tension increases as the molecular chains get longer. The interfacial thickness and surface tension appear to exhibit an asymptotic limiting behaviour for long chains. A similar behaviour is also observed for the coexistence densities and critical properties. Agreement between theory and simulation results indicates that SAFT-VR DFT is only able to predict qualitatively the interfacial properties of the model. Our results are also compared with simulation data taken from the literature, including the vapour-liquid coexistence densities, vapour pressures, and surface tension.

Supply chain carbon footprinting and responsibility allocation under emission regulations.

PubMed

Chen, Jin-Xiao; Chen, Jian

2017-03-01

Reduction of greenhouse gas emissions has become an enormous challenge for any single enterprise and its supply chain because of the increasing concern on global warming. This paper investigates carbon footprinting and responsibility allocation for supply chains involved in joint production. Our study is conducted from the perspective of a social planner who aims to achieve social value optimization. The carbon footprinting model is based on operational activities rather than on firms because joint production blurs the organizational boundaries of footprints. A general model is proposed for responsibility allocation among firms who seek to maximize individual profits. This study looks into ways for the decentralized supply chain to achieve centralized optimality of social value under two emission regulations. Given a balanced allocation for the entire supply chain, we examine the necessity of over-allocation to certain firms under specific situations and find opportunities for the firms to avoid over-allocation. The comparison of the two regulations reveals that setting an emission standard per unit of product will motivate firms to follow the standard and improve their emission efficiencies. Hence, a more efficient and promising policy is needed in contrast to existing regulations on total production. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Markov chain model for studying suicide dynamics: an illustration of the Rose theorem

PubMed Central

2014-01-01

Background High-risk strategies would only have a modest effect on suicide prevention within a population. It is best to incorporate both high-risk and population-based strategies to prevent suicide. This study aims to compare the effectiveness of suicide prevention between high-risk and population-based strategies. Methods A Markov chain illness and death model is proposed to determine suicide dynamic in a population and examine its effectiveness for reducing the number of suicides by modifying certain parameters of the model. Assuming a population with replacement, the suicide risk of the population was estimated by determining the final state of the Markov model. Results The model shows that targeting the whole population for suicide prevention is more effective than reducing risk in the high-risk tail of the distribution of psychological distress (i.e. the mentally ill). Conclusions The results of this model reinforce the essence of the Rose theorem that lowering the suicidal risk in the population at large may be more effective than reducing the high risk in a small population. PMID:24948330

Review of the "AS-BUILT BIM" Approaches

NASA Astrophysics Data System (ADS)

Hichri, N.; Stefani, C.; De Luca, L.; Veron, P.

2013-02-01

Today, we need 3D models of heritage buildings in order to handle more efficiently projects of restoration, documentation and maintenance. In this context, developing a performing approach, based on a first phase of building survey, is a necessary step in order to build a semantically enriched digital model. For this purpose, the Building Information Modeling is an efficient tool for storing and exchanging knowledge about buildings. In order to create such a model, there are three fundamental steps: acquisition, segmentation and modeling. For these reasons, it is essential to understand and analyze this entire chain that leads to a well- structured and enriched 3D digital model. This paper proposes a survey and an analysis of the existing approaches on these topics and tries to define a new approach of semantic structuring taking into account the complexity of this chain.

Multilocus Association Mapping Using Variable-Length Markov Chains

PubMed Central

Browning, Sharon R.

2006-01-01

I propose a new method for association-based gene mapping that makes powerful use of multilocus data, is computationally efficient, and is straightforward to apply over large genomic regions. The approach is based on the fitting of variable-length Markov chain models, which automatically adapt to the degree of linkage disequilibrium (LD) between markers to create a parsimonious model for the LD structure. Edges of the fitted graph are tested for association with trait status. This approach can be thought of as haplotype testing with sophisticated windowing that accounts for extent of LD to reduce degrees of freedom and number of tests while maximizing information. I present analyses of two published data sets that show that this approach can have better power than single-marker tests or sliding-window haplotypic tests. PMID:16685642

Multilocus association mapping using variable-length Markov chains.

PubMed

Browning, Sharon R

2006-06-01

I propose a new method for association-based gene mapping that makes powerful use of multilocus data, is computationally efficient, and is straightforward to apply over large genomic regions. The approach is based on the fitting of variable-length Markov chain models, which automatically adapt to the degree of linkage disequilibrium (LD) between markers to create a parsimonious model for the LD structure. Edges of the fitted graph are tested for association with trait status. This approach can be thought of as haplotype testing with sophisticated windowing that accounts for extent of LD to reduce degrees of freedom and number of tests while maximizing information. I present analyses of two published data sets that show that this approach can have better power than single-marker tests or sliding-window haplotypic tests.

Influence of Microstructure Representation on Flow Stress and Grain Size Prediction in Through-Process Modeling of AA5182 Sheet Production

NASA Astrophysics Data System (ADS)

Lohmar, Johannes; Bambach, Markus; Karhausen, Kai F.

2013-01-01

Integrated computational materials engineering is an up to date method for developing new materials and optimizing complete process chains. In the simulation of a process chain, material models play a central role as they capture the response of the material to external process conditions. While much effort is put into their development and improvement, less attention is paid to their implementation, which is problematic because the representation of microstructure in the model has a decisive influence on modeling accuracy and calculation speed. The aim of this article is to analyze the influence of different microstructure representation concepts on the prediction of flow stress and microstructure evolution when using the same set of material equations. Scalar, tree-based and cluster-based concepts are compared for a multi-stage rolling process of an AA5182 alloy. It was found that implementation influences the predicted flow stress and grain size, in particular in the regime of coupled hardening and softening.

Thermodynamics and mechanics of stretch-induced crystallization in rubbers

NASA Astrophysics Data System (ADS)

Guo, Qiang; Zaïri, Fahmi; Guo, Xinglin

2018-05-01

The aim of the present paper is to provide a quantitative prediction of the stretch-induced crystallization in natural rubber, the exclusive reason for its history-dependent thermomechanical features. A constitutive model based on a micromechanism inspired molecular chain approach is formulated within the context of the thermodynamic framework. The molecular configuration of the partially crystallized single chain is analyzed and calculated by means of some statistical mechanical methods. The random thermal oscillation of the crystal orientation, considered as a continuous random variable, is treated by means of a representative angle. The physical expression of the chain free energy is derived according to a two-step strategy by separating crystallization and stretching. This strategy ensures that the stretch-induced part of the thermodynamic crystallization force is null at the initial instant and allows, without any additional constraint, the formulation of a simple linear relationship for the crystallinity evolution law. The model contains very few physically interpretable material constants to simulate the complex mechanism: two chain-scale constants, one crystallinity kinetics constant, three thermodynamic constants related to the newly formed crystallites, and a function controlling the crystal orientation with respect to the chain. The model is used to discuss some important aspects of the micromechanism and the macroresponse under the equilibrium state and the nonequilibrium state involved during stretching and recovery, and continuous relaxation.

Using state variables to model the response of tumour cells to radiation and heat: a novel multi-hit-repair approach.

PubMed

Scheidegger, Stephan; Fuchs, Hans U; Zaugg, Kathrin; Bodis, Stephan; Füchslin, Rudolf M

2013-01-01

In order to overcome the limitations of the linear-quadratic model and include synergistic effects of heat and radiation, a novel radiobiological model is proposed. The model is based on a chain of cell populations which are characterized by the number of radiation induced damages (hits). Cells can shift downward along the chain by collecting hits and upward by a repair process. The repair process is governed by a repair probability which depends upon state variables used for a simplistic description of the impact of heat and radiation upon repair proteins. Based on the parameters used, populations up to 4-5 hits are relevant for the calculation of the survival. The model describes intuitively the mathematical behaviour of apoptotic and nonapoptotic cell death. Linear-quadratic-linear behaviour of the logarithmic cell survival, fractionation, and (with one exception) the dose rate dependencies are described correctly. The model covers the time gap dependence of the synergistic cell killing due to combined application of heat and radiation, but further validation of the proposed approach based on experimental data is needed. However, the model offers a work bench for testing different biological concepts of damage induction, repair, and statistical approaches for calculating the variables of state.

Snap-through instability analysis of dielectric elastomers with consideration of chain entanglements

NASA Astrophysics Data System (ADS)

Zhu, Jiakun; Luo, Jun; Xiao, Zhongmin

2018-06-01

It is widely recognized that the extension limit of polymer chains has a significant effect on the snap-through instability of dielectric elastomers (DEs). The snap-through instability performance of DEs has been extensively studied by two limited-stretch models, i.e., the eight-chain model and Gent model. However, the real polymer networks usually have many entanglements due to the impenetrability of the network chains as well as a finite extensibility resulting from the full stretching of the polymer chains. The effects of entanglements on the snap-through instability of DEs cannot be captured by the previous two limited-stretch models. In this paper, the nonaffine model proposed by Davidson and Goulbourne is adopted to characterize the influence of entanglements and extension limit of the polymer chains. It is demonstrated that the nonaffine model is almost identical to the eight-chain model and is close to the Gent model if we ignore the effects of chain entanglements and adopt the affine assumption. The suitability of the nonaffine model to characterize the mechanical behavior of elastomers is validated by fitting the experimental results reported in the open literature. After that, the snap-through stability performance of an ideal DE membrane under equal-biaxial prestretches is studied with the nonaffine model. It is revealed that besides the prestretch and chain extension limit, the chain entanglements can markedly influence the snap-through instability and the path to failure of DEs. These results provide a more comprehensive understanding on the snap-through instability of a DE and may be helpful to guide the design of DE devices.

Model-based Confirmation of Alternative Substrates of Mitochondrial Electron Transport Chain

PubMed Central

Kleessen, Sabrina; Araújo, Wagner L.; Fernie, Alisdair R.; Nikoloski, Zoran

2012-01-01

Discrimination of metabolic models based on high throughput metabolomics data, reflecting various internal and external perturbations, is essential for identifying the components that contribute to the emerging behavior of metabolic processes. Here, we investigate 12 different models of the mitochondrial electron transport chain (ETC) in Arabidopsis thaliana during dark-induced senescence in order to elucidate the alternative substrates to this metabolic pathway. Our findings demonstrate that the coupling of the proposed computational approach, based on dynamic flux balance analysis, with time-resolved metabolomics data results in model-based confirmations of the hypotheses that, during dark-induced senescence in Arabidopsis, (i) under conditions where the main substrate for the ETC are not fully available, isovaleryl-CoA dehydrogenase and 2-hydroxyglutarate dehydrogenase are able to donate electrons to the ETC, (ii) phytanoyl-CoA does not act even as an indirect substrate of the electron transfer flavoprotein/electron-transfer flavoprotein:ubiquinone oxidoreductase complex, and (iii) the mitochondrial γ-aminobutyric acid transporter has functional significance in maintaining mitochondrial metabolism. Our study provides a basic framework for future in silico studies of alternative pathways in mitochondrial metabolism under extended darkness whereby the role of its components can be computationally discriminated based on available molecular profile data. PMID:22334689

Topological analysis of polymeric melts: chain-length effects and fast-converging estimators for entanglement length.

PubMed

Hoy, Robert S; Foteinopoulou, Katerina; Kröger, Martin

2009-09-01

Primitive path analyses of entanglements are performed over a wide range of chain lengths for both bead spring and atomistic polyethylene polymer melts. Estimators for the entanglement length N_{e} which operate on results for a single chain length N are shown to produce systematic O(1/N) errors. The mathematical roots of these errors are identified as (a) treating chain ends as entanglements and (b) neglecting non-Gaussian corrections to chain and primitive path dimensions. The prefactors for the O(1/N) errors may be large; in general their magnitude depends both on the polymer model and the method used to obtain primitive paths. We propose, derive, and test new estimators which eliminate these systematic errors using information obtainable from the variation in entanglement characteristics with chain length. The new estimators produce accurate results for N_{e} from marginally entangled systems. Formulas based on direct enumeration of entanglements appear to converge faster and are simpler to apply.

Long-range magnetic order and interchain interactions in the S = 2 chain system MnCl 3 (bpy)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fishman, Randy S.; Shinozaki, Shin-ichi; Okutani, Akira

Here,more » a compound with very weakly interacting chains, MnCl 3(bpy), has attracted a great deal of attention as a possible S = 2 Haldane chain. However, long-range magnetic order of the chains prevents the Haldane gap from developing below 11.5 K. Based on a four-sublattice model, a description of the antiferromagnetic resonance (AFMR) spectrum up to frequencies of 1.5 THz and magnetic fields up to 50 T indicates that the interchain coupling is indeed quite small but that the Dzaloshinskii-Moriya interaction produced by broken inversion symmetry is substantial (0.12 meV). In addition, the antiferromagnetic, nearest-neighbor interaction within each chain (3.3 meV) is significantly stronger than previously reported. The excitation spectrum of this S = 2 compound is well described by a 1/S expansion about the classical limit.« less

Long-range magnetic order and interchain interactions in the S = 2 chain system MnCl 3 (bpy)

DOE PAGES

Fishman, Randy S.; Shinozaki, Shin-ichi; Okutani, Akira; ...

2016-09-28

Here,more » a compound with very weakly interacting chains, MnCl 3(bpy), has attracted a great deal of attention as a possible S = 2 Haldane chain. However, long-range magnetic order of the chains prevents the Haldane gap from developing below 11.5 K. Based on a four-sublattice model, a description of the antiferromagnetic resonance (AFMR) spectrum up to frequencies of 1.5 THz and magnetic fields up to 50 T indicates that the interchain coupling is indeed quite small but that the Dzaloshinskii-Moriya interaction produced by broken inversion symmetry is substantial (0.12 meV). In addition, the antiferromagnetic, nearest-neighbor interaction within each chain (3.3 meV) is significantly stronger than previously reported. The excitation spectrum of this S = 2 compound is well described by a 1/S expansion about the classical limit.« less

Exploring the folding pattern of a polymer chain in a single crystal by combining single-molecule force spectroscopy and steered molecular dynamics simulations.

PubMed

Song, Yu; Feng, Wei; Liu, Kai; Yang, Peng; Zhang, Wenke; Zhang, Xi

2013-03-26

Understanding the folding pattern of a single polymer chain within its single crystal will shed light on the mechanism of crystallization. Here, we use the combined techniques of atomic force microscopy (AFM)-based single-molecule force spectroscopy (SMFS) and steered molecular dynamics (SMD) simulations to study the folding pattern of a polyethylene oxide (PEO) chain in its single crystal. Our results show that the folding pattern of a PEO chain in the crystal formed in dilute solution follows the adjacent re-entry folding model. While in the crystal obtained from the melt, the nonadjacent folding with large and irregular loops contributes to big force fluctuations in the force-extension curves. The method established here can offer a novel strategy to directly unravel the chain-folding pattern of polymer single crystals at single-molecule level.

Small Subunits of Serine Palmitoyltransferase (ssSPTs) and Their Physiological Roles

DTIC Science & Technology

2014-02-12

showing that organisms also have unique sphingoid base chain lengths. In insects, such as Drosophila melanogaster , the predominant chain lengths of the ... Drosophila melanogaster mutant defective in male meiotic cytokinesis (‘Ghiberti’) has a mutation in a gene with low homology to the ssSPT subunits of...INTRODUCTION: Sphingolipid metabolism in Drosophila melanogaster (fly) is an active area of research. It is a good model system to study the roles of

Long-distance entanglement and quantum teleportation in XX spin chains

DOE Office of Scientific and Technical Information (OSTI.GOV)

Campos Venuti, L.; Giampaolo, S. M.; CNR-INFM Coherentia, Napoli

2007-11-15

Isotropic XX models of one-dimensional spin-1/2 chains are investigated with the aim to elucidate the formal structure and the physical properties that allow these systems to act as channels for long-distance, high-fidelity quantum teleportation. We introduce two types of models: (i) open, dimerized XX chains, and (ii) open XX chains with small end bonds. For both models we obtain the exact expressions for the end-to-end correlations and the scaling of the energy gap with the length of the chain. We determine the end-to-end concurrence and show that model (i) supports true long-distance entanglement at zero temperature, while model (ii) supportsmore » 'quasi-long-distance' entanglement that slowly falls off with the size of the chain. Due to the different scalings of the gaps, respectively exponential for model (i) and algebraic in model (ii), we demonstrate that the latter allows for efficient qubit teleportation with high fidelity in sufficiently long chains even at moderately low temperatures.« less

Customer involvement in greening the supply chain: an interpretive structural modeling methodology

NASA Astrophysics Data System (ADS)

Kumar, Sanjay; Luthra, Sunil; Haleem, Abid

2013-04-01

The role of customers in green supply chain management needs to be identified and recognized as an important research area. This paper is an attempt to explore the involvement aspect of customers towards greening of the supply chain (SC). An empirical research approach has been used to collect primary data to rank different variables for effective customer involvement in green concept implementation in SC. An interpretive structural-based model has been presented, and variables have been classified using matrice d' impacts croises- multiplication appliqué a un classement analysis. Contextual relationships among variables have been established using experts' opinions. The research may help practicing managers to understand the interaction among variables affecting customer involvement. Further, this understanding may be helpful in framing the policies and strategies to green SC. Analyzing interaction among variables for effective customer involvement in greening SC to develop the structural model in the Indian perspective is an effort towards promoting environment consciousness.

Integrated strategic and tactical biomass-biofuel supply chain optimization.

PubMed

Lin, Tao; Rodríguez, Luis F; Shastri, Yogendra N; Hansen, Alan C; Ting, K C

2014-03-01

To ensure effective biomass feedstock provision for large-scale biofuel production, an integrated biomass supply chain optimization model was developed to minimize annual biomass-ethanol production costs by optimizing both strategic and tactical planning decisions simultaneously. The mixed integer linear programming model optimizes the activities range from biomass harvesting, packing, in-field transportation, stacking, transportation, preprocessing, and storage, to ethanol production and distribution. The numbers, locations, and capacities of facilities as well as biomass and ethanol distribution patterns are key strategic decisions; while biomass production, delivery, and operating schedules and inventory monitoring are key tactical decisions. The model was implemented to study Miscanthus-ethanol supply chain in Illinois. The base case results showed unit Miscanthus-ethanol production costs were $0.72L(-1) of ethanol. Biorefinery related costs accounts for 62% of the total costs, followed by biomass procurement costs. Sensitivity analysis showed that a 50% reduction in biomass yield would increase unit production costs by 11%. Copyright © 2014 Elsevier Ltd. All rights reserved.

The spread model of food safety risk under the supply-demand disturbance.

PubMed

Wang, Jining; Chen, Tingqiang

2016-01-01

In this paper, based on the imbalance of the supply-demand relationship of food, we design a spreading model of food safety risk, which is about from food producers to consumers in the food supply chain. We use theoretical analysis and numerical simulation to describe the supply-demand relationship and government supervision behaviors' influence on the risk spread of food safety and the behaviors of the food producers and the food retailers. We also analyze the influence of the awareness of consumer rights protection and the level of legal protection of consumer rights on the risk spread of food safety. This model contributes to the explicit investigation of the influence relationship among supply-demand factors, the regulation behavioral choice of government, the behavioral choice of food supply chain members and food safety risk spread. And this paper provides a new viewpoint for considering food safety risk spread in the food supply chain, which has a great reference for food safety management.

ICE CONTROL - Towards optimizing wind energy production during icing events

NASA Astrophysics Data System (ADS)

Dorninger, Manfred; Strauss, Lukas; Serafin, Stefano; Beck, Alexander; Wittmann, Christoph; Weidle, Florian; Meier, Florian; Bourgeois, Saskia; Cattin, René; Burchhart, Thomas; Fink, Martin

2017-04-01

Forecasts of wind power production loss caused by icing weather conditions are produced by a chain of physical models. The model chain consists of a numerical weather prediction model, an icing model and a production loss model. Each element of the model chain is affected by significant uncertainty, which can be quantified using targeted observations and a probabilistic forecasting approach. In this contribution, we present preliminary results from the recently launched project ICE CONTROL, an Austrian research initiative on measurements, probabilistic forecasting, and verification of icing on wind turbine blades. ICE CONTROL includes an experimental field phase, consisting of measurement campaigns in a wind park in Rhineland-Palatinate, Germany, in the winters 2016/17 and 2017/18. Instruments deployed during the campaigns consist of a conventional icing detector on the turbine hub and newly devised ice sensors (eologix Sensor System) on the turbine blades, as well as meteorological sensors for wind, temperature, humidity, visibility, and precipitation type and spectra. Liquid water content and spectral characteristics of super-cooled water droplets are measured using a Fog Monitor FM-120. Three cameras document the icing conditions on the instruments and on the blades. Different modelling approaches are used to quantify the components of the model-chain uncertainties. The uncertainty related to the initial conditions of the weather prediction is evaluated using the existing global ensemble prediction system (EPS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). Furthermore, observation system experiments are conducted with the AROME model and its 3D-Var data assimilation to investigate the impact of additional observations (such as Mode-S aircraft data, SCADA data and MSG cloud mask initialization) on the numerical icing forecast. The uncertainty related to model formulation is estimated from multi-physics ensembles based on the Weather Research and Forecasting model (WRF) by perturbing parameters in the physical parameterization schemes. In addition, uncertainties of the icing model and of its adaptations to the rotating turbine blade are addressed. The model forecasts combined with the suite of instruments and their measurements make it possible to conduct a step-wise verification of all the components of the model chain - a novel aspect compared to similar ongoing and completed forecasting projects.

Fast analysis of radionuclide decay chain migration

NASA Astrophysics Data System (ADS)

Chen, J. S.; Liang, C. P.; Liu, C. W.; Li, L.

2014-12-01

A novel tool for rapidly predicting the long-term plume behavior of an arbitrary length radionuclide decay chain is presented in this study. This fast tool is achieved based on generalized analytical solutions in compact format derived for a set of two-dimensional advection-dispersion equations coupled with sequential first-order decay reactions in groundwater system. The performance of the developed tool is evaluated by a numerical model using a Laplace transform finite difference scheme. The results of performance evaluation indicate that the developed model is robust and accurate. The developed model is then used to fast understand the transport behavior of a four-member radionuclide decay chain. Results show that the plume extents and concentration levels of any target radionuclide are very sensitive to longitudinal, transverse dispersion, decay rate constant and retardation factor. The developed model are useful tools for rapidly assessing the ecological and environmental impact of the accidental radionuclide releases such as the Fukushima nuclear disaster where multiple radionuclides leaked through the reactor, subsequently contaminating the local groundwater and ocean seawater in the vicinity of the nuclear plant.

Evaluation and selection of sustainable suppliers in supply chain using new GP-DEA model with imprecise data

NASA Astrophysics Data System (ADS)

Jafarzadeh Ghoushchi, Saeid; Dodkanloi Milan, Mehran; Jahangoshai Rezaee, Mustafa

2017-11-01

Nowadays, with respect to knowledge growth about enterprise sustainability, sustainable supplier selection is considered a vital factor in sustainable supply chain management. On the other hand, usually in real problems, the data are imprecise. One method that is helpful for the evaluation and selection of the sustainable supplier and has the ability to use a variety of data types is data envelopment analysis (DEA). In the present article, first, the supplier efficiency is measured with respect to all economic, social and environmental dimensions using DEA and applying imprecise data. Then, to have a general evaluation of the suppliers, the DEA model is developed using imprecise data based on goal programming (GP). Integrating the set of criteria changes the new model into a coherent framework for sustainable supplier selection. Moreover, employing this model in a multilateral sustainable supplier selection can be an incentive for the suppliers to move towards environmental, social and economic activities. Improving environmental, economic and social performance will mean improving the supply chain performance. Finally, the application of the proposed approach is presented with a real dataset.

Momentum-Based Dynamics for Spacecraft with Chained Revolute Appendages

NASA Technical Reports Server (NTRS)

Queen, Steven; London, Ken; Gonzalez, Marcelo

2005-01-01

An efficient formulation is presented for a sub-class of multi-body dynamics problems that involve a six degree-of-freedom base body and a chain of N rigid linkages connected in series by single degree-of-freedom revolute joints. This general method is particularly well suited for simulations of spacecraft dynamics and control that include the modeling of an orbiting platform with or without internal degrees of freedom such as reaction wheels, dampers, and/or booms. In the present work, particular emphasis is placed on dynamic simulation of multi-linkage robotic manipulators. The differential equations of motion are explicitly given in terms of linear and angular momentum states, which can be evaluated recursively along a serial chain of linkages for an efficient real-time solution on par with the best of the O(N3) methods.

Equilibrating high-molecular-weight symmetric and miscible polymer blends with hierarchical back-mapping.

PubMed

Ohkuma, Takahiro; Kremer, Kurt; Daoulas, Kostas

2018-05-02

Understanding properties of polymer alloys with computer simulations frequently requires equilibration of samples comprised of microscopically described long molecules. We present the extension of an efficient hierarchical backmapping strategy, initially developed for homopolymer melts, to equilibrate high-molecular-weight binary blends. These mixtures present significant interest for practical applications and fundamental polymer physics. In our approach, the blend is coarse-grained into models representing polymers as chains of soft blobs. Each blob stands for a subchain with N b microscopic monomers. A hierarchy of blob-based models with different resolution is obtained by varying N b . First the model with the largest N b is used to obtain an equilibrated blend. This configuration is sequentially fine-grained, reinserting at each step the degrees of freedom of the next in the hierarchy blob-based model. Once the blob-based description is sufficiently detailed, the microscopic monomers are reinserted. The hard excluded volume is recovered through a push-off procedure and the sample is re-equilibrated with molecular dynamics (MD), requiring relaxation on the order of the entanglement time. For the initial method development we focus on miscible blends described on microscopic level through a generic bead-spring model, which reproduces hard excluded volume, strong covalent bonds, and realistic liquid density. The blended homopolymers are symmetric with respect to molecular architecture and liquid structure. To parameterize the blob-based models and validate equilibration of backmapped samples, we obtain reference data from independent hybrid simulations combining MD and identity exchange Monte Carlo moves, taking advantage of the symmetry of the blends. The potential of the backmapping strategy is demonstrated by equilibrating blend samples with different degree of miscibility, containing 500 chains with 1000 monomers each. Equilibration is verified by comparing chain conformations and liquid structure in backmapped blends with the reference data. Possible directions for further methodological developments are discussed.

Equilibrating high-molecular-weight symmetric and miscible polymer blends with hierarchical back-mapping

NASA Astrophysics Data System (ADS)

Ohkuma, Takahiro; Kremer, Kurt; Daoulas, Kostas

2018-05-01

Understanding properties of polymer alloys with computer simulations frequently requires equilibration of samples comprised of microscopically described long molecules. We present the extension of an efficient hierarchical backmapping strategy, initially developed for homopolymer melts, to equilibrate high-molecular-weight binary blends. These mixtures present significant interest for practical applications and fundamental polymer physics. In our approach, the blend is coarse-grained into models representing polymers as chains of soft blobs. Each blob stands for a subchain with N b microscopic monomers. A hierarchy of blob-based models with different resolution is obtained by varying N b. First the model with the largest N b is used to obtain an equilibrated blend. This configuration is sequentially fine-grained, reinserting at each step the degrees of freedom of the next in the hierarchy blob-based model. Once the blob-based description is sufficiently detailed, the microscopic monomers are reinserted. The hard excluded volume is recovered through a push-off procedure and the sample is re-equilibrated with molecular dynamics (MD), requiring relaxation on the order of the entanglement time. For the initial method development we focus on miscible blends described on microscopic level through a generic bead-spring model, which reproduces hard excluded volume, strong covalent bonds, and realistic liquid density. The blended homopolymers are symmetric with respect to molecular architecture and liquid structure. To parameterize the blob-based models and validate equilibration of backmapped samples, we obtain reference data from independent hybrid simulations combining MD and identity exchange Monte Carlo moves, taking advantage of the symmetry of the blends. The potential of the backmapping strategy is demonstrated by equilibrating blend samples with different degree of miscibility, containing 500 chains with 1000 monomers each. Equilibration is verified by comparing chain conformations and liquid structure in backmapped blends with the reference data. Possible directions for further methodological developments are discussed.

Dimension and bridging ligand effects on Mo-mediated catalytic transformation of dinitrogen to ammonia: Chain-like extended models of Nishibayashi’s catalyst

DOE PAGES

Sheng, Xiao -Lan; Batista, Enrique Ricardo; Duan, Yi -Xiang; ...

2016-11-01

Previous studies suggested that in Nishibayashi’s homogenous catalytic systems based on molybdenum (Mo) complexes, the bimetallic structure facilitated dinitrogen to ammonia conversion in comparison to the corresponding monometallic complexes, likely due to the through-bond interactions between the two Mo centers. However, more detailed model systems are necessary to support this bimetallic hypothesis, and to elucidate the multi-metallic effects on the catalytic mechanism. In this work, we computationally examined the effects of dimension as well as the types of bridging ligands on the catalytic activities of molybdenum-dinitrogen complexes by using a set of extended model systems based on Nishibayashi’s bimetallic structure.more » The polynuclear chains containing four ([Mo] 4) or more Mo centers were found to drastically enhance the catalytic performance by comparing with both the monometallic and bimetallic complexes. Carbide ([:C≡C:] 2–) was found to be a more effective bridging ligand than N 2 in terms of electronic charges dispersion between metal centers thereby facilitating reactions in the catalytic cycle. Furthermore, the mechanistic modelling suggests that in principle, more efficient catalytic system for N 2 to NH 3 transformation might be obtained by extending the polynuclear chain to a proper size in combination with an effective bridging ligand for charge dispersion.« less

Dimension and bridging ligand effects on Mo-mediated catalytic transformation of dinitrogen to ammonia: Chain-like extended models of Nishibayashi’s catalyst

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sheng, Xiao -Lan; Batista, Enrique Ricardo; Duan, Yi -Xiang

Previous studies suggested that in Nishibayashi’s homogenous catalytic systems based on molybdenum (Mo) complexes, the bimetallic structure facilitated dinitrogen to ammonia conversion in comparison to the corresponding monometallic complexes, likely due to the through-bond interactions between the two Mo centers. However, more detailed model systems are necessary to support this bimetallic hypothesis, and to elucidate the multi-metallic effects on the catalytic mechanism. In this work, we computationally examined the effects of dimension as well as the types of bridging ligands on the catalytic activities of molybdenum-dinitrogen complexes by using a set of extended model systems based on Nishibayashi’s bimetallic structure.more » The polynuclear chains containing four ([Mo] 4) or more Mo centers were found to drastically enhance the catalytic performance by comparing with both the monometallic and bimetallic complexes. Carbide ([:C≡C:] 2–) was found to be a more effective bridging ligand than N 2 in terms of electronic charges dispersion between metal centers thereby facilitating reactions in the catalytic cycle. Furthermore, the mechanistic modelling suggests that in principle, more efficient catalytic system for N 2 to NH 3 transformation might be obtained by extending the polynuclear chain to a proper size in combination with an effective bridging ligand for charge dispersion.« less

Quantitative farm-to-fork risk assessment model for norovirus and hepatitis A virus in European leafy green vegetable and berry fruit supply chains.

PubMed

Bouwknegt, Martijn; Verhaelen, Katharina; Rzeżutka, Artur; Kozyra, Iwona; Maunula, Leena; von Bonsdorff, Carl-Henrik; Vantarakis, Apostolos; Kokkinos, Petros; Petrovic, Tamas; Lazic, Sava; Pavlik, Ivo; Vasickova, Petra; Willems, Kris A; Havelaar, Arie H; Rutjes, Saskia A; de Roda Husman, Ana Maria

2015-04-02

Fresh produce that is contaminated with viruses may lead to infection and viral gastroenteritis or hepatitis when consumed raw. It is thus important to reduce virus numbers on these foods. Prevention of virus contamination in fresh produce production and processing may be more effective than treatment, as sufficient virus removal or inactivation by post-harvest treatment requires high doses that may adversely affect food quality. To date knowledge of the contribution of various potential contamination routes is lacking. A risk assessment model was developed for human norovirus, hepatitis A virus and human adenovirus in raspberry and salad vegetable supply chains to quantify contributions of potential contamination sources to the contamination of produce at retail. These models were used to estimate public health risks. Model parameterization was based on monitoring data from European supply chains and literature data. No human pathogenic viruses were found in the soft fruit supply chains; human adenovirus (hAdV) was detected, which was additionally monitored as an indicator of fecal pollution to assess the contribution of potential contamination points. Estimated risks per serving of lettuce based on the models were 3×10(-4) (6×10(-6)-5×10(-3)) for NoV infection and 3×10(-8) (7×10(-10)-3×10(-6)) for hepatitis A jaundice. The contribution to virus contamination of hand-contact was larger as compared with the contribution of irrigation, the conveyor belt or the water used for produce rinsing. In conclusion, viral contamination in the lettuce and soft fruit supply chains occurred and estimated health risks were generally low. Nevertheless, the 97.5% upper limit for the estimated NoV contamination of lettuce suggested that infection risks up to 50% per serving might occur. Our study suggests that attention to full compliance for hand hygiene will improve fresh produce safety related to virus risks most as compared to the other examined sources, given the monitoring results. This effect will be further aided by compliance with other hygiene and water quality regulations in production and processing facilities. Copyright © 2015 Elsevier B.V. All rights reserved.

Subnational mobility and consumption-based environmental accounting of US corn in animal protein and ethanol supply chains

PubMed Central

Smith, Timothy M.; Kim, Taegon; Pelton, Rylie E. O.; Suh, Kyo; Schmitt, Jennifer

2017-01-01

Corn production, and its associated inputs, is a relatively large source of greenhouse gas emissions and uses significant amounts of water and land, thus contributing to climate change, fossil fuel depletion, local air pollutants, and local water scarcity. As large consumers of this corn, corporations in the ethanol and animal protein industries are increasingly assessing and reporting sustainability impacts across their supply chains to identify, prioritize, and communicate sustainability risks and opportunities material to their operations. In doing so, many have discovered that the direct impacts of their owned operations are dwarfed by those upstream in the supply chain, requiring transparency and knowledge about environmental impacts along the supply chains. Life cycle assessments (LCAs) have been used to identify hotspots of environmental impacts at national levels, yet these provide little subnational information necessary for guiding firms’ specific supply networks. In this paper, our Food System Supply-Chain Sustainability (FoodS3) model connects spatial, firm-specific demand of corn purchasers with upstream corn production in the United States through a cost minimization transport model. This provides a means to link county-level corn production in the United States to firm-specific demand locations associated with downstream processing facilities. Our model substantially improves current LCA assessment efforts that are confined to broad national or state level impacts. In drilling down to subnational levels of environmental impacts that occur over heterogeneous areas and aggregating these landscape impacts by specific supply networks, targeted opportunities for improvements to the sustainability performance of supply chains are identified. PMID:28874548

Effects of changes along the risk chain on flood risk

NASA Astrophysics Data System (ADS)

Duha Metin, Ayse; Apel, Heiko; Viet Dung, Nguyen; Guse, Björn; Kreibich, Heidi; Schröter, Kai; Vorogushyn, Sergiy; Merz, Bruno

2017-04-01

Interactions of hydrological and socio-economic factors shape flood disaster risk. For this reason, assessment of flood risk ideally takes into account the whole flood risk chain from atmospheric processes, through the catchment and river system processes to the damage mechanisms in the affected areas. Since very different processes at various scales are interacting along the flood risk, the impact of the single components is rather unclear. However for flood risk management, it is required to know the controlling factor of flood damages. The present study, using the flood-prone Mulde catchment in Germany, discusses the sensitivity of flood risk to disturbances along the risk chain: How do disturbances propagate through the risk chain? How do different disturbances combine or conflict and affect flood risk? In this sensitivity analysis, the five components of the flood risk change are included. These are climate, catchment, river system, exposure and vulnerability. A model framework representing the complete risk chain is combined with observational data to understand how the sensitivities evolve along the risk chain by considering three plausible change scenarios for each of five components. The flood risk is calculated by using the Regional Flood Model (RFM) which is based on a continuous simulation approach, including rainfall-runoff, 1D river network, 2D hinterland inundation and damage estimation models. The sensitivity analysis covers more than 240 scenarios with different combinations of the five components. It is investigated how changes in different components affect risk indicators, such as the risk curve and expected annual damage (EAD). In conclusion, it seems that changes in exposure and vulnerability seem to outweigh changes in hazard.

Subnational mobility and consumption-based environmental accounting of US corn in animal protein and ethanol supply chains.

PubMed

Smith, Timothy M; Goodkind, Andrew L; Kim, Taegon; Pelton, Rylie E O; Suh, Kyo; Schmitt, Jennifer

2017-09-19

Corn production, and its associated inputs, is a relatively large source of greenhouse gas emissions and uses significant amounts of water and land, thus contributing to climate change, fossil fuel depletion, local air pollutants, and local water scarcity. As large consumers of this corn, corporations in the ethanol and animal protein industries are increasingly assessing and reporting sustainability impacts across their supply chains to identify, prioritize, and communicate sustainability risks and opportunities material to their operations. In doing so, many have discovered that the direct impacts of their owned operations are dwarfed by those upstream in the supply chain, requiring transparency and knowledge about environmental impacts along the supply chains. Life cycle assessments (LCAs) have been used to identify hotspots of environmental impacts at national levels, yet these provide little subnational information necessary for guiding firms' specific supply networks. In this paper, our Food System Supply-Chain Sustainability (FoodS 3 ) model connects spatial, firm-specific demand of corn purchasers with upstream corn production in the United States through a cost minimization transport model. This provides a means to link county-level corn production in the United States to firm-specific demand locations associated with downstream processing facilities. Our model substantially improves current LCA assessment efforts that are confined to broad national or state level impacts. In drilling down to subnational levels of environmental impacts that occur over heterogeneous areas and aggregating these landscape impacts by specific supply networks, targeted opportunities for improvements to the sustainability performance of supply chains are identified.

Conductance of single microRNAs chains related to the autism spectrum disorder

NASA Astrophysics Data System (ADS)

Oliveira, J. I. N.; Albuquerque, E. L.; Fulco, U. L.; Mauriz, P. W.; Sarmento, R. G.; Caetano, E. W. S.; Freire, V. N.

2014-09-01

The charge transport properties of single-stranded microRNAs (miRNAs) chains associated to autism disorder were investigated. The computations were performed within a tight-binding model, together with a transfer matrix technique, with ionization energies and hopping parameters obtained by quantum chemistry method. Current-voltage (I× V) curves of twelve miRNA chains related to the autism spectrum disorders were calculated and analysed. We have obtained both semiconductor and insulator behavior, and a relationship between the current intensity and the autism-related miRNA bases sequencies, suggesting that a kind of electronic biosensor can be developed to distinguish different profiles of autism disorders.

BetaSCPWeb: side-chain prediction for protein structures using Voronoi diagrams and geometry prioritization

PubMed Central

Ryu, Joonghyun; Lee, Mokwon; Cha, Jehyun; Laskowski, Roman A.; Ryu, Seong Eon; Kim, Deok-Soo

2016-01-01

Many applications, such as protein design, homology modeling, flexible docking, etc. require the prediction of a protein's optimal side-chain conformations from just its amino acid sequence and backbone structure. Side-chain prediction (SCP) is an NP-hard energy minimization problem. Here, we present BetaSCPWeb which efficiently computes a conformation close to optimal using a geometry-prioritization method based on the Voronoi diagram of spherical atoms. Its outputs are visual, textual and PDB file format. The web server is free and open to all users at http://voronoi.hanyang.ac.kr/betascpweb with no login requirement. PMID:27151195

Exploring the Influence of Differentiated Nutrition Information on Consumers' Mental Models Regarding Foods from Edible Insects: A Means-End Chain Analysis.

PubMed

Pambo, Kennedy O; Okello, Julius J; Mbeche, Robert M; Kinyuru, John N

2017-01-01

This study used a field experiment and means-end chain analysis to examine the effects of positive and perceived negative nutrition information on the households' motivations to consume insect-based foods. It used a random sample of households drawn from rural communities in Kenya. The study found that provision of nutrition information on benefits of edible insects and perceived negative aspects of insect-based foods influences participants' perceptions of insect-based foods and hence acceptance. We also found that tasting real products influenced the nature of mental constructs. The results provide marketers of edible insects with potential marketing messages for promotion.

Thermoreversible gelation of poly(vinylidene fluoride) in phthalates: the influence of aliphatic chain length of solvents.

PubMed

Yadav, P Jaya Prakash; Ghosh, Goutam; Maiti, Biswajit; Aswal, Vinod K; Goyal, P S; Maiti, Pralay

2008-04-17

Thermoreversible gelation of poly(vinylidene fluoride) (PVDF) has been studied in a new series of solvents (phthalates), for example, dimethyl phthalate (DMP), diethyl phthalate (DEP), dibutyl phthalate (DBP), and dihexyl phthalate (DHP) as a function of temperature and polymer concentration, both by test tube tilting and dynamic light scattering (DLS) method. The effect of aliphatic chain length (n) of diesters on the gelation kinetics, structure/microstructure and morphology of PVDF gels has been examined. Gelation rate was found to increase with increasing aliphatic chain length of diester. DLS results indicate that the sol-gel transformation proceeds via two-steps: first, microgel domains were formed, and then the infinite three-dimensional (3D) network is established by connecting microgels through polymer chains. The crystallites are responsible for 3D network for gelation in phthalates, and alpha-polymorph is formed during gelation producing higher amount of crystallinity with increasing aliphatic chain length of diester. Morphology of the networks of dried gels in different phthalates showed that fibril thickness and lateral dimensions decrease with higher homologues of phthalates. The scattering intensity is fitted with Debye-Bueche model in small-angle neutron scattering and suggested that both the correlation length and interlamellar spacing increases with n. A model has been proposed, based on electronic structure calculations, to explain the conformation of PVDF chain in presence of various phthalates and their complexes, which offer the cause of higher gelation rate for longer aliphatic chain length.

Size of the Dynamic Bead in Polymers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agapov, Alexander L; Sokolov, Alexei P

2010-01-01

Presented analysis of neutron, mechanical, and MD simulation data available in the literature demonstrates that the dynamic bead size (the smallest subchain that still exhibits the Rouse-like dynamics) in most of the polymers is significantly larger than the traditionally defined Kuhn segment. Moreover, our analysis emphasizes that even the static bead size (e.g., chain statistics) disagrees with the Kuhn segment length. We demonstrate that the deficiency of the Kuhn segment definition is based on the assumption of a chain being completely extended inside a single bead. The analysis suggests that representation of a real polymer chain by the bead-and-spring modelmore » with a single parameter C cannot be correct. One needs more parameters to reflect correctly details of the chain structure in the bead-and-spring model.« less

Asymptotic study of pulsating evolution of overdriven and CJ detonation with a chain-branching kinetics model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Short, Mark; Chliquete, Carlos

2011-01-20

The pulsating dynamics of gaseous detonations with a model two-step chain-branching kinetic mechanism are studied both numerically and asymptotically. The model studied here was also used in [4], [3] and [2] and mimics the attributes of some chain-branching reaction mechanisms. Specifically, the model comprises a chain-initiationlbranching zone with an Arrhenius temperature-sensitive rate behind the detonation shock where fuel is converted into chain-radical with no heat release. This is followed by a chain-termination zone having a temperature insensitive rate where the exothermic heat of reaction is released. The lengths of these two zones depend on the relative rates of each stage.more » It was determined in [4] and [3] via asymptotic and numerical analysis that the ratio of the length of the chain-branching zone to that of the chain-initation zone relative to the size of the von Neumann state scaled activation energy in the chain initiation/branching zone has a primary influence of the stability of one-dimensional pulsating instability behavior for this model. In [2], the notion of a specific stability parameter related to this ratio was proposed that determines the boundary between stable and unstable waves. In [4], a slow-time varying asymptotic study was conducted of pulsating instability of Chapman-Jouguet (CJ) detonations with the above two-step rate model, assuming a large activation energy for the chain-initiation zone and a chain-termination zone longer than the chain-initiation zone. Deviations D{sub n}{sup (1)} ({tau}) of the detonation velocity from Chapman-Jouguet were of the order of the non-dimensional activation energy. Solutions were sought for a pulsation timescale of the order of the non-dimensional activation energy times the particle transit time through the induction zone. On this time-scale, the evolution of the chain-initation zone is quasi-steady. In [4], a time-dependent non-linear evolution equation for D{sub n}{sup (1)} ({tau}) was then constructed via a perturbation procedure for cases where the ratio of the length of the chain-termination zone to chain-initiation zone was less than the non-dimensional activation energy. To leading order, the steady CJ detonation was found to be unstable; higher-order corrections lead to the construction of a stability limit between stable and unsteady pulsating solutions. One conclusion from this study is that for a stability limit to occur at leading order, the period of pulsation of the detonation must occur on the time scale of particle passage through the longer chain-termination zone, while the length of the chain-termination zone must be of order of the non-dimensional activation energy longer than the chain-initiation zone. The relevance of these suggested scalings was verified via numerical solutions of the full Euler system in [3], and formed the basis of the stability parameter criteria suggested in [2]. In the following, we formulate an asymptotic study based on these new suggested scales, studying the implications for describing pulsating behavior in gaseous chain-branching detonations. Specifically, we find that the chain-induction zone structure is the same as that studied in [4]. However, the study of unsteady evolution in the chain-termination region is now governed by a set of asymptotically derived nonlinear POEs. Equations for the linear stablity behavior of this set of POE's is obtained, while the nonlinear POEs are solved numerically using a shock-attached, shock-fitting method developed by Henrick et aJ. [1]. The results thus far show that the stability threshold calculated using the new ratio of the chain-termination zone length to that of the chain-initiation zone yields a marked improvement over [2]. Additionally, solutions will be compared with predictions obtained from the solution of the full Euler system. Finally, the evolution equation previously derived in [4] has been generalized to consider both arbitrary reaction orders and any degree of overdrive.« less

Hybrid life-cycle assessment of natural gas based fuel chains for transportation.

PubMed

Strømman, Anders Hammer; Solli, Christian; Hertwich, Edgar G

2006-04-15

This research compares the use of natural gas, methanol, and hydrogen as transportation fuels. These three fuel chains start with the extraction and processing of natural gas in the Norwegian North Sea and end with final use in Central Europe. The end use is passenger transportation with a sub-compact car that has an internal combustion engine for the natural gas case and a fuel cell for the methanol and hydrogen cases. The life cycle assessment is performed by combining a process based life-cycle inventory with economic input-output data. The analysis shows that the potential climate impacts are lowest for the hydrogen fuel scenario with CO2 deposition. The hydrogen fuel chain scenario has no significant environmental disadvantage compared to the other fuel chains. Detailed analysis shows that the construction of the car contributes significantly to most impact categories. Finally, it is shown how the application of a hybrid inventory model ensures a more complete inventory description compared to standard process-based life-cycle assessment. This is particularly significant for car construction which would have been significantly underestimated in this study using standard process life-cycle assessment alone.

Research on Coordination of Fresh Produce Supply Chain in Big Market Sales Environment

PubMed Central

Su, Juning; Liu, Chenguang

2014-01-01

In this paper, we propose two decision models for decentralized and centralized fresh produce supply chains with stochastic supply and demand and controllable transportation time. The optimal order quantity and the optimal transportation time in these two supply chain systems are derived. To improve profits in a decentralized supply chain, based on analyzing the risk taken by each participant in the supply chain, we design a set of contracts which can coordinate this type of fresh produce supply chain with stochastic supply and stochastic demand, and controllable transportation time as well. We also obtain a value range of contract parameters that can increase profits of all participants in the decentralized supply chain. The expected profits of the decentralized setting and the centralized setting are compared with respect to given numerical examples. Furthermore, the sensitivity analyses of the deterioration rate factor and the freshness factor are performed. The results of numerical examples show that the transportation time is shorter, the order quantity is smaller, the total profit of whole supply chain is less, and the possibility of cooperation between supplier and retailer is higher for the fresh produce which is more perishable and its quality decays more quickly. PMID:24764770

Research on coordination of fresh produce supply chain in big market sales environment.

PubMed

Su, Juning; Wu, Jiebing; Liu, Chenguang

2014-01-01

In this paper, we propose two decision models for decentralized and centralized fresh produce supply chains with stochastic supply and demand and controllable transportation time. The optimal order quantity and the optimal transportation time in these two supply chain systems are derived. To improve profits in a decentralized supply chain, based on analyzing the risk taken by each participant in the supply chain, we design a set of contracts which can coordinate this type of fresh produce supply chain with stochastic supply and stochastic demand, and controllable transportation time as well. We also obtain a value range of contract parameters that can increase profits of all participants in the decentralized supply chain. The expected profits of the decentralized setting and the centralized setting are compared with respect to given numerical examples. Furthermore, the sensitivity analyses of the deterioration rate factor and the freshness factor are performed. The results of numerical examples show that the transportation time is shorter, the order quantity is smaller, the total profit of whole supply chain is less, and the possibility of cooperation between supplier and retailer is higher for the fresh produce which is more perishable and its quality decays more quickly.

Dynamic Game Behavior of Retailers Considering the Quality of Substitute Products Based on Delay Decision

NASA Astrophysics Data System (ADS)

Bao, Binshuo; Ma, Junhai

2017-12-01

Motivated by the Silk Road Economic Belt and the 21st-Century Maritime Silk Road project, i.e. the Belt and Road (B&R), more goods will flow around the world. With this trading platform, people can buy products at relatively cheap prices, and it is easier for people to buy various goods. The quality and quantity of products thus attract more and more attention in the supply chains. This paper discusses the quantity decision by considering the product quality in parallel supply chains where two manufacturers produce substitute products and then sell them to their downstream retailers separately. In terms of the changing quantity, as well as the different quality, this paper establishes a dynamic game model to explore the dynamic behavior when the optimal profits of two retailers have been calculated. The dynamic behaviors of the system, such as stable region, bifurcation and chaos, strange attractors and the largest Lyapunov exponents (LLE) are analyzed. The effect of the quantity adjustment parameter on the stability of the supply chain system is investigated through numerical simulations. Furthermore, a dynamic game model is established based on the quality delay decision, to investigate the influence of the quality delay parameter on the dynamic game model and the profits. Finally, the optimal decisions are obtained and analyzed.

Fitting mechanistic epidemic models to data: A comparison of simple Markov chain Monte Carlo approaches.

PubMed

Li, Michael; Dushoff, Jonathan; Bolker, Benjamin M

2018-07-01

Simple mechanistic epidemic models are widely used for forecasting and parameter estimation of infectious diseases based on noisy case reporting data. Despite the widespread application of models to emerging infectious diseases, we know little about the comparative performance of standard computational-statistical frameworks in these contexts. Here we build a simple stochastic, discrete-time, discrete-state epidemic model with both process and observation error and use it to characterize the effectiveness of different flavours of Bayesian Markov chain Monte Carlo (MCMC) techniques. We use fits to simulated data, where parameters (and future behaviour) are known, to explore the limitations of different platforms and quantify parameter estimation accuracy, forecasting accuracy, and computational efficiency across combinations of modeling decisions (e.g. discrete vs. continuous latent states, levels of stochasticity) and computational platforms (JAGS, NIMBLE, Stan).

A stochastic Markov chain model to describe lung cancer growth and metastasis.

PubMed

Newton, Paul K; Mason, Jeremy; Bethel, Kelly; Bazhenova, Lyudmila A; Nieva, Jorge; Kuhn, Peter

2012-01-01

A stochastic Markov chain model for metastatic progression is developed for primary lung cancer based on a network construction of metastatic sites with dynamics modeled as an ensemble of random walkers on the network. We calculate a transition matrix, with entries (transition probabilities) interpreted as random variables, and use it to construct a circular bi-directional network of primary and metastatic locations based on postmortem tissue analysis of 3827 autopsies on untreated patients documenting all primary tumor locations and metastatic sites from this population. The resulting 50 potential metastatic sites are connected by directed edges with distributed weightings, where the site connections and weightings are obtained by calculating the entries of an ensemble of transition matrices so that the steady-state distribution obtained from the long-time limit of the Markov chain dynamical system corresponds to the ensemble metastatic distribution obtained from the autopsy data set. We condition our search for a transition matrix on an initial distribution of metastatic tumors obtained from the data set. Through an iterative numerical search procedure, we adjust the entries of a sequence of approximations until a transition matrix with the correct steady-state is found (up to a numerical threshold). Since this constrained linear optimization problem is underdetermined, we characterize the statistical variance of the ensemble of transition matrices calculated using the means and variances of their singular value distributions as a diagnostic tool. We interpret the ensemble averaged transition probabilities as (approximately) normally distributed random variables. The model allows us to simulate and quantify disease progression pathways and timescales of progression from the lung position to other sites and we highlight several key findings based on the model.

Modelling Lean and Green Supply Chain

NASA Astrophysics Data System (ADS)

Duarte, Susana Carla Vieira Lino Medina

The success of an organization depends on the effective control of its supply chain. It is important to recognize new opportunities for organization and its supply chain. In the last few years the approach to lean, agile, resilient and green supply chain paradigms has been addressed in the scientific literature. Research in this field shows that the integration of these concepts revealed some contradictions among so many paradigms. This thesis is mainly focused on the lean and green approaches. Thirteen different management frameworks, embodied in awards, standards and tools were studied to understand if they could contribute for the modelling process of a lean and green approach. The study reveals a number of categories that are common in most management frameworks, providing adequate conditions for a lean and green supply chain transformation. A conceptual framework for the evaluation of a lean and green organization`s supply chain was proposed. The framework considers six key criteria, namely, leadership, people, strategic planning, stakeholders, processes and results. It was proposed an assessment method considering a criteria score for each criterion. The purpose is to understand how lean and green supply chain can be compatible, using principles, practices, techniques or tools (i.e. elements) that support both, a lean and a green approach, in all key criteria. A case study in the automotive upstream supply chain was performed to understand more deeply if the elements proposed for the conceptual framework could be implemented in a real-scenario. Based on the conceptual framework and the case study, a roadmap to achieve a lean-green transformation is presented. The proposed roadmap revealed its contribution to the understanding on how and when an organization`s supply chain should apply the lean and green elements. This study is relevant to practice, as it may assist managers in the adoption of a lean and green supply chain approach, giving insights for the implementation of a hybrid supply chain.

Graded, Dynamically Routable Information Processing with Synfire-Gated Synfire Chains.

PubMed

Wang, Zhuo; Sornborger, Andrew T; Tao, Louis

2016-06-01

Coherent neural spiking and local field potentials are believed to be signatures of the binding and transfer of information in the brain. Coherent activity has now been measured experimentally in many regions of mammalian cortex. Recently experimental evidence has been presented suggesting that neural information is encoded and transferred in packets, i.e., in stereotypical, correlated spiking patterns of neural activity. Due to their relevance to coherent spiking, synfire chains are one of the main theoretical constructs that have been appealed to in order to describe coherent spiking and information transfer phenomena. However, for some time, it has been known that synchronous activity in feedforward networks asymptotically either approaches an attractor with fixed waveform and amplitude, or fails to propagate. This has limited the classical synfire chain's ability to explain graded neuronal responses. Recently, we have shown that pulse-gated synfire chains are capable of propagating graded information coded in mean population current or firing rate amplitudes. In particular, we showed that it is possible to use one synfire chain to provide gating pulses and a second, pulse-gated synfire chain to propagate graded information. We called these circuits synfire-gated synfire chains (SGSCs). Here, we present SGSCs in which graded information can rapidly cascade through a neural circuit, and show a correspondence between this type of transfer and a mean-field model in which gating pulses overlap in time. We show that SGSCs are robust in the presence of variability in population size, pulse timing and synaptic strength. Finally, we demonstrate the computational capabilities of SGSC-based information coding by implementing a self-contained, spike-based, modular neural circuit that is triggered by streaming input, processes the input, then makes a decision based on the processed information and shuts itself down.

Ablation of ceramide synthase 2 exacerbates dextran sodium sulphate-induced colitis in mice due to increased intestinal permeability.

PubMed

Kim, Ye-Ryung; Volpert, Giora; Shin, Kyong-Oh; Kim, So-Yeon; Shin, Sun-Hye; Lee, Younghay; Sung, Sun Hee; Lee, Yong-Moon; Ahn, Jung-Hyuck; Pewzner-Jung, Yael; Park, Woo-Jae; Futerman, Anthony H; Park, Joo-Won

2017-12-01

Ceramides mediate crucial cellular processes including cell death and inflammation and have recently been implicated in inflammatory bowel disease. Ceramides consist of a sphingoid long-chain base to which fatty acids of various length can be attached. We now investigate the effect of alerting the ceramide acyl chain length on a mouse model of colitis. Ceramide synthase (CerS) 2 null mice, which lack very-long acyl chain ceramides with concomitant increase of long chain bases and C16-ceramides, were more susceptible to dextran sodium sulphate-induced colitis, and their survival rate was markedly decreased compared with that of wild-type littermates. Using mixed bone-marrow chimeric mice, we showed that the host environment is primarily responsible for intestinal barrier dysfunction and increased intestinal permeability. In the colon of CerS2 null mice, the expression of junctional adhesion molecule-A was markedly decreased and the phosphorylation of myosin light chain 2 was increased. In vitro experiments using Caco-2 cells also confirmed an important role of CerS2 in maintaining epithelial barrier function; CerS2-knockdown via CRISPR-Cas9 technology impaired barrier function. In vivo myriocin administration, which normalized long-chain bases and C16-ceramides of the colon of CerS2 null mice, increased intestinal permeability as measured by serum FITC-dextran levels, indicating that altered SLs including deficiency of very-long-chain ceramides are critical for epithelial barrier function. In conclusion, deficiency of CerS2 influences intestinal barrier function and the severity of experimental colitis and may represent a potential mechanism for inflammatory bowel disease pathogenesis. © 2017 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

A nonaffine network model for elastomers undergoing finite deformations

NASA Astrophysics Data System (ADS)

Davidson, Jacob D.; Goulbourne, N. C.

2013-08-01

In this work, we construct a new physics-based model of rubber elasticity to capture the strain softening, strain hardening, and deformation-state dependent response of rubber materials undergoing finite deformations. This model is unique in its ability to capture large-stretch mechanical behavior with parameters that are connected to the polymer chemistry and can also be easily identified with the important characteristics of the macroscopic stress-stretch response. The microscopic picture consists of two components: a crosslinked network of Langevin chains and an entangled network with chains confined to a nonaffine tube. These represent, respectively, changes in entropy due to thermally averaged chain conformations and changes in entropy due to the magnitude of these conformational fluctuations. A simple analytical form for the strain energy density is obtained using Rubinstein and Panyukov's single-chain description of network behavior. The model only depends on three parameters that together define the initial modulus, extent of strain softening, and the onset of strain hardening. Fits to large stretch data for natural rubber, silicone rubber, VHB 4905 (polyacrylate rubber), and b186 rubber (a carbon black-filled rubber) are presented, and a comparison is made with other similar constitutive models of large-stretch rubber elasticity. We demonstrate that the proposed model provides a complete description of elastomers undergoing large deformations for different applied loading configurations. Moreover, since the strain energy is obtained using a clear set of physical assumptions, this model may be tested and used to interpret the results of computer simulation and experiments on polymers of known microscopic structure.

Models and parameters for environmental radiological assessments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, C W

1984-01-01

This book presents a unified compilation of models and parameters appropriate for assessing the impact of radioactive discharges to the environment. Models examined include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Chapters have been entered separately into the data base. (ACR)

Towards early software reliability prediction for computer forensic tools (case study).

PubMed

Abu Talib, Manar

2016-01-01

Versatility, flexibility and robustness are essential requirements for software forensic tools. Researchers and practitioners need to put more effort into assessing this type of tool. A Markov model is a robust means for analyzing and anticipating the functioning of an advanced component based system. It is used, for instance, to analyze the reliability of the state machines of real time reactive systems. This research extends the architecture-based software reliability prediction model for computer forensic tools, which is based on Markov chains and COSMIC-FFP. Basically, every part of the computer forensic tool is linked to a discrete time Markov chain. If this can be done, then a probabilistic analysis by Markov chains can be performed to analyze the reliability of the components and of the whole tool. The purposes of the proposed reliability assessment method are to evaluate the tool's reliability in the early phases of its development, to improve the reliability assessment process for large computer forensic tools over time, and to compare alternative tool designs. The reliability analysis can assist designers in choosing the most reliable topology for the components, which can maximize the reliability of the tool and meet the expected reliability level specified by the end-user. The approach of assessing component-based tool reliability in the COSMIC-FFP context is illustrated with the Forensic Toolkit Imager case study.

A theoretical investigation of symmetry-origin unidirectional energy gradient in light-harvesting dendrimers.

PubMed

Koda, Shin-ichi

2016-03-21

We theoretically investigate a possibility that the symmetry of the repetitively branched structure of light-harvesting dendrimers creates the energy gradient descending toward inner generations (layers of pigment molecules) of the dendrimers. In the first half of this paper, we define a model system using the Frenkel exciton Hamiltonian that focuses only on the topology of dendrimers and numerically show that excitation energy tends to gather at inner generations of the model system at a thermal equilibrium state. This indicates that an energy gradient is formed in the model system. In the last half, we attribute this result to the symmetry of the model system and propose two symmetry-origin mechanisms creating the energy gradient. The present analysis and proposition are based on the theory of the linear chain (LC) decomposition [S. Koda, J. Chem. Phys. 142, 204112 (2015)], which equivalently transforms the model system into a set of one-dimensional systems on the basis of the symmetry of dendrimers. In the picture of the LC decomposition, we find that energy gradient is formed both in each linear chain and among linear chains, and these two mechanisms explain the numerical results well.

A theoretical investigation of symmetry-origin unidirectional energy gradient in light-harvesting dendrimers

NASA Astrophysics Data System (ADS)

Koda, Shin-ichi

2016-03-01

We theoretically investigate a possibility that the symmetry of the repetitively branched structure of light-harvesting dendrimers creates the energy gradient descending toward inner generations (layers of pigment molecules) of the dendrimers. In the first half of this paper, we define a model system using the Frenkel exciton Hamiltonian that focuses only on the topology of dendrimers and numerically show that excitation energy tends to gather at inner generations of the model system at a thermal equilibrium state. This indicates that an energy gradient is formed in the model system. In the last half, we attribute this result to the symmetry of the model system and propose two symmetry-origin mechanisms creating the energy gradient. The present analysis and proposition are based on the theory of the linear chain (LC) decomposition [S. Koda, J. Chem. Phys. 142, 204112 (2015)], which equivalently transforms the model system into a set of one-dimensional systems on the basis of the symmetry of dendrimers. In the picture of the LC decomposition, we find that energy gradient is formed both in each linear chain and among linear chains, and these two mechanisms explain the numerical results well.

Integration of environmental aspects in modelling and optimisation of water supply chains.

PubMed

Koleva, Mariya N; Calderón, Andrés J; Zhang, Di; Styan, Craig A; Papageorgiou, Lazaros G

2018-04-26

Climate change becomes increasingly more relevant in the context of water systems planning. Tools are necessary to provide the most economic investment option considering the reliability of the infrastructure from technical and environmental perspectives. Accordingly, in this work, an optimisation approach, formulated as a spatially-explicit multi-period Mixed Integer Linear Programming (MILP) model, is proposed for the design of water supply chains at regional and national scales. The optimisation framework encompasses decisions such as installation of new purification plants, capacity expansion, and raw water trading schemes. The objective is to minimise the total cost incurring from capital and operating expenditures. Assessment of available resources for withdrawal is performed based on hydrological balances, governmental rules and sustainable limits. In the light of the increasing importance of reliability of water supply, a second objective, seeking to maximise the reliability of the supply chains, is introduced. The epsilon-constraint method is used as a solution procedure for the multi-objective formulation. Nash bargaining approach is applied to investigate the fair trade-offs between the two objectives and find the Pareto optimality. The models' capability is addressed through a case study based on Australia. The impact of variability in key input parameters is tackled through the implementation of a rigorous global sensitivity analysis (GSA). The findings suggest that variations in water demand can be more disruptive for the water supply chain than scenarios in which rainfalls are reduced. The frameworks can facilitate governmental multi-aspect decision making processes for the adequate and strategic investments of regional water supply infrastructure. Copyright © 2018. Published by Elsevier B.V.

A model and simulation of fast space charge pulses in polymers

NASA Astrophysics Data System (ADS)

Lv, Zepeng; Rowland, Simon M.; Wu, Kai

2017-11-01

The transport of space charge packets across polyethylene and epoxy resin in high electric fields has been characterized as fast or slow depending on packet mobility. Several explanations for the formation and transport of slow space charge packets have been proposed, but the origins of fast space charge pulses, with mobilities above 10-11 m2 V-1 s-1, are unclear. In one suggested model, it is assumed that the formation of fast charge pulses is due to discontinuous electromechanical compression and charge injection at the electrode-insulation interface, and their transport is related to corresponding relaxation processes. In that model, charges travel as a pulse because of group polarization. This paper provides an alternative model based on the reduction of charge carrier activation energy due to charge density triggered polymer chain movement and subsequent chain relaxation times. The generation and transport of fast charge pulses are readily simulated by a bipolar charge transport model with three additional parameters: reduced activation energy, charge density threshold, and chain relaxation time. Such a model is shown to reproduce key features of fast space charge pulses including speed, duration, repetition rate and pulse size. This model provides the basis for a deep understanding of the physical origins of fast space charge pulses in polymers.

Controlling Synfire Chain by Inhibitory Synaptic Input

NASA Astrophysics Data System (ADS)

Shinozaki, Takashi; Câteau, Hideyuki; Urakubo, Hidetoshi; Okada, Masato

2007-04-01

The propagation of highly synchronous firings across neuronal networks, called the synfire chain, has been actively studied both theoretically and experimentally. The temporal accuracy and remarkable stability of the propagation have been repeatedly examined in previous studies. However, for such a mode of signal transduction to play a major role in processing information in the brain, the propagation should also be controlled dynamically and flexibly. Here, we show that inhibitory but not excitatory input can bidirectionally modulate the propagation, i.e., enhance or suppress the synchronous firings depending on the timing of the input. Our simulations based on the Hodgkin-Huxley neuron model demonstrate this bidirectional modulation and suggest that it should be achieved with any biologically inspired modeling. Our finding may help describe a concrete scenario of how multiple synfire chains lying in a neuronal network are appropriately controlled to perform significant information processing.

Sorting processes with energy-constrained comparisons*

NASA Astrophysics Data System (ADS)

Geissmann, Barbara; Penna, Paolo

2018-05-01

We study very simple sorting algorithms based on a probabilistic comparator model. In this model, errors in comparing two elements are due to (1) the energy or effort put in the comparison and (2) the difference between the compared elements. Such algorithms repeatedly compare and swap pairs of randomly chosen elements, and they correspond to natural Markovian processes. The study of these Markov chains reveals an interesting phenomenon. Namely, in several cases, the algorithm that repeatedly compares only adjacent elements is better than the one making arbitrary comparisons: in the long-run, the former algorithm produces sequences that are "better sorted". The analysis of the underlying Markov chain poses interesting questions as the latter algorithm yields a nonreversible chain, and therefore its stationary distribution seems difficult to calculate explicitly. We nevertheless provide bounds on the stationary distributions and on the mixing time of these processes in several restrictions.

Copula-based analysis of rhythm

NASA Astrophysics Data System (ADS)

García, J. E.; González-López, V. A.; Viola, M. L. Lanfredi

2016-06-01

In this paper we establish stochastic profiles of the rhythm for three languages: English, Japanese and Spanish. We model the increase or decrease of the acoustical energy, collected into three bands coming from the acoustic signal. The number of parameters needed to specify a discrete multivariate Markov chain grows exponentially with the order and dimension of the chain. In this case the size of the database is not large enough for a consistent estimation of the model. We apply a strategy to estimate a multivariate process with an order greater than the order achieved using standard procedures. The new strategy consist on obtaining a partition of the state space which is constructed from a combination of the partitions corresponding to the three marginal processes, one for each band of energy, and the partition coming from to the multivariate Markov chain. Then, all the partitions are linked using a copula, in order to estimate the transition probabilities.

A BENCHMARKING ANALYSIS FOR FIVE RADIONUCLIDE VADOSE ZONE MODELS (CHAIN, MULTIMED_DP, FECTUZ, HYDRUS, AND CHAIN 2D) IN SOIL SCREENING LEVEL CALCULATIONS

EPA Science Inventory

Five radionuclide vadose zone models with different degrees of complexity (CHAIN, MULTIMED_DP, FECTUZ, HYDRUS, and CHAIN 2D) were selected for use in soil screening level (SSL) calculations. A benchmarking analysis between the models was conducted for a radionuclide (99Tc) rele...

Collective effects on activated segmental relaxation in supercooled polymer melts

NASA Astrophysics Data System (ADS)

Mirigian, Stephen; Schweizer, Kenneth

2013-03-01

We extend the polymer nonlinear Langevin equation (NLE) theory of activated segmental dynamics in supercooled polymer melts in two new directions. First, a well-defined mapping from real monomers to a freely-jointed chain is formulated that retains information about chain stiffness, monomer volume, and the amplitude of thermal density fluctuations. Second, collective effects beyond the local cage scale are included based on an elastic solid-state perspective in the ``shoving model'' spirit which accounts for longer range contributions to the activation barrier. In contrast to previous phenomenological treatments of this model, we formulate an explicit microscopic picture of the hopping event, and derive, not assume, that the collective barrier is directly related to the elastic shear modulus. Local hopping is thus renormalized by collective motions of the surroundings that are required to physically accommodate it. Using the PRISM theory of structure, and known compressibility and chain statistics information, quantitative applications of the new theory to predict the temperature and chain length dependence of the alpha time, shear modulus, and fragility are carried out for a range of real polymer liquids and compared to experiment.

Catalytic Mechanism of Short Ethoxy Chain Nonylphenol Dehydrogenase Belonging to a Polyethylene Glycol Dehydrogenase Group in the GMC Oxidoreductase Family

PubMed Central

Liu, Xin; Ohta, Takeshi; Kawabata, Takeshi; Kawai, Fusako

2013-01-01

Ethoxy (EO) chain nonylphenol dehydrogenase (NPEO-DH) from Ensifer sp. AS08 and EO chain octylphenol dehydrogenase from Pseudomonas putida share common molecular characteristics with polyethylene glycol (PEG) dehydrogenases (PEG-DH) and comprise a PEG-DH subgroup in the family of glucose-methanol-choline (GMC) oxidoreductases that includes glucose/alcohol oxidase and glucose/choline dehydrogenase. Three-dimensional (3D) molecular modeling suggested that differences in the size, secondary structure and hydropathy in the active site caused differences in their substrate specificities toward EO chain alkylphenols and free PEGs. Based on 3D molecular modeling, site-directed mutagenesis was utilized to introduce mutations into potential catalytic residues of NPEO-DH. From steady state and rapid kinetic characterization of wild type and mutant NPEO-DHs, we can conclude that His465 and Asn507 are directly involved in the catalysis. Asn507 mediates the transfer of proton from a substrate to FAD and His465 transfers the same proton from the reduced flavin to an electron acceptor. PMID:23306149

Catalytic mechanism of short ethoxy chain nonylphenol dehydrogenase belonging to a polyethylene glycol dehydrogenase group in the GMC oxidoreductase family.

PubMed

Liu, Xin; Ohta, Takeshi; Kawabata, Takeshi; Kawai, Fusako

2013-01-10

Ethoxy (EO) chain nonylphenol dehydrogenase (NPEO-DH) from Ensifer sp. AS08 and EO chain octylphenol dehydrogenase from Pseudomonas putida share common molecular characteristics with polyethylene glycol (PEG) dehydrogenases (PEG-DH) and comprise a PEG-DH subgroup in the family of glucose-methanol-choline (GMC) oxidoreductases that includes glucose/alcohol oxidase and glucose/choline dehydrogenase. Three-dimensional (3D) molecular modeling suggested that differences in the size, secondary structure and hydropathy in the active site caused differences in their substrate specificities toward EO chain alkylphenols and free PEGs. Based on 3D molecular modeling, site-directed mutagenesis was utilized to introduce mutations into potential catalytic residues of NPEO-DH. From steady state and rapid kinetic characterization of wild type and mutant NPEO-DHs, we can conclude that His465 and Asn507 are directly involved in the catalysis. Asn507 mediates the transfer of proton from a substrate to FAD and His465 transfers the same proton from the reduced flavin to an electron acceptor.

Predicting hepatitis B monthly incidence rates using weighted Markov chains and time series methods.

PubMed

Shahdoust, Maryam; Sadeghifar, Majid; Poorolajal, Jalal; Javanrooh, Niloofar; Amini, Payam

2015-01-01

Hepatitis B (HB) is a major global mortality. Accurately predicting the trend of the disease can provide an appropriate view to make health policy disease prevention. This paper aimed to apply three different to predict monthly incidence rates of HB. This historical cohort study was conducted on the HB incidence data of Hamadan Province, the west of Iran, from 2004 to 2012. Weighted Markov Chain (WMC) method based on Markov chain theory and two time series models including Holt Exponential Smoothing (HES) and SARIMA were applied on the data. The results of different applied methods were compared to correct percentages of predicted incidence rates. The monthly incidence rates were clustered into two clusters as state of Markov chain. The correct predicted percentage of the first and second clusters for WMC, HES and SARIMA methods was (100, 0), (84, 67) and (79, 47) respectively. The overall incidence rate of HBV is estimated to decrease over time. The comparison of results of the three models indicated that in respect to existing seasonality trend and non-stationarity, the HES had the most accurate prediction of the incidence rates.

Distributed Algorithms for Probabilistic Solution of Computational Vision Problems.

DTIC Science & Technology

1988-03-01

34 targets. Legters and Young (1982) developed an operator-based approach r% using foreground and background models and solved a least-squares minimiza...1960), "Finite Markov Chains", Van Nostrand, , - New York. Legters , G.R., and Young, T.Y. (1982), "A Mathematical Model for Computer Image Tracking

Simple model of sickle hemogloblin

NASA Astrophysics Data System (ADS)

Shiryayev, Andrey; Li, Xiaofei; Gunton, J. D.

2006-07-01

A microscopic model is proposed for the interactions between sickle hemoglobin molecules based on information from the protein data bank. A solution of this model, however, requires accurate estimates of the interaction parameters which are currently unavailable. Therefore, as a first step toward a molecular understanding of the nucleation mechanisms in sickle hemoglobin, a Monte Carlo simulation of a simplified two patch model is carried out. A gradual transition from monomers to one dimensional chains is observed as one varies the density of molecules at fixed temperature, somewhat similar to the transition from monomers to polymer fibers in sickle hemoglobin molecules in solution. An observed competition between chain formation and crystallization for the model is also discussed. The results of the simulation of the equation of state are shown to be in excellent agreement with a theory for a model of globular proteins, for the case of two interacting sites.

Experimental observation of the 1/3 magnetization plateau in the diamond-chain compound Cu3(CO3)2(OH)2.

PubMed

Kikuchi, H; Fujii, Y; Chiba, M; Mitsudo, S; Idehara, T; Tonegawa, T; Okamoto, K; Sakai, T; Kuwai, T; Ohta, H

2005-06-10

The magnetic susceptibility, high field magnetization, and specific heat measurements of Cu3(CO3)2(OH)2, which is a model substance for the frustrating diamond spin chain model, have been performed using single crystals. Two broad peaks are observed at around 20 and 5 K in both magnetic susceptibility and specific heat results. The magnetization curve has a clear plateau at one third of the saturation magnetization. The experimental results are examined in terms of theoretical expectations based on exact diagonalization and density matrix renormalization group methods. An origin of magnetic anisotropy is also discussed.

An Agent-Based Modeling Approach for Determining Corn Stover Removal Rate and Transboundary Effects

NASA Astrophysics Data System (ADS)

Gan, Jianbang; Langeveld, J. W. A.; Smith, C. T.

2014-02-01

Bioenergy production involves different agents with potentially different objectives, and an agent's decision often has transboundary impacts on other agents along the bioenergy value chain. Understanding and estimating the transboundary impacts is essential to portraying the interactions among the different agents and in the search for the optimal configuration of the bioenergy value chain. We develop an agent-based model to mimic the decision making by feedstock producers and feedstock-to-biofuel conversion plant operators and propose multipliers (i.e., ratios of economic values accruing to different segments and associated agents in the value chain) for assessing the transboundary impacts. Our approach is generic and thus applicable to a variety of bioenergy production systems at different sites and geographic scales. We apply it to the case of producing ethanol using corn stover in Iowa, USA. The results from the case study indicate that stover removal rate is site specific and varies considerably with soil type, as well as other factors, such as stover price and harvesting cost. In addition, ethanol production using corn stover in the study region would have strong positive ripple effects, with the values of multipliers varying with greenhouse gas price and national energy security premium. The relatively high multiplier values suggest that a large portion of the value associated with corn stover ethanol production would accrue to the downstream end of the value chain instead of stover producers.

A temperature-dependent coarse-grained model for the thermoresponsive polymer poly(N-isopropylacrylamide)

DOE PAGES

Abbott, Lauren J.; Stevens, Mark J.

2015-12-22

In this study, a coarse-grained (CG) model is developed for the thermoresponsive polymer poly(N-isopropylacrylamide) (PNIPAM), using a hybrid top-down and bottom-up approach. Nonbonded parameters are fit to experimental thermodynamic data following the procedures of the SDK (Shinoda, DeVane, and Klein) CG force field, with minor adjustments to provide better agreement with radial distribution functions from atomistic simulations. Bonded parameters are fit to probability distributions from atomistic simulations using multi-centered Gaussian-based potentials. The temperature-dependent potentials derived for the PNIPAM CG model in this work properly capture the coil–globule transition of PNIPAM single chains and yield a chain-length dependence consistent with atomisticmore » simulations.« less

Free Energy Perturbation Calculations of the Thermodynamics of Protein Side-Chain Mutations.

PubMed

Steinbrecher, Thomas; Abel, Robert; Clark, Anthony; Friesner, Richard

2017-04-07

Protein side-chain mutation is fundamental both to natural evolutionary processes and to the engineering of protein therapeutics, which constitute an increasing fraction of important medications. Molecular simulation enables the prediction of the effects of mutation on properties such as binding affinity, secondary and tertiary structure, conformational dynamics, and thermal stability. A number of widely differing approaches have been applied to these predictions, including sequence-based algorithms, knowledge-based potential functions, and all-atom molecular mechanics calculations. Free energy perturbation theory, employing all-atom and explicit-solvent molecular dynamics simulations, is a rigorous physics-based approach for calculating thermodynamic effects of, for example, protein side-chain mutations. Over the past several years, we have initiated an investigation of the ability of our most recent free energy perturbation methodology to model the thermodynamics of protein mutation for two specific problems: protein-protein binding affinities and protein thermal stability. We highlight recent advances in the field and outline current and future challenges. Copyright © 2017 Elsevier Ltd. All rights reserved.

ℤ3 parafermionic chain emerging from Yang-Baxter equation.

PubMed

Yu, Li-Wei; Ge, Mo-Lin

2016-02-23

We construct the 1D ℤ3 parafermionic model based on the solution of Yang-Baxter equation and express the model by three types of fermions. It is shown that the ℤ3 parafermionic chain possesses both triple degenerate ground states and non-trivial topological winding number. Hence, the ℤ3 parafermionic model is a direct generalization of 1D ℤ2 Kitaev model. Both the ℤ2 and ℤ3 model can be obtained from Yang-Baxter equation. On the other hand, to show the algebra of parafermionic tripling intuitively, we define a new 3-body Hamiltonian H123 based on Yang-Baxter equation. Different from the Majorana doubling, the H123 holds triple degeneracy at each of energy levels. The triple degeneracy is protected by two symmetry operators of the system, ω-parity P [formula in text] and emergent parafermionic operator Γ, which are the generalizations of parity PM and emergent Majorana operator in Lee-Wilczek model, respectively. Both the ℤ3 parafermionic model and H123 can be viewed as SU(3) models in color space. In comparison with the Majorana models for SU(2), it turns out that the SU(3) models are truly the generalization of Majorana models resultant from Yang-Baxter equation.

Improved performance in CAPRI round 37 using LZerD docking and template-based modeling with combined scoring functions.

PubMed

Peterson, Lenna X; Shin, Woong-Hee; Kim, Hyungrae; Kihara, Daisuke

2018-03-01

We report our group's performance for protein-protein complex structure prediction and scoring in Round 37 of the Critical Assessment of PRediction of Interactions (CAPRI), an objective assessment of protein-protein complex modeling. We demonstrated noticeable improvement in both prediction and scoring compared to previous rounds of CAPRI, with our human predictor group near the top of the rankings and our server scorer group at the top. This is the first time in CAPRI that a server has been the top scorer group. To predict protein-protein complex structures, we used both multi-chain template-based modeling (TBM) and our protein-protein docking program, LZerD. LZerD represents protein surfaces using 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. Because 3DZD are a soft representation of the protein surface, LZerD is tolerant to small conformational changes, making it well suited to docking unbound and TBM structures. The key to our improved performance in CAPRI Round 37 was to combine multi-chain TBM and docking. As opposed to our previous strategy of performing docking for all target complexes, we used TBM when multi-chain templates were available and docking otherwise. We also describe the combination of multiple scoring functions used by our server scorer group, which achieved the top rank for the scorer phase. © 2017 Wiley Periodicals, Inc.

A reward semi-Markov process with memory for wind speed modeling

NASA Astrophysics Data System (ADS)

Petroni, F.; D'Amico, G.; Prattico, F.

2012-04-01

The increasing interest in renewable energy leads scientific research to find a better way to recover most of the available energy. Particularly, the maximum energy recoverable from wind is equal to 59.3% of that available (Betz law) at a specific pitch angle and when the ratio between the wind speed in output and in input is equal to 1/3. The pitch angle is the angle formed between the airfoil of the blade of the wind turbine and the wind direction. Old turbine and a lot of that actually marketed, in fact, have always the same invariant geometry of the airfoil. This causes that wind turbines will work with an efficiency that is lower than 59.3%. New generation wind turbines, instead, have a system to variate the pitch angle by rotating the blades. This system able the wind turbines to recover, at different wind speed, always the maximum energy, working in Betz limit at different speed ratios. A powerful system control of the pitch angle allows the wind turbine to recover better the energy in transient regime. A good stochastic model for wind speed is then needed to help both the optimization of turbine design and to assist the system control to predict the value of the wind speed to positioning the blades quickly and correctly. The possibility to have synthetic data of wind speed is a powerful instrument to assist designer to verify the structures of the wind turbines or to estimate the energy recoverable from a specific site. To generate synthetic data, Markov chains of first or higher order are often used [1,2,3]. In particular in [1] is presented a comparison between a first-order Markov chain and a second-order Markov chain. A similar work, but only for the first-order Markov chain, is conduced by [2], presenting the probability transition matrix and comparing the energy spectral density and autocorrelation of real and synthetic wind speed data. A tentative to modeling and to join speed and direction of wind is presented in [3], by using two models, first-order Markov chain with different number of states, and Weibull distribution. All this model use Markov chains to generate synthetic wind speed time series but the search for a better model is still open. Approaching this issue, we applied new models which are generalization of Markov models. More precisely we applied semi-Markov models to generate synthetic wind speed time series. The primary goal of this analysis is the study of the time history of the wind in order to assess its reliability as a source of power and to determine the associated storage levels required. In order to assess this issue we use a probabilistic model based on indexed semi-Markov process [4] to which a reward structure is attached. Our model is used to calculate the expected energy produced by a given turbine and its variability expressed by the variance of the process. Our results can be used to compare different wind farms based on their reward and also on the risk of missed production due to the intrinsic variability of the wind speed process. The model is used to generate synthetic time series for wind speed by means of Monte Carlo simulations and backtesting procedure is used to compare results on first and second oder moments of rewards between real and synthetic data. [1] A. Shamshad, M.A. Bawadi, W.M.W. Wan Hussin, T.A. Majid, S.A.M. Sanusi, First and second order Markov chain models for synthetic gen- eration of wind speed time series, Energy 30 (2005) 693-708. [2] H. Nfaoui, H. Essiarab, A.A.M. Sayigh, A stochastic Markov chain model for simulating wind speed time series at Tangiers, Morocco, Re- newable Energy 29 (2004) 1407-1418. [3] F. Youcef Ettoumi, H. Sauvageot, A.-E.-H. Adane, Statistical bivariate modeling of wind using first-order Markov chain and Weibull distribu- tion, Renewable Energy 28 (2003) 1787-1802. [4]F. Petroni, G. D'Amico, F. Prattico, Indexed semi-Markov process for wind speed modeling. To be submitted.

The parallel reaction monitoring method contributes to a highly sensitive polyubiquitin chain quantification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsuchiya, Hikaru; Tanaka, Keiji, E-mail: tanaka-kj@igakuken.or.jp; Saeki, Yasushi, E-mail: saeki-ys@igakuken.or.jp

2013-06-28

Highlights: •The parallel reaction monitoring method was applied to ubiquitin quantification. •The ubiquitin PRM method is highly sensitive even in biological samples. •Using the method, we revealed that Ufd4 assembles the K29-linked ubiquitin chain. -- Abstract: Ubiquitylation is an essential posttranslational protein modification that is implicated in a diverse array of cellular functions. Although cells contain eight structurally distinct types of polyubiquitin chains, detailed function of several chain types including K29-linked chains has remained largely unclear. Current mass spectrometry (MS)-based quantification methods are highly inefficient for low abundant atypical chains, such as K29- and M1-linked chains, in complex mixtures thatmore » typically contain highly abundant proteins. In this study, we applied parallel reaction monitoring (PRM), a quantitative, high-resolution MS method, to quantify ubiquitin chains. The ubiquitin PRM method allows us to quantify 100 attomole amounts of all possible ubiquitin chains in cell extracts. Furthermore, we quantified ubiquitylation levels of ubiquitin-proline-β-galactosidase (Ub-P-βgal), a historically known model substrate of the ubiquitin fusion degradation (UFD) pathway. In wild-type cells, Ub-P-βgal is modified with ubiquitin chains consisting of 21% K29- and 78% K48-linked chains. In contrast, K29-linked chains are not detected in UFD4 knockout cells, suggesting that Ufd4 assembles the K29-linked ubiquitin chain(s) on Ub-P-βgal in vivo. Thus, the ubiquitin PRM is a novel, useful, quantitative method for analyzing the highly complicated ubiquitin system.« less

Global surgery: A view from the south.

PubMed

Roy, Nobhojit

2017-02-01

This article is based on the Hugh Greenwood Lecture delivered at the 2016 Congress of the British Association of Paediatric Surgeons. It presents the view of the global surgery movement from the bottom of the surgical food chain and proposes what HICs (high-income countries) can do for global surgery in a coordinated fashion. From the LMIC (low- and middle-income countries) surgeon perspective, global surgery is transitioning from the charity-based surgery model to codevelopment with multiple stakeholders. The caveats and current opportunities are described using two case studies. Surgeons may not play a pivotal role in the solutions. The future of the surgical workforce, innovation, workarounds, unmet burden of disease, and health metrics are discussed and multidisciplinary solutions proposed for the entire chain of surgical healthcare delivery in LMIC. A new breed of "essential surgeons", technology solutions for intellectual and physical isolation, competency-based credentialing, industry-driven innovation, task sharing over task shifting, prioritizing delivery based on surgical burden, and a rota-based overseas model of help are proposed as solutions for the issues facing global surgery. Level V. Copyright © 2017 Elsevier Inc. All rights reserved.

How to fold a spin chain: Integrable boundaries of the Heisenberg XXX and Inozemtsev hyperbolic models

NASA Astrophysics Data System (ADS)

De La Rosa Gomez, Alejandro; MacKay, Niall; Regelskis, Vidas

2017-04-01

We present a general method of folding an integrable spin chain, defined on a line, to obtain an integrable open spin chain, defined on a half-line. We illustrate our method through two fundamental models with sl2 Lie algebra symmetry: the Heisenberg XXX and the Inozemtsev hyperbolic spin chains. We obtain new long-range boundary Hamiltonians and demonstrate that they exhibit Yangian symmetries, thus ensuring integrability of the models we obtain. The method presented provides a ;bottom-up; approach for constructing integrable boundaries and can be applied to any spin chain model.

Surface-induced effects in fluctuation-based measurements of single-polymer elasticity: A direct probe of the radius of gyration

NASA Astrophysics Data System (ADS)

Innes-Gold, Sarah N.; Morgan, Ian L.; Saleh, Omar A.

2018-03-01

Single-molecule measurements of polymer elasticity are powerful, direct probes of both biomolecular structure and principles of polymer physics. Recent work has revealed low-force regimes in which biopolymer elasticity is understood through blob-based scaling models. However, the small tensions required to observe these regimes have the potential to create measurement biases, particularly due to the increased interactions of the polymer chain with tethering surfaces. Here, we examine one experimentally observed bias, in which fluctuation-based estimates of elasticity report an unexpectedly low chain compliance. We show that the effect is in good agreement with predictions based on quantifying the exclusion effect of the surface through an image-method calculation of available polymer configurations. The analysis indicates that the effect occurs at an external tension inversely proportional to the polymer's zero-tension radius of gyration. We exploit this to demonstrate a self-consistent scheme for estimating the radius of gyration of the tethered polymer. This is shown in measurements of both hyaluronic acid and poly(ethylene glycol) chains.

Research on the exponential growth effect on network topology: Theoretical and empirical analysis

NASA Astrophysics Data System (ADS)

Li, Shouwei; You, Zongjun

Integrated circuit (IC) industry network has been built in Yangtze River Delta with the constant expansion of IC industry. The IC industry network grows exponentially with the establishment of new companies and the establishment of contacts with old firms. Based on preferential attachment and exponential growth, the paper presents the analytical results in which the vertices degree of scale-free network follows power-law distribution p(k)˜k‑γ (γ=2β+1) and parameter β satisfies 0.5≤β≤1. At the same time, we find that the preferential attachment takes place in a dynamic local world and the size of the dynamic local world is in direct proportion to the size of whole networks. The paper also gives the analytical results of no-preferential attachment and exponential growth on random networks. The computer simulated results of the model illustrate these analytical results. Through some investigations on the enterprises, this paper at first presents the distribution of IC industry, composition of industrial chain and service chain firstly. Then, the correlative network and its analysis of industrial chain and service chain are presented. The correlative analysis of the whole IC industry is also presented at the same time. Based on the theory of complex network, the analysis and comparison of industrial chain network and service chain network in Yangtze River Delta are provided in the paper.

Statistical theory for protein combinatorial libraries. Packing interactions, backbone flexibility, and the sequence variability of a main-chain structure.

PubMed

Kono, H; Saven, J G

2001-02-23

Combinatorial experiments provide new ways to probe the determinants of protein folding and to identify novel folding amino acid sequences. These types of experiments, however, are complicated both by enormous conformational complexity and by large numbers of possible sequences. Therefore, a quantitative computational theory would be helpful in designing and interpreting these types of experiment. Here, we present and apply a statistically based, computational approach for identifying the properties of sequences compatible with a given main-chain structure. Protein side-chain conformations are included in an atom-based fashion. Calculations are performed for a variety of similar backbone structures to identify sequence properties that are robust with respect to minor changes in main-chain structure. Rather than specific sequences, the method yields the likelihood of each of the amino acids at preselected positions in a given protein structure. The theory may be used to quantify the characteristics of sequence space for a chosen structure without explicitly tabulating sequences. To account for hydrophobic effects, we introduce an environmental energy that it is consistent with other simple hydrophobicity scales and show that it is effective for side-chain modeling. We apply the method to calculate the identity probabilities of selected positions of the immunoglobulin light chain-binding domain of protein L, for which many variant folding sequences are available. The calculations compare favorably with the experimentally observed identity probabilities.

Role of special cross-links in structure formation of bacterial DNA polymer

NASA Astrophysics Data System (ADS)

Agarwal, Tejal; Manjunath, G. P.; Habib, Farhat; Lakshmi Vaddavalli, Pavana; Chatterji, Apratim

2018-01-01

Using data from contact maps of the DNA-polymer of Escherichia coli (E. Coli) (at kilobase pair resolution) as an input to our model, we introduce cross-links between monomers in a bead-spring model of a ring polymer at very specific points along the chain. Via suitable Monte Carlo simulations, we show that the presence of these cross-links leads to a particular organization of the chain at large (micron) length scales of the DNA. We also investigate the structure of a ring polymer with an equal number of cross-links at random positions along the chain. We find that though the polymer does get organized at the large length scales, the nature of the organization is quite different from the organization observed with cross-links at specific biologically determined positions. We used the contact map of E. Coli bacteria which has around 4.6 million base pairs in a single circular chromosome. In our coarse-grained flexible ring polymer model, we used 4642 monomer beads and observed that around 80 cross-links are enough to induce the large-scale organization of the molecule accounting for statistical fluctuations caused by thermal energy. The length of a DNA chain even of a simple bacterial cell such as E. Coli is much longer than typical proteins, hence we avoided methods used to tackle protein folding problems. We define new suitable quantities to identify the large scale structure of a polymer chain with a few cross-links.

Effective S =2 antiferromagnetic spin chain in the salt (o -MePy-V)FeCl4

NASA Astrophysics Data System (ADS)

Iwasaki, Y.; Kida, T.; Hagiwara, M.; Kawakami, T.; Hosokoshi, Y.; Tamekuni, Y.; Yamaguchi, H.

2018-02-01

We present a model compound for the S =2 antiferromagnetic (AF) spin chain composed of the salt (o -MePy-V ) FeCl4 . Ab initio molecular-orbital calculations indicate the formation of a partially stacked two-dimensional (2D) spin model comprising five types of exchange interactions between S =1 /2 and S =5 /2 spins, which locate on verdazyl radical and Fe ion, respectively. The magnetic properties of the synthesized crystals indicate that the dominant interaction between the S =1 /2 and S =5 /2 spins stabilizes an S =2 spin in the low-temperature region, and an effective S =2 AF chain is formed for T ≪10 K and H <4 T. We explain the magnetization curve and electron-spin-resonance modes quantitatively based on the S =2 AF chain. At higher fields above quantitatively 4 T, the magnetization curve assumes two-thirds of the full saturation value for fields between 4 and 20 T, and approaches saturation at ˜40 T. The spin model in the high-field region can be considered as a quasi-2D S =1 /2 honeycomb lattice under an effective internal field caused by the fully polarized S =5 /2 spin.

Improved modeling of side-chain--base interactions and plasticity in protein--DNA interface design.

PubMed

Thyme, Summer B; Baker, David; Bradley, Philip

2012-06-08

Combinatorial sequence optimization for protein design requires libraries of discrete side-chain conformations. The discreteness of these libraries is problematic, particularly for long, polar side chains, since favorable interactions can be missed. Previously, an approach to loop remodeling where protein backbone movement is directed by side-chain rotamers predicted to form interactions previously observed in native complexes (termed "motifs") was described. Here, we show how such motif libraries can be incorporated into combinatorial sequence optimization protocols and improve native complex recapitulation. Guided by the motif rotamer searches, we made improvements to the underlying energy function, increasing recapitulation of native interactions. To further test the methods, we carried out a comprehensive experimental scan of amino acid preferences in the I-AniI protein-DNA interface and found that many positions tolerated multiple amino acids. This sequence plasticity is not observed in the computational results because of the fixed-backbone approximation of the model. We improved modeling of this diversity by introducing DNA flexibility and reducing the convergence of the simulated annealing algorithm that drives the design process. In addition to serving as a benchmark, this extensive experimental data set provides insight into the types of interactions essential to maintain the function of this potential gene therapy reagent. Published by Elsevier Ltd.

Differential cytotoxicity of long-chain bases for human oral gingival epithelial keratinocytes, oral fibroblasts, and dendritic cells.

PubMed

Mehalick, Leslie A; Poulsen, Christopher; Fischer, Carol L; Lanzel, Emily A; Bates, Amber M; Walters, Katherine S; Cavanaugh, Joseph E; Guthmiller, Janet M; Johnson, Georgia K; Wertz, Philip W; Brogden, Kim A

2015-12-01

Long-chain bases, found in the oral cavity, have potent antimicrobial activity against oral pathogens. In an article associated with this dataset, Poulson and colleagues determined the cytotoxicities of long-chain bases (sphingosine, dihydrosphingosine, and phytosphingosine) for human oral gingival epithelial (GE) keratinocytes, oral gingival fibroblasts (GF), dendritic cells (DC), and squamous cell carcinoma (SCC) cell lines [1]. Poulson and colleagues found that GE keratinocytes were more resistant to long-chain bases as compared to GF, DC, and SCC cell lines [1]. In this study, we assess the susceptibility of DC to lower concentrations of long chain bases. 0.2-10.0 µM long-chain bases and GML were not cytotoxic to DC; 40.0-80.0 µM long-chain bases, but not GML, were cytotoxic for DC; and 80.0 µM long-chain bases were cytotoxic to DC and induced cellular damage and death in less than 20 mins. Overall, the LD50 of long-chain bases for GE keratinocytes, GF, and DC were considerably higher than their minimal inhibitory concentrations for oral pathogens, a finding important to pursuing their future potential in treating periodontal and oral infections.

Improved packing of protein side chains with parallel ant colonies

PubMed Central

2014-01-01

Introduction The accurate packing of protein side chains is important for many computational biology problems, such as ab initio protein structure prediction, homology modelling, and protein design and ligand docking applications. Many of existing solutions are modelled as a computational optimisation problem. As well as the design of search algorithms, most solutions suffer from an inaccurate energy function for judging whether a prediction is good or bad. Even if the search has found the lowest energy, there is no certainty of obtaining the protein structures with correct side chains. Methods We present a side-chain modelling method, pacoPacker, which uses a parallel ant colony optimisation strategy based on sharing a single pheromone matrix. This parallel approach combines different sources of energy functions and generates protein side-chain conformations with the lowest energies jointly determined by the various energy functions. We further optimised the selected rotamers to construct subrotamer by rotamer minimisation, which reasonably improved the discreteness of the rotamer library. Results We focused on improving the accuracy of side-chain conformation prediction. For a testing set of 442 proteins, 87.19% of X1 and 77.11% of X12 angles were predicted correctly within 40° of the X-ray positions. We compared the accuracy of pacoPacker with state-of-the-art methods, such as CIS-RR and SCWRL4. We analysed the results from different perspectives, in terms of protein chain and individual residues. In this comprehensive benchmark testing, 51.5% of proteins within a length of 400 amino acids predicted by pacoPacker were superior to the results of CIS-RR and SCWRL4 simultaneously. Finally, we also showed the advantage of using the subrotamers strategy. All results confirmed that our parallel approach is competitive to state-of-the-art solutions for packing side chains. Conclusions This parallel approach combines various sources of searching intelligence and energy functions to pack protein side chains. It provides a frame-work for combining different inaccuracy/usefulness objective functions by designing parallel heuristic search algorithms. PMID:25474164

Analytic hierarchy process-based approach for selecting a Pareto-optimal solution of a multi-objective, multi-site supply-chain planning problem

NASA Astrophysics Data System (ADS)

Ayadi, Omar; Felfel, Houssem; Masmoudi, Faouzi

2017-07-01

The current manufacturing environment has changed from traditional single-plant to multi-site supply chain where multiple plants are serving customer demands. In this article, a tactical multi-objective, multi-period, multi-product, multi-site supply-chain planning problem is proposed. A corresponding optimization model aiming to simultaneously minimize the total cost, maximize product quality and maximize the customer satisfaction demand level is developed. The proposed solution approach yields to a front of Pareto-optimal solutions that represents the trade-offs among the different objectives. Subsequently, the analytic hierarchy process method is applied to select the best Pareto-optimal solution according to the preferences of the decision maker. The robustness of the solutions and the proposed approach are discussed based on a sensitivity analysis and an application to a real case from the textile and apparel industry.

Fragmentation-based QM/MM simulations: length dependence of chain dynamics and hydrogen bonding of polyethylene oxide and polyethylene in aqueous solutions.

PubMed

Li, Hui; Li, Wei; Li, Shuhua; Ma, Jing

2008-06-12

Molecular fragmentation quantum mechanics (QM) calculations have been combined with molecular mechanics (MM) to construct the fragmentation QM/MM method for simulations of dilute solutions of macromolecules. We adopt the electrostatics embedding QM/MM model, where the low-cost generalized energy-based fragmentation calculations are employed for the QM part. Conformation energy calculations, geometry optimizations, and Born-Oppenheimer molecular dynamics simulations of poly(ethylene oxide), PEO(n) (n = 6-20), and polyethylene, PE(n) ( n = 9-30), in aqueous solution have been performed within the framework of both fragmentation and conventional QM/MM methods. The intermolecular hydrogen bonding and chain configurations obtained from the fragmentation QM/MM simulations are consistent with the conventional QM/MM method. The length dependence of chain conformations and dynamics of PEO and PE oligomers in aqueous solutions is also investigated through the fragmentation QM/MM molecular dynamics simulations.

Managing perceived operational risk factors for effective supply-chain management

NASA Astrophysics Data System (ADS)

Sylla, Cheickna

2014-12-01

This research is part of a large scale comprehensive mathematical and empirical modeling investigation projects aimed at developing a better understanding of supply-chain risk management by offering a comprehensive framework including theoretical elements and empirical evidence based on managers' perception of improved organizational level of preparedness to safeguard against the threats of disruptions, delays and stoppage in the supply chain. More specifically, this paper reports the empirical investigation conducted using 92 companies in several eastern USA regions involved in international trades with global supply chains. Among the 56 general hypotheses investigated, the results support that managers strive to balance their control and decision impacts to mold their responses to risk factors with knowledge of the extent of cost consequences as stated in previous research. However, the results also propose new findings which significantly vary from previous research reports.

An efficient interpolation technique for jump proposals in reversible-jump Markov chain Monte Carlo calculations

PubMed Central

Farr, W. M.; Mandel, I.; Stevens, D.

2015-01-01

Selection among alternative theoretical models given an observed dataset is an important challenge in many areas of physics and astronomy. Reversible-jump Markov chain Monte Carlo (RJMCMC) is an extremely powerful technique for performing Bayesian model selection, but it suffers from a fundamental difficulty and it requires jumps between model parameter spaces, but cannot efficiently explore both parameter spaces at once. Thus, a naive jump between parameter spaces is unlikely to be accepted in the Markov chain Monte Carlo (MCMC) algorithm and convergence is correspondingly slow. Here, we demonstrate an interpolation technique that uses samples from single-model MCMCs to propose intermodel jumps from an approximation to the single-model posterior of the target parameter space. The interpolation technique, based on a kD-tree data structure, is adaptive and efficient in modest dimensionality. We show that our technique leads to improved convergence over naive jumps in an RJMCMC, and compare it to other proposals in the literature to improve the convergence of RJMCMCs. We also demonstrate the use of the same interpolation technique as a way to construct efficient ‘global’ proposal distributions for single-model MCMCs without prior knowledge of the structure of the posterior distribution, and discuss improvements that permit the method to be used in higher dimensional spaces efficiently. PMID:26543580

Modeling methodology for supply chain synthesis and disruption analysis

NASA Astrophysics Data System (ADS)

Wu, Teresa; Blackhurst, Jennifer

2004-11-01

The concept of an integrated or synthesized supply chain is a strategy for managing today's globalized and customer driven supply chains in order to better meet customer demands. Synthesizing individual entities into an integrated supply chain can be a challenging task due to a variety of factors including conflicting objectives, mismatched incentives and constraints of the individual entities. Furthermore, understanding the effects of disruptions occurring at any point in the system is difficult when working toward synthesizing supply chain operations. Therefore, the goal of this research is to present a modeling methodology to manage the synthesis of a supply chain by linking hierarchical levels of the system and to model and analyze disruptions in the integrated supply chain. The contribution of this research is threefold: (1) supply chain systems can be modeled hierarchically (2) the performance of synthesized supply chain system can be evaluated quantitatively (3) reachability analysis is used to evaluate the system performance and verify whether a specific state is reachable, allowing the user to understand the extent of effects of a disruption.

Modeling the Commuting Travel Activities within Historic Districts in Chinese Cities

PubMed Central

Yin, Fengjun; Hu, Qizhou

2014-01-01

The primary objective of this study is to analyze the characteristics of commuting activities within the historical districts in cities of China. The impacts of various explanatory variables on commuters' travels are evaluated using the structural equation modeling (SEM) approach. The household survey was conducted in the historical districts in Yangzhou, China. Based on the data, various individual and household attributes were considered exogenous variables, while the subsistence activity characteristics, travel times, numbers of three typical home-based trip chains, trip chains, and travel mode were considered as the endogenous variables. Commuters in our study were classified into two main groups according to their working location, which were the commuters in the historic district and those out of the district. The modeling results show that several individual and household attributes of commuters in historic district have significant impacts on the characteristics of travel activities. Additionally, the characteristics of travel activities within the two groups are quite different, and the contributing factors related to commuting travels are different as well. PMID:25435864

A PageRank-based reputation model for personalised manufacturing service recommendation

NASA Astrophysics Data System (ADS)

Zhang, W. Y.; Zhang, S.; Guo, S. S.

2017-05-01

The number of manufacturing services for cross-enterprise business collaborations is increasing rapidly because of the explosive growth of Web service technologies. This trend demands intelligent and robust models to address information overload in order to enable efficient discovery of manufacturing services. In this paper, we present a personalised manufacturing service recommendation approach, which combines a PageRank-based reputation model and a collaborative filtering technique in a unified framework for recommending the right manufacturing services to an active service user for supply chain deployment. The novel aspect of this research is adapting the PageRank algorithm to a network of service-oriented multi-echelon supply chain in order to determine both user reputation and service reputation. In addition, it explores the use of these methods in alleviating data sparsity and cold start problems that hinder traditional collaborative filtering techniques. A case study is conducted to validate the practicality and effectiveness of the proposed approach in recommending the right manufacturing services to active service users.

Modeling the commuting travel activities within historic districts in Chinese cities.

PubMed

Ye, Mao; Yu, Miao; Li, Zhibin; Yin, Fengjun; Hu, Qizhou

2014-01-01

The primary objective of this study is to analyze the characteristics of commuting activities within the historical districts in cities of China. The impacts of various explanatory variables on commuters' travels are evaluated using the structural equation modeling (SEM) approach. The household survey was conducted in the historical districts in Yangzhou, China. Based on the data, various individual and household attributes were considered exogenous variables, while the subsistence activity characteristics, travel times, numbers of three typical home-based trip chains, trip chains, and travel mode were considered as the endogenous variables. Commuters in our study were classified into two main groups according to their working location, which were the commuters in the historic district and those out of the district. The modeling results show that several individual and household attributes of commuters in historic district have significant impacts on the characteristics of travel activities. Additionally, the characteristics of travel activities within the two groups are quite different, and the contributing factors related to commuting travels are different as well.

Modeling and Computing of Stock Index Forecasting Based on Neural Network and Markov Chain

PubMed Central

Dai, Yonghui; Han, Dongmei; Dai, Weihui

2014-01-01

The stock index reflects the fluctuation of the stock market. For a long time, there have been a lot of researches on the forecast of stock index. However, the traditional method is limited to achieving an ideal precision in the dynamic market due to the influences of many factors such as the economic situation, policy changes, and emergency events. Therefore, the approach based on adaptive modeling and conditional probability transfer causes the new attention of researchers. This paper presents a new forecast method by the combination of improved back-propagation (BP) neural network and Markov chain, as well as its modeling and computing technology. This method includes initial forecasting by improved BP neural network, division of Markov state region, computing of the state transition probability matrix, and the prediction adjustment. Results of the empirical study show that this method can achieve high accuracy in the stock index prediction, and it could provide a good reference for the investment in stock market. PMID:24782659

Antioxidant efficacy of feruloyl glycerols in model membranes

USDA-ARS?s Scientific Manuscript database

Ferulic acid and its esters are known to be effective antioxidants. Ethyl ferulate was biocatalytically transesterified with triacylglycerols and long chain alcohols to form a series of lipid-based feruloyl esters: feruloylglycerol, diferuloylglycerol, feruloyldiacylglycerol, diferuloylacylglycerol...

Active learning of constitutive relation from mesoscopic dynamics for macroscopic modeling of non-Newtonian flows

NASA Astrophysics Data System (ADS)

Zhao, Lifei; Li, Zhen; Caswell, Bruce; Ouyang, Jie; Karniadakis, George Em

2018-06-01

We simulate complex fluids by means of an on-the-fly coupling of the bulk rheology to the underlying microstructure dynamics. In particular, a continuum model of polymeric fluids is constructed without a pre-specified constitutive relation, but instead it is actively learned from mesoscopic simulations where the dynamics of polymer chains is explicitly computed. To couple the bulk rheology of polymeric fluids and the microscale dynamics of polymer chains, the continuum approach (based on the finite volume method) provides the transient flow field as inputs for the (mesoscopic) dissipative particle dynamics (DPD), and in turn DPD returns an effective constitutive relation to close the continuum equations. In this multiscale modeling procedure, we employ an active learning strategy based on Gaussian process regression (GPR) to minimize the number of expensive DPD simulations, where adaptively selected DPD simulations are performed only as necessary. Numerical experiments are carried out for flow past a circular cylinder of a non-Newtonian fluid, modeled at the mesoscopic level by bead-spring chains. The results show that only five DPD simulations are required to achieve an effective closure of the continuum equations at Reynolds number Re = 10. Furthermore, when Re is increased to 100, only one additional DPD simulation is required for constructing an extended GPR-informed model closure. Compared to traditional message-passing multiscale approaches, applying an active learning scheme to multiscale modeling of non-Newtonian fluids can significantly increase the computational efficiency. Although the method demonstrated here obtains only a local viscosity from the polymer dynamics, it can be extended to other multiscale models of complex fluids whose macro-rheology is unknown.

New Model of Wood Cell Wall Microfibril and Its Implications

Treesearch

Umesh P. Agarwal; Sally A. Ralph; Rick S. Reiner; Carlos Baez

2015-01-01

Traditionally it has been accepted that the cell walls are made up of microfibrils which are partly crystalline. However, based on the recently obtained Raman evidence that showed that the interior of the microfibril was significantly disordered and water accessible, a new model is proposed. In this model, the molecular chains of cellulose are still organized along the...

BetaSCPWeb: side-chain prediction for protein structures using Voronoi diagrams and geometry prioritization.

PubMed

Ryu, Joonghyun; Lee, Mokwon; Cha, Jehyun; Laskowski, Roman A; Ryu, Seong Eon; Kim, Deok-Soo

2016-07-08

Many applications, such as protein design, homology modeling, flexible docking, etc. require the prediction of a protein's optimal side-chain conformations from just its amino acid sequence and backbone structure. Side-chain prediction (SCP) is an NP-hard energy minimization problem. Here, we present BetaSCPWeb which efficiently computes a conformation close to optimal using a geometry-prioritization method based on the Voronoi diagram of spherical atoms. Its outputs are visual, textual and PDB file format. The web server is free and open to all users at http://voronoi.hanyang.ac.kr/betascpweb with no login requirement. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Chaotic itinerancy and power-law residence time distribution in stochastic dynamical systems.

PubMed

Namikawa, Jun

2005-08-01

Chaotic itinerant motion among varieties of ordered states is described by a stochastic model based on the mechanism of chaotic itinerancy. The model consists of a random walk on a half-line and a Markov chain with a transition probability matrix. The stability of attractor ruin in the model is investigated by analyzing the residence time distribution of orbits at attractor ruins. It is shown that the residence time distribution averaged over all attractor ruins can be described by the superposition of (truncated) power-law distributions if the basin of attraction for each attractor ruin has a zero measure. This result is confirmed by simulation of models exhibiting chaotic itinerancy. Chaotic itinerancy is also shown to be absent in coupled Milnor attractor systems if the transition probability among attractor ruins can be represented as a Markov chain.

Lattice model simulation of interchain protein interactions and the folding dynamics and dimerization of the GCN4 Leucine zipper

NASA Astrophysics Data System (ADS)

Liu, Yanxin; Chapagain, Prem P.; Parra, Jose L.; Gerstman, Bernard S.

2008-01-01

The highest level in the hierarchy of protein structure and folding is the formation of protein complexes through protein-protein interactions. We have made modifications to a well established computer lattice model to expand its applicability to two-protein dimerization and aggregation. Based on Brownian dynamics, we implement translation and rotation moves of two peptide chains relative to each other, in addition to the intrachain motions already present in the model. We use this two-chain model to study the folding dynamics of the yeast transcription factor GCN4 leucine zipper. The calculated heat capacity curves agree well with experimental measurements. Free energy landscapes and median first passage times for the folding process are calculated and elucidate experimentally measured characteristics such as the multistate nature of the dimerization process.

Use of an ecosystem model for testing ecosystem response to inaccuracies of root and microflora productivity estimates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Petersen, H.; O'Neill, R.V.; Gardner, R.H.

1984-01-01

A seventy-compartment model for a Danish beech forest ecosystem is described in outline. The unmodified model predicts considerable accumulation of wood litter and decreasing accumulation through secondary to final decomposition products. Increment rates are similar for all components of the detritus based food chain. Modification of fine root production rate produces strong, positive response for root litter, and less, but still significant, response for detritus, humus and the components of the decomposer food chain. Increase of microbial biomass with adjustments of metabolism and production causes reduced accumulation of detritus and humus. The soil organisms respond according to food source. Themore » use of the model for testing the sensitivity of the ecosystem to inaccuracies of rroot- and microflora estimates is discussed. 21 references, 3 figures, 1 table.« less

Bayesian comparison of protein structures using partial Procrustes distance.

PubMed

Ejlali, Nasim; Faghihi, Mohammad Reza; Sadeghi, Mehdi

2017-09-26

An important topic in bioinformatics is the protein structure alignment. Some statistical methods have been proposed for this problem, but most of them align two protein structures based on the global geometric information without considering the effect of neighbourhood in the structures. In this paper, we provide a Bayesian model to align protein structures, by considering the effect of both local and global geometric information of protein structures. Local geometric information is incorporated to the model through the partial Procrustes distance of small substructures. These substructures are composed of β-carbon atoms from the side chains. Parameters are estimated using a Markov chain Monte Carlo (MCMC) approach. We evaluate the performance of our model through some simulation studies. Furthermore, we apply our model to a real dataset and assess the accuracy and convergence rate. Results show that our model is much more efficient than previous approaches.

Exploring the Dynamics and Modeling National Budget as a Supply Chain System: A Proposal for Reengineering the Budgeting Process and for Developing a Management Flight Simulator

DTIC Science & Technology

2012-09-01

Elmendorf, D. W., & Gregory Mankiw , N. (1999). Government debt. Handbook of Macroeconomics , 1, 1615-1669. European Union. European financial stability...budget process, based on the supply chain demand management process principles of operations and it is introduced the idea of developing a Budget... principles of systems dynamics, a proposal for the development of a Budget Management Flight Simulator, that will operate as a learning and educational

From single Debye-Hückel chains to polyelectrolyte solutions: Simulation results

NASA Astrophysics Data System (ADS)

Kremer, Kurt

1996-03-01

This lecture will present results from simulations of single weakly charged flexible chains, where the electrostatic part of the interaction is modeled by a Debye-Hückel potential,( with U. Micka, IFF, Forschungszentrum Jülich, 52425 Jülich, Germany) as well as simulations of polyelectrolyte solutions, where the counterions are explicitly taken into account( with M. J. Stevens, Sandia Nat. Lab., Albuquerque, NM 87185-1111) ( M. J. Stevens, K. Kremer, JCP 103), 1669 (1995). The first set of the simulations is meant to clear a recent contoversy on the dependency of the persistence length LP on the screening length Γ. While the analytic theories give Lp ~ Γ^x with either x=1 or x=2, the simulations find for all experimentally accessible chain lengths a varying exponent, which is significantly smaller than 1. This causes serious doubts on the applicability of this model for weakly charged polyelectrolytes in general. The second part deals with strongly charged flexible polyelectrolytes in salt free solution. These simulations are performed for multichain systems. The full Coulomb interactions of the monomers and counterions are treated explicitly. Experimental measurements of the osmotic pressure and the structure factor are reproduced and extended. The simulations reveal a new picture of the chain structure based on calculations of the structure factor, persistence length, end-to-end distance, etc. Even at very low density, the chains show significant bending. Furthermore, the chains contract significantly before they start to overlap. We also show that counterion condensation dramatically alters the chain structure, even for a good solvent backbone.

On geoid heights derived from GEOS 3 altimeter data along the Hawaiian-Emperor seamount chain

NASA Technical Reports Server (NTRS)

Watts, A. B.

1979-01-01

The geoid heights derived from preliminary GEOS 3 satellite radar altimeter data over the Hawaiian-Emperor seamount chain are examined. Two objectives are pursued: (1) to evaluate the contribution of the topography of the seamount chain and its compensation to the marine geoid; and (2) to determine whether geoid heights derived from GEOS 3 altimeter data can be used to provide information on isostasy at geological features such as the Hawaiian-Emperor seamount chain which formed as relatively young loads on the oceanic lithosphere. Short-wavelength geoid highs of 5-12 m over the crest of the seamount chain and geoid lows over flanking regions are observed. The geological undulations can be explained by a simple model in which the seamount-chain load is supported by a strong rigid lithospheric plate. The elastic thickness estimates agree with values based on surface ship gravity and bathymetry observations, and provide further support to the hypothesis that the elastic thickness acquired at a surface load depends on the temperature gradient of the lithosphere at the time of loading.

Chain conformational and physicochemical properties of fucoidans from sea cucumber.

PubMed

Xu, Xiaoqi; Xue, Changhu; Chang, Yaoguang; Wang, Jun; Jiang, Kunhao

2016-11-05

Although fucoidans from sea cucumber (SC-FUCs) have been proven as potential bioactive polysaccharides and functional food ingridents, their chain conformation and physicochemical properties were still poorly understood. This study investigated the chain conformation of fucoidans from sea cucumber Acaudina molpadioides (Am-FUC), Isostichopus badionotus (Ib-FUC) and Apostichopus japonicus (Aj-FUC), of which primary structure has been recently clarified. Chain conformation parameters demonstrated that studied SC-FUCs adopted random coil conformation in 150mM NaCl solution (pH 7.4). Based on the worm-like cylinder model and atomic force microscopy, the chain stiffness of SC-FUCs was further evaluated as Am-FUC≈Ib-FUC>Aj-FUC. It was suggested that the existence of branch structure increased the chain flexibility, while sulfated pattern exerted limited influence. SC-FUCs demonstrated shear-thinning rheological behavior and negative charge. Am-FUC possessed a higher thermostability than Ib-FUC and Aj-FUC. These results have important implications for understanding the molecular characteristics of SC-FUCs, which could facilitate their further application. Copyright © 2016 Elsevier Ltd. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Amy Cha-Tien; Downes, Paula Sue; Heinen, Russell

Analysis of chemical supply chains is an inherently complex task, given the dependence of these supply chains on multiple infrastructure systems (e.g., the petroleum sector, transportation, etc.). This effort requires data and information at various levels of resolution, ranging from network-level distribution systems to individual chemical reactions. Sandia National Laboratories (Sandia) has integrated its existing simulation and infrastructure analysis capabilities with chemical data models to analyze the chemical supply chains of several nationally critical chemical commodities. This paper describes how Sandia models the ethylene supply chain; that is, the supply chain for the most widely used raw material for plasticsmore » production including a description of the types of data and modeling capabilities that are required to represent the ethylene supply chain. The paper concludes with a description of Sandia's use the model to project how the supply chain would be affected by and adapt to a disruptive scenario hurricane.« less

Reinforcement learning in supply chains.

PubMed

Valluri, Annapurna; North, Michael J; Macal, Charles M

2009-10-01

Effective management of supply chains creates value and can strategically position companies. In practice, human beings have been found to be both surprisingly successful and disappointingly inept at managing supply chains. The related fields of cognitive psychology and artificial intelligence have postulated a variety of potential mechanisms to explain this behavior. One of the leading candidates is reinforcement learning. This paper applies agent-based modeling to investigate the comparative behavioral consequences of three simple reinforcement learning algorithms in a multi-stage supply chain. For the first time, our findings show that the specific algorithm that is employed can have dramatic effects on the results obtained. Reinforcement learning is found to be valuable in multi-stage supply chains with several learning agents, as independent agents can learn to coordinate their behavior. However, learning in multi-stage supply chains using these postulated approaches from cognitive psychology and artificial intelligence take extremely long time periods to achieve stability which raises questions about their ability to explain behavior in real supply chains. The fact that it takes thousands of periods for agents to learn in this simple multi-agent setting provides new evidence that real world decision makers are unlikely to be using strict reinforcement learning in practice.

Interactions of Aqueous Imidazolium-Based Ionic Liquid Mixtures with Solid-Supported Phospholipid Vesicles

PubMed Central

Losada-Pérez, Patricia; Khorshid, Mehran; Renner, Frank Uwe

2016-01-01

Despite the environmentally friendly reputation of ionic liquids (ILs), their safety has been recently questioned given their potential as cytotoxic agents. The fundamental mechanisms underlying the interactions between ILs and cells are less studied and by far not completely understood. Biomimetic films are here important biophysical model systems to elucidate fundamental aspects and mechanisms relevant for a large range of biological interaction ranging from signaling to drug reception or toxicity. Here we use dissipative quartz crystal microbalance QCM-D to examine the effect of aqueous imidazolium-based ionic liquid mixtures on solid-supported biomimetic membranes. Specifically, we assess in real time the effect of the cation chain length and the anion nature on a supported vesicle layer of the model phospholipid DMPC. Results indicate that interactions are mainly driven by the hydrophobic components of the IL, which significantly distort the layer and promote vesicle rupture. Our analyses evidence the gradual decrease of the main phase transition temperature upon increasing IL concentration, reflecting increased disorder by weakening of lipid chain interactions. The degree of rupture is significant for ILs with long hydrophobic cation chains and large hydrophobic anions whose behavior is reminiscent of that of antimicrobial peptides. PMID:27684947

Flexibility evaluation of multiechelon supply chains.

PubMed

Almeida, João Flávio de Freitas; Conceição, Samuel Vieira; Pinto, Luiz Ricardo; de Camargo, Ricardo Saraiva; Júnior, Gilberto de Miranda

2018-01-01

Multiechelon supply chains are complex logistics systems that require flexibility and coordination at a tactical level to cope with environmental uncertainties in an efficient and effective manner. To cope with these challenges, mathematical programming models are developed to evaluate supply chain flexibility. However, under uncertainty, supply chain models become complex and the scope of flexibility analysis is generally reduced. This paper presents a unified approach that can evaluate the flexibility of a four-echelon supply chain via a robust stochastic programming model. The model simultaneously considers the plans of multiple business divisions such as marketing, logistics, manufacturing, and procurement, whose goals are often conflicting. A numerical example with deterministic parameters is presented to introduce the analysis, and then, the model stochastic parameters are considered to evaluate flexibility. The results of the analysis on supply, manufacturing, and distribution flexibility are presented. Tradeoff analysis of demand variability and service levels is also carried out. The proposed approach facilitates the adoption of different management styles, thus improving supply chain resilience. The model can be extended to contexts pertaining to supply chain disruptions; for example, the model can be used to explore operation strategies when subtle events disrupt supply, manufacturing, or distribution.

Flexibility evaluation of multiechelon supply chains

PubMed Central

Conceição, Samuel Vieira; Pinto, Luiz Ricardo; de Camargo, Ricardo Saraiva; Júnior, Gilberto de Miranda

2018-01-01

Multiechelon supply chains are complex logistics systems that require flexibility and coordination at a tactical level to cope with environmental uncertainties in an efficient and effective manner. To cope with these challenges, mathematical programming models are developed to evaluate supply chain flexibility. However, under uncertainty, supply chain models become complex and the scope of flexibility analysis is generally reduced. This paper presents a unified approach that can evaluate the flexibility of a four-echelon supply chain via a robust stochastic programming model. The model simultaneously considers the plans of multiple business divisions such as marketing, logistics, manufacturing, and procurement, whose goals are often conflicting. A numerical example with deterministic parameters is presented to introduce the analysis, and then, the model stochastic parameters are considered to evaluate flexibility. The results of the analysis on supply, manufacturing, and distribution flexibility are presented. Tradeoff analysis of demand variability and service levels is also carried out. The proposed approach facilitates the adoption of different management styles, thus improving supply chain resilience. The model can be extended to contexts pertaining to supply chain disruptions; for example, the model can be used to explore operation strategies when subtle events disrupt supply, manufacturing, or distribution. PMID:29584755

A Model for Administrative Evaluation by Subordinates.

ERIC Educational Resources Information Center

Budig, Jeanne E.

Under the administrator evaluation program adopted at Vincennes University, all faculty and professional staff are invited to evaluate each administrator above them in the chain of command. Originally based on the Purdue University "cafeteria" system, this evaluation model has been used biannually for 10 years. In an effort to simplify the system,…

Primitive-path statistics of entangled polymers: mapping multi-chain simulations onto single-chain mean-field models

NASA Astrophysics Data System (ADS)

Steenbakkers, Rudi J. A.; Tzoumanekas, Christos; Li, Ying; Liu, Wing Kam; Kröger, Martin; Schieber, Jay D.

2014-01-01

We present a method to map the full equilibrium distribution of the primitive-path (PP) length, obtained from multi-chain simulations of polymer melts, onto a single-chain mean-field ‘target’ model. Most previous works used the Doi-Edwards tube model as a target. However, the average number of monomers per PP segment, obtained from multi-chain PP networks, has consistently shown a discrepancy of a factor of two with respect to tube-model estimates. Part of the problem is that the tube model neglects fluctuations in the lengths of PP segments, the number of entanglements per chain and the distribution of monomers among PP segments, while all these fluctuations are observed in multi-chain simulations. Here we use a recently proposed slip-link model, which includes fluctuations in all these variables as well as in the spatial positions of the entanglements. This turns out to be essential to obtain qualitative and quantitative agreement with the equilibrium PP-length distribution obtained from multi-chain simulations. By fitting this distribution, we are able to determine two of the three parameters of the model, which govern its equilibrium properties. This mapping is executed for four different linear polymers and for different molecular weights. The two parameters are found to depend on chemistry, but not on molecular weight. The model predicts a constant plateau modulus minus a correction inversely proportional to molecular weight. The value for well-entangled chains, with the parameters determined ab initio, lies in the range of experimental data for the materials investigated.

Whole Protein Native Fitness Potentials

NASA Astrophysics Data System (ADS)

Faraggi, Eshel; Kloczkowski, Andrzej

2013-03-01

Protein structure prediction can be separated into two tasks: sample the configuration space of the protein chain, and assign a fitness between these hypothetical models and the native structure of the protein. One of the more promising developments in this area is that of knowledge based energy functions. However, standard approaches using pair-wise interactions have shown shortcomings demonstrated by the superiority of multi-body-potentials. These shortcomings are due to residue pair-wise interaction being dependent on other residues along the chain. We developed a method that uses whole protein information filtered through machine learners to score protein models based on their likeness to native structures. For all models we calculated parameters associated with the distance to the solvent and with distances between residues. These parameters, in addition to energy estimates obtained by using a four-body-potential, DFIRE, and RWPlus were used as training for machine learners to predict the fitness of the models. Testing on CASP 9 targets showed that our method is superior to DFIRE, RWPlus, and the four-body potential, which are considered standards in the field.

Steric interactions determine side-chain conformations in protein cores.

PubMed

Caballero, D; Virrueta, A; O'Hern, C S; Regan, L

2016-09-01

We investigate the role of steric interactions in defining side-chain conformations in protein cores. Previously, we explored the strengths and limitations of hard-sphere dipeptide models in defining sterically allowed side-chain conformations and recapitulating key features of the side-chain dihedral angle distributions observed in high-resolution protein structures. Here, we show that modeling residues in the context of a particular protein environment, with both intra- and inter-residue steric interactions, is sufficient to specify which of the allowed side-chain conformations is adopted. This model predicts 97% of the side-chain conformations of Leu, Ile, Val, Phe, Tyr, Trp and Thr core residues to within 20°. Although the hard-sphere dipeptide model predicts the observed side-chain dihedral angle distributions for both Thr and Ser, the model including the protein environment predicts side-chain conformations to within 20° for only 60% of core Ser residues. Thus, this approach can identify the amino acids for which hard-sphere interactions alone are sufficient and those for which additional interactions are necessary to accurately predict side-chain conformations in protein cores. We also show that our approach can predict alternate side-chain conformations of core residues, which are supported by the observed electron density. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Comparative assessment of the global fate and transport pathways of long-chain perfluorocarboxylic acids (PFCAs) and perfluorocarboxylates (PFCs) emitted from direct sources.

PubMed

Armitage, James M; Macleod, Matthew; Cousins, Ian T

2009-08-01

A global-scale multispecies mass balance model was used to simulate the long-term fate and transport of perfluorocarboxylic acids (PFCAs) with eight to thirteen carbons (C8-C13) and their conjugate bases, the perfluorocarboxylates (PFCs). The main purpose of this study was to assess the relative long-range transport (LRT) potential of each conjugate pair, collectively termed PFC(A)s, considering emissions from direct sources (i.e., manufacturing and use) only. Overall LRT potential (atmospheric + oceanic) varied as a function of chain length and depended on assumptions regarding pKa and mode of entry. Atmospheric transport makes a relatively higher contribution to overall LRT potential for PFC(A)s with longer chain length, which reflects the increasing trend in the air-water partition coefficient (K(AW)) of the neutral PFCA species with chain length. Model scenarios using estimated direct emissions of the C8, C9, and C11 PFC(A)s indicate that the mass fluxes to the Arctic marine environment associated with oceanic transport are in excess of mass fluxes from indirect sources (i.e., atmospheric transport of precursor substances such as fluorotelomer alcohols and subsequent degradation to PFCAs). Modeled concentrations of C8 and C9 in the abiotic environment are broadly consistent with available monitoring data in surface ocean waters. Furthermore, the modeled concentration ratios of C8 to C9 are reconcilable with the homologue pattern frequently observed in biota, assuming a positive correlation between bioaccumulation potential and chain length. Modeled concentration ratios of C11 to C10 are more difficult to reconcile with monitoring data in both source and remote regions. Our model results for C11 and C10 therefore imply that either (i) indirect sources are dominant or (ii) estimates of direct emission are not accurate for these homologues.

Finding the Missing Physics: Simulating Polydisperse Polymer Melts

NASA Astrophysics Data System (ADS)

Rorrer, Nichoals; Dorgan, John

2014-03-01

A Monte Carlo algorithm has been developed to model polydisperse polymer melts. For the first time, this enables the specification of a predetermined molecular weight distribution for lattice based simulations. It is demonstrated how to map an arbitrary probability distributions onto a discrete number of chains residing on an fcc lattice. The resulting algorithm is able to simulate a wide variety of behaviors for polydisperse systems including confinement effects, shear flow, and parabolic flow. The dynamic version of the algorithm accurately captures Rouse dynamics for short polymer chains, and reptation-like dynamics for longer chain lengths.1 When polydispersity is introduced, smaller Rouse times and broadened the transition between different scaling regimes are observed. Rouse times also decrease under confinement for both polydisperse and monodisperse systems and chain length dependent migration effects are observed. The steady-state version of the algorithm enables the simulation of flow and when polydisperse systems are subject to parabolic (Poiseulle) flow, a migration phenomenon based on chain length is again present. These and other phenomena highlight the importance of including polydispersity in obtaining physically realistic simulations of polymeric melts. 1. Dorgan, J.R.; Rorrer, N.A.; Maupin, C.M., Macromolecules 2012, 45(21), 8833-8840. Work funded by the Fluid Dynamics program of the National Science Foundation under grant CBET-1067707.

The effects of chain length, embedded polar groups, pressure, and pore shape on structure and retention in reversed-phase liquid chromatography: molecular-level insights from Monte Carlo simulations.

PubMed

Rafferty, Jake L; Siepmann, J Ilja; Schure, Mark R

2009-03-20

Particle-based simulations using the configurational-bias and Gibbs ensemble Monte Carlo techniques are carried out to probe the effects of various chromatographic parameters on bonded-phase chain conformation, solvent penetration, and retention in reversed-phase liquid chromatography (RPLC). Specifically, we investigate the effects due to the length of the bonded-phase chains (C(18), C(8), and C(1)), the inclusion of embedded polar groups (amide and ether) near the base of the bonded-phase chains, the column pressure (1, 400, and 1000 atm), and the pore shape (planar slit pore versus cylindrical pore with a 60A diameter). These simulations utilize a bonded-phase coverage of 2.9 micromol/m(2)and a mobile phase containing methanol at a molfraction of 33% (about 50% by volume). The simulations show that chain length, embedded polar groups, and pore shape significantly alter structural and retentive properties of the model RPLC system, whereas the column pressure has a relatively small effect. The simulation results are extensively compared to retention measurements. A molecular view of the RPLC retention mechanism emerges that is more complex than can be inferred from thermodynamic measurements.

Bayesian inversion of seismic and electromagnetic data for marine gas reservoir characterization using multi-chain Markov chain Monte Carlo sampling

NASA Astrophysics Data System (ADS)

Ren, Huiying; Ray, Jaideep; Hou, Zhangshuan; Huang, Maoyi; Bao, Jie; Swiler, Laura

2017-12-01

In this study we developed an efficient Bayesian inversion framework for interpreting marine seismic Amplitude Versus Angle and Controlled-Source Electromagnetic data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis and Adaptive Metropolis samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and Controlled-Source Electromagnetic data. The multi-chain Markov-chain Monte Carlo is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration, the approach is used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic Amplitude Versus Angle and Controlled-Source Electromagnetic joint inversion provides better estimation of reservoir saturations than the seismic Amplitude Versus Angle only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated - reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.

An automated method for modeling proteins on known templates using distance geometry.

PubMed

Srinivasan, S; March, C J; Sudarsanam, S

1993-02-01

We present an automated method incorporated into a software package, FOLDER, to fold a protein sequence on a given three-dimensional (3D) template. Starting with the sequence alignment of a family of homologous proteins, tertiary structures are modeled using the known 3D structure of one member of the family as a template. Homologous interatomic distances from the template are used as constraints. For nonhomologous regions in the model protein, the lower and the upper bounds for the interatomic distances are imposed by steric constraints and the globular dimensions of the template, respectively. Distance geometry is used to embed an ensemble of structures consistent with these distance bounds. Structures are selected from this ensemble based on minimal distance error criteria, after a penalty function optimization step. These structures are then refined using energy optimization methods. The method is tested by simulating the alpha-chain of horse hemoglobin using the alpha-chain of human hemoglobin as the template and by comparing the generated models with the crystal structure of the alpha-chain of horse hemoglobin. We also test the packing efficiency of this method by reconstructing the atomic positions of the interior side chains beyond C beta atoms of a protein domain from a known 3D structure. In both test cases, models retain the template constraints and any additionally imposed constraints while the packing of the interior residues is optimized with no short contacts or bond deformations. To demonstrate the use of this method in simulating structures of proteins with nonhomologous disulfides, we construct a model of murine interleukin (IL)-4 using the NMR structure of human IL-4 as the template. The resulting geometry of the nonhomologous disulfide in the model structure for murine IL-4 is consistent with standard disulfide geometry.

Modeling the SOA Forming Potential of Substituted Dihydrofurans from Alkane + OH Reactions in the Atmosphere

NASA Astrophysics Data System (ADS)

Jordan, C. E.; Griffin, R. J.; Lim, Y. B.; Ziemann, P. J.; Atkinson, R.; Arey, J.

2005-12-01

Recent laboratory studies show that δ-hydroxycarbonyls formed in the atmosphere via OH-initiated reactions with alkanes can cyclize then dehydrate to form substituted dihydrofurans. These dihydrofurans are highly reactive, with lifetimes in the atmosphere of 1.3 h (OH), 24 s (NO3), and 7 min (O3). The ability of the δ-hydroxycarbonyls to cyclize and dehydrate has been shown to increase with increasing carbon number. Recent laboratory results show that the secondary organic aerosol (SOA) yields from alkanes also increase with carbon number reaching ~53% for C15. The reaction mechanism proposed based on the chamber results is the basis of the modeling study presented here. We have incorporated this proposed mechanism into the Caltech Atmospheric Chemistry Mechanism (CACM). For computational reasons, similar compounds are lumped together and represented by a single suitable compound. In the present case, alkanes are lumped into 3 groups: short chains (≤C6), medium chains (C7 - C12), and long chains (≥C13). SOA yields obtained in chamber studies increase dramatically from 0.5% for C8 to 25% for C12. The most dramatic increase is observed from C11 (8%) to C13 (~50%). This is attributed to the low volatility of first generation products contributing to the SOA from longer chain alkanes. Here we have studied OH reactions with the substituted dihydrofurans for medium (represented by C10) and long (represented by C16) chain alkanes using CACM along with the aerosol partitioning module MPMPO (Model to Predict the Multi-phase Partitioning of Organics). We will present the results of this modeling study, characterizing the influence of substituted dihydrofurans on the SOA forming potential of alkanes.

Differential cytotoxicity of long-chain bases for human oral gingival epithelial keratinocytes, oral fibroblasts, and dendritic cells

PubMed Central

Mehalick, Leslie A.; Poulsen, Christopher; Fischer, Carol L.; Lanzel, Emily A.; Bates, Amber M.; Walters, Katherine S.; Cavanaugh, Joseph E.; Guthmiller, Janet M.; Johnson, Georgia K.; Wertz, Philip W.; Brogden, Kim A.

2015-01-01

Long-chain bases, found in the oral cavity, have potent antimicrobial activity against oral pathogens. In an article associated with this dataset, Poulson and colleagues determined the cytotoxicities of long-chain bases (sphingosine, dihydrosphingosine, and phytosphingosine) for human oral gingival epithelial (GE) keratinocytes, oral gingival fibroblasts (GF), dendritic cells (DC), and squamous cell carcinoma (SCC) cell lines [1]. Poulson and colleagues found that GE keratinocytes were more resistant to long-chain bases as compared to GF, DC, and SCC cell lines [1]. In this study, we assess the susceptibility of DC to lower concentrations of long chain bases. 0.2–10.0 µM long-chain bases and GML were not cytotoxic to DC; 40.0–80.0 µM long-chain bases, but not GML, were cytotoxic for DC; and 80.0 µM long-chain bases were cytotoxic to DC and induced cellular damage and death in less than 20 mins. Overall, the LD50 of long-chain bases for GE keratinocytes, GF, and DC were considerably higher than their minimal inhibitory concentrations for oral pathogens, a finding important to pursuing their future potential in treating periodontal and oral infections. PMID:26550599

Effects of Acids, Bases, and Heteroatoms on Proximal Radial Distribution Functions for Proteins.

PubMed

Nguyen, Bao Linh; Pettitt, B Montgomery

2015-04-14

The proximal distribution of water around proteins is a convenient method of quantifying solvation. We consider the effect of charged and sulfur-containing amino acid side-chain atoms on the proximal radial distribution function (pRDF) of water molecules around proteins using side-chain analogs. The pRDF represents the relative probability of finding any solvent molecule at a distance from the closest or surface perpendicular protein atom. We consider the near-neighbor distribution. Previously, pRDFs were shown to be universal descriptors of the water molecules around C, N, and O atom types across hundreds of globular proteins. Using averaged pRDFs, a solvent density around any globular protein can be reconstructed with controllable relative error. Solvent reconstruction using the additional information from charged amino acid side-chain atom types from both small models and protein averages reveals the effects of surface charge distribution on solvent density and improves the reconstruction errors relative to simulation. Solvent density reconstructions from the small-molecule models are as effective and less computationally demanding than reconstructions from full macromolecular models in reproducing preferred hydration sites and solvent density fluctuations.

Orthogonal use of a human tRNA synthetase active site to achieve multi-functionality

PubMed Central

Zhou, Quansheng; Kapoor, Mili; Guo, Min; Belani, Rajesh; Xu, Xiaoling; Kiosses, William B.; Hanan, Melanie; Park, Chulho; Armour, Eva; Do, Minh-Ha; Nangle, Leslie A.; Schimmel, Paul; Yang, Xiang-Lei

2011-01-01

Protein multi-functionality is an emerging explanation for the complexity of higher organisms. In this regard, while aminoacyl tRNA synthetases catalyze amino acid activation for protein synthesis, some also act in pathways for inflammation, angiogenesis, and apoptosis. How multiple functions evolved and their relationship to the active site is not clear. Here structural modeling analysis, mutagenesis, and cell-based functional studies show that the potent angiostatic, natural fragment of human TrpRS associates via Trp side chains that protrude from the cognate cellular receptor VE-cadherin. Modeling indicates that (I prefer the way it was because the conclusion was reached not only by modeling, but more so by experimental studies.)VE-cadherin Trp side chains fit into the Trp-specific active site of the synthetase. Thus, specific side chains of the receptor mimic (?) amino acid substrates and expand the functionality of the active site of the synthetase. We propose that orthogonal use of the same active site may be a general way to develop multi-functionality of human tRNA synthetases and other proteins. PMID:20010843

Differential cytotoxicity of long-chain bases for human oral gingival epithelial keratinocytes, oral fibroblasts, and dendritic cells

PubMed Central

Poulsen, Christopher; Mehalick, Leslie A.; Fischer, Carol L.; Lanzel, Emily A.; Bates, Amber M.; Walters, Katherine S.; Cavanaugh, Joseph E.; Guthmiller, Janet M.; Johnson, Georgia K.; Wertz, Philip W.; Brogden, Kim A.

2015-01-01

Long-chain bases are present in the oral cavity. Previously we determined that sphingosine, dihydrosphingosine, and phytosphingosine have potent antimicrobial activity against oral pathogens. Here, we determined the cytotoxicities of long-chain bases for oral cells, an important step in considering their potential as antimicrobial agents for oral infections. This information would clearly help in establishing prophylactic or therapeutic doses. To assess this, human oral gingival epithelial (GE) keratinocytes, oral gingival fibroblasts (GF), and dendritic cells (DC) were exposed to 10.0-640.0 µM long-chain bases and glycerol monolaurate (GML). The effects of long-chain bases on cell metabolism (conversion of resazurin to resorufin), membrane permeability (uptake of propridium iodide or SYTOX-Green), release of cellular contents (LDH), and cell morphology (confocal microscopy) were all determined. GE keratinocytes were more resistant to long-chain bases as compared to GF and DC, which were more susceptible. For DC, 0.2 to 10.0 µM long-chain bases and GML were not cytotoxic; 40.0 to 80.0 µM long-chain bases, but not GML, were cytotoxic; and 80.0 µM long-chain bases induced cellular damage and death in less than 20 minutes. The LD50 of long-chain bases for GE keratinocytes, GF, and DC were considerably higher than their minimal inhibitory concentrations for oral pathogens, a finding important to pursuing their future potential in treating periodontal and oral infections. PMID:26005054

Differential cytotoxicity of long-chain bases for human oral gingival epithelial keratinocytes, oral fibroblasts, and dendritic cells.

PubMed

Poulsen, Christopher; Mehalick, Leslie A; Fischer, Carol L; Lanzel, Emily A; Bates, Amber M; Walters, Katherine S; Cavanaugh, Joseph E; Guthmiller, Janet M; Johnson, Georgia K; Wertz, Philip W; Brogden, Kim A

2015-08-19

Long-chain bases are present in the oral cavity. Previously we determined that sphingosine, dihydrosphingosine, and phytosphingosine have potent antimicrobial activity against oral pathogens. Here, we determined the cytotoxicities of long-chain bases for oral cells, an important step in considering their potential as antimicrobial agents for oral infections. This information would clearly help in establishing prophylactic or therapeutic doses. To assess this, human oral gingival epithelial (GE) keratinocytes, oral gingival fibroblasts (GF), and dendritic cells (DC) were exposed to 10.0-640.0 μM long-chain bases and glycerol monolaurate (GML). The effects of long-chain bases on cell metabolism (conversion of resazurin to resorufin), membrane permeability (uptake of propidium iodide or SYTOX-Green), release of cellular contents (LDH), and cell morphology (confocal microscopy) were all determined. GE keratinocytes were more resistant to long-chain bases as compared to GF and DC, which were more susceptible. For DC, 0.2-10.0 μM long-chain bases and GML were not cytotoxic; 40.0-80.0 μM long-chain bases, but not GML, were cytotoxic; and 80.0 μM long-chain bases induced cellular damage and death in less than 20 min. The LD50 of long-chain bases for GE keratinocytes, GF, and DC were considerably higher than their minimal inhibitory concentrations for oral pathogens, a finding important to pursuing their future potential in treating periodontal and oral infections. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Copula-based prediction of economic movements

NASA Astrophysics Data System (ADS)

García, J. E.; González-López, V. A.; Hirsh, I. D.

2016-06-01

In this paper we model the discretized returns of two paired time series BM&FBOVESPA Dividend Index and BM&FBOVESPA Public Utilities Index using multivariate Markov models. The discretization corresponds to three categories, high losses, high profits and the complementary periods of the series. In technical terms, the maximal memory that can be considered for a Markov model, can be derived from the size of the alphabet and dataset. The number of parameters needed to specify a discrete multivariate Markov chain grows exponentially with the order and dimension of the chain. In this case the size of the database is not large enough for a consistent estimation of the model. We apply a strategy to estimate a multivariate process with an order greater than the order achieved using standard procedures. The new strategy consist on obtaining a partition of the state space which is constructed from a combination, of the partitions corresponding to the two marginal processes and the partition corresponding to the multivariate Markov chain. In order to estimate the transition probabilities, all the partitions are linked using a copula. In our application this strategy provides a significant improvement in the movement predictions.

Model-Driven Useware Engineering

NASA Astrophysics Data System (ADS)

Meixner, Gerrit; Seissler, Marc; Breiner, Kai

User-oriented hardware and software development relies on a systematic development process based on a comprehensive analysis focusing on the users' requirements and preferences. Such a development process calls for the integration of numerous disciplines, from psychology and ergonomics to computer sciences and mechanical engineering. Hence, a correspondingly interdisciplinary team must be equipped with suitable software tools to allow it to handle the complexity of a multimodal and multi-device user interface development approach. An abstract, model-based development approach seems to be adequate for handling this complexity. This approach comprises different levels of abstraction requiring adequate tool support. Thus, in this chapter, we present the current state of our model-based software tool chain. We introduce the use model as the core model of our model-based process, transformation processes, and a model-based architecture, and we present different software tools that provide support for creating and maintaining the models or performing the necessary model transformations.

Crystallization in melts of short, semiflexible hard polymer chains: An interplay of entropies and dimensions

NASA Astrophysics Data System (ADS)

Shakirov, T.; Paul, W.

2018-04-01

What is the thermodynamic driving force for the crystallization of melts of semiflexible polymers? We try to answer this question by employing stochastic approximation Monte Carlo simulations to obtain the complete thermodynamic equilibrium information for a melt of short, semiflexible polymer chains with purely repulsive nonbonded interactions. The thermodynamics is obtained based on the density of states of our coarse-grained model, which varies by up to 5600 orders of magnitude. We show that our polymer melt undergoes a first-order crystallization transition upon increasing the chain stiffness at fixed density. This crystallization can be understood by the interplay of the maximization of different entropy contributions in different spatial dimensions. At sufficient stiffness and density, the three-dimensional orientational interactions drive the orientational ordering transition, which is accompanied by a two-dimensional translational ordering transition in the plane perpendicular to the chains resulting in a hexagonal crystal structure. While the three-dimensional ordering can be understood in terms of Onsager theory, the two-dimensional transition can be understood in terms of the liquid-hexatic transition of hard disks. Due to the domination of lateral two-dimensional translational entropy over the one-dimensional translational entropy connected with columnar displacements, the chains form a lamellar phase. Based on this physical understanding, orientational ordering and translational ordering should be separable for polymer melts. A phenomenological theory based on this understanding predicts a qualitative phase diagram as a function of volume fraction and stiffness in good agreement with results from the literature.

Impact of the alkyl chain length on binding of imidazolium-based ionic liquids to bovine serum albumin

NASA Astrophysics Data System (ADS)

Zhang, Mengyue; Wang, Ying; Zhang, Hongmei; Cao, Jian; Fei, Zhenghao; Wang, Yanqing

2018-05-01

The effects of six imidazolium-based ionic liquids (ILs) with different alkyl chain length ([CnMim]Cl, n = 2, 4, 6, 8, 10, 12) on the structure and functions of bovine serum albumin (BSA) were studied by multi-spectral methods and molecular docking. ILs with the longer alkyl chain length have the stronger binding interaction with BSA and the greater conformational damage to protein. The effects of ILs on the functional properties of BSA were further studied by the determination of non-enzyme esterase activity, β-fibrosis and other properties of BSA. The thermal stability of BSA was reduced, the rate of the formation of beta sheet structures of BSA was lowered, and the esterase-like activity of BSA were decreased with the increase of ILs concentration. Simultaneous molecular modeling technique revealed the favorable binding sites of ILs on protein. The hydrophobic force and polar interactions were the mainly binding forces of them. The calculated results are in a good agreement with the spectroscopic experiments. These studies on the impact of the alkyl chain length on binding of imidazolium-based ionic liquids to BSA are of great significance for understanding and developing the application of ionic liquid in life and physiological system.

Automatic Near-Real-Time Image Processing Chain for Very High Resolution Optical Satellite Data

NASA Astrophysics Data System (ADS)

Ostir, K.; Cotar, K.; Marsetic, A.; Pehani, P.; Perse, M.; Zaksek, K.; Zaletelj, J.; Rodic, T.

2015-04-01

In response to the increasing need for automatic and fast satellite image processing SPACE-SI has developed and implemented a fully automatic image processing chain STORM that performs all processing steps from sensor-corrected optical images (level 1) to web-delivered map-ready images and products without operator's intervention. Initial development was tailored to high resolution RapidEye images, and all crucial and most challenging parts of the planned full processing chain were developed: module for automatic image orthorectification based on a physical sensor model and supported by the algorithm for automatic detection of ground control points (GCPs); atmospheric correction module, topographic corrections module that combines physical approach with Minnaert method and utilizing anisotropic illumination model; and modules for high level products generation. Various parts of the chain were implemented also for WorldView-2, THEOS, Pleiades, SPOT 6, Landsat 5-8, and PROBA-V. Support of full-frame sensor currently in development by SPACE-SI is in plan. The proposed paper focuses on the adaptation of the STORM processing chain to very high resolution multispectral images. The development concentrated on the sub-module for automatic detection of GCPs. The initially implemented two-step algorithm that worked only with rasterized vector roads and delivered GCPs with sub-pixel accuracy for the RapidEye images, was improved with the introduction of a third step: super-fine positioning of each GCP based on a reference raster chip. The added step exploits the high spatial resolution of the reference raster to improve the final matching results and to achieve pixel accuracy also on very high resolution optical satellite data.

Differential effects of saturated fatty acids on the risk of metabolic syndrome: a matched case-control and meta-analysis study.

PubMed

Yang, Wei-Sin; Chen, Pei-Chun; Hsu, Hsiu-Ching; Su, Ta-Chen; Lin, Hung-Ju; Chen, Ming-Fong; Lee, Yuan-Teh; Chien, Kuo-Liong

2018-06-01

We investigated the association between plasma saturated fatty acids (SFAs) and the risk of metabolic syndrome among ethnic Chinese adults in Taiwan who attended a health check-up center. A case-control study based on 1000 cases of metabolic syndrome and 1:1 matched control participants (mean age, 54.9 ± 10.7 y; 36% females) were recruited. Metabolic syndrome was defined according to the criteria of the International Diabetes Federation. Gas chromatography was used to measure the distribution of fatty acids in plasma (% of total fatty acids). Even-chain SFAs, including 14:0, 16:0, and 18:0, were associated with metabolic syndrome; the adjusted odds ratio [OR] and 95% confidence interval [CI] per standard deviation [SD] difference was 3.32, [1.98-5.59]; however, very-long-chain SFAs, including 20:0, 21:0, 22:0, 23:0, and 24:0, were inversely associated with metabolic syndrome. The adjusted OR [95% CI] per SD difference was 0.67 [0.58-0.78]. The area under the receiver operative characteristic curve increased from 0.814 in the basic model to 0.815 (p = 0.54, compared with the basic model), 0.818 (p < 0.0001), and 0.820 (p < 0.0001) after adding odd-chain, even-chain, and very-long chain SFAs. A meta-analysis based on 12 studies showed that the summarized OR for type 2 diabetes mellitus was 1.16 [0.96-1.41] for the top versus bottom SFAs. Different carbon numbers of SFAs have been shown to have differential effects on the status of metabolic syndrome, implying that SFAs are not homogenous for the effects. Copyright © 2018 Elsevier Inc. All rights reserved.

Modeling sustainability in renewable energy supply chain systems

NASA Astrophysics Data System (ADS)

Xie, Fei

This dissertation aims at modeling sustainability of renewable fuel supply chain systems against emerging challenges. In particular, the dissertation focuses on the biofuel supply chain system design, and manages to develop advanced modeling framework and corresponding solution methods in tackling challenges in sustaining biofuel supply chain systems. These challenges include: (1) to integrate "environmental thinking" into the long-term biofuel supply chain planning; (2) to adopt multimodal transportation to mitigate seasonality in biofuel supply chain operations; (3) to provide strategies in hedging against uncertainty from conversion technology; and (4) to develop methodologies in long-term sequential planning of the biofuel supply chain under uncertainties. All models are mixed integer programs, which also involves multi-objective programming method and two-stage/multistage stochastic programming methods. In particular for the long-term sequential planning under uncertainties, to reduce the computational challenges due to the exponential expansion of the scenario tree, I also developed efficient ND-Max method which is more efficient than CPLEX and Nested Decomposition method. Through result analysis of four independent studies, it is found that the proposed modeling frameworks can effectively improve the economic performance, enhance environmental benefits and reduce risks due to systems uncertainties for the biofuel supply chain systems.

Chemically Realistic Tetrahedral Lattice Models for Polymer Chains: Application to Polyethylene Oxide.

PubMed

Dietschreit, Johannes C B; Diestler, Dennis J; Knapp, Ernst W

2016-05-10

To speed up the generation of an ensemble of poly(ethylene oxide) (PEO) polymer chains in solution, a tetrahedral lattice model possessing the appropriate bond angles is used. The distance between noncovalently bonded atoms is maintained at realistic values by generating chains with an enhanced degree of self-avoidance by a very efficient Monte Carlo (MC) algorithm. Potential energy parameters characterizing this lattice model are adjusted so as to mimic realistic PEO polymer chains in water simulated by molecular dynamics (MD), which serves as a benchmark. The MD data show that PEO chains have a fractal dimension of about two, in contrast to self-avoiding walk lattice models, which exhibit the fractal dimension of 1.7. The potential energy accounts for a mild hydrophobic effect (HYEF) of PEO and for a proper setting of the distribution between trans and gauche conformers. The potential energy parameters are determined by matching the Flory radius, the radius of gyration, and the fraction of trans torsion angles in the chain. A gratifying result is the excellent agreement of the pair distribution function and the angular correlation for the lattice model with the benchmark distribution. The lattice model allows for the precise computation of the torsional entropy of the chain. The generation of polymer conformations of the adjusted lattice model is at least 2 orders of magnitude more efficient than MD simulations of the PEO chain in explicit water. This method of generating chain conformations on a tetrahedral lattice can also be applied to other types of polymers with appropriate adjustment of the potential energy function. The efficient MC algorithm for generating chain conformations on a tetrahedral lattice is available for download at https://github.com/Roulattice/Roulattice .

Configuration complexity assessment of convergent supply chain systems

NASA Astrophysics Data System (ADS)

Modrak, Vladimir; Marton, David

2014-07-01

System designers usually generate alternative configurations of supply chains (SCs) by varying especially fixed assets to satisfy a desired production scope and rate. Such alternatives often vary in associated costs and other facets including degrees of complexity. Hence, a measure of configuration complexity can be a tool for comparison and decision-making. This paper presents three approaches to assessment of configuration complexity and their applications to designing convergent SC systems. Presented approaches are conceptually distinct ways of measuring structural complexity parameters based on different preconditions and circumstances of assembly systems which are typical representatives of convergent SCs. There are applied two similar approaches based on different preconditions that are related to demand shares. Third approach does not consider any special condition relating to character of final product demand. Subsequently, we propose a framework for modeling of assembly SC models, which are dividing to classes.

Development of the IBSAL-SimMOpt Method for the Optimization of Quality in a Corn Stover Supply Chain

DOE PAGES

Chavez, Hernan; Castillo-Villar, Krystel; Webb, Erin

2017-08-01

Variability on the physical characteristics of feedstock has a relevant effect on the reactor’s reliability and operating cost. Most of the models developed to optimize biomass supply chains have failed to quantify the effect of biomass quality and preprocessing operations required to meet biomass specifications on overall cost and performance. The Integrated Biomass Supply Analysis and Logistics (IBSAL) model estimates the harvesting, collection, transportation, and storage cost while considering the stochastic behavior of the field-to-biorefinery supply chain. This paper proposes an IBSAL-SimMOpt (Simulation-based Multi-Objective Optimization) method for optimizing the biomass quality and costs associated with the efforts needed to meetmore » conversion technology specifications. The method is developed in two phases. For the first phase, a SimMOpt tool that interacts with the extended IBSAL is developed. For the second phase, the baseline IBSAL model is extended so that the cost for meeting and/or penalization for failing in meeting specifications are considered. The IBSAL-SimMOpt method is designed to optimize quality characteristics of biomass, cost related to activities intended to improve the quality of feedstock, and the penalization cost. A case study based on 1916 farms in Ontario, Canada is considered for testing the proposed method. Analysis of the results demonstrates that this method is able to find a high-quality set of non-dominated solutions.« less

Development of the IBSAL-SimMOpt Method for the Optimization of Quality in a Corn Stover Supply Chain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chavez, Hernan; Castillo-Villar, Krystel; Webb, Erin

Variability on the physical characteristics of feedstock has a relevant effect on the reactor’s reliability and operating cost. Most of the models developed to optimize biomass supply chains have failed to quantify the effect of biomass quality and preprocessing operations required to meet biomass specifications on overall cost and performance. The Integrated Biomass Supply Analysis and Logistics (IBSAL) model estimates the harvesting, collection, transportation, and storage cost while considering the stochastic behavior of the field-to-biorefinery supply chain. This paper proposes an IBSAL-SimMOpt (Simulation-based Multi-Objective Optimization) method for optimizing the biomass quality and costs associated with the efforts needed to meetmore » conversion technology specifications. The method is developed in two phases. For the first phase, a SimMOpt tool that interacts with the extended IBSAL is developed. For the second phase, the baseline IBSAL model is extended so that the cost for meeting and/or penalization for failing in meeting specifications are considered. The IBSAL-SimMOpt method is designed to optimize quality characteristics of biomass, cost related to activities intended to improve the quality of feedstock, and the penalization cost. A case study based on 1916 farms in Ontario, Canada is considered for testing the proposed method. Analysis of the results demonstrates that this method is able to find a high-quality set of non-dominated solutions.« less

A model based bayesian solution for characterization of complex damage scenarios in aerospace composite structures.

PubMed

Reed, H; Leckey, Cara A C; Dick, A; Harvey, G; Dobson, J

2018-01-01

Ultrasonic damage detection and characterization is commonly used in nondestructive evaluation (NDE) of aerospace composite components. In recent years there has been an increased development of guided wave based methods. In real materials and structures, these dispersive waves result in complicated behavior in the presence of complex damage scenarios. Model-based characterization methods utilize accurate three dimensional finite element models (FEMs) of guided wave interaction with realistic damage scenarios to aid in defect identification and classification. This work describes an inverse solution for realistic composite damage characterization by comparing the wavenumber-frequency spectra of experimental and simulated ultrasonic inspections. The composite laminate material properties are first verified through a Bayesian solution (Markov chain Monte Carlo), enabling uncertainty quantification surrounding the characterization. A study is undertaken to assess the efficacy of the proposed damage model and comparative metrics between the experimental and simulated output. The FEM is then parameterized with a damage model capable of describing the typical complex damage created by impact events in composites. The damage is characterized through a transdimensional Markov chain Monte Carlo solution, enabling a flexible damage model capable of adapting to the complex damage geometry investigated here. The posterior probability distributions of the individual delamination petals as well as the overall envelope of the damage site are determined. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimating and validating ground-based timber harvesting production through computer simulation

Treesearch

Jingxin Wang; Chris B. LeDoux

2003-01-01

Estimating ground-based timber harvesting systems production with an object oriented methodology was investigated. The estimation model developed generates stands of trees, simulates chain saw, drive-to-tree feller-buncher, swing-to-tree single-grip harvester felling, and grapple skidder and forwarder extraction activities, and analyzes costs and productivity. It also...

Blob-Spring Model for the Dynamics of Ring Polymer in Obstacle Environment

NASA Astrophysics Data System (ADS)

Lele, Ashish K.; Iyer, Balaji V. S.; Juvekar, Vinay A.

2008-07-01

The dynamical behavior of cyclic macromolecules in a fixed obstacle (FO) environment is very different than the behavior of linear chains in the same topological environment; while the latter relax by a snake-like reptational motion from their chain ends the former can relax only by contour length fluctuations since they are endless. Duke, Obukhov and Rubinstein proposed a scaling model (the DOR model) to interpret the dynamical scaling exponents shown by Monte Carlo simulations of rings in a FO environment. We present a model (blob-spring model) to describe the dynamics of flexible and non-concatenated ring polymer in FO environment based on a theoretical formulation developed for the dynamics of an unentangled fractal polymer. We argue that the perpetual evolution of ring perimeter by the motion of contour segments results in an extra frictional load. Our model predicts self-similar dynamics with scaling exponents for the molecular weight dependence of diffusion coefficient and relaxation times that are in agreement with the scaling model proposed by Obukhov et al.

Perspectives for geographically oriented management of fusarium mycotoxins in the cereal supply chain.

PubMed

van der Fels-Klerx, H J; Booij, C J H

2010-06-01

This article provides an overview of available systems for management of Fusarium mycotoxins in the cereal grain supply chain, with an emphasis on the use of predictive mathematical modeling. From the state of the art, it proposes future developments in modeling and management and their challenges. Mycotoxin contamination in cereal grain-based feed and food products is currently managed and controlled by good agricultural practices, good manufacturing practices, hazard analysis critical control points, and by checking and more recently by notification systems and predictive mathematical models. Most of the predictive models for Fusarium mycotoxins in cereal grains focus on deoxynivalenol in wheat and aim to help growers make decisions about the application of fungicides during cultivation. Future developments in managing Fusarium mycotoxins should include the linkage between predictive mathematical models and geographical information systems, resulting into region-specific predictions for mycotoxin occurrence. The envisioned geographically oriented decision support system may incorporate various underlying models for specific users' demands and regions and various related databases to feed the particular models with (geographically oriented) input data. Depending on the user requirements, the system selects the best fitting model and available input information. Future research areas include organizing data management in the cereal grain supply chain, developing predictive models for other stakeholders (taking into account the period up to harvest), other Fusarium mycotoxins, and cereal grain types, and understanding the underlying effects of the regional component in the models.

A Simulation Model Articulation of the REA Ontology

NASA Astrophysics Data System (ADS)

Laurier, Wim; Poels, Geert

This paper demonstrates how the REA enterprise ontology can be used to construct simulation models for business processes, value chains and collaboration spaces in supply chains. These models support various high-level and operational management simulation applications, e.g. the analysis of enterprise sustainability and day-to-day planning. First, the basic constructs of the REA ontology and the ExSpect modelling language for simulation are introduced. Second, collaboration space, value chain and business process models and their conceptual dependencies are shown, using the ExSpect language. Third, an exhibit demonstrates the use of value chain models in predicting the financial performance of an enterprise.

Analytical model of multi-planetary resonant chains and constraints on migration scenarios

NASA Astrophysics Data System (ADS)

Delisle, J.-B.

2017-09-01

Resonant chains are groups of planets for which each pair is in resonance, with an orbital period ratio locked at a rational value (2/1, 3/2, etc.). Such chains naturally form as a result of convergent migration of the planets in the proto-planetary disk. In this article, I present an analytical model of resonant chains of any number of planets. Using this model, I show that a system captured in a resonant chain can librate around several possible equilibrium configurations. The probability of capture around each equilibrium depends on how the chain formed, and especially on the order in which the planets have been captured in the chain. Therefore, for an observed resonant chain, knowing around which equilibrium the chain is librating allows for constraints to be put on the formation and migration scenario of the system. I apply this reasoning to the four planets orbiting Kepler-223 in a 3:4:6:8 resonant chain. I show that the system is observed around one of the six equilibria predicted by the analytical model. Using N-body integrations, I show that the most favorable scenario to reproduce the observed configuration is to first capture the two intermediate planets, then the outermost, and finally the innermost.

Using SCOR as a Supply Chain Management Framework for Government Agency Contract Requirements

NASA Technical Reports Server (NTRS)

Paxton, Joseph; Tucker, Brian

2010-01-01

This paper will present a model that uses the Supply-Chain Operations Reference (SCOR) model as a foundation for a framework to illustrate the information needed throughout a product lifecycle to support a healthy supply chain management function and the subsequent contract requirements to enable it. It will also show where in the supply chain the information must be extracted. The ongoing case study used to exemplify the model is NASA's (National Aeronautics and Space Administration) Ares I program for human spaceflight. Effective supply chain management and contract requirements are ongoing opportunities for continuous improvement within government agencies, specifically development of systems for human spaceflight operations. Multiple reports from the Government Accountability Office (GAO) reinforce this importance. The SCOR model is a framework for describing a supply chain with process building blocks and business activities. It provides a set of metrics for measuring supply chain performance and best practices for continuously improving. This paper expands the application of the SCOR to also provide the framework for defining information needed from different levels of the supply chain and at different phases of the lifecycle. These needs can be incorporated into contracts to enable more effective supply chain management. Depending on the phase of the lifecycle, effective supply chain management will require involvement from different levels of the organization and different levels of the supply chain.

Follow-the-leader cell migration requires biased cell-cell contact and local microenvironmental signals

NASA Astrophysics Data System (ADS)

Wynn, Michelle L.; Rupp, Paul; Trainor, Paul A.; Schnell, Santiago; Kulesa, Paul M.

2013-06-01

Directed cell migration often involves at least two types of cell motility that include multicellular streaming and chain migration. However, what is unclear is how cell contact dynamics and the distinct microenvironments through which cells travel influence the selection of one migratory mode or the other. The embryonic and highly invasive neural crest (NC) are an excellent model system to study this question since NC cells have been observed in vivo to display both of these types of cell motility. Here, we present data from tissue transplantation experiments in chick and in silico modeling that test our hypothesis that cell contact dynamics with each other and the microenvironment promote and sustain either multicellular stream or chain migration. We show that when premigratory cranial NC cells (at the pre-otic level) are transplanted into a more caudal region in the head (at the post-otic level), cells alter their characteristic stream behavior and migrate in chains. Similarly, post-otic NC cells migrate in streams after transplantation into the pre-otic hindbrain, suggesting that local microenvironmental signals dictate the mode of NC cell migration. Simulations of an agent-based model (ABM) that integrates the NC cell behavioral data predict that chain migration critically depends on the interplay of biased cell-cell contact and local microenvironment signals. Together, this integrated modeling and experimental approach suggests new experiments and offers a powerful tool to examine mechanisms that underlie complex cell migration patterns.

Parsing Social Network Survey Data from Hidden Populations Using Stochastic Context-Free Grammars

PubMed Central

Poon, Art F. Y.; Brouwer, Kimberly C.; Strathdee, Steffanie A.; Firestone-Cruz, Michelle; Lozada, Remedios M.; Kosakovsky Pond, Sergei L.; Heckathorn, Douglas D.; Frost, Simon D. W.

2009-01-01

Background Human populations are structured by social networks, in which individuals tend to form relationships based on shared attributes. Certain attributes that are ambiguous, stigmatized or illegal can create a ÔhiddenÕ population, so-called because its members are difficult to identify. Many hidden populations are also at an elevated risk of exposure to infectious diseases. Consequently, public health agencies are presently adopting modern survey techniques that traverse social networks in hidden populations by soliciting individuals to recruit their peers, e.g., respondent-driven sampling (RDS). The concomitant accumulation of network-based epidemiological data, however, is rapidly outpacing the development of computational methods for analysis. Moreover, current analytical models rely on unrealistic assumptions, e.g., that the traversal of social networks can be modeled by a Markov chain rather than a branching process. Methodology/Principal Findings Here, we develop a new methodology based on stochastic context-free grammars (SCFGs), which are well-suited to modeling tree-like structure of the RDS recruitment process. We apply this methodology to an RDS case study of injection drug users (IDUs) in Tijuana, México, a hidden population at high risk of blood-borne and sexually-transmitted infections (i.e., HIV, hepatitis C virus, syphilis). Survey data were encoded as text strings that were parsed using our custom implementation of the inside-outside algorithm in a publicly-available software package (HyPhy), which uses either expectation maximization or direct optimization methods and permits constraints on model parameters for hypothesis testing. We identified significant latent variability in the recruitment process that violates assumptions of Markov chain-based methods for RDS analysis: firstly, IDUs tended to emulate the recruitment behavior of their own recruiter; and secondly, the recruitment of like peers (homophily) was dependent on the number of recruits. Conclusions SCFGs provide a rich probabilistic language that can articulate complex latent structure in survey data derived from the traversal of social networks. Such structure that has no representation in Markov chain-based models can interfere with the estimation of the composition of hidden populations if left unaccounted for, raising critical implications for the prevention and control of infectious disease epidemics. PMID:19738904

Influence of chain rigidity on the conformation of model lipid membranes in the presence of cylindrical nanoparticle inclusions

NASA Astrophysics Data System (ADS)

Diloreto, Chris; Wickham, Robert

2012-02-01

We employ real-space self-consistent field theory to study the conformation of model lipid membranes in the presence of solvent and cylindrical nanoparticle inclusions (''peptides''). Whereas it is common to employ a polymeric Gaussian chain model for the lipids, here we model the lipids as persistent, worm-like chains. Our motivation is to develop a more realistic field theory to describe the action of pore-forming anti-microbial peptides that disrupt the bacterial cell membrane. We employ operator-splitting and a pseudo-spectral algorithm, using SpharmonicKit for the chain tangent degrees of freedom, to solve for the worm-like chain propagator. The peptides, modelled using a mask function, have a surface patterned with hydrophobic and hydrophillic patches, but no charge. We examine the role chain rigidity plays in the hydrophobic mismatch, the membrane-mediated interaction between two peptides, the size and structure of pores formed by peptide aggregates, and the free-energy barrier for peptide insertion into the membrane. Our results suggest that chain rigidity influences both the pore structure and the mechanism of pore formation.

A decision-making process model of young online shoppers.

PubMed

Lin, Chin-Feng; Wang, Hui-Fang

2008-12-01

Based on the concepts of brand equity, means-end chain, and Web site trust, this study proposes a novel model called the consumption decision-making process of adolescents (CDMPA) to understand adolescents' Internet consumption habits and behavioral intention toward particular sporting goods. The findings of the CDMPA model can help marketers understand adolescents' consumption preferences and habits for developing effective Internet marketing strategies.

Polyelectrolyte properties of single stranded DNA measured using SAXS and single molecule FRET: beyond the wormlike chain model

PubMed Central

Meisburger, Steve P.; Sutton, Julie L.; Chen, Huimin; Pabit, Suzette A.; Kirmizialtin, Serdal; Elber, Ron; Pollack, Lois

2013-01-01

Nucleic acids are highly charged polyelectrolytes that interact strongly with salt ions. Rigid, base-paired regions are successfully described with worm like chain models, but non base-paired single stranded regions have fundamentally different polymer properties because of their greater flexibility. Recently, attention has turned to single stranded nucleic acids due to the growing recognition of their biological importance, as well as the availability of sophisticated experimental techniques sensitive to the conformation of individual molecules. We investigate polyelectrolyte properties of poly(dT), an important and widely studied model system for flexible single stranded nucleic acids, in physiologically important mixed mono- and di-valent salt. We report measurements of the form factor and interparticle interactions using SAXS, end to end distances using smFRET, and number of excess ions using ASAXS. We present a coarse-grained model that accounts for flexibility, excluded volume, and electrostatic interactions in these systems. Predictions of the model are validated against experiment. We also discuss the state of all-atom, explicit solvent Molecular Dynamics simulations of poly(dT), the next step in understanding the complexities of ion interactions with these highly charged and flexible polymers. PMID:23606337

A multi-objective model for closed-loop supply chain optimization and efficient supplier selection in a competitive environment considering quantity discount policy

NASA Astrophysics Data System (ADS)

Jahangoshai Rezaee, Mustafa; Yousefi, Samuel; Hayati, Jamileh

2017-06-01

Supplier selection and allocation of optimal order quantity are two of the most important processes in closed-loop supply chain (CLSC) and reverse logistic (RL). So that providing high quality raw material is considered as a basic requirement for a manufacturer to produce popular products, as well as achieve more market shares. On the other hand, considering the existence of competitive environment, suppliers have to offer customers incentives like discounts and enhance the quality of their products in a competition with other manufacturers. Therefore, in this study, a model is presented for CLSC optimization, efficient supplier selection, as well as orders allocation considering quantity discount policy. It is modeled using multi-objective programming based on the integrated simultaneous data envelopment analysis-Nash bargaining game. In this study, maximizing profit and efficiency and minimizing defective and functions of delivery delay rate are taken into accounts. Beside supplier selection, the suggested model selects refurbishing sites, as well as determining the number of products and parts in each network's sector. The suggested model's solution is carried out using global criteria method. Furthermore, based on related studies, a numerical example is examined to validate it.

Inferring soil salinity in a drip irrigation system from multi-configuration EMI measurements using adaptive Markov chain Monte Carlo

NASA Astrophysics Data System (ADS)

Zaib Jadoon, Khan; Umer Altaf, Muhammad; McCabe, Matthew Francis; Hoteit, Ibrahim; Muhammad, Nisar; Moghadas, Davood; Weihermüller, Lutz

2017-10-01

A substantial interpretation of electromagnetic induction (EMI) measurements requires quantifying optimal model parameters and uncertainty of a nonlinear inverse problem. For this purpose, an adaptive Bayesian Markov chain Monte Carlo (MCMC) algorithm is used to assess multi-orientation and multi-offset EMI measurements in an agriculture field with non-saline and saline soil. In MCMC the posterior distribution is computed using Bayes' rule. The electromagnetic forward model based on the full solution of Maxwell's equations was used to simulate the apparent electrical conductivity measured with the configurations of EMI instrument, the CMD Mini-Explorer. Uncertainty in the parameters for the three-layered earth model are investigated by using synthetic data. Our results show that in the scenario of non-saline soil, the parameters of layer thickness as compared to layers electrical conductivity are not very informative and are therefore difficult to resolve. Application of the proposed MCMC-based inversion to field measurements in a drip irrigation system demonstrates that the parameters of the model can be well estimated for the saline soil as compared to the non-saline soil, and provides useful insight about parameter uncertainty for the assessment of the model outputs.

Risk assessment in the upstream crude oil supply chain: Leveraging analytic hierarchy process

NASA Astrophysics Data System (ADS)

Briggs, Charles Awoala

For an organization to be successful, an effective strategy is required, and if implemented appropriately the strategy will result in a sustainable competitive advantage. The importance of decision making in the oil industry is reflected in the magnitude and nature of the industry. Specific features of the oil industry supply chain, such as its longer chain, the complexity of its transportation system, its complex production and storage processes, etc., pose challenges to its effective management. Hence, understanding the risks, the risk sources, and their potential impacts on the oil industry's operations will be helpful in proposing a risk management model for the upstream oil supply chain. The risk-based model in this research uses a three-level analytic hierarchy process (AHP), a multiple-attribute decision-making technique, to underline the importance of risk analysis and risk management in the upstream crude oil supply chain. Level 1 represents the overall goal of risk management; Level 2 is comprised of the various risk factors; and Level 3 represents the alternative criteria of the decision maker as indicated on the hierarchical structure of the crude oil supply chain. Several risk management experts from different oil companies around the world were surveyed, and six major types of supply chain risks were identified: (1) exploration and production, (2) environmental and regulatory compliance, (3) transportation, (4) availability of oil, (5) geopolitical, and (6) reputational. Also identified are the preferred methods of managing risks which include; (1) accept and control the risks, (2) avoid the risk by stopping the activity, or (3) transfer or share the risks to other companies or insurers. The results from the survey indicate that the most important risk to manage is transportation risk with a priority of .263, followed by exploration/production with priority of .198, with an overall inconsistency of .03. With respect to major objectives the most preferred risk management policy option based on the result of the composite score is accept and control risk with a priority of .446, followed by transfer or share risk with a priority of .303. The least likely option is to terminate or forgo activity with a priority of .251.

Molecular Mechanisms of ZnO Nanoparticle Dispersion in Solution: Modeling of Surfactant Association, Electrostatic Shielding and Counter Ion Dynamics.

PubMed

Duchstein, Patrick; Milek, Theodor; Zahn, Dirk

2015-01-01

Molecular models of 5 nm sized ZnO/Zn(OH)2 core-shell nanoparticles in ethanolic solution were derived as scale-up models (based on an earlier model created from ion-by-ion aggregation and self-organization) and subjected to mechanistic analyses of surface stabilization by block-copolymers. The latter comprise a poly-methacrylate chain accounting for strong surfactant association to the nanoparticle by hydrogen bonding and salt-bridges. While dangling poly-ethylene oxide chains provide only a limited degree of sterical hindering to nanoparticle agglomeration, the key mechanism of surface stabilization is electrostatic shielding arising from the acrylates and a halo of Na+ counter ions associated to the nanoparticle. Molecular dynamics simulations reveal different solvent shells and distance-dependent mobility of ions and solvent molecules. From this, we provide a molecular rationale of effective particle size, net charge and polarizability of the nanoparticles in solution.

Molecular Mechanisms of ZnO Nanoparticle Dispersion in Solution: Modeling of Surfactant Association, Electrostatic Shielding and Counter Ion Dynamics

PubMed Central

Duchstein, Patrick; Milek, Theodor; Zahn, Dirk

2015-01-01

Molecular models of 5 nm sized ZnO/Zn(OH)2 core-shell nanoparticles in ethanolic solution were derived as scale-up models (based on an earlier model created from ion-by-ion aggregation and self-organization) and subjected to mechanistic analyses of surface stabilization by block-copolymers. The latter comprise a poly-methacrylate chain accounting for strong surfactant association to the nanoparticle by hydrogen bonding and salt-bridges. While dangling poly-ethylene oxide chains provide only a limited degree of sterical hindering to nanoparticle agglomeration, the key mechanism of surface stabilization is electrostatic shielding arising from the acrylates and a halo of Na+ counter ions associated to the nanoparticle. Molecular dynamics simulations reveal different solvent shells and distance-dependent mobility of ions and solvent molecules. From this, we provide a molecular rationale of effective particle size, net charge and polarizability of the nanoparticles in solution. PMID:25962096

Self-Consistent Field Lattice Model for Polymer Networks.

PubMed

Tito, Nicholas B; Storm, Cornelis; Ellenbroek, Wouter G

2017-12-26

A lattice model based on polymer self-consistent field theory is developed to predict the equilibrium statistics of arbitrary polymer networks. For a given network topology, our approach uses moment propagators on a lattice to self-consistently construct the ensemble of polymer conformations and cross-link spatial probability distributions. Remarkably, the calculation can be performed "in the dark", without any prior knowledge on preferred chain conformations or cross-link positions. Numerical results from the model for a test network exhibit close agreement with molecular dynamics simulations, including when the network is strongly sheared. Our model captures nonaffine deformation, mean-field monomer interactions, cross-link fluctuations, and finite extensibility of chains, yielding predictions that differ markedly from classical rubber elasticity theory for polymer networks. By examining polymer networks with different degrees of interconnectivity, we gain insight into cross-link entropy, an important quantity in the macroscopic behavior of gels and self-healing materials as they are deformed.

Cometary Nuclei and Tidal Disruption: The Geologic Record of Crater Chains on Callisto and Ganymede

NASA Technical Reports Server (NTRS)

Schenk, Paul M.; Asphaug, Erik; McKinnon, William B.; Melosh, H. J.; Weissman, Paul R.

1996-01-01

Prominent crater chains on Ganymede and Callisto are most likely the impact scars of comets tidally disrupted by Jupiter and are not secondary crater chains. We have examined the morphology of these chains in detail in order to place constraints on the properties of the comets that formed them and the disruption process. In these chains, intercrater spacing varies by no more than a factor of 2 and the craters within a given chain show almost no deviation from linearity (although the chains themselves are on gently curved small circles). All of these crater chains occur on or very near the Jupiter-facing hemisphere. For a given chain, the estimated masses of the fragments that formed each crater vary by no more than an order of magnitude. The mean fragment masses for all the chains vary by over four orders of magnitude (W. B. McKinnon and P. M. Schenk 1995, Geophys. Res. Lett. 13, 1829-1832), however. The mass of the parent comet for each crater chain is not correlated with the number of fragments produced during disruption but is correlated with the mean mass of the fragments produced in a given disruption event. Also, the larger fragments are located near the center of each chain. All of these characteristics are consistent with those predicted by disruption simulations based on the rubble pile cometary nucleus model (in which nuclei are composed on numerous small fragments weakly bound by self-gravity), and with those observed in Comet D/Shoemaker-Levy 9. Similar crater chains have not been found on the other icy satellites, but the impact record of disrupted comets on Callisto and Ganymede indicates that disruption events occur within the Jupiter system roughly once every 200 to 400 years.

A chain-retrieval model for voluntary task switching.

PubMed

Vandierendonck, André; Demanet, Jelle; Liefooghe, Baptist; Verbruggen, Frederick

2012-09-01

To account for the findings obtained in voluntary task switching, this article describes and tests the chain-retrieval model. This model postulates that voluntary task selection involves retrieval of task information from long-term memory, which is then used to guide task selection and task execution. The model assumes that the retrieved information consists of acquired sequences (or chains) of tasks, that selection may be biased towards chains containing more task repetitions and that bottom-up triggered repetitions may overrule the intended task. To test this model, four experiments are reported. In Studies 1 and 2, sequences of task choices and the corresponding transition sequences (task repetitions or switches) were analyzed with the help of dependency statistics. The free parameters of the chain-retrieval model were estimated on the observed task sequences and these estimates were used to predict autocorrelations of tasks and transitions. In Studies 3 and 4, sequences of hand choices and their transitions were analyzed similarly. In all studies, the chain-retrieval model yielded better fits and predictions than statistical models of event choice. In applications to voluntary task switching (Studies 1 and 2), all three parameters of the model were needed to account for the data. When no task switching was required (Studies 3 and 4), the chain-retrieval model could account for the data with one or two parameters clamped to a neutral value. Implications for our understanding of voluntary task selection and broader theoretical implications are discussed. Copyright © 2012 Elsevier Inc. All rights reserved.

Bayesian inference based on dual generalized order statistics from the exponentiated Weibull model

NASA Astrophysics Data System (ADS)

Al Sobhi, Mashail M.

2015-02-01

Bayesian estimation for the two parameters and the reliability function of the exponentiated Weibull model are obtained based on dual generalized order statistics (DGOS). Also, Bayesian prediction bounds for future DGOS from exponentiated Weibull model are obtained. The symmetric and asymmetric loss functions are considered for Bayesian computations. The Markov chain Monte Carlo (MCMC) methods are used for computing the Bayes estimates and prediction bounds. The results have been specialized to the lower record values. Comparisons are made between Bayesian and maximum likelihood estimators via Monte Carlo simulation.

Interfacial welding of dynamic covalent network polymers

NASA Astrophysics Data System (ADS)

Yu, Kai; Shi, Qian; Li, Hao; Jabour, John; Yang, Hua; Dunn, Martin L.; Wang, Tiejun; Qi, H. Jerry

2016-09-01

Dynamic covalent network (or covalent adaptable network) polymers can rearrange their macromolecular chain network by bond exchange reactions (BERs) where an active unit replaces a unit in an existing bond to form a new bond. Such macromolecular events, when they occur in large amounts, can attribute to unusual properties that are not seen in conventional covalent network polymers, such as shape reforming and surface welding; the latter further enables the important attributes of material malleability and powder-based reprocessing. In this paper, a multiscale modeling framework is developed to study the surface welding of thermally induced dynamic covalent network polymers. At the macromolecular network level, a lattice model is developed to describe the chain density evolution across the interface and its connection to bulk stress relaxation due to BERs. The chain density evolution rule is then fed into a continuum level interfacial model that takes into account surface roughness and applied pressure to predict the effective elastic modulus and interfacial fracture energy of welded polymers. The model yields particularly accessible results where the moduli and interfacial strength of the welded samples as a function of temperature and pressure can be predicted with four parameters, three of which can be measured directly. The model identifies the dependency of surface welding efficiency on the applied thermal and mechanical fields: the pressure will affect the real contact area under the consideration of surface roughness of dynamic covalent network polymers; the chain density increment on the real contact area of interface is only dependent on the welding time and temperature. The modeling approach shows good agreement with experiments and can be extended to other types of dynamic covalent network polymers using different stimuli for BERs, such as light and moisture etc.

Video Self-Modeling: A Job Skills Intervention with Individuals with Intellectual Disability in Employment Settings

ERIC Educational Resources Information Center

Goh, Ailsa E.; Bambara, Linda M.

2013-01-01

The purpose of this study was to explore the effectiveness of video self-modeling (VSM) to teach chained job tasks to individuals with intellectual disability in community-based employment settings. Initial empirical evaluations have demonstrated that VSM when used in combination with other instructional strategies, are effective methods to teach…

A General and Flexible Approach to Estimating the Social Relations Model Using Bayesian Methods

ERIC Educational Resources Information Center

Ludtke, Oliver; Robitzsch, Alexander; Kenny, David A.; Trautwein, Ulrich

2013-01-01

The social relations model (SRM) is a conceptual, methodological, and analytical approach that is widely used to examine dyadic behaviors and interpersonal perception within groups. This article introduces a general and flexible approach to estimating the parameters of the SRM that is based on Bayesian methods using Markov chain Monte Carlo…

Helping Students Assess the Relative Importance of Different Intermolecular Interactions

ERIC Educational Resources Information Center

Jasien, Paul G.

2008-01-01

A semi-quantitative model has been developed to estimate the relative effects of dispersion, dipole-dipole interactions, and H-bonding on the normal boiling points ("T[subscript b]") for a subset of simple organic systems. The model is based upon a statistical analysis using multiple linear regression on a series of straight-chain organic…

Investigating the principles of recrystallization from glyceride melts.

PubMed

Windbergs, Maike; Strachan, Clare J; Kleinebudde, Peter

2009-01-01

Different lipids were melted and resolidified as model systems to gain deeper insight into the principles of recrystallization processes in lipid-based dosage forms. Solid-state characterization was performed on the samples with differential scanning calorimetry and X-ray powder diffraction. Several recrystallization processes could be identified during storage of the lipid layers. Pure triglycerides that generally crystallize to the metastable alpha-form from the melt followed by a recrystallization process to the stable beta-form with time showed a chain-length-dependent behavior during storage. With increasing chain length, the recrystallization to the stable beta-form was decelerated. Partial glycerides exhibited a more complex recrystallization behavior due to the fact that these substances are less homogenous. Mixtures of a long-chain triglyceride and a partial glyceride showed evidence of some interaction between the two components as the partial glyceride hindered the recrystallization of the triglyceride to the stable beta-form. In addition, the extent of this phenomenon depended on the amount of partial glyceride in the mixture. Based on these results, changes in solid dosage forms based on glycerides during processing and storage can be better understood.

How Can Students Generalize the Chain Rule? The Roles of Abduction in Mathematical Modeling

ERIC Educational Resources Information Center

Park, Jin Hyeong; Lee, Kyeong-Hwa

2016-01-01

The purpose of this study is to design a modeling task to facilitate students' inquiries into the chain rule in calculus and to analyze the results after implementation of the task. In this study, we take a modeling approach to the teaching and learning of the chain rule by facilitating the generalization of students' models and modeling…

Demand Activated Manufacturing Architecture (DAMA) model for supply chain collaboration

DOE Office of Scientific and Technical Information (OSTI.GOV)

CHAPMAN,LEON D.; PETERSEN,MARJORIE B.

The Demand Activated Manufacturing Architecture (DAMA) project during the last five years of work with the U.S. Integrated Textile Complex (retail, apparel, textile, and fiber sectors) has developed an inter-enterprise architecture and collaborative model for supply chains. This model will enable improved collaborative business across any supply chain. The DAMA Model for Supply Chain Collaboration is a high-level model for collaboration to achieve Demand Activated Manufacturing. The five major elements of the architecture to support collaboration are (1) activity or process, (2) information, (3) application, (4) data, and (5) infrastructure. These five elements are tied to the application of themore » DAMA architecture to three phases of collaboration - prepare, pilot, and scale. There are six collaborative activities that may be employed in this model: (1) Develop Business Planning Agreements, (2) Define Products, (3) Forecast and Plan Capacity Commitments, (4) Schedule Product and Product Delivery, (5) Expedite Production and Delivery Exceptions, and (6) Populate Supply Chain Utility. The Supply Chain Utility is a set of applications implemented to support collaborative product definition, forecast visibility, planning, scheduling, and execution. The DAMA architecture and model will be presented along with the process for implementing this DAMA model.« less

A Gibbs sampler for Bayesian analysis of site-occupancy data

USGS Publications Warehouse

Dorazio, Robert M.; Rodriguez, Daniel Taylor

2012-01-01

1. A Bayesian analysis of site-occupancy data containing covariates of species occurrence and species detection probabilities is usually completed using Markov chain Monte Carlo methods in conjunction with software programs that can implement those methods for any statistical model, not just site-occupancy models. Although these software programs are quite flexible, considerable experience is often required to specify a model and to initialize the Markov chain so that summaries of the posterior distribution can be estimated efficiently and accurately. 2. As an alternative to these programs, we develop a Gibbs sampler for Bayesian analysis of site-occupancy data that include covariates of species occurrence and species detection probabilities. This Gibbs sampler is based on a class of site-occupancy models in which probabilities of species occurrence and detection are specified as probit-regression functions of site- and survey-specific covariate measurements. 3. To illustrate the Gibbs sampler, we analyse site-occupancy data of the blue hawker, Aeshna cyanea (Odonata, Aeshnidae), a common dragonfly species in Switzerland. Our analysis includes a comparison of results based on Bayesian and classical (non-Bayesian) methods of inference. We also provide code (based on the R software program) for conducting Bayesian and classical analyses of site-occupancy data.

Innovation value chain capability in Malaysian-owned company: A theoretical framework

NASA Astrophysics Data System (ADS)

Abidin, Norkisme Zainal; Suradi, Nur Riza Mohd

2014-09-01

Good quality products or services are no longer adequate to guarantee the sustainability of a company in the present competitive business. Prior research has developed various innovation models with the hope to better understand the innovativeness of the company. Due to countless definitions, indicators, factors, parameter and approaches in the study of innovation, it is difficult to ensure which one will best suit the Malaysian-owned company innovativeness. This paper aims to provide a theoretical background to support the framework of the innovation value chain capability in Malaysian-owned Company. The theoretical framework was based on the literature reviews, expert interviews and focus group study. The framework will be used to predict and assess the innovation value chain capability in Malaysian-owned company.

Template-free modeling by LEE and LEER in CASP11.

PubMed

Joung, InSuk; Lee, Sun Young; Cheng, Qianyi; Kim, Jong Yun; Joo, Keehyoung; Lee, Sung Jong; Lee, Jooyoung

2016-09-01

For the template-free modeling of human targets of CASP11, we utilized two of our modeling protocols, LEE and LEER. The LEE protocol took CASP11-released server models as the input and used some of them as templates for 3D (three-dimensional) modeling. The template selection procedure was based on the clustering of the server models aided by a community detection method of a server-model network. Restraining energy terms generated from the selected templates together with physical and statistical energy terms were used to build 3D models. Side-chains of the 3D models were rebuilt using target-specific consensus side-chain library along with the SCWRL4 rotamer library, which completed the LEE protocol. The first success factor of the LEE protocol was due to efficient server model screening. The average backbone accuracy of selected server models was similar to that of top 30% server models. The second factor was that a proper energy function along with our optimization method guided us, so that we successfully generated better quality models than the input template models. In 10 out of 24 cases, better backbone structures than the best of input template structures were generated. LEE models were further refined by performing restrained molecular dynamics simulations to generate LEER models. CASP11 results indicate that LEE models were better than the average template models in terms of both backbone structures and side-chain orientations. LEER models were of improved physical realism and stereo-chemistry compared to LEE models, and they were comparable to LEE models in the backbone accuracy. Proteins 2016; 84(Suppl 1):118-130. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Markov chain-incorporated and synthetic data-supported conditional artificial neural network models for forecasting monthly precipitation in arid regions

NASA Astrophysics Data System (ADS)

Aksoy, Hafzullah; Dahamsheh, Ahmad

2018-07-01

For forecasting monthly precipitation in an arid region, the feed forward back-propagation, radial basis function and generalized regression artificial neural networks (ANNs) are used in this study. The ANN models are improved after incorporation of a Markov chain-based algorithm (MC-ANNs) with which the percentage of dry months is forecasted perfectly, thus generation of any non-physical negative precipitation is eliminated. Due to the fact that recorded precipitation time series are usually shorter than the length needed for a proper calibration of ANN models, synthetic monthly precipitation data are generated by Thomas-Fiering model to further improve the performance of forecasting. For case studies from Jordan, it is seen that only a slightly better performance is achieved with the use of MC and synthetic data. A conditional statement is, therefore, established and imbedded into the ANN models after the incorporation of MC and support of synthetic data, to substantially improve the ability of the models for forecasting monthly precipitation in arid regions.

Combined state and parameter identification of nonlinear structural dynamical systems based on Rao-Blackwellization and Markov chain Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Abhinav, S.; Manohar, C. S.

2018-03-01

The problem of combined state and parameter estimation in nonlinear state space models, based on Bayesian filtering methods, is considered. A novel approach, which combines Rao-Blackwellized particle filters for state estimation with Markov chain Monte Carlo (MCMC) simulations for parameter identification, is proposed. In order to ensure successful performance of the MCMC samplers, in situations involving large amount of dynamic measurement data and (or) low measurement noise, the study employs a modified measurement model combined with an importance sampling based correction. The parameters of the process noise covariance matrix are also included as quantities to be identified. The study employs the Rao-Blackwellization step at two stages: one, associated with the state estimation problem in the particle filtering step, and, secondly, in the evaluation of the ratio of likelihoods in the MCMC run. The satisfactory performance of the proposed method is illustrated on three dynamical systems: (a) a computational model of a nonlinear beam-moving oscillator system, (b) a laboratory scale beam traversed by a loaded trolley, and (c) an earthquake shake table study on a bending-torsion coupled nonlinear frame subjected to uniaxial support motion.

Modeling of Nonlinear Hydrodynamics of the Coastal Areas of the Black Sea by the Chain of the Proprietary and Open Source Models

NASA Astrophysics Data System (ADS)

Kantardgi, Igor; Zheleznyak, Mark; Demchenko, Raisa; Dykyi, Pavlo; Kivva, Sergei; Kolomiets, Pavlo; Sorokin, Maxim

2014-05-01

The nearshore hydrodynamic fields are produced by the nonlinear interactions of the shoaling waves of different time scales and currents. To simulate the wind wave and swells propagated to the coasts, wave generated near shore currents, nonlinear-dispersive wave transformation and wave diffraction in interaction with coastal and port structure, sediment transport and coastal erosion the chains of the models should be used. The objective of this presentation is to provide an overview of the results of the application of the model chains for the assessment of the wave impacts on new construction designed at the Black Sea coasts and the impacts of these constructions on the coastal erosion/ accretion processes to demonstrate needs for further development of the nonlinear models for the coastal engineering applications. The open source models Wave Watch III and SWAN has been used to simulate wave statistics of the dedicated areas of the Black Sea in high resolution to calculated the statistical parameters of the extreme wave approaching coastal zone construction in accordance with coastal engineering standards. As the main tool for the costal hydrodynamic simulations the modeling system COASTOX-MORPHO has been used, that includes the following models. HWAVE -code based on hyperbolic version of mild slope equations., HWAVE-S - spectral version of HWAVE., BOUSS-FNL - fully nonlinear system of Boussinesq equations for simulation wave nonlinear -dispersive wave transformation in coastal areas. COASTOX-CUR - the code provided the numerical solution of the Nonlinear Shallow Water Equations (NLSWE) by finite-volume methods on the unstructured grid describing the long wave transformation in the coastal zone with the efficient drying -wetting algorithms to simulate the inundation of the coastal areas including tsunami wave runup. Coastox -Cur equations with the radiation stress term calculated via near shore wave fields simulate the wave generated nearhore currents. COASTOX-SED - the module of the simulation of the sediment transport in which the suspended sediments are simulated on the basis of the solution of 2-D advection -diffusion equation and the bottom sediment transport calculations are provided the basis of a library of the most popular semi-empirical formulas. MORPH - the module of the simulation of the morphological transformation of coastal zone based on the mass balance equation, on the basis of the sediment fluxes, calculated in the SED module. MORPH management submodel is responsible for the execution of the model chain "waves- current- sediments - morphodynamics- waves". The open source model SWASH has been used to simulate nonlinear resonance phenomena in coastal waters. The model chain was applied to simulate the potential impact of the designed shore protection structures at the Sochi Olympic Park on coastal morphodynamics, the wave parameters and nonlinear oscillations in the new ports designed in Gelenddjik and Taman at North-East coast of the Black Sea. The modeling results are compared with the results of the physical modeling in the hydraulic flumes of Moscow University of Civil Engineering.

Role of single-point mutations and deletions on transition temperatures in ideal proteinogenic heteropolymer chains in the gas phase.

PubMed

Olivares-Quiroz, L

2016-07-01

A coarse-grained statistical mechanics-based model for ideal heteropolymer proteinogenic chains of non-interacting residues is presented in terms of the size K of the chain and the set of helical propensities [Formula: see text] associated with each residue j along the chain. For this model, we provide an algorithm to compute the degeneracy tensor [Formula: see text] associated with energy level [Formula: see text] where [Formula: see text] is the number of residues with a native contact in a given conformation. From these results, we calculate the equilibrium partition function [Formula: see text] and characteristic temperature [Formula: see text] at which a transition from a low to a high entropy states is observed. The formalism is applied to analyze the effect on characteristic temperatures [Formula: see text] of single-point mutations and deletions of specific amino acids [Formula: see text] along the chain. Two probe systems are considered. First, we address the case of a random heteropolymer of size K and given helical propensities [Formula: see text] on a conformational phase space. Second, we focus our attention to a particular set of neuropentapeptides, [Met-5] and [Leu-5] enkephalins whose thermodynamic stability is a key feature on their coupling to [Formula: see text] and [Formula: see text] receptors and the triggering of biochemical responses.