Near-Optimal Resource Allocation in Cooperative Cellular Networks Using Genetic Algorithms

OpenAIRE

Luo, Zihan; Armour, Simon; McGeehan, Joe

2015-01-01

This paper shows how a genetic algorithm can be used as a method of obtaining the near-optimal solution of the resource block scheduling problem in a cooperative cellular network. An exhaustive search is initially implementedto guarantee that the optimal result, in terms of maximizing the bandwidth efficiency of the overall network, is found, and then the genetic algorithm with the properly selected termination conditions is used in the same network. The simulation results show that the genet...

Optimization of spectral printer modeling based on a modified cellular Yule-Nielsen spectral Neugebauer model.

Science.gov (United States)

Liu, Qiang; Wan, Xiaoxia; Xie, Dehong

2014-06-01

The study presented here optimizes several steps in the spectral printer modeling workflow based on a cellular Yule-Nielsen spectral Neugebauer (CYNSN) model. First, a printer subdividing method was developed that reduces the number of sub-models while maintaining the maximum device gamut. Second, the forward spectral prediction accuracy of the CYNSN model for each subspace of the printer was improved using back propagation artificial neural network (BPANN) estimated n values. Third, a sequential gamut judging method, which clearly reduced the complexity of the optimal sub-model and cell searching process during printer backward modeling, was proposed. After that, we further modified the use of the modeling color metric and comprehensively improved the spectral and perceptual accuracy of the spectral printer model. The experimental results show that the proposed optimization approaches provide obvious improvements in aspects of the modeling accuracy or efficiency for each of the corresponding steps, and an overall improvement of the optimized spectral printer modeling workflow was also demonstrated.

Magnetohydrodynamics cellular automata

International Nuclear Information System (INIS)

Hatori, Tadatsugu.

1990-02-01

There has been a renewal of interest in cellular automata, partly because they give an architecture for a special purpose computer with parallel processing optimized to solve a particular problem. The lattice gas cellular automata are briefly surveyed, which are recently developed to solve partial differential equations such as hydrodynamics or magnetohydrodynamics. A new model is given in the present paper to implement the magnetic Lorentz force in a more deterministic and local procedure than the previous one. (author)

Magnetohydrodynamic cellular automata

Energy Technology Data Exchange (ETDEWEB)

Hatori, Tadatsugu [National Inst. for Fusion Science, Nagoya (Japan)

1990-03-01

There has been a renewal of interest in cellular automata, partly because they give an architecture for a special purpose computer with parallel processing optimized to solve a particular problem. The lattice gas cellular automata are briefly surveyed, which are recently developed to solve partial differential equations such as hydrodynamics or magnetohydrodynamics. A new model is given in the present paper to implement the magnetic Lorentz force in a more deterministic and local procedure than the previous one. (author).

Magnetohydrodynamic cellular automata

International Nuclear Information System (INIS)

Hatori, Tadatsugu

1990-01-01

There has been a renewal of interest in cellular automata, partly because they give an architecture for a special purpose computer with parallel processing optimized to solve a particular problem. The lattice gas cellular automata are briefly surveyed, which are recently developed to solve partial differential equations such as hydrodynamics or magnetohydrodynamics. A new model is given in the present paper to implement the magnetic Lorentz force in a more deterministic and local procedure than the previous one. (author)

Smallest-Small-World Cellular Harmony Search for Optimization of Unconstrained Benchmark Problems

Directory of Open Access Journals (Sweden)

Sung Soo Im

2013-01-01

Full Text Available We presented a new hybrid method that combines cellular harmony search algorithms with the Smallest-Small-World theory. A harmony search (HS algorithm is based on musical performance processes that occur when a musician searches for a better state of harmony. Harmony search has successfully been applied to a wide variety of practical optimization problems. Most of the previous researches have sought to improve the performance of the HS algorithm by changing the pitch adjusting rate and harmony memory considering rate. However, there has been a lack of studies to improve the performance of the algorithm by the formation of population structures. Therefore, we proposed an improved HS algorithm that uses the cellular automata formation and the topological structure of Smallest-Small-World network. The improved HS algorithm has a high clustering coefficient and a short characteristic path length, having good exploration and exploitation efficiencies. Nine benchmark functions were applied to evaluate the performance of the proposed algorithm. Unlike the existing improved HS algorithm, the proposed algorithm is expected to have improved algorithmic efficiency from the formation of the population structure.

Iterative feedback bio-printing-derived cell-laden hydrogel scaffolds with optimal geometrical fidelity and cellular controllability.

Science.gov (United States)

Wang, Ling; Xu, Ming-En; Luo, Li; Zhou, Yongyong; Si, Peijian

2018-02-12

For three-dimensional bio-printed cell-laden hydrogel tissue constructs, the well-designed internal porous geometry is tailored to obtain the desired structural and cellular properties. However, significant differences often exist between the designed and as-printed scaffolds because of the inherent characteristics of hydrogels and cells. In this study, an iterative feedback bio-printing (IFBP) approach based on optical coherence tomography (OCT) for the fabrication of cell-laden hydrogel scaffolds with optimal geometrical fidelity and cellular controllability was proposed. A custom-made swept-source OCT (SS-OCT) system was applied to characterize the printed scaffolds quantitatively. Based on the obtained empirical linear formula from the first experimental feedback loop, we defined the most appropriate design constraints and optimized the printing process to improve the geometrical fidelity. The effectiveness of IFBP was verified from the second run using gelatin/alginate hydrogel scaffolds laden with C3A cells. The mismatch of the morphological parameters greatly decreased from 40% to within 7%, which significantly optimized the cell viability, proliferation, and morphology, as well as the representative expression of hepatocyte markers, including CYP3A4 and albumin, of the printed cell-laden hydrogel scaffolds. The demonstrated protocol paves the way for the mass fabrication of cell-laden hydrogel scaffolds, engineered tissues, and scaled-up applications of the 3D bio-printing technique.

Cellular Particle Dynamics simulation of biomechanical relaxation processes of multi-cellular systems

Science.gov (United States)

McCune, Matthew; Kosztin, Ioan

2013-03-01

Cellular Particle Dynamics (CPD) is a theoretical-computational-experimental framework for describing and predicting the time evolution of biomechanical relaxation processes of multi-cellular systems, such as fusion, sorting and compression. In CPD, cells are modeled as an ensemble of cellular particles (CPs) that interact via short range contact interactions, characterized by an attractive (adhesive interaction) and a repulsive (excluded volume interaction) component. The time evolution of the spatial conformation of the multicellular system is determined by following the trajectories of all CPs through numerical integration of their equations of motion. Here we present CPD simulation results for the fusion of both spherical and cylindrical multi-cellular aggregates. First, we calibrate the relevant CPD model parameters for a given cell type by comparing the CPD simulation results for the fusion of two spherical aggregates to the corresponding experimental results. Next, CPD simulations are used to predict the time evolution of the fusion of cylindrical aggregates. The latter is relevant for the formation of tubular multi-cellular structures (i.e., primitive blood vessels) created by the novel bioprinting technology. Work supported by NSF [PHY-0957914]. Computer time provided by the University of Missouri Bioinformatics Consortium.

Cellular automata in image processing and geometry

CERN Document Server

Adamatzky, Andrew; Sun, Xianfang

2014-01-01

The book presents findings, views and ideas on what exact problems of image processing, pattern recognition and generation can be efficiently solved by cellular automata architectures. This volume provides a convenient collection in this area, in which publications are otherwise widely scattered throughout the literature. The topics covered include image compression and resizing; skeletonization, erosion and dilation; convex hull computation, edge detection and segmentation; forgery detection and content based retrieval; and pattern generation. The book advances the theory of image processing, pattern recognition and generation as well as the design of efficient algorithms and hardware for parallel image processing and analysis. It is aimed at computer scientists, software programmers, electronic engineers, mathematicians and physicists, and at everyone who studies or develops cellular automaton algorithms and tools for image processing and analysis, or develops novel architectures and implementations of mass...

Cellular Neural Networks: A genetic algorithm for parameters optimization in artificial vision applications

International Nuclear Information System (INIS)

Taraglio, S.; Zanela, A.

1997-03-01

An optimization method for some of the CNN's (Cellular Neural Network) parameters, based on evolutionary strategies, is proposed. The new class of feedback template found is more effective in extracting features from the images that an autonomous vehicle acquires, than in the previous CNN's literature

Study on Parameter Optimization Design of Drum Brake Based on Hybrid Cellular Multiobjective Genetic Algorithm

Directory of Open Access Journals (Sweden)

Yi Zhang

2012-01-01

Full Text Available In consideration of the significant role the brake plays in ensuring the fast and safe running of vehicles, and since the present parameter optimization design models of brake are far from the practical application, this paper proposes a multiobjective optimization model of drum brake, aiming at maximizing the braking efficiency and minimizing the volume and temperature rise of drum brake. As the commonly used optimization algorithms are of some deficiency, we present a differential evolution cellular multiobjective genetic algorithm (DECell by introducing differential evolution strategy into the canonical cellular genetic algorithm for tackling this problem. For DECell, the gained Pareto front could be as close as possible to the exact Pareto front, and also the diversity of nondominated individuals could be better maintained. The experiments on the test functions reveal that DECell is of good performance in solving high-dimension nonlinear multiobjective problems. And the results of optimizing the new brake model indicate that DECell obviously outperforms the compared popular algorithm NSGA-II concerning the number of obtained brake design parameter sets, the speed, and stability for finding them.

Cellular Neural Networks: A genetic algorithm for parameters optimization in artificial vision applications

Energy Technology Data Exchange (ETDEWEB)

Taraglio, S. [ENEA, Centro Ricerche Casaccia, Rome (Italy). Dipt. Innovazione; Zanela, A. [Rome Univ. `La Sapienza` (Italy). Dipt. di Fisica

1997-03-01

An optimization method for some of the CNN`s (Cellular Neural Network) parameters, based on evolutionary strategies, is proposed. The new class of feedback template found is more effective in extracting features from the images that an autonomous vehicle acquires, than in the previous CNN`s literature.

Optimized Reaction Conditions for Removal of Cellular Organic Matter of Microcystis aeruginosa During the Destabilization and Aggregation Process Using Ferric Sulfate in Water Purification

Czech Academy of Sciences Publication Activity Database

Pivokonský, Martin; Polášek, Pavel; Pivokonská, Lenka; Tomášková, Hana

2009-01-01

Roč. 81, č. 5 (2009), s. 514-522 ISSN 1061-4303 R&D Projects: GA ČR GA103/07/0295 Institutional research plan: CEZ:AV0Z20600510 Keywords : Microcystis aeruginosa * cellular organic matter * destabilization * aggregation * optimized reaction conditions * water purification Subject RIV: BK - Fluid Dynamics Impact factor: 0.965, year: 2009

Surface Dynamic Process Simulation with the Use of Cellular Automata

International Nuclear Information System (INIS)

Adamska-Szatko, M.; Bala, J.

2010-01-01

Cellular automata are known for many applications, especially for physical and biological simulations. Universal cellular automata can be used for modelling complex natural phenomena. The paper presents simulation of surface dynamic process. Simulation uses 2-dimensional cellular automata algorithm. Modelling and visualisation were created by in-house developed software with standard OpenGL graphic library. (authors)

A material optimization model to approximate energy bounds for cellular materials under multiload conditions

DEFF Research Database (Denmark)

Guedes, J.M.; Rodrigues, H.C.; Bendsøe, Martin P.

2003-01-01

This paper describes a computational model, based on inverse homogenization and topology design, for approximating energy bounds for two-phase composites under multiple load cases. The approach allows for the identification of possible single-scale cellular materials that give rise to the optimal...

Intracellular response to process optimization and impact on productivity and product aggregates for a high-titer CHO cell process.

Science.gov (United States)

Handlogten, Michael W; Lee-O'Brien, Allison; Roy, Gargi; Levitskaya, Sophia V; Venkat, Raghavan; Singh, Shailendra; Ahuja, Sanjeev

2018-01-01

A key goal in process development for antibodies is to increase productivity while maintaining or improving product quality. During process development of an antibody, titers were increased from 4 to 10 g/L while simultaneously decreasing aggregates. Process development involved optimization of media and feed formulations, feed strategy, and process parameters including pH and temperature. To better understand how CHO cells respond to process changes, the changes were implemented in a stepwise manner. The first change was an optimization of the feed formulation, the second was an optimization of the medium, and the third was an optimization of process parameters. Multiple process outputs were evaluated including cell growth, osmolality, lactate production, ammonium concentration, antibody production, and aggregate levels. Additionally, detailed assessment of oxygen uptake, nutrient and amino acid consumption, extracellular and intracellular redox environment, oxidative stress, activation of the unfolded protein response (UPR) pathway, protein disulfide isomerase (PDI) expression, and heavy and light chain mRNA expression provided an in-depth understanding of the cellular response to process changes. The results demonstrate that mRNA expression and UPR activation were unaffected by process changes, and that increased PDI expression and optimized nutrient supplementation are required for higher productivity processes. Furthermore, our findings demonstrate the role of extra- and intracellular redox environment on productivity and antibody aggregation. Processes using the optimized medium, with increased concentrations of redox modifying agents, had the highest overall specific productivity, reduced aggregate levels, and helped cells better withstand the high levels of oxidative stress associated with increased productivity. Specific productivities of different processes positively correlated to average intracellular values of total glutathione. Additionally

Optimized Energy Efficiency and Spectral Efficiency Resource Allocation Strategies for Phantom Cellular Networks

KAUST Repository

Abdelhady, Amr, M.; Amin, Osama; Alouini, Mohamed-Slim

2016-01-01

Multi-teir hetrogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-teir architecture known as Phantom cellular networks. The optimization framework includes both EE and SE, where we propose an algorithm that computes the SE and EE resource allocation for Phantom cellular networks. Then, we compare the performance of both design strategies versus the number of users, and the ration of Phantom cellresource blocks to the total number or resource blocks. We aim to investigate the effect of some system parameters to acheive improved SE or EE performance at a non-significant loss in EE or SE performance, respectively. It was found that the system parameters can be tuned so that the EE solution does not yield a significant loss in the SE performance.

Optimized Energy Efficiency and Spectral Efficiency Resource Allocation Strategies for Phantom Cellular Networks

KAUST Repository

Abdelhady, Amr, M.

2016-01-06

Multi-teir hetrogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-teir architecture known as Phantom cellular networks. The optimization framework includes both EE and SE, where we propose an algorithm that computes the SE and EE resource allocation for Phantom cellular networks. Then, we compare the performance of both design strategies versus the number of users, and the ration of Phantom cellresource blocks to the total number or resource blocks. We aim to investigate the effect of some system parameters to acheive improved SE or EE performance at a non-significant loss in EE or SE performance, respectively. It was found that the system parameters can be tuned so that the EE solution does not yield a significant loss in the SE performance.

Two-material optimization of plate armour for blast mitigation using hybrid cellular automata

Science.gov (United States)

Goetz, J.; Tan, H.; Renaud, J.; Tovar, A.

2012-08-01

With the increased use of improvised explosive devices in regions at war, the threat to military and civilian life has risen. Cabin penetration and gross acceleration are the primary threats in an explosive event. Cabin penetration crushes occupants, damaging the lower body. Acceleration causes death at high magnitudes. This investigation develops a process of designing armour that simultaneously mitigates cabin penetration and acceleration. The hybrid cellular automaton (HCA) method of topology optimization has proven efficient and robust in problems involving large, plastic deformations such as crash impact. Here HCA is extended to the design of armour under blast loading. The ability to distribute two metallic phases, as opposed to one material and void, is also added. The blast wave energy transforms on impact into internal energy (IE) inside the solid medium. Maximum attenuation occurs with maximized IE. The resulting structures show HCA's potential for designing blast mitigating armour structures.

A process insight repository supporting process optimization

OpenAIRE

Vetlugin, Andrey

2012-01-01

Existing solutions for analysis and optimization of manufacturing processes, such as online analysis processing or statistical calculations, have shortcomings that limit continuous process improvements. In particular, they lack means of storing and integrating the results of analysis. This makes the valuable information that can be used for process optimizations used only once and then disposed. The goal of the Advanced Manufacturing Analytics (AdMA) research project is to design an integrate...

MODERNIZATION OF TECHNOLOGICAL LINE FOR CELLULAR EXTRUSION PROCESS

Directory of Open Access Journals (Sweden)

Tomasz Garbacz

2014-06-01

As part of the modernization of the cellular extrusion technology the extrusion head was designed and made. During the designing and modeling of the head the Auto CAD programe was used. After the prototyping the extrusion head was tested. In the article specification of cellular extrusion process of thermoplastics was presented. In the research, the endothermal chemical blowing agents in amount 1,0% by mass were used. The quantity of used blowing agent has a direct influence on density and structure of the extruded product of modified polymers. However, these properties have further influence on porosity, impact strength, hardness, tensile strength and another.

Navigating neurites utilize cellular topography of Schwann cell somas and processes for optimal guidance

Science.gov (United States)

Lopez-Fagundo, Cristina; Mitchel, Jennifer A.; Ramchal, Talisha D.; Dingle, Yu-Ting L.; Hoffman-Kim, Diane

2013-01-01

The path created by aligned Schwann cells (SCs) after nerve injury underlies peripheral nerve regeneration. We developed geometric bioinspired substrates to extract key information needed for axon guidance by deconstructing the topographical cues presented by SCs. We have previously reported materials that directly replicate SC topography with micro- and nanoscale resolution, but a detailed explanation of the means of directed axon extension on SC topography has not yet been described. Here, using neurite tracing and time-lapse microscopy, we analyzed the SC features that influence axon guidance. Novel poly(dimethylsiloxane) materials, fabricated via photolithography, incorporated bioinspired topographical components with the shapes and sizes of aligned SCs, namely somas and processes, where the length of the processes were varied but the soma geometry and dimensions were kept constant. Rat dorsal root ganglia neurites aligned to all materials presenting bioinspired topography after a 5 days in culture and to bioinspired materials presenting soma and process features after only 17 hours in culture. Key findings of this study were: Neurite response to underlying bioinspired topographical features was time dependent, where at 5 days, neurites aligned most strongly to materials presenting combinations of soma and process features, with higher than average density of either process or soma features; but at 17 hours they aligned more strongly to materials presenting average densities of soma and process features and to materials presenting process features only. These studies elucidate the influence of SC topography on axon guidance in a time-dependent setting and have implications for the optimization of nerve regeneration strategies. PMID:23557939

Using Electromagnetic Algorithm for Total Costs of Sub-contractor Optimization in the Cellular Manufacturing Problem

Directory of Open Access Journals (Sweden)

Mohammad Reza Shahriari

2016-12-01

Full Text Available In this paper, we present a non-linear binary programing for optimizing a specific cost in cellular manufacturing system in a controlled production condition. The system parameters are determined by the continuous distribution functions. The aim of the presented model is to optimize the total cost of imposed sub-contractors to the manufacturing system by determining how to allocate the machines and parts to each seller. In this system, DM could control the occupation level of each machine in the system. For solving the presented model, we used the electromagnetic meta-heuristic algorithm and Taguchi method for determining the optimal algorithm parameters.

Dynamic Optimization of UV Flash Processes

DEFF Research Database (Denmark)

Ritschel, Tobias Kasper Skovborg; Capolei, Andrea; Jørgensen, John Bagterp

2017-01-01

UV ash processes, also referred to as isoenergetic-isochoric ash processes, occur for dynamic simulation and optimization of vapor-liquid equilibrium processes. Dynamic optimization and nonlinear model predictive control of distillation columns, certain two-phase ow problems, as well as oil reser...... that the optimization solver, the compiler, and high-performance linear algebra software are all important for e_cient dynamic optimization of UV ash processes....

Algorithm for cellular reprogramming.

Science.gov (United States)

Ronquist, Scott; Patterson, Geoff; Muir, Lindsey A; Lindsly, Stephen; Chen, Haiming; Brown, Markus; Wicha, Max S; Bloch, Anthony; Brockett, Roger; Rajapakse, Indika

2017-11-07

The day we understand the time evolution of subcellular events at a level of detail comparable to physical systems governed by Newton's laws of motion seems far away. Even so, quantitative approaches to cellular dynamics add to our understanding of cell biology. With data-guided frameworks we can develop better predictions about, and methods for, control over specific biological processes and system-wide cell behavior. Here we describe an approach for optimizing the use of transcription factors (TFs) in cellular reprogramming, based on a device commonly used in optimal control. We construct an approximate model for the natural evolution of a cell-cycle-synchronized population of human fibroblasts, based on data obtained by sampling the expression of 22,083 genes at several time points during the cell cycle. To arrive at a model of moderate complexity, we cluster gene expression based on division of the genome into topologically associating domains (TADs) and then model the dynamics of TAD expression levels. Based on this dynamical model and additional data, such as known TF binding sites and activity, we develop a methodology for identifying the top TF candidates for a specific cellular reprogramming task. Our data-guided methodology identifies a number of TFs previously validated for reprogramming and/or natural differentiation and predicts some potentially useful combinations of TFs. Our findings highlight the immense potential of dynamical models, mathematics, and data-guided methodologies for improving strategies for control over biological processes. Copyright © 2017 the Author(s). Published by PNAS.

PM - processing for manufacturing of metals with cellular structures

International Nuclear Information System (INIS)

Strobl, S.; Danninger, H.

2001-01-01

In this review the major Processes about manufacturing of metals with cellular structure are described - based on powder metallurgy, chemical deposition and some other methods (without melting techniques). It can be shown that during the last decade many interesting innovations led to new production methods to design cellular materials. Some of them are used nowadays in industry. Also characterization and properties become more important and have therefore been carried out carefully, because of their strong influence on the functions and applications of such materials. (author)

Honing process optimization algorithms

Science.gov (United States)

Kadyrov, Ramil R.; Charikov, Pavel N.; Pryanichnikova, Valeria V.

2018-03-01

This article considers the relevance of honing processes for creating high-quality mechanical engineering products. The features of the honing process are revealed and such important concepts as the task for optimization of honing operations, the optimal structure of the honing working cycles, stepped and stepless honing cycles, simulation of processing and its purpose are emphasized. It is noted that the reliability of the mathematical model determines the quality parameters of the honing process control. An algorithm for continuous control of the honing process is proposed. The process model reliably describes the machining of a workpiece in a sufficiently wide area and can be used to operate the CNC machine CC743.

Efficiency of cellular information processing

International Nuclear Information System (INIS)

Barato, Andre C; Hartich, David; Seifert, Udo

2014-01-01

We show that a rate of conditional Shannon entropy reduction, characterizing the learning of an internal process about an external process, is bounded by the thermodynamic entropy production. This approach allows for the definition of an informational efficiency that can be used to study cellular information processing. We analyze three models of increasing complexity inspired by the Escherichia coli sensory network, where the external process is an external ligand concentration jumping between two values. We start with a simple model for which ATP must be consumed so that a protein inside the cell can learn about the external concentration. With a second model for a single receptor we show that the rate at which the receptor learns about the external environment can be nonzero even without any dissipation inside the cell since chemical work done by the external process compensates for this learning rate. The third model is more complete, also containing adaptation. For this model we show inter alia that a bacterium in an environment that changes at a very slow time-scale is quite inefficient, dissipating much more than it learns. Using the concept of a coarse-grained learning rate, we show for the model with adaptation that while the activity learns about the external signal the option of changing the methylation level increases the concentration range for which the learning rate is substantial. (paper)

Optimal operation of batch membrane processes

CERN Document Server

Paulen, Radoslav

2016-01-01

This study concentrates on a general optimization of a particular class of membrane separation processes: those involving batch diafiltration. Existing practices are explained and operational improvements based on optimal control theory are suggested. The first part of the book introduces the theory of membrane processes, optimal control and dynamic optimization. Separation problems are defined and mathematical models of batch membrane processes derived. The control theory focuses on problems of dynamic optimization from a chemical-engineering point of view. Analytical and numerical methods that can be exploited to treat problems of optimal control for membrane processes are described. The second part of the text builds on this theoretical basis to establish solutions for membrane models of increasing complexity. Each chapter starts with a derivation of optimal operation and continues with case studies exemplifying various aspects of the control problems under consideration. The authors work their way from th...

FPGA Implementation of one-dimensional and two-dimensional cellular automata

International Nuclear Information System (INIS)

D'Antone, I.

1999-01-01

This report describes the hardware implementation of one-dimensional and two-dimensional cellular automata (CAs). After a general introduction to the cellular automata, we consider a one-dimensional CA used to implement pseudo-random techniques in built-in self test for VLSI. Due to the increase in digital ASIC complexity, testing is becoming one of the major costs in the VLSI production. The high electronics complexity, used in particle physics experiments, demands higher reliability than in the past time. General criterions are given to evaluate the feasibility of the circuit used for testing and some quantitative parameters are underlined to optimize the architecture of the cellular automaton. Furthermore, we propose a two-dimensional CA that performs a peak finding algorithm in a matrix of cells mapping a sub-region of a calorimeter. As in a two-dimensional filtering process, the peaks of the energy clusters are found in one evolution step. This CA belongs to Wolfram class II cellular automata. Some quantitative parameters are given to optimize the architecture of the cellular automaton implemented in a commercial field programmable gate array (FPGA)

Piezo Proteins: Regulators of Mechanosensation and Other Cellular Processes*

Science.gov (United States)

Bagriantsev, Sviatoslav N.; Gracheva, Elena O.; Gallagher, Patrick G.

2014-01-01

Piezo proteins have recently been identified as ion channels mediating mechanosensory transduction in mammalian cells. Characterization of these channels has yielded important insights into mechanisms of somatosensation, as well as other mechano-associated biologic processes such as sensing of shear stress, particularly in the vasculature, and regulation of urine flow and bladder distention. Other roles for Piezo proteins have emerged, some unexpected, including participation in cellular development, volume regulation, cellular migration, proliferation, and elongation. Mutations in human Piezo proteins have been associated with a variety of disorders including hereditary xerocytosis and several syndromes with muscular contracture as a prominent feature. PMID:25305018

Image processing with a cellular nonlinear network

International Nuclear Information System (INIS)

Morfu, S.

2005-01-01

A cellular nonlinear network (CNN) based on uncoupled nonlinear oscillators is proposed for image processing purposes. It is shown theoretically and numerically that the contrast of an image loaded at the nodes of the CNN is strongly enhanced, even if this one is initially weak. An image inversion can be also obtained without reconfiguration of the network whereas a gray levels extraction can be performed with an additional threshold filtering. Lastly, an electronic implementation of this CNN is presented

Optimizing towing processes at airports

OpenAIRE

Du, Jia Yan

2015-01-01

This work addresses the optimization of push-back and towing processes at airports, as an important part of the turnaround process. A vehicle routing based scheduling model is introduced to find a cost optimal assignment of jobs to towing tractors in daily operations. A second model derives an investment strategy to optimize tractor fleet size and mix in the long-run. Column generation heuristics are proposed as solution procedures. The thesis concludes with a case study of a major European ...

Optimization of the diabetic nephropathy treatment with attention to the special features of cellular inflammation mechanisms

Directory of Open Access Journals (Sweden)

Тетяна Дмитрівна Щербань

2016-02-01

Full Text Available Aim. Optimization of the diabetic nephropathy (DN treatment in association with hypertonic disease (HD based on the study of neutrophil chain of pathogenic cellular mechanisms of these diseases development and the special features of its clinical course.Materials and methods. There were complexly examined 86 patients with HD associated with DN and 30 patients with isolated HD. The control group was formed by 30 practically healthy persons. The activity of NO-synthases in neutrophils was detected by Green colorimetric methods using Griess reagent. The expression of ІСАМ-1 (CD54, CD11b-integrin and inducible NO-synthase on neutrophils was detected by the indirect immunocytochemical method. Oxygen-depending activity of neutrophils was assessed in NBT-test.Results. Expression of adhesive molecules of CD54and CD11b-integrin on neutrophils of peripheral blood essentially increases (р <0,001 in patients with DN in association with HD comparing with isolated HD and the control group.At associated pathology on the background of high oxygen-depending activity of neutrophils its functional reserve decreases that results in intensification of inflammatory processes in kidneys (р<0,001.In comorbid patients chronization of pathological process results in imbalance of NO-synthases system in neutrophils: on the background of decrease of activity of constituent NO-synthases the expression and activity of inducible NO-synthase increase (р<0,001 .The use of L-arginine hydrochloride in the complex therapy of patients with DN associated with HD intensifies organoprotective effect of basal therapy, results in facilitation of the clinical course, decreases albuminuria, corrects the functional indices of neutrophils and diminishes imbalance in NO-synthases system.Conclusions. In patients with DN in association with HD the neutrophil chain of cellular inflammation mechanisms are activated: expression of adhesive molecules grows, oxygen-depending metabolism is

Piezo proteins: regulators of mechanosensation and other cellular processes.

Science.gov (United States)

Bagriantsev, Sviatoslav N; Gracheva, Elena O; Gallagher, Patrick G

2014-11-14

Piezo proteins have recently been identified as ion channels mediating mechanosensory transduction in mammalian cells. Characterization of these channels has yielded important insights into mechanisms of somatosensation, as well as other mechano-associated biologic processes such as sensing of shear stress, particularly in the vasculature, and regulation of urine flow and bladder distention. Other roles for Piezo proteins have emerged, some unexpected, including participation in cellular development, volume regulation, cellular migration, proliferation, and elongation. Mutations in human Piezo proteins have been associated with a variety of disorders including hereditary xerocytosis and several syndromes with muscular contracture as a prominent feature. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

Filtering and spectral processing of 1-D signals using cellular neural networks

NARCIS (Netherlands)

Moreira-Tamayo, O.; Pineda de Gyvez, J.

1996-01-01

This paper presents cellular neural networks (CNN) for one-dimensional discrete signal processing. Although CNN has been extensively used in image processing applications, little has been done for 1-dimensional signal processing. We propose a novel CNN architecture to carry out these tasks. This

Molecular processes in cellular arsenic metabolism

International Nuclear Information System (INIS)

Thomas, David J.

2007-01-01

Elucidating molecular processes that underlie accumulation, metabolism and binding of iAs and its methylated metabolites provides a basis for understanding the modes of action by which iAs acts as a toxin and a carcinogen. One approach to this problem is to construct a conceptual model that incorporates available information on molecular processes involved in the influx, metabolism, binding and efflux of arsenicals in cells. This conceptual model is initially conceived as a non-quantitative representation of critical molecular processes that can be used as a framework for experimental design and prediction. However, with refinement and incorporation of additional data, the conceptual model can be expressed in mathematical terms and should be useful for quantitative estimates of the kinetic and dynamic behavior of iAs and its methylated metabolites in cells. Development of a quantitative model will be facilitated by the availability of tools and techniques to manipulate molecular processes underlying transport of arsenicals across cell membranes or expression and activity of enzymes involved in methylation of arsenicals. This model of cellular metabolism might be integrated into more complex pharmacokinetic models for systemic metabolism of iAs and its methylated metabolites. It may also be useful in development of biologically based dose-response models describing the toxic and carcinogenic actions of arsenicals

Experimental design for dynamics identification of cellular processes.

Science.gov (United States)

Dinh, Vu; Rundell, Ann E; Buzzard, Gregery T

2014-03-01

We address the problem of using nonlinear models to design experiments to characterize the dynamics of cellular processes by using the approach of the Maximally Informative Next Experiment (MINE), which was introduced in W. Dong et al. (PLoS ONE 3(8):e3105, 2008) and independently in M.M. Donahue et al. (IET Syst. Biol. 4:249-262, 2010). In this approach, existing data is used to define a probability distribution on the parameters; the next measurement point is the one that yields the largest model output variance with this distribution. Building upon this approach, we introduce the Expected Dynamics Estimator (EDE), which is the expected value using this distribution of the output as a function of time. We prove the consistency of this estimator (uniform convergence to true dynamics) even when the chosen experiments cluster in a finite set of points. We extend this proof of consistency to various practical assumptions on noisy data and moderate levels of model mismatch. Through the derivation and proof, we develop a relaxed version of MINE that is more computationally tractable and robust than the original formulation. The results are illustrated with numerical examples on two nonlinear ordinary differential equation models of biomolecular and cellular processes.

Stochastic processes, multiscale modeling, and numerical methods for computational cellular biology

CERN Document Server

2017-01-01

This book focuses on the modeling and mathematical analysis of stochastic dynamical systems along with their simulations. The collected chapters will review fundamental and current topics and approaches to dynamical systems in cellular biology. This text aims to develop improved mathematical and computational methods with which to study biological processes. At the scale of a single cell, stochasticity becomes important due to low copy numbers of biological molecules, such as mRNA and proteins that take part in biochemical reactions driving cellular processes. When trying to describe such biological processes, the traditional deterministic models are often inadequate, precisely because of these low copy numbers. This book presents stochastic models, which are necessary to account for small particle numbers and extrinsic noise sources. The complexity of these models depend upon whether the biochemical reactions are diffusion-limited or reaction-limited. In the former case, one needs to adopt the framework of s...

Triple Bioluminescence Imaging for In Vivo Monitoring of Cellular Processes

Directory of Open Access Journals (Sweden)

Casey A Maguire

2013-01-01

Full Text Available Bioluminescence imaging (BLI has shown to be crucial for monitoring in vivo biological processes. So far, only dual bioluminescence imaging using firefly (Fluc and Renilla or Gaussia (Gluc luciferase has been achieved due to the lack of availability of other efficiently expressed luciferases using different substrates. Here, we characterized a codon-optimized luciferase from Vargula hilgendorfii (Vluc as a reporter for mammalian gene expression. We showed that Vluc can be multiplexed with Gluc and Fluc for sequential imaging of three distinct cellular phenomena in the same biological system using vargulin, coelenterazine, and D-luciferin substrates, respectively. We applied this triple imaging system to monitor the effect of soluble tumor necrosis factor-related apoptosis-inducing ligand (sTRAIL delivered using an adeno-associated viral vector (AAV on brain tumors in mice. Vluc imaging showed efficient sTRAIL gene delivery to the brain, while Fluc imaging revealed a robust antiglioma therapy. Further, nuclear factor-κB (NF-κB activation in response to sTRAIL binding to glioma cells death receptors was monitored by Gluc imaging. This work is the first demonstration of trimodal in vivo bioluminescence imaging and will have a broad applicability in many different fields including immunology, oncology, virology, and neuroscience.

Manufacturing processes of cellular metals. Part I. Liquid route processes

International Nuclear Information System (INIS)

Fernandez, P.; Cruz, L. J.; Coleto, J.

2008-01-01

With its interesting and particular characteristics, cellular metals are taking part of the great family of new materials. They can have open or closed porosity. At the present time, the major challenge for the materials researchers is based in the manufacturing techniques improvement in order to obtain reproducible and reliable cellular metals with quality. In the present paper, the different production methods to manufacture cellular metals by liquid route are reviewed; making a short description about the main parameters involved and the advantages and drawbacks in each of them. (Author) 106 refs

Can complex cellular processes be governed by simple linear rules?

Science.gov (United States)

Selvarajoo, Kumar; Tomita, Masaru; Tsuchiya, Masa

2009-02-01

Complex living systems have shown remarkably well-orchestrated, self-organized, robust, and stable behavior under a wide range of perturbations. However, despite the recent generation of high-throughput experimental datasets, basic cellular processes such as division, differentiation, and apoptosis still remain elusive. One of the key reasons is the lack of understanding of the governing principles of complex living systems. Here, we have reviewed the success of perturbation-response approaches, where without the requirement of detailed in vivo physiological parameters, the analysis of temporal concentration or activation response unravels biological network features such as causal relationships of reactant species, regulatory motifs, etc. Our review shows that simple linear rules govern the response behavior of biological networks in an ensemble of cells. It is daunting to know why such simplicity could hold in a complex heterogeneous environment. Provided physical reasons can be explained for these phenomena, major advancement in the understanding of basic cellular processes could be achieved.

Optimization and control of metal forming processes

NARCIS (Netherlands)

Havinga, Gosse Tjipke

2016-01-01

Inevitable variations in process and material properties limit the accuracy of metal forming processes. Robust optimization methods or control systems can be used to improve the production accuracy. Robust optimization methods are used to design production processes with low sensitivity to the

Simulation of electrochemical processes in cardiac tissue based on cellular automaton

International Nuclear Information System (INIS)

Avdeev, S A; Bogatov, N M

2014-01-01

A new class of cellular automata using special accumulative function for nonuniformity distribution is presented. Usage of this automata type for simulation of excitable media applied to electrochemical processes in human cardiac tissue is shown

Cellular Neural Network for Real Time Image Processing

International Nuclear Information System (INIS)

Vagliasindi, G.; Arena, P.; Fortuna, L.; Mazzitelli, G.; Murari, A.

2008-01-01

Since their introduction in 1988, Cellular Nonlinear Networks (CNNs) have found a key role as image processing instruments. Thanks to their structure they are able of processing individual pixels in a parallel way providing fast image processing capabilities that has been applied to a wide range of field among which nuclear fusion. In the last years, indeed, visible and infrared video cameras have become more and more important in tokamak fusion experiments for the twofold aim of understanding the physics and monitoring the safety of the operation. Examining the output of these cameras in real-time can provide significant information for plasma control and safety of the machines. The potentiality of CNNs can be exploited to this aim. To demonstrate the feasibility of the approach, CNN image processing has been applied to several tasks both at the Frascati Tokamak Upgrade (FTU) and the Joint European Torus (JET)

A genome-wide screen in yeast identifies specific oxidative stress genes required for the maintenance of sub-cellular redox homeostasis

NARCIS (Netherlands)

Ayer, A.; Fellermeier, S.; Fife, C.; Li, S.S.; Smits, G.; Meyer, A.J.; Dawes, I.W.; Perrone, G.G.

2012-01-01

Maintenance of an optimal redox environment is critical for appropriate functioning of cellular processes and cell survival. Despite the importance of maintaining redox homeostasis, it is not clear how the optimal redox potential is sensed and set, and the processes that impact redox on a

Piezo Proteins: Regulators of Mechanosensation and Other Cellular Processes*

OpenAIRE

Bagriantsev, Sviatoslav N.; Gracheva, Elena O.; Gallagher, Patrick G.

2014-01-01

Piezo proteins have recently been identified as ion channels mediating mechanosensory transduction in mammalian cells. Characterization of these channels has yielded important insights into mechanisms of somatosensation, as well as other mechano-associated biologic processes such as sensing of shear stress, particularly in the vasculature, and regulation of urine flow and bladder distention. Other roles for Piezo proteins have emerged, some unexpected, including participation in cellular deve...

Towards the prediction of essential genes by integration of network topology, cellular localization and biological process information

Directory of Open Access Journals (Sweden)

Lemke Ney

2009-09-01

Full Text Available Abstract Background The identification of essential genes is important for the understanding of the minimal requirements for cellular life and for practical purposes, such as drug design. However, the experimental techniques for essential genes discovery are labor-intensive and time-consuming. Considering these experimental constraints, a computational approach capable of accurately predicting essential genes would be of great value. We therefore present here a machine learning-based computational approach relying on network topological features, cellular localization and biological process information for prediction of essential genes. Results We constructed a decision tree-based meta-classifier and trained it on datasets with individual and grouped attributes-network topological features, cellular compartments and biological processes-to generate various predictors of essential genes. We showed that the predictors with better performances are those generated by datasets with integrated attributes. Using the predictor with all attributes, i.e., network topological features, cellular compartments and biological processes, we obtained the best predictor of essential genes that was then used to classify yeast genes with unknown essentiality status. Finally, we generated decision trees by training the J48 algorithm on datasets with all network topological features, cellular localization and biological process information to discover cellular rules for essentiality. We found that the number of protein physical interactions, the nuclear localization of proteins and the number of regulating transcription factors are the most important factors determining gene essentiality. Conclusion We were able to demonstrate that network topological features, cellular localization and biological process information are reliable predictors of essential genes. Moreover, by constructing decision trees based on these data, we could discover cellular rules governing

A Markov Process Inspired Cellular Automata Model of Road Traffic

OpenAIRE

Wang, Fa; Li, Li; Hu, Jianming; Ji, Yan; Yao, Danya; Zhang, Yi; Jin, Xuexiang; Su, Yuelong; Wei, Zheng

2008-01-01

To provide a more accurate description of the driving behaviors in vehicle queues, a namely Markov-Gap cellular automata model is proposed in this paper. It views the variation of the gap between two consequent vehicles as a Markov process whose stationary distribution corresponds to the observed distribution of practical gaps. The multiformity of this Markov process provides the model enough flexibility to describe various driving behaviors. Two examples are given to show how to specialize i...

PROPOSAL OF SPATIAL OPTIMIZATION OF PRODUCTION PROCESS IN PROCESS DESIGNER

Directory of Open Access Journals (Sweden)

Peter Malega

2015-03-01

Full Text Available This contribution is focused on optimizing the use of space in the production process using software Process Designer. The aim of this contribution is to suggest possible improvements to the existing layout of the selected production process. Production process was analysed in terms of inputs, outputs and course of actions. Nowadays there are many software solutions aimed at optimizing the use of space. One of these software products is the Process Designer, which belongs to the product line Tecnomatix. This software is primarily aimed at production planning. With Process Designer is possible to design the layout of production and subsequently to analyse the production or to change according to the current needs of the company.

Heterogeneous architecture to process swarm optimization algorithms

Directory of Open Access Journals (Sweden)

Maria A. Dávila-Guzmán

2014-01-01

Full Text Available Since few years ago, the parallel processing has been embedded in personal computers by including co-processing units as the graphics processing units resulting in a heterogeneous platform. This paper presents the implementation of swarm algorithms on this platform to solve several functions from optimization problems, where they highlight their inherent parallel processing and distributed control features. In the swarm algorithms, each individual and dimension problem are parallelized by the granularity of the processing system which also offer low communication latency between individuals through the embedded processing. To evaluate the potential of swarm algorithms on graphics processing units we have implemented two of them: the particle swarm optimization algorithm and the bacterial foraging optimization algorithm. The algorithms’ performance is measured using the acceleration where they are contrasted between a typical sequential processing platform and the NVIDIA GeForce GTX480 heterogeneous platform; the results show that the particle swarm algorithm obtained up to 36.82x and the bacterial foraging swarm algorithm obtained up to 9.26x. Finally, the effect to increase the size of the population is evaluated where we show both the dispersion and the quality of the solutions are decreased despite of high acceleration performance since the initial distribution of the individuals can converge to local optimal solution.

Food processing optimization using evolutionary algorithms | Enitan ...

African Journals Online (AJOL)

Evolutionary algorithms are widely used in single and multi-objective optimization. They are easy to use and provide solution(s) in one simulation run. They are used in food processing industries for decision making. Food processing presents constrained and unconstrained optimization problems. This paper reviews the ...

Rejuvenating cellular respiration for optimizing respiratory function: targeting mitochondria.

Science.gov (United States)

Agrawal, Anurag; Mabalirajan, Ulaganathan

2016-01-15

Altered bioenergetics with increased mitochondrial reactive oxygen species production and degradation of epithelial function are key aspects of pathogenesis in asthma and chronic obstructive pulmonary disease (COPD). This motif is not unique to obstructive airway disease, reported in related airway diseases such as bronchopulmonary dysplasia and parenchymal diseases such as pulmonary fibrosis. Similarly, mitochondrial dysfunction in vascular endothelium or skeletal muscles contributes to the development of pulmonary hypertension and systemic manifestations of lung disease. In experimental models of COPD or asthma, the use of mitochondria-targeted antioxidants, such as MitoQ, has substantially improved mitochondrial health and restored respiratory function. Modulation of noncoding RNA or protein regulators of mitochondrial biogenesis, dynamics, or degradation has been found to be effective in models of fibrosis, emphysema, asthma, and pulmonary hypertension. Transfer of healthy mitochondria to epithelial cells has been associated with remarkable therapeutic efficacy in models of acute lung injury and asthma. Together, these form a 3R model--repair, reprogramming, and replacement--for mitochondria-targeted therapies in lung disease. This review highlights the key role of mitochondrial function in lung health and disease, with a focus on asthma and COPD, and provides an overview of mitochondria-targeted strategies for rejuvenating cellular respiration and optimizing respiratory function in lung diseases. Copyright © 2016 the American Physiological Society.

Point process models for localization and interdependence of punctate cellular structures.

Science.gov (United States)

Li, Ying; Majarian, Timothy D; Naik, Armaghan W; Johnson, Gregory R; Murphy, Robert F

2016-07-01

Accurate representations of cellular organization for multiple eukaryotic cell types are required for creating predictive models of dynamic cellular function. To this end, we have previously developed the CellOrganizer platform, an open source system for generative modeling of cellular components from microscopy images. CellOrganizer models capture the inherent heterogeneity in the spatial distribution, size, and quantity of different components among a cell population. Furthermore, CellOrganizer can generate quantitatively realistic synthetic images that reflect the underlying cell population. A current focus of the project is to model the complex, interdependent nature of organelle localization. We built upon previous work on developing multiple non-parametric models of organelles or structures that show punctate patterns. The previous models described the relationships between the subcellular localization of puncta and the positions of cell and nuclear membranes and microtubules. We extend these models to consider the relationship to the endoplasmic reticulum (ER), and to consider the relationship between the positions of different puncta of the same type. Our results do not suggest that the punctate patterns we examined are dependent on ER position or inter- and intra-class proximity. With these results, we built classifiers to update previous assignments of proteins to one of 11 patterns in three distinct cell lines. Our generative models demonstrate the ability to construct statistically accurate representations of puncta localization from simple cellular markers in distinct cell types, capturing the complex phenomena of cellular structure interaction with little human input. This protocol represents a novel approach to vesicular protein annotation, a field that is often neglected in high-throughput microscopy. These results suggest that spatial point process models provide useful insight with respect to the spatial dependence between cellular structures. �

Gaussian process regression for geometry optimization

Science.gov (United States)

Denzel, Alexander; Kästner, Johannes

2018-03-01

We implemented a geometry optimizer based on Gaussian process regression (GPR) to find minimum structures on potential energy surfaces. We tested both a two times differentiable form of the Matérn kernel and the squared exponential kernel. The Matérn kernel performs much better. We give a detailed description of the optimization procedures. These include overshooting the step resulting from GPR in order to obtain a higher degree of interpolation vs. extrapolation. In a benchmark against the Limited-memory Broyden-Fletcher-Goldfarb-Shanno optimizer of the DL-FIND library on 26 test systems, we found the new optimizer to generally reduce the number of required optimization steps.

Discovery of Transition Rules for Cellular Automata Using Artificial Bee Colony and Particle Swarm Optimization Algorithms in Urban Growth Modeling

Directory of Open Access Journals (Sweden)

Fereydoun Naghibi

2016-12-01

Full Text Available This paper presents an advanced method in urban growth modeling to discover transition rules of cellular automata (CA using the artificial bee colony (ABC optimization algorithm. Also, comparisons between the simulation results of CA models optimized by the ABC algorithm and the particle swarm optimization algorithms (PSO as intelligent approaches were performed to evaluate the potential of the proposed methods. According to previous studies, swarm intelligence algorithms for solving optimization problems such as discovering transition rules of CA in land use change/urban growth modeling can produce reasonable results. Modeling of urban growth as a dynamic process is not straightforward because of the existence of nonlinearity and heterogeneity among effective involved variables which can cause a number of challenges for traditional CA. ABC algorithm, the new powerful swarm based optimization algorithms, can be used to capture optimized transition rules of CA. This paper has proposed a methodology based on remote sensing data for modeling urban growth with CA calibrated by the ABC algorithm. The performance of ABC-CA, PSO-CA, and CA-logistic models in land use change detection is tested for the city of Urmia, Iran, between 2004 and 2014. Validations of the models based on statistical measures such as overall accuracy, figure of merit, and total operating characteristic were made. We showed that the overall accuracy of the ABC-CA model was 89%, which was 1.5% and 6.2% higher than those of the PSO-CA and CA-logistic model, respectively. Moreover, the allocation disagreement (simulation error of the simulation results for the ABC-CA, PSO-CA, and CA-logistic models are 11%, 12.5%, and 17.2%, respectively. Finally, for all evaluation indices including running time, convergence capability, flexibility, statistical measurements, and the produced spatial patterns, the ABC-CA model performance showed relative improvement and therefore its superiority was

Thermodynamic Aspects and Reprogramming Cellular Energy Metabolism during the Fibrosis Process

Directory of Open Access Journals (Sweden)

Alexandre Vallée

2017-11-01

Full Text Available Fibrosis is characterized by fibroblast proliferation and fibroblast differentiation into myofibroblasts, which generate a relaxation-free contraction mechanism associated with excessive collagen synthesis in the extracellular matrix, which promotes irreversible tissue retraction evolving towards fibrosis. From a thermodynamic point of view, the mechanisms leading to fibrosis are irreversible processes that can occur through changing the entropy production rate. The thermodynamic behaviors of metabolic enzymes involved in fibrosis are modified by the dysregulation of both transforming growth factor β (TGF-β signaling and the canonical WNT/β-catenin pathway, leading to aerobic glycolysis, called the Warburg effect. Molecular signaling pathways leading to fibrosis are considered dissipative structures that exchange energy or matter with their environment far from the thermodynamic equilibrium. The myofibroblastic cells arise from exergonic processes by switching the core metabolism from oxidative phosphorylation to glycolysis, which generates energy and reprograms cellular energy metabolism to induce the process of myofibroblast differentiation. Circadian rhythms are far-from-equilibrium thermodynamic processes. They directly participate in regulating the TGF-β and WNT/β-catenin pathways involved in energetic dysregulation and enabling fibrosis. The present review focusses on the thermodynamic implications of the reprogramming of cellular energy metabolism, leading to fibroblast differentiation into myofibroblasts through the positive interplay between TGF-β and WNT/β-catenin pathways underlying in fibrosis.

Optimal control of a CSTR process

Directory of Open Access Journals (Sweden)

A. Soukkou

2008-12-01

Full Text Available Designing an effective criterion and learning algorithm for find the best structure is a major problem in the control design process. In this paper, the fuzzy optimal control methodology is applied to the design of the feedback loops of an Exothermic Continuous Stirred Tank Reactor system. The objective of design process is to find an optimal structure/gains of the Robust and Optimal Takagi Sugeno Fuzzy Controller (ROFLC. The control signal thus obtained will minimize a performance index, which is a function of the tracking/regulating errors, the quantity of the energy of the control signal applied to the system, and the number of fuzzy rules. The genetic learning is proposed for constructing the ROFLC. The chromosome genes are arranged into two parts, the binary-coded part contains the control genes and the real-coded part contains the genes parameters representing the fuzzy knowledge base. The effectiveness of this chromosome formulation enables the fuzzy sets and rules to be optimally reduced. The performances of the ROFLC are compared to these found by the traditional PD controller with Genetic Optimization (PD_GO. Simulations demonstrate that the proposed ROFLC and PD_GO has successfully met the design specifications.

Optimal control of switched systems arising in fermentation processes

CERN Document Server

Liu, Chongyang

2014-01-01

The book presents, in a systematic manner, the optimal controls under different mathematical models in fermentation processes. Variant mathematical models – i.e., those for multistage systems; switched autonomous systems; time-dependent and state-dependent switched systems; multistage time-delay systems and switched time-delay systems – for fed-batch fermentation processes are proposed and the theories and algorithms of their optimal control problems are studied and discussed. By putting forward novel methods and innovative tools, the book provides a state-of-the-art and comprehensive systematic treatment of optimal control problems arising in fermentation processes. It not only develops nonlinear dynamical system, optimal control theory and optimization algorithms, but can also help to increase productivity and provide valuable reference material on commercial fermentation processes.

Multi-Objective Optimization of Squeeze Casting Process using Genetic Algorithm and Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Patel G.C.M.

2016-09-01

Full Text Available The near net shaped manufacturing ability of squeeze casting process requiresto set the process variable combinations at their optimal levels to obtain both aesthetic appearance and internal soundness of the cast parts. The aesthetic and internal soundness of cast parts deal with surface roughness and tensile strength those can readily put the part in service without the requirement of costly secondary manufacturing processes (like polishing, shot blasting, plating, hear treatment etc.. It is difficult to determine the levels of the process variable (that is, pressure duration, squeeze pressure, pouring temperature and die temperature combinations for extreme values of the responses (that is, surface roughness, yield strength and ultimate tensile strength due to conflicting requirements. In the present manuscript, three population based search and optimization methods, namely genetic algorithm (GA, particle swarm optimization (PSO and multi-objective particle swarm optimization based on crowding distance (MOPSO-CD methods have been used to optimize multiple outputs simultaneously. Further, validation test has been conducted for the optimal casting conditions suggested by GA, PSO and MOPSO-CD. The results showed that PSO outperformed GA with regard to computation time.

Optimization of forging processes using finite element simulations

NARCIS (Netherlands)

Bonte, M.H.A.; Fourment, Lionel; Do, Tien-tho; van den Boogaard, Antonius H.; Huetink, Han

2010-01-01

During the last decades, simulation software based on the Finite Element Method (FEM) has significantly contributed to the design of feasible forming processes. Coupling FEM to mathematical optimization algorithms offers a promising opportunity to design optimal metal forming processes rather than

On the theory of optimal processes

International Nuclear Information System (INIS)

Goldenberg, P.; Provenzano, V.

1975-01-01

The theory of optimal processes is a recent mathematical formalism that is used to solve an important class of problems in science and in technology, that cannot be solved by classical variational techniques. An example of such processes would be the control of a nuclear reactor. Certain features of the theory of optimal processes are discussed, emphasizing the central contribution of Pontryagin with his formulation of the maximum principle. An application of the theory of optimum control is presented. The example is a time optimum problem applied to a simplified model of a nuclear reactor. It deals with the question of changing the equilibrium power level of the reactor in an optimum time

Model reduction for dynamic real-time optimization of chemical processes

NARCIS (Netherlands)

Van den Berg, J.

2005-01-01

The value of models in process industries becomes apparent in practice and literature where numerous successful applications are reported. Process models are being used for optimal plant design, simulation studies, for off-line and online process optimization. For online optimization applications

Topology Optimization - Engineering Contribution to Architectural Design

Science.gov (United States)

Tajs-Zielińska, Katarzyna; Bochenek, Bogdan

2017-10-01

The idea of the topology optimization is to find within a considered design domain the distribution of material that is optimal in some sense. Material, during optimization process, is redistributed and parts that are not necessary from objective point of view are removed. The result is a solid/void structure, for which an objective function is minimized. This paper presents an application of topology optimization to multi-material structures. The design domain defined by shape of a structure is divided into sub-regions, for which different materials are assigned. During design process material is relocated, but only within selected region. The proposed idea has been inspired by architectural designs like multi-material facades of buildings. The effectiveness of topology optimization is determined by proper choice of numerical optimization algorithm. This paper utilises very efficient heuristic method called Cellular Automata. Cellular Automata are mathematical, discrete idealization of a physical systems. Engineering implementation of Cellular Automata requires decomposition of the design domain into a uniform lattice of cells. It is assumed, that the interaction between cells takes place only within the neighbouring cells. The interaction is governed by simple, local update rules, which are based on heuristics or physical laws. The numerical studies show, that this method can be attractive alternative to traditional gradient-based algorithms. The proposed approach is evaluated by selected numerical examples of multi-material bridge structures, for which various material configurations are examined. The numerical studies demonstrated a significant influence the material sub-regions location on the final topologies. The influence of assumed volume fraction on final topologies for multi-material structures is also observed and discussed. The results of numerical calculations show, that this approach produces different results as compared with classical one

Simulative design and process optimization of the two-stage stretch-blow molding process

Energy Technology Data Exchange (ETDEWEB)

Hopmann, Ch.; Rasche, S.; Windeck, C. [Institute of Plastics Processing at RWTH Aachen University (IKV) Pontstraße 49, 52062 Aachen (Germany)

2015-05-22

The total production costs of PET bottles are significantly affected by the costs of raw material. Approximately 70 % of the total costs are spent for the raw material. Therefore, stretch-blow molding industry intends to reduce the total production costs by an optimized material efficiency. However, there is often a trade-off between an optimized material efficiency and required product properties. Due to a multitude of complex boundary conditions, the design process of new stretch-blow molded products is still a challenging task and is often based on empirical knowledge. Application of current CAE-tools supports the design process by reducing development time and costs. This paper describes an approach to determine optimized preform geometry and corresponding process parameters iteratively. The wall thickness distribution and the local stretch ratios of the blown bottle are calculated in a three-dimensional process simulation. Thereby, the wall thickness distribution is correlated with an objective function and preform geometry as well as process parameters are varied by an optimization algorithm. Taking into account the correlation between material usage, process history and resulting product properties, integrative coupled simulation steps, e.g. structural analyses or barrier simulations, are performed. The approach is applied on a 0.5 liter PET bottle of Krones AG, Neutraubling, Germany. The investigations point out that the design process can be supported by applying this simulative optimization approach. In an optimization study the total bottle weight is reduced from 18.5 g to 15.5 g. The validation of the computed results is in progress.

Simulative design and process optimization of the two-stage stretch-blow molding process

International Nuclear Information System (INIS)

Hopmann, Ch.; Rasche, S.; Windeck, C.

2015-01-01

The total production costs of PET bottles are significantly affected by the costs of raw material. Approximately 70 % of the total costs are spent for the raw material. Therefore, stretch-blow molding industry intends to reduce the total production costs by an optimized material efficiency. However, there is often a trade-off between an optimized material efficiency and required product properties. Due to a multitude of complex boundary conditions, the design process of new stretch-blow molded products is still a challenging task and is often based on empirical knowledge. Application of current CAE-tools supports the design process by reducing development time and costs. This paper describes an approach to determine optimized preform geometry and corresponding process parameters iteratively. The wall thickness distribution and the local stretch ratios of the blown bottle are calculated in a three-dimensional process simulation. Thereby, the wall thickness distribution is correlated with an objective function and preform geometry as well as process parameters are varied by an optimization algorithm. Taking into account the correlation between material usage, process history and resulting product properties, integrative coupled simulation steps, e.g. structural analyses or barrier simulations, are performed. The approach is applied on a 0.5 liter PET bottle of Krones AG, Neutraubling, Germany. The investigations point out that the design process can be supported by applying this simulative optimization approach. In an optimization study the total bottle weight is reduced from 18.5 g to 15.5 g. The validation of the computed results is in progress

Recent Progress on Data-Based Optimization for Mineral Processing Plants

Directory of Open Access Journals (Sweden)

Jinliang Ding

2017-04-01

Full Text Available In the globalized market environment, increasingly significant economic and environmental factors within complex industrial plants impose importance on the optimization of global production indices; such optimization includes improvements in production efficiency, product quality, and yield, along with reductions of energy and resource usage. This paper briefly overviews recent progress in data-driven hybrid intelligence optimization methods and technologies in improving the performance of global production indices in mineral processing. First, we provide the problem description. Next, we summarize recent progress in data-based optimization for mineral processing plants. This optimization consists of four layers: optimization of the target values for monthly global production indices, optimization of the target values for daily global production indices, optimization of the target values for operational indices, and automation systems for unit processes. We briefly overview recent progress in each of the different layers. Finally, we point out opportunities for future works in data-based optimization for mineral processing plants.

[Imaging center - optimization of the imaging process].

Science.gov (United States)

Busch, H-P

2013-04-01

Hospitals around the world are under increasing pressure to optimize the economic efficiency of treatment processes. Imaging is responsible for a great part of the success but also of the costs of treatment. In routine work an excessive supply of imaging methods leads to an "as well as" strategy up to the limit of the capacity without critical reflection. Exams that have no predictable influence on the clinical outcome are an unjustified burden for the patient. They are useless and threaten the financial situation and existence of the hospital. In recent years the focus of process optimization was exclusively on the quality and efficiency of performed single examinations. In the future critical discussion of the effectiveness of single exams in relation to the clinical outcome will be more important. Unnecessary exams can be avoided, only if in addition to the optimization of single exams (efficiency) there is an optimization strategy for the total imaging process (efficiency and effectiveness). This requires a new definition of processes (Imaging Pathway), new structures for organization (Imaging Center) and a new kind of thinking on the part of the medical staff. Motivation has to be changed from gratification of performed exams to gratification of process quality (medical quality, service quality, economics), including the avoidance of additional (unnecessary) exams. © Georg Thieme Verlag KG Stuttgart · New York.

Information theory based approaches to cellular signaling.

Science.gov (United States)

Waltermann, Christian; Klipp, Edda

2011-10-01

Cells interact with their environment and they have to react adequately to internal and external changes such changes in nutrient composition, physical properties like temperature or osmolarity and other stresses. More specifically, they must be able to evaluate whether the external change is significant or just in the range of noise. Based on multiple external parameters they have to compute an optimal response. Cellular signaling pathways are considered as the major means of information perception and transmission in cells. Here, we review different attempts to quantify information processing on the level of individual cells. We refer to Shannon entropy, mutual information, and informal measures of signaling pathway cross-talk and specificity. Information theory in systems biology has been successfully applied to identification of optimal pathway structures, mutual information and entropy as system response in sensitivity analysis, and quantification of input and output information. While the study of information transmission within the framework of information theory in technical systems is an advanced field with high impact in engineering and telecommunication, its application to biological objects and processes is still restricted to specific fields such as neuroscience, structural and molecular biology. However, in systems biology dealing with a holistic understanding of biochemical systems and cellular signaling only recently a number of examples for the application of information theory have emerged. This article is part of a Special Issue entitled Systems Biology of Microorganisms. Copyright © 2011 Elsevier B.V. All rights reserved.

Power Consumption Optimization in Tooth Gears Processing

Science.gov (United States)

Kanatnikov, N.; Harlamov, G.; Kanatnikova, P.; Pashmentova, A.

2018-01-01

The paper reviews the issue of optimization of technological process of tooth gears production of the power consumption criteria. The authors dwell on the indices used for cutting process estimation by the consumed energy criteria and their applicability in the analysis of the toothed wheel production process. The inventors proposed a method for optimization of power consumptions based on the spatial modeling of cutting pattern. The article is aimed at solving the problem of effective source management in order to achieve economical and ecological effect during the mechanical processing of toothed gears. The research was supported by Russian Science Foundation (project No. 17-79-10316).

Optimization of process variables for the microbial degradation of ...

African Journals Online (AJOL)

STORAGESEVER

2008-07-18

Jul 18, 2008 ... The optimum process conditions for maximizing phenol degradation (removal) ... cellular maintenance requirements on temperature makes it an important ..... the International Foundation for Science (IFS) for the financial ...

Cellular processing and destinies of artificial DNA nanostructures.

Science.gov (United States)

Lee, Di Sheng; Qian, Hang; Tay, Chor Yong; Leong, David Tai

2016-08-07

Since many bionanotechnologies are targeted at cells, understanding how and where their interactions occur and the subsequent results of these interactions is important. Changing the intrinsic properties of DNA nanostructures and linking them with interactions presents a holistic and powerful strategy for understanding dual nanostructure-biological systems. With the recent advances in DNA nanotechnology, DNA nanostructures present a great opportunity to understand the often convoluted mass of information pertaining to nanoparticle-biological interactions due to the more precise control over their chemistry, sizes, and shapes. Coupling just some of these designs with an understanding of biological processes is both a challenge and a source of opportunities. Despite continuous advances in the field of DNA nanotechnology, the intracellular fate of DNA nanostructures has remained unclear and controversial. Because understanding its cellular processing and destiny is a necessary prelude to any rational design of exciting and innovative bionanotechnology, in this review, we will discuss and provide a comprehensive picture relevant to the intracellular processing and the fate of various DNA nanostructures which have been remained elusive for some time. We will also link the unique capabilities of DNA to some novel ideas for developing next-generation bionanotechnologies.

A Taguchi approach on optimal process control parameters for HDPE pipe extrusion process

Science.gov (United States)

Sharma, G. V. S. S.; Rao, R. Umamaheswara; Rao, P. Srinivasa

2017-06-01

High-density polyethylene (HDPE) pipes find versatile applicability for transportation of water, sewage and slurry from one place to another. Hence, these pipes undergo tremendous pressure by the fluid carried. The present work entails the optimization of the withstanding pressure of the HDPE pipes using Taguchi technique. The traditional heuristic methodology stresses on a trial and error approach and relies heavily upon the accumulated experience of the process engineers for determining the optimal process control parameters. This results in setting up of less-than-optimal values. Hence, there arouse a necessity to determine optimal process control parameters for the pipe extrusion process, which can ensure robust pipe quality and process reliability. In the proposed optimization strategy, the design of experiments (DoE) are conducted wherein different control parameter combinations are analyzed by considering multiple setting levels of each control parameter. The concept of signal-to-noise ratio ( S/ N ratio) is applied and ultimately optimum values of process control parameters are obtained as: pushing zone temperature of 166 °C, Dimmer speed at 08 rpm, and Die head temperature to be 192 °C. Confirmation experimental run is also conducted to verify the analysis and research result and values proved to be in synchronization with the main experimental findings and the withstanding pressure showed a significant improvement from 0.60 to 1.004 Mpa.

Process control and optimization with simple interval calculation method

DEFF Research Database (Denmark)

Pomerantsev, A.; Rodionova, O.; Høskuldsson, Agnar

2006-01-01

for the quality improvement in the course of production. The latter is an active quality optimization, which takes into account the actual history of the process. The advocate approach is allied to the conventional method of multivariate statistical process control (MSPC) as it also employs the historical process......Methods of process control and optimization are presented and illustrated with a real world example. The optimization methods are based on the PLS block modeling as well as on the simple interval calculation methods of interval prediction and object status classification. It is proposed to employ...... the series of expanding PLS/SIC models in order to support the on-line process improvements. This method helps to predict the effect of planned actions on the product quality and thus enables passive quality control. We have also considered an optimization approach that proposes the correcting actions...

Multi-objective optimization of cellular scanning strategy in selective laser melting

DEFF Research Database (Denmark)

Ahrari, Ali; Deb, Kalyanmoy; Mohanty, Sankhya

2017-01-01

The scanning strategy for selective laser melting - an additive manufacturing process - determines the temperature fields during the manufacturing process, which in turn affects residual stresses and distortions, two of the main sources of process-induced defects. The goal of this study is to dev......The scanning strategy for selective laser melting - an additive manufacturing process - determines the temperature fields during the manufacturing process, which in turn affects residual stresses and distortions, two of the main sources of process-induced defects. The goal of this study......, the problem is a combination of combinatorial and choice optimization, which makes the problem difficult to solve. On a process simulation domain consisting of 32 cells, our multi-objective evolutionary method is able to find a set of trade-off solutions for the defined conflicting objectives, which cannot...

Process optimization of friction stir welding based on thermal models

DEFF Research Database (Denmark)

Larsen, Anders Astrup

2010-01-01

This thesis investigates how to apply optimization methods to numerical models of a friction stir welding process. The work is intended as a proof-of-concept using different methods that are applicable to models of high complexity, possibly with high computational cost, and without the possibility...... information of the high-fidelity model. The optimization schemes are applied to stationary thermal models of differing complexity of the friction stir welding process. The optimization problems considered are based on optimizing the temperature field in the workpiece by finding optimal translational speed....... Also an optimization problem based on a microstructure model is solved, allowing the hardness distribution in the plate to be optimized. The use of purely thermal models represents a simplification of the real process; nonetheless, it shows the applicability of the optimization methods considered...

(Sub-)Optimality of Treating Interference as Noise in the Cellular Uplink With Weak Interference

KAUST Repository

Gherekhloo, Soheil; Chaaban, Anas; Di, Chen; Sezgin, Aydin

2015-01-01

Despite the simplicity of the scheme of treating interference as noise (TIN), it was shown to be sum-capacity optimal in the Gaussian interference channel (IC) with very-weak (noisy) interference. In this paper, the two-user IC is altered by introducing an additional transmitter that wants to communicate with one of the receivers of the IC. The resulting network thus consists of a point-to-point channel interfering with a multiple access channel (MAC) and is denoted by PIMAC. The sum-capacity of the PIMAC is studied with main focus on the optimality of TIN. It turns out that TIN in its naive variant, where all transmitters are active and both receivers use TIN for decoding, is not the best choice for the PIMAC. In fact, a scheme that combines both time division multiple access and TIN (TDMA-TIN) strictly outperforms the naive-TIN scheme. Furthermore, it is shown that in some regimes, TDMA-TIN achieves the sum-capacity for the deterministic PIMAC and the sum-capacity within a constant gap for the Gaussian PIMAC. In addition, it is shown that, even for very-weak interference, there are some regimes where a combination of interference alignment with power control and TIN at the receiver side outperforms TDMA-TIN. As a consequence, on the one hand, TIN in a cellular uplink is approximately optimal in certain regimes. On the other hand, those regimes cannot be simply described by the strength of interference.

(Sub-)Optimality of Treating Interference as Noise in the Cellular Uplink With Weak Interference

KAUST Repository

Gherekhloo, Soheil

2015-11-09

Despite the simplicity of the scheme of treating interference as noise (TIN), it was shown to be sum-capacity optimal in the Gaussian interference channel (IC) with very-weak (noisy) interference. In this paper, the two-user IC is altered by introducing an additional transmitter that wants to communicate with one of the receivers of the IC. The resulting network thus consists of a point-to-point channel interfering with a multiple access channel (MAC) and is denoted by PIMAC. The sum-capacity of the PIMAC is studied with main focus on the optimality of TIN. It turns out that TIN in its naive variant, where all transmitters are active and both receivers use TIN for decoding, is not the best choice for the PIMAC. In fact, a scheme that combines both time division multiple access and TIN (TDMA-TIN) strictly outperforms the naive-TIN scheme. Furthermore, it is shown that in some regimes, TDMA-TIN achieves the sum-capacity for the deterministic PIMAC and the sum-capacity within a constant gap for the Gaussian PIMAC. In addition, it is shown that, even for very-weak interference, there are some regimes where a combination of interference alignment with power control and TIN at the receiver side outperforms TDMA-TIN. As a consequence, on the one hand, TIN in a cellular uplink is approximately optimal in certain regimes. On the other hand, those regimes cannot be simply described by the strength of interference.

Optimized Energy Procurement for Cellular Networks with Uncertain Renewable Energy Generation

KAUST Repository

Rached, Nadhir B.; Ghazzai, Hakim; Kadri, Abdullah; Alouini, Mohamed-Slim

2017-01-01

Renewable energy (RE) is an emerging solution for reducing carbon dioxide (CO2) emissions from cellular networks. One of the challenges of using RE sources is to handle its inherent uncertainty. In this paper, a RE powered cellular network

Design and optimization of food processing conditions

OpenAIRE

Silva, C. L. M.

1996-01-01

The main research objectives of the group are the design and optimization of food processing conditions. Most of the work already developed is on the use of mathematical modeling of transport phenomena and quantification of degradation kinetics as two tools to optimize the final quality of thermally processed food products. Recently, we initiated a project with the main goal of studying the effects of freezing and frozen storage on orange and melon juice pectinesterase activity and q...

Environment Aware Cellular Networks

KAUST Repository

Ghazzai, Hakim

2015-02-01

The unprecedented rise of mobile user demand over the years have led to an enormous growth of the energy consumption of wireless networks as well as the greenhouse gas emissions which are estimated currently to be around 70 million tons per year. This significant growth of energy consumption impels network companies to pay huge bills which represent around half of their operating expenditures. Therefore, many service providers, including mobile operators, are looking for new and modern green solutions to help reduce their expenses as well as the level of their CO2 emissions. Base stations are the most power greedy element in cellular networks: they drain around 80% of the total network energy consumption even during low traffic periods. Thus, there is a growing need to develop more energy-efficient techniques to enhance the green performance of future 4G/5G cellular networks. Due to the problem of traffic load fluctuations in cellular networks during different periods of the day and between different areas (shopping or business districts and residential areas), the base station sleeping strategy has been one of the main popular research topics in green communications. In this presentation, we present several practical green techniques that provide significant gains for mobile operators. Indeed, combined with the base station sleeping strategy, these techniques achieve not only a minimization of the fossil fuel consumption but also an enhancement of mobile operator profits. We start with an optimized cell planning method that considers varying spatial and temporal user densities. We then use the optimal transport theory in order to define the cell boundaries such that the network total transmit power is reduced. Afterwards, we exploit the features of the modern electrical grid, the smart grid, as a new tool of power management for cellular networks and we optimize the energy procurement from multiple energy retailers characterized by different prices and pollutant

Energy optimization of bread baking process undergoing quality constraints

International Nuclear Information System (INIS)

Papasidero, Davide; Pierucci, Sauro; Manenti, Flavio

2016-01-01

International home energy rating regulations are forcing to use efficient cooking equipment and processes towards energy saving and sustainability. For this reason gas ovens are replaced by the electric ones, to get the highest energy rating. Due to this fact, the study of the technologies related to the energy efficiency in cooking is increasingly developing. Indeed, big industries are working to the energy optimization of their processes since decades, while there is still a lot of room in energy optimization of single household appliances. The achievement of a higher efficiency can have a big impact on the society only if the use of modern equipment gets widespread. The combination of several energy sources (e.g. forced convection, irradiation, microwave, etc.) and their optimization is an emerging target for oven manufacturers towards optimal oven design. In this work, an energy consumption analysis and optimization is applied to the case of bread baking. Each source of energy gets the due importance and the process conditions are compared. A basic quality standard is guaranteed by taking into account some quality markers, which are relevant based on a consumer viewpoint. - Highlights: • Energy optimization is based on a validated finite-element model for bread baking. • Quality parameters for the product acceptability are introduced as constraints. • Dynamic optimization leads to 20% energy saving compared to non-optimized case. • The approach is applicable to many products, quality parameters, thermal processes. • Other heating processes can be easily integrated in the presented model.

Advanced Process Control Application and Optimization in Industrial Facilities

Directory of Open Access Journals (Sweden)

Howes S.

2015-01-01

Full Text Available This paper describes application of the new method and tool for system identification and PID tuning/advanced process control (APC optimization using the new 3G (geometric, gradient, gravity optimization method. It helps to design and implement control schemes directly inside the distributed control system (DCS or programmable logic controller (PLC. Also, the algorithm helps to identify process dynamics in closed-loop mode, optimizes controller parameters, and helps to develop adaptive control and model-based control (MBC. Application of the new 3G algorithm for designing and implementing APC schemes is presented. Optimization of primary and advanced control schemes stabilizes the process and allows the plant to run closer to process, equipment and economic constraints. This increases production rates, minimizes operating costs and improves product quality.

Optimization of thermal processing of canned mussels.

Science.gov (United States)

Ansorena, M R; Salvadori, V O

2011-10-01

The design and optimization of thermal processing of solid-liquid food mixtures, such as canned mussels, requires the knowledge of the thermal history at the slowest heating point. In general, this point does not coincide with the geometrical center of the can, and the results show that it is located along the axial axis at a height that depends on the brine content. In this study, a mathematical model for the prediction of the temperature at this point was developed using the discrete transfer function approach. Transfer function coefficients were experimentally obtained, and prediction equations fitted to consider other can dimensions and sampling interval. This model was coupled with an optimization routine in order to search for different retort temperature profiles to maximize a quality index. Both constant retort temperature (CRT) and variable retort temperature (VRT; discrete step-wise and exponential) were considered. In the CRT process, the optimal retort temperature was always between 134 °C and 137 °C, and high values of thiamine retention were achieved. A significant improvement in surface quality index was obtained for optimal VRT profiles compared to optimal CRT. The optimization procedure shown in this study produces results that justify its utilization in the industry.

Using Primary Literature in an Undergraduate Assignment: Demonstrating Connections among Cellular Processes

Science.gov (United States)

Yeong, Foong May

2015-01-01

Learning basic cell biology in an essential module can be daunting to second-year undergraduates, given the depth of information that is provided in major molecular and cell biology textbooks. Moreover, lectures on cellular pathways are organised into sections, such that at the end of lectures, students might not see how various processes are…

Tank Waste Remediation System optimized processing strategy

International Nuclear Information System (INIS)

Slaathaug, E.J.; Boldt, A.L.; Boomer, K.D.; Galbraith, J.D.; Leach, C.E.; Waldo, T.L.

1996-03-01

This report provides an alternative strategy evolved from the current Hanford Site Tank Waste Remediation System (TWRS) programmatic baseline for accomplishing the treatment and disposal of the Hanford Site tank wastes. This optimized processing strategy performs the major elements of the TWRS Program, but modifies the deployment of selected treatment technologies to reduce the program cost. The present program for development of waste retrieval, pretreatment, and vitrification technologies continues, but the optimized processing strategy reuses a single facility to accomplish the separations/low-activity waste (LAW) vitrification and the high-level waste (HLW) vitrification processes sequentially, thereby eliminating the need for a separate HLW vitrification facility

Optimization of lime treatment processes

International Nuclear Information System (INIS)

Zinck, J. M.; Aube, B. C.

2000-01-01

Lime neutralization technology used in the treatment of acid mine drainage and other acidic effluents is discussed. Theoretical studies and laboratory experiments designed to optimize the technology of lime neutralization processes and to improve the cost efficiency of the treatment process are described. Effluent quality, slaking temperature, aeration, solid-liquid separation, sludge production and geochemical stability have been studied experimentally and on site. Results show that through minor modification of the treatment process, costs, sludge volume generated, and metal released to the environment can be significantly reduced. 17 refs., 4 figs

Bidirectional optimization of the melting spinning process.

Science.gov (United States)

Liang, Xiao; Ding, Yongsheng; Wang, Zidong; Hao, Kuangrong; Hone, Kate; Wang, Huaping

2014-02-01

A bidirectional optimizing approach for the melting spinning process based on an immune-enhanced neural network is proposed. The proposed bidirectional model can not only reveal the internal nonlinear relationship between the process configuration and the quality indices of the fibers as final product, but also provide a tool for engineers to develop new fiber products with expected quality specifications. A neural network is taken as the basis for the bidirectional model, and an immune component is introduced to enlarge the searching scope of the solution field so that the neural network has a larger possibility to find the appropriate and reasonable solution, and the error of prediction can therefore be eliminated. The proposed intelligent model can also help to determine what kind of process configuration should be made in order to produce satisfactory fiber products. To make the proposed model practical to the manufacturing, a software platform is developed. Simulation results show that the proposed model can eliminate the approximation error raised by the neural network-based optimizing model, which is due to the extension of focusing scope by the artificial immune mechanism. Meanwhile, the proposed model with the corresponding software can conduct optimization in two directions, namely, the process optimization and category development, and the corresponding results outperform those with an ordinary neural network-based intelligent model. It is also proved that the proposed model has the potential to act as a valuable tool from which the engineers and decision makers of the spinning process could benefit.

Process optimization and particle engineering of micronized drug powders via milling.

Science.gov (United States)

Brunaugh, A; Smyth, H D C

2017-11-13

Process control and optimization is a critical aspect of process analytical technology (PAT), quality by design (QbD), and the implementation of continuous manufacturing procedures. While process control and optimization techniques have been utilized in other manufacturing industries for decades, the pharmaceutical industry has only recently begun to adopt these procedures. Micronization, particularly milling, is a generally low-yield, high-energy consumption process that is well suited for a process optimization mindset. This review discusses optimization of the pharmaceutical milling process through design space development, theoretical and empirical modeling, and monitoring of critical quality attributes.

Radio resource management for mobile traffic offloading in heterogeneous cellular networks

CERN Document Server

Wu, Yuan; Huang, Jianwei; Shen, Xuemin (Sherman)

2017-01-01

This SpringerBrief offers two concrete design examples for traffic offloading. The first is an optimal resource allocation for small-cell based traffic offloading that aims at minimizing mobile users’ data cost. The second is an optimal resource allocation for device-to-device assisted traffic offloading that also minimizes the total energy consumption and cellular link usage (while providing an overview of the challenging issues). Both examples illustrate the importance of proper resource allocation to the success of traffic offloading, show the consequent performance advantages of executing optimal resource allocation, and present the methodologies to achieve the corresponding optimal offloading solution for traffic offloading in heterogeneous cellular networks. The authors also include an overview of heterogeneous cellular networks and explain different traffic offloading paradigms ranging from uplink traffic offloading through small cells to downlink traffic offloading via mobile device-to-device cooper...

Global Detection of Live Virtual Machine Migration Based on Cellular Neural Networks

Directory of Open Access Journals (Sweden)

Kang Xie

2014-01-01

Full Text Available In order to meet the demands of operation monitoring of large scale, autoscaling, and heterogeneous virtual resources in the existing cloud computing, a new method of live virtual machine (VM migration detection algorithm based on the cellular neural networks (CNNs, is presented. Through analyzing the detection process, the parameter relationship of CNN is mapped as an optimization problem, in which improved particle swarm optimization algorithm based on bubble sort is used to solve the problem. Experimental results demonstrate that the proposed method can display the VM migration processing intuitively. Compared with the best fit heuristic algorithm, this approach reduces the processing time, and emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI implementation allowing the VM migration detection to be performed better.

Global detection of live virtual machine migration based on cellular neural networks.

Science.gov (United States)

Xie, Kang; Yang, Yixian; Zhang, Ling; Jing, Maohua; Xin, Yang; Li, Zhongxian

2014-01-01

In order to meet the demands of operation monitoring of large scale, autoscaling, and heterogeneous virtual resources in the existing cloud computing, a new method of live virtual machine (VM) migration detection algorithm based on the cellular neural networks (CNNs), is presented. Through analyzing the detection process, the parameter relationship of CNN is mapped as an optimization problem, in which improved particle swarm optimization algorithm based on bubble sort is used to solve the problem. Experimental results demonstrate that the proposed method can display the VM migration processing intuitively. Compared with the best fit heuristic algorithm, this approach reduces the processing time, and emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI) implementation allowing the VM migration detection to be performed better.

Mathematical Modeling and Experimental Validation of Nanoemulsion-Based Drug Transport across Cellular Barriers.

Science.gov (United States)

Kadakia, Ekta; Shah, Lipa; Amiji, Mansoor M

2017-07-01

Nanoemulsions have shown potential in delivering drug across epithelial and endothelial cell barriers, which express efflux transporters. However, their transport mechanisms are not entirely understood. Our goal was to investigate the cellular permeability of nanoemulsion-encapsulated drugs and apply mathematical modeling to elucidate transport mechanisms and sensitive nanoemulsion attributes. Transport studies were performed in Caco-2 cells, using fish oil nanoemulsions and a model substrate, rhodamine-123. Permeability data was modeled using a semi-mechanistic approach, capturing the following cellular processes: endocytotic uptake of the nanoemulsion, release of rhodamine-123 from the nanoemulsion, efflux and passive permeability of rhodamine-123 in aqueous solution. Nanoemulsions not only improved the permeability of rhodamine-123, but were also less sensitive to efflux transporters. The model captured bidirectional permeability results and identified sensitive processes, such as the release of the nanoemulsion-encapsulated drug and cellular uptake of the nanoemulsion. Mathematical description of cellular processes, improved our understanding of transport mechanisms, such as nanoemulsions don't inhibit efflux to improve drug permeability. Instead, their endocytotic uptake, results in higher intracellular drug concentrations, thereby increasing the concentration gradient and transcellular permeability across biological barriers. Modeling results indicated optimizing nanoemulsion attributes like the droplet size and intracellular drug release rate, may further improve drug permeability.

Dynamic cellular manufacturing system considering machine failure and workload balance

Science.gov (United States)

Rabbani, Masoud; Farrokhi-Asl, Hamed; Ravanbakhsh, Mohammad

2018-02-01

Machines are a key element in the production system and their failure causes irreparable effects in terms of cost and time. In this paper, a new multi-objective mathematical model for dynamic cellular manufacturing system (DCMS) is provided with consideration of machine reliability and alternative process routes. In this dynamic model, we attempt to resolve the problem of integrated family (part/machine cell) formation as well as the operators' assignment to the cells. The first objective minimizes the costs associated with the DCMS. The second objective optimizes the labor utilization and, finally, a minimum value of the variance of workload between different cells is obtained by the third objective function. Due to the NP-hard nature of the cellular manufacturing problem, the problem is initially validated by the GAMS software in small-sized problems, and then the model is solved by two well-known meta-heuristic methods including non-dominated sorting genetic algorithm and multi-objective particle swarm optimization in large-scaled problems. Finally, the results of the two algorithms are compared with respect to five different comparison metrics.

Cellular Decision Making by Non-Integrative Processing of TLR Inputs

Directory of Open Access Journals (Sweden)

Ryan A. Kellogg

2017-04-01

Full Text Available Cells receive a multitude of signals from the environment, but how they process simultaneous signaling inputs is not well understood. Response to infection, for example, involves parallel activation of multiple Toll-like receptors (TLRs that converge on the nuclear factor κB (NF-κB pathway. Although we increasingly understand inflammatory responses for isolated signals, it is not clear how cells process multiple signals that co-occur in physiological settings. We therefore examined a bacterial infection scenario involving co-stimulation of TLR4 and TLR2. Independent stimulation of these receptors induced distinct NF-κB dynamic profiles, although surprisingly, under co-stimulation, single cells continued to show ligand-specific dynamic responses characteristic of TLR2 or TLR4 signaling rather than a mixed response, comprising a cellular decision that we term “non-integrative” processing. Iterating modeling and microfluidic experiments revealed that non-integrative processing occurred through interaction of switch-like NF-κB activation, receptor-specific processing timescales, cell-to-cell variability, and TLR cross-tolerance mediated by multilayer negative feedback.

Use of Experimental Design for Peuhl Cheese Process Optimization ...

African Journals Online (AJOL)

Use of Experimental Design for Peuhl Cheese Process Optimization. ... Journal of Applied Sciences and Environmental Management ... This work consisting in use of a central composite design enables the determination of optimal process conditions concerning: leaf extract volume added (7 mL), heating temperature ...

Multi-stage and multi-response process optimization in Taguchi ...

African Journals Online (AJOL)

Product quality is all about reducing variations of key performance indicators. However, product manufacturing often, requires multiple processes with multiple indicators, which make reducing variation a complex task. There are tools used to optimize a single stage process independently which ensure local optimization ...

Cellular reprogramming dynamics follow a simple 1D reaction coordinate

Science.gov (United States)

Teja Pusuluri, Sai; Lang, Alex H.; Mehta, Pankaj; Castillo, Horacio E.

2018-01-01

Cellular reprogramming, the conversion of one cell type to another, induces global changes in gene expression involving thousands of genes, and understanding how cells globally alter their gene expression profile during reprogramming is an ongoing problem. Here we reanalyze time-course data on cellular reprogramming from differentiated cell types to induced pluripotent stem cells (iPSCs) and show that gene expression dynamics during reprogramming follow a simple 1D reaction coordinate. This reaction coordinate is independent of both the time it takes to reach the iPSC state as well as the details of the experimental protocol used. Using Monte-Carlo simulations, we show that such a reaction coordinate emerges from epigenetic landscape models where cellular reprogramming is viewed as a ‘barrier-crossing’ process between cell fates. Overall, our analysis and model suggest that gene expression dynamics during reprogramming follow a canonical trajectory consistent with the idea of an ‘optimal path’ in gene expression space for reprogramming.

Shock enhancement of cellular materials subjected to intensive pulse loading

Science.gov (United States)

Zhang, J.; Fan, J.; Wang, Z.; Zhao, L.; Li, Z.

2018-03-01

Cellular materials can dissipate a large amount of energy due to their considerable stress plateau, which contributes to their extensive applications in structural design for crashworthiness. However, in some experiments with specimens subjected to intense impact loads, transmitted stress enhancement has been observed, leading to severe damage to the objects protected. Transmitted stress through two-dimensional Voronoi cellular materials as a protective device is qualitatively studied in this paper. Dimensionless parameters of material properties and loading parameters are defined to give critical conditions for shock enhancement and clarify the correlation between the deformations and stress enhancement. The effect of relative density on this amplifying phenomenon is investigated as well. In addition, local strain fields are calculated by using the optimal local deformation gradient, which gives a clear presentation of deformations and possible local non-uniformity in the crushing process. This research provides valuable insight into the reliability of cellular materials as protective structures.

Cellular targets for improved manufacturing of virus-based biopharmaceuticals in animal cells.

Science.gov (United States)

Rodrigues, Ana F; Carrondo, Manuel J T; Alves, Paula M; Coroadinha, Ana S

2014-12-01

The past decade witnessed the entry into the market of new virus-based biopharmaceuticals produced in animal cells such as oncolytic vectors, virus-like particle vaccines, and gene transfer vectors. Therefore, increased attention and investment to optimize cell culture processes towards enhanced manufacturing of these bioproducts is anticipated. Herein, we review key findings on virus-host interactions that have been explored in cell culture optimization. Approaches supporting improved productivity or quality of vector preparations are discussed, mainly focusing on medium design and genetic manipulation. This review provides an integrated outline for current and future efforts in exploring cellular targets for the optimization of cell culture manufacturing of virus-based biopharmaceuticals. Copyright © 2014 Elsevier Ltd. All rights reserved.

Cellular-based preemption system

Science.gov (United States)

Bachelder, Aaron D. (Inventor)

2011-01-01

A cellular-based preemption system that uses existing cellular infrastructure to transmit preemption related data to allow safe passage of emergency vehicles through one or more intersections. A cellular unit in an emergency vehicle is used to generate position reports that are transmitted to the one or more intersections during an emergency response. Based on this position data, the one or more intersections calculate an estimated time of arrival (ETA) of the emergency vehicle, and transmit preemption commands to traffic signals at the intersections based on the calculated ETA. Additional techniques may be used for refining the position reports, ETA calculations, and the like. Such techniques include, without limitation, statistical preemption, map-matching, dead-reckoning, augmented navigation, and/or preemption optimization techniques, all of which are described in further detail in the above-referenced patent applications.

Optimizing a Laser Process for Making Carbon Nanotubes

Science.gov (United States)

Arepalli, Sivaram; Nikolaev, Pavel; Holmes, William

2010-01-01

A systematic experimental study has been performed to determine the effects of each of the operating conditions in a double-pulse laser ablation process that is used to produce single-wall carbon nanotubes (SWCNTs). The comprehensive data compiled in this study have been analyzed to recommend conditions for optimizing the process and scaling up the process for mass production. The double-pulse laser ablation process for making SWCNTs was developed by Rice University researchers. Of all currently known nanotube-synthesizing processes (arc and chemical vapor deposition), this process yields the greatest proportion of SWCNTs in the product material. The aforementioned process conditions are important for optimizing the production of SWCNTs and scaling up production. Reports of previous research (mostly at Rice University) toward optimization of process conditions mention effects of oven temperature and briefly mention effects of flow conditions, but no systematic, comprehensive study of the effects of process conditions was done prior to the study described here. This was a parametric study, in which several production runs were carried out, changing one operating condition for each run. The study involved variation of a total of nine parameters: the sequence of the laser pulses, pulse-separation time, laser pulse energy density, buffer gas (helium or nitrogen instead of argon), oven temperature, pressure, flow speed, inner diameter of the flow tube, and flow-tube material.

Parametric optimization of ultrasonic machining process using gravitational search and fireworks algorithms

Directory of Open Access Journals (Sweden)

Debkalpa Goswami

2015-03-01

Full Text Available Ultrasonic machining (USM is a mechanical material removal process used to erode holes and cavities in hard or brittle workpieces by using shaped tools, high-frequency mechanical motion and an abrasive slurry. Unlike other non-traditional machining processes, such as laser beam and electrical discharge machining, USM process does not thermally damage the workpiece or introduce significant levels of residual stress, which is important for survival of materials in service. For having enhanced machining performance and better machined job characteristics, it is often required to determine the optimal control parameter settings of an USM process. The earlier mathematical approaches for parametric optimization of USM processes have mostly yielded near optimal or sub-optimal solutions. In this paper, two almost unexplored non-conventional optimization techniques, i.e. gravitational search algorithm (GSA and fireworks algorithm (FWA are applied for parametric optimization of USM processes. The optimization performance of these two algorithms is compared with that of other popular population-based algorithms, and the effects of their algorithm parameters on the derived optimal solutions and computational speed are also investigated. It is observed that FWA provides the best optimal results for the considered USM processes.

Transition from a planar interface to cellular and dendritic structures during rapid solidification processing

Science.gov (United States)

Laxmanan, V.

1986-01-01

The development of theoretical models which characterize the planar-cellular and cell-dendrite transitions is described. The transitions are analyzed in terms of the Chalmers number, the solute Peclet number, and the tip stability parameter, which correlate microstructural features and processing conditions. The planar-cellular transition is examined using the constitutional supercooling theory of Chalmers et al., (1953) and it is observed that the Chalmers number is between 0 and 1 during dendritic and cellular growth. Analysis of cell-dendrite transition data reveal that the transition occurs when the solute Peclet number goes through a minimum, the primary arm spacings go through a maximum, and the Chalmers number is equal to 1/2. The relation between the tip stability parameter and the solute Peclet number is investigated and it is noted that the tip stability parameter is useful for studying dendritic growth in alloys.

Processed fruit juice ready to drink: screening acute toxicity at the cellular level

Directory of Open Access Journals (Sweden)

Erick Leal da Silva

2017-06-01

Full Text Available The present study evaluated the acute toxicity at the cellular level of processed juice ready for consumption Orange and Grape flavors, produced by five companies with significant influence on the food market of South American countries, especially in Brazil. This evaluation was performed in root meristem cells of Allium cepa L., at the exposure times of 24 and 48 hours, directly with marketed liquid preparations. Based on the results, it was found that fruit juices, of all companies considered, promoted significant antiproliferative effect to root meristems at the exposure time of 24 hours and resulted in at both exposure times, statistically significant number of mitotic spindle changes and chromosomal breaks. Therefore, under the study conditions, all juice samples analyzed were cytotoxic, genotoxic and mutagenic to root meristem cells. These results indicate that such beverages have relevant potential to cause cellular disorders and, thus, need to be evaluated more fully in more complex test systems, as those in rodents, and then establish specific toxicity at the cellular level of these juices and ensure the well-being of those who consume them.

GA based CNC turning center exploitation process parameters optimization

Directory of Open Access Journals (Sweden)

Z. Car

2009-01-01

Full Text Available This paper presents machining parameters (turning process optimization based on the use of artificial intelligence. To obtain greater efficiency and productivity of the machine tool, optimal cutting parameters have to be obtained. In order to find optimal cutting parameters, the genetic algorithm (GA has been used as an optimal solution finder. Optimization has to yield minimum machining time and minimum production cost, while considering technological and material constrains.

Mitochondrial correlates of signaling processes involved with the cellular response to eimeria infection in broiler chickens

Science.gov (United States)

Host cellular responses to coccidiosis infection are consistent with elements of apoptosis, autophagy, and necrosis. These processes are enhanced in the cell through cell-directed signaling or repressed through parasite-derived inhibitors of these processes favoring the survival of the parasite. Acr...

Nitric Oxide and ERK mediates regulation of cellular processes by Ecdysterone

Energy Technology Data Exchange (ETDEWEB)

Omanakuttan, Athira; Bose, Chinchu; Pandurangan, Nanjan; Kumar, Geetha B.; Banerji, Asoke; Nair, Bipin G., E-mail: bipin@amrita.edu

2016-08-15

The complex process of wound healing is a major problem associated with diabetes, venous or arterial disease, old age and infection. A wide range of pharmacological effects including anabolic, anti-diabetic and hepato-protective activities have been attributed to Ecdysterone. In earlier studies, Ecdysterone has been shown to modulate eNOS and iNOS expression in diabetic animals and activate osteogenic differentiation through the Extracellular-signal-Regulated Kinase (ERK) pathway in periodontal ligament stem cells. However, in the wound healing process, Ecdysterone has only been shown to enhance granulation tissue formation in rabbits. There have been no studies to date, which elucidate the molecular mechanism underlying the complex cellular process involved in wound healing. The present study, demonstrates a novel interaction between the phytosteroid Ecdysterone and Nitric Oxide Synthase (NOS), in an Epidermal Growth Factor Receptor (EGFR)-dependent manner, thereby promoting cell proliferation, cell spreading and cell migration. These observations were further supported by the 4-amino-5-methylamino- 2′ ,7′ -difluorofluorescein diacetate (DAF FM) fluorescence assay which indicated that Ecdysterone activates NOS resulting in increased Nitric Oxide (NO) production. Additionally, studies with inhibitors of both the EGFR and ERK, demonstrated that Ecdysterone activates NOS through modulation of EGFR and ERK. These results clearly demonstrate, for the first time, that Ecdysterone enhances Nitric Oxide production and modulates complex cellular processes by activating ERK1/2 through the EGF pathway. - Highlights: • Ecdysterone significantly enhances cell migration in a dose dependent manner. • Ecdysterone augments cell spreading during the initial phase of cell migration through actin cytoskeletal rearrangement. • Ecdysterone enhances cell proliferation in a nitric oxide dependent manner. • Ecdysterone enhances nitric oxide production via activation of EGFR

Nitric Oxide and ERK mediates regulation of cellular processes by Ecdysterone

International Nuclear Information System (INIS)

Omanakuttan, Athira; Bose, Chinchu; Pandurangan, Nanjan; Kumar, Geetha B.; Banerji, Asoke; Nair, Bipin G.

2016-01-01

The complex process of wound healing is a major problem associated with diabetes, venous or arterial disease, old age and infection. A wide range of pharmacological effects including anabolic, anti-diabetic and hepato-protective activities have been attributed to Ecdysterone. In earlier studies, Ecdysterone has been shown to modulate eNOS and iNOS expression in diabetic animals and activate osteogenic differentiation through the Extracellular-signal-Regulated Kinase (ERK) pathway in periodontal ligament stem cells. However, in the wound healing process, Ecdysterone has only been shown to enhance granulation tissue formation in rabbits. There have been no studies to date, which elucidate the molecular mechanism underlying the complex cellular process involved in wound healing. The present study, demonstrates a novel interaction between the phytosteroid Ecdysterone and Nitric Oxide Synthase (NOS), in an Epidermal Growth Factor Receptor (EGFR)-dependent manner, thereby promoting cell proliferation, cell spreading and cell migration. These observations were further supported by the 4-amino-5-methylamino- 2′ ,7′ -difluorofluorescein diacetate (DAF FM) fluorescence assay which indicated that Ecdysterone activates NOS resulting in increased Nitric Oxide (NO) production. Additionally, studies with inhibitors of both the EGFR and ERK, demonstrated that Ecdysterone activates NOS through modulation of EGFR and ERK. These results clearly demonstrate, for the first time, that Ecdysterone enhances Nitric Oxide production and modulates complex cellular processes by activating ERK1/2 through the EGF pathway. - Highlights: • Ecdysterone significantly enhances cell migration in a dose dependent manner. • Ecdysterone augments cell spreading during the initial phase of cell migration through actin cytoskeletal rearrangement. • Ecdysterone enhances cell proliferation in a nitric oxide dependent manner. • Ecdysterone enhances nitric oxide production via activation of EGFR

On process optimization considering LCA methodology.

Science.gov (United States)

Pieragostini, Carla; Mussati, Miguel C; Aguirre, Pío

2012-04-15

The goal of this work is to research the state-of-the-art in process optimization techniques and tools based on LCA, focused in the process engineering field. A collection of methods, approaches, applications, specific software packages, and insights regarding experiences and progress made in applying the LCA methodology coupled to optimization frameworks is provided, and general trends are identified. The "cradle-to-gate" concept to define the system boundaries is the most used approach in practice, instead of the "cradle-to-grave" approach. Normally, the relationship between inventory data and impact category indicators is linearly expressed by the characterization factors; then, synergic effects of the contaminants are neglected. Among the LCIA methods, the eco-indicator 99, which is based on the endpoint category and the panel method, is the most used in practice. A single environmental impact function, resulting from the aggregation of environmental impacts, is formulated as the environmental objective in most analyzed cases. SimaPro is the most used software for LCA applications in literature analyzed. The multi-objective optimization is the most used approach for dealing with this kind of problems, where the ε-constraint method for generating the Pareto set is the most applied technique. However, a renewed interest in formulating a single economic objective function in optimization frameworks can be observed, favored by the development of life cycle cost software and progress made in assessing costs of environmental externalities. Finally, a trend to deal with multi-period scenarios into integrated LCA-optimization frameworks can be distinguished providing more accurate results upon data availability. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Methodology for Optimization in Multistage Industrial Processes: A Pilot Study

Directory of Open Access Journals (Sweden)

Piotr Jarosz

2015-01-01

Full Text Available The paper introduces a methodology for optimization in multistage industrial processes with multiple quality criteria. Two ways of formulation of optimization problem and four different approaches to solve the problem are considered. Proposed methodologies were tested first on a virtual process described by benchmark functions and next were applied in optimization of multistage lead refining process.

Simulation-based optimization for product and process design

NARCIS (Netherlands)

Driessen, L.

2006-01-01

The design of products and processes has gradually shifted from a purely physical process towards a process that heavily relies on computer simulations (virtual prototyping). To optimize this virtual design process in terms of speed and final product quality, statistical methods and mathematical

Programmable cellular arrays. Faults testing and correcting in cellular arrays

International Nuclear Information System (INIS)

Cercel, L.

1978-03-01

A review of some recent researches about programmable cellular arrays in computing and digital processing of information systems is presented, and includes both combinational and sequential arrays, with full arbitrary behaviour, or which can realize better implementations of specialized blocks as: arithmetic units, counters, comparators, control systems, memory blocks, etc. Also, the paper presents applications of cellular arrays in microprogramming, in implementing of a specialized computer for matrix operations, in modeling of universal computing systems. The last section deals with problems of fault testing and correcting in cellular arrays. (author)

Hydrogen production by onboard gasoline processing – Process simulation and optimization

Energy Technology Data Exchange (ETDEWEB)

Bisaria, Vega; Smith, R.J. Byron,

2013-12-15

Highlights: • Process flow sheet for an onboard fuel processor for 100 kW fuel cell output was simulated. • Gasoline fuel requirement was found to be 30.55 kg/hr. • The fuel processor efficiency was found to be 95.98%. • An heat integrated optimum flow sheet was developed. - Abstract: Fuel cell vehicles have reached the commercialization stage and hybrid vehicles are already on the road. While hydrogen storage and infrastructure remain critical issues in stand alone commercialization of the technology, researchers are developing onboard fuel processors, which can convert a variety of fuels into hydrogen to power these fuel cell vehicles. The feasibility study of a 100 kW on board fuel processor based on gasoline fuel is carried out using process simulation. The steady state model has been developed with the help of Aspen HYSYS to analyze the fuel processor and total system performance. The components of the fuel processor are the fuel reforming unit, CO clean-up unit and auxiliary units. Optimization studies were carried out by analyzing the influence of various operating parameters such as oxygen to carbon ratio, steam to carbon ratio, temperature and pressure on the process equipments. From the steady state model optimization using Aspen HYSYS, an optimized reaction composition in terms of hydrogen production and carbon monoxide concentration corresponds to: oxygen to carbon ratio of 0.5 and steam to carbon ratio of 0.5. The fuel processor efficiency of 95.98% is obtained under these optimized conditions. The heat integration of the system using the composite curve, grand composite curve and utility composite curve were studied for the system. The most appropriate heat exchanger network from the generated ones was chosen and that was incorporated into the optimized flow sheet of the100 kW fuel processor. A completely heat integrated 100 kW fuel processor flow sheet using gasoline as fuel was thus successfully simulated and optimized.

Hydrogen production by onboard gasoline processing – Process simulation and optimization

International Nuclear Information System (INIS)

Bisaria, Vega; Smith, R.J. Byron

2013-01-01

Highlights: • Process flow sheet for an onboard fuel processor for 100 kW fuel cell output was simulated. • Gasoline fuel requirement was found to be 30.55 kg/hr. • The fuel processor efficiency was found to be 95.98%. • An heat integrated optimum flow sheet was developed. - Abstract: Fuel cell vehicles have reached the commercialization stage and hybrid vehicles are already on the road. While hydrogen storage and infrastructure remain critical issues in stand alone commercialization of the technology, researchers are developing onboard fuel processors, which can convert a variety of fuels into hydrogen to power these fuel cell vehicles. The feasibility study of a 100 kW on board fuel processor based on gasoline fuel is carried out using process simulation. The steady state model has been developed with the help of Aspen HYSYS to analyze the fuel processor and total system performance. The components of the fuel processor are the fuel reforming unit, CO clean-up unit and auxiliary units. Optimization studies were carried out by analyzing the influence of various operating parameters such as oxygen to carbon ratio, steam to carbon ratio, temperature and pressure on the process equipments. From the steady state model optimization using Aspen HYSYS, an optimized reaction composition in terms of hydrogen production and carbon monoxide concentration corresponds to: oxygen to carbon ratio of 0.5 and steam to carbon ratio of 0.5. The fuel processor efficiency of 95.98% is obtained under these optimized conditions. The heat integration of the system using the composite curve, grand composite curve and utility composite curve were studied for the system. The most appropriate heat exchanger network from the generated ones was chosen and that was incorporated into the optimized flow sheet of the100 kW fuel processor. A completely heat integrated 100 kW fuel processor flow sheet using gasoline as fuel was thus successfully simulated and optimized

Pavement maintenance optimization model using Markov Decision Processes

Science.gov (United States)

Mandiartha, P.; Duffield, C. F.; Razelan, I. S. b. M.; Ismail, A. b. H.

2017-09-01

This paper presents an optimization model for selection of pavement maintenance intervention using a theory of Markov Decision Processes (MDP). There are some particular characteristics of the MDP developed in this paper which distinguish it from other similar studies or optimization models intended for pavement maintenance policy development. These unique characteristics include a direct inclusion of constraints into the formulation of MDP, the use of an average cost method of MDP, and the policy development process based on the dual linear programming solution. The limited information or discussions that are available on these matters in terms of stochastic based optimization model in road network management motivates this study. This paper uses a data set acquired from road authorities of state of Victoria, Australia, to test the model and recommends steps in the computation of MDP based stochastic optimization model, leading to the development of optimum pavement maintenance policy.

Computer performance optimization systems, applications, processes

CERN Document Server

Osterhage, Wolfgang W

2013-01-01

Computing power performance was important at times when hardware was still expensive, because hardware had to be put to the best use. Later on this criterion was no longer critical, since hardware had become inexpensive. Meanwhile, however, people have realized that performance again plays a significant role, because of the major drain on system resources involved in developing complex applications. This book distinguishes between three levels of performance optimization: the system level, application level and business processes level. On each, optimizations can be achieved and cost-cutting p

STATISTICAL OPTIMIZATION OF PROCESS VARIABLES FOR ...

African Journals Online (AJOL)

2012-11-03

Nov 3, 2012 ... The osmotic dehydration process was optimized for water loss and solutes gain. ... basis) with safe moisture content for storage (10% wet basis) [3]. Due to ... sucrose, glucose, fructose, corn syrup and sodium chlo- ride have ...

Optimization of CernVM early boot process

CERN Document Server

Mazdin, Petra

2015-01-01

CernVM virtual machine is a Linux based virtual appliance optimized for High Energy Physics experiments. It is used for cloud computing, volunteer computing, and software development by the four large LHC experiments. The goal of this project is proling and optimizing the boot process of the CernVM. A key part was the development of a performance profiler for shell scripts as an extension to the popular BusyBox open source UNIX tool suite. Based on the measurements, costly shell code was replaced by more efficient, custom C programs. The results are compared to the original ones and successful optimization is proven.

Optimization of airport security process

Science.gov (United States)

Wei, Jianan

2017-05-01

In order to facilitate passenger travel, on the basis of ensuring public safety, the airport security process and scheduling to optimize. The stochastic Petri net is used to simulate the single channel security process, draw the reachable graph, construct the homogeneous Markov chain to realize the performance analysis of the security process network, and find the bottleneck to limit the passenger throughput. Curve changes in the flow of passengers to open a security channel for the initial state. When the passenger arrives at a rate that exceeds the processing capacity of the security channel, it is queued. The passenger reaches the acceptable threshold of the queuing time as the time to open or close the next channel, simulate the number of dynamic security channel scheduling to reduce the passenger queuing time.

Spectral and Energy Efficiencies in mmWave Cellular Networks for Optimal Utilization

Directory of Open Access Journals (Sweden)

Abdulbaset M. Hamed

2018-01-01

Full Text Available Millimeter wave (mmWave spectrum has been proposed for use in commercial cellular networks to relieve the already severely congested microwave spectrum. Thus, the design of an efficient mmWave cellular network has gained considerable importance and has to take into account regulations imposed by government agencies with regard to global warming and sustainable development. In this paper, a dense mmWave hexagonal cellular network with each cell consisting of a number of smaller cells with their own Base Stations (BSs is presented as a solution to meet the increasing demand for a variety of high data rate services and growing number of users of cellular networks. Since spectrum and power are critical resources in the design of such a network, a framework is presented that addresses efficient utilization of these resources in mmWave cellular networks in the 28 and 73 GHz bands. These bands are already an integral part of well-known standards such as IEEE 802.15.3c, IEEE 802.11ad, and IEEE 802.16.1. In the analysis, a well-known accurate mmWave channel model for Line of Sight (LOS and Non-Line of Sight (NLOS links is used. The cellular network is analyzed in terms of spectral efficiency, bit/s, energy efficiency, bit/J, area spectral efficiency, bit/s/m2, area energy efficiency, bit/J/m2, and network latency, s/bit. These efficiency metrics are illustrated, using Monte Carlo simulation, as a function of Signal-to-Noise Ratio (SNR, channel model parameters, user distance from BS, and BS transmission power. The efficiency metrics for optimum deployment of cellular networks in 28 and 73 GHz bands are identified. Results show that 73 GHz band achieves better spectrum efficiency and the 28 GHz band is superior in terms of energy efficiency. It is observed that while the latter band is expedient for indoor networks, the former band is appropriate for outdoor networks.

Cellular compartments cause multistability and allow cells to process more information

DEFF Research Database (Denmark)

Harrington, Heather A; Feliu, Elisenda; Wiuf, Carsten

2013-01-01

recent developments from dynamical systems and chemical reaction network theory to identify and characterize the key-role of the spatial organization of eukaryotic cells in cellular information processing. In particular, the existence of distinct compartments plays a pivotal role in whether a system...... is capable of multistationarity (multiple response states), and is thus directly linked to the amount of information that the signaling molecules can represent in the nucleus. Multistationarity provides a mechanism for switching between different response states in cell signaling systems and enables multiple...

On the optimization of endoreversible processes

Science.gov (United States)

Pescetti, D.

2014-03-01

This paper is intended for undergraduates and specialists in thermodynamics and related areas. We consider and discuss the optimization of endoreversible thermodynamic processes under the condition of maximum work production. Explicit thermodynamic analyses of the solutions are carried out for the Novikov and Agrawal processes. It is shown that the efficiencies at maximum work production and maximum power output are not necessarily equal. They are for the Novikov process but not for the Agrawal process. The role of the constraints is put into evidence. The physical aspects are enhanced by the simplicity of the involved mathematics.

Multidisciplinary Design Optimization (MDO) Methods: Their Synergy with Computer Technology in Design Process

Science.gov (United States)

Sobieszczanski-Sobieski, Jaroslaw

1998-01-01

The paper identifies speed, agility, human interface, generation of sensitivity information, task decomposition, and data transmission (including storage) as important attributes for a computer environment to have in order to support engineering design effectively. It is argued that when examined in terms of these attributes the presently available environment can be shown to be inadequate a radical improvement is needed, and it may be achieved by combining new methods that have recently emerged from multidisciplinary design optimization (MDO) with massively parallel processing computer technology. The caveat is that, for successful use of that technology in engineering computing, new paradigms for computing will have to be developed - specifically, innovative algorithms that are intrinsically parallel so that their performance scales up linearly with the number of processors. It may be speculated that the idea of simulating a complex behavior by interaction of a large number of very simple models may be an inspiration for the above algorithms, the cellular automata are an example. Because of the long lead time needed to develop and mature new paradigms, development should be now, even though the widespread availability of massively parallel processing is still a few years away.

Ring rolling process simulation for geometry optimization

Science.gov (United States)

Franchi, Rodolfo; Del Prete, Antonio; Donatiello, Iolanda; Calabrese, Maurizio

2017-10-01

Ring Rolling is a complex hot forming process where different rolls are involved in the production of seamless rings. Since each roll must be independently controlled, different speed laws must be set; usually, in the industrial environment, a milling curve is introduced to monitor the shape of the workpiece during the deformation in order to ensure the correct ring production. In the present paper a ring rolling process has been studied and optimized in order to obtain anular components to be used in aerospace applications. In particular, the influence of process input parameters (feed rate of the mandrel and angular speed of main roll) on geometrical features of the final ring has been evaluated. For this purpose, a three-dimensional finite element model for HRR (Hot Ring Rolling) has been implemented in SFTC DEFORM V11. The FEM model has been used to formulate a proper optimization problem. The optimization procedure has been implemented in the commercial software DS ISight in order to find the combination of process parameters which allows to minimize the percentage error of each obtained dimension with respect to its nominal value. The software allows to find the relationship between input and output parameters applying Response Surface Methodology (RSM), by using the exact values of output parameters in the control points of the design space explored through FEM simulation. Once this relationship is known, the values of the output parameters can be calculated for each combination of the input parameters. After the calculation of the response surfaces for the selected output parameters, an optimization procedure based on Genetic Algorithms has been applied. At the end, the error between each obtained dimension and its nominal value has been minimized. The constraints imposed were the maximum values of standard deviations of the dimensions obtained for the final ring.

Isobutane Alkylation Process Synthesis by means of Hybrid Simulation-Multiobjective Optimization

OpenAIRE

Fernandez-Torres, Maria J.; García, Norberto; Caballero, José A.

2014-01-01

Multiobjective Generalized Disjunctive Programming (MO-GDP) optimization has been used for the synthesis of an important industrial process, isobutane alkylation. The two objective functions to be simultaneously optimized are the environmental impact, determined by means of LCA (Life Cycle Assessment), and the economic potential of the process. The main reason for including the minimization of the environmental impact in the optimization process is the widespread environmental concern by the ...

Expert system and process optimization techniques for real-time monitoring and control of plasma processes

Science.gov (United States)

Cheng, Jie; Qian, Zhaogang; Irani, Keki B.; Etemad, Hossein; Elta, Michael E.

1991-03-01

To meet the ever-increasing demand of the rapidly-growing semiconductor manufacturing industry it is critical to have a comprehensive methodology integrating techniques for process optimization real-time monitoring and adaptive process control. To this end we have accomplished an integrated knowledge-based approach combining latest expert system technology machine learning method and traditional statistical process control (SPC) techniques. This knowledge-based approach is advantageous in that it makes it possible for the task of process optimization and adaptive control to be performed consistently and predictably. Furthermore this approach can be used to construct high-level and qualitative description of processes and thus make the process behavior easy to monitor predict and control. Two software packages RIST (Rule Induction and Statistical Testing) and KARSM (Knowledge Acquisition from Response Surface Methodology) have been developed and incorporated with two commercially available packages G2 (real-time expert system) and ULTRAMAX (a tool for sequential process optimization).

The Adjoint Method for Gradient-based Dynamic Optimization of UV Flash Processes

DEFF Research Database (Denmark)

Ritschel, Tobias Kasper Skovborg; Capolei, Andrea; Jørgensen, John Bagterp

2017-01-01

This paper presents a novel single-shooting algorithm for gradient-based solution of optimal control problems with vapor-liquid equilibrium constraints. Dynamic optimization of UV flash processes is relevant in nonlinear model predictive control of distillation columns, certain two-phase flow pro......-component flash process which demonstrate the importance of the optimization solver, the compiler, and the linear algebra software for the efficiency of dynamic optimization of UV flash processes....

Truss systems and shape optimization

Science.gov (United States)

Pricop, Mihai Victor; Bunea, Marian; Nedelcu, Roxana

2017-07-01

Structure optimization is an important topic because of its benefits and wide applicability range, from civil engineering to aerospace and automotive industries, contributing to a more green industry and life. Truss finite elements are still in use in many research/industrial codesfor their simple stiffness matrixand are naturally matching the requirements for cellular materials especially considering various 3D printing technologies. Optimality Criteria combined with Solid Isotropic Material with Penalization is the optimization method of choice, particularized for truss systems. Global locked structures areobtainedusinglocally locked lattice local organization, corresponding to structured or unstructured meshes. Post processing is important for downstream application of the method, to make a faster link to the CAD systems. To export the optimal structure in CATIA, a CATScript file is automatically generated. Results, findings and conclusions are given for two and three-dimensional cases.

Sequential metabolic phases as a means to optimize cellular output in a constant environment.

Science.gov (United States)

Palinkas, Aljoscha; Bulik, Sascha; Bockmayr, Alexander; Holzhütter, Hermann-Georg

2015-01-01

Temporal changes of gene expression are a well-known regulatory feature of all cells, which is commonly perceived as a strategy to adapt the proteome to varying external conditions. However, temporal (rhythmic and non-rhythmic) changes of gene expression are also observed under virtually constant external conditions. Here we hypothesize that such changes are a means to render the synthesis of the metabolic output more efficient than under conditions of constant gene activities. In order to substantiate this hypothesis, we used a flux-balance model of the cellular metabolism. The total time span spent on the production of a given set of target metabolites was split into a series of shorter time intervals (metabolic phases) during which only selected groups of metabolic genes are active. The related flux distributions were calculated under the constraint that genes can be either active or inactive whereby the amount of protein related to an active gene is only controlled by the number of active genes: the lower the number of active genes the more protein can be allocated to the enzymes carrying non-zero fluxes. This concept of a predominantly protein-limited efficiency of gene expression clearly differs from other concepts resting on the assumption of an optimal gene regulation capable of allocating to all enzymes and transporters just that fraction of protein necessary to prevent rate limitation. Applying this concept to a simplified metabolic network of the central carbon metabolism with glucose or lactate as alternative substrates, we demonstrate that switching between optimally chosen stationary flux modes comprising different sets of active genes allows producing a demanded amount of target metabolites in a significantly shorter time than by a single optimal flux mode at fixed gene activities. Our model-based findings suggest that temporal expression of metabolic genes can be advantageous even under conditions of constant external substrate supply.

Optimal fabrication processes for unidirectional metal-matrix composites: A computational simulation

Science.gov (United States)

Saravanos, D. A.; Murthy, P. L. N.; Morel, M.

1990-01-01

A method is proposed for optimizing the fabrication process of unidirectional metal matrix composites. The temperature and pressure histories are optimized such that the residual microstresses of the composite at the end of the fabrication process are minimized and the material integrity throughout the process is ensured. The response of the composite during the fabrication is simulated based on a nonlinear micromechanics theory. The optimal fabrication problem is formulated and solved with non-linear programming. Application cases regarding the optimization of the fabrication cool-down phases of unidirectional ultra-high modulus graphite/copper and silicon carbide/titanium composites are presented.

Optimal fabrication processes for unidirectional metal-matrix composites - A computational simulation

Science.gov (United States)

Saravanos, D. A.; Murthy, P. L. N.; Morel, M.

1990-01-01

A method is proposed for optimizing the fabrication process of unidirectional metal matrix composites. The temperature and pressure histories are optimized such that the residual microstresses of the composite at the end of the fabrication process are minimized and the material integrity throughout the process is ensured. The response of the composite during the fabrication is simulated based on a nonlinear micromechanics theory. The optimal fabrication problem is formulated and solved with nonlinear programming. Application cases regarding the optimization of the fabrication cool-down phases of unidirectional ultra-high modulus graphite/copper and silicon carbide/titanium composites are presented.

A Thermodynamic Library for Simulation and Optimization of Dynamic Processes

DEFF Research Database (Denmark)

Ritschel, Tobias Kasper Skovborg; Gaspar, Jozsef; Jørgensen, John Bagterp

2017-01-01

Process system tools, such as simulation and optimization of dynamic systems, are widely used in the process industries for development of operational strategies and control for process systems. These tools rely on thermodynamic models and many thermodynamic models have been developed for different...... compounds and mixtures. However, rigorous thermodynamic models are generally computationally intensive and not available as open-source libraries for process simulation and optimization. In this paper, we describe the application of a novel open-source rigorous thermodynamic library, ThermoLib, which...... is designed for dynamic simulation and optimization of vapor-liquid processes. ThermoLib is implemented in Matlab and C and uses cubic equations of state to compute vapor and liquid phase thermodynamic properties. The novelty of ThermoLib is that it provides analytical first and second order derivatives...

An Optimized Three-Level Design of Decoder Based on Nanoscale Quantum-Dot Cellular Automata

Science.gov (United States)

Seyedi, Saeid; Navimipour, Nima Jafari

2018-03-01

Quantum-dot Cellular Automata (QCA) has been potentially considered as a supersede to Complementary Metal-Oxide-Semiconductor (CMOS) because of its inherent advantages. Many QCA-based logic circuits with smaller feature size, improved operating frequency, and lower power consumption than CMOS have been offered. This technology works based on electron relations inside quantum-dots. Due to the importance of designing an optimized decoder in any digital circuit, in this paper, we design, implement and simulate a new 2-to-4 decoder based on QCA with low delay, area, and complexity. The logic functionality of the 2-to-4 decoder is verified using the QCADesigner tool. The results have shown that the proposed QCA-based decoder has high performance in terms of a number of cells, covered area, and time delay. Due to the lower clock pulse frequency, the proposed 2-to-4 decoder is helpful for building QCA-based sequential digital circuits with high performance.

Sequential optimization and reliability assessment method for metal forming processes

International Nuclear Information System (INIS)

Sahai, Atul; Schramm, Uwe; Buranathiti, Thaweepat; Chen Wei; Cao Jian; Xia, Cedric Z.

2004-01-01

Uncertainty is inevitable in any design process. The uncertainty could be due to the variations in geometry of the part, material properties or due to the lack of knowledge about the phenomena being modeled itself. Deterministic design optimization does not take uncertainty into account and worst case scenario assumptions lead to vastly over conservative design. Probabilistic design, such as reliability-based design and robust design, offers tools for making robust and reliable decisions under the presence of uncertainty in the design process. Probabilistic design optimization often involves double-loop procedure for optimization and iterative probabilistic assessment. This results in high computational demand. The high computational demand can be reduced by replacing computationally intensive simulation models with less costly surrogate models and by employing Sequential Optimization and reliability assessment (SORA) method. The SORA method uses a single-loop strategy with a series of cycles of deterministic optimization and reliability assessment. The deterministic optimization and reliability assessment is decoupled in each cycle. This leads to quick improvement of design from one cycle to other and increase in computational efficiency. This paper demonstrates the effectiveness of Sequential Optimization and Reliability Assessment (SORA) method when applied to designing a sheet metal flanging process. Surrogate models are used as less costly approximations to the computationally expensive Finite Element simulations

On-line optimal control improves gas processing

International Nuclear Information System (INIS)

Berkowitz, P.N.; Papadopoulos, M.N.

1992-01-01

This paper reports that the authors' companies jointly funded the first phase of a gas processing liquids optimization project that has the specific purposes to: Improve the return of processing natural gas liquids, Develop sets of control algorithms, Make available a low-cost solution suitable for small to medium-sized gas processing plants, Test and demonstrate the feasibility of line control. The ARCO Willard CO 2 gas recovery processing plant was chosen as the initial test site to demonstrate the application of multivariable on-line optimal control. One objective of this project is to support an R ampersand D effort to provide a standardized solution to the various types of gas processing plants in the U.S. Processes involved in these gas plants include cryogenic separations, demethanization, lean oil absorption, fractionation and gas treating. Next, the proposed solutions had to be simple yet comprehensive enough to allow an operator to maintain product specifications while operating over a wide range of gas input flow and composition. This had to be a supervisors system that remained on-line more than 95% of the time, and achieved reduced plant operating variability and improved variable cost control. It took more than a year to study various gas processes and to develop a control approach before a real application was finally exercised. An initial process for C 2 and CO 2 recoveries was chosen

A Generic Methodology for Superstructure Optimization of Different Processing Networks

DEFF Research Database (Denmark)

Bertran, Maria-Ona; Frauzem, Rebecca; Zhang, Lei

2016-01-01

In this paper, we propose a generic computer-aided methodology for synthesis of different processing networks using superstructure optimization. The methodology can handle different network optimization problems of various application fields. It integrates databases with a common data architecture......, a generic model to represent the processing steps, and appropriate optimization tools. A special software interface has been created to automate the steps in the methodology workflow, allow the transfer of data between tools and obtain the mathematical representation of the problem as required...

Optimization and standardization of pavement management processes.

Science.gov (United States)

2004-08-01

This report addresses issues related to optimization and standardization of current pavement management processes in Kentucky. Historical pavement management records were analyzed, which indicates that standardization is necessary in future pavement ...

Optimal redundant systems for works with random processing time

International Nuclear Information System (INIS)

Chen, M.; Nakagawa, T.

2013-01-01

This paper studies the optimal redundant policies for a manufacturing system processing jobs with random working times. The redundant units of the parallel systems and standby systems are subject to stochastic failures during the continuous production process. First, a job consisting of only one work is considered for both redundant systems and the expected cost functions are obtained. Next, each redundant system with a random number of units is assumed for a single work. The expected cost functions and the optimal expected numbers of units are derived for redundant systems. Subsequently, the production processes of N tandem works are introduced for parallel and standby systems, and the expected cost functions are also summarized. Finally, the number of works is estimated by a Poisson distribution for the parallel and standby systems. Numerical examples are given to demonstrate the optimization problems of redundant systems

Optimization of Nano-Process Deposition Parameters Based on Gravitational Search Algorithm

Directory of Open Access Journals (Sweden)

Norlina Mohd Sabri

2016-06-01

Full Text Available This research is focusing on the radio frequency (RF magnetron sputtering process, a physical vapor deposition technique which is widely used in thin film production. This process requires the optimized combination of deposition parameters in order to obtain the desirable thin film. The conventional method in the optimization of the deposition parameters had been reported to be costly and time consuming due to its trial and error nature. Thus, gravitational search algorithm (GSA technique had been proposed to solve this nano-process parameters optimization problem. In this research, the optimized parameter combination was expected to produce the desirable electrical and optical properties of the thin film. The performance of GSA in this research was compared with that of Particle Swarm Optimization (PSO, Genetic Algorithm (GA, Artificial Immune System (AIS and Ant Colony Optimization (ACO. Based on the overall results, the GSA optimized parameter combination had generated the best electrical and an acceptable optical properties of thin film compared to the others. This computational experiment is expected to overcome the problem of having to conduct repetitive laboratory experiments in obtaining the most optimized parameter combination. Based on this initial experiment, the adaptation of GSA into this problem could offer a more efficient and productive way of depositing quality thin film in the fabrication process.

Signal processing for molecular and cellular biological physics: an emerging field.

Science.gov (United States)

Little, Max A; Jones, Nick S

2013-02-13

Recent advances in our ability to watch the molecular and cellular processes of life in action--such as atomic force microscopy, optical tweezers and Forster fluorescence resonance energy transfer--raise challenges for digital signal processing (DSP) of the resulting experimental data. This article explores the unique properties of such biophysical time series that set them apart from other signals, such as the prevalence of abrupt jumps and steps, multi-modal distributions and autocorrelated noise. It exposes the problems with classical linear DSP algorithms applied to this kind of data, and describes new nonlinear and non-Gaussian algorithms that are able to extract information that is of direct relevance to biological physicists. It is argued that these new methods applied in this context typify the nascent field of biophysical DSP. Practical experimental examples are supplied.

Optimization of submerged arc welding process parameters using quasi-oppositional based Jaya algorithm

International Nuclear Information System (INIS)

Rao, R. Venkata; Rai, Dhiraj P.

2017-01-01

Submerged arc welding (SAW) is characterized as a multi-input process. Selection of optimum combination of process parameters of SAW process is a vital task in order to achieve high quality of weld and productivity. The objective of this work is to optimize the SAW process parameters using a simple optimization algorithm, which is fast, robust and convenient. Therefore, in this work a very recently proposed optimization algorithm named Jaya algorithm is applied to solve the optimization problems in SAW process. In addition, a modified version of Jaya algorithm with oppositional based learning, named “Quasi-oppositional based Jaya algorithm” (QO-Jaya) is proposed in order to improve the performance of the Jaya algorithm. Three optimization case studies are considered and the results obtained by Jaya algorithm and QO-Jaya algorithm are compared with the results obtained by well-known optimization algorithms such as Genetic algorithm (GA), Particle swarm optimization (PSO), Imperialist competitive algorithm (ICA) and Teaching learning based optimization (TLBO).

Optimization of submerged arc welding process parameters using quasi-oppositional based Jaya algorithm

Energy Technology Data Exchange (ETDEWEB)

Rao, R. Venkata; Rai, Dhiraj P. [Sardar Vallabhbhai National Institute of Technology, Gujarat (India)

2017-05-15

Submerged arc welding (SAW) is characterized as a multi-input process. Selection of optimum combination of process parameters of SAW process is a vital task in order to achieve high quality of weld and productivity. The objective of this work is to optimize the SAW process parameters using a simple optimization algorithm, which is fast, robust and convenient. Therefore, in this work a very recently proposed optimization algorithm named Jaya algorithm is applied to solve the optimization problems in SAW process. In addition, a modified version of Jaya algorithm with oppositional based learning, named “Quasi-oppositional based Jaya algorithm” (QO-Jaya) is proposed in order to improve the performance of the Jaya algorithm. Three optimization case studies are considered and the results obtained by Jaya algorithm and QO-Jaya algorithm are compared with the results obtained by well-known optimization algorithms such as Genetic algorithm (GA), Particle swarm optimization (PSO), Imperialist competitive algorithm (ICA) and Teaching learning based optimization (TLBO).

Data processing and optimization system to study prospective interstate power interconnections

Science.gov (United States)

Podkovalnikov, Sergei; Trofimov, Ivan; Trofimov, Leonid

2018-01-01

The paper presents Data processing and optimization system for studying and making rational decisions on the formation of interstate electric power interconnections, with aim to increasing effectiveness of their functioning and expansion. The technologies for building and integrating a Data processing and optimization system including an object-oriented database and a predictive mathematical model for optimizing the expansion of electric power systems ORIRES, are described. The technology of collection and pre-processing of non-structured data collected from various sources and its loading to the object-oriented database, as well as processing and presentation of information in the GIS system are described. One of the approaches of graphical visualization of the results of optimization model is considered on the example of calculating the option for expansion of the South Korean electric power grid.

USAF Logistics Process Optimization Study for the Aircraft Asset Sustainment Process. Volume 2

National Research Council Canada - National Science Library

Adamson, Anthony

1998-01-01

.... It is published as three separate volumes. Volume I, USAF Logistics Process Optimization Study for the Aircraft Asset Sustainment Process -- Phase II Report, discusses the result and cost/benefit analysis of testing three initiatives...

USAF Logistics Process Optimization Study for the Aircraft Asset Sustainment Process. Volume 1

National Research Council Canada - National Science Library

Adamson, Anthony

1998-01-01

.... It is published as three separate volumes. Volume I, USAF Logistics Process Optimization Study for the Aircraft Asset Sustainment Process -- Phase II Report, discusses the result and cost/benefit analysis of testing three initiatives...

Macro-architectured cellular materials: Properties, characteristic modes, and prediction methods

Science.gov (United States)

Ma, Zheng-Dong

2017-12-01

Macro-architectured cellular (MAC) material is defined as a class of engineered materials having configurable cells of relatively large (i.e., visible) size that can be architecturally designed to achieve various desired material properties. Two types of novel MAC materials, negative Poisson's ratio material and biomimetic tendon reinforced material, were introduced in this study. To estimate the effective material properties for structural analyses and to optimally design such materials, a set of suitable homogenization methods was developed that provided an effective means for the multiscale modeling of MAC materials. First, a strain-based homogenization method was developed using an approach that separated the strain field into a homogenized strain field and a strain variation field in the local cellular domain superposed on the homogenized strain field. The principle of virtual displacements for the relationship between the strain variation field and the homogenized strain field was then used to condense the strain variation field onto the homogenized strain field. The new method was then extended to a stress-based homogenization process based on the principle of virtual forces and further applied to address the discrete systems represented by the beam or frame structures of the aforementioned MAC materials. The characteristic modes and the stress recovery process used to predict the stress distribution inside the cellular domain and thus determine the material strengths and failures at the local level are also discussed.

Plate-impact loading of cellular structures formed by selective laser melting

International Nuclear Information System (INIS)

Winter, R E; Cotton, M; Harris, E J; Maw, J R; Chapman, D J; Eakins, D E; McShane, G

2014-01-01

Porous materials are of great interest because of improved energy absorption over their solid counterparts. Their properties, however, have been difficult to optimize. Additive manufacturing has emerged as a potential technique to closely define the structure and properties of porous components, i.e. density, strut width and pore size; however, the behaviour of these materials at very high impact energies remains largely unexplored. We describe an initial study of the dynamic compression response of lattice materials fabricated through additive manufacturing. Lattices consisting of an array of intersecting stainless steel rods were fabricated into discs using selective laser melting. The resulting discs were impacted against solid stainless steel targets at velocities ranging from 300 to 700 m s −1 using a gas gun. Continuum CTH simulations were performed to identify key features in the measured wave profiles, while 3D simulations, in which the individual cells were modelled, revealed details of microscale deformation during collapse of the lattice structure. The validated computer models have been used to provide an understanding of the deformation processes in the cellular samples. The study supports the optimization of cellular structures for application as energy absorbers. (paper)

Resource allocation for phantom cellular networks: Energy efficiency vs spectral efficiency

KAUST Repository

Abdelhady, Amr Mohamed Abdelaziz; Amin, Osama; Alouini, Mohamed-Slim

2016-01-01

Multi-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Mean-while, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-tier network architecture known as phantom cellular networks. The optimization framework includes both EE and SE, where we propose an algorithm that finds the SE and EE resource allocation strategies for phantom cellular networks. Then, we compare the performance of both design strategies versus the number of users, and phantom cells share of the total number of available resource blocks. We aim to investigate the effect of some system parameters to achieve improved SE performance at a non-significant loss in EE performance, or vice versa. It was found that increasing phantom cells share of resource blocks decreases the SE performance loss due to EE optimization when compared with the optimized SE performance. © 2016 IEEE.

Resource allocation for phantom cellular networks: Energy efficiency vs spectral efficiency

KAUST Repository

Abdelhady, Amr M.

2016-07-26

Multi-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Mean-while, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-tier network architecture known as phantom cellular networks. The optimization framework includes both EE and SE, where we propose an algorithm that finds the SE and EE resource allocation strategies for phantom cellular networks. Then, we compare the performance of both design strategies versus the number of users, and phantom cells share of the total number of available resource blocks. We aim to investigate the effect of some system parameters to achieve improved SE performance at a non-significant loss in EE performance, or vice versa. It was found that increasing phantom cells share of resource blocks decreases the SE performance loss due to EE optimization when compared with the optimized SE performance. © 2016 IEEE.

Energy Cost Minimization in Heterogeneous Cellular Networks with Hybrid Energy Supplies

Directory of Open Access Journals (Sweden)

Bang Wang

2016-01-01

Full Text Available The ever increasing data demand has led to the significant increase of energy consumption in cellular mobile networks. Recent advancements in heterogeneous cellular networks and green energy supplied base stations provide promising solutions for cellular communications industry. In this article, we first review the motivations and challenges as well as approaches to address the energy cost minimization problem for such green heterogeneous networks. Owing to the diversities of mobile traffic and renewable energy, the energy cost minimization problem involves both temporal and spatial optimization of resource allocation. We next present a new solution to illustrate how to combine the optimization of the temporal green energy allocation and spatial mobile traffic distribution. The whole optimization problem is decomposed into four subproblems, and correspondingly our proposed solution is divided into four parts: energy consumption estimation, green energy allocation, user association, and green energy reallocation. Simulation results demonstrate that our proposed algorithm can significantly reduce the total energy cost.

Topology Optimization for Reducing Additive Manufacturing Processing Distortions

Science.gov (United States)

2017-12-01

distribution is unlimited. 1. Introduction Additive manufacturing (AM) is a production method that involves gradual, layer- by-layer building of material... design space—allowing the production of pre- viously unmanufacturable topologically optimized structures—constraints remain. One constraint, for...ARL-TR-8242•DEC 2017 US Army Research Laboratory Topology Optimization for ReducingAdditive Manufacturing ProcessingDistortions by Raymond A Wildman

A novel approach in optimization problem for research reactors fuel plate using a synergy between cellular automata and quasi-simulated annealing methods

International Nuclear Information System (INIS)

Barati, Ramin

2014-01-01

Highlights: • An innovative optimization technique for multi-objective optimization is presented. • The technique utilizes combination of CA and quasi-simulated annealing. • Mass and deformation of fuel plate are considered as objective functions. • Computational burden is significantly reduced compared to classic tools. - Abstract: This paper presents a new and innovative optimization technique utilizing combination of cellular automata (CA) and quasi-simulated annealing (QSA) as solver concerning conceptual design optimization which is indeed a multi-objective optimization problem. Integrating CA and QSA into a unified optimizer tool has a great potential for solving multi-objective optimization problems. Simulating neighborhood effects while taking local information into account from CA and accepting transitions based on decreasing of objective function and Boltzmann distribution from QSA as transition rule make this tool effective in multi-objective optimization. Optimization of fuel plate safety design while taking into account major goals of conceptual design such as improving reliability and life-time – which are the most significant elements during shutdown – is a major multi-objective optimization problem. Due to hugeness of search space in fuel plate optimization problem, finding optimum solution in classical methods requires a huge amount of calculation and CPU time. The CA models, utilizing local information, require considerably less computation. In this study, minimizing both mass and deformation of fuel plate of a multipurpose research reactor (MPRR) are considered as objective functions. Results, speed, and qualification of proposed method are comparable with those of genetic algorithm and neural network methods applied to this problem before

Road maintenance optimization through a discrete-time semi-Markov decision process

International Nuclear Information System (INIS)

Zhang Xueqing; Gao Hui

2012-01-01

Optimization models are necessary for efficient and cost-effective maintenance of a road network. In this regard, road deterioration is commonly modeled as a discrete-time Markov process such that an optimal maintenance policy can be obtained based on the Markov decision process, or as a renewal process such that an optimal maintenance policy can be obtained based on the renewal theory. However, the discrete-time Markov process cannot capture the real time at which the state transits while the renewal process considers only one state and one maintenance action. In this paper, road deterioration is modeled as a semi-Markov process in which the state transition has the Markov property and the holding time in each state is assumed to follow a discrete Weibull distribution. Based on this semi-Markov process, linear programming models are formulated for both infinite and finite planning horizons in order to derive optimal maintenance policies to minimize the life-cycle cost of a road network. A hypothetical road network is used to illustrate the application of the proposed optimization models. The results indicate that these linear programming models are practical for the maintenance of a road network having a large number of road segments and that they are convenient to incorporate various constraints on the decision process, for example, performance requirements and available budgets. Although the optimal maintenance policies obtained for the road network are randomized stationary policies, the extent of this randomness in decision making is limited. The maintenance actions are deterministic for most states and the randomness in selecting actions occurs only for a few states.

Optimal Control of Beer Fermentation Process Using Differential ...

African Journals Online (AJOL)

Optimal Control of Beer Fermentation Process Using Differential Transform Method. ... Journal of Applied Sciences and Environmental Management ... The method of differential transform was used to obtain the solution governing the fermentation process; the system of equation was transformed using the differential ...

Mixing of two-component flow in a simplified stirred tank with cellular automaton method; Cellular automaton ho ni yoru kakuhan sonai no niseibunryu no kongo keisan

Energy Technology Data Exchange (ETDEWEB)

Watanabe, S; Takahashi, R [Tokyo Institute of Technology, Tokyo (Japan)

1996-01-25

The applicability of a cellular automaton technique to engineering problems will be examined by dealing with mixing in multicomponent flow. The quality and accumulation rate of the product depend on the mixing of raw materials basically. After thoroughly understanding the mixing process, we optimize the geometrical allocation of such elements as a propeller with casing, a chimney and a product output nozzle in a reactor. Usually mixing is formulated by partial differential equations of conservation laws and empirical formulae, and solved numerically by the finite difference technique. In order to evaluate the fine structure of time-dependent interfacial behavior in multicomponent flow, the cellular automaton technique is used, since this has an advantage of describing the pattern formation in detail. It will be demonstrated in the present paper that mixing of two-component immiscible flow is reasonably simulated mesoscopically. 13 refs., 17 figs.

Optimization of the production process using virtual model of a workspace

Science.gov (United States)

Monica, Z.

2015-11-01

Optimization of the production process is an element of the design cycle consisting of: problem definition, modelling, simulation, optimization and implementation. Without the use of simulation techniques, the only thing which could be achieved is larger or smaller improvement of the process, not the optimization (i.e., the best result it is possible to get for the conditions under which the process works). Optimization is generally management actions that are ultimately bring savings in time, resources, and raw materials and improve the performance of a specific process. It does not matter whether it is a service or manufacturing process. Optimizing the savings generated by improving and increasing the efficiency of the processes. Optimization consists primarily of organizational activities that require very little investment, or rely solely on the changing organization of work. Modern companies operating in a market economy shows a significant increase in interest in modern methods of production management and services. This trend is due to the high competitiveness among companies that want to achieve success are forced to continually modify the ways to manage and flexible response to changing demand. Modern methods of production management, not only imply a stable position of the company in the sector, but also influence the improvement of health and safety within the company and contribute to the implementation of more efficient rules for standardization work in the company. This is why in the paper is presented the application of such developed environment like Siemens NX to create the virtual model of a production system and to simulate as well as optimize its work. The analyzed system is the robotized workcell consisting of: machine tools, industrial robots, conveyors, auxiliary equipment and buffers. In the program could be defined the control program realizing the main task in the virtual workcell. It is possible, using this tool, to optimize both the

First-order Convex Optimization Methods for Signal and Image Processing

DEFF Research Database (Denmark)

Jensen, Tobias Lindstrøm

2012-01-01

In this thesis we investigate the use of first-order convex optimization methods applied to problems in signal and image processing. First we make a general introduction to convex optimization, first-order methods and their iteration complexity. Then we look at different techniques, which can...... be used with first-order methods such as smoothing, Lagrange multipliers and proximal gradient methods. We continue by presenting different applications of convex optimization and notable convex formulations with an emphasis on inverse problems and sparse signal processing. We also describe the multiple...

Probing Cellular Dynamics with Mesoscopic Simulations

DEFF Research Database (Denmark)

Shillcock, Julian C.

2010-01-01

Cellular processes span a huge range of length and time scales from the molecular to the near-macroscopic. Understanding how effects on one scale influence, and are themselves influenced by, those on lower and higher scales is a critical issue for the construction of models in Systems Biology....... Advances in computing hardware and software now allow explicit simulation of some aspects of cellular dynamics close to the molecular scale. Vesicle fusion is one example of such a process. Experiments, however, typically probe cellular behavior from the molecular scale up to microns. Standard particle...... soon be coupled to Mass Action models allowing the parameters in such models to be continuously tuned according to the finer resolution simulation. This will help realize the goal of a computational cellular simulation that is able to capture the dynamics of membrane-associated processes...

Wavefront cellular learning automata.

Science.gov (United States)

Moradabadi, Behnaz; Meybodi, Mohammad Reza

2018-02-01

This paper proposes a new cellular learning automaton, called a wavefront cellular learning automaton (WCLA). The proposed WCLA has a set of learning automata mapped to a connected structure and uses this structure to propagate the state changes of the learning automata over the structure using waves. In the WCLA, after one learning automaton chooses its action, if this chosen action is different from the previous action, it can send a wave to its neighbors and activate them. Each neighbor receiving the wave is activated and must choose a new action. This structure for the WCLA is necessary in many dynamic areas such as social networks, computer networks, grid computing, and web mining. In this paper, we introduce the WCLA framework as an optimization tool with diffusion capability, study its behavior over time using ordinary differential equation solutions, and present its accuracy using expediency analysis. To show the superiority of the proposed WCLA, we compare the proposed method with some other types of cellular learning automata using two benchmark problems.

Wavefront cellular learning automata

Science.gov (United States)

Moradabadi, Behnaz; Meybodi, Mohammad Reza

2018-02-01

This paper proposes a new cellular learning automaton, called a wavefront cellular learning automaton (WCLA). The proposed WCLA has a set of learning automata mapped to a connected structure and uses this structure to propagate the state changes of the learning automata over the structure using waves. In the WCLA, after one learning automaton chooses its action, if this chosen action is different from the previous action, it can send a wave to its neighbors and activate them. Each neighbor receiving the wave is activated and must choose a new action. This structure for the WCLA is necessary in many dynamic areas such as social networks, computer networks, grid computing, and web mining. In this paper, we introduce the WCLA framework as an optimization tool with diffusion capability, study its behavior over time using ordinary differential equation solutions, and present its accuracy using expediency analysis. To show the superiority of the proposed WCLA, we compare the proposed method with some other types of cellular learning automata using two benchmark problems.

Optimal cellular mobility for synchronization arising from the gradual recovery of intercellular interactions

International Nuclear Information System (INIS)

Uriu, Koichiro; Ares, Saúl; Oates, Andrew C; Morelli, Luis G

2012-01-01

Cell movement and intercellular signaling occur simultaneously during the development of tissues, but little is known about how movement affects signaling. Previous theoretical studies have shown that faster moving cells favor synchronization across a population of locally coupled genetic oscillators. An important assumption in these studies is that cells can immediately interact with their new neighbors after arriving at a new location. However, intercellular interactions in cellular systems may need some time to become fully established. How movement affects synchronization in this situation has not been examined. Here, we develop a coupled phase oscillator model in which we consider cell movement and the gradual recovery of intercellular coupling experienced by a cell after movement, characterized by a moving rate and a coupling recovery rate, respectively. We find (1) an optimal moving rate for synchronization and (2) a critical moving rate above which achieving synchronization is not possible. These results indicate that the extent to which movement enhances synchrony is limited by a gradual recovery of coupling. These findings suggest that the ratio of time scales of movement and signaling recovery is critical for information transfer between moving cells. (paper)

47 CFR 90.672 - Unacceptable interference to non-cellular 800 MHz licensees from 800 MHz cellular systems or part...

Science.gov (United States)

2010-10-01

... 47 Telecommunication 5 2010-10-01 2010-10-01 false Unacceptable interference to non-cellular 800 MHz licensees from 800 MHz cellular systems or part 22 Cellular Radiotelephone systems, and within the... Procedures and Process-Unacceptable Interference § 90.672 Unacceptable interference to non-cellular 800 MHz...

Optimal control of transitions between nonequilibrium steady states.

Directory of Open Access Journals (Sweden)

Patrick R Zulkowski

Full Text Available Biological systems fundamentally exist out of equilibrium in order to preserve organized structures and processes. Many changing cellular conditions can be represented as transitions between nonequilibrium steady states, and organisms have an interest in optimizing such transitions. Using the Hatano-Sasa Y-value, we extend a recently developed geometrical framework for determining optimal protocols so that it can be applied to systems driven from nonequilibrium steady states. We calculate and numerically verify optimal protocols for a colloidal particle dragged through solution by a translating optical trap with two controllable parameters. We offer experimental predictions, specifically that optimal protocols are significantly less costly than naive ones. Optimal protocols similar to these may ultimately point to design principles for biological energy transduction systems and guide the design of artificial molecular machines.

Hierarchical optimal control of large-scale nonlinear chemical processes.

Science.gov (United States)

Ramezani, Mohammad Hossein; Sadati, Nasser

2009-01-01

In this paper, a new approach is presented for optimal control of large-scale chemical processes. In this approach, the chemical process is decomposed into smaller sub-systems at the first level, and a coordinator at the second level, for which a two-level hierarchical control strategy is designed. For this purpose, each sub-system in the first level can be solved separately, by using any conventional optimization algorithm. In the second level, the solutions obtained from the first level are coordinated using a new gradient-type strategy, which is updated by the error of the coordination vector. The proposed algorithm is used to solve the optimal control problem of a complex nonlinear chemical stirred tank reactor (CSTR), where its solution is also compared with the ones obtained using the centralized approach. The simulation results show the efficiency and the capability of the proposed hierarchical approach, in finding the optimal solution, over the centralized method.

Optimal integration of organic Rankine cycles with industrial processes

International Nuclear Information System (INIS)

Hipólito-Valencia, Brígido J.; Rubio-Castro, Eusiel; Ponce-Ortega, José M.; Serna-González, Medardo; Nápoles-Rivera, Fabricio; El-Halwagi, Mahmoud M.

2013-01-01

Highlights: • An optimization approach for heat integration is proposed. • A new general superstructure for heat integration is proposed. • Heat process streams are simultaneously integrated with an organic Rankine cycle. • Better results can be obtained respect to other previously reported methodologies. - Abstract: This paper presents a procedure for simultaneously handling the problem of optimal integration of regenerative organic Rankine cycles (ORCs) with overall processes. ORCs may allow the recovery of an important fraction of the low-temperature process excess heat (i.e., waste heat from industrial processes) in the form of mechanical energy. An integrated stagewise superstructure is proposed for representing the interconnections and interactions between the HEN and ORC for fixed data of process streams. Based on the integrated superstructure, the optimization problem is formulated as a mixed integer nonlinear programming problem to simultaneously account for the capital and operating costs including the revenue from the sale of the shaft power produced by the integrated system. The application of this method is illustrated with three example problems. Results show that the proposed procedure provides significantly better results than an earlier developed method for discovering optimal integrated systems using a sequential approach, due to the fact that it accounts simultaneously for the tradeoffs between the capital and operating costs as well as the sale of the produced energy. Also, the proposed method is an improvement over the previously reported methods for solving the synthesis problem of heat exchanger networks without the option of integration with an ORC (i.e., stand-alone heat exchanger networks)

PROCESS TIME OPTIMIZATION IN DEPOSITOR AND FILLER

Directory of Open Access Journals (Sweden)

Jesús Iván Ruíz-Ibarra

2017-07-01

Full Text Available As in any industry, in soft drink manufacturing demand, customer service and production is of great importance that forces this production to have their equipment and production machines in optimal conditions for the product to be in the hands of the consumer without delays, therefore it is important to have the established times of each process, since the syrup is elaborated, packaged, distributed, until it is purchased by the consumer. After a chronometer analysis, the most common faults were detected in each analyzed process. In the filler machine the most frequent faults are: accumulation of bottles in the subsequent and previous processes to filling process, which in general the cause of the collection of bottles is due to failures in the other equipment of the production line. In the process of unloading the most common faults are: boxes jammed in bump and pusher (pushing boxes; boxes fallen in rollers and platforms transporter. According to observations in each machine, the actions to be followed are presented to solve the problems that arise. Also described the methodology to obtain results, to data analyze and decisions. Firstly an analysis of operations is done to know each machine, supported by the manuals of the machines and the operators themselves a study of times is done by chronometer to determine the standard time of the process where also they present the most common faults, then observations are made on the machines according to the determined sample size, thus obtaining the information necessary to take measurements and to make the study of optimization of the production processes. An analysis of the predetermined process times is also performed by the MTM methods and the MOST time analysis. The results of operators with MTM: Fault Filler = 0.846 minutes, Faultless Filler = 0.61 minutes, Fault Breaker = 0.74 minutes and Fault Flasher = 0.45 minutes. The results of MOST operators are: Fault Filler = 2.58 minutes, Filler Fails

Benchmarking of radiological departments. Starting point for successful process optimization

International Nuclear Information System (INIS)

Busch, Hans-Peter

2010-01-01

Continuous optimization of the process of organization and medical treatment is part of the successful management of radiological departments. The focus of this optimization can be cost units such as CT and MRI or the radiological parts of total patient treatment. Key performance indicators for process optimization are cost- effectiveness, service quality and quality of medical treatment. The potential for improvements can be seen by comparison (benchmark) with other hospitals and radiological departments. Clear definitions of key data and criteria are absolutely necessary for comparability. There is currently little information in the literature regarding the methodology and application of benchmarks especially from the perspective of radiological departments and case-based lump sums, even though benchmarking has frequently been applied to radiological departments by hospital management. The aim of this article is to describe and discuss systematic benchmarking as an effective starting point for successful process optimization. This includes the description of the methodology, recommendation of key parameters and discussion of the potential for cost-effectiveness analysis. The main focus of this article is cost-effectiveness (efficiency and effectiveness) with respect to cost units and treatment processes. (orig.)

Interplay between cellular activity and three-dimensional scaffold-cell constructs with different foam structure processed by electron beam melting.

Science.gov (United States)

Nune, Krishna C; Misra, R Devesh K; Gaytan, Sara M; Murr, Lawrence E

2015-05-01

The cellular activity, biological response, and consequent integration of scaffold-cell construct in the physiological system are governed by the ability of cells to adhere, proliferate, and biomineralize. In this regard, we combine cellular biology and materials science and engineering to fundamentally elucidate the interplay between cellular activity and interconnected three-dimensional foamed architecture obtained by a novel process of electron beam melting and computational tools. Furthermore, the organization of key proteins, notably, actin, vinclulin, and fibronectin, involved in cellular activity and biological functions and relationship with the structure was explored. The interconnected foamed structure with ligaments was favorable to cellular activity that includes cell attachment, proliferation, and differentiation. The primary rationale for favorable modulation of cellular functions is that the foamed structure provided a channel for migration and communication between cells leading to highly mineralized extracellular matrix (ECM) by the differentiating osteoblasts. The filopodial interaction amongst cells on the ligaments was a governing factor in the secretion of ECM, with consequent influence on maturation and mineralization. © 2014 Wiley Periodicals, Inc.

Preparation of Well-Dispersed Chitosan/Alginate Hollow Multilayered Microcapsules for Enhanced Cellular Internalization

Directory of Open Access Journals (Sweden)

Carla Ribeiro

2018-03-01

Full Text Available Hollow multilayered capsules have shown massive potential for being used in the biomedical and biotechnology fields, in applications such as cellular internalization, intracellular trafficking, drug delivery, or tissue engineering. In particular, hollow microcapsules, developed by resorting to porous calcium carbonate sacrificial templates, natural-origin building blocks and the prominent Layer-by-Layer (LbL technology, have attracted increasing attention owing to their key features. However, these microcapsules revealed a great tendency to aggregate, which represents a major hurdle when aiming for cellular internalization and intracellular therapeutics delivery. Herein, we report the preparation of well-dispersed polysaccharide-based hollow multilayered microcapsules by combining the LbL technique with an optimized purification process. Cationic chitosan (CHT and anionic alginate (ALG were chosen as the marine origin polysaccharides due to their biocompatibility and structural similarity to the extracellular matrices of living tissues. Moreover, the inexpensive and highly versatile LbL technology was used to fabricate core-shell microparticles and hollow multilayered microcapsules, with precise control over their composition and physicochemical properties, by repeating the alternate deposition of both materials. The microcapsules’ synthesis procedure was optimized to extensively reduce their natural aggregation tendency, as shown by the morphological analysis monitored by advanced microscopy techniques. The well-dispersed microcapsules showed an enhanced uptake by fibroblasts, opening new perspectives for cellular internalization.

OPTIMIZATION OF FLOCCULATION PROCESS BY MICROBIAL COAGULANT IN RIVER WATER

Directory of Open Access Journals (Sweden)

Fatin Nabilah Murad

2017-12-01

Full Text Available The existing process of coagulation and flocculation are using chemicals that known as cationic coagulant such as alum, ferric sulfate, calcium oxide, and organic polymers.  Thus, this study concentrates on optimizing of flocculation process by microbial coagulant in river water. Turbidity and suspended solids are the main constraints of river water quality in Malaysia. Hence, a study is proposed to produce microbial coagulants isolated locally for river water treatment. The chosen microbe used as the bioflocculant producer is Aspergillus niger. The parameters to optimization in the flocculation process were pH, bioflocculant dosage and effluent concentration. The research was done in the jar test process and the process parameters for maximum turbidity removal was validated. The highest flocculating activity was obtained on day seven of cultivation in the supernatant. The optimum pH and bioflocculant dosage for an optimize sedimentation process were between 4-5 and 2-3 mL for 0.3 g/L of effluent concentration respectively. The model was validated by using a river water sample from Sg. Pusu and the result showed that the model was acceptable to evaluate the bioflocculation process.

Production of Low Cost Carbon-Fiber through Energy Optimization of Stabilization Process

Directory of Open Access Journals (Sweden)

Gelayol Golkarnarenji

2018-03-01

Full Text Available To produce high quality and low cost carbon fiber-based composites, the optimization of the production process of carbon fiber and its properties is one of the main keys. The stabilization process is the most important step in carbon fiber production that consumes a large amount of energy and its optimization can reduce the cost to a large extent. In this study, two intelligent optimization techniques, namely Support Vector Regression (SVR and Artificial Neural Network (ANN, were studied and compared, with a limited dataset obtained to predict physical property (density of oxidative stabilized PAN fiber (OPF in the second zone of a stabilization oven within a carbon fiber production line. The results were then used to optimize the energy consumption in the process. The case study can be beneficial to chemical industries involving carbon fiber manufacturing, for assessing and optimizing different stabilization process conditions at large.

When teams shift among processes: insights from simulation and optimization.

Science.gov (United States)

Kennedy, Deanna M; McComb, Sara A

2014-09-01

This article introduces process shifts to study the temporal interplay among transition and action processes espoused in the recurring phase model proposed by Marks, Mathieu, and Zacarro (2001). Process shifts are those points in time when teams complete a focal process and change to another process. By using team communication patterns to measure process shifts, this research explores (a) when teams shift among different transition processes and initiate action processes and (b) the potential of different interventions, such as communication directives, to manipulate process shift timing and order and, ultimately, team performance. Virtual experiments are employed to compare data from observed laboratory teams not receiving interventions, simulated teams receiving interventions, and optimal simulated teams generated using genetic algorithm procedures. Our results offer insights about the potential for different interventions to affect team performance. Moreover, certain interventions may promote discussions about key issues (e.g., tactical strategies) and facilitate shifting among transition processes in a manner that emulates optimal simulated teams' communication patterns. Thus, we contribute to theory regarding team processes in 2 important ways. First, we present process shifts as a way to explore the timing of when teams shift from transition to action processes. Second, we use virtual experimentation to identify those interventions with the greatest potential to affect performance by changing when teams shift among processes. Additionally, we employ computational methods including neural networks, simulation, and optimization, thereby demonstrating their applicability in conducting team research. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Optimal control of stretching process of flexible solar arrays on spacecraft based on a hybrid optimization strategy

Directory of Open Access Journals (Sweden)

Qijia Yao

2017-07-01

Full Text Available The optimal control of multibody spacecraft during the stretching process of solar arrays is investigated, and a hybrid optimization strategy based on Gauss pseudospectral method (GPM and direct shooting method (DSM is presented. First, the elastic deformation of flexible solar arrays was described approximately by the assumed mode method, and a dynamic model was established by the second Lagrangian equation. Then, the nonholonomic motion planning problem is transformed into a nonlinear programming problem by using GPM. By giving fewer LG points, initial values of the state variables and control variables were obtained. A serial optimization framework was adopted to obtain the approximate optimal solution from a feasible solution. Finally, the control variables were discretized at LG points, and the precise optimal control inputs were obtained by DSM. The optimal trajectory of the system can be obtained through numerical integration. Through numerical simulation, the stretching process of solar arrays is stable with no detours, and the control inputs match the various constraints of actual conditions. The results indicate that the method is effective with good robustness. Keywords: Motion planning, Multibody spacecraft, Optimal control, Gauss pseudospectral method, Direct shooting method

RNA-SeQC: RNA-seq metrics for quality control and process optimization.

Science.gov (United States)

DeLuca, David S; Levin, Joshua Z; Sivachenko, Andrey; Fennell, Timothy; Nazaire, Marc-Danie; Williams, Chris; Reich, Michael; Winckler, Wendy; Getz, Gad

2012-06-01

RNA-seq, the application of next-generation sequencing to RNA, provides transcriptome-wide characterization of cellular activity. Assessment of sequencing performance and library quality is critical to the interpretation of RNA-seq data, yet few tools exist to address this issue. We introduce RNA-SeQC, a program which provides key measures of data quality. These metrics include yield, alignment and duplication rates; GC bias, rRNA content, regions of alignment (exon, intron and intragenic), continuity of coverage, 3'/5' bias and count of detectable transcripts, among others. The software provides multi-sample evaluation of library construction protocols, input materials and other experimental parameters. The modularity of the software enables pipeline integration and the routine monitoring of key measures of data quality such as the number of alignable reads, duplication rates and rRNA contamination. RNA-SeQC allows investigators to make informed decisions about sample inclusion in downstream analysis. In summary, RNA-SeQC provides quality control measures critical to experiment design, process optimization and downstream computational analysis. See www.genepattern.org to run online, or www.broadinstitute.org/rna-seqc/ for a command line tool.

An Overview and Analysis of Mobile Internet Protocols in Cellular Environments.

Science.gov (United States)

Chao, Han-Chieh

2001-01-01

Notes that cellular is the inevitable future architecture for the personal communication service system. Discusses the current cellular support based on Mobile Internet Protocol version 6 (Ipv6) and points out the shortfalls of using Mobile IP. Highlights protocols especially for mobile management schemes which can optimize a high-speed mobile…

A Technical Survey on Optimization of Processing Geo Distributed Data

Science.gov (United States)

Naga Malleswari, T. Y. J.; Ushasukhanya, S.; Nithyakalyani, A.; Girija, S.

2018-04-01

With growing cloud services and technology, there is growth in some geographically distributed data centers to store large amounts of data. Analysis of geo-distributed data is required in various services for data processing, storage of essential information, etc., processing this geo-distributed data and performing analytics on this data is a challenging task. The distributed data processing is accompanied by issues in storage, computation and communication. The key issues to be dealt with are time efficiency, cost minimization, utility maximization. This paper describes various optimization methods like end-to-end multiphase, G-MR, etc., using the techniques like Map-Reduce, CDS (Community Detection based Scheduling), ROUT, Workload-Aware Scheduling, SAGE, AMP (Ant Colony Optimization) to handle these issues. In this paper various optimization methods and techniques used are analyzed. It has been observed that end-to end multiphase achieves time efficiency; Cost minimization concentrates to achieve Quality of Service, Computation and reduction of Communication cost. SAGE achieves performance improvisation in processing geo-distributed data sets.

Modeling cellular systems

CERN Document Server

Matthäus, Franziska; Pahle, Jürgen

2017-01-01

This contributed volume comprises research articles and reviews on topics connected to the mathematical modeling of cellular systems. These contributions cover signaling pathways, stochastic effects, cell motility and mechanics, pattern formation processes, as well as multi-scale approaches. All authors attended the workshop on "Modeling Cellular Systems" which took place in Heidelberg in October 2014. The target audience primarily comprises researchers and experts in the field, but the book may also be beneficial for graduate students.

Optimization and Improvement of Test Processes on a Production Line

Science.gov (United States)

Sujová, Erika; Čierna, Helena

2018-06-01

The paper deals with increasing processes efficiency at a production line of cylinder heads of engines in a production company operating in the automotive industry. The goal is to achieve improvement and optimization of test processes on a production line. It analyzes options for improving capacity, availability and productivity of processes of an output test by using modern technology available on the market. We have focused on analysis of operation times before and after optimization of test processes at specific production sections. By analyzing measured results we have determined differences in time before and after improvement of the process. We have determined a coefficient of efficiency OEE and by comparing outputs we have confirmed real improvement of the process of the output test of cylinder heads.

A Multivariate Quality Loss Function Approach for Optimization of Spinning Processes

Science.gov (United States)

Chakraborty, Shankar; Mitra, Ankan

2018-05-01

Recent advancements in textile industry have given rise to several spinning techniques, such as ring spinning, rotor spinning etc., which can be used to produce a wide variety of textile apparels so as to fulfil the end requirements of the customers. To achieve the best out of these processes, they should be utilized at their optimal parametric settings. However, in presence of multiple yarn characteristics which are often conflicting in nature, it becomes a challenging task for the spinning industry personnel to identify the best parametric mix which would simultaneously optimize all the responses. Hence, in this paper, the applicability of a new systematic approach in the form of multivariate quality loss function technique is explored for optimizing multiple quality characteristics of yarns while identifying the ideal settings of two spinning processes. It is observed that this approach performs well against the other multi-objective optimization techniques, such as desirability function, distance function and mean squared error methods. With slight modifications in the upper and lower specification limits of the considered quality characteristics, and constraints of the non-linear optimization problem, it can be successfully applied to other processes in textile industry to determine their optimal parametric settings.

Forecasting optimal duration of a beer main fermentation process using the Kalman filter

OpenAIRE

Niyonsaba T.; Pavlov V.A.

2016-01-01

One of the most important processes of beer production is the main process of fermentation. In this process, the wort transforms into beer. The quality of beer depends on the dynamics of wort parameters. The main fermentation process continues for 10 days and requires high costs. Therefore, the main purpose of this article is to forecast the optimal duration of the beer main fermentation process and provide its optimal control. The Kalman filter can provide optimal control of the main ferment...

Simulation and optimization of fractional crystallization processes

DEFF Research Database (Denmark)

Thomsen, Kaj; Rasmussen, Peter; Gani, Rafiqul

1998-01-01

A general method for the calculation of various types of phase diagrams for aqueous electrolyte mixtures is outlined. It is shown how the thermodynamic equilibrium precipitation process can be used to satisfy the operational needs of industrial crystallizer/centrifuge units. Examples of simulation...... and optimization of fractional crystallization processes are shown. In one of these examples, a process with multiple steady states is analyzed. The thermodynamic model applied for describing the highly non-ideal aqueous electrolyte systems is the Extended UNIQUAC model. (C) 1998 Published by Elsevier Science Ltd...

Coordination of plant mitochondrial biogenesis: keeping pace with cellular requirements

Science.gov (United States)

Welchen, Elina; García, Lucila; Mansilla, Natanael; Gonzalez, Daniel H.

2014-01-01

Plant mitochondria are complex organelles that carry out numerous metabolic processes related with the generation of energy for cellular functions and the synthesis and degradation of several compounds. Mitochondria are semiautonomous and dynamic organelles changing in shape, number, and composition depending on tissue or developmental stage. The biogenesis of functional mitochondria requires the coordination of genes present both in the nucleus and the organelle. In addition, due to their central role, all processes held inside mitochondria must be finely coordinated with those in other organelles according to cellular demands. Coordination is achieved by transcriptional control of nuclear genes encoding mitochondrial proteins by specific transcription factors that recognize conserved elements in their promoter regions. In turn, the expression of most of these transcription factors is linked to developmental and environmental cues, according to the availability of nutrients, light–dark cycles, and warning signals generated in response to stress conditions. Among the signals impacting in the expression of nuclear genes, retrograde signals that originate inside mitochondria help to adjust mitochondrial biogenesis to organelle demands. Adding more complexity, several nuclear encoded proteins are dual localized to mitochondria and either chloroplasts or the nucleus. Dual targeting might establish a crosstalk between the nucleus and cell organelles to ensure a fine coordination of cellular activities. In this article, we discuss how the different levels of coordination of mitochondrial biogenesis interconnect to optimize the function of the organelle according to both internal and external demands. PMID:24409193

Coordination of plant mitochondrial biogenesis: keeping pace with cellular requirements.

Directory of Open Access Journals (Sweden)

Elina eWelchen

2014-01-01

Full Text Available Plant mitochondria are complex organelles that carry out numerous metabolic processes related with the generation of energy for cellular functions and the synthesis and degradation of several compounds. Mitochondria are semiautonomous and dynamic organelles changing in shape, number and composition depending on tissue or developmental stage. The biogenesis of functional mitochondria requires the coordination of genes present both in the nucleus and the organelle. In addition, due to their central role, all processes held inside mitochondria must be finely coordinated with those in other organelles according to cellular demands. Coordination is achieved by transcriptional control of nuclear genes encoding mitochondrial proteins by specific transcription factors that recognize conserved elements in their promoter regions. In turn, the expression of most of these transcription factors is linked to developmental and environmental cues, according to the availability of nutrients, light-dark cycles and warning signals generated in response to stress conditions. Among the signals impacting in the expression of nuclear genes, retrograde signals that originate inside mitochondria help to adjust mitochondrial biogenesis to organelle demands. Adding more complexity, several nuclear encoded proteins are dual localized to mitochondria and either chloroplasts or the nucleus. Dual targeting might establish a crosstalk between the nucleus and cell organelles to ensure a fine coordination of cellular activities. In this article, we discuss how the different levels of coordination of mitochondrial biogenesis interconnect to optimize the function of the organelle according to both internal and external demands.

HIV-1 Replication and the Cellular Eukaryotic Translation Apparatus

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Santiago Guerrero

2015-01-01

Full Text Available Eukaryotic translation is a complex process composed of three main steps: initiation, elongation, and termination. During infections by RNA- and DNA-viruses, the eukaryotic translation machinery is used to assure optimal viral protein synthesis. Human immunodeficiency virus type I (HIV-1 uses several non-canonical pathways to translate its own proteins, such as leaky scanning, frameshifting, shunt, and cap-independent mechanisms. Moreover, HIV-1 modulates the host translation machinery by targeting key translation factors and overcomes different cellular obstacles that affect protein translation. In this review, we describe how HIV-1 proteins target several components of the eukaryotic translation machinery, which consequently improves viral translation and replication.

Simulation and Optimization of Foam EOR Processes

NARCIS (Netherlands)

Namdar Zanganeh, M.

2011-01-01

Chemical enhanced oil recovery (EOR) is relatively expensive due to the high cost of the injected chemicals such as surfactants. Excessive use of these chemicals leads to processes that are not economically feasible. Therefore, optimizing the volume of these injected chemicals is of extreme

Electromagnetic cellular interactions.

Science.gov (United States)

Cifra, Michal; Fields, Jeremy Z; Farhadi, Ashkan

2011-05-01

Chemical and electrical interaction within and between cells is well established. Just the opposite is true about cellular interactions via other physical fields. The most probable candidate for an other form of cellular interaction is the electromagnetic field. We review theories and experiments on how cells can generate and detect electromagnetic fields generally, and if the cell-generated electromagnetic field can mediate cellular interactions. We do not limit here ourselves to specialized electro-excitable cells. Rather we describe physical processes that are of a more general nature and probably present in almost every type of living cell. The spectral range included is broad; from kHz to the visible part of the electromagnetic spectrum. We show that there is a rather large number of theories on how cells can generate and detect electromagnetic fields and discuss experimental evidence on electromagnetic cellular interactions in the modern scientific literature. Although small, it is continuously accumulating. Copyright © 2010 Elsevier Ltd. All rights reserved.

Construction and cellular uptake behavior of redox-sensitive docetaxel prodrug-loaded liposomes.

Science.gov (United States)

Ren, Guolian; Jiang, Mengjuan; Guo, Weiling; Sun, Bingjun; Lian, He; Wang, Yongjun; He, Zhonggui

2018-01-01

A redox-responsive docetaxel (DTX) prodrug consisting of a disulfide linkage between DTX and vitamin E (DTX-SS-VE) was synthesized in our laboratory and was successfully formulated into liposomes. The aim of this study was to optimize the formulation and investigate the cellular uptake of DTX prodrug-loaded liposomes (DPLs). The content of DTX-SS-VE was determined by ultrahigh-performance liquid chromatography (UPLC). The formulation and process were optimized using entrapment efficiency (EE), drug-loading (DL), particle size and polydispersity index (PDI) as the evaluation indices. The optimal formulation was as follows: drug/lipid ratio of 1:12, cholesterol/lipid ratio of 1:10, hydration temperature of 40 °C, sonication power and time of 400 W and 5 min. The EE, DL and particle size of the optimized DPLs were 97.60 ± 0.03%, 7.09 ± 0.22% and 93.06 ± 0.72 nm, respectively. DPLs had good dilution stability under the physiological conditions over 24 h. In addition, DPLs were found to enter tumor cells via different pathways and released DTX from the prodrug to induce apoptosis. Taken together, the optimized formulation and process were found to be a simple, stable and applicable method for the preparation of DPLs that could successfully escape from lysosomes.

Movies of cellular and sub-cellular motion by digital holographic microscopy

Directory of Open Access Journals (Sweden)

Yu Lingfeng

2006-03-01

Full Text Available Abstract Background Many biological specimens, such as living cells and their intracellular components, often exhibit very little amplitude contrast, making it difficult for conventional bright field microscopes to distinguish them from their surroundings. To overcome this problem phase contrast techniques such as Zernike, Normarsky and dark-field microscopies have been developed to improve specimen visibility without chemically or physically altering them by the process of staining. These techniques have proven to be invaluable tools for studying living cells and furthering scientific understanding of fundamental cellular processes such as mitosis. However a drawback of these techniques is that direct quantitative phase imaging is not possible. Quantitative phase imaging is important because it enables determination of either the refractive index or optical thickness variations from the measured optical path length with sub-wavelength accuracy. Digital holography is an emergent phase contrast technique that offers an excellent approach in obtaining both qualitative and quantitative phase information from the hologram. A CCD camera is used to record a hologram onto a computer and numerical methods are subsequently applied to reconstruct the hologram to enable direct access to both phase and amplitude information. Another attractive feature of digital holography is the ability to focus on multiple focal planes from a single hologram, emulating the focusing control of a conventional microscope. Methods A modified Mach-Zender off-axis setup in transmission is used to record and reconstruct a number of holographic amplitude and phase images of cellular and sub-cellular features. Results Both cellular and sub-cellular features are imaged with sub-micron, diffraction-limited resolution. Movies of holographic amplitude and phase images of living microbes and cells are created from a series of holograms and reconstructed with numerically adjustable

Magnetic Resonance Microscopy of Human and Porcine Neurons and Cellular Processes

Science.gov (United States)

Flint, Jeremy J.; Hansen, Brian; Portnoy, Sharon; Lee, Choong-Heon; King, Michael A.; Fey, Michael; Vincent, Franck; Stanisz, Greg J; Vestergaard-Poulsen, Peter; Blackband, Stephen J

2012-01-01

With its unparalleled ability to safely generate high-contrast images of soft tissues, magnetic resonance imaging (MRI) has remained at the forefront of diagnostic clinical medicine. Unfortunately due to resolution limitations, clinical scans are most useful for detecting macroscopic structural changes associated with a small number of pathologies. Moreover, due to a longstanding inability to directly observe magnetic resonance (MR) signal behavior at the cellular level, such information is poorly characterized and generally must be inferred. With the advent of the MR microscope in 1986 came the ability to measure MR signal properties of theretofore unobservable tissue structures. Recently, further improvements in hardware technology have made possible the ability to visualize mammalian cellular structure. In the current study, we expand upon previous work by imaging the neuronal cell bodies and processes of human and porcine α-motor neurons. Complimentary imaging studies are conducted in pig tissue in order to demonstrate qualitative similarities to human samples. Also, apparent diffusion coefficient (ADC) maps were generated inside porcine α-motor neuron cell bodies and portions of their largest processes (mean = 1.7±0.5 μm2/ms based on 53 pixels) as well as in areas containing a mixture of extracellular space, microvasculature, and neuropil (0.59±0.37 μm2/ms based on 33 pixels). Three-dimensional reconstruction of MR images containing α-motor neurons shows the spatial arrangement of neuronal projections between adjacent cells. Such advancements in imaging portend the ability to construct accurate models of MR signal behavior based on direct observation and measurement of the components which comprise functional tissues. These tools would not only be useful for improving our interpretation of macroscopic MRI performed in the clinic, but they could potentially be used to develop new methods of differential diagnosis to aid in the early detection of a

Taming the sphinx: Mechanisms of cellular sphingolipid homeostasis.

Science.gov (United States)

Olson, D K; Fröhlich, F; Farese, R V; Walther, T C

2016-08-01

Sphingolipids are important structural membrane components of eukaryotic cells, and potent signaling molecules. As such, their levels must be maintained to optimize cellular functions in different cellular membranes. Here, we review the current knowledge of homeostatic sphingolipid regulation. We describe recent studies in Saccharomyces cerevisiae that have provided insights into how cells sense changes in sphingolipid levels in the plasma membrane and acutely regulate sphingolipid biosynthesis by altering signaling pathways. We also discuss how cellular trafficking has emerged as an important determinant of sphingolipid homeostasis. Finally, we highlight areas where work is still needed to elucidate the mechanisms of sphingolipid regulation and the physiological functions of such regulatory networks, especially in mammalian cells. This article is part of a Special Issue entitled: The cellular lipid landscape edited by Tim P. Levine and Anant K. Menon. Copyright © 2015. Published by Elsevier B.V.

In vitro cellular uptake of evodiamine and rutaecarpine using a microemulsion.

Science.gov (United States)

Zhang, Yong-Tai; Huang, Zhe-Bin; Zhang, Su-Juan; Zhao, Ji-Hui; Wang, Zhi; Liu, Ying; Feng, Nian-Ping

2012-01-01

To investigate the cellular uptake of evodiamine and rutaecarpine in a microemulsion in comparison with aqueous suspensions and tinctures. A microemulsion was prepared using the dropwise addition method. Mouse skin fibroblasts were cultured in vitro to investigate the optimal conditions for evodiamine and rutaecarpine uptake with different drug concentrations and administration times. Under optimal conditions, the cellular uptake of microemulsified drugs was assayed and compared to tinctures and aqueous suspensions. Rhodamine B labeling and laser scanning confocal microscopy (LSCM) were used to explore the distribution of fluorochrome transferred with the microemulsion in fibroblasts. Cellular morphology was also investigated, using optical microscopy to evaluate microemulsion-induced cellular toxicity. The maximum cellular drug uptake amounts were obtained with a 20% concentration (v/v) of microemulsion and an 8 hour administration time. Drug uptake by mouse skin fibroblasts was lowest when the drugs were loaded in microemulsion. After incubation with rhodamine B-labeled microemulsion for 8 hours, the highest fluorescence intensity was achieved, and the fluorochrome was primarily distributed in the cytochylema. No obvious cellular morphologic changes were observed with the administration of either the microemulsion or the aqueous suspension; for the tincture group, however, massive cellular necrocytosis was observed. The lower cellular uptake with microemulsion may be due to the fact that most of the drug loaded in the microemulsion vehicle was transported via the intercellular space, while a small quantity of free drug (released from the vehicle) was ingested through transmembrane transport. Mouse skin fibroblasts rarely endocytosed evodiamine and rutaecarpine with a microemulsion as the vehicle. The microemulsion had no obvious effect on cellular morphology, suggesting there is little or no cellular toxicity associated with the administration of microemulsion on

Research in Mobile Database Query Optimization and Processing

Directory of Open Access Journals (Sweden)

Agustinus Borgy Waluyo

2005-01-01

Full Text Available The emergence of mobile computing provides the ability to access information at any time and place. However, as mobile computing environments have inherent factors like power, storage, asymmetric communication cost, and bandwidth limitations, efficient query processing and minimum query response time are definitely of great interest. This survey groups a variety of query optimization and processing mechanisms in mobile databases into two main categories, namely: (i query processing strategy, and (ii caching management strategy. Query processing includes both pull and push operations (broadcast mechanisms. We further classify push operation into on-demand broadcast and periodic broadcast. Push operation (on-demand broadcast relates to designing techniques that enable the server to accommodate multiple requests so that the request can be processed efficiently. Push operation (periodic broadcast corresponds to data dissemination strategies. In this scheme, several techniques to improve the query performance by broadcasting data to a population of mobile users are described. A caching management strategy defines a number of methods for maintaining cached data items in clients' local storage. This strategy considers critical caching issues such as caching granularity, caching coherence strategy and caching replacement policy. Finally, this survey concludes with several open issues relating to mobile query optimization and processing strategy.

Real-time economic optimization for a fermentation process using Model Predictive Control

DEFF Research Database (Denmark)

Petersen, Lars Norbert; Jørgensen, John Bagterp

2014-01-01

Fermentation is a widely used process in production of many foods, beverages, and pharmaceuticals. The main goal of the control system is to maximize profit of the fermentation process, and thus this is also the main goal of this paper. We present a simple dynamic model for a fermentation process...... and demonstrate its usefulness in economic optimization. The model is formulated as an index-1 differential algebraic equation (DAE), which guarantees conservation of mass and energy in discrete form. The optimization is based on recent advances within Economic Nonlinear Model Predictive Control (E......-NMPC), and also utilizes the index-1 DAE model. The E-NMPC uses the single-shooting method and the adjoint method for computation of the optimization gradients. The process constraints are relaxed to soft-constraints on the outputs. Finally we derive the analytical solution to the economic optimization problem...

Alternative oxidase pathway optimizes photosynthesis during osmotic and temperature stress by regulating cellular ROS, malate valve and antioxidative systems

Directory of Open Access Journals (Sweden)

DINAKAR eCHALLABATHULA

2016-02-01

Full Text Available The present study reveals the importance of alternative oxidase (AOX pathway in optimizing photosynthesis under osmotic and temperature stress conditions in the mesophyll protoplasts of Pisum sativum. The responses of photosynthesis and respiration were monitored at saturating light intensity of 1000 µmoles m-2 s-1 at 25 oC under a range of sorbitol concentrations from 0.4 M to 1.0M to induce hyper-osmotic stress and by varying the temperature of the thermo-jacketed pre-incubation chamber from 25 oC to 10 oC to impose sub-optimal temperature stress. Compared to controls (0.4 M sorbitol and 25 OC, the mesophyll protoplasts showed remarkable decrease in NaHCO3-dependent O2 evolution (indicator of photosynthetic carbon assimilation, under both hyper-osmotic (1.0 M sorbitol and sub-optimal temperature stress conditions (10 OC, while the decrease in rates of respiratory O2 uptake were marginal. The capacity of AOX pathway increased significantly in parallel to increase in intracellular pyruvate and reactive oxygen species (ROS levels under both hyper-osmotic stress and sub-optimal temperature stress under the background of saturating light. The ratio of redox couple (Malate/OAA related to malate valve increased in contrast to the ratio of redox couple (GSH/GSSG related to antioxidative system during hyper-osmotic stress. Nevertheless, the ratio of GSH/GSSG decreased in the presence of sub-optimal temperature, while the ratio of Malate/OAA showed no visible changes. Also, the redox ratios of pyridine nucleotides increased under hyper-osmotic (NADH/NAD and sub-optimal temperature (NADPH/NADP stresses, respectively. However, upon restriction of AOX pathway by using salicylhydroxamic acid (SHAM, the observed changes in NaHCO3 dependent O2 evolution, cellular ROS, redox ratios of Malate/OAA, NAD(PH/NAD(P and GSH/GSSG were further aggravated under stress conditions with concomitant modulations in NADP-MDH and antioxidant enzymes. Taken together, the

Equipment reliability process improvement and preventive maintenance optimization

International Nuclear Information System (INIS)

Darragi, M.; Georges, A.; Vaillancourt, R.; Komljenovic, D.; Croteau, M.

2004-01-01

The Gentilly-2 Nuclear Power Plant wants to optimize its preventive maintenance program through an Integrated Equipment Reliability Process. All equipment reliability related activities should be reviewed and optimized in a systematic approach especially for aging plants such as G2. This new approach has to be founded on best practices methods with the purpose of the rationalization of the preventive maintenance program and the performance monitoring of on-site systems, structures and components (SSC). A rational preventive maintenance strategy is based on optimized task scopes and frequencies depending on their applicability, critical effects on system safety and plant availability as well as cost-effectiveness. Preventive maintenance strategy efficiency is systematically monitored through degradation indicators. (author)

Improving processes through evolutionary optimization.

Science.gov (United States)

Clancy, Thomas R

2011-09-01

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies on complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 18th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, I discuss methods to optimize complex healthcare processes through learning, adaptation, and evolutionary planning.

Cellular automata machines as physics emulators

International Nuclear Information System (INIS)

Toffoli, T.

1988-01-01

Can one design a computer optimized to be a physics emulator rather than a software interpreter? Cellular automata are discrete dynamical systems whose behavior is completely specified in terms of a local relation, much as is the case for a large class of continuous dynamical systems defined by partial differential equations. 31 refs, 3 figs

Urban Growth Modeling Using Cellular Automata with Multi-Temporal Remote Sensing Images Calibrated by the Artificial Bee Colony Optimization Algorithm.

Science.gov (United States)

Naghibi, Fereydoun; Delavar, Mahmoud Reza; Pijanowski, Bryan

2016-12-14

Cellular Automata (CA) is one of the most common techniques used to simulate the urbanization process. CA-based urban models use transition rules to deliver spatial patterns of urban growth and urban dynamics over time. Determining the optimum transition rules of the CA is a critical step because of the heterogeneity and nonlinearities existing among urban growth driving forces. Recently, new CA models integrated with optimization methods based on swarm intelligence algorithms were proposed to overcome this drawback. The Artificial Bee Colony (ABC) algorithm is an advanced meta-heuristic swarm intelligence-based algorithm. Here, we propose a novel CA-based urban change model that uses the ABC algorithm to extract optimum transition rules. We applied the proposed ABC-CA model to simulate future urban growth in Urmia (Iran) with multi-temporal Landsat images from 1997, 2006 and 2015. Validation of the simulation results was made through statistical methods such as overall accuracy, the figure of merit and total operating characteristics (TOC). Additionally, we calibrated the CA model by ant colony optimization (ACO) to assess the performance of our proposed model versus similar swarm intelligence algorithm methods. We showed that the overall accuracy and the figure of merit of the ABC-CA model are 90.1% and 51.7%, which are 2.9% and 8.8% higher than those of the ACO-CA model, respectively. Moreover, the allocation disagreement of the simulation results for the ABC-CA model is 9.9%, which is 2.9% less than that of the ACO-CA model. Finally, the ABC-CA model also outperforms the ACO-CA model with fewer quantity and allocation errors and slightly more hits.

Multi-objective optimization model of CNC machining to minimize processing time and environmental impact

Science.gov (United States)

Hamada, Aulia; Rosyidi, Cucuk Nur; Jauhari, Wakhid Ahmad

2017-11-01

Minimizing processing time in a production system can increase the efficiency of a manufacturing company. Processing time are influenced by application of modern technology and machining parameter. Application of modern technology can be apply by use of CNC machining, one of the machining process can be done with a CNC machining is turning. However, the machining parameters not only affect the processing time but also affect the environmental impact. Hence, optimization model is needed to optimize the machining parameters to minimize the processing time and environmental impact. This research developed a multi-objective optimization to minimize the processing time and environmental impact in CNC turning process which will result in optimal decision variables of cutting speed and feed rate. Environmental impact is converted from environmental burden through the use of eco-indicator 99. The model were solved by using OptQuest optimization software from Oracle Crystal Ball.

Optimization of Multiple Responses of Ultrasonic Machining (USM Process: A Comparative Study

Directory of Open Access Journals (Sweden)

Rina Chakravorty

2013-04-01

Full Text Available Ultrasonic machining (USM process has multiple performance measures, e.g. material removal rate (MRR, tool wear rate (TWR, surface roughness (SR etc., which are affected by several process parameters. The researchers commonly attempted to optimize USM process with respect to individual responses, separately. In the recent past, several systematic procedures for dealing with the multi-response optimization problems have been proposed in the literature. Although most of these methods use complex mathematics or statistics, there are some simple methods, which can be comprehended and implemented by the engineers to optimize the multiple responses of USM processes. However, the relative optimization performance of these approaches is unknown because the effectiveness of different methods has been demonstrated using different sets of process data. In this paper, the computational requirements for four simple methods are presented, and two sets of past experimental data on USM processes are analysed using these methods. The relative performances of these methods are then compared. The results show that weighted signal-to-noise (WSN ratio method and utility theory (UT method usually give better overall optimisation performance for the USM process than the other approaches.

Optimizing The DSSC Fabrication Process Using Lean Six Sigma

Science.gov (United States)

Fauss, Brian

Alternative energy technologies must become more cost effective to achieve grid parity with fossil fuels. Dye sensitized solar cells (DSSCs) are an innovative third generation photovoltaic technology, which is demonstrating tremendous potential to become a revolutionary technology due to recent breakthroughs in cost of fabrication. The study here focused on quality improvement measures undertaken to improve fabrication of DSSCs and enhance process efficiency and effectiveness. Several quality improvement methods were implemented to optimize the seven step individual DSSC fabrication processes. Lean Manufacturing's 5S method successfully increased efficiency in all of the processes. Six Sigma's DMAIC methodology was used to identify and eliminate each of the root causes of defects in the critical titanium dioxide deposition process. These optimizations resulted with the following significant improvements in the production process: 1. fabrication time of the DSSCs was reduced by 54 %; 2. fabrication procedures were improved to the extent that all critical defects in the process were eliminated; 3. the quantity of functioning DSSCs fabricated was increased from 17 % to 90 %.

Optimization Of A Mass Spectrometry Process

International Nuclear Information System (INIS)

Lopes, Jose; Alegria, F. Correa; Redondo, Luis; Barradas, N. P.; Alves, E.; Rocha, Jorge

2011-01-01

In this paper we present and discuss a system developed in order to optimize the mass spectrometry process of an ion implanter. The system uses a PC to control and display the mass spectrum. The operator interacts with the I/O board, that interfaces with the computer and the ion implanter by a LabVIEW code. Experimental results are shown and the capabilities of the system are discussed.

High-Concentrate Diet-Induced Change of Cellular Metabolism Leads to Decreases of Immunity and Imbalance of Cellular Activities in Rumen Epithelium.

Science.gov (United States)

Lu, Zhongyan; Shen, Hong; Shen, Zanming

2018-01-01

In animals, the immune and cellular processes of tissue largely depend on the status of local metabolism. However, in the rumen epithelium, how the cellular metabolism affects epithelial immunity, and cellular processes, when the diet is switched from energy-rich to energy-excess status, with regard to animal production and health, have not as yet been reported. RNA-seq was applied to compare the biological processes altered by an increase of dietary concentration from 10% to 35% with those altered by an increase of dietary concentration from 35% to 65% (dietary concentrate: the non-grass component in diet, including corn, soya bean meal and additive. High concentrate diet composed of 35% grass, 55% corn, 8% soya bean meal and 2% additive). In addition to the functional analysis of enriched genes in terms of metabolism, the immune system, and cellular process, the highly correlated genes to the enriched metabolism genes were identified, and the function and signaling pathways related to the differentially expressed neighbors were compared among the groups. The variation trends of molar proportions of ruminal SCFAs and those of enriched pathways belonging to metabolism, immune system, and cellular process were altered with the change of diets. With regard to metabolism, lipid metabolism and amino acid metabolism were most affected. According to the correlation analysis, both innate and adaptive immune responses were promoted by the metabolism genes enriched under the 65% concentrate diet. However, the majority of immune responses were suppressed under the 35% concentrate diet. Moreover, the exclusive upregulation of cell growth and dysfunction of cellular transport and catabolism were induced by the metabolism genes enriched under the 65% concentrate diet. On the contrary, a balanced regulation of cellular processes was detected under the 35% concentrate diet. These results indicated that the alterations of cellular metabolism promote the alterations in cellular

High-Concentrate Diet-Induced Change of Cellular Metabolism Leads to Decreases of Immunity and Imbalance of Cellular Activities in Rumen Epithelium

Directory of Open Access Journals (Sweden)

Zhongyan Lu

2018-03-01

Full Text Available Background/Aims: In animals, the immune and cellular processes of tissue largely depend on the status of local metabolism. However, in the rumen epithelium, how the cellular metabolism affects epithelial immunity, and cellular processes, when the diet is switched from energy-rich to energy-excess status, with regard to animal production and health, have not as yet been reported. Methods: RNA-seq was applied to compare the biological processes altered by an increase of dietary concentration from 10% to 35% with those altered by an increase of dietary concentration from 35% to 65% (dietary concentrate: the non-grass component in diet, including corn, soya bean meal and additive. High concentrate diet composed of 35% grass, 55% corn, 8% soya bean meal and 2% additive. In addition to the functional analysis of enriched genes in terms of metabolism, the immune system, and cellular process, the highly correlated genes to the enriched metabolism genes were identified, and the function and signaling pathways related to the differentially expressed neighbors were compared among the groups. Results: The variation trends of molar proportions of ruminal SCFAs and those of enriched pathways belonging to metabolism, immune system, and cellular process were altered with the change of diets. With regard to metabolism, lipid metabolism and amino acid metabolism were most affected. According to the correlation analysis, both innate and adaptive immune responses were promoted by the metabolism genes enriched under the 65% concentrate diet. However, the majority of immune responses were suppressed under the 35% concentrate diet. Moreover, the exclusive upregulation of cell growth and dysfunction of cellular transport and catabolism were induced by the metabolism genes enriched under the 65% concentrate diet. On the contrary, a balanced regulation of cellular processes was detected under the 35% concentrate diet. Conclusions: These results indicated that the

Optimization of turning process through the analytic flank wear modelling

Science.gov (United States)

Del Prete, A.; Franchi, R.; De Lorenzis, D.

2018-05-01

In the present work, the approach used for the optimization of the process capabilities for Oil&Gas components machining will be described. These components are machined by turning of stainless steel castings workpieces. For this purpose, a proper Design Of Experiments (DOE) plan has been designed and executed: as output of the experimentation, data about tool wear have been collected. The DOE has been designed starting from the cutting speed and feed values recommended by the tools manufacturer; the depth of cut parameter has been maintained as a constant. Wear data has been obtained by means the observation of the tool flank wear under an optical microscope: the data acquisition has been carried out at regular intervals of working times. Through a statistical data and regression analysis, analytical models of the flank wear and the tool life have been obtained. The optimization approach used is a multi-objective optimization, which minimizes the production time and the number of cutting tools used, under the constraint on a defined flank wear level. The technique used to solve the optimization problem is a Multi Objective Particle Swarm Optimization (MOPS). The optimization results, validated by the execution of a further experimental campaign, highlighted the reliability of the work and confirmed the usability of the optimized process parameters and the potential benefit for the company.

Importance of design optimization of gamma processing plants

International Nuclear Information System (INIS)

George, Jain Reji

2014-01-01

Radiation processing of food commodities using ionizing radiations is well established world wide. In India too, novel designs are coming up for food irradiation as well as for multiproduct irradiation. It has been observed that though the designs of the product movement systems are excelling, the actual purpose for which the designs are made are failing in some. In such situations it is difficult to achieve an effective dose delivery by controlling the process parameters or even by modifying the source activity distribution without compromising some other aspects like throughput. It is very essential to arrive at an optimization in all components such as radiation source geometry, source product geometry and protective barriers of an irradiator system. Optimization of the various parameters can be done by modeling and analysis of the design

Intelligent Optimization of a Mixed Culture Cultivation Process

Directory of Open Access Journals (Sweden)

Petia Koprinkova-Hristova

2015-04-01

Full Text Available In the present paper a neural network approach called "Adaptive Critic Design" (ACD was applied to optimal tuning of set point controllers of the three main substrates (sugar, nitrogen source and dissolved oxygen for PHB production process. For approximation of the critic and the controllers a special kind of recurrent neural networks called Echo state networks (ESN were used. Their structure allows fast training that will be of crucial importance in on-line applications. The critic network is trained to minimize the temporal difference error using Recursive Least Squares method. Two approaches - gradient and heuristic - were exploited for training of the controllers. The comparison is made with respect to achieved improvement of the utility function subject of optimization as well as with known expert strategy for control the PHB production process.

Optimal Information Processing in Biochemical Networks

Science.gov (United States)

Wiggins, Chris

2012-02-01

A variety of experimental results over the past decades provide examples of near-optimal information processing in biological networks, including in biochemical and transcriptional regulatory networks. Computing information-theoretic quantities requires first choosing or computing the joint probability distribution describing multiple nodes in such a network --- for example, representing the probability distribution of finding an integer copy number of each of two interacting reactants or gene products while respecting the `intrinsic' small copy number noise constraining information transmission at the scale of the cell. I'll given an overview of some recent analytic and numerical work facilitating calculation of such joint distributions and the associated information, which in turn makes possible numerical optimization of information flow in models of noisy regulatory and biochemical networks. Illustrating cases include quantification of form-function relations, ideal design of regulatory cascades, and response to oscillatory driving.

Method of optimization of the natural gas refining process

Energy Technology Data Exchange (ETDEWEB)

Sadykh-Zade, E.S.; Bagirov, A.A.; Mardakhayev, I.M.; Razamat, M.S.; Tagiyev, V.G.

1980-01-01

The SATUM (automatic control system of technical operations) system introduced at the Shatlyk field should assure good quality of gas refining. In order to optimize the natural gas refining processes and experimental-analytical method is used in compiling the mathematical descriptions. The program, compiled in Fortran language, in addition to parameters of optimal conditions gives information on the yield of concentrate and water, concentration and consumption of DEG, composition and characteristics of the gas and condensate. The algorithm for calculating optimum engineering conditions of gas refining is proposed to be used in ''advice'' mode, and also for monitoring progress of the gas refining process.

Modelling on optimal portfolio with exchange rate based on discontinuous stochastic process

Science.gov (United States)

Yan, Wei; Chang, Yuwen

2016-12-01

Considering the stochastic exchange rate, this paper is concerned with the dynamic portfolio selection in financial market. The optimal investment problem is formulated as a continuous-time mathematical model under mean-variance criterion. These processes follow jump-diffusion processes (Weiner process and Poisson process). Then the corresponding Hamilton-Jacobi-Bellman(HJB) equation of the problem is presented and its efferent frontier is obtained. Moreover, the optimal strategy is also derived under safety-first criterion.

Fast engineering optimization: A novel highly effective control parameterization approach for industrial dynamic processes.

Science.gov (United States)

Liu, Ping; Li, Guodong; Liu, Xinggao

2015-09-01

Control vector parameterization (CVP) is an important approach of the engineering optimization for the industrial dynamic processes. However, its major defect, the low optimization efficiency caused by calculating the relevant differential equations in the generated nonlinear programming (NLP) problem repeatedly, limits its wide application in the engineering optimization for the industrial dynamic processes. A novel highly effective control parameterization approach, fast-CVP, is first proposed to improve the optimization efficiency for industrial dynamic processes, where the costate gradient formulae is employed and a fast approximate scheme is presented to solve the differential equations in dynamic process simulation. Three well-known engineering optimization benchmark problems of the industrial dynamic processes are demonstrated as illustration. The research results show that the proposed fast approach achieves a fine performance that at least 90% of the computation time can be saved in contrast to the traditional CVP method, which reveals the effectiveness of the proposed fast engineering optimization approach for the industrial dynamic processes. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

An optimization methodology for identifying robust process integration investments under uncertainty

Energy Technology Data Exchange (ETDEWEB)

Svensson, Elin; Berntsson, Thore [Department of Energy and Environment, Division of Heat and Power Technology, Chalmers University of Technology, SE-412 96 Goeteborg (Sweden); Stroemberg, Ann-Brith [Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Gothenburg (Sweden); Patriksson, Michael [Department of Mathematical Sciences, Chalmers University of Technology and Department of Mathematical Sciences, University of Gothenburg, SE-412 96 Goeteborg (Sweden)

2009-02-15

Uncertainties in future energy prices and policies strongly affect decisions on investments in process integration measures in industry. In this paper, we present a five-step methodology for the identification of robust investment alternatives incorporating explicitly such uncertainties in the optimization model. Methods for optimization under uncertainty (or, stochastic programming) are thus combined with a deep understanding of process integration and process technology in order to achieve a framework for decision-making concerning the investment planning of process integration measures under uncertainty. The proposed methodology enables the optimization of investments in energy efficiency with respect to their net present value or an environmental objective. In particular, as a result of the optimization approach, complex investment alternatives, allowing for combinations of energy efficiency measures, can be analyzed. Uncertainties as well as time-dependent parameters, such as energy prices and policies, are modelled using a scenario-based approach, enabling the identification of robust investment solutions. The methodology is primarily an aid for decision-makers in industry, but it will also provide insight for policy-makers into how uncertainties regarding future price levels and policy instruments affect the decisions on investments in energy efficiency measures. (author)

An optimization methodology for identifying robust process integration investments under uncertainty

International Nuclear Information System (INIS)

Svensson, Elin; Berntsson, Thore; Stroemberg, Ann-Brith; Patriksson, Michael

2009-01-01

Uncertainties in future energy prices and policies strongly affect decisions on investments in process integration measures in industry. In this paper, we present a five-step methodology for the identification of robust investment alternatives incorporating explicitly such uncertainties in the optimization model. Methods for optimization under uncertainty (or, stochastic programming) are thus combined with a deep understanding of process integration and process technology in order to achieve a framework for decision-making concerning the investment planning of process integration measures under uncertainty. The proposed methodology enables the optimization of investments in energy efficiency with respect to their net present value or an environmental objective. In particular, as a result of the optimization approach, complex investment alternatives, allowing for combinations of energy efficiency measures, can be analyzed. Uncertainties as well as time-dependent parameters, such as energy prices and policies, are modelled using a scenario-based approach, enabling the identification of robust investment solutions. The methodology is primarily an aid for decision-makers in industry, but it will also provide insight for policy-makers into how uncertainties regarding future price levels and policy instruments affect the decisions on investments in energy efficiency measures. (author)

Synthesis and Optimization of a Methanol Process

DEFF Research Database (Denmark)

Grue, J.; Bendtsen, Jan Dimon

2003-01-01

of reaction. The resulting model consists of a system of DAEs. The model is compared with rigorous simulation results from Pro/II and good agreement is found. The process is optimized followed by heat integration and large differences in the operating economy of the plant can be observed as a result hereof...

Optimization of TRPO process parameters for americium extraction from high level waste

International Nuclear Information System (INIS)

Chen Jing; Wang Jianchen; Song Chongli

2001-01-01

The numerical calculations for Am multistage fractional extraction by trialkyl phosphine oxide (TRPO) were verified by a hot test. 1750L/t-U high level waste (HLW) was used as the feed to the TRPO process. The analysis used the simple objective function to minimize the total waste content in the TRPO process streams. Some process parameters were optimized after other parameters were selected. The optimal process parameters for Am extraction by TRPO are: 10 stages for extraction and 2 stages for scrubbing; a flow rate ratio of 0.931 for extraction and 4.42 for scrubbing; nitric acid concentration of 1.35 mol/L for the feed and 0.5 mol/L for the scrubbing solution. Finally, the nitric acid and Am concentration profiles in the optimal TRPO extraction process are given

Off-Policy Reinforcement Learning: Optimal Operational Control for Two-Time-Scale Industrial Processes.

Science.gov (United States)

Li, Jinna; Kiumarsi, Bahare; Chai, Tianyou; Lewis, Frank L; Fan, Jialu

2017-12-01

Industrial flow lines are composed of unit processes operating on a fast time scale and performance measurements known as operational indices measured at a slower time scale. This paper presents a model-free optimal solution to a class of two time-scale industrial processes using off-policy reinforcement learning (RL). First, the lower-layer unit process control loop with a fast sampling period and the upper-layer operational index dynamics at a slow time scale are modeled. Second, a general optimal operational control problem is formulated to optimally prescribe the set-points for the unit industrial process. Then, a zero-sum game off-policy RL algorithm is developed to find the optimal set-points by using data measured in real-time. Finally, a simulation experiment is employed for an industrial flotation process to show the effectiveness of the proposed method.

Analysis of Human Mobility Based on Cellular Data

Science.gov (United States)

Arifiansyah, F.; Saptawati, G. A. P.

2017-01-01

Nowadays not only adult but even teenager and children have then own mobile phones. This phenomena indicates that the mobile phone becomes an important part of everyday’s life. Based on these indication, the amount of cellular data also increased rapidly. Cellular data defined as the data that records communication among mobile phone users. Cellular data is easy to obtain because the telecommunications company had made a record of the data for the billing system of the company. Billing data keeps a log of the users cellular data usage each time. We can obtained information from the data about communication between users. Through data visualization process, an interesting pattern can be seen in the raw cellular data, so that users can obtain prior knowledge to perform data analysis. Cellular data processing can be done using data mining to find out human mobility patterns and on the existing data. In this paper, we use frequent pattern mining and finding association rules to observe the relation between attributes in cellular data and then visualize them. We used weka tools for finding the rules in stage of data mining. Generally, the utilization of cellular data can provide supporting information for the decision making process and become a data support to provide solutions and information needed by the decision makers.

[Optimization of Energy Saving Measures with ABR-MBR Integrated Process].

Science.gov (United States)

Wu, Peng; Lu, Shuang-jun; Xu, Yue-zhong; Liu, Jie; Shen, Yao-liang

2015-08-01

High energy consumption and membrane fouling are important factors that limit the wide use of membrane bioreactor (MBR). In order to reduce energy consumption and delay the process of membrane fouling, the process of anaerobic baffled reactor (ABR)-MBR was used to treat domestic sewage. The structure of the process and conditions of nitrogen and phosphorus removal were optimized in this study. The results showed that energy consumption was reduced by 43% through optimizing the structure of ABR-MBR process. Meanwhile, the process achieved a high level of COD, NH: -N, TN and TP removal, with the average removal efficiencies of 91%, 85%, 76% and 86%, respectively. In addition, the added particulate media could effectively delay membrane fouling, while the formation process of membrane fouling was changed. The extracted amount of carbohydrates increased while the amount of proteins decreased. Finally, the potential was enhanced for the practical application of MBR.

Proteomic characterization of cellular and molecular processes that enable the Nanoarchaeum equitans--Ignicoccus hospitalis relationship.

Directory of Open Access Journals (Sweden)

Richard J Giannone

Full Text Available Nanoarchaeum equitans, the only cultured representative of the Nanoarchaeota, is dependent on direct physical contact with its host, the hyperthermophile Ignicoccus hospitalis. The molecular mechanisms that enable this relationship are unknown. Using whole-cell proteomics, differences in the relative abundance of >75% of predicted protein-coding genes from both Archaea were measured to identify the specific response of I. hospitalis to the presence of N. equitans on its surface. A purified N. equitans sample was also analyzed for evidence of interspecies protein transfer. The depth of cellular proteome coverage achieved here is amongst the highest reported for any organism. Based on changes in the proteome under the specific conditions of this study, I. hospitalis reacts to N. equitans by curtailing genetic information processing (replication, transcription in lieu of intensifying its energetic, protein processing and cellular membrane functions. We found no evidence of significant Ignicoccus biosynthetic enzymes being transported to N. equitans. These results suggest that, under laboratory conditions, N. equitans diverts some of its host's metabolism and cell cycle control to compensate for its own metabolic shortcomings, thus appearing to be entirely dependent on small, transferable metabolites and energetic precursors from I. hospitalis.

Cellularized Cellular Solids via Freeze-Casting.

Science.gov (United States)

Christoph, Sarah; Kwiatoszynski, Julien; Coradin, Thibaud; Fernandes, Francisco M

2016-02-01

The elaboration of metabolically active cell-containing materials is a decisive step toward the successful application of cell based technologies. The present work unveils a new process allowing to simultaneously encapsulate living cells and shaping cell-containing materials into solid-state macroporous foams with precisely controlled morphology. Our strategy is based on freeze casting, an ice templating materials processing technique that has recently emerged for the structuration of colloids into macroporous materials. Our results indicate that it is possible to combine the precise structuration of the materials with cellular metabolic activity for the model organism Saccharomyces cerevisiae. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimization process for thin-walled High Performance Concrete sandwich panels

DEFF Research Database (Denmark)

Hodicky, Kamil; Hulin, Thomas; Schmidt, Jacob Wittrup

2013-01-01

A Nearly zero energy buildings are to become a requirement as part of the European energy pol-icy. There are many ways of designing nearly zero energy buildings, but there is a lack of knowledge on opti-mization processes in the sense of structurally and thermally efficient design with an optimal...

A cellular automata based FPGA realization of a new metaheuristic bat-inspired algorithm

Science.gov (United States)

Progias, Pavlos; Amanatiadis, Angelos A.; Spataro, William; Trunfio, Giuseppe A.; Sirakoulis, Georgios Ch.

2016-10-01

Optimization algorithms are often inspired by processes occuring in nature, such as animal behavioral patterns. The main concern with implementing such algorithms in software is the large amounts of processing power they require. In contrast to software code, that can only perform calculations in a serial manner, an implementation in hardware, exploiting the inherent parallelism of single-purpose processors, can prove to be much more efficient both in speed and energy consumption. Furthermore, the use of Cellular Automata (CA) in such an implementation would be efficient both as a model for natural processes, as well as a computational paradigm implemented well on hardware. In this paper, we propose a VHDL implementation of a metaheuristic algorithm inspired by the echolocation behavior of bats. More specifically, the CA model is inspired by the metaheuristic algorithm proposed earlier in the literature, which could be considered at least as efficient than other existing optimization algorithms. The function of the FPGA implementation of our algorithm is explained in full detail and results of our simulations are also demonstrated.

Modeling and optimization of CO2 capture processes by chemical absorption

International Nuclear Information System (INIS)

Neveux, Thibaut

2013-01-01

CO 2 capture processes by chemical absorption lead to a large energy penalty on efficiency of coal-fired power plants, establishing one of the main bottleneck to its industrial deployment. The objective of this thesis is the development and validation of a global methodology, allowing the precise evaluation of the potential of a given amine capture process. Characteristic phenomena of chemical absorption have been thoroughly studied and represented with state-of-the-art models. The e-UNIQUAC model has been used to describe vapor-liquid and chemical equilibria of electrolyte solutions and the model parameters have been identified for four solvents. A rate-based formulation has been adopted for the representation of chemically enhanced heat and mass transfer in columns. The absorption and stripping models have been successfully validated against experimental data from an industrial and a laboratory pilot plants. The influence of the numerous phenomena has been investigated in order to highlight the most limiting ones. A methodology has been proposed to evaluate the total energy penalty resulting from the implementation of a capture process on an advanced supercritical coal-fired power plant, including thermal and electric consumptions. Then, the simulation and process evaluation environments have been coupled with a non-linear optimization algorithm in order to find optimal operating and design parameters with respect to energetic and economic performances. This methodology has been applied to optimize five process flow schemes operating with an monoethanolamine aqueous solution at 30% by weight: the conventional flow scheme and four process modifications. The performance comparison showed that process modifications using a heat pump effect give the best gains. The use of technical-economic analysis as an evaluation criterion of a process performance, coupled with a optimization algorithm, has proved its capability to find values for the numerous operating and design

Process optimization in petrochemical industries; Otimizacao de processo nas industrias petroquimicas

Energy Technology Data Exchange (ETDEWEB)

Castro Filho, Paulo Farias; Chachamovitz, Joao Carlos

1993-12-31

The most recent and efficient technologies of simulation, modeling and process optimization are presented. Some practical problems are analyzed together with a methodology for applying the optimization technologies. (author) 2 refs., 7 figs., 2 tabs.

Optimal energy control of a crushing process based on vertical shaft impactor

International Nuclear Information System (INIS)

Numbi, B.P.; Xia, X.

2016-01-01

Highlights: • Energy optimal control strategy of a VSI crushing process is modeled. • Potential of a daily energy cost saving of about 49.7% is shown. • Potential of a daily energy saving of about 15.3% is shown. • Most of energy cost saving is due to the optimal load shifting under time-of-use tariff. • Energy saving is due to the operation of the process at the boundary of the admissible region. - Abstract: This paper presents an optimal control model to improve the operation energy efficiency of a vertical shaft impact (VSI) crushing process. The optimal control model takes the energy cost as the performance index to be minimized by accounting for the time-of-use tariff and process constraints such as storage capacity of the VSI crusher hopper, capacity of the main storage system, flow rate limits, cascade ratio setting, production requirement and product quality requirement. The control variables in the developed model are the belt conveyor feed rate, the material feed rate into the VSI crusher rotor, the bi-flow or cascade feed rate and the rotor tip speed of the crusher. These four control variables are optimally coordinated in order to improve the operation energy efficiency of the VSI crushing process. Simulation results based on a crushing process in a coal-fired power plant demonstrate a potential of a daily energy cost saving of about 49.7% and energy saving of about 15.3% in a high-demand season weekday.

Experimental reversion of the optimal quantum cloning and flipping processes

International Nuclear Information System (INIS)

Sciarrino, Fabio; Secondi, Veronica; De Martini, Francesco

2006-01-01

The quantum cloner machine maps an unknown arbitrary input qubit into two optimal clones and one optimal flipped qubit. By combining linear and nonlinear optical methods we experimentally implement a scheme that, after the cloning transformation, restores the original input qubit in one of the output channels, by using local measurements, classical communication, and feedforward. This nonlocal method demonstrates how the information on the input qubit can be restored after the cloning process. The realization of the reversion process is expected to find useful applications in the field of modern multipartite quantum cryptography

Energy-saving management modelling and optimization for lead-acid battery formation process

Science.gov (United States)

Wang, T.; Chen, Z.; Xu, J. Y.; Wang, F. Y.; Liu, H. M.

2017-11-01

In this context, a typical lead-acid battery producing process is introduced. Based on the formation process, an efficiency management method is proposed. An optimization model with the objective to minimize the formation electricity cost in a single period is established. This optimization model considers several related constraints, together with two influencing factors including the transformation efficiency of IGBT charge-and-discharge machine and the time-of-use price. An example simulation is shown using PSO algorithm to solve this mathematic model, and the proposed optimization strategy is proved to be effective and learnable for energy-saving and efficiency optimization in battery producing industries.

A method of network topology optimization design considering application process characteristic

Science.gov (United States)

Wang, Chunlin; Huang, Ning; Bai, Yanan; Zhang, Shuo

2018-03-01

Communication networks are designed to meet the usage requirements of users for various network applications. The current studies of network topology optimization design mainly considered network traffic, which is the result of network application operation, but not a design element of communication networks. A network application is a procedure of the usage of services by users with some demanded performance requirements, and has obvious process characteristic. In this paper, we first propose a method to optimize the design of communication network topology considering the application process characteristic. Taking the minimum network delay as objective, and the cost of network design and network connective reliability as constraints, an optimization model of network topology design is formulated, and the optimal solution of network topology design is searched by Genetic Algorithm (GA). Furthermore, we investigate the influence of network topology parameter on network delay under the background of multiple process-oriented applications, which can guide the generation of initial population and then improve the efficiency of GA. Numerical simulations show the effectiveness and validity of our proposed method. Network topology optimization design considering applications can improve the reliability of applications, and provide guidance for network builders in the early stage of network design, which is of great significance in engineering practices.

Experimental Study On The Optimization Of Extraction Process Of ...

African Journals Online (AJOL)

The objective is to study the extraction process of garlic oil and its antibacterial effects. Materials and Methods: CO2 Supercritical extraction was used to investigate the optimal processing conditions for garlic oil extraction; filter paper test and suspension dilution test were applied to determine the bacteriostatic action of ...

The Cellular Differential Evolution Based on Chaotic Local Search

Directory of Open Access Journals (Sweden)

Qingfeng Ding

2015-01-01

Full Text Available To avoid immature convergence and tune the selection pressure in the differential evolution (DE algorithm, a new differential evolution algorithm based on cellular automata and chaotic local search (CLS or ccDE is proposed. To balance the exploration and exploitation tradeoff of differential evolution, the interaction among individuals is limited in cellular neighbors instead of controlling parameters in the canonical DE. To improve the optimizing performance of DE, the CLS helps by exploring a large region to avoid immature convergence in the early evolutionary stage and exploiting a small region to refine the final solutions in the later evolutionary stage. What is more, to improve the convergence characteristics and maintain the population diversity, the binomial crossover operator in the canonical DE may be instead by the orthogonal crossover operator without crossover rate. The performance of ccDE is widely evaluated on a set of 14 bound constrained numerical optimization problems compared with the canonical DE and several DE variants. The simulation results show that ccDE has better performances in terms of convergence rate and solution accuracy than other optimizers.

Parameter optimization of electrochemical machining process using black hole algorithm

Science.gov (United States)

Singh, Dinesh; Shukla, Rajkamal

2017-12-01

Advanced machining processes are significant as higher accuracy in machined component is required in the manufacturing industries. Parameter optimization of machining processes gives optimum control to achieve the desired goals. In this paper, electrochemical machining (ECM) process is considered to evaluate the performance of the considered process using black hole algorithm (BHA). BHA considers the fundamental idea of a black hole theory and it has less operating parameters to tune. The two performance parameters, material removal rate (MRR) and overcut (OC) are considered separately to get optimum machining parameter settings using BHA. The variations of process parameters with respect to the performance parameters are reported for better and effective understanding of the considered process using single objective at a time. The results obtained using BHA are found better while compared with results of other metaheuristic algorithms, such as, genetic algorithm (GA), artificial bee colony (ABC) and bio-geography based optimization (BBO) attempted by previous researchers.

Optimization process planning using hybrid genetic algorithm and intelligent search for job shop machining.

Science.gov (United States)

Salehi, Mojtaba; Bahreininejad, Ardeshir

2011-08-01

Optimization of process planning is considered as the key technology for computer-aided process planning which is a rather complex and difficult procedure. A good process plan of a part is built up based on two elements: (1) the optimized sequence of the operations of the part; and (2) the optimized selection of the machine, cutting tool and Tool Access Direction (TAD) for each operation. In the present work, the process planning is divided into preliminary planning, and secondary/detailed planning. In the preliminary stage, based on the analysis of order and clustering constraints as a compulsive constraint aggregation in operation sequencing and using an intelligent searching strategy, the feasible sequences are generated. Then, in the detailed planning stage, using the genetic algorithm which prunes the initial feasible sequences, the optimized operation sequence and the optimized selection of the machine, cutting tool and TAD for each operation based on optimization constraints as an additive constraint aggregation are obtained. The main contribution of this work is the optimization of sequence of the operations of the part, and optimization of machine selection, cutting tool and TAD for each operation using the intelligent search and genetic algorithm simultaneously.

Stochastic Model of Vesicular Sorting in Cellular Organelles

Science.gov (United States)

Vagne, Quentin; Sens, Pierre

2018-02-01

The proper sorting of membrane components by regulated exchange between cellular organelles is crucial to intracellular organization. This process relies on the budding and fusion of transport vesicles, and should be strongly influenced by stochastic fluctuations, considering the relatively small size of many organelles. We identify the perfect sorting of two membrane components initially mixed in a single compartment as a first passage process, and we show that the mean sorting time exhibits two distinct regimes as a function of the ratio of vesicle fusion to budding rates. Low ratio values lead to fast sorting but result in a broad size distribution of sorted compartments dominated by small entities. High ratio values result in two well-defined sorted compartments but sorting is exponentially slow. Our results suggest an optimal balance between vesicle budding and fusion for the rapid and efficient sorting of membrane components and highlight the importance of stochastic effects for the steady-state organization of intracellular compartments.

Cellular senescence and organismal aging.

Science.gov (United States)

Jeyapalan, Jessie C; Sedivy, John M

2008-01-01

Cellular senescence, first observed and defined using in vitro cell culture studies, is an irreversible cell cycle arrest which can be triggered by a variety of factors. Emerging evidence suggests that cellular senescence acts as an in vivo tumor suppression mechanism by limiting aberrant proliferation. It has also been postulated that cellular senescence can occur independently of cancer and contribute to the physiological processes of normal organismal aging. Recent data have demonstrated the in vivo accumulation of senescent cells with advancing age. Some characteristics of senescent cells, such as the ability to modify their extracellular environment, could play a role in aging and age-related pathology. In this review, we examine current evidence that links cellular senescence and organismal aging.

A Bayesian optimal design for degradation tests based on the inverse Gaussian process

Energy Technology Data Exchange (ETDEWEB)

Peng, Weiwen; Liu, Yu; Li, Yan Feng; Zhu, Shun Peng; Huang, Hong Zhong [University of Electronic Science and Technology of China, Chengdu (China)

2014-10-15

The inverse Gaussian process is recently introduced as an attractive and flexible stochastic process for degradation modeling. This process has been demonstrated as a valuable complement for models that are developed on the basis of the Wiener and gamma processes. We investigate the optimal design of the degradation tests on the basis of the inverse Gaussian process. In addition to an optimal design with pre-estimated planning values of model parameters, we also address the issue of uncertainty in the planning values by using the Bayesian method. An average pre-posterior variance of reliability is used as the optimization criterion. A trade-off between sample size and number of degradation observations is investigated in the degradation test planning. The effects of priors on the optimal designs and on the value of prior information are also investigated and quantified. The degradation test planning of a GaAs Laser device is performed to demonstrate the proposed method.

Terminal addition in a cellular world.

Science.gov (United States)

Torday, J S; Miller, William B

2018-07-01

Recent advances in our understanding of evolutionary development permit a reframed appraisal of Terminal Addition as a continuous historical process of cellular-environmental complementarity. Within this frame of reference, evolutionary terminal additions can be identified as environmental induction of episodic adjustments to cell-cell signaling patterns that yield the cellular-molecular pathways that lead to differing developmental forms. Phenotypes derive, thereby, through cellular mutualistic/competitive niche constructions in reciprocating responsiveness to environmental stresses and epigenetic impacts. In such terms, Terminal Addition flows according to a logic of cellular needs confronting environmental challenges over space-time. A reconciliation of evolutionary development and Terminal Addition can be achieved through a combined focus on cell-cell signaling, molecular phylogenies and a broader understanding of epigenetic phenomena among eukaryotic organisms. When understood in this manner, Terminal Addition has an important role in evolutionary development, and chronic disease might be considered as a form of 'reverse evolution' of the self-same processes. Copyright © 2017. Published by Elsevier Ltd.

The Process of Optimizing Mechanical Sound Quality in Product Design

DEFF Research Database (Denmark)

Eriksen, Kaare; Holst, Thomas

2011-01-01

The research field concerning optimizing product sound quality is a relatively unexplored area, and may become difficult for designers to operate in. To some degree, sound is a highly subjective parameter, which is normally targeted sound specialists. This paper describes the theoretical...... and practical background for managing a process of optimizing the mechanical sound quality in a product design by using simple tools and workshops systematically. The procedure is illustrated by a case study of a computer navigation tool (computer mouse or mouse). The process is divided into 4 phases, which...... clarify the importance of product sound, defining perceptive demands identified by users, and, finally, how to suggest mechanical principles for modification of an existing sound design. The optimized mechanical sound design is followed by tests on users of the product in its use context. The result...

Optimization of multi-objective integrated process planning and scheduling problem using a priority based optimization algorithm

Science.gov (United States)

Ausaf, Muhammad Farhan; Gao, Liang; Li, Xinyu

2015-12-01

For increasing the overall performance of modern manufacturing systems, effective integration of process planning and scheduling functions has been an important area of consideration among researchers. Owing to the complexity of handling process planning and scheduling simultaneously, most of the research work has been limited to solving the integrated process planning and scheduling (IPPS) problem for a single objective function. As there are many conflicting objectives when dealing with process planning and scheduling, real world problems cannot be fully captured considering only a single objective for optimization. Therefore considering multi-objective IPPS (MOIPPS) problem is inevitable. Unfortunately, only a handful of research papers are available on solving MOIPPS problem. In this paper, an optimization algorithm for solving MOIPPS problem is presented. The proposed algorithm uses a set of dispatching rules coupled with priority assignment to optimize the IPPS problem for various objectives like makespan, total machine load, total tardiness, etc. A fixed sized external archive coupled with a crowding distance mechanism is used to store and maintain the non-dominated solutions. To compare the results with other algorithms, a C-matric based method has been used. Instances from four recent papers have been solved to demonstrate the effectiveness of the proposed algorithm. The experimental results show that the proposed method is an efficient approach for solving the MOIPPS problem.

Gold-copper ores processing-Case study: optimization of flotation residue cyanidation

International Nuclear Information System (INIS)

McMullen, J.; Pelletier, P.; Breau, Y.; Pelletier, D.

1999-01-01

Typically, economic optimization of Gold-Copper ore processing presents challenges. Barrick's Bousquet II ore is a good example where many processing units such as gravity, flotation and cyanidation are required to efficiently recover the metals from the ore. Flowsheet criterion, operating strategy selections, cyanidation process optimization and its inter-dependence with flotation are discussed in detail. Real-time conservation integration of the cyanide control strategy has allowed a reduction of cyanide consumption of over 40% since 1994, while maintaining or improving metals recovery. A detailed analysis of the cyanidation control strategy such as key process sensor reliability and accuracy, process monitoring and fault detection is presented. This robust and efficient control strategy is a key building block that enhances the overall economic return of the process plant. (author)

Behaviour of cellular structures with fluid fillers under impact loading

Directory of Open Access Journals (Sweden)

Matej Vesenjak

2007-03-01

Full Text Available The paper investigates the behaviour of closed- and open-cell cellular structures under uniaxial impact loading by means of computational simulations using the explicit nonlinear finite element code LS-DYNA. Simulations also consider the influence of pore fillers and the base material strain rate sensitivity. The behaviour of closed-cell cellular structure has been evaluated with use of the representative volume element, where the influence of residual gas inside the closed pores has been studied. Open- cell cellular structure was modelled as a whole to properly account for considered fluid flow through the cells, which significantly influences macroscopic behaviour of the cellular structure. The fluid has been modelled by applying a meshless Smoothed Particle Hydrodynamics (SPH method. Parametric computational simulations provide grounds for optimization of cellular structures to satisfy different requirements, which makes them very attractive for use in general engineering applications.

Multiplex protein pattern unmixing using a non-linear variable-weighted support vector machine as optimized by a particle swarm optimization algorithm.

Science.gov (United States)

Yang, Qin; Zou, Hong-Yan; Zhang, Yan; Tang, Li-Juan; Shen, Guo-Li; Jiang, Jian-Hui; Yu, Ru-Qin

2016-01-15

Most of the proteins locate more than one organelle in a cell. Unmixing the localization patterns of proteins is critical for understanding the protein functions and other vital cellular processes. Herein, non-linear machine learning technique is proposed for the first time upon protein pattern unmixing. Variable-weighted support vector machine (VW-SVM) is a demonstrated robust modeling technique with flexible and rational variable selection. As optimized by a global stochastic optimization technique, particle swarm optimization (PSO) algorithm, it makes VW-SVM to be an adaptive parameter-free method for automated unmixing of protein subcellular patterns. Results obtained by pattern unmixing of a set of fluorescence microscope images of cells indicate VW-SVM as optimized by PSO is able to extract useful pattern features by optimally rescaling each variable for non-linear SVM modeling, consequently leading to improved performances in multiplex protein pattern unmixing compared with conventional SVM and other exiting pattern unmixing methods. Copyright © 2015 Elsevier B.V. All rights reserved.

Radioactive tracer technique in process optimization: applications in the chemical industry

International Nuclear Information System (INIS)

Charlton, J.S.

1989-01-01

Process optimization is concerned with the selection of the most appropriate technological design of the process and with controlling its operation to obtain maximum benefit. The role of radioactive tracers in process optimization is discussed and the various circumstances under which such techniques may be beneficially applied are identified. Case studies are presented which illustrate how radioisotopes may be used to monitor plant performance under dynamic conditions to improve production efficiency and to investigate the cause of production limitations. In addition, the use of sealed sources to provide information complementary to the tracer study is described. (author)

Energy-Efficient Resource Allocation for Phantom Cellular Networks with Imperfect CSI

KAUST Repository

Abdelhady, Amr Mohamed Abdelaziz

2017-03-28

Multi-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for a two-tier phantom cellular network, The optimization framework includes both EE and SE. We consider densely deployed phantom cellular networks and model the EE optimization problem taking into consideration the inevitable interference in this setup and imperfect channel estimation impairments. To this end, we propose three resource allocation strategies aiming at optimizing this network EE performance metric. Furthermore, we investigate the effect of changing some system parameters on the performance of these strategies, such as phantom cells resource units share, number of deployed phantom cells within a macro cell , number of pilots, and the phantom cells transmission power budget. It is found that increasing the number of pilots will deteriorate the EE performance of the whole setup, while increasing phantom cells transmission power budget will not affect the EE of the whole setup significantly. In addition, we observed that it is always useful to allocate most of the network resource units to the phantom cells tier.

Energy-Efficient Resource Allocation for Phantom Cellular Networks with Imperfect CSI

KAUST Repository

Abdelhady, Amr Mohamed Abdelaziz; Amin, Osama; Alouini, Mohamed-Slim

2017-01-01

Multi-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for a two-tier phantom cellular network, The optimization framework includes both EE and SE. We consider densely deployed phantom cellular networks and model the EE optimization problem taking into consideration the inevitable interference in this setup and imperfect channel estimation impairments. To this end, we propose three resource allocation strategies aiming at optimizing this network EE performance metric. Furthermore, we investigate the effect of changing some system parameters on the performance of these strategies, such as phantom cells resource units share, number of deployed phantom cells within a macro cell , number of pilots, and the phantom cells transmission power budget. It is found that increasing the number of pilots will deteriorate the EE performance of the whole setup, while increasing phantom cells transmission power budget will not affect the EE of the whole setup significantly. In addition, we observed that it is always useful to allocate most of the network resource units to the phantom cells tier.

Tuning of PID controller using optimization techniques for a MIMO process

Science.gov (United States)

Thulasi dharan, S.; Kavyarasan, K.; Bagyaveereswaran, V.

2017-11-01

In this paper, two processes were considered one is Quadruple tank process and the other is CSTR (Continuous Stirred Tank Reactor) process. These are majorly used in many industrial applications for various domains, especially, CSTR in chemical plants.At first mathematical model of both the process is to be done followed by linearization of the system due to MIMO process and controllers are the major part to control the whole process to our desired point as per the applications so the tuning of the controller plays a major role among the whole process. For tuning of parameters we use two optimizations techniques like Particle Swarm Optimization, Genetic Algorithm. The above techniques are majorly used in different applications to obtain which gives the best among all, we use these techniques to obtain the best tuned values among many. Finally, we will compare the performance of the each process with both the techniques.

Thermodynamic and economic optimization of LNG mixed refrigerant processes

International Nuclear Information System (INIS)

Wang, Mengyu; Khalilpour, Rajab; Abbas, Ali

2014-01-01

Highlights: • We study performance and cost optimization of C3MR and DMR processes. • A new economic objective function is proposed to reduce both compression work and equipment size. • The comparison of C3MR and DMR processes is based on process configuration, performance, and cost. - Abstract: Natural gas liquefaction processes are energy and cost intensive. This paper performs thermodynamic and economic optimization of the mid-scale mixed refrigerant cycles including propane precooled mixed refrigerant (C3MR) and dual mixed refrigerant (DMR) processes. Four different objective functions in this study are selected: total shaft work consumption, total cost investment (TCI), total annualized cost (TAC), and total capital cost of compressors and main cryogenic exchangers (MCHEs). Total cost investment (TCI) is a function of two key variables: shaft work (W) and overall heat transfer coefficient and area (UA) of MCHEs. It is proposed for reducing energy consumption and simultaneously minimizing total capital expenditure (CAPEX) and operating expenditure (OPEX). Total shaft work objective function can result in a 44.5% reduction of shaft work for C3MR and a 48.6% reduction for DMR compared to their baseline values, but infinitely high UA of MCHEs. Optimal results show that total capital cost of compressors and MCHEs is more suitable than other objective functions for the objective of reducing both shaft work and UA. It reduces 14.5% of specific power for C3MR and 26.7% for DMR when achieving the relatively lower UA values than their baseline values. In addition, TCI and TAC can also reduce a certain amount of total shaft work at a finite increased UA

Optimization Of PVDF-TrFE Processing Conditions For The Fabrication Of Organic MEMS Resonators.

Science.gov (United States)

Ducrot, Pierre-Henri; Dufour, Isabelle; Ayela, Cédric

2016-01-21

This paper reports a systematic optimization of processing conditions of PVDF-TrFE piezoelectric thin films, used as integrated transducers in organic MEMS resonators. Indeed, despite data on electromechanical properties of PVDF found in the literature, optimized processing conditions that lead to these properties remain only partially described. In this work, a rigorous optimization of parameters enabling state-of-the-art piezoelectric properties of PVDF-TrFE thin films has been performed via the evaluation of the actuation performance of MEMS resonators. Conditions such as annealing duration, poling field and poling duration have been optimized and repeatability of the process has been demonstrated.

USAF Logistics Process Optimization Study for the Aircraft Asset Sustainment Process. Volume 3. Future to be Asset Sustainment Process Model

National Research Council Canada - National Science Library

Adamson, Anthony

1998-01-01

.... It is published as three separate volumes. Volume I, USAF Logistics Process Optimization Study for the Aircraft Asset Sustainment Process -- Phase II Report, discusses the result and cost/benefit analysis of testing three initiatives...

Increasing efficiency of human mesenchymal stromal cell culture by optimization of microcarrier concentration and design of medium feed.

Science.gov (United States)

Chen, Allen Kuan-Liang; Chew, Yi Kong; Tan, Hong Yu; Reuveny, Shaul; Weng Oh, Steve Kah

2015-02-01

Large amounts of human mesenchymal stromal cells (MSCs) are needed for clinical cellular therapy. In a previous publication, we described a microcarrier-based process for expansion of MSCs. The present study optimized this process by selecting suitable basal media, microcarrier concentration and feeding regime to achieve higher cell yields and more efficient medium utilization. MSCs were expanded in stirred cultures on Cytodex 3 microcarriers with media containing 10% fetal bovine serum. Process optimization was carried out in spinner flasks. A 2-L bioreactor with an automated feeding system was used to validate the optimized parameters explored in spinner flask cultures. Minimum essential medium-α-based medium supported faster MSC growth on microcarriers than did Dulbecco's modified Eagle's medium (doubling time, 31.6 ± 1.4 vs 42 ± 1.7 h) and shortened the process time. At microcarrier concentration of 8 mg/mL, a high cell concentration of 1.08 × 10(6) cells/mL with confluent cell concentration of 4.7 × 10(4)cells/cm(2) was achieved. Instead of 50% medium exchange every 2 days, we have designed a full medium feed that is based on glucose consumption rate. The optimal medium feed that consisted of 1.5 g/L glucose supported MSC growth to full confluency while achieving the low medium usage efficiency of 3.29 mL/10(6)cells. Finally, a controlled bioreactor with the optimized parameters achieved maximal confluent cell concentration with 16-fold expansion and a further improved medium usage efficiency of 1.68 mL/10(6)cells. We have optimized the microcarrier-based platform for expansion of MSCs that generated high cell yields in a more efficient and cost-effective manner. This study highlighted the critical parameters in the optimization of MSC production process. Copyright © 2015 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

Design optimization of single mixed refrigerant LNG process using a hybrid modified coordinate descent algorithm

Science.gov (United States)

Qyyum, Muhammad Abdul; Long, Nguyen Van Duc; Minh, Le Quang; Lee, Moonyong

2018-01-01

Design optimization of the single mixed refrigerant (SMR) natural gas liquefaction (LNG) process involves highly non-linear interactions between decision variables, constraints, and the objective function. These non-linear interactions lead to an irreversibility, which deteriorates the energy efficiency of the LNG process. In this study, a simple and highly efficient hybrid modified coordinate descent (HMCD) algorithm was proposed to cope with the optimization of the natural gas liquefaction process. The single mixed refrigerant process was modeled in Aspen Hysys® and then connected to a Microsoft Visual Studio environment. The proposed optimization algorithm provided an improved result compared to the other existing methodologies to find the optimal condition of the complex mixed refrigerant natural gas liquefaction process. By applying the proposed optimization algorithm, the SMR process can be designed with the 0.2555 kW specific compression power which is equivalent to 44.3% energy saving as compared to the base case. Furthermore, in terms of coefficient of performance (COP), it can be enhanced up to 34.7% as compared to the base case. The proposed optimization algorithm provides a deep understanding of the optimization of the liquefaction process in both technical and numerical perspectives. In addition, the HMCD algorithm can be employed to any mixed refrigerant based liquefaction process in the natural gas industry.

Impact of Antenna Placement on Frequency Domain Adaptive Antenna Array in Hybrid FRF Cellular System

Directory of Open Access Journals (Sweden)

Sri Maldia Hari Asti

2012-01-01

Full Text Available Frequency domain adaptive antenna array (FDAAA is an effective method to suppress interference caused by frequency selective fading and multiple-access interference (MAI in single-carrier (SC transmission. However, the performance of FDAAA receiver will be affected by the antenna placement parameters such as antenna separation and spread of angle of arrival (AOA. On the other hand, hybrid frequency reuse can be adopted in cellular system to improve the cellular capacity. However, optimal frequency reuse factor (FRF depends on the channel propagation and transceiver scheme as well. In this paper, we analyze the impact of antenna separation and AOA spread on FDAAA receiver and optimize the cellular capacity by using hybrid FRF.

Laser Processing of Multilayered Thermal Spray Coatings: Optimal Processing Parameters

Science.gov (United States)

Tewolde, Mahder; Zhang, Tao; Lee, Hwasoo; Sampath, Sanjay; Hwang, David; Longtin, Jon

2017-12-01

Laser processing offers an innovative approach for the fabrication and transformation of a wide range of materials. As a rapid, non-contact, and precision material removal technology, lasers are natural tools to process thermal spray coatings. Recently, a thermoelectric generator (TEG) was fabricated using thermal spray and laser processing. The TEG device represents a multilayer, multimaterial functional thermal spray structure, with laser processing serving an essential role in its fabrication. Several unique challenges are presented when processing such multilayer coatings, and the focus of this work is on the selection of laser processing parameters for optimal feature quality and device performance. A parametric study is carried out using three short-pulse lasers, where laser power, repetition rate and processing speed are varied to determine the laser parameters that result in high-quality features. The resulting laser patterns are characterized using optical and scanning electron microscopy, energy-dispersive x-ray spectroscopy, and electrical isolation tests between patterned regions. The underlying laser interaction and material removal mechanisms that affect the feature quality are discussed. Feature quality was found to improve both by using a multiscanning approach and an optional assist gas of air or nitrogen. Electrically isolated regions were also patterned in a cylindrical test specimen.

Bayesian Optimization for Neuroimaging Pre-processing in Brain Age Classification and Prediction

Directory of Open Access Journals (Sweden)

Jenessa Lancaster

2018-02-01

Full Text Available Neuroimaging-based age prediction using machine learning is proposed as a biomarker of brain aging, relating to cognitive performance, health outcomes and progression of neurodegenerative disease. However, even leading age-prediction algorithms contain measurement error, motivating efforts to improve experimental pipelines. T1-weighted MRI is commonly used for age prediction, and the pre-processing of these scans involves normalization to a common template and resampling to a common voxel size, followed by spatial smoothing. Resampling parameters are often selected arbitrarily. Here, we sought to improve brain-age prediction accuracy by optimizing resampling parameters using Bayesian optimization. Using data on N = 2003 healthy individuals (aged 16–90 years we trained support vector machines to (i distinguish between young (<22 years and old (>50 years brains (classification and (ii predict chronological age (regression. We also evaluated generalisability of the age-regression model to an independent dataset (CamCAN, N = 648, aged 18–88 years. Bayesian optimization was used to identify optimal voxel size and smoothing kernel size for each task. This procedure adaptively samples the parameter space to evaluate accuracy across a range of possible parameters, using independent sub-samples to iteratively assess different parameter combinations to arrive at optimal values. When distinguishing between young and old brains a classification accuracy of 88.1% was achieved, (optimal voxel size = 11.5 mm3, smoothing kernel = 2.3 mm. For predicting chronological age, a mean absolute error (MAE of 5.08 years was achieved, (optimal voxel size = 3.73 mm3, smoothing kernel = 3.68 mm. This was compared to performance using default values of 1.5 mm3 and 4mm respectively, resulting in MAE = 5.48 years, though this 7.3% improvement was not statistically significant. When assessing generalisability, best performance was achieved when applying the entire Bayesian

Origami interleaved tube cellular materials

International Nuclear Information System (INIS)

Cheung, Kenneth C; Tachi, Tomohiro; Calisch, Sam; Miura, Koryo

2014-01-01

A novel origami cellular material based on a deployable cellular origami structure is described. The structure is bi-directionally flat-foldable in two orthogonal (x and y) directions and is relatively stiff in the third orthogonal (z) direction. While such mechanical orthotropicity is well known in cellular materials with extruded two dimensional geometry, the interleaved tube geometry presented here consists of two orthogonal axes of interleaved tubes with high interfacial surface area and relative volume that changes with fold-state. In addition, the foldability still allows for fabrication by a flat lamination process, similar to methods used for conventional expanded two dimensional cellular materials. This article presents the geometric characteristics of the structure together with corresponding kinematic and mechanical modeling, explaining the orthotropic elastic behavior of the structure with classical dimensional scaling analysis. (paper)

Origami interleaved tube cellular materials

Science.gov (United States)

Cheung, Kenneth C.; Tachi, Tomohiro; Calisch, Sam; Miura, Koryo

2014-09-01

A novel origami cellular material based on a deployable cellular origami structure is described. The structure is bi-directionally flat-foldable in two orthogonal (x and y) directions and is relatively stiff in the third orthogonal (z) direction. While such mechanical orthotropicity is well known in cellular materials with extruded two dimensional geometry, the interleaved tube geometry presented here consists of two orthogonal axes of interleaved tubes with high interfacial surface area and relative volume that changes with fold-state. In addition, the foldability still allows for fabrication by a flat lamination process, similar to methods used for conventional expanded two dimensional cellular materials. This article presents the geometric characteristics of the structure together with corresponding kinematic and mechanical modeling, explaining the orthotropic elastic behavior of the structure with classical dimensional scaling analysis.

Designing cellular manufacturing system under risk conditions ...

African Journals Online (AJOL)

This paper develops a mathematical modeling to design a cellular manufacturing system. In addition some of the total or portion of the demand of the part types can be subcontracted.. In order to designing the optimal CMS, we needs to detrmined a plan to produce and subcontract parts at a minimum cost and to mitigate the ...

Systemic evaluation of cellular reprogramming processes exploiting a novel R-tool: eegc.

Science.gov (United States)

Zhou, Xiaoyuan; Meng, Guofeng; Nardini, Christine; Mei, Hongkang

2017-08-15

Cells derived by cellular engineering, i.e. differentiation of induced pluripotent stem cells and direct lineage reprogramming, carry a tremendous potential for medical applications and in particular for regenerative therapies. These approaches consist in the definition of lineage-specific experimental protocols that, by manipulation of a limited number of biological cues-niche mimicking factors, (in)activation of transcription factors, to name a few-enforce the final expression of cell-specific (marker) molecules. To date, given the intricate complexity of biological pathways, these approaches still present imperfect reprogramming fidelity, with uncertain consequences on the functional properties of the resulting cells. We propose a novel tool eegc to evaluate cellular engineering processes, in a systemic rather than marker-based fashion, by integrating transcriptome profiling and functional analysis. Our method clusters genes into categories representing different states of (trans)differentiation and further performs functional and gene regulatory network analyses for each of the categories of the engineered cells, thus offering practical indications on the potential lack of the reprogramming protocol. eegc R package is released under the GNU General Public License within the Bioconductor project, freely available at https://bioconductor.org/packages/eegc/. christine.nardini.rsrc@gmail.com or hongkang.k.mei@gsk.com. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

A hybrid gene selection approach for microarray data classification using cellular learning automata and ant colony optimization.

Science.gov (United States)

Vafaee Sharbaf, Fatemeh; Mosafer, Sara; Moattar, Mohammad Hossein

2016-06-01

This paper proposes an approach for gene selection in microarray data. The proposed approach consists of a primary filter approach using Fisher criterion which reduces the initial genes and hence the search space and time complexity. Then, a wrapper approach which is based on cellular learning automata (CLA) optimized with ant colony method (ACO) is used to find the set of features which improve the classification accuracy. CLA is applied due to its capability to learn and model complicated relationships. The selected features from the last phase are evaluated using ROC curve and the most effective while smallest feature subset is determined. The classifiers which are evaluated in the proposed framework are K-nearest neighbor; support vector machine and naïve Bayes. The proposed approach is evaluated on 4 microarray datasets. The evaluations confirm that the proposed approach can find the smallest subset of genes while approaching the maximum accuracy. Copyright © 2016 Elsevier Inc. All rights reserved.

Transceiver Optimization for Multi-Antenna Deviceto-Device Communications

Institute of Scientific and Technical Information of China (English)

Daohua Zhu; Yajuan Guo; Lei Wei; Chaoyang Zhu; Biyao Huang; Wei Xu; Chunming Zhao

2016-01-01

It has been shown that the deployment of device-to-device (D2D) communication in cellular systems can provide better support for local services.However,improper design of the hybrid system may cause severe interference between cellular and D2D links.In this paper,we consider transceiver design for the system employing multiple antennas to mitigate the interference.The precoder and decoder matrices are optimized in terms of sum mean squared error (MSE) and capacity,respectively.For the MSE minimization problem,we present an alternative transceiver optimization algorithm.While for the non-convex capacity maximization problem,we decompose the primal problem into a sequence of standard convex quadratic programs for efficient optimization.The evaluation of our proposed algorithms for performance enhancement of the entire D2D integrated cellular system is carried out through simulations.

Microtubule self-organisation by reaction-diffusion processes causes collective transport and organisation of cellular particles

Directory of Open Access Journals (Sweden)

Demongeot Jacques

2004-06-01

Full Text Available Abstract Background The transport of intra-cellular particles by microtubules is a major biological function. Under appropriate in vitro conditions, microtubule preparations behave as a 'complex' system and show 'emergent' phenomena. In particular, they form dissipative structures that self-organise over macroscopic distances by a combination of reaction and diffusion. Results Here, we show that self-organisation also gives rise to a collective transport of colloidal particles along a specific direction. Particles, such as polystyrene beads, chromosomes, nuclei, and vesicles are carried at speeds of several microns per minute. The process also results in the macroscopic self-organisation of these particles. After self-organisation is completed, they show the same pattern of organisation as the microtubules. Numerical simulations of a population of growing and shrinking microtubules, incorporating experimentally realistic reaction dynamics, predict self-organisation. They forecast that during self-organisation, macroscopic parallel arrays of oriented microtubules form which cross the reaction space in successive waves. Such travelling waves are capable of transporting colloidal particles. The fact that in the simulations, the aligned arrays move along the same direction and at the same speed as the particles move, suggest that this process forms the underlying mechanism for the observed transport properties. Conclusions This process constitutes a novel physical chemical mechanism by which chemical energy is converted into collective transport of colloidal particles along a given direction. Self-organisation of this type provides a new mechanism by which intra cellular particles such as chromosomes and vesicles can be displaced and simultaneously organised by microtubules. It is plausible that processes of this type occur in vivo.

Microtubule self-organisation by reaction-diffusion processes causes collective transport and organisation of cellular particles

Science.gov (United States)

Glade, Nicolas; Demongeot, Jacques; Tabony, James

2004-01-01

Background The transport of intra-cellular particles by microtubules is a major biological function. Under appropriate in vitro conditions, microtubule preparations behave as a 'complex' system and show 'emergent' phenomena. In particular, they form dissipative structures that self-organise over macroscopic distances by a combination of reaction and diffusion. Results Here, we show that self-organisation also gives rise to a collective transport of colloidal particles along a specific direction. Particles, such as polystyrene beads, chromosomes, nuclei, and vesicles are carried at speeds of several microns per minute. The process also results in the macroscopic self-organisation of these particles. After self-organisation is completed, they show the same pattern of organisation as the microtubules. Numerical simulations of a population of growing and shrinking microtubules, incorporating experimentally realistic reaction dynamics, predict self-organisation. They forecast that during self-organisation, macroscopic parallel arrays of oriented microtubules form which cross the reaction space in successive waves. Such travelling waves are capable of transporting colloidal particles. The fact that in the simulations, the aligned arrays move along the same direction and at the same speed as the particles move, suggest that this process forms the underlying mechanism for the observed transport properties. Conclusions This process constitutes a novel physical chemical mechanism by which chemical energy is converted into collective transport of colloidal particles along a given direction. Self-organisation of this type provides a new mechanism by which intra cellular particles such as chromosomes and vesicles can be displaced and simultaneously organised by microtubules. It is plausible that processes of this type occur in vivo. PMID:15176973

Increasing cellular coverage within integrated terrestrial/satellite mobile networks

Science.gov (United States)

Castro, Jonathan P.

1995-01-01

When applying the hierarchical cellular concept, the satellite acts as giant umbrella cell covering a region with some terrestrial cells. If a mobile terminal traversing the region arrives to the border-line or limits of a regular cellular ground service, network transition occurs and the satellite system continues the mobile coverage. To adequately assess the boundaries of service of a mobile satellite system an a cellular network within an integrated environment, this paper provides an optimized scheme to predict when a network transition may be necessary. Under the assumption of a classified propagation phenomenon and Lognormal shadowing, the study applies an analytical approach to estimate the location of a mobile terminal based on a reception of the signal strength emitted by a base station.

Training practices of cell processing laboratory staff: analysis of a survey by the Alliance for Harmonization of Cellular Therapy Accreditation.

Science.gov (United States)

Keever-Taylor, Carolyn A; Slaper-Cortenbach, Ineke; Celluzzi, Christina; Loper, Kathy; Aljurf, Mahmoud; Schwartz, Joseph; Mcgrath, Eoin; Eldridge, Paul

2015-12-01

Methods for processing products used for hematopoietic progenitor cell (HPC) transplantation must ensure their safety and efficacy. Personnel training and ongoing competency assessment is critical to this goal. Here we present results from a global survey of methods used by a diverse array of cell processing facilities for the initial training and ongoing competency assessment of key personnel. The Alliance for Harmonisation of Cellular Therapy Accreditation (AHCTA) created a survey to identify facility type, location, activity, personnel, and methods used for training and competency. A survey link was disseminated through organizations represented in AHCTA to processing facilities worldwide. Responses were tabulated and analyzed as a percentage of total responses and as a percentage of response by region group. Most facilities were based at academic medical centers or hospitals. Facilities with a broad range of activity, product sources and processing procedures were represented. Facilities reported using a combination of training and competency methods. However, some methods predominated. Cellular sources for training differed for training versus competency and also differed based on frequency of procedures performed. Most facilities had responsibilities for procedures in addition to processing for which training and competency methods differed. Although regional variation was observed, training and competency requirements were generally consistent. Survey data showed the use of a variety of training and competency methods but some methods predominated, suggesting their utility. These results could help new and established facilities in making decisions for their own training and competency programs. Copyright © 2015 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

Optimization of aqueous extraction process to enhance the ...

African Journals Online (AJOL)

Kumar Sudhir

2014-02-12

Feb 12, 2014 ... Aqueous extraction process was optimized to reduce endotoxins from mixed ... management and minimizes the initial capital costs for ... of about 40%, was suggested to be an economic ... industry and as the nutraceutical food for human due to ... economical production of industrial enzymes and as feed.

Network-Coded Content Delivery in Femtocaching-Assisted Cellular Networks

KAUST Repository

Shnaiwer, Yousef N.; Sorour, Sameh; Aboutorab, Neda; Sadeghi, Parastoo; Al-Naffouri, Tareq Y.

2015-01-01

Next-generation cellular networks are expected to be assisted by femtocaches (FCs), which collectively store the most popular files for the clients. Given any arbitrary non-fragmented placement of such files, a strict no-latency constraint, and clients' prior knowledge, new file download requests could be efficiently handled by both the FCs and the macrocell base station (MBS) using opportunistic network coding (ONC). In this paper, we aim to find the best allocation of coded file downloads to the FCs so as to minimize the MBS involvement in this download process. We first formulate this optimization problem over an ONC graph, and show that it is NP-hard. We then propose a greedy approach that maximizes the number of files downloaded by the FCs, with the goal to reduce the download share of the MBS. This allocation is performed using a dual conflict ONC graph to avoid conflicts among the FC downloads. Simulations show that our proposed scheme almost achieves the optimal performance and significantly saves on the MBS bandwidth.

Network-Coded Content Delivery in Femtocaching-Assisted Cellular Networks

KAUST Repository

Shnaiwer, Yousef N.

2015-12-06

Next-generation cellular networks are expected to be assisted by femtocaches (FCs), which collectively store the most popular files for the clients. Given any arbitrary non-fragmented placement of such files, a strict no-latency constraint, and clients\\' prior knowledge, new file download requests could be efficiently handled by both the FCs and the macrocell base station (MBS) using opportunistic network coding (ONC). In this paper, we aim to find the best allocation of coded file downloads to the FCs so as to minimize the MBS involvement in this download process. We first formulate this optimization problem over an ONC graph, and show that it is NP-hard. We then propose a greedy approach that maximizes the number of files downloaded by the FCs, with the goal to reduce the download share of the MBS. This allocation is performed using a dual conflict ONC graph to avoid conflicts among the FC downloads. Simulations show that our proposed scheme almost achieves the optimal performance and significantly saves on the MBS bandwidth.

Parameters and characteristics governing cellular internalization and trans-barrier trafficking of nanostructures

Directory of Open Access Journals (Sweden)

Murugan K

2015-03-01

Full Text Available Karmani Murugan, Yahya E Choonara, Pradeep Kumar, Divya Bijukumar, Lisa C du Toit, Viness Pillay Wits Advanced Drug Delivery Platform Research Unit, Department of Pharmacy and Pharmacology, School of Therapeutic Sciences, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa Abstract: Cellular internalization and trans-barrier transport of nanoparticles can be manipulated on the basis of the physicochemical and mechanical characteristics of nanoparticles. Research has shown that these factors significantly influence the uptake of nanoparticles. Dictating these characteristics allows for the control of the rate and extent of cellular uptake, as well as delivering the drug-loaded nanosystem intra-cellularly, which is imperative for drugs that require a specific cellular level to exert their effects. Additionally, physicochemical characteristics of the nanoparticles should be optimal for the nanosystem to bypass the natural restricting phenomena of the body and act therapeutically at the targeted site. The factors at the focal point of emerging smart nanomedicines include nanoparticle size, surface charge, shape, hydrophobicity, surface chemistry, and even protein and ligand conjugates. Hence, this review discusses the mechanism of internalization of nanoparticles and ideal nanoparticle characteristics that allow them to evade the biological barriers in order to achieve optimal cellular uptake in different organ systems. Identifying these parameters assists with the progression of nanomedicine as an outstanding vector of pharmaceuticals. Keywords: nanoparticles, transport mechanisms, cellular uptake, size, shape, charge

Optimal estimation of the intensity function of a spatial point process

DEFF Research Database (Denmark)

Guan, Yongtao; Jalilian, Abdollah; Waagepetersen, Rasmus

easily computable estimating functions. We derive the optimal estimating function in a class of first-order estimating functions. The optimal estimating function depends on the solution of a certain Fredholm integral equation and reduces to the likelihood score in case of a Poisson process. We discuss...

Optimal Stopping Problems Driven by Lévy Processes and Pasting Principles

NARCIS (Netherlands)

Surya, B.A.

2007-01-01

Solving optimal stopping problems driven by Lévy processes has been a challenging task and has found many applications in modern theory of mathematical finance. For example situations in which optimal stopping typically arise include the problem of finding the arbitrage-free price of the American

Synthesis of Optimal Processing Pathway for Microalgae-based Biorefinery under Uncertainty

DEFF Research Database (Denmark)

Rizwan, Muhammad; Lee, Jay H.; Gani, Rafiqul

2015-01-01

decision making, we propose a systematic framework for the synthesis and optimal design of microalgae-based processing network under uncertainty. By incorporating major uncertainties into the biorefinery superstructure model we developed previously, a stochastic mixed integer nonlinear programming (s......The research in the field of microalgae-based biofuels and chemicals is in early phase of the development, and therefore a wide range of uncertainties exist due to inconsistencies among and shortage of technical information. In order to handle and address these uncertainties to ensure robust......MINLP) problem is formulated for determining the optimal biorefinery structure under given parameter uncertainties modelled as sampled scenarios. The solution to the sMINLP problem determines the optimal decisions with respect to processing technologies, material flows, and product portfolio in the presence...

Optimization of process parameters for synthesis of silica–Ni ...

Indian Academy of Sciences (India)

Optimization of process parameters for synthesis of silica–Ni nanocomposite by design of experiment ... Sol–gel; Ni; design of experiments; nanocomposites. ... Kolkata 700 032, India; Rustech Products Pvt. Ltd., Kolkata 700 045, India ...

Process optimization and insecticidal activity of alkaloids from the ...

African Journals Online (AJOL)

Process optimization and insecticidal activity of alkaloids from the root bark of Catalpa ovata G. Don by response surface methodology. ... Tropical Journal of Pharmaceutical Research. Journal Home · ABOUT THIS JOURNAL · Advanced ...

The Brewing Process: Optimizing the Fermentation

Directory of Open Access Journals (Sweden)

Teodora Coldea

2014-11-01

Full Text Available Beer is a carbonated alcoholic beverage obtained by alcoholic fermentation of malt wort boiled with hops. Brown beer obtained at Beer Pilot Station of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca was the result of a recipe based on blond, caramel and black malt in different proportions, water, hops and yeast. This study aimed to monitorize the evolution of wort in primary and secondary alcoholic fermentation in order to optimize the process. Two wort batches were assambled in order to increase the brewing yeast fermentation performance. The primary fermentation was 14 days, followed by another 14 days of secondary fermentation (maturation. The must fermentation monitoring was done by the automatic FermentoStar analyzer. The whole fermentation process was monitorized (temperature, pH, alcohol concentration, apparent and total wort extract.

A new decomposition method for parallel processing multi-level optimization

International Nuclear Information System (INIS)

Park, Hyung Wook; Kim, Min Soo; Choi, Dong Hoon

2002-01-01

In practical designs, most of the multidisciplinary problems have a large-size and complicate design system. Since multidisciplinary problems have hundreds of analyses and thousands of variables, the grouping of analyses and the order of the analyses in the group affect the speed of the total design cycle. Therefore, it is very important to reorder and regroup the original design processes in order to minimize the total computational cost by decomposing large multidisciplinary problems into several MultiDisciplinary Analysis SubSystems (MDASS) and by processing them in parallel. In this study, a new decomposition method is proposed for parallel processing of multidisciplinary design optimization, such as Collaborative Optimization (CO) and Individual Discipline Feasible (IDF) method. Numerical results for two example problems are presented to show the feasibility of the proposed method

Energy Efficient Resource Allocation for Phantom Cellular Networks

KAUST Repository

Abdelhady, Amr

2016-04-01

Multi-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-tier network architecture known as phantom cellular networks. The optimization framework includes both EE and SE. First, we consider sparsely deployed cells experiencing negligible interference and assume perfect channel state information (CSI). For this setting, we propose an algorithm that finds the SE and EE resource allocation strategies. Then, we compare the performance of both design strategies versus number of users, and phantom cells share of the total available resource units (RUs). We aim to investigate the effect of some system parameters to achieve improved SE performance at a non-significant loss in EE performance, or vice versa. It is found that increasing phantom cells share of RUs decreases the SE performance loss due to EE optimization when compared with the optimized SE performance. Second, we consider the densely deployed phantom cellular networks and model the EE optimization problem having into consideration the inevitable interference and imperfect channel estimation. To this end, we propose three resource allocation strategies aiming at optimizing the EE performance metric of this network. Furthermore, we investigate the effect of changing some of the system parameters on the performance of the proposed strategies, such as phantom cells share of RUs, number of deployed phantom cells within a macro cell coverage, number of pilots and the maximum power available for transmission by the phantom cells BSs. It is found that increasing the number of pilots deteriorates the EE performance of the whole setup, while increasing maximum power available for phantom cells transmissions reduces the EE of the whole setup in a

Towards Optimal Multi-Dimensional Query Processing with BitmapIndices

Energy Technology Data Exchange (ETDEWEB)

Rotem, Doron; Stockinger, Kurt; Wu, Kesheng

2005-09-30

Bitmap indices have been widely used in scientific applications and commercial systems for processing complex, multi-dimensional queries where traditional tree-based indices would not work efficiently. This paper studies strategies for minimizing the access costs for processing multi-dimensional queries using bitmap indices with binning. Innovative features of our algorithm include (a) optimally placing the bin boundaries and (b) dynamically reordering the evaluation of the query terms. In addition, we derive several analytical results concerning optimal bin allocation for a probabilistic query model. Our experimental evaluation with real life data shows an average I/O cost improvement of at least a factor of 10 for multi-dimensional queries on datasets from two different applications. Our experiments also indicate that the speedup increases with the number of query dimensions.

Optimization of cryogenic cooled EDM process parameters using grey relational analysis

International Nuclear Information System (INIS)

Kumar, S Vinoth; Kumar, M Pradeep

2014-01-01

This paper presents an experimental investigation on cryogenic cooling of liquid nitrogen (LN 2 ) copper electrode in the electrical discharge machining (EDM) process. The optimization of the EDM process parameters, such as the electrode environment (conventional electrode and cryogenically cooled electrode in EDM), discharge current, pulse on time, gap voltage on material removal rate, electrode wear, and surface roughness on machining of AlSiCp metal matrix composite using multiple performance characteristics on grey relational analysis was investigated. The L 18 orthogonal array was utilized to examine the process parameters, and the optimal levels of the process parameters were identified through grey relational analysis. Experimental data were analyzed through analysis of variance. Scanning electron microscopy analysis was conducted to study the characteristics of the machined surface.

Analyses of Methods and Algorithms for Modelling and Optimization of Biotechnological Processes

Directory of Open Access Journals (Sweden)

Stoyan Stoyanov

2009-08-01

Full Text Available A review of the problems in modeling, optimization and control of biotechnological processes and systems is given in this paper. An analysis of existing and some new practical optimization methods for searching global optimum based on various advanced strategies - heuristic, stochastic, genetic and combined are presented in the paper. Methods based on the sensitivity theory, stochastic and mix strategies for optimization with partial knowledge about kinetic, technical and economic parameters in optimization problems are discussed. Several approaches for the multi-criteria optimization tasks are analyzed. The problems concerning optimal controls of biotechnological systems are also discussed.

Drying of water based foundry coatings: Innovative test, process design and optimization methods

DEFF Research Database (Denmark)

Di Muoio, Giovanni Luca; Johansen, Bjørn Budolph

on real industrial cases. These tools have been developed in order to simulate and optimize the drying process and reduce drying time and power consumption as well as production process design time and cost of expensive drying equipment. Results show that test methods from other industries can be used...... capacity goals there is a need to understand how to design, control and optimize drying processes. The main focus of this project was on the critical parameters and properties to be controlled in production in order to achieve a stable and predictable drying process. We propose for each of these parameters...... of Denmark with the overall aim to optimize the drying process of water based foundry coatings. Drying of foundry coatings is a relatively new process in the foundry industry that followed the introduction of water as a solvent. In order to avoid moisture related quality problems and reach production...

Graphene transfer process and optimization of graphene coverage

OpenAIRE

Sabki Syarifah Norfaezah; Shamsuri Shafiq Hafly; Fauzi Siti Fazlina; Chon-Ki Meghashama Lim; Othman Noraini

2017-01-01

Graphene grown on transition metal is known to be high in quality due to its controlled amount of defects and potentially used for many electronic applications. The transfer process of graphene grown on transition metal to a new substrate requires optimization in order to ensure that high graphene coverage can be obtained. In this work, an improvement in the graphene transfer process is performed from graphene grown on copper foil. It has been observed that the graphene coverage is affected b...

Discrete stochastic processes and optimal filtering

CERN Document Server

Bertein, Jean-Claude

2012-01-01

Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter processing in the telecommunications industry, etc. This book provides a comprehensive overview of this area, discussing random and Gaussian vectors, outlining the results necessary for the creation of Wiener and adaptive filters used for stationary signals, as well as examining Kalman filters which ar

Cellular processes involved in human epidermal cells exposed to extremely low frequency electric fields.

Science.gov (United States)

Collard, J-F; Hinsenkamp, M

2015-05-01

We observed on different tissues and organisms a biological response after exposure to pulsed low frequency and low amplitude electric or electromagnetic fields but the precise mechanism of cell response remains unknown. The aim of this publication is to understand, using bioinformatics, the biological relevance of processes involved in the modification of gene expression. The list of genes analyzed was obtained after microarray protocol realized on cultures of human epidermal explants growing on deepidermized human skin exposed to a pulsed low frequency electric field. The directed acyclic graph on a WebGestalt Gene Ontology module shows six categories under the biological process root: "biological regulation", "cellular process", "cell proliferation", "death", "metabolic process" and "response to stimulus". Enriched derived categories are coherent with the type of in vitro culture, the stimulation protocol or with the previous results showing a decrease of cell proliferation and an increase of differentiation. The Kegg module on WebGestalt has highlighted "cell cycle" and "p53 signaling pathway" as significantly involved. The Kegg website brings out interactions between FoxO, MAPK, JNK, p53, p38, PI3K/Akt, Wnt, mTor or NF-KappaB. Some genes expressed by the stimulation are known to have an exclusive function on these pathways. Analyses performed with Pathway Studio linked cell proliferation, cell differentiation, apoptosis, cell cycle, mitosis, cell death etc. with our microarrays results. Medline citation generated by the software and the fold change variation confirms a diminution of the proliferation, activation of the differentiation and a less well-defined role of apoptosis or wound healing. Wnt and DKK functional classes, DKK1, MACF1, ATF3, MME, TXNRD1, and BMP-2 genes proposed in previous publications after a manual analysis are also highlighted with other genes after Pathway Studio automatic procedure. Finally, an analysis conducted on a list of genes

Optimization of CO2 Laser Cutting Process using Taguchi and Dual Response Surface Methodology

Directory of Open Access Journals (Sweden)

M. Madić

2014-09-01

Full Text Available Selection of optimal cutting parameter settings for obtaining high cut quality in CO2 laser cutting process is of great importance. Among various analytical and experimental optimization methods, the application of Taguchi and response surface methodology is one of most commonly used for laser cutting process optimization. Although the concept of dual response surface methodology for process optimization has been used with success, till date, no experimental study has been reported in the field of laser cutting. In this paper an approach for optimization of CO2 laser cutting process using Taguchi and dual response surface methodology is presented. The goal was to determine the near optimal laser cutting parameter values in order to ensure robust condition for minimization of average surface roughness. To obtain experimental database for development of response surface models, Taguchi’s L25 orthogonal array was implemented for experimental plan. Three cutting parameters, the cutting speed (3, 4, 5, 6, 7 m/min, the laser power (0.7, 0.9, 1.1, 1.3, 1.5 kW, and the assist gas pressure (3, 4, 5, 6, 7 bar, were used in the experiment. To obtain near optimal cutting parameters settings, multi-stage Monte Carlo simulation procedure was performed on the developed response surface models.

Impact of light on Hypocrea jecorina and the multiple cellular roles of ENVOY in this process

Directory of Open Access Journals (Sweden)

Druzhinina Irina S

2007-12-01

Full Text Available Abstract Background In fungi, light is primarily known to influence general morphogenesis and both sexual and asexual sporulation. In order to expand the knowledge on the effect of light in fungi and to determine the role of the light regulatory protein ENVOY in the implementation of this effect, we performed a global screen for genes, which are specifically effected by light in the fungus Hypocrea jecorina (anamorph Trichoderma reesei using Rapid Subtraction Hybridization (RaSH. Based on these data, we analyzed whether these genes are influenced by ENVOY and if overexpression of ENVOY in darkness would be sufficient to execute its function. Results The cellular functions of the detected light responsive genes comprised a variety of roles in transcription, translation, signal transduction, metabolism, and transport. Their response to light with respect to the involvement of ENVOY could be classified as follows: (i ENVOY-mediated upregulation by light; (ii ENVOY-independent upregulation by light; (iii ENVOY-antagonized upregulation by light; ENVOY-dependent repression by light; (iv ENVOY-independent repression by light; and (v both positive and negative regulation by ENVOY of genes not responsive to light in the wild-type. ENVOY was found to be crucial for normal growth in light on various carbon sources and is not able to execute its regulatory function if overexpressed in the darkness. Conclusion The different responses indicate that light impacts fungi like H. jecorina at several cellular processes, and that it has both positive and negative effects. The data also emphasize that ENVOY has an apparently more widespread cellular role in this process than only in modulating the response to light.

A sentinel protein assay for simultaneously quantifying cellular processes

Czech Academy of Sciences Publication Activity Database

Soste, M.; Hrabáková, Rita; Wanka, S.; Melnik, A.; Boersema, P.; Maiolica, A.; Wernas, T.; Tognetti, M.; von Mering, Ch.; Picotti, P.

2014-01-01

Roč. 11, č. 10 (2014), s. 1045-1048 ISSN 1548-7091 R&D Projects: GA MŠk ED2.1.00/03.0124 Institutional support: RVO:67985904 Keywords : targeted proteomics * selected reaction monitoring * cellular signaling Subject RIV: CE - Biochemistry Impact factor: 32.072, year: 2014

Modeling, Simulation and Optimization of Hydrogen Production Process from Glycerol using Steam Reforming

International Nuclear Information System (INIS)

Park, Jeongpil; Cho, Sunghyun; Kim, Tae-Ok; Shin, Dongil; Lee, Seunghwan; Moon, Dong Ju

2014-01-01

For improved sustainability of the biorefinery industry, biorefinery-byproduct glycerol is being investigated as an alternate source for hydrogen production. This research designs and optimizes a hydrogen-production process for small hydrogen stations using steam reforming of purified glycerol as the main reaction, replacing existing processes relying on steam methane reforming. Modeling, simulation and optimization using a commercial process simulator are performed for the proposed hydrogen production process from glycerol. The mixture of glycerol and steam are used for making syngas in the reforming process. Then hydrogen are produced from carbon monoxide and steam through the water-gas shift reaction. Finally, hydrogen is separated from carbon dioxide using PSA. This study shows higher yield than former U.S.. DOE and Linde studies. Economic evaluations are performed for optimal planning of constructing domestic hydrogen energy infrastructure based on the proposed glycerol-based hydrogen station

THE OPTIMIZATION OF PLUSH YARNS BULKING PROCESS

Directory of Open Access Journals (Sweden)

VINEREANU Adam

2014-05-01

Full Text Available This paper presents the experiments that were conducted on the installation of continuous bulking and thermofixing “SUPERBA” type TVP-2S for optimization of the plush yarns bulking process. There were considered plush yarns Nm 6.5/2, made of the fibrous blend of 50% indigenous wool sort 41 and 50% PES. In the first stage, it performs a thermal treatment with a turboprevaporizer at a temperature lower than thermofixing temperature, at atmospheric pressure, such that the plush yarns - deposed in a freely state on a belt conveyor - are uniformly bulking and contracting. It was followed the mathematical modeling procedure, working with a factorial program, rotatable central composite type, and two independent variables. After analyzing the parameters that have a direct influence on the bulking degree, there were selected the pre-vaporization temperature (coded x1,oC and the velocity of belt inside pre-vaporizer (coded x 2, m/min. As for the dependent variable, it was chosen the plush yarn diameter (coded y, mm. There were found the coordinates of the optimal point, and then this pair of values was verified in practice. These coordinates are: x1optim= 90oC and x 2optim= 6.5 m/min. The conclusion is that the goal was accomplished: it was obtained a good cover degree f or double-plush carpets by reducing the number of tufts per unit surface.

Optimization of upstream and development of cellulose hydrolysis process for cellulosic bio-ethanol production

International Nuclear Information System (INIS)

Bae, Hyeun Jong; Wi, Seung Gon; Lee, Yoon Gyo; Kim, Ho Myung; Kim, Su Bae

2011-10-01

The purpose of this project is optimization of upstream and development of cellulose hydrolysis process for cellulosic bio-ethanol production. The 2nd year Research scope includes: 1) Optimization of pre-treatment conditions for enzymatic hydrolysis of lignocellulosic biomass and 2) Demonstration of enzymatic hydrolysis by recombinant enzymes. To optimize the pretreatment, we applied two processes: a wet process (wet milling + popping), and dry process (popping + dry milling). Out of these, the wet process presented the best glucose yield with a 93.1% conversion, while the dry process yielded 69.6%, and the unpretreated process yielded <20%. The recombinant cellulolytic enzymes showed very high specific activity, about 80-1000 times on CMC and 13-70 times on filter paper at pH 3.5 and 55 .deg. C

Laser dimpling process parameters selection and optimization using surrogate-driven process capability space

Science.gov (United States)

Ozkat, Erkan Caner; Franciosa, Pasquale; Ceglarek, Dariusz

2017-08-01

Remote laser welding technology offers opportunities for high production throughput at a competitive cost. However, the remote laser welding process of zinc-coated sheet metal parts in lap joint configuration poses a challenge due to the difference between the melting temperature of the steel (∼1500 °C) and the vapourizing temperature of the zinc (∼907 °C). In fact, the zinc layer at the faying surface is vapourized and the vapour might be trapped within the melting pool leading to weld defects. Various solutions have been proposed to overcome this problem over the years. Among them, laser dimpling has been adopted by manufacturers because of its flexibility and effectiveness along with its cost advantages. In essence, the dimple works as a spacer between the two sheets in lap joint and allows the zinc vapour escape during welding process, thereby preventing weld defects. However, there is a lack of comprehensive characterization of dimpling process for effective implementation in real manufacturing system taking into consideration inherent changes in variability of process parameters. This paper introduces a methodology to develop (i) surrogate model for dimpling process characterization considering multiple-inputs (i.e. key control characteristics) and multiple-outputs (i.e. key performance indicators) system by conducting physical experimentation and using multivariate adaptive regression splines; (ii) process capability space (Cp-Space) based on the developed surrogate model that allows the estimation of a desired process fallout rate in the case of violation of process requirements in the presence of stochastic variation; and, (iii) selection and optimization of the process parameters based on the process capability space. The proposed methodology provides a unique capability to: (i) simulate the effect of process variation as generated by manufacturing process; (ii) model quality requirements with multiple and coupled quality requirements; and (iii

Optimization of Processing Technology of Compound Dandelion Wine

Directory of Open Access Journals (Sweden)

Wu Jixuan

2016-01-01

Full Text Available Exploring dandelion food has been the concern in fields of the food processing and pharmaceutical industry for playing exact curative effect on high-fat-diet induced hepatic steatosis and diuretic activity. Few dandelion foods including drinks and microencapsulation were explored and unilateral dandelion wine were less carried out for its bitter flavour. In tis paper, to optimize the processing technologies of fermented compound wine from dandelion root, the orthogonal experiment design method was used to composite dandelion root powder with glutinous rice and schisandra fruit and optimize the fermenting parameters. Four factors with dandelion content, schisandra content, acidity and sugar content were discussed. The acidity factor was firstly confirmed as 7.0 g/L. The other three factors were confirmed by a series experiments as dandelion 0.55%, schisandra 0.5%, sugar 22%. With nine step processing of mixing substrate, stirring with water, cooking rice, amylase saccharification, pectinase hydrolysis, adjusting juice, fermenting with yeast, fitering, aging, sterilization, a light yellow wine with the special taste with flavour of dandelion, schisandra and rice and less bitter, few index were determined as 14.7% alcohol, 6.85 g/L acidity. A dandelion fermented compound wine with suitable flavour and sanitarian function was developed for enriching the dandelion food.

FPGA based hardware optimized implementation of signal processing system for LFM pulsed radar

Science.gov (United States)

Azim, Noor ul; Jun, Wang

2016-11-01

Signal processing is one of the main parts of any radar system. Different signal processing algorithms are used to extract information about different parameters like range, speed, direction etc, of a target in the field of radar communication. This paper presents LFM (Linear Frequency Modulation) pulsed radar signal processing algorithms which are used to improve target detection, range resolution and to estimate the speed of a target. Firstly, these algorithms are simulated in MATLAB to verify the concept and theory. After the conceptual verification in MATLAB, the simulation is converted into implementation on hardware using Xilinx FPGA. Chosen FPGA is Xilinx Virtex-6 (XC6LVX75T). For hardware implementation pipeline optimization is adopted and also other factors are considered for resources optimization in the process of implementation. Focusing algorithms in this work for improving target detection, range resolution and speed estimation are hardware optimized fast convolution processing based pulse compression and pulse Doppler processing.

Process optimization for osmo-dehydrated carambola (Averrhoa carambola L) slices and its storage studies.

Science.gov (United States)

Roopa, N; Chauhan, O P; Raju, P S; Das Gupta, D K; Singh, R K R; Bawa, A S

2014-10-01

An osmotic-dehydration process protocol for Carambola (Averrhoacarambola L.,), an exotic star shaped tropical fruit, was developed. The process was optimized using Response Surface Methodology (RSM) following Central Composite Rotatable Design (CCRD). The experimental variables selected for the optimization were soak solution concentration (°Brix), soaking temperature (°C) and soaking time (min) with 6 experiments at central point. The effect of process variables was studied on solid gain and water loss during osmotic dehydration process. The data obtained were analyzed employing multiple regression technique to generate suitable mathematical models. Quadratic models were found to fit well (R(2), 95.58 - 98.64 %) in describing the effect of variables on the responses studied. The optimized levels of the process variables were achieved at 70°Brix, 48 °C and 144 min for soak solution concentration, soaking temperature and soaking time, respectively. The predicted and experimental results at optimized levels of variables showed high correlation. The osmo-dehydrated product prepared at optimized conditions showed a shelf-life of 10, 8 and 6 months at 5 °C, ambient (30 ± 2 °C) and 37 °C, respectively.

Mechanoluminescence assisting agile optimization of processing design on surgical epiphysis plates

Science.gov (United States)

Terasaki, Nao; Toyomasu, Takashi; Sonohata, Motoki

2018-04-01

We propose a novel method for agile optimization of processing design by visualization of mechanoluminescence. To demonstrate the effect of the new method, epiphysis plates were processed to form dots (diameters: 1 and 1.5 mm) and the mechanical information was evaluated. As a result, the appearance of new strain concentration was successfully visualized on the basis of mechanoluminescence, and complex mechanical information was instinctively understood by surgeons as the designers. In addition, it was clarified by mechanoluminescence analysis that small dots do not have serious mechanical effects such as strength reduction. Such detail mechanical information evaluated on the basis of mechanoluminescence was successfully applied to the judgement of the validity of the processing design. This clearly proves the effectiveness of the new methodology using mechanoluminescence for assisting agile optimization of the processing design.

Cellular therapies for heart disease: unveiling the ethical and public policy challenges.

Science.gov (United States)

Raval, Amish N; Kamp, Timothy J; Hogle, Linda F

2008-10-01

Cellular therapies have emerged as a potential revolutionary treatment for cardiovascular disease. Promising preclinical results have resulted in a flurry of basic research activity and spawned multiple clinical trials worldwide. However, the optimal cell type and delivery mode have not been determined for target patient populations. Nor have the mechanisms of benefit for the range of cellular interventions been clearly defined. Experiences to date have unveiled a myriad of ethical and public policy challenges which will affect the way researchers and clinicians make decisions for both basic and clinical research. Stem cells derived from embryos are at the forefront of the ethical and political debate, raising issues of which derivation methods are morally and socially permissible to pursue, as much as which are technically feasible. Adult stem cells are less controversial; however, important challenges exist in determining study design, cell processing, delivery mode, and target patient population. Pathways to successful commercialization and hence broad accessibility of cellular therapies for heart disease are only beginning to be explored. Comprehensive, multi-disciplinary and collaborative networks involving basic researchers, clinicians, regulatory officials and policymakers are required to share information, develop research, regulatory and policy standards and enable rational and ethical cell-based treatment approaches.

Monocyte Activation in Immunopathology: Cellular Test for Development of Diagnostics and Therapy

Directory of Open Access Journals (Sweden)

Ekaterina A. Ivanova

2016-01-01

Full Text Available Several highly prevalent human diseases are associated with immunopathology. Alterations in the immune system are found in such life-threatening disorders as cancer and atherosclerosis. Monocyte activation followed by macrophage polarization is an important step in normal immune response to pathogens and other relevant stimuli. Depending on the nature of the activation signal, macrophages can acquire pro- or anti-inflammatory phenotypes that are characterized by the expression of distinct patterns of secreted cytokines and surface antigens. This process is disturbed in immunopathologies resulting in abnormal monocyte activation and/or bias of macrophage polarization towards one or the other phenotype. Such alterations could be used as important diagnostic markers and also as possible targets for the development of immunomodulating therapy. Recently developed cellular tests are designed to analyze the phenotype and activity of living cells circulating in patient’s bloodstream. Monocyte/macrophage activation test is a successful example of cellular test relevant for atherosclerosis and oncopathology. This test demonstrated changes in macrophage activation in subclinical atherosclerosis and breast cancer and could also be used for screening a panel of natural agents with immunomodulatory activity. Further development of cellular tests will allow broadening the scope of their clinical implication. Such tests may become useful tools for drug research and therapy optimization.

Multi-Response Parameter Interval Sensitivity and Optimization for the Composite Tape Winding Process

Science.gov (United States)

Yu, Tao; Kang, Chao; Zhao, Pan

2018-01-01

The composite tape winding process, which utilizes a tape winding machine and prepreg tapes, provides a promising way to improve the quality of composite products. Nevertheless, the process parameters of composite tape winding have crucial effects on the tensile strength and void content, which are closely related to the performances of the winding products. In this article, two different object values of winding products, including mechanical performance (tensile strength) and a physical property (void content), were respectively calculated. Thereafter, the paper presents an integrated methodology by combining multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis to obtain the optimal intervals of the composite tape winding process. First, the global multi-parameter sensitivity analysis method was applied to investigate the sensitivity of each parameter in the tape winding processing. Then, the local single-parameter sensitivity analysis method was employed to calculate the sensitivity of a single parameter within the corresponding range. Finally, the stability and instability ranges of each parameter were distinguished. Meanwhile, the authors optimized the process parameter ranges and provided comprehensive optimized intervals of the winding parameters. The verification test validated that the optimized intervals of the process parameters were reliable and stable for winding products manufacturing. PMID:29385048

Systematic Optimization-Based Integrated Chemical Product–Process Design Framework

DEFF Research Database (Denmark)

Cignitti, Stefano; Mansouri, Seyed Soheil; Woodley, John M.

2018-01-01

An integrated optimization-based framework for product and process design is proposed. The framework uses a set of methods and tools to obtain the optimal product–process design solution given a set of economic and environmental sustainability targets. The methods and tools required are property...... of the framework is demonstrated through three case studies: (i) refrigeration cycle unit for R134a replacement, (ii) a mixed working fluid design problem for R134a replacement, and (iii) pure solvent design for water-acetic acid LLE extraction. Through the application of the framework it is demonstrated that all...... prediction through group contributions, unless supported with a database, computer-aided molecular and mixture/blend design for generation of novel as well as existing products and mathematical programming for formulating and solving multiscale integrated process–product design problems. The application...

Optimization of the process of egg omelet production with fillings with extended storage period

Directory of Open Access Journals (Sweden)

V. Sukmanov

2015-05-01

Full Text Available Introduction. Optimization of the egg omelets (EO production using high pressure (HP will allow to produce a minimum cost product during manufacturing and also to obtain a product with high consumer properties. Materialsand methods. The concerned product is -EO -a mixture of liquid egg with grated or chopped cheese, xanthan gum, water or milk and spices. The EO manufacturing process consisted of packing the mixture in an airtight container with heating and processing in the high pressure installation. The EO suitability for long-term storage was evaluated by the "water activity" term. The EO quality was evaluated by an expert. There was used the undetermined Lagrange multipliers method to obtain the optimal process parameters. Results. As a result of the central composite rotatabel plan there was developed optimization model allowed to obtain the optimal EO HP processing parameters: pressure – 690 МPа, temperature –1220С, treatment duration –7×60s, 14g of water on 100 g of melange, 13 g of dry milk on 100 g of melange, xanthan gum content -0,75% of the total mixture mass, 25 g of cheese on 100 g of melange. These indicators allow to obtain the EO process parameters with the next indicators: water activity -0.704 and comprehensive quality Score - 0.98 that characterize the product as a product with high quality indicators stable over a long period of storage. The developed model analysis with using of Student's t test, Fisher dyspepsia and predicted optimization values calculation errors confirmed the reliability of the optimization parameters obtained values and the optimization model reliability. The calculations results for the given optimization parameters are presented as confidence intervals, confirming that their experimental values do not exceed the respective intervals and thus confirm the results authenticity . Conclusions. These results have practical significance and were adopted as the basis for the technical documentation

Optimization of cutting parameters for machining time in turning process

Science.gov (United States)

Mavliutov, A. R.; Zlotnikov, E. G.

2018-03-01

This paper describes the most effective methods for nonlinear constraint optimization of cutting parameters in the turning process. Among them are Linearization Programming Method with Dual-Simplex algorithm, Interior Point method, and Augmented Lagrangian Genetic Algorithm (ALGA). Every each of them is tested on an actual example – the minimization of production rate in turning process. The computation was conducted in the MATLAB environment. The comparative results obtained from the application of these methods show: The optimal value of the linearized objective and the original function are the same. ALGA gives sufficiently accurate values, however, when the algorithm uses the Hybrid function with Interior Point algorithm, the resulted values have the maximal accuracy.

Information theoretic methods for image processing algorithm optimization

Science.gov (United States)

Prokushkin, Sergey F.; Galil, Erez

2015-01-01

Modern image processing pipelines (e.g., those used in digital cameras) are full of advanced, highly adaptive filters that often have a large number of tunable parameters (sometimes > 100). This makes the calibration procedure for these filters very complex, and the optimal results barely achievable in the manual calibration; thus an automated approach is a must. We will discuss an information theory based metric for evaluation of algorithm adaptive characteristics ("adaptivity criterion") using noise reduction algorithms as an example. The method allows finding an "orthogonal decomposition" of the filter parameter space into the "filter adaptivity" and "filter strength" directions. This metric can be used as a cost function in automatic filter optimization. Since it is a measure of a physical "information restoration" rather than perceived image quality, it helps to reduce the set of the filter parameters to a smaller subset that is easier for a human operator to tune and achieve a better subjective image quality. With appropriate adjustments, the criterion can be used for assessment of the whole imaging system (sensor plus post-processing).

The parallel processing impact in the optimization of the reactors neutronic by genetic algorithms

International Nuclear Information System (INIS)

Pereira, Claudio M.N.A.; Universidade Federal, Rio de Janeiro, RJ; Lapa, Celso M.F.; Mol, Antonio C.A.

2002-01-01

Nowadays, many optimization problems found in nuclear engineering has been solved through genetic algorithms (GA). The robustness of such methods is strongly related to the nature of search process which is based on populations of solution candidates, and this fact implies high computational cost in the optimization process. The use of GA become more critical when the evaluation process of a solution candidate is highly time consuming. Problems of this nature are common in the nuclear engineering, and an example is the reactor design optimization, where neutronic codes, which consume high CPU time, must be run. Aiming to investigate the impact of the use of parallel computation in the solution, through GA, of a reactor design optimization problem, a parallel genetic algorithm (PGA), using the Island Model, was developed. Exhaustive experiments, then 1500 processing hours in 550 MHz personal computers, have been done, in order to compare the conventional GA with the PGA. Such experiments have demonstrating the superiority of the PGA not only in terms of execution time, but also, in the optimization results. (author)

Process optimization and evaluation of novel baicalin solid nanocrystals

Directory of Open Access Journals (Sweden)

Yue PF

2013-08-01

Full Text Available Peng-Fei Yue,1,2 Yu Li,1 Jing Wan,1 Yong Wang,1 Ming Yang,1 Wei-Feng Zhu,1 Chang-Hong Wang,2 Hai-Long Yuan31Key Lab of Modern Preparation of TCM, Jiangxi University of Traditional Chinese Medicine, Nanchang, 2Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, 3302 Hospital of PLA Institute of Chinese Materia Medica, Beijing, People's Republic of ChinaAbstract: The objective of this study was to prepare baicalin solid nanocrystals (BCN-SNS to enhance oral bioavailability of baicalin. A Box–Behnken design approach was used for process optimization. The physicochemical properties and pharmacokinetics of the optimal BCN-SNS were investigated. Multiple linear regression analysis for process optimization revealed that the fine BCN-SNS was obtained wherein the optimal values of homogenization pressure (bar, homogenization cycles (cycles, amount of TPGS to drug (w/w, and amount of MCCS to drug (w/w were 850 bar, 25 cycles, 10%, and 10%, respectively. Transmission electron microscopy and scanning electron microscopy results indicated that no significant aggregation or crystal growth could be observed in the redispersed freeze-dried BCN-SNS. Differential scanning calorimetry and X-ray diffraction results showed that BCN remained in a crystalline state. Dissolution velocity of the freeze-dried BCN-SNS powder was distinctly superior compared to those of the crude powder and physical mixture. The bioavailability of BCN in rats was increased remarkably after oral administration of BCN-SNS (P < 0.05, compared with those of BCN or the physical mixture. The SNS might be a good choice for oral administration of poorly soluble BCN, due to an improvement of the bioavailability and dissolution velocity of BCN-SNS.Keywords: baicalin, solid nanocrystals, optimization, in vivo/vitro evaluation

A model for optimization of process integration investments under uncertainty

International Nuclear Information System (INIS)

Svensson, Elin; Stroemberg, Ann-Brith; Patriksson, Michael

2011-01-01

The long-term economic outcome of energy-related industrial investment projects is difficult to evaluate because of uncertain energy market conditions. In this article, a general, multistage, stochastic programming model for the optimization of investments in process integration and industrial energy technologies is proposed. The problem is formulated as a mixed-binary linear programming model where uncertainties are modelled using a scenario-based approach. The objective is to maximize the expected net present value of the investments which enables heat savings and decreased energy imports or increased energy exports at an industrial plant. The proposed modelling approach enables a long-term planning of industrial, energy-related investments through the simultaneous optimization of immediate and later decisions. The stochastic programming approach is also suitable for modelling what is possibly complex process integration constraints. The general model formulation presented here is a suitable basis for more specialized case studies dealing with optimization of investments in energy efficiency. -- Highlights: → Stochastic programming approach to long-term planning of process integration investments. → Extensive mathematical model formulation. → Multi-stage investment decisions and scenario-based modelling of uncertain energy prices. → Results illustrate how investments made now affect later investment and operation opportunities. → Approach for evaluation of robustness with respect to variations in probability distribution.

On the optimal design of the disassembly and recovery processes.

Science.gov (United States)

Xanthopoulos, A; Iakovou, E

2009-05-01

This paper tackles the problem of the optimal design of the recovery processes of the end-of-life (EOL) electric and electronic products, with a special focus on the disassembly issues. The objective is to recover as much ecological and economic value as possible, and to reduce the overall produced quantities of waste. In this context, a medium-range tactical problem is defined and a novel two-phased algorithm is presented for a remanufacturing-driven reverse supply chain. In the first phase, we propose a multicriteria/goal-programming analysis for the identification and the optimal selection of the most 'desirable' subassemblies and components to be disassembled for recovery, from a set of different types of EOL products. In the second phase, a multi-product, multi-period mixed-integer linear programming (MILP) model is presented, which addresses the optimization of the recovery processes, while taking into account explicitly the lead times of the disassembly and recovery processes. Moreover, a simulation-based solution approach is proposed for capturing the uncertainties in reverse logistics. The overall approach leads to an easy-to-use methodology that could support effectively middle level management decisions. Finally, the applicability of the developed methodology is illustrated by its application on a specific case study.

On the optimal design of the disassembly and recovery processes

International Nuclear Information System (INIS)

Xanthopoulos, A.; Iakovou, E.

2009-01-01

This paper tackles the problem of the optimal design of the recovery processes of the end-of-life (EOL) electric and electronic products, with a special focus on the disassembly issues. The objective is to recover as much ecological and economic value as possible, and to reduce the overall produced quantities of waste. In this context, a medium-range tactical problem is defined and a novel two-phased algorithm is presented for a remanufacturing-driven reverse supply chain. In the first phase, we propose a multicriteria/goal-programming analysis for the identification and the optimal selection of the most 'desirable' subassemblies and components to be disassembled for recovery, from a set of different types of EOL products. In the second phase, a multi-product, multi-period mixed-integer linear programming (MILP) model is presented, which addresses the optimization of the recovery processes, while taking into account explicitly the lead times of the disassembly and recovery processes. Moreover, a simulation-based solution approach is proposed for capturing the uncertainties in reverse logistics. The overall approach leads to an easy-to-use methodology that could support effectively middle level management decisions. Finally, the applicability of the developed methodology is illustrated by its application on a specific case study

Optimization of the Fermentation Process in a Brewery with a Fuzzy Logic Controller

Directory of Open Access Journals (Sweden)

Philip B. OSOFISAN

2007-08-01

Full Text Available In this research work, the fermentation process in a Brewery will be optimized, with the application of Fuzzy Logic Controller (FLC. Fermentation is controlled by regulating the temperature, the oxygen content and the pitch rate; but the temperature plays a dominant role in the optimization of the fermentation process. For our case study (Guinness Nigeria Plc the optimal fermentation temperature is 16ºC, so the FLC has been designed to maintain this temperature. The designed FLC can also be applied to maintain any other optimal fermentation temperature e.g. 20ºC. These two cases have been investigated. The FLC has been stimulated on a digital computer using MATLAB 5.0 Fuzzy Logic Tool Box.

Optimization of injection molding process parameters for a plastic cell phone housing component

Science.gov (United States)

Rajalingam, Sokkalingam; Vasant, Pandian; Khe, Cheng Seong; Merican, Zulkifli; Oo, Zeya

2016-11-01

To produce thin-walled plastic items, injection molding process is one of the most widely used application tools. However, to set optimal process parameters is difficult as it may cause to produce faulty items on injected mold like shrinkage. This study aims at to determine such an optimum injection molding process parameters which can reduce the fault of shrinkage on a plastic cell phone cover items. Currently used setting of machines process produced shrinkage and mis-specified length and with dimensions below the limit. Thus, for identification of optimum process parameters, maintaining closer targeted length and width setting magnitudes with minimal variations, more experiments are needed. The mold temperature, injection pressure and screw rotation speed are used as process parameters in this research. For optimal molding process parameters the Response Surface Methods (RSM) is applied. The major contributing factors influencing the responses were identified from analysis of variance (ANOVA) technique. Through verification runs it was found that the shrinkage defect can be minimized with the optimal setting found by RSM.

Epigenetics and Cellular Metabolism

Directory of Open Access Journals (Sweden)

Wenyi Xu

2016-01-01

Full Text Available Living eukaryotic systems evolve delicate cellular mechanisms for responding to various environmental signals. Among them, epigenetic machinery (DNA methylation, histone modifications, microRNAs, etc. is the hub in transducing external stimuli into transcriptional response. Emerging evidence reveals the concept that epigenetic signatures are essential for the proper maintenance of cellular metabolism. On the other hand, the metabolite, a main environmental input, can also influence the processing of epigenetic memory. Here, we summarize the recent research progress in the epigenetic regulation of cellular metabolism and discuss how the dysfunction of epigenetic machineries influences the development of metabolic disorders such as diabetes and obesity; then, we focus on discussing the notion that manipulating metabolites, the fuel of cell metabolism, can function as a strategy for interfering epigenetic machinery and its related disease progression as well.

Optimization of WEDM process parameters using deep cryo-treated Inconel 718 as work material

Directory of Open Access Journals (Sweden)

Bijaya Bijeta Nayak

2016-03-01

Full Text Available The present work proposes an experimental investigation and optimization of various process parameters during taper cutting of deep cryo-treated Inconel 718 in wire electrical discharge machining process. Taguchi's design of experiment is used to gather information regarding the process with less number of experimental runs considering six input parameters such as part thickness, taper angle, pulse duration, discharge current, wire speed and wire tension. Since traditional Taguchi method fails to optimize multiple performance characteristics, maximum deviation theory is applied to convert multiple performance characteristics into an equivalent single performance characteristic. Due to the complexity and non-linearity involved in this process, good functional relationship with reasonable accuracy between performance characteristics and process parameters is difficult to obtain. To address this issue, the present study proposes artificial neural network (ANN model to determine the relationship between input parameters and performance characteristics. Finally, the process model is optimized to obtain a best parametric combination by a new meta-heuristic approach known as bat algorithm. The results of the proposed algorithm show that the proposed method is an effective tool for simultaneous optimization of performance characteristics during taper cutting in WEDM process.

Process and Energy Optimization Assessment, Tobyhanna Army Depot, PA

Science.gov (United States)

2006-04-17

assembly of electronic-communication components, different welding processes are performed at TYAD. It uses shielded arc, metal inert gas (MIG...tungsten inert gas ( TIG ), and silver braz- ing oxygen/acetylene cutting plasma arc methods to complete mission re- quirements. Major welding jobs are...ER D C/ CE R L TR -0 6 -1 1 Process and Energy Optimization Assessment Tobyhanna Army Depot, PA Mike C.J. Lin, Alexander M. Zhivov

Hydrologic Process-oriented Optimization of Electrical Resistivity Tomography

Science.gov (United States)

Hinnell, A.; Bechtold, M.; Ferre, T. A.; van der Kruk, J.

2010-12-01

Electrical resistivity tomography (ERT) is commonly used in hydrologic investigations. Advances in joint and coupled hydrogeophysical inversion have enhanced the quantitative use of ERT to construct and condition hydrologic models (i.e. identify hydrologic structure and estimate hydrologic parameters). However the selection of which electrical resistivity data to collect and use is often determined by a combination of data requirements for geophysical analysis, intuition on the part of the hydrogeophysicist and logistical constraints of the laboratory or field site. One of the advantages of coupled hydrogeophysical inversion is the direct link between the hydrologic model and the individual geophysical data used to condition the model. That is, there is no requirement to collect geophysical data suitable for independent geophysical inversion. The geophysical measurements collected can be optimized for estimation of hydrologic model parameters rather than to develop a geophysical model. Using a synthetic model of drip irrigation we evaluate the value of individual resistivity measurements to describe the soil hydraulic properties and then use this information to build a data set optimized for characterizing hydrologic processes. We then compare the information content in the optimized data set with the information content in a data set optimized using a Jacobian sensitivity analysis.

Optimal design issues of a gas-to-liquid process

Energy Technology Data Exchange (ETDEWEB)

Rafiee, Ahmad

2012-07-01

Interests in Fischer-Tropsch (FT) synthesis is increasing rapidly due to the recent improvements of the technology, clean-burning fuels (low sulphur, low aromatics) derived from the FT process and the realization that the process can be used to monetize stranded natural gas resources. The economy of GTL plants depends very much on the natural gas price and there is a strong incentive to reduce the investment cost and in addition there is a need to improve energy efficiency and carbon efficiency. A model is constructed based on the available information in open literature. This model is used to simulate the GTL process with UNISIM DESIGN process simulator. In the FT reactor with cobalt based catalyst, Co2 is inert and will accumulate in the system. Five placements of Co2 removal unit in the GTL process are evaluated from an economical point of view. For each alternative, the process is optimized with respect to steam to carbon ratio, purge ratio of light ends, amount of tail gas recycled to syngas and FT units, reactor volume, and Co2 recovery. The results show that carbon and energy efficiencies and the annual net cash flow of the process with or without Co2 removal unit are not significantly different and there is not much to gain by removing Co2 from the process. It is optimal to recycle about 97 % of the light ends to the process (mainly to the FT unit) to obtain higher conversion of CO and H2 in the reactor. Different syngas configurations in a gas-to-liquid (GTL) plant are studied including auto-thermal reformer (ATR), combined reformer, and series arrangement of Gas Heated Reformer (GHR) and ATR. The Fischer-Tropsch (FT) reactor is based on cobalt catalyst and the degrees of freedom are; steam to carbon ratio, purge ratio of light ends, amount of tail gas recycled to synthesis gas (syngas) and Fischer-Tropsch (FT) synthesis units, and reactor volume. The production rate of liquid hydrocarbons is maximized for each syngas configuration. Installing a steam

Design strategy for optimal iterative learning control applied on a deep drawing process

DEFF Research Database (Denmark)

Endelt, Benny Ørtoft

2017-01-01

Metal forming processes in general can be characterised as repetitive processes; this work will take advantage of this characteristic by developing an algorithm or control system which transfers process information from part to part, reducing the impact of repetitive uncertainties, e.g. a gradual...... changes in the material properties. The process is highly non-linear and the system plant is modelled using a non-linear finite element and the gain factors for the iterative learning controller is identified solving a non-linear optimal control problem. The optimal control problem is formulated as a non...

Optimal channel utilization and service protection in cellular communication systems

DEFF Research Database (Denmark)

Iversen, Villy Bæk

1997-01-01

In mobile communications an efficient utilization of the channels is of great importance.In this paper we consider the basic principles for obtaining the maximum utilization, and we study strategies for obtaining these limits.In general a high degree of sharing is efficient, but requires service...... protection mechanisms for protecting services and subscriber groups.We study cellular systems with overlaid cells, and the effect of overlapping cells, and we show that by dynamic channel allocation we obtain a high utilization.The models are generalizations of the Erlang-B formula, and can be evaluated...

Variance-optimal hedging for processes with stationary independent increments

DEFF Research Database (Denmark)

Hubalek, Friedrich; Kallsen, J.; Krawczyk, L.

We determine the variance-optimal hedge when the logarithm of the underlying price follows a process with stationary independent increments in discrete or continuous time. Although the general solution to this problem is known as backward recursion or backward stochastic differential equation, we...

Optimization of Sunflower Oil Transesterification Process Using Sodium Methoxide

Directory of Open Access Journals (Sweden)

Sara KoohiKamali

2012-01-01

Full Text Available In this study, the methanolysis process of sunflower oil was investigated to get high methyl esters (biodiesel content using sodium methoxide. To reach to the best process conditions, central composite design (CCD through response surface methodology (RSM was employed. The optimal conditions predicted were the reaction time of 60 min, an excess stoichiometric amount of alcohol to oil ratio of 25%w/w and the catalyst content of 0.5%w/w, which lead to the highest methyl ester content (100%w/w. The methyl ester content of the mixture from gas chromatography analysis (GC was compared to that of optimum point. Results, confirmed that there was no significant difference between the fatty acid methyl ester content of sunflower oil produced under the optimized condition and the experimental value (P≥0.05. Furthermore, some fuel specifications of the resultant biodiesel were tested according to American standards for testing of materials (ASTM methods. The outcome showed that the methyl ester mixture produced from the optimized condition met nearly most of the important biodiesel specifications recommended in ASTM D 6751 requirements. Thus, the sunflower oil methyl esters resulted from this study could be a suitable alternative for petrol diesels.

Fundamental Theories and Key Technologies for Smart and Optimal Manufacturing in the Process Industry

Directory of Open Access Journals (Sweden)

Feng Qian

2017-04-01

Full Text Available Given the significant requirements for transforming and promoting the process industry, we present the major limitations of current petrochemical enterprises, including limitations in decision-making, production operation, efficiency and security, information integration, and so forth. To promote a vision of the process industry with efficient, green, and smart production, modern information technology should be utilized throughout the entire optimization process for production, management, and marketing. To focus on smart equipment in manufacturing processes, as well as on the adaptive intelligent optimization of the manufacturing process, operating mode, and supply chain management, we put forward several key scientific problems in engineering in a demand-driven and application-oriented manner, namely: ① intelligent sensing and integration of all process information, including production and management information; ② collaborative decision-making in the supply chain, industry chain, and value chain, driven by knowledge; ③ cooperative control and optimization of plant-wide production processes via human-cyber-physical interaction; and ④ life-cycle assessments for safety and environmental footprint monitoring, in addition to tracing analysis and risk control. In order to solve these limitations and core scientific problems, we further present fundamental theories and key technologies for smart and optimal manufacturing in the process industry. Although this paper discusses the process industry in China, the conclusions in this paper can be extended to the process industry around the world.

Geometric Process-Based Maintenance and Optimization Strategy for the Energy Storage Batteries

Directory of Open Access Journals (Sweden)

Yan Li

2016-01-01

Full Text Available Renewable energy is critical for improving energy structure and reducing environment pollution. But its strong fluctuation and randomness have a serious effect on the stability of the microgrid without the coordination of the energy storage batteries. The main factors that influence the development of the energy storage system are the lack of valid operation and maintenance management as well as the cost control. By analyzing the typical characteristics of the energy storage batteries in their life cycle, the geometric process-based model including the deteriorating system and the improving system is firstly built for describing the operation process, the preventive maintenance process, and the corrective maintenance process. In addition, this paper proposes an optimized management strategy, which aims to minimize the long-run average cost of the energy storage batteries by defining the time interval of the detection and preventive maintenance process as well as the optimal corrective maintenance times, subjected to the state of health and the reliability conditions. The simulation is taken under the built model by applying the proposed energy storage batteries’ optimized management strategy, which verifies the effectiveness and applicability of the management strategy, denoting its obvious practicality on the current application.

Optimization of the coherence function estimation for multi-core central processing unit

Science.gov (United States)

Cheremnov, A. G.; Faerman, V. A.; Avramchuk, V. S.

2017-02-01

The paper considers use of parallel processing on multi-core central processing unit for optimization of the coherence function evaluation arising in digital signal processing. Coherence function along with other methods of spectral analysis is commonly used for vibration diagnosis of rotating machinery and its particular nodes. An algorithm is given for the function evaluation for signals represented with digital samples. The algorithm is analyzed for its software implementation and computational problems. Optimization measures are described, including algorithmic, architecture and compiler optimization, their results are assessed for multi-core processors from different manufacturers. Thus, speeding-up of the parallel execution with respect to sequential execution was studied and results are presented for Intel Core i7-4720HQ и AMD FX-9590 processors. The results show comparatively high efficiency of the optimization measures taken. In particular, acceleration indicators and average CPU utilization have been significantly improved, showing high degree of parallelism of the constructed calculating functions. The developed software underwent state registration and will be used as a part of a software and hardware solution for rotating machinery fault diagnosis and pipeline leak location with acoustic correlation method.

Hierarchical random cellular neural networks for system-level brain-like signal processing.

Science.gov (United States)

Kozma, Robert; Puljic, Marko

2013-09-01

Sensory information processing and cognition in brains are modeled using dynamic systems theory. The brain's dynamic state is described by a trajectory evolving in a high-dimensional state space. We introduce a hierarchy of random cellular automata as the mathematical tools to describe the spatio-temporal dynamics of the cortex. The corresponding brain model is called neuropercolation which has distinct advantages compared to traditional models using differential equations, especially in describing spatio-temporal discontinuities in the form of phase transitions. Phase transitions demarcate singularities in brain operations at critical conditions, which are viewed as hallmarks of higher cognition and awareness experience. The introduced Monte-Carlo simulations obtained by parallel computing point to the importance of computer implementations using very large-scale integration (VLSI) and analog platforms. Copyright © 2013 Elsevier Ltd. All rights reserved.

Some applications and prospects of cellular automata in traffic problems

NARCIS (Netherlands)

Goldengorin, Boris; Makarenko, Alexander; Smelyanec, Natalia; Yacoubi, SE; Chopard, B; Bandini, S

2006-01-01

In this paper we deal with mathematical modeling of participants' movement based on cellular automata (CA). We describe some improvements of CA models of pedestrian motion taking into account the real geometrical constraints induced by a specific restricted space. Also some presumable optimization

Systems analysis as a tool for optimal process strategy

International Nuclear Information System (INIS)

Ditterich, K.; Schneider, J.

1975-09-01

For the description and the optimal treatment of complex processes, the methods of Systems Analysis are used as the most promising approach in recent times. In general every process should be optimised with respect to reliability, safety, economy and environmental pollution. In this paper the complex relations between these general optimisation postulates are established in qualitative form. These general trend relations have to be quantified for every particular system studied in practice

Rate-optimal Bayesian intensity smoothing for inhomogeneous Poisson processes

NARCIS (Netherlands)

Belitser, E.; Andrade Serra, De P.J.; Zanten, van J.H.

2013-01-01

We apply nonparametric Bayesian methods to study the problem of estimating the intensity function of an inhomogeneous Poisson process. We exhibit a prior on intensities which both leads to a computationally feasible method and enjoys desirable theoretical optimality properties. The prior we use is

Optimization of CNC end milling process parameters using PCA ...

African Journals Online (AJOL)

Optimization of CNC end milling process parameters using PCA-based Taguchi method. ... International Journal of Engineering, Science and Technology ... To meet the basic assumption of Taguchi method; in the present work, individual response correlations have been eliminated first by means of Principal Component ...

Towards Massive Machine Type Cellular Communications

OpenAIRE

Dawy, Zaher; Saad, Walid; Ghosh, Arunabha; Andrews, Jeffrey G.; Yaacoub, Elias

2015-01-01

Cellular networks have been engineered and optimized to carrying ever-increasing amounts of mobile data, but over the last few years, a new class of applications based on machine-centric communications has begun to emerge. Automated devices such as sensors, tracking devices, and meters - often referred to as machine-to-machine (M2M) or machine-type communications (MTC) - introduce an attractive revenue stream for mobile network operators, if a massive number of them can be efficiently support...

Combining On-Line Characterization Tools with Modern Software Environments for Optimal Operation of Polymerization Processes

Directory of Open Access Journals (Sweden)

Navid Ghadipasha

2016-02-01

Full Text Available This paper discusses the initial steps towards the formulation and implementation of a generic and flexible model centric framework for integrated simulation, estimation, optimization and feedback control of polymerization processes. For the first time it combines the powerful capabilities of the automatic continuous on-line monitoring of polymerization system (ACOMP, with a modern simulation, estimation and optimization software environment towards an integrated scheme for the optimal operation of polymeric processes. An initial validation of the framework was performed for modelling and optimization using literature data, illustrating the flexibility of the method to apply under different systems and conditions. Subsequently, off-line capabilities of the system were fully tested experimentally for model validations, parameter estimation and process optimization using ACOMP data. Experimental results are provided for free radical solution polymerization of methyl methacrylate.

Analytical study on the criticality of the stochastic optimal velocity model

International Nuclear Information System (INIS)

Kanai, Masahiro; Nishinari, Katsuhiro; Tokihiro, Tetsuji

2006-01-01

In recent works, we have proposed a stochastic cellular automaton model of traffic flow connecting two exactly solvable stochastic processes, i.e., the asymmetric simple exclusion process and the zero range process, with an additional parameter. It is also regarded as an extended version of the optimal velocity model, and moreover it shows particularly notable properties. In this paper, we report that when taking optimal velocity function to be a step function, all of the flux-density graph (i.e. the fundamental diagram) can be estimated. We first find that the fundamental diagram consists of two line segments resembling an inversed-λ form, and next identify their end-points from a microscopic behaviour of vehicles. It is notable that by using a microscopic parameter which indicates a driver's sensitivity to the traffic situation, we give an explicit formula for the critical point at which a traffic jam phase arises. We also compare these analytical results with those of the optimal velocity model, and point out the crucial differences between them

Constructal design of a blast furnace iron-making process based on multi-objective optimization

International Nuclear Information System (INIS)

Liu, Xiong; Chen, Lingen; Feng, Huijun; Qin, Xiaoyong; Sun, Fengrui

2016-01-01

For the fixed total raw material cost and based on constructal theory and finite time thermodynamics, a BFIM (blast furnace iron-making) process is optimized by taking a complex function as optimization objective. The complex function is integrated with HM (hot metal) yield and useful energy of the BF (blast furnace). The optimal cost distribution of raw materials (namely “generalized optimal construct”) is obtained. The effects of some parameters, such as oxygen enrichment, blast temperature and pulverized coal dosage, on the optimization results are analyzed. The results show that the HM yield, useful energy and complex function are, respectively, increased by 3.13%, 2.66% and 2.90% after generalized constructal optimization. The utilization efficiencies of the BFG (blast furnace gas) and slag are 41.3% and 57.1%, respectively, which means that the utilization potentials of the BFG and slag can be further exploited. Increasing pulverized coal dosage and decreasing the agglomerate ratio can increase the complex function. The performance the BFIM process can be improved by adjusting the oxygen enrichment, blast temperature, blast dosage, pressure ratio of the Brayton cycle's air compressor and relative pressure drop of the air compressor inlet to their optimal values, respectively, which are new findings of this paper. - Highlights: • Constructal optimization of a blast furnace iron-making process is performed. • Finite time thermodynamic model of open Brayton cycle is adopted. • Weighting function is taken as optimization objective. • Optimal cost distribution of the raw materials is obtained.

Cellular processing of gold nanoparticles: CE-ICP-MS evidence for the speciation changes in human cytosol.

Science.gov (United States)

Legat, Joanna; Matczuk, Magdalena; Timerbaev, Andrei R; Jarosz, Maciej

2018-01-01

The cellular uptake of gold nanoparticles (AuNPs) may (or may not) affect their speciation, but information on the chemical forms in which the particles exist in the cell remains obscure. An analytical method based on the use of capillary electrophoresis hyphenated with inductively coupled plasma mass spectrometry (ICP-MS) has been proposed to shed light on the intracellular processing of AuNPs. It was observed that when being introduced into normal cytosol, the conjugates of 10-50 nm AuNPs with albumin evolved in human serum stayed intact. On the contrary, under simulated cancer cytosol conditions, the nanoconjugates underwent decomposition, the rate of which and the resulting metal speciation patterns were strongly influenced by particle size. The new peaks that appeared in ICP-MS electropherograms could be ascribed to nanosized species, as upon ultracentrifugation, they quantitatively precipitated whereas the supernatant showed only trace Au signals. Our present study is the first step to unravel a mystery of the cellular chemistry for metal-based nanomedicines.

Optimal nonlinear information processing capacity in delay-based reservoir computers

Science.gov (United States)

Grigoryeva, Lyudmila; Henriques, Julie; Larger, Laurent; Ortega, Juan-Pablo

2015-09-01

Reservoir computing is a recently introduced brain-inspired machine learning paradigm capable of excellent performances in the processing of empirical data. We focus in a particular kind of time-delay based reservoir computers that have been physically implemented using optical and electronic systems and have shown unprecedented data processing rates. Reservoir computing is well-known for the ease of the associated training scheme but also for the problematic sensitivity of its performance to architecture parameters. This article addresses the reservoir design problem, which remains the biggest challenge in the applicability of this information processing scheme. More specifically, we use the information available regarding the optimal reservoir working regimes to construct a functional link between the reservoir parameters and its performance. This function is used to explore various properties of the device and to choose the optimal reservoir architecture, thus replacing the tedious and time consuming parameter scannings used so far in the literature.

Deciphering cellular morphology and biocompatibility using polymer microarrays

International Nuclear Information System (INIS)

Pernagallo, Salvatore; Unciti-Broceta, Asier; DIaz-Mochon, Juan Jose; Bradley, Mark

2008-01-01

A quantitative and qualitative analysis of cellular adhesion, morphology and viability is essential in understanding and designing biomaterials such as those involved in implant surfaces or as tissue-engineering scaffolds. As a means to simultaneously perform these studies in a high-throughput (HT) manner, we report a normalized protocol which allows the rapid analysis of a large number of potential cell binding substrates using polymer microarrays and high-content fluorescence microscopy. The method was successfully applied to the discovery of optimal polymer substrates from a 214-member polyurethane library with mouse fibroblast cells (L929), as well as simultaneous evaluation of cell viability and cellular morphology. Analysis demonstrated high biocompatibility of the binding polymers and permitted the identification of several different cellular morphologies, showing that specific polymer interactions may provoke changes in cell shape. In addition, SAR studies showed a clear correspondence between cellular adhesion and polymer structure. The approach can be utilized to perform multiple experiments (up to 1024 single experiments per slide) in a highly reproducible manner, leading to the generation of vast amounts of data in a short time period (48-72 h) while reducing dramatically the quantities of polymers, reagents and cells used

Design and optimization of sustainable process technologies

DEFF Research Database (Denmark)

Mussatto, Solange I.; Qin, Fen; Yamakawa, Celina Kiyomi

has been then considered a keypoint to achieve such purposes, being also able to result in potential environmental, economic, and social benefits. In this sense, the Biomass Conversion and Bioprocess TechnologyGroup (BCBT) has been working on the development of newstrategies for the use of biomass......, minimizing the costs and maximizing the efficiencyand productivity.Once the optimal conditions are identified, the process scale-up can be then evaluated. This could be translated in a faster time to market for newprocess technologies....

Tank waste remediation system optimized processing strategy with an altered treatment scheme

International Nuclear Information System (INIS)

Slaathaug, E.J.

1996-03-01

This report provides an alternative strategy evolved from the current Hanford Site Tank Waste Remediation System (TWRS) programmatic baseline for accomplishing the treatment and disposal of the Hanford Site tank wastes. This optimized processing strategy with an altered treatment scheme performs the major elements of the TWRS Program, but modifies the deployment of selected treatment technologies to reduce the program cost. The present program for development of waste retrieval, pretreatment, and vitrification technologies continues, but the optimized processing strategy reuses a single facility to accomplish the separations/low-activity waste (LAW) vitrification and the high-level waste (HLW) vitrification processes sequentially, thereby eliminating the need for a separate HLW vitrification facility

Identification of Optimal Policies in Markov Decision Processes

Czech Academy of Sciences Publication Activity Database

Sladký, Karel

46 2010, č. 3 (2010), s. 558-570 ISSN 0023-5954. [International Conference on Mathematical Methods in Economy and Industry. České Budějovice, 15.06.2009-18.06.2009] R&D Projects: GA ČR(CZ) GA402/08/0107; GA ČR GA402/07/1113 Institutional research plan: CEZ:AV0Z10750506 Keywords : finite state Markov decision processes * discounted and average costs * elimination of suboptimal policies Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.461, year: 2010 http://library.utia.cas.cz/separaty/2010/E/sladky-identification of optimal policies in markov decision processes.pdf

Die design and process optimization of plastic gear extrusion

Science.gov (United States)

Zhang, Lei; Fu, Zhihong; Yao, Chen; Zang, Gongzheng; Wan, Yue

2018-01-01

The flow velocity of the melt in the extruder was simulated by using software Polyflow, and the size of the die channel with the best flow uniformity was obtained. The die profile shape is obtained by reverse design. The length of the shaping section is determined by Ansys transient thermal analysis. According to the simulation results, the design and manufacture of extrusion die of plastic gear and vacuum cooling setting were obtained. The influence of the five process parameters on the precision of the plastic gear were studied by the single factor analysis method, such as the die temperature T, the screw speed R, the die spacing S, the vacuum degree M and the hauling speed V. The optimal combination of process parameters was obtained by using the neural network particle swarm optimization algorithm(T = 197.05 °C, R = 9.04rpm, S = 67mm, M = -0.0194MPa). The tooth profile deviation of the extruded plastic gear can reach 9 level of accuracy.

An Optimization Framework for Travel Pattern Interpretation of Cellular Data

Directory of Open Access Journals (Sweden)

Sarit Freund

2013-09-01

This paper explores methods for identifying travel patterns from cellular data. A primary challenge in this research is to provide an interpretation of the raw data that distinguishes between activity durations and travel durations. A novel framework is proposed for this purpose, based on a grading scheme for candidate interpretations of the raw data. A genetic algorithm is used to find interpretations with high grades, which are considered as the most reasonable ones. The proposed method is tested on a dataset of records covering 9454 cell-phone users over a period of one week. Preliminary evaluation of the resulting interpretations is presented.

Data Mining Process Optimization in Computational Multi-agent Systems

OpenAIRE

Kazík, O.; Neruda, R. (Roman)

2015-01-01

In this paper, we present an agent-based solution of metalearning problem which focuses on optimization of data mining processes. We exploit the framework of computational multi-agent systems in which various meta-learning problems have been already studied, e.g. parameter-space search or simple method recommendation. In this paper, we examine the effect of data preprocessing for machine learning problems. We perform the set of experiments in the search-space of data mining processes which is...

A high-throughput sample preparation method for cellular proteomics using 96-well filter plates.

Science.gov (United States)

Switzar, Linda; van Angeren, Jordy; Pinkse, Martijn; Kool, Jeroen; Niessen, Wilfried M A

2013-10-01

A high-throughput sample preparation protocol based on the use of 96-well molecular weight cutoff (MWCO) filter plates was developed for shotgun proteomics of cell lysates. All sample preparation steps, including cell lysis, buffer exchange, protein denaturation, reduction, alkylation and proteolytic digestion are performed in a 96-well plate format, making the platform extremely well suited for processing large numbers of samples and directly compatible with functional assays for cellular proteomics. In addition, the usage of a single plate for all sample preparation steps following cell lysis reduces potential samples losses and allows for automation. The MWCO filter also enables sample concentration, thereby increasing the overall sensitivity, and implementation of washing steps involving organic solvents, for example, to remove cell membranes constituents. The optimized protocol allowed for higher throughput with improved sensitivity in terms of the number of identified cellular proteins when compared to an established protocol employing gel-filtration columns. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

THE EFFECT OF CELLULAR PHONE USE ON DRIVING PERFORMANCE

OpenAIRE

Toshiro ISHIDA

2001-01-01

Many experiments using driving simulators or real roads have shown that using a cellular phone while driving may cause an accident because it delays visual information processing by the driver. In this research, we examined the influence on driving performance of cellular phone use on a course that simulated streets. Driving conditions were driving only, listening to the car radio, hands-free cellular phone use and using a cellular phone with the left hand. Driving performance measurements in...

Optimization of process parameters for a quasi-continuous tablet coating system using design of experiments.

Science.gov (United States)

Cahyadi, Christine; Heng, Paul Wan Sia; Chan, Lai Wah

2011-03-01

The aim of this study was to identify and optimize the critical process parameters of the newly developed Supercell quasi-continuous coater for optimal tablet coat quality. Design of experiments, aided by multivariate analysis techniques, was used to quantify the effects of various coating process conditions and their interactions on the quality of film-coated tablets. The process parameters varied included batch size, inlet temperature, atomizing pressure, plenum pressure, spray rate and coating level. An initial screening stage was carried out using a 2(6-1(IV)) fractional factorial design. Following these preliminary experiments, optimization study was carried out using the Box-Behnken design. Main response variables measured included drug-loading efficiency, coat thickness variation, and the extent of tablet damage. Apparent optimum conditions were determined by using response surface plots. The process parameters exerted various effects on the different response variables. Hence, trade-offs between individual optima were necessary to obtain the best compromised set of conditions. The adequacy of the optimized process conditions in meeting the combined goals for all responses was indicated by the composite desirability value. By using response surface methodology and optimization, coating conditions which produced coated tablets of high drug-loading efficiency, low incidences of tablet damage and low coat thickness variation were defined. Optimal conditions were found to vary over a large spectrum when different responses were considered. Changes in processing parameters across the design space did not result in drastic changes to coat quality, thereby demonstrating robustness in the Supercell coating process. © 2010 American Association of Pharmaceutical Scientists

Advanced landfill leachate treatment using iron-carbon microelectrolysis- Fenton process: Process optimization and column experiments

International Nuclear Information System (INIS)

Wang, Liqun; Yang, Qi; Wang, Dongbo; Li, Xiaoming; Zeng, Guangming; Li, Zhijun; Deng, Yongchao; Liu, Jun; Yi, Kaixin

2016-01-01

Highlights: • Fe-C microelectrolysis-Fenton process is proposed to pretreat landfill leachate. • Operating variables are optimized by response surface methodology (RSM). • 3D-EEMs and MW distribution explain the mechanism of enhanced biodegradability. • Fixed-bed column experiments are performed at different flow rates. - Abstract: A novel hydrogen peroxide-enhanced iron-carbon (Fe-C) microelectrolysis reactor was proposed for the pretreatment of mature landfill leachate. This reactor, combining microelectrolysis with Fenton process, revealed high treatment efficiency. The operating variables, including Fe-C dosage, H_2O_2 concentration and initial pH, were optimized by the response surface methodology (RSM), regarding the chemical oxygen demand (COD) removal efficiency and biochemical oxygen demand: chemical oxygen demand (BOD_5/COD) as the responses. The highest COD removal (74.59%) and BOD_5/COD (0.50) was obtained at optimal conditions of Fe-C dosage 55.72 g/L, H_2O_2 concentration 12.32 mL/L and initial pH 3.12. Three-dimensional excitation and emission matrix (3D-EEM) fluorescence spectroscopy and molecular weight (MW) distribution demonstrated that high molecular weight fractions such as refractory fulvic-like substances in leachate were effectively destroyed during the combined processes, which should be attributed to the combination oxidative effect of microelectrolysis and Fenton. The fixed-bed column experiments were performed and the breakthrough curves at different flow rates were evaluated to determine the practical applicability of the combined process. All these results show that the hydrogen peroxide-enhanced iron-carbon (Fe-C) microelectrolysis reactor is a promising and efficient technology for the treatment of mature landfill leachate.

Advanced landfill leachate treatment using iron-carbon microelectrolysis- Fenton process: Process optimization and column experiments

Energy Technology Data Exchange (ETDEWEB)

Wang, Liqun, E-mail: 691127317@qq.com [College of Environmental Science and Engineering, Hunan University, Changsha 410082 (China); Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082 (China); Yang, Qi, E-mail: yangqi@hnu.edu.cn [College of Environmental Science and Engineering, Hunan University, Changsha 410082 (China); Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082 (China); Wang, Dongbo [College of Environmental Science and Engineering, Hunan University, Changsha 410082 (China); Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082 (China); Li, Xiaoming, E-mail: xmli121x@hotmail.com [College of Environmental Science and Engineering, Hunan University, Changsha 410082 (China); Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082 (China); Zeng, Guangming; Li, Zhijun; Deng, Yongchao; Liu, Jun; Yi, Kaixin [College of Environmental Science and Engineering, Hunan University, Changsha 410082 (China); Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082 (China)

2016-11-15

Highlights: • Fe-C microelectrolysis-Fenton process is proposed to pretreat landfill leachate. • Operating variables are optimized by response surface methodology (RSM). • 3D-EEMs and MW distribution explain the mechanism of enhanced biodegradability. • Fixed-bed column experiments are performed at different flow rates. - Abstract: A novel hydrogen peroxide-enhanced iron-carbon (Fe-C) microelectrolysis reactor was proposed for the pretreatment of mature landfill leachate. This reactor, combining microelectrolysis with Fenton process, revealed high treatment efficiency. The operating variables, including Fe-C dosage, H{sub 2}O{sub 2} concentration and initial pH, were optimized by the response surface methodology (RSM), regarding the chemical oxygen demand (COD) removal efficiency and biochemical oxygen demand: chemical oxygen demand (BOD{sub 5}/COD) as the responses. The highest COD removal (74.59%) and BOD{sub 5}/COD (0.50) was obtained at optimal conditions of Fe-C dosage 55.72 g/L, H{sub 2}O{sub 2} concentration 12.32 mL/L and initial pH 3.12. Three-dimensional excitation and emission matrix (3D-EEM) fluorescence spectroscopy and molecular weight (MW) distribution demonstrated that high molecular weight fractions such as refractory fulvic-like substances in leachate were effectively destroyed during the combined processes, which should be attributed to the combination oxidative effect of microelectrolysis and Fenton. The fixed-bed column experiments were performed and the breakthrough curves at different flow rates were evaluated to determine the practical applicability of the combined process. All these results show that the hydrogen peroxide-enhanced iron-carbon (Fe-C) microelectrolysis reactor is a promising and efficient technology for the treatment of mature landfill leachate.

Optimization strategies based on sequential quadratic programming applied for a fermentation process for butanol production.

Science.gov (United States)

Pinto Mariano, Adriano; Bastos Borba Costa, Caliane; de Franceschi de Angelis, Dejanira; Maugeri Filho, Francisco; Pires Atala, Daniel Ibraim; Wolf Maciel, Maria Regina; Maciel Filho, Rubens

2009-11-01

In this work, the mathematical optimization of a continuous flash fermentation process for the production of biobutanol was studied. The process consists of three interconnected units, as follows: fermentor, cell-retention system (tangential microfiltration), and vacuum flash vessel (responsible for the continuous recovery of butanol from the broth). The objective of the optimization was to maximize butanol productivity for a desired substrate conversion. Two strategies were compared for the optimization of the process. In one of them, the process was represented by a deterministic model with kinetic parameters determined experimentally and, in the other, by a statistical model obtained using the factorial design technique combined with simulation. For both strategies, the problem was written as a nonlinear programming problem and was solved with the sequential quadratic programming technique. The results showed that despite the very similar solutions obtained with both strategies, the problems found with the strategy using the deterministic model, such as lack of convergence and high computational time, make the use of the optimization strategy with the statistical model, which showed to be robust and fast, more suitable for the flash fermentation process, being recommended for real-time applications coupling optimization and control.

Receptor Oligomerization as a Process Modulating Cellular Semiotics

DEFF Research Database (Denmark)

Giorgi, Franco; Bruni, Luis Emilio; Maggio, Roberto

2010-01-01

be another level of quality control that may help maintaining GPCRs rather stable throughout evolution. We propose here receptor oligomerization to be a basic molecular mechanism controlling GPCRs redundancy in many different cell types, and the plasma membrane as the first hierarchical cell structure...... at which selective categorical sensing may occur. Categorical sensing can be seen as the cellular capacity for identifying and ordering complex patterns of mixed signals out of a contextual matrix, i.e., the recognition of meaningful patterns out of ubiquitous signals. In this context, redundancy...

Optimization of process and solution parameters in electrospinning polyethylene oxide

CSIR Research Space (South Africa)

Jacobs, V

2011-11-01

Full Text Available This paper reports the optimization of electrospinning process and solution parameters using factorial design approach to obtain uniform polyethylene oxide (PEO) nanofibers. The parameters studied were distance between nozzle and collector screen...

Optimization of processing parameters of amaranth grits before grinding into flour

Science.gov (United States)

Zharkova, I. M.; Safonova, Yu A.; Slepokurova, Yu I.

2018-05-01

There are the results of experimental studies about the influence of infrared treatment (IR processing) parameters of the amaranth grits before their grinding into flour on the composition and properties of the received product. Using the method called as regressionfactor analysis, the optimal conditions of the thermal processing to the amaranth grits were obtained: the belt speed of the conveyor – 0.049 m/s; temperature of amaranth grits in the tempering silo – 65.4 °C the thickness of the layer of amaranth grits on the belt is 3 - 5 mm and the lamp power is 69.2 kW/m2. The conducted researches confirmed that thermal effect to the amaranth grains in the IR setting allows getting flour with a smaller size of starch grains, with the increased water-holding ability, and with a changed value of its glycemic index. Mathematical processing of experimental data allowed establishing the dependence of the structural and technological characteristics of the amaranth flour on the IR processing parameters of amaranth grits. The obtained results are quite consistent with the experimental ones that proves the effectiveness of optimization based on mathematical planning of the experiment to determine the influence of heat treatment optimal parameters of the amaranth grits on the functional and technological properties of the flour received from it.

Assessing the implications of cellular network performance on mobile content access

DEFF Research Database (Denmark)

Kaup, Fabian; Michelinakis, Foivos; Bui, Nicola

2016-01-01

Mobile applications such as VoIP, (live) gaming, or video streaming have diverse QoS requirements ranging from low delay to high throughput. The optimization of the network quality experienced by end-users requires detailed knowledge of the expected network performance. Also, the achieved service...... of cellular network measurements, focused on analyzing root causes of mobile network performance variability. Measurements conducted on a 4G cellular network in Germany show that management and configuration decisions have a substantial impact on the performance. Specifically, it is observed...

[Optimization of digital chest radiography image post-processing in diagnosis of pneumoconiosis].

Science.gov (United States)

Sheng, Bing-yong; Mao, Ling; Zhou, Shao-wei; Shi, Jin

2013-11-01

To establish the optimal image post-processing parameters for digital chest radiography as preliminary research for introducing digital radiography (DR) to pneumoconiosis diagnosis in China. A total of 204 pneumoconiosis patients and 31 dust-exposed workers were enrolled as the subjects in this research. Film-screen radiography (FSR) and DR images were taken for all subjects. DR films were printed after raw images were processed and parameters were altered using DR workstation (GE Healthcare, U.S.A.). Image gradations, lung textures, and the imaging of thoracic vertebra were evaluated by pneumoconiosis experts, and the optimal post-processing parameters were selected. Optical density was measured for both DR films and FSR films. For the DR machine used in this research, the contrast adjustment (CA) and brightness adjustment (BA) were the main parameters that determine the brightness and gray levels of images. The optimal ranges for CA and BA were 115%∼120% and 160%∼165%, respectively. The quality of DR chest films would be optimized when tissue contrast was adjusted to a maximum of 0.15, edge to a minimum of 1, and both noise reduction and tissue equalization to0.The failure rate of chest DR (0.4%) was significantly lower than that of chest FSR (17%) (P image post-processing on DR machine purchased from GE Healthcare, the DR chest films can meet all requirements for the quality of chest X-ray films in the Chinese diagnostic criteria for pneumoconiosis.

WE-DE-202-02: Are Track Structure Simulations Truly Needed for Radiobiology at the Cellular and Tissue Levels?

International Nuclear Information System (INIS)

Stewart, R.

2016-01-01

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological

WE-DE-202-02: Are Track Structure Simulations Truly Needed for Radiobiology at the Cellular and Tissue Levels?

Energy Technology Data Exchange (ETDEWEB)

Stewart, R. [University of Washington (United States)

2016-06-15

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological

1,4-Naphthoquinones: From Oxidative Damage to Cellular and Inter-Cellular Signaling

Directory of Open Access Journals (Sweden)

Lars-Oliver Klotz

2014-09-01

Full Text Available Naphthoquinones may cause oxidative stress in exposed cells and, therefore, affect redox signaling. Here, contributions of redox cycling and alkylating properties of quinones (both natural and synthetic, such as plumbagin, juglone, lawsone, menadione, methoxy-naphthoquinones, and others to cellular and inter-cellular signaling processes are discussed: (i naphthoquinone-induced Nrf2-dependent modulation of gene expression and its potentially beneficial outcome; (ii the modulation of receptor tyrosine kinases, such as the epidermal growth factor receptor by naphthoquinones, resulting in altered gap junctional intercellular communication. Generation of reactive oxygen species and modulation of redox signaling are properties of naphthoquinones that render them interesting leads for the development of novel compounds of potential use in various therapeutic settings.

Design optimization of single mixed refrigerant natural gas liquefaction process using the particle swarm paradigm with nonlinear constraints

International Nuclear Information System (INIS)

Khan, Mohd Shariq; Lee, Moonyong

2013-01-01

The particle swarm paradigm is employed to optimize single mixed refrigerant natural gas liquefaction process. Liquefaction design involves multivariable problem solving and non-optimal execution of these variables can waste energy and contribute to process irreversibilities. Design optimization requires these variables to be optimized simultaneously; minimizing the compression energy requirement is selected as the optimization objective. Liquefaction is modeled using Honeywell UniSim Design ™ and the resulting rigorous model is connected with the particle swarm paradigm coded in MATLAB. Design constraints are folded into the objective function using the penalty function method. Optimization successfully improved efficiency by reducing the compression energy requirement by ca. 10% compared with the base case. -- Highlights: ► The particle swarm paradigm (PSP) is employed for design optimization of SMR NG liquefaction process. ► Rigorous SMR process model based on UniSim is connected with PSP coded in MATLAB. ► Stochastic features of PSP give more confidence in the optimality of complex nonlinear problems. ► Optimization with PSP notably improves energy efficiency of the SMR process.

Integrated design and optimization of technologies for utilizing low grade heat in process industries

International Nuclear Information System (INIS)

Kwak, Dong-Hun; Binns, Michael; Kim, Jin-Kuk

2014-01-01

Highlights: • Implementation of a modeling and design framework for the utilization of low grade heat. • Application of process simulator and optimization techniques for the design of technologies for heat recovery. • Systematic and holistic exploitation for the recovery of industrial low grade heat. • Demonstration of the applicability and benefit of integrated design and optimization framework through a case study. - Abstract: The utilization of low grade heat in process industries has significant potential for improving site-wide energy efficiency. This paper focuses on the techno-economic analysis of key technologies for energy recovery and re-use, namely: Organic Rankine Cycles (ORC), boiler feed water heating, heat pumping and absorption refrigeration in the context of process integration. Process modeling and optimization in a holistic manner identifies the optimal integrated configuration of these technologies, with rigorous assessment of costs and technical feasibility of these technologies. For the systematic screening and evaluation of design options, detailed process simulator models are evaluated and optimization proceeds subject to design constraints for the particular economic scenarios where technology using low grade heat is introduced into the process site. Case studies are presented to illustrate how the proposed modeling and optimization framework can be useful and effective in practice, in terms of providing design guidelines and conceptual insights for the application of technologies using low grade heat. From the case study, the best options during winter are the ORC giving a 6.4% cost reduction for the ideal case with low grade heat available at a fixed temperature and boiler feed water heating giving a 2.5% cost reduction for the realistic case with low grade heat available at a range of temperatures. Similarly during summer boiler feed water heating was found to be the best option giving a 3.1% reduction of costs considering a

Development and optimization of a modified process for producing the battery grade LiOH: Optimization of energy and water consumption

International Nuclear Information System (INIS)

Grágeda, Mario; González, Alonso; Alavia, Wilson; Ushak, Svetlana

2015-01-01

LiOH·H 2 O is used for preparation of alkaline batteries. The required characteristics of this compound are low levels of impurities and a specific particle size distribution. LiOH·H 2 O is produced from ore and brines. In northern Chile, lithium is produced from brines. This region presents particular desert climate conditions where water and energy are scarce. To help solve this problem, the conventional production process for battery grade LiOH·H 2 O was simulated and a modified process was developed, with an efficient consumption of energy and water, to improve the environmental sustainability of the plant, and greater process yield and product purity. Different configurations of the equipments were studied and for the best configurations the behavior of the modified process at different scenarios were simulated. It was found that the purity is independent of concentration used in feed to thickeners. The process yield increases in average 2.4% for modified process due to recycling operation. In modified process is obtained 28% more product mass, specific energy consumption decreases up to 4.8% and losses of Li/kg of product decreased by 83% compared to conventional process. The water consumption per kg of product in modified process is 1%–6.3%, being lower than in conventional process. The results presented can be considered as guidelines to address the optimization of the industrial process for obtaining the battery grade LiOH. - Highlights: • Water and energy are important resources in any sustainable industrial process. • High purity LiOH·H 2 O is a material for producing of lithium batteries. • Conventional and modified optimized processes for LiOH·H 2 O production were simulated. • Energy and water consumptions decrease for the modified process. • Optimal operational conditions of H 2 O, feed, pressure and energy were established

Multi objective optimization model for minimizing production cost and environmental impact in CNC turning process

Science.gov (United States)

Widhiarso, Wahyu; Rosyidi, Cucuk Nur

2018-02-01

Minimizing production cost in a manufacturing company will increase the profit of the company. The cutting parameters will affect total processing time which then will affect the production cost of machining process. Besides affecting the production cost and processing time, the cutting parameters will also affect the environment. An optimization model is needed to determine the optimum cutting parameters. In this paper, we develop an optimization model to minimize the production cost and the environmental impact in CNC turning process. The model is used a multi objective optimization. Cutting speed and feed rate are served as the decision variables. Constraints considered are cutting speed, feed rate, cutting force, output power, and surface roughness. The environmental impact is converted from the environmental burden by using eco-indicator 99. Numerical example is given to show the implementation of the model and solved using OptQuest of Oracle Crystal Ball software. The results of optimization indicate that the model can be used to optimize the cutting parameters to minimize the production cost and the environmental impact.

Proportional fair scheduling with superposition coding in a cellular cooperative relay system

DEFF Research Database (Denmark)

Kaneko, Megumi; Hayashi, Kazunori; Popovski, Petar

2013-01-01

Many works have tackled on the problem of throughput and fairness optimization in cellular cooperative relaying systems. Considering firstly a two-user relay broadcast channel, we design a scheme based on superposition coding (SC) which maximizes the achievable sum-rate under a proportional...... fairness constraint. Unlike most relaying schemes where users are allocated orthogonally, our scheme serves the two users simultaneously on the same time-frequency resource unit by superposing their messages into three SC layers. The optimal power allocation parameters of each SC layer are derived...... by analysis. Next, we consider the general multi-user case in a cellular relay system, for which we design resource allocation algorithms based on proportional fair scheduling exploiting the proposed SC-based scheme. Numerical results show that the proposed algorithms allowing simultaneous user allocation...

NDDP multi-stage flash desalination process simulator design process optimization

International Nuclear Information System (INIS)

Sashi Kumar, G.N.; Mahendra, A.K.; Sanyal, A.; Gouthaman, G.

2009-03-01

The improvement of NDDP-MSF plant's performance ratio (PR) from design value of 9.0 to 13.1 was achieved by optimizing the plant's operating parameters within the feasible zone of operation. This plant has 20% excess heat transfer area over the design condition which helped us to get a PR of 15.1 after optimization. Thus we have obtained, (1) A 45% increase in the output over design value by the optimization carried out with design heat transfer area. (2) A 68% increase in the output over design value by the optimization carried out with increased heat transfer area. This report discusses the approach, methodology and results of the optimization study carried out. A simulator, MSFSIM which predicts the performance of a multi-stage flash (MSF) desalination plant has been coupled with Genetic Algorithm (GA) optimizer. Exhaustive optimization case studies have been conducted on this plant with an objective to increase the performance ratio (PR). The steady state optimization performed was based on obtaining the best stage wise pressure profile to enhance thermal efficiency which in-turn improves the performance ratio. Apart from this, the recirculating brine flow rate was also optimized. This optimization study enabled us to increase the PR of NDDP-MSF plant from design value of 9.0 to an optimized value 13.1. The actual plant is provided with 20% additional heat transfer area over and above the design heat transfer area. Optimization with this additional heat transfer area has taken the PR to 15.1. A desire to maintain equal flashing rates in all of the stages (a feature required for long life of the plant and to avoid cascading effect of non-flashing triggered by any stage) of the MSF plant has also been achieved. The deviation in the flashing rates within stages has been reduced. The startup characteristic of the plant (i.e the variation of stage pressure and the variation of recirculation flow rate with time), have been optimized with a target to minimize the

[Optimization of processing technology for semen cuscuta by uniform and regression analysis].

Science.gov (United States)

Li, Chun-yu; Luo, Hui-yu; Wang, Shu; Zhai, Ya-nan; Tian, Shu-hui; Zhang, Dan-shen

2011-02-01

To optimize the best preparation technology for the contains of total flavornoids, polysaccharides, the percentage of water and alcohol-soluble components in Semen Cuscuta herb processing. UV-spectrophotometry was applied to determine the contains of total flavornoids and polysaccharides, which were extracted from Semen Cuscuta. And the processing was optimized by the way of uniform design and contour map. The best preparation technology was satisfied with some conditions as follows: baking temperature 150 degrees C, baking time 140 seconds. The regression models are notable and reasonable, which can forecast results precisely.

Statistical optimization of process parameters for the production of ...

African Journals Online (AJOL)

In this study, optimization of process parameters such as moisture content, incubation temperature and initial pH (fixed) for the improvement of citric acid production from oil palm empty fruit bunches through solid state bioconversion was carried out using traditional one-factor-at-a-time (OFAT) method and response surface ...

Applications of genetic algorithms to optimization problems in the solvent extraction process for spent nuclear fuel

International Nuclear Information System (INIS)

Omori, Ryota, Sakakibara, Yasushi; Suzuki, Atsuyuki

1997-01-01

Applications of genetic algorithms (GAs) to optimization problems in the solvent extraction process for spent nuclear fuel are described. Genetic algorithms have been considered a promising tool for use in solving optimization problems in complicated and nonlinear systems because they require no derivatives of the objective function. In addition, they have the ability to treat a set of many possible solutions and consider multiple objectives simultaneously, so they can calculate many pareto optimal points on the trade-off curve between the competing objectives in a single iteration, which leads to small computing time. Genetic algorithms were applied to two optimization problems. First, process variables in the partitioning process were optimized using a weighted objective function. It was observed that the average fitness of a generation increased steadily as the generation proceeded and satisfactory solutions were obtained in all cases, which means that GAs are an appropriate method to obtain such an optimization. Secondly, GAs were applied to a multiobjective optimization problem in the co-decontamination process, and the trade-off curve between the loss of uranium and the solvent flow rate was successfully obtained. For both optimization problems, CPU time with the present method was estimated to be several tens of times smaller than with the random search method

Optimization of a micro-scale, high throughput process development tool and the demonstration of comparable process performance and product quality with biopharmaceutical manufacturing processes.

Science.gov (United States)

Evans, Steven T; Stewart, Kevin D; Afdahl, Chris; Patel, Rohan; Newell, Kelcy J

2017-07-14

In this paper, we discuss the optimization and implementation of a high throughput process development (HTPD) tool that utilizes commercially available micro-liter sized column technology for the purification of multiple clinically significant monoclonal antibodies. Chromatographic profiles generated using this optimized tool are shown to overlay with comparable profiles from the conventional bench-scale and clinical manufacturing scale. Further, all product quality attributes measured are comparable across scales for the mAb purifications. In addition to supporting chromatography process development efforts (e.g., optimization screening), comparable product quality results at all scales makes this tool is an appropriate scale model to enable purification and product quality comparisons of HTPD bioreactors conditions. The ability to perform up to 8 chromatography purifications in parallel with reduced material requirements per run creates opportunities for gathering more process knowledge in less time. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Light Weight Biomorphous Cellular Ceramics from Cellulose Templates

Science.gov (United States)

Singh, Mrityunjay; Yee, Bo-Moon; Gray, Hugh R. (Technical Monitor)

2003-01-01

Bimorphous ceramics are a new class of materials that can be fabricated from the cellulose templates derived from natural biopolymers. These biopolymers are abundantly available in nature and are produced by the photosynthesis process. The wood cellulose derived carbon templates have three- dimensional interconnectivity. A wide variety of non-oxide and oxide based ceramics have been fabricated by template conversion using infiltration and reaction-based processes. The cellular anatomy of the cellulose templates plays a key role in determining the processing parameters (pyrolysis, infiltration conditions, etc.) and resulting ceramic materials. The processing approach, microstructure, and mechanical properties of the biomorphous cellular ceramics (silicon carbide and oxide based) have been discussed.

Probabilistic cellular automata.

Science.gov (United States)

Agapie, Alexandru; Andreica, Anca; Giuclea, Marius

2014-09-01

Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involved to some degree in the transition rule, we speak of probabilistic automata, otherwise they are called deterministic. With either type of cellular automaton we are dealing with, the main theoretical challenge stays the same: starting from an arbitrary initial configuration, predict (with highest accuracy) the end configuration. If the automaton is deterministic, the outcome simplifies to one of two configurations, all zeros or all ones. If the automaton is probabilistic, the whole process is modeled by a finite homogeneous Markov chain, and the outcome is the corresponding stationary distribution. Based on our previous results for the asynchronous case-connecting the probability of a configuration in the stationary distribution to its number of zero-one borders-the article offers both numerical and theoretical insight into the long-term behavior of synchronous cellular automata.

Optimal Reinsurance-Investment Problem for an Insurer and a Reinsurer with Jump-Diffusion Process

Directory of Open Access Journals (Sweden)

Hanlei Hu

2018-01-01

Full Text Available The optimal reinsurance-investment strategies considering the interests of both the insurer and reinsurer are investigated. The surplus process is assumed to follow a jump-diffusion process and the insurer is permitted to purchase proportional reinsurance from the reinsurer. Applying dynamic programming approach and dual theory, the corresponding Hamilton-Jacobi-Bellman equations are derived and the optimal strategies for exponential utility function are obtained. In addition, several sensitivity analyses and numerical illustrations in the case with exponential claiming distributions are presented to analyze the effects of parameters about the optimal strategies.

Fuel consumption optimization for smart hybrid electric vehicle during a car-following process

Science.gov (United States)

Li, Liang; Wang, Xiangyu; Song, Jian

2017-03-01

Hybrid electric vehicles (HEVs) provide large potential to save energy and reduce emission, and smart vehicles bring out great convenience and safety for drivers. By combining these two technologies, vehicles may achieve excellent performances in terms of dynamic, economy, environmental friendliness, safety, and comfort. Hence, a smart hybrid electric vehicle (s-HEV) is selected as a platform in this paper to study a car-following process with optimizing the fuel consumption. The whole process is a multi-objective optimal problem, whose optimal solution is not just adding an energy management strategy (EMS) to an adaptive cruise control (ACC), but a deep fusion of these two methods. The problem has more restricted conditions, optimal objectives, and system states, which may result in larger computing burden. Therefore, a novel fuel consumption optimization algorithm based on model predictive control (MPC) is proposed and some search skills are adopted in receding horizon optimization to reduce computing burden. Simulations are carried out and the results indicate that the fuel consumption of proposed method is lower than that of the ACC+EMS method on the condition of ensuring car-following performances.

Magnetic manipulation device for the optimization of cell processing conditions.

Science.gov (United States)

Ito, Hiroshi; Kato, Ryuji; Ino, Kosuke; Honda, Hiroyuki

2010-02-01

Variability in human cell phenotypes make it's advancements in optimized cell processing necessary for personalized cell therapy. Here we propose a strategy of palm-top sized device to assist physically manipulating cells for optimizing cell preparations. For the design of such a device, we combined two conventional approaches: multi-well plate formatting and magnetic cell handling using magnetite cationic liposomes (MCLs). From our previous works, we showed the labeling applications of MCL on adhesive cells for various tissue engineering approaches. To feasibly transfer cells in multi-well plate, we here evaluated the magnetic response of MCL-labeled suspension type cells. The cell handling performance of Jurkat cells proved to be faster and more robust compared to MACS (Magnetic Cell Sorting) bead methods. To further confirm our strategy, prototype palm-top sized device "magnetic manipulation device (MMD)" was designed. In the device, the actual cell transportation efficacy of Jurkat cells was satisfying. Moreover, as a model of the most distributed clinical cell processing, primary peripheral blood mononuclear cells (PBMCs) from different volunteers were evaluated. By MMD, individual PBMCs indicated to have optimum Interleukin-2 (IL-2) concentrations for the expansion. Such huge differences of individual cells indicated that MMD, our proposing efficient and self-contained support tool, could assist the feasible and cost-effective optimization of cell processing in clinical facilities. Copyright (c) 2009 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Simulation based optimization on automated fibre placement process

Science.gov (United States)

Lei, Shi

2018-02-01

In this paper, a software simulation (Autodesk TruPlan & TruFiber) based method is proposed to optimize the automate fibre placement (AFP) process. Different types of manufacturability analysis are introduced to predict potential defects. Advanced fibre path generation algorithms are compared with respect to geometrically different parts. Major manufacturing data have been taken into consideration prior to the tool paths generation to achieve high success rate of manufacturing.

Molecular identification of potential denitrifying bacteria and use of D-optimal mixture experimental design for the optimization of denitrification process.

Science.gov (United States)

Ben Taheur, Fadia; Fdhila, Kais; Elabed, Hamouda; Bouguerra, Amel; Kouidhi, Bochra; Bakhrouf, Amina; Chaieb, Kamel

2016-04-01

Three bacterial strains (TE1, TD3 and FB2) were isolated from date palm (degla), pistachio and barley. The presence of nitrate reductase (narG) and nitrite reductase (nirS and nirK) genes in the selected strains was detected by PCR technique. Molecular identification based on 16S rDNA sequencing method was applied to identify positive strains. In addition, the D-optimal mixture experimental design was used to optimize the optimal formulation of probiotic bacteria for denitrification process. Strains harboring denitrification genes were identified as: TE1, Agrococcus sp LN828197; TD3, Cronobacter sakazakii LN828198 and FB2, Pedicoccus pentosaceus LN828199. PCR results revealed that all strains carried the nirS gene. However only C. sakazakii LN828198 and Agrococcus sp LN828197 harbored the nirK and the narG genes respectively. Moreover, the studied bacteria were able to form biofilm on abiotic surfaces with different degree. Process optimization showed that the most significant reduction of nitrate was 100% with 14.98% of COD consumption and 5.57 mg/l nitrite accumulation. Meanwhile, the response values were optimized and showed that the most optimal combination was 78.79% of C. sakazakii LN828198 (curve value), 21.21% of P. pentosaceus LN828199 (curve value) and absence (0%) of Agrococcus sp LN828197 (curve value). Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimization process for thin-walled high performance concrete sandwich panels

DEFF Research Database (Denmark)

Hodicky, Kamil; Hulin, Thomas; Schmidt, Jacob Wittrup

2014-01-01

with the specifications of the design constrains and variables. The tool integrates the processes of HPCSP design, quantity take-off and cost estimation into a single system that would provide different costs for different HPCSP designs. The proposed multi-objective optimisation scheme results into derivation of basic......A Nearly zero energy buildings are to become a requirement as part of the European energy policy. There are many ways of designing nearly zero energy buildings, but there is a lack of knowledge on optimization processes in the sense of structurally and thermally efficient design with an optimal...... economical solution. The present paper aims to provide multi-objective optimisation procedure addressed to structural precast thin-walled High Performance Concrete Sandwich Panels (HPCSP). The research aim is concerned with developing a tool that considers the cost of HPCSP materials along...

MO-B-BRB-00: Optimizing the Treatment Planning Process

International Nuclear Information System (INIS)

2015-01-01

The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequential events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d) semi

MO-B-BRB-00: Optimizing the Treatment Planning Process

Energy Technology Data Exchange (ETDEWEB)

NONE

2015-06-15

The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequential events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d) semi

Comparative analysis of cogeneration power plants optimization based on stochastic method using superstructure and process simulator

Energy Technology Data Exchange (ETDEWEB)

Araujo, Leonardo Rodrigues de [Instituto Federal do Espirito Santo, Vitoria, ES (Brazil)], E-mail: leoaraujo@ifes.edu.br; Donatelli, Joao Luiz Marcon [Universidade Federal do Espirito Santo (UFES), Vitoria, ES (Brazil)], E-mail: joaoluiz@npd.ufes.br; Silva, Edmar Alino da Cruz [Instituto Tecnologico de Aeronautica (ITA/CTA), Sao Jose dos Campos, SP (Brazil); Azevedo, Joao Luiz F. [Instituto de Aeronautica e Espaco (CTA/IAE/ALA), Sao Jose dos Campos, SP (Brazil)

2010-07-01

Thermal systems are essential in facilities such as thermoelectric plants, cogeneration plants, refrigeration systems and air conditioning, among others, in which much of the energy consumed by humanity is processed. In a world with finite natural sources of fuels and growing energy demand, issues related with thermal system design, such as cost estimative, design complexity, environmental protection and optimization are becoming increasingly important. Therefore the need to understand the mechanisms that degrade energy, improve energy sources use, reduce environmental impacts and also reduce project, operation and maintenance costs. In recent years, a consistent development of procedures and techniques for computational design of thermal systems has occurred. In this context, the fundamental objective of this study is a performance comparative analysis of structural and parametric optimization of a cogeneration system using stochastic methods: genetic algorithm and simulated annealing. This research work uses a superstructure, modelled in a process simulator, IPSEpro of SimTech, in which the appropriate design case studied options are included. Accordingly, the cogeneration system optimal configuration is determined as a consequence of the optimization process, restricted within the configuration options included in the superstructure. The optimization routines are written in MsExcel Visual Basic, in order to work perfectly coupled to the simulator process. At the end of the optimization process, the system optimal configuration, given the characteristics of each specific problem, should be defined. (author)

Application of Hybrid Genetic Algorithm Routine in Optimizing Food and Bioengineering Processes

Directory of Open Access Journals (Sweden)

Jaya Shankar Tumuluru

2016-11-01

Full Text Available Optimization is a crucial step in the analysis of experimental results. Deterministic methods only converge on local optimums and require exponentially more time as dimensionality increases. Stochastic algorithms are capable of efficiently searching the domain space; however convergence is not guaranteed. This article demonstrates the novelty of the hybrid genetic algorithm (HGA, which combines both stochastic and deterministic routines for improved optimization results. The new hybrid genetic algorithm developed is applied to the Ackley benchmark function as well as case studies in food, biofuel, and biotechnology processes. For each case study, the hybrid genetic algorithm found a better optimum candidate than reported by the sources. In the case of food processing, the hybrid genetic algorithm improved the anthocyanin yield by 6.44%. Optimization of bio-oil production using HGA resulted in a 5.06% higher yield. In the enzyme production process, HGA predicted a 0.39% higher xylanase yield. Hybridization of the genetic algorithm with a deterministic algorithm resulted in an improved optimum compared to statistical methods.

Optimization and application of spray-drying process on oyster cooking soup byproduct

Directory of Open Access Journals (Sweden)

Huibin CHEN

Full Text Available Abstract Oyster drying processes have produced a large amount of cooking soup byproducts. In this study, oyster cooking soup byproduct was concentrated and spray-dried after enzymatic hydrolysis to produce seasoning powder. Response surface methodology (RSM was performed on the basis of single-factor studies to optimize the feeding temperature, hot air temperature, atomization pressure, and total solid content of oyster drying. Results revealed the following optimized parameters of this process: feeding temperature of 60 °C, total solid content of 30%, hot air temperature of 197 °C, and atomization pressure of 92 MPa. Under these conditions, the oyster powder yield was 63.7% ± 0.7% and the moisture content was 4.1% ± 0.1%. Our pilot trial also obtained 63.1% yield and 4.0% moisture content. The enzyme hydrolysis of cooking soup byproduct further enhanced the antioxidant activity of the produced oyster seasoning powder to some extent. Spray drying process optimized by RSM can provide a reference for high-valued applications of oyster cooking soup byproducts.

Passive Noise Filtering by Cellular Compartmentalization.

Science.gov (United States)

Stoeger, Thomas; Battich, Nico; Pelkmans, Lucas

2016-03-10

Chemical reactions contain an inherent element of randomness, which presents itself as noise that interferes with cellular processes and communication. Here we discuss the ability of the spatial partitioning of molecular systems to filter and, thus, remove noise, while preserving regulated and predictable differences between single living cells. In contrast to active noise filtering by network motifs, cellular compartmentalization is highly effective and easily scales to numerous systems without requiring a substantial usage of cellular energy. We will use passive noise filtering by the eukaryotic cell nucleus as an example of how this increases predictability of transcriptional output, with possible implications for the evolution of complex multicellularity. Copyright © 2016 Elsevier Inc. All rights reserved.

Application of dragonfly algorithm for optimal performance analysis of process parameters in turn-mill operations- A case study

Science.gov (United States)

Vikram, K. Arun; Ratnam, Ch; Lakshmi, VVK; Kumar, A. Sunny; Ramakanth, RT

2018-02-01

Meta-heuristic multi-response optimization methods are widely in use to solve multi-objective problems to obtain Pareto optimal solutions during optimization. This work focuses on optimal multi-response evaluation of process parameters in generating responses like surface roughness (Ra), surface hardness (H) and tool vibration displacement amplitude (Vib) while performing operations like tangential and orthogonal turn-mill processes on A-axis Computer Numerical Control vertical milling center. Process parameters like tool speed, feed rate and depth of cut are considered as process parameters machined over brass material under dry condition with high speed steel end milling cutters using Taguchi design of experiments (DOE). Meta-heuristic like Dragonfly algorithm is used to optimize the multi-objectives like ‘Ra’, ‘H’ and ‘Vib’ to identify the optimal multi-response process parameters combination. Later, the results thus obtained from multi-objective dragonfly algorithm (MODA) are compared with another multi-response optimization technique Viz. Grey relational analysis (GRA).

Decomposition based parallel processing technique for efficient collaborative optimization

International Nuclear Information System (INIS)

Park, Hyung Wook; Kim, Sung Chan; Kim, Min Soo; Choi, Dong Hoon

2000-01-01

In practical design studies, most of designers solve multidisciplinary problems with complex design structure. These multidisciplinary problems have hundreds of analysis and thousands of variables. The sequence of process to solve these problems affects the speed of total design cycle. Thus it is very important for designer to reorder original design processes to minimize total cost and time. This is accomplished by decomposing large multidisciplinary problem into several MultiDisciplinary Analysis SubSystem (MDASS) and processing it in parallel. This paper proposes new strategy for parallel decomposition of multidisciplinary problem to raise design efficiency by using genetic algorithm and shows the relationship between decomposition and Multidisciplinary Design Optimization(MDO) methodology

Cellular scanning strategy for selective laser melting: Generating reliable, optimized scanning paths and processing parameters

DEFF Research Database (Denmark)

Mohanty, Sankhya; Hattel, Jesper Henri

2015-01-01

method based uncertainty and reliability analysis. The reliability of the scanning paths are established using cumulative probability distribution functions for process output criteria such as sample density, thermal homogeneity, etc. A customized genetic algorithm is used along with the simulation model...

An algorithm for gradient-based dynamic optimization of UV flash processes

DEFF Research Database (Denmark)

Ritschel, Tobias Kasper Skovborg; Capolei, Andrea; Gaspar, Jozsef

2017-01-01

This paper presents a novel single-shooting algorithm for gradient-based solution of optimal control problems with vapor-liquid equilibrium constraints. Such optimal control problems are important in several engineering applications, for instance in control of distillation columns, in certain two...... softwareaswellastheperformanceofdifferentcompilersinaLinuxoperatingsystem. Thesetestsindicatethatreal-timenonlinear model predictive control of UV flash processes is computationally feasible....

Optimization of the thermal conditions for processing hatchery waste eggs as meal for feed.

Science.gov (United States)

Chiu, W Z; Wei, H W

2011-05-01

The purpose of this study was to optimize the thermal conditions for processing hatchery waste eggs (HWE) into rich feedstuff with lower electricity consumption by using response surface methodology. In the study, the effects of processing temperature and time on HWE meal (HWEM) quality and production were evaluated. As the results indicate, optimization was obtained when the processing lasted for 23 h at the fixed temperature of 65°C, resulting in higher protein digestibility in vitro (89.6%) and DM (88.5%) content of HWEM with lower electricity consumption (82.4 kWh/60 kg of HWE). No significant differences existed between the quality values predicted by mathematical formulae and those obtained through practical analyses in DM (87 vs. 88.5%), CP (39.2 vs. 38.3%), protein digestibility in vitro (90.7 vs. 89.6%), and electricity consumed (80.8 vs. 82.4 kWh/60 kg of HWE). Furthermore, the product derived from the optimized processing conditions had better biosecurity; Salmonella spp. were not found and Escherichia coli levels were substantially reduced (from 10(7) to 10(4) cfu/g). In summary, HWEM of superior quality can be produced when the processing conditions optimized in the current research are utilized.

An analysis to optimize the process parameters of friction stir welded ...

African Journals Online (AJOL)

The friction stir welding (FSW) of steel is a challenging task. Experiments are conducted here, with a tool having a conical pin of 0.4mm clearance. The process parameters are optimized by using the Taguchi technique based on Taguchi's L9 orthogonal array. Experiments have been conducted based on three process ...

A new model for anaerobic processes of up-flow anaerobic sludge blanket reactors based on cellular automata

DEFF Research Database (Denmark)

Skiadas, Ioannis V.; Ahring, Birgitte Kiær

2002-01-01

characteristics and lead to different reactor behaviour. A dynamic mathematical model has been developed for the anaerobic digestion of a glucose based synthetic wastewater in UASB reactors. Cellular automata (CA) theory has been applied to simulate the granule development process. The model takes...... into consideration that granule diameter and granule microbial composition are functions of the reactor operational parameters and is capable of predicting the UASB performance and the layer structure of the granules....

Path searching in switching networks using cellular algorithm

Energy Technology Data Exchange (ETDEWEB)

Koczy, L T; Langer, J; Legendi, T

1981-01-01

After a survey of the important statements in the paper A Mathematical Model of Path Searching in General Type Switching Networks (see IBID., vol.25, no.1, p.31-43, 1981) the authors consider the possible implementation for cellular automata of the algorithm introduced there. The cellular field used consists of 5 neighbour 8 state cells. Running times required by a traditional serial processor and by the cellular field, respectively, are compared. By parallel processing this running time can be reduced. 5 references.

Optimization of Electrochemical Treatment Process Conditions for Distillery Effluent Using Response Surface Methodology

Directory of Open Access Journals (Sweden)

P. Arulmathi

2015-01-01

Full Text Available Distillery industry is recognized as one of the most polluting industries in India with a large amount of annual effluent production. In this present study, the optimization of electrochemical treatment process variables was reported to treat the color and COD of distillery spent wash using Ti/Pt as an anode in a batch mode. Process variables such as pH, current density, electrolysis time, and electrolyte dose were selected as operation variables and chemical oxygen demand (COD and color removal efficiency were considered as response variable for optimization using response surface methodology. Indirect electrochemical-oxidation process variables were optimized using Box-Behnken response surface design (BBD. The results showed that electrochemical treatment process effectively removed the COD (89.5% and color (95.1% of the distillery industry spent wash under the optimum conditions: pH of 4.12, current density of 25.02 mA/cm2, electrolysis time of 103.27 min, and electrolyte (NaCl concentration of 1.67 g/L, respectively.

Derived heuristics-based consistent optimization of material flow in a gold processing plant

Science.gov (United States)

Myburgh, Christie; Deb, Kalyanmoy

2018-01-01

Material flow in a chemical processing plant often follows complicated control laws and involves plant capacity constraints. Importantly, the process involves discrete scenarios which when modelled in a programming format involves if-then-else statements. Therefore, a formulation of an optimization problem of such processes becomes complicated with nonlinear and non-differentiable objective and constraint functions. In handling such problems using classical point-based approaches, users often have to resort to modifications and indirect ways of representing the problem to suit the restrictions associated with classical methods. In a particular gold processing plant optimization problem, these facts are demonstrated by showing results from MATLAB®'s well-known fmincon routine. Thereafter, a customized evolutionary optimization procedure which is capable of handling all complexities offered by the problem is developed. Although the evolutionary approach produced results with comparatively less variance over multiple runs, the performance has been enhanced by introducing derived heuristics associated with the problem. In this article, the development and usage of derived heuristics in a practical problem are presented and their importance in a quick convergence of the overall algorithm is demonstrated.

Switching and optimizing control for coal flotation process based on a hybrid model

Science.gov (United States)

Dong, Zhiyong; Wang, Ranfeng; Fan, Minqiang; Fu, Xiang

2017-01-01

Flotation is an important part of coal preparation, and the flotation column is widely applied as efficient flotation equipment. This process is complex and affected by many factors, with the froth depth and reagent dosage being two of the most important and frequently manipulated variables. This paper proposes a new method of switching and optimizing control for the coal flotation process. A hybrid model is built and evaluated using industrial data. First, wavelet analysis and principal component analysis (PCA) are applied for signal pre-processing. Second, a control model for optimizing the set point of the froth depth is constructed based on fuzzy control, and a control model is designed to optimize the reagent dosages based on expert system. Finally, the least squares-support vector machine (LS-SVM) is used to identify the operating conditions of the flotation process and to select one of the two models (froth depth or reagent dosage) for subsequent operation according to the condition parameters. The hybrid model is developed and evaluated on an industrial coal flotation column and exhibits satisfactory performance. PMID:29040305

Laser cutting: industrial relevance, process optimization, and laser safety

Science.gov (United States)

Haferkamp, Heinz; Goede, Martin; von Busse, Alexander; Thuerk, Oliver

1998-09-01

Compared to other technological relevant laser machining processes, up to now laser cutting is the application most frequently used. With respect to the large amount of possible fields of application and the variety of different materials that can be machined, this technology has reached a stable position within the world market of material processing. Reachable machining quality for laser beam cutting is influenced by various laser and process parameters. Process integrated quality techniques have to be applied to ensure high-quality products and a cost effective use of the laser manufacturing plant. Therefore, rugged and versatile online process monitoring techniques at an affordable price would be desirable. Methods for the characterization of single plant components (e.g. laser source and optical path) have to be substituted by an omnivalent control system, capable of process data acquisition and analysis as well as the automatic adaptation of machining and laser parameters to changes in process and ambient conditions. At the Laser Zentrum Hannover eV, locally highly resolved thermographic measurements of the temperature distribution within the processing zone using cost effective measuring devices are performed. Characteristic values for cutting quality and plunge control as well as for the optimization of the surface roughness at the cutting edges can be deducted from the spatial distribution of the temperature field and the measured temperature gradients. Main influencing parameters on the temperature characteristic within the cutting zone are the laser beam intensity and pulse duration in pulse operation mode. For continuous operation mode, the temperature distribution is mainly determined by the laser output power related to the cutting velocity. With higher cutting velocities temperatures at the cutting front increase, reaching their maximum at the optimum cutting velocity. Here absorption of the incident laser radiation is drastically increased due to

Energy Center Structure Optimization by using Smart Technologies in Process Control System

Science.gov (United States)

Shilkina, Svetlana V.

2018-03-01

The article deals with practical application of fuzzy logic methods in process control systems. A control object - agroindustrial greenhouse complex, which includes its own energy center - is considered. The paper analyzes object power supply options taking into account connection to external power grids and/or installation of own power generating equipment with various layouts. The main problem of a greenhouse facility basic process is extremely uneven power consumption, which forces to purchase redundant generating equipment idling most of the time, which quite negatively affects project profitability. Energy center structure optimization is largely based on solving the object process control system construction issue. To cut investor’s costs it was proposed to optimize power consumption by building an energy-saving production control system based on a fuzzy logic controller. The developed algorithm of automated process control system functioning ensured more even electric and thermal energy consumption, allowed to propose construction of the object energy center with a smaller number of units due to their more even utilization. As a result, it is shown how practical use of microclimate parameters fuzzy control system during object functioning leads to optimization of agroindustrial complex energy facility structure, which contributes to a significant reduction in object construction and operation costs.

Probabilistic safety assessment and optimal control of hazardous technological systems. A marked point process approach

International Nuclear Information System (INIS)

Holmberg, J.

1997-04-01

The thesis models risk management as an optimal control problem for a stochastic process. The approach classes the decisions made by management into three categories according to the control methods of a point process: (1) planned process lifetime, (2) modification of the design, and (3) operational decisions. The approach is used for optimization of plant shutdown criteria and surveillance test strategies of a hypothetical nuclear power plant

Next-Generation Environment-Aware Cellular Networks: Modern Green Techniques and Implementation Challenges

KAUST Repository

Ghazzai, Hakim

2016-09-16

Over the last decade, mobile communications have been witnessing a noteworthy increase of data traffic demand that is causing an enormous energy consumption in cellular networks. The reduction of their fossil fuel consumption in addition to the huge energy bills paid by mobile operators is considered as the most important challenges for the next-generation cellular networks. Although most of the proposed studies were focusing on individual physical layer power optimizations, there is a growing necessity to meet the green objective of fifth-generation cellular networks while respecting the user\\'s quality of service. This paper investigates four important techniques that could be exploited separately or together in order to enable wireless operators achieve significant economic benefits and environmental savings: 1) the base station sleeping strategy; 2) the optimized energy procurement from the smart grid; 3) the base station energy sharing; and 4) the green networking collaboration between competitive mobile operators. The presented simulation results measure the gain that could be obtained using these techniques compared with that of traditional scenarios. Finally, this paper discusses the issues and challenges related to the implementations of these techniques in real environments. © 2016 IEEE.

The Enterprise Derivative Application: Flexible Software for Optimizing Manufacturing Processes

Energy Technology Data Exchange (ETDEWEB)

Ward, Richard C [ORNL; Allgood, Glenn O [ORNL; Knox, John R [ORNL

2008-11-01

The Enterprise Derivative Application (EDA) implements the enterprise-derivative analysis for optimization of an industrial process (Allgood and Manges, 2001). It is a tool to help industry planners choose the most productive way of manufacturing their products while minimizing their cost. Developed in MS Access, the application allows users to input initial data ranging from raw material to variable costs and enables the tracking of specific information as material is passed from one process to another. Energy-derivative analysis is based on calculation of sensitivity parameters. For the specific application to a steel production process these include: the cost to product sensitivity, the product to energy sensitivity, the energy to efficiency sensitivity, and the efficiency to cost sensitivity. Using the EDA, for all processes the user can display a particular sensitivity or all sensitivities can be compared for all processes. Although energy-derivative analysis was originally designed for use by the steel industry, it is flexible enough to be applied to many other industrial processes. Examples of processes where energy-derivative analysis would prove useful are wireless monitoring of processes in the petroleum cracking industry and wireless monitoring of motor failure for determining the optimum time to replace motor parts. One advantage of the MS Access-based application is its flexibility in defining the process flow and establishing the relationships between parent and child process and products resulting from a process. Due to the general design of the program, a process can be anything that occurs over time with resulting output (products). So the application can be easily modified to many different industrial and organizational environments. Another advantage is the flexibility of defining sensitivity parameters. Sensitivities can be determined between all possible variables in the process flow as a function of time. Thus the dynamic development of the

Nested cellular automata

International Nuclear Information System (INIS)

Quasthoff, U.

1985-07-01

Cellular automata by definition consist of a finite or infinite number of cells, say of unit length, with each cell having the same transition function. These cells are usually considered as the smallest elements and so the space filled with these cells becomes discrete. Nevertheless, large pictures created by such cellular automata look very fractal. So we try to replace each cell by a couple of smaller cells, which have the same transition functions as the large ones. There are automata where this replacement does not destroy the macroscopic structure. In these cases this nesting process can be iterated. The paper contains large classes of automata with the above properties. In the case of one dimensional automata with two states and next neighbour interaction and a nesting function of the same type a complete classification is given. (author)

USHPRR FUEL FABRICATION PILLAR: FABRICATION STATUS, PROCESS OPTIMIZATIONS, AND FUTURE PLANS

Energy Technology Data Exchange (ETDEWEB)

Wight, Jared M.; Joshi, Vineet V.; Lavender, Curt A.

2018-03-12

The Fuel Fabrication (FF) Pillar, a project within the U.S. High Performance Research Reactor Conversion program of the National Nuclear Security Administration’s Office of Material Management and Minimization, is tasked with the scale-up and commercialization of high-density monolithic U-Mo fuel for the conversion of appropriate research reactors to use of low-enriched fuel. The FF Pillar has made significant steps to demonstrate and optimize the baseline co-rolling process using commercial-scale equipment at both the Y-12 National Security Complex (Y-12) and BWX Technologies (BWXT). These demonstrations include the fabrication of the next irradiation experiment, Mini-Plate 1 (MP-1), and casting optimizations at Y-12. The FF Pillar uses a detailed process flow diagram to identify potential gaps in processing knowledge or demonstration, which helps direct the strategic research agenda of the FF Pillar. This paper describes the significant progress made toward understanding the fuel characteristics, and models developed to make informed decisions, increase process yield, and decrease lifecycle waste and costs.

Optimal time points sampling in pathway modelling.

Science.gov (United States)

Hu, Shiyan

2004-01-01

Modelling cellular dynamics based on experimental data is at the heart of system biology. Considerable progress has been made to dynamic pathway modelling as well as the related parameter estimation. However, few of them gives consideration for the issue of optimal sampling time selection for parameter estimation. Time course experiments in molecular biology rarely produce large and accurate data sets and the experiments involved are usually time consuming and expensive. Therefore, to approximate parameters for models with only few available sampling data is of significant practical value. For signal transduction, the sampling intervals are usually not evenly distributed and are based on heuristics. In the paper, we investigate an approach to guide the process of selecting time points in an optimal way to minimize the variance of parameter estimates. In the method, we first formulate the problem to a nonlinear constrained optimization problem by maximum likelihood estimation. We then modify and apply a quantum-inspired evolutionary algorithm, which combines the advantages of both quantum computing and evolutionary computing, to solve the optimization problem. The new algorithm does not suffer from the morass of selecting good initial values and being stuck into local optimum as usually accompanied with the conventional numerical optimization techniques. The simulation results indicate the soundness of the new method.

The epidermis of grhl3-null mice displays altered lipid processing and cellular hyperproliferation.

Science.gov (United States)

Ting, Stephen B; Caddy, Jacinta; Wilanowski, Tomasz; Auden, Alana; Cunningham, John M; Elias, Peter M; Holleran, Walter M; Jane, Stephen M

2005-04-01

The presence of an impermeable surface barrier is an essential homeostatic mechanism in almost all living organisms. We have recently described a novel gene that is critical for the developmental instruction and repair of the integument in mammals. This gene, Grainy head-like 3 (Grhl3) is a member of a large family of transcription factors that are homologs of the Drosophila developmental gene grainy head (grh). Mice lacking Grhl3 fail to form an adequate skin barrier, and die at birth due to dehydration. These animals are also unable to repair the epidermis, exhibiting failed wound healing in both fetal and adult stages of development. These defects are due, in part, to diminished expression of a Grhl3 target gene, Transglutaminase 1 (TGase 1), which encodes a key enzyme involved in cross-linking of epidermal structural proteins and lipids into the cornified envelope (CE). Remarkably, the Drosophila grh gene plays an analogous role, regulating enzymes involved in the generation of quinones, which are essential for cross-linking structural components of the fly epidermis. In an extension of our initial analyses, we focus this report on additional defects observed in the Grhl3-null epidermis, namely defective extra-cellular lipid processing, altered lamellar lipid architecture and cellular hyperproliferation. These abnormalities suggest that Grhl3 plays diverse mechanistic roles in maintaining homeostasis in the skin.

Optimal processing pathway selection for microalgae-based biorefinery under uncertainty

DEFF Research Database (Denmark)

Rizwan, Muhammad; Zaman, Muhammad; Lee, Jay H.

2015-01-01

We propose a systematic framework for the selection of optimal processing pathways for a microalgaebased biorefinery under techno-economic uncertainty. The proposed framework promotes robust decision making by taking into account the uncertainties that arise due to inconsistencies among...... and shortage in the available technical information. A stochastic mixed integer nonlinear programming (sMINLP) problem is formulated for determining the optimal biorefinery configurations based on a superstructure model where parameter uncertainties are modeled and included as sampled scenarios. The solution...... the accounting of uncertainty are compared with respect to different objectives. (C) 2015 Elsevier Ltd. All rights reserved....

The use of real-time cell analyzer technology in drug discovery: defining optimal cell culture conditions and assay reproducibility with different adherent cellular models.

Science.gov (United States)

Atienzar, Franck A; Tilmant, Karen; Gerets, Helga H; Toussaint, Gaelle; Speeckaert, Sebastien; Hanon, Etienne; Depelchin, Olympe; Dhalluin, Stephane

2011-07-01

The use of impedance-based label-free technology applied to drug discovery is nowadays receiving more and more attention. Indeed, such a simple and noninvasive assay that interferes minimally with cell morphology and function allows one to perform kinetic measurements and to obtain information on proliferation, migration, cytotoxicity, and receptor-mediated signaling. The objective of the study was to further assess the usefulness of a real-time cell analyzer (RTCA) platform based on impedance in the context of quality control and data reproducibility. The data indicate that this technology is useful to determine the best coating and cellular density conditions for different adherent cellular models including hepatocytes, cardiomyocytes, fibroblasts, and hybrid neuroblastoma/neuronal cells. Based on 31 independent experiments, the reproducibility of cell index data generated from HepG2 cells exposed to DMSO and to Triton X-100 was satisfactory, with a coefficient of variation close to 10%. Cell index data were also well reproduced when cardiomyocytes and fibroblasts were exposed to 21 compounds three times (correlation >0.91, p technology appears to be a powerful and reliable tool in drug discovery because of the reasonable throughput, rapid and efficient performance, technical optimization, and cell quality control.

Design and Optimization of Sheet Hydroforming Process for Manufacturing Oil tank

International Nuclear Information System (INIS)

Prakash, C.; Narasimhan, K.

2005-01-01

The need for reduction of weight is an important issue in sheet metal forming industry. The hydroforming process has become an effective manufacturing process, as it can be adapted for the manufacturing of complex structural components with high structural stiffness. The process parameters and material properties are important factors that influence the quality of final product. In this paper, an optimized window of process parameters is obtained for successful sheet hydroforming of Oil tank. The simulation of hydroforming process is performed by using a Finite Element Method based Commercial code

Tube formation by complex cellular processes in Ciona intestinalis notochord.

Science.gov (United States)

Dong, Bo; Horie, Takeo; Denker, Elsa; Kusakabe, Takehiro; Tsuda, Motoyuki; Smith, William C; Jiang, Di

2009-06-15

In the course of embryogenesis multicellular structures and organs are assembled from constituent cells. One structural component common to many organs is the tube, which consists most simply of a luminal space surrounded by a single layer of epithelial cells. The notochord of ascidian Ciona forms a tube consisting of only 40 cells, and serves as a hydrostatic "skeleton" essential for swimming. While the early processes of convergent extension in ascidian notochord development have been extensively studied, the later phases of development, which include lumen formation, have not been well characterized. Here we used molecular markers and confocal imaging to describe tubulogenesis in the developing Ciona notochord. We found that during tubulogenesis each notochord cell established de novo apical domains, and underwent a mesenchymal-epithelial transition to become an unusual epithelial cell with two opposing apical domains. Concomitantly, extracellular luminal matrix was produced and deposited between notochord cells. Subsequently, each notochord cell simultaneously executed two types of crawling movements bi-directionally along the anterior/posterior axis on the inner surface of notochordal sheath. Lamellipodia-like protrusions resulted in cell lengthening along the anterior/posterior axis, while the retraction of trailing edges of the same cell led to the merging of the two apical domains. As a result, the notochord cells acquired endothelial-like shape and formed the wall of the central lumen. Inhibition of actin polymerization prevented the cell movement and tube formation. Ciona notochord tube formation utilized an assortment of common and fundamental cellular processes including cell shape change, apical membrane biogenesis, cell/cell adhesion remodeling, dynamic cell crawling, and lumen matrix secretion.