Modelling the Dynamics of Intracellular Processes as an Organisation of Multiple Agents

NARCIS (Netherlands)

Bosse, T.; Jonker, C.M.; Treur, J.; Armano, G.; Merelli, E.; Denzinger, J.; Martin, A.; Miles, S.; Tianfield, H.; Unland, R.

2005-01-01

This paper explores how the dynamics of complex biological processes can be modeled as an organisation of multiple agents. This modelling perspective identifies organisational structure occurring in complex decentralised processes and handles complexity of the analysis of the dynamics by structuring

Bayesian integration of position and orientation cues in perception of biological and non-biological dynamic forms

Directory of Open Access Journals (Sweden)

Steven Matthew Thurman

2014-02-01

Full Text Available Visual form analysis is fundamental to shape perception and likely plays a central role in perception of more complex dynamic shapes, such as moving objects or biological motion. Two primary form-based cues serve to represent the overall shape of an object: the spatial position and the orientation of locations along the boundary of the object. However, it is unclear how the visual system integrates these two sources of information in dynamic form analysis, and in particular how the brain resolves ambiguities due to sensory uncertainty and/or cue conflict. In the current study, we created animations of sparsely-sampled dynamic objects (human walkers or rotating squares comprised of oriented Gabor patches in which orientation could either coincide or conflict with information provided by position cues. When the cues were incongruent, we found a characteristic trade-off between position and orientation information whereby position cues increasingly dominated perception as the relative uncertainty of orientation increased and vice versa. Furthermore, we found no evidence for differences in the visual processing of biological and non-biological objects, casting doubt on the claim that biological motion may be specialized in the human brain, at least in specific terms of form analysis. To explain these behavioral results quantitatively, we adopt a probabilistic template-matching model that uses Bayesian inference within local modules to estimate object shape separately from either spatial position or orientation signals. The outputs of the two modules are integrated with weights that reflect individual estimates of subjective cue reliability, and integrated over time to produce a decision about the perceived dynamics of the input data. Results of this model provided a close fit to the behavioral data, suggesting a mechanism in the human visual system that approximates rational Bayesian inference to integrate position and orientation signals in dynamic

Dynamic models in research and management of biological invasions.

Science.gov (United States)

Buchadas, Ana; Vaz, Ana Sofia; Honrado, João P; Alagador, Diogo; Bastos, Rita; Cabral, João A; Santos, Mário; Vicente, Joana R

2017-07-01

Invasive species are increasing in number, extent and impact worldwide. Effective invasion management has thus become a core socio-ecological challenge. To tackle this challenge, integrating spatial-temporal dynamics of invasion processes with modelling approaches is a promising approach. The inclusion of dynamic processes in such modelling frameworks (i.e. dynamic or hybrid models, here defined as models that integrate both dynamic and static approaches) adds an explicit temporal dimension to the study and management of invasions, enabling the prediction of invasions and optimisation of multi-scale management and governance. However, the extent to which dynamic approaches have been used for that purpose is under-investigated. Based on a literature review, we examined the extent to which dynamic modelling has been used to address invasions worldwide. We then evaluated how the use of dynamic modelling has evolved through time in the scope of invasive species management. The results suggest that modelling, in particular dynamic modelling, has been increasingly applied to biological invasions, especially to support management decisions at local scales. Also, the combination of dynamic and static modelling approaches (hybrid models with a spatially explicit output) can be especially effective, not only to support management at early invasion stages (from prevention to early detection), but also to improve the monitoring of invasion processes and impact assessment. Further development and testing of such hybrid models may well be regarded as a priority for future research aiming to improve the management of invasions across scales. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantum Dynamics in Biological Systems

Science.gov (United States)

Shim, Sangwoo

In the first part of this dissertation, recent efforts to understand quantum mechanical effects in biological systems are discussed. Especially, long-lived quantum coherences observed during the electronic energy transfer process in the Fenna-Matthews-Olson complex at physiological condition are studied extensively using theories of open quantum systems. In addition to the usual master equation based approaches, the effect of the protein structure is investigated in atomistic detail through the combined application of quantum chemistry and molecular dynamics simulations. To evaluate the thermalized reduced density matrix, a path-integral Monte Carlo method with a novel importance sampling approach is developed for excitons coupled to an arbitrary phonon bath at a finite temperature. In the second part of the thesis, simulations of molecular systems and applications to vibrational spectra are discussed. First, the quantum dynamics of a molecule is simulated by combining semiclassical initial value representation and density funcitonal theory with analytic derivatives. A computationally-tractable approximation to the sum-of-states formalism of Raman spectra is subsequently discussed.

Towards the understanding of network information processing in biology

Science.gov (United States)

Singh, Vijay

Living organisms perform incredibly well in detecting a signal present in the environment. This information processing is achieved near optimally and quite reliably, even though the sources of signals are highly variable and complex. The work in the last few decades has given us a fair understanding of how individual signal processing units like neurons and cell receptors process signals, but the principles of collective information processing on biological networks are far from clear. Information processing in biological networks, like the brain, metabolic circuits, cellular-signaling circuits, etc., involves complex interactions among a large number of units (neurons, receptors). The combinatorially large number of states such a system can exist in makes it impossible to study these systems from the first principles, starting from the interactions between the basic units. The principles of collective information processing on such complex networks can be identified using coarse graining approaches. This could provide insights into the organization and function of complex biological networks. Here I study models of biological networks using continuum dynamics, renormalization, maximum likelihood estimation and information theory. Such coarse graining approaches identify features that are essential for certain processes performed by underlying biological networks. We find that long-range connections in the brain allow for global scale feature detection in a signal. These also suppress the noise and remove any gaps present in the signal. Hierarchical organization with long-range connections leads to large-scale connectivity at low synapse numbers. Time delays can be utilized to separate a mixture of signals with temporal scales. Our observations indicate that the rules in multivariate signal processing are quite different from traditional single unit signal processing.

100 years after Smoluchowski: stochastic processes in cell biology

International Nuclear Information System (INIS)

Holcman, D; Schuss, Z

2017-01-01

100 years after Smoluchowski introduced his approach to stochastic processes, they are now at the basis of mathematical and physical modeling in cellular biology: they are used for example to analyse and to extract features from a large number (tens of thousands) of single molecular trajectories or to study the diffusive motion of molecules, proteins or receptors. Stochastic modeling is a new step in large data analysis that serves extracting cell biology concepts. We review here Smoluchowski’s approach to stochastic processes and provide several applications for coarse-graining diffusion, studying polymer models for understanding nuclear organization and finally, we discuss the stochastic jump dynamics of telomeres across cell division and stochastic gene regulation. (topical review)

Surface-Assisted Dynamic Search Processes.

Science.gov (United States)

Shin, Jaeoh; Kolomeisky, Anatoly B

2018-03-01

Many chemical and biological systems exhibit intermittent search phenomena when participating particles alternate between dynamic regimes with different dimensionalities. Here we investigate theoretically a dynamic search process of finding a small target on a two-dimensional surface starting from a bulk solution, which is an example of such an intermittent search process. Both continuum and discrete-state stochastic descriptions are developed. It is found that depending on the scanning length λ, which describes the area visited by the reacting molecule during one search cycle, the system can exhibit three different search regimes: (i) For small λ values, the reactant finds the target mostly via three-dimensional bulk diffusion; (ii) for large λ values, the reactant molecule associates to the target mostly via surface diffusion; and (iii) for intermediate λ values, the reactant reaches the target via a combination of three-dimensional and two-dimensional search cycles. Our analysis also shows that the mean search times have different scalings as a function of the size of the surface segment depending on the nature of the dynamic search regime. Search dynamics are also sensitive to the position of the target for large scanning lengths. In addition, it is argued that the continuum description underestimates mean search times and does not always correctly describe the most optimal conditions for the surface-assisted dynamic processes. The importance of our findings for real natural systems is discussed.

Applying differential dynamic logic to reconfigurable biological networks.

Science.gov (United States)

Figueiredo, Daniel; Martins, Manuel A; Chaves, Madalena

2017-09-01

Qualitative and quantitative modeling frameworks are widely used for analysis of biological regulatory networks, the former giving a preliminary overview of the system's global dynamics and the latter providing more detailed solutions. Another approach is to model biological regulatory networks as hybrid systems, i.e., systems which can display both continuous and discrete dynamic behaviors. Actually, the development of synthetic biology has shown that this is a suitable way to think about biological systems, which can often be constructed as networks with discrete controllers, and present hybrid behaviors. In this paper we discuss this approach as a special case of the reconfigurability paradigm, well studied in Computer Science (CS). In CS there are well developed computational tools to reason about hybrid systems. We argue that it is worth applying such tools in a biological context. One interesting tool is differential dynamic logic (dL), which has recently been developed by Platzer and applied to many case-studies. In this paper we discuss some simple examples of biological regulatory networks to illustrate how dL can be used as an alternative, or also as a complement to methods already used. Copyright © 2017 Elsevier Inc. All rights reserved.

Understanding the biological underpinnings of ecohydrological processes

Science.gov (United States)

Huxman, T. E.; Scott, R. L.; Barron-Gafford, G. A.; Hamerlynck, E. P.; Jenerette, D.; Tissue, D. T.; Breshears, D. D.; Saleska, S. R.

2012-12-01

Climate change presents a challenge for predicting ecosystem response, as multiple factors drive both the physical and life processes happening on the land surface and their interactions result in a complex, evolving coupled system. For example, changes in surface temperature and precipitation influence near-surface hydrology through impacts on system energy balance, affecting a range of physical processes. These changes in the salient features of the environment affect biological processes and elicit responses along the hierarchy of life (biochemistry to community composition). Many of these structural or process changes can alter patterns of soil water-use and influence land surface characteristics that affect local climate. Of the many features that affect our ability to predict the future dynamics of ecosystems, it is this hierarchical response of life that creates substantial complexity. Advances in the ability to predict or understand aspects of demography help describe thresholds in coupled ecohydrological system. Disentangling the physical and biological features that underlie land surface dynamics following disturbance are allowing a better understanding of the partitioning of water in the time-course of recovery. Better predicting the timing of phenology and key seasonal events allow for a more accurate description of the full functional response of the land surface to climate. In addition, explicitly considering the hierarchical structural features of life are helping to describe complex time-dependent behavior in ecosystems. However, despite this progress, we have yet to build an ability to fully account for the generalization of the main features of living systems into models that can describe ecohydrological processes, especially acclimation, assembly and adaptation. This is unfortunate, given that many key ecosystem services are functions of these coupled co-evolutionary processes. To date, both the lack of controlled measurements and experimentation

Dynamical systems in population biology

CERN Document Server

Zhao, Xiao-Qiang

2017-01-01

This research monograph provides an introduction to the theory of nonautonomous semiflows with applications to population dynamics. It develops dynamical system approaches to various evolutionary equations such as difference, ordinary, functional, and partial differential equations, and pays more attention to periodic and almost periodic phenomena. The presentation includes persistence theory, monotone dynamics, periodic and almost periodic semiflows, basic reproduction ratios, traveling waves, and global analysis of prototypical population models in ecology and epidemiology. Research mathematicians working with nonlinear dynamics, particularly those interested in applications to biology, will find this book useful. It may also be used as a textbook or as supplementary reading for a graduate special topics course on the theory and applications of dynamical systems. Dr. Xiao-Qiang Zhao is a University Research Professor at Memorial University of Newfoundland, Canada. His main research interests involve applied...

Modeling dynamics of biological and chemical components of aquatic ecosystems

International Nuclear Information System (INIS)

Lassiter, R.R.

1975-05-01

To provide capability to model aquatic ecosystems or their subsystems as needed for particular research goals, a modeling strategy was developed. Submodels of several processes common to aquatic ecosystems were developed or adapted from previously existing ones. Included are submodels for photosynthesis as a function of light and depth, biological growth rates as a function of temperature, dynamic chemical equilibrium, feeding and growth, and various types of losses to biological populations. These submodels may be used as modules in the construction of models of subsystems or ecosystems. A preliminary model for the nitrogen cycle subsystem was developed using the modeling strategy and applicable submodels. (U.S.)

Green Algae as Model Organisms for Biological Fluid Dynamics

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Goldstein, Raymond E.

2015-01-01

In the past decade, the volvocine green algae, spanning from the unicellular Chlamydomonas to multicellular Volvox, have emerged as model organisms for a number of problems in biological fluid dynamics. These include flagellar propulsion, nutrient uptake by swimming organisms, hydrodynamic interactions mediated by walls, collective dynamics and transport within suspensions of microswimmers, the mechanism of phototaxis, and the stochastic dynamics of flagellar synchronization. Green algae are well suited to the study of such problems because of their range of sizes (from 10 μm to several millimeters), their geometric regularity, the ease with which they can be cultured, and the availability of many mutants that allow for connections between molecular details and organism-level behavior. This review summarizes these recent developments and highlights promising future directions in the study of biological fluid dynamics, especially in the context of evolutionary biology, that can take advantage of these remarkable organisms.

Dynamic optimization of distributed biological systems using robust and efficient numerical techniques.

Science.gov (United States)

Vilas, Carlos; Balsa-Canto, Eva; García, Maria-Sonia G; Banga, Julio R; Alonso, Antonio A

2012-07-02

Systems biology allows the analysis of biological systems behavior under different conditions through in silico experimentation. The possibility of perturbing biological systems in different manners calls for the design of perturbations to achieve particular goals. Examples would include, the design of a chemical stimulation to maximize the amplitude of a given cellular signal or to achieve a desired pattern in pattern formation systems, etc. Such design problems can be mathematically formulated as dynamic optimization problems which are particularly challenging when the system is described by partial differential equations.This work addresses the numerical solution of such dynamic optimization problems for spatially distributed biological systems. The usual nonlinear and large scale nature of the mathematical models related to this class of systems and the presence of constraints on the optimization problems, impose a number of difficulties, such as the presence of suboptimal solutions, which call for robust and efficient numerical techniques. Here, the use of a control vector parameterization approach combined with efficient and robust hybrid global optimization methods and a reduced order model methodology is proposed. The capabilities of this strategy are illustrated considering the solution of a two challenging problems: bacterial chemotaxis and the FitzHugh-Nagumo model. In the process of chemotaxis the objective was to efficiently compute the time-varying optimal concentration of chemotractant in one of the spatial boundaries in order to achieve predefined cell distribution profiles. Results are in agreement with those previously published in the literature. The FitzHugh-Nagumo problem is also efficiently solved and it illustrates very well how dynamic optimization may be used to force a system to evolve from an undesired to a desired pattern with a reduced number of actuators. The presented methodology can be used for the efficient dynamic optimization of

Dynamical processes in atomic and molecular physics

CERN Document Server

Ogurtsov, Gennadi

2012-01-01

Atomic and molecular physics underlie a basis for our knowledge of fundamental processes in nature and technology and in such applications as solid state physics, chemistry and biology. In recent years, atomic and molecular physics has undergone a revolutionary change due to great achievements in computing and experimental techniques. As a result, it has become possible to obtain information both on atomic and molecular characteristics and on dynamics of atomic and molecular processes. This e-book highlights the present state of investigations in the field of atomic and molecular physics. Rece

Application of Wavelet-Based Tools to Study the Dynamics of Biological Processes

DEFF Research Database (Denmark)

Pavlov, A. N.; Makarov, V. A.; Mosekilde, Erik

2006-01-01

The article makes use of three different examples (sensory information processing in the rat trigeminal complex, intracellular interaction in snail neurons and multimodal dynamics in nephron autoregulation) to demonstrate how modern approaches to time-series analysis based on the wavelet-transfor...

Activating and inhibiting connections in biological network dynamics

Directory of Open Access Journals (Sweden)

Knight Rob

2008-12-01

Full Text Available Abstract Background Many studies of biochemical networks have analyzed network topology. Such work has suggested that specific types of network wiring may increase network robustness and therefore confer a selective advantage. However, knowledge of network topology does not allow one to predict network dynamical behavior – for example, whether deleting a protein from a signaling network would maintain the network's dynamical behavior, or induce oscillations or chaos. Results Here we report that the balance between activating and inhibiting connections is important in determining whether network dynamics reach steady state or oscillate. We use a simple dynamical model of a network of interacting genes or proteins. Using the model, we study random networks, networks selected for robust dynamics, and examples of biological network topologies. The fraction of activating connections influences whether the network dynamics reach steady state or oscillate. Conclusion The activating fraction may predispose a network to oscillate or reach steady state, and neutral evolution or selection of this parameter may affect the behavior of biological networks. This principle may unify the dynamics of a wide range of cellular networks. Reviewers Reviewed by Sergei Maslov, Eugene Koonin, and Yu (Brandon Xia (nominated by Mark Gerstein. For the full reviews, please go to the Reviewers' comments section.

A MODELING AND SIMULATION LANGUAGE FOR BIOLOGICAL CELLS WITH COUPLED MECHANICAL AND CHEMICAL PROCESSES.

Science.gov (United States)

Somogyi, Endre; Glazier, James A

2017-04-01

Biological cells are the prototypical example of active matter. Cells sense and respond to mechanical, chemical and electrical environmental stimuli with a range of behaviors, including dynamic changes in morphology and mechanical properties, chemical uptake and secretion, cell differentiation, proliferation, death, and migration. Modeling and simulation of such dynamic phenomena poses a number of computational challenges. A modeling language describing cellular dynamics must naturally represent complex intra and extra-cellular spatial structures and coupled mechanical, chemical and electrical processes. Domain experts will find a modeling language most useful when it is based on concepts, terms and principles native to the problem domain. A compiler must then be able to generate an executable model from this physically motivated description. Finally, an executable model must efficiently calculate the time evolution of such dynamic and inhomogeneous phenomena. We present a spatial hybrid systems modeling language, compiler and mesh-free Lagrangian based simulation engine which will enable domain experts to define models using natural, biologically motivated constructs and to simulate time evolution of coupled cellular, mechanical and chemical processes acting on a time varying number of cells and their environment.

Chemical and biological activity in open flows: A dynamical system approach

International Nuclear Information System (INIS)

Tel, Tamas; Moura, Alessandro de; Grebogi, Celso; Karolyi, Gyoergy

2005-01-01

Chemical and biological processes often take place in fluid flows. Many of them, like environmental or microfluidical ones, generate filamentary patterns which have a fractal structure, due to the presence of chaos in the underlying advection dynamics. In such cases, hydrodynamical stirring strongly couples to the reactivity of the advected species: the outcome of the reaction is then typically different from that of the same reaction taking place in a well-mixed environment. Here we review recent progress in this field, which became possible due to the application of methods taken from dynamical system theory. We place special emphasis on the derivation of effective rate equations which contain singular terms expressing the fact that the reaction takes place on a moving fractal catalyst, on the unstable foliation of the reaction free advection dynamics

Applications of dynamical systems in biology and medicine

CERN Document Server

Radunskaya, Ami

2015-01-01

This volume highlights problems from a range of biological and medical applications that can be interpreted as questions about system behavior or control.  Topics include drug resistance in cancer and malaria, biological fluid dynamics, auto-regulation in the kidney, anti-coagulation therapy, evolutionary diversification and photo-transduction.  Mathematical techniques used to describe and investigate these biological and medical problems include ordinary, partial and stochastic differentiation equations, hybrid discrete-continuous approaches, as well as 2 and 3D numerical simulation. .

Organization of excitable dynamics in hierarchical biological networks.

Directory of Open Access Journals (Sweden)

Mark Müller-Linow

Full Text Available This study investigates the contributions of network topology features to the dynamic behavior of hierarchically organized excitable networks. Representatives of different types of hierarchical networks as well as two biological neural networks are explored with a three-state model of node activation for systematically varying levels of random background network stimulation. The results demonstrate that two principal topological aspects of hierarchical networks, node centrality and network modularity, correlate with the network activity patterns at different levels of spontaneous network activation. The approach also shows that the dynamic behavior of the cerebral cortical systems network in the cat is dominated by the network's modular organization, while the activation behavior of the cellular neuronal network of Caenorhabditis elegans is strongly influenced by hub nodes. These findings indicate the interaction of multiple topological features and dynamic states in the function of complex biological networks.

Dynamic Open Inquiry Performances of High-School Biology Students

Science.gov (United States)

Zion, Michal; Sadeh, Irit

2010-01-01

In examining open inquiry projects among high-school biology students, we found dynamic inquiry performances expressed in two criteria: "changes occurring during inquiry" and "procedural understanding". Characterizing performances in a dynamic open inquiry project can shed light on both the procedural and epistemological…

Disease processes as hybrid dynamical systems

Directory of Open Access Journals (Sweden)

Pietro Liò

2012-08-01

Full Text Available We investigate the use of hybrid techniques in complex processes of infectious diseases. Since predictive disease models in biomedicine require a multiscale approach for understanding the molecule-cell-tissue-organ-body interactions, heterogeneous methodologies are often employed for describing the different biological scales. Hybrid models provide effective means for complex disease modelling where the action and dosage of a drug or a therapy could be meaningfully investigated: the infection dynamics can be classically described in a continuous fashion, while the scheduling of multiple treatment discretely. We define an algebraic language for specifying general disease processes and multiple treatments, from which a semantics in terms of hybrid dynamical system can be derived. Then, the application of control-theoretic tools is proposed in order to compute the optimal scheduling of multiple therapies. The potentialities of our approach are shown in the case study of the SIR epidemic model and we discuss its applicability on osteomyelitis, a bacterial infection affecting the bone remodelling system in a specific and multiscale manner. We report that formal languages are helpful in giving a general homogeneous formulation for the different scales involved in a multiscale disease process; and that the combination of hybrid modelling and control theory provides solid grounds for computational medicine.

Disentangling physical and biological drivers of phytoplankton dynamics in a coastal system.

Science.gov (United States)

Cianelli, Daniela; D'Alelio, Domenico; Uttieri, Marco; Sarno, Diana; Zingone, Adriana; Zambianchi, Enrico; d'Alcalà, Maurizio Ribera

2017-11-20

This proof-of-concept study integrates the surface currents measured by high-frequency coastal radars with plankton time-series data collected at a fixed sampling point from the Mediterranean Sea (MareChiara Long Term Ecological Research site in the Gulf of Naples) to characterize the spatial origin of phytoplankton assemblages and to scrutinize the processes ruling their dynamics. The phytoplankton community generally originated from the coastal waters whereby species succession was mainly regulated by biological factors (life-cycle processes, species-specific physiological performances and inter-specific interactions). Physical factors, e.g. the alternation between coastal and offshore waters and the horizontal mixing, were also important drivers of phytoplankton dynamics promoting diversity maintenance by i) advecting species from offshore and ii) diluting the resident coastal community so as to dampen resource stripping by dominant species and thereby increase the numerical importance of rarer species. Our observations highlight the resilience of coastal communities, which may favour their persistence over time and the prevalence of successional events over small time and space scales. Although coastal systems may act differently from one another, our findings provide a conceptual framework to address physical-biological interactions occurring in coastal basins, which can be generalised to other areas.

Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation.

Science.gov (United States)

Villaverde, Alejandro F; Banga, Julio R

2017-11-01

The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. However, the original definition of dynamical compensation amounts to lack of structural identifiability. This is relevant if model parameters need to be estimated, as is often the case in biological modelling. Care should we taken when using an unidentifiable model to extract biological insight: the estimated values of structurally unidentifiable parameters are meaningless, and model predictions about unmeasured state variables can be wrong. Taking this into account, we explore alternative definitions of dynamical compensation that do not necessarily imply structural unidentifiability. Accordingly, we show different ways in which a model can be made identifiable while exhibiting dynamical compensation. Our analyses enable the use of the new concept of dynamical compensation in the context of parameter identification, and reconcile it with the desirable property of structural identifiability.

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)

Stochastic processes in cell biology

CERN Document Server

Bressloff, Paul C

2014-01-01

This book develops the theory of continuous and discrete stochastic processes within the context of cell biology.  A wide range of biological topics are covered including normal and anomalous diffusion in complex cellular environments, stochastic ion channels and excitable systems, stochastic calcium signaling, molecular motors, intracellular transport, signal transduction, bacterial chemotaxis, robustness in gene networks, genetic switches and oscillators, cell polarization, polymerization, cellular length control, and branching processes. The book also provides a pedagogical introduction to the theory of stochastic process – Fokker Planck equations, stochastic differential equations, master equations and jump Markov processes, diffusion approximations and the system size expansion, first passage time problems, stochastic hybrid systems, reaction-diffusion equations, exclusion processes, WKB methods, martingales and branching processes, stochastic calculus, and numerical methods.   This text is primarily...

Information-theoretic analysis of the dynamics of an executable biological model.

Directory of Open Access Journals (Sweden)

Avital Sadot

Full Text Available To facilitate analysis and understanding of biological systems, large-scale data are often integrated into models using a variety of mathematical and computational approaches. Such models describe the dynamics of the biological system and can be used to study the changes in the state of the system over time. For many model classes, such as discrete or continuous dynamical systems, there exist appropriate frameworks and tools for analyzing system dynamics. However, the heterogeneous information that encodes and bridges molecular and cellular dynamics, inherent to fine-grained molecular simulation models, presents significant challenges to the study of system dynamics. In this paper, we present an algorithmic information theory based approach for the analysis and interpretation of the dynamics of such executable models of biological systems. We apply a normalized compression distance (NCD analysis to the state representations of a model that simulates the immune decision making and immune cell behavior. We show that this analysis successfully captures the essential information in the dynamics of the system, which results from a variety of events including proliferation, differentiation, or perturbations such as gene knock-outs. We demonstrate that this approach can be used for the analysis of executable models, regardless of the modeling framework, and for making experimentally quantifiable predictions.

Hybrid Thermochemical/Biological Processing

Science.gov (United States)

Brown, Robert C.

The conventional view of biorefineries is that lignocellulosic plant material will be fractionated into cellulose, hemicellulose, lignin, and terpenes before these components are biochemically converted into market products. Occasionally, these plants include a thermochemical step at the end of the process to convert recalcitrant plant components or mixed waste streams into heat to meet thermal energy demands elsewhere in the facility. However, another possibility for converting high-fiber plant materials is to start by thermochemically processing it into a uniform intermediate product that can be biologically converted into a bio-based product. This alternative route to bio-based products is known as hybrid thermochemical/biological processing. There are two distinct approaches to hybrid processing: (a) gasification followed by fermentation of the resulting gaseous mixture of carbon monoxide (CO), hydrogen (H2), and carbon dioxide (CO2) and (b) fast pyrolysis followed by hydrolysis and/or fermentation of the anhydrosugars found in the resulting bio-oil. This article explores this "cart before the horse" approach to biorefineries.

Monitoring Biological Modes in a Bioreactor Process by Computer Simulation

Directory of Open Access Journals (Sweden)

Samia Semcheddine

2015-12-01

Full Text Available This paper deals with the general framework of fermentation system modeling and monitoring, focusing on the fermentation of Escherichia coli. Our main objective is to develop an algorithm for the online detection of acetate production during the culture of recombinant proteins. The analysis the fermentation process shows that it behaves like a hybrid dynamic system with commutation (since it can be represented by 5 nonlinear models. We present a strategy of fault detection based on residual generation for detecting the different actual biological modes. The residual generation is based on nonlinear analytical redundancy relations. The simulation results show that the several modes that are occulted during the bacteria cultivation can be detected by residuals using a nonlinear dynamic model and a reduced instrumentation.

Dynamically analyzing cell interactions in biological environments using multiagent social learning framework.

Science.gov (United States)

Zhang, Chengwei; Li, Xiaohong; Li, Shuxin; Feng, Zhiyong

2017-09-20

Biological environment is uncertain and its dynamic is similar to the multiagent environment, thus the research results of the multiagent system area can provide valuable insights to the understanding of biology and are of great significance for the study of biology. Learning in a multiagent environment is highly dynamic since the environment is not stationary anymore and each agent's behavior changes adaptively in response to other coexisting learners, and vice versa. The dynamics becomes more unpredictable when we move from fixed-agent interaction environments to multiagent social learning framework. Analytical understanding of the underlying dynamics is important and challenging. In this work, we present a social learning framework with homogeneous learners (e.g., Policy Hill Climbing (PHC) learners), and model the behavior of players in the social learning framework as a hybrid dynamical system. By analyzing the dynamical system, we obtain some conditions about convergence or non-convergence. We experimentally verify the predictive power of our model using a number of representative games. Experimental results confirm the theoretical analysis. Under multiagent social learning framework, we modeled the behavior of agent in biologic environment, and theoretically analyzed the dynamics of the model. We present some sufficient conditions about convergence or non-convergence and prove them theoretically. It can be used to predict the convergence of the system.

Quantum Information Biology: From Theory of Open Quantum Systems to Adaptive Dynamics

Science.gov (United States)

Asano, Masanari; Basieva, Irina; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro

This chapter reviews quantum(-like) information biology (QIB). Here biology is treated widely as even covering cognition and its derivatives: psychology and decision making, sociology, and behavioral economics and finances. QIB provides an integrative description of information processing by bio-systems at all scales of life: from proteins and cells to cognition, ecological and social systems. Mathematically QIB is based on the theory of adaptive quantum systems (which covers also open quantum systems). Ideologically QIB is based on the quantum-like (QL) paradigm: complex bio-systems process information in accordance with the laws of quantum information and probability. This paradigm is supported by plenty of statistical bio-data collected at all bio-scales. QIB re ects the two fundamental principles: a) adaptivity; and, b) openness (bio-systems are fundamentally open). In addition, quantum adaptive dynamics provides the most generally possible mathematical representation of these principles.

Breeding biology and the evolution of dynamic sexual dichromatism in frogs.

Science.gov (United States)

Bell, R C; Webster, G N; Whiting, M J

2017-12-01

Dynamic sexual dichromatism is a temporary colour change between the sexes and has evolved independently in a wide range of anurans, many of which are explosive breeders wherein males physically compete for access to females. Behavioural studies in a few species indicate that dynamic dichromatism functions as a visual signal in large breeding aggregations; however, the prevalence of this trait and the social and environmental factors underlying its expression are poorly understood. We compiled a database of 178 anurans with dynamic dichromatism that include representatives from 15 families and subfamilies. Dynamic dichromatism is common in two of the three subfamilies of hylid treefrogs. Phylogenetic comparative analyses of 355 hylid species (of which 95 display dynamic dichromatism) reveal high transition rates between dynamic dichromatism, ontogenetic (permanent) dichromatism and monochromatism reflecting the high evolutionary lability of this trait. Correlated evolution in hylids between dynamic dichromatism and forming large breeding aggregations indicates that the evolution of large breeding aggregations precedes the evolution of dynamic dichromatism. Multivariate phylogenetic logistic regression recovers the interaction between biogeographic distribution and forming breeding aggregations as a significant predictor of dynamic dichromatism in hylids. Accounting for macroecological differences between temperate and tropical regions, such as seasonality and the availability of breeding sites, may improve our understanding of ecological contexts in which dynamic dichromatism is likely to arise in tropical lineages and why it is retained in some temperate species and lost in others. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

AC Calorimetric Design for Dynamic of Biological Materials

OpenAIRE

Shigeo Imaizumi

2006-01-01

We developed a new AC calorimeter for the measurement of dynamic specific heat capacity in liquids, including aqueous suspensions of biological materials. This method has several advantages. The first is that a high-resolution measurement of heat capacity, inmillidegrees, can be performed as a function of temperature, even with a very small sample. Therefore, AC calorimeter is a powerful tool to study critical behavior a tphase transition in biological materials. The second advantage is that ...

Stochastic Simulation of Process Calculi for Biology

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Andrew Phillips

2010-10-01

Full Text Available Biological systems typically involve large numbers of components with complex, highly parallel interactions and intrinsic stochasticity. To model this complexity, numerous programming languages based on process calculi have been developed, many of which are expressive enough to generate unbounded numbers of molecular species and reactions. As a result of this expressiveness, such calculi cannot rely on standard reaction-based simulation methods, which require fixed numbers of species and reactions. Rather than implementing custom stochastic simulation algorithms for each process calculus, we propose to use a generic abstract machine that can be instantiated to a range of process calculi and a range of reaction-based simulation algorithms. The abstract machine functions as a just-in-time compiler, which dynamically updates the set of possible reactions and chooses the next reaction in an iterative cycle. In this short paper we give a brief summary of the generic abstract machine, and show how it can be instantiated with the stochastic simulation algorithm known as Gillespie's Direct Method. We also discuss the wider implications of such an abstract machine, and outline how it can be used to simulate multiple calculi simultaneously within a common framework.

The biology and dynamics of mammalian cortical granules

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Liu Min

2011-11-01

Full Text Available Abstract Cortical granules are membrane bound organelles located in the cortex of unfertilized oocytes. Following fertilization, cortical granules undergo exocytosis to release their contents into the perivitelline space. This secretory process, which is calcium dependent and SNARE protein-mediated pathway, is known as the cortical reaction. After exocytosis, the released cortical granule proteins are responsible for blocking polyspermy by modifying the oocytes' extracellular matrices, such as the zona pellucida in mammals. Mammalian cortical granules range in size from 0.2 um to 0.6 um in diameter and different from most other regulatory secretory organelles in that they are not renewed once released. These granules are only synthesized in female germ cells and transform an egg upon sperm entry; therefore, this unique cellular structure has inherent interest for our understanding of the biology of fertilization. Cortical granules are long thought to be static and awaiting in the cortex of unfertilized oocytes to be stimulated undergoing exocytosis upon gamete fusion. Not till recently, the dynamic nature of cortical granules is appreciated and understood. The latest studies of mammalian cortical granules document that this organelle is not only biochemically heterogeneous, but also displays complex distribution during oocyte development. Interestingly, some cortical granules undergo exocytosis prior to fertilization; and a number of granule components function beyond the time of fertilization in regulating embryonic cleavage and preimplantation development, demonstrating their functional significance in fertilization as well as early embryonic development. The following review will present studies that investigate the biology of cortical granules and will also discuss new findings that uncover the dynamic aspect of this organelle in mammals.

Modeling Dynamic Regulatory Processes in Stroke

Science.gov (United States)

McDermott, Jason E.; Jarman, Kenneth; Taylor, Ronald; Lancaster, Mary; Shankaran, Harish; Vartanian, Keri B.; Stevens, Susan L.; Stenzel-Poore, Mary P.; Sanfilippo, Antonio

2012-01-01

The ability to examine the behavior of biological systems in silico has the potential to greatly accelerate the pace of discovery in diseases, such as stroke, where in vivo analysis is time intensive and costly. In this paper we describe an approach for in silico examination of responses of the blood transcriptome to neuroprotective agents and subsequent stroke through the development of dynamic models of the regulatory processes observed in the experimental gene expression data. First, we identified functional gene clusters from these data. Next, we derived ordinary differential equations (ODEs) from the data relating these functional clusters to each other in terms of their regulatory influence on one another. Dynamic models were developed by coupling these ODEs into a model that simulates the expression of regulated functional clusters. By changing the magnitude of gene expression in the initial input state it was possible to assess the behavior of the networks through time under varying conditions since the dynamic model only requires an initial starting state, and does not require measurement of regulatory influences at each time point in order to make accurate predictions. We discuss the implications of our models on neuroprotection in stroke, explore the limitations of the approach, and report that an optimized dynamic model can provide accurate predictions of overall system behavior under several different neuroprotective paradigms. PMID:23071432

Graphics processing units in bioinformatics, computational biology and systems biology.

Science.gov (United States)

Nobile, Marco S; Cazzaniga, Paolo; Tangherloni, Andrea; Besozzi, Daniela

2017-09-01

Several studies in Bioinformatics, Computational Biology and Systems Biology rely on the definition of physico-chemical or mathematical models of biological systems at different scales and levels of complexity, ranging from the interaction of atoms in single molecules up to genome-wide interaction networks. Traditional computational methods and software tools developed in these research fields share a common trait: they can be computationally demanding on Central Processing Units (CPUs), therefore limiting their applicability in many circumstances. To overcome this issue, general-purpose Graphics Processing Units (GPUs) are gaining an increasing attention by the scientific community, as they can considerably reduce the running time required by standard CPU-based software, and allow more intensive investigations of biological systems. In this review, we present a collection of GPU tools recently developed to perform computational analyses in life science disciplines, emphasizing the advantages and the drawbacks in the use of these parallel architectures. The complete list of GPU-powered tools here reviewed is available at http://bit.ly/gputools. © The Author 2016. Published by Oxford University Press.

Towards a Population Dynamics Theory for Evolutionary Computing: Learning from Biological Population Dynamics in Nature

Science.gov (United States)

Ma, Zhanshan (Sam)

In evolutionary computing (EC), population size is one of the critical parameters that a researcher has to deal with. Hence, it was no surprise that the pioneers of EC, such as De Jong (1975) and Holland (1975), had already studied the population sizing from the very beginning of EC. What is perhaps surprising is that more than three decades later, we still largely depend on the experience or ad-hoc trial-and-error approach to set the population size. For example, in a recent monograph, Eiben and Smith (2003) indicated: "In almost all EC applications, the population size is constant and does not change during the evolutionary search." Despite enormous research on this issue in recent years, we still lack a well accepted theory for population sizing. In this paper, I propose to develop a population dynamics theory forEC with the inspiration from the population dynamics theory of biological populations in nature. Essentially, the EC population is considered as a dynamic system over time (generations) and space (search space or fitness landscape), similar to the spatial and temporal dynamics of biological populations in nature. With this conceptual mapping, I propose to 'transplant' the biological population dynamics theory to EC via three steps: (i) experimentally test the feasibility—whether or not emulating natural population dynamics improves the EC performance; (ii) comparatively study the underlying mechanisms—why there are improvements, primarily via statistical modeling analysis; (iii) conduct theoretical analysis with theoretical models such as percolation theory and extended evolutionary game theory that are generally applicable to both EC and natural populations. This article is a summary of a series of studies we have performed to achieve the general goal [27][30]-[32]. In the following, I start with an extremely brief introduction on the theory and models of natural population dynamics (Sections 1 & 2). In Sections 4 to 6, I briefly discuss three

Posttranslational modifications of desmin and their implication in biological processes and pathologies.

Science.gov (United States)

Winter, Daniel L; Paulin, Denise; Mericskay, Mathias; Li, Zhenlin

2014-01-01

Desmin, the muscle-specific intermediate filament, is involved in myofibrillar myopathies, dilated cardiomyopathy and muscle wasting. Desmin is the target of posttranslational modifications (PTMs) such as phosphorylation, ADP-ribosylation and ubiquitylation as well as nonenzymatic modifications such as glycation, oxidation and nitration. Several PTM target residues and their corresponding modifying enzymes have been discovered in human and nonhuman desmin. The major effect of phosphorylation and ADP-ribosylation is the disassembly of desmin filaments, while ubiquitylation of desmin leads to its degradation. The regulation of the desmin filament network by phosphorylation and ADP-ribosylation was found to be implicated in several major biological processes such as myogenesis, myoblast fusion, muscle contraction, muscle atrophy, cell division and possibly desmin interactions with its binding partners. Phosphorylation of desmin is also implicated in many forms of desmin-related myopathies (desminopathies). In this review, we summarize the findings on desmin PTMs and their implication in biological processes and pathologies, and discuss the current knowledge on the regulation of the desmin network by PTMs. We conclude that the desmin filament network can be seen as an intricate scaffold for muscle cell structure and biological processes and that its dynamics can be affected by PTMs. There are now precise tools to investigate PTMs and visualize cellular structures that have been underexploited in the study of desminopathies. Future studies should focus on these aspects.

Dynamic respiration index as a descriptor of the biological stability of organic wastes.

Science.gov (United States)

Adani, Fabrizio; Confalonieri, Roberto; Tambone, Fulvia

2004-01-01

Analytical methods applicable to different organic wastes are needed to establish the extent to which readily biodegradable organic matter has decomposed (i.e., biological stability). The objective of this study was to test a new respirometric method for biological stability determination of organic wastes. Dynamic respiration index (DRI) measurements were performed on 16 organic wastes of different origin, composition, and biological stability degree to validate the test method and result expression, and to propose biological stability limits. In addition, theoretical DRI trends were obtained by using a mathematical model. Each test lasted 96 h in a 148-L-capacity respirometer apparatus, and DRI was monitored every hour. The biological stability was expressed as both single and cumulative DRI values. Results obtained indicated that DRI described biological stability in relation to waste typology and age well, revealing lower-stability waste characterized by a well-pronounced DRI profile (a marked peak was evident) that became practically flat for samples with higher biological stability. Fitting indices showed good model prediction compared with the experimental data, indicating that the method was able to reproduce the aerobic process, providing a reliable indication of the biological stability. The DRI can therefore be proposed as a useful method to measure the biological stability of organic wastes, and DRI values, calculated as a mean of 24 h of the highest microbial activity, of 1000 and 500 mg O(2) kg(-1) volatile solids (VS) h(-1) are proposed to indicate medium (e.g., fresh compost) and high (e.g., mature compost) biological stabilities, respectively.

Biology-inspired AMO physics

Science.gov (United States)

Mathur, Deepak

2015-01-01

This Topical Review presents an overview of increasingly robust interconnects that are being established between atomic, molecular and optical (AMO) physics and the life sciences. AMO physics, outgrowing its historical role as a facilitator—a provider of optical methodologies, for instance—now seeks to partner biology in its quest to link systems-level descriptions of biological entities to insights based on molecular processes. Of course, perspectives differ when AMO physicists and biologists consider various processes. For instance, while AMO physicists link molecular properties and dynamics to potential energy surfaces, these have to give way to energy landscapes in considerations of protein dynamics. But there are similarities also: tunnelling and non-adiabatic transitions occur both in protein dynamics and in molecular dynamics. We bring to the fore some such differences and similarities; we consider imaging techniques based on AMO concepts, like 4D fluorescence microscopy which allows access to the dynamics of cellular processes, multiphoton microscopy which offers a built-in confocality, and microscopy with femtosecond laser beams to saturate the suppression of fluorescence in spatially controlled fashion so as to circumvent the diffraction limit. Beyond imaging, AMO physics contributes with optical traps that probe the mechanical and dynamical properties of single ‘live’ cells, highlighting differences between healthy and diseased cells. Trap methodologies have also begun to probe the dynamics governing of neural stem cells adhering to each other to form neurospheres and, with squeezed light to probe sub-diffusive motion of yeast cells. Strong field science contributes not only by providing a source of energetic electrons and γ-rays via laser-plasma accelerations schemes, but also via filamentation and supercontinuum generation, enabling mainstream collision physics into play in diverse processes like DNA damage induced by low-energy collisions to

Microbial phylogeny determines transcriptional response of resistome to dynamic composting processes

OpenAIRE

Wang, Cheng; Dong, Da; Strong, P. J.; Zhu, Weijing; Ma, Zhuang; Qin, Yong; Wu, Weixiang

2017-01-01

Background Animal manure is a reservoir of antibiotic resistance genes (ARGs) that pose a potential health risk globally, especially for resistance to the antibiotics commonly used in livestock production (such as tetracycline, sulfonamide, and fluoroquinolone). Currently, the effects of biological treatment (composting) on the transcriptional response of manure ARGs and their microbial hosts are not well characterized. Composting is a dynamic process that consists of four distinct phases tha...

Open Water Processes of the San Francisco Estuary: From Physical Forcing to Biological Responses

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Wim Kimmerer

2004-02-01

Full Text Available This paper reviews the current state of knowledge of the open waters of the San Francisco Estuary. This estuary is well known for the extent to which it has been altered through loss of wetlands, changes in hydrography, and the introduction of chemical and biological contaminants. It is also one of the most studied estuaries in the world, with much of the recent research effort aimed at supporting restoration efforts. In this review I emphasize the conceptual foundations for our current understanding of estuarine dynamics, particularly those aspects relevant to restoration. Several themes run throughout this paper. First is the critical role physical dynamics play in setting the stage for chemical and biological responses. Physical forcing by the tides and by variation in freshwater input combine to control the movement of the salinity field, and to establish stratification, mixing, and dilution patterns throughout the estuary. Many aspects of estuarine dynamics respond to interannual variation in freshwater flow; in particular, abundance of several estuarine-dependent species of fish and shrimp varies positively with flow, although the mechanisms behind these relationships are largely unknown. The second theme is the importance of time scales in determining the degree of interaction between dynamic processes. Physical effects tend to dominate when they operate at shorter time scales than biological processes; when the two time scales are similar, important interactions can arise between physical and biological variability. These interactions can be seen, for example, in the response of phytoplankton blooms, with characteristic time scales of days, to stratification events occurring during neap tides. The third theme is the key role of introduced species in all estuarine habitats; particularly noteworthy are introduced waterweeds and fishes in the tidal freshwater reaches of the estuary, and introduced clams there and in brackish water. The

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....

Magnetic Nanotweezers for Interrogating Biological Processes in Space and Time.

Science.gov (United States)

Kim, Ji-Wook; Jeong, Hee-Kyung; Southard, Kaden M; Jun, Young-Wook; Cheon, Jinwoo

2018-04-17

The ability to sense and manipulate the state of biological systems has been extensively advanced during the past decade with the help of recent developments in physical tools. Unlike standard genetic and pharmacological perturbation techniques-knockdown, overexpression, small molecule inhibition-that provide a basic on/off switching capability, these physical tools provide the capacity to control the spatial, temporal, and mechanical properties of the biological targets. Among the various physical cues, magnetism offers distinct advantages over light or electricity. Magnetic fields freely penetrate biological tissues and are already used for clinical applications. As one of the unique features, magnetic fields can be transformed into mechanical stimuli which can serve as a cue in regulating biological processes. However, their biological applications have been limited due to a lack of high-performance magnetism-to-mechanical force transducers with advanced spatiotemporal capabilities. In this Account, we present recent developments in magnetic nanotweezers (MNTs) as a useful tool for interrogating the spatiotemporal control of cells in living tissue. MNTs are composed of force-generating magnetic nanoparticles and field generators. Through proper design and the integration of individual components, MNTs deliver controlled mechanical stimulation to targeted biomolecules at any desired space and time. We first discuss about MNT configuration with different force-stimulation modes. By modulating geometry of the magnetic field generator, MNTs exert pulling, dipole-dipole attraction, and rotational forces to the target specifically and quantitatively. We discuss the key physical parameters determining force magnitude, which include magnetic field strength, magnetic field gradient, magnetic moment of the magnetic particle, as well as distance between the field generator and the particle. MNTs also can be used over a wide range of biological time scales. By simply

Dynamic neuronal ensembles: Issues in representing structure change in object-oriented, biologically-based brain models

Energy Technology Data Exchange (ETDEWEB)

Vahie, S.; Zeigler, B.P.; Cho, H. [Univ. of Arizona, Tucson, AZ (United States)

1996-12-31

This paper describes the structure of dynamic neuronal ensembles (DNEs). DNEs represent a new paradigm for learning, based on biological neural networks that use variable structures. We present a computational neural element that demonstrates biological neuron functionality such as neurotransmitter feedback absolute refractory period and multiple output potentials. More specifically, we will develop a network of neural elements that have the ability to dynamically strengthen, weaken, add and remove interconnections. We demonstrate that the DNE is capable of performing dynamic modifications to neuron connections and exhibiting biological neuron functionality. In addition to its applications for learning, DNEs provide an excellent environment for testing and analysis of biological neural systems. An example of habituation and hyper-sensitization in biological systems, using a neural circuit from a snail is presented and discussed. This paper provides an insight into the DNE paradigm using models developed and simulated in DEVS.

Automated force volume image processing for biological samples.

Directory of Open Access Journals (Sweden)

Pavel Polyakov

2011-04-01

Full Text Available Atomic force microscopy (AFM has now become a powerful technique for investigating on a molecular level, surface forces, nanomechanical properties of deformable particles, biomolecular interactions, kinetics, and dynamic processes. This paper specifically focuses on the analysis of AFM force curves collected on biological systems, in particular, bacteria. The goal is to provide fully automated tools to achieve theoretical interpretation of force curves on the basis of adequate, available physical models. In this respect, we propose two algorithms, one for the processing of approach force curves and another for the quantitative analysis of retraction force curves. In the former, electrostatic interactions prior to contact between AFM probe and bacterium are accounted for and mechanical interactions operating after contact are described in terms of Hertz-Hooke formalism. Retraction force curves are analyzed on the basis of the Freely Jointed Chain model. For both algorithms, the quantitative reconstruction of force curves is based on the robust detection of critical points (jumps, changes of slope or changes of curvature which mark the transitions between the various relevant interactions taking place between the AFM tip and the studied sample during approach and retraction. Once the key regions of separation distance and indentation are detected, the physical parameters describing the relevant interactions operating in these regions are extracted making use of regression procedure for fitting experiments to theory. The flexibility, accuracy and strength of the algorithms are illustrated with the processing of two force-volume images, which collect a large set of approach and retraction curves measured on a single biological surface. For each force-volume image, several maps are generated, representing the spatial distribution of the searched physical parameters as estimated for each pixel of the force-volume image.

Introductory Biology Textbooks Under-Represent Scientific Process

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Dara B. Duncan

2011-08-01

Full Text Available Attrition of undergraduates from Biology majors is a long-standing problem. Introductory courses that fail to engage students or spark their curiosity by emphasizing the open-ended and creative nature of biological investigation and discovery could contribute to student detachment from the field. Our hypothesis was that introductory biology books devote relatively few figures to illustration of the design and interpretation of experiments or field studies, thereby de-emphasizing the scientific process.To investigate this possibility, we examined figures in six Introductory Biology textbooks published in 2008. On average, multistep scientific investigations were presented in fewer than 5% of the hundreds of figures in each book. Devoting such a small percentage of figures to the processes by which discoveries are made discourages an emphasis on scientific thinking. We suggest that by increasing significantly the illustration of scientific investigations, textbooks could support undergraduates’ early interest in biology, stimulate the development of design and analytical skills, and inspire some students to participate in investigations of their own.

Decoding network dynamics in cancer

DEFF Research Database (Denmark)

Linding, Rune

2014-01-01

Biological systems are composed of highly dynamic and interconnected molecular networks that drive biological decision processes. The goal of network biology is to describe, quantify and predict the information flow and functional behaviour of living systems in a formal language and with an accur......Biological systems are composed of highly dynamic and interconnected molecular networks that drive biological decision processes. The goal of network biology is to describe, quantify and predict the information flow and functional behaviour of living systems in a formal language...... and with an accuracy that parallels our characterisation of other physical systems such as Jumbo-jets. Decades of targeted molecular and biological studies have led to numerous pathway models of developmental and disease related processes. However, so far no global models have been derived from pathways, capable...

Microbial phylogeny determines transcriptional response of resistome to dynamic composting processes.

Science.gov (United States)

Wang, Cheng; Dong, Da; Strong, P J; Zhu, Weijing; Ma, Zhuang; Qin, Yong; Wu, Weixiang

2017-08-16

Animal manure is a reservoir of antibiotic resistance genes (ARGs) that pose a potential health risk globally, especially for resistance to the antibiotics commonly used in livestock production (such as tetracycline, sulfonamide, and fluoroquinolone). Currently, the effects of biological treatment (composting) on the transcriptional response of manure ARGs and their microbial hosts are not well characterized. Composting is a dynamic process that consists of four distinct phases that are distinguished by the temperature resulting from microbial activity, namely the mesophilic, thermophilic, cooling, and maturing phases. In this study, changes of resistome expression were determined and related to active microbiome profiles during the dynamic composting process. This was achieved by integrating metagenomic and time series metatranscriptomic data for the evolving microbial community during composting. Composting noticeably reduced the aggregated expression level of the manure resistome, which primarily consisted of genes encoding for tetracycline, vancomycin, fluoroquinolone, beta-lactam, and aminoglycoside resistance, as well as efflux pumps. Furthermore, a varied transcriptional response of resistome to composting at the ARG levels was highlighted. The expression of tetracycline resistance genes (tetM-tetW-tetO-tetS) decreased during composting, where distinctive shifts in the four phases of composting were related to variations in antibiotic concentration. Composting had no effect on the expression of sulfonamide and fluoroquinolone resistance genes, which increased slightly during the thermophilic phase and then decreased to initial levels. As indigenous populations switched greatly throughout the dynamic composting, the core resistome persisted and their reservoir hosts' composition was significantly correlated with dynamic active microbial phylogenetic structure. Hosts for sulfonamide and fuoroquinolone resistance genes changed notably in phylognetic structure

Mathematical methods in biology and neurobiology

CERN Document Server

Jost, Jürgen

2014-01-01

Mathematical models can be used to meet many of the challenges and opportunities offered by modern biology. The description of biological phenomena requires a range of mathematical theories. This is the case particularly for the emerging field of systems biology. Mathematical Methods in Biology and Neurobiology introduces and develops these mathematical structures and methods in a systematic manner. It studies:   • discrete structures and graph theory • stochastic processes • dynamical systems and partial differential equations • optimization and the calculus of variations.   The biological applications range from molecular to evolutionary and ecological levels, for example:   • cellular reaction kinetics and gene regulation • biological pattern formation and chemotaxis • the biophysics and dynamics of neurons • the coding of information in neuronal systems • phylogenetic tree reconstruction • branching processes and population genetics • optimal resource allocation • sexual recombi...

Chaotic population dynamics and biology of the top-predator

International Nuclear Information System (INIS)

Rai, Vikas; Upadhyay, Ranjit Kumar

2004-01-01

We study how the dynamics of a food chain depends on the biology of the top-predator. We consider two model food chains with specialist and generalist top-predators. Both types of food chains display same type of chaotic behavior, short-term recurrent chaos; but the generating mechanisms are drastically different. Food chains with specialist top-predators are dictated by exogenous stochastic factors. On the contrary, the dynamics of those with the generalist top-predator is governed by deterministic changes in system parameters. The study also suggests that robust chaos would be a rarity

Quantum Biology

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Alessandro Sergi

2009-06-01

Full Text Available A critical assessment of the recent developmentsof molecular biology is presented.The thesis that they do not lead to a conceptualunderstanding of life and biological systems is defended.Maturana and Varela's concept of autopoiesis is briefly sketchedand its logical circularity avoided by postulatingthe existence of underlying living processes,entailing amplification from the microscopic to the macroscopic scale,with increasing complexity in the passage from one scale to the other.Following such a line of thought, the currently accepted model of condensed matter, which is based on electrostatics and short-ranged forces,is criticized. It is suggested that the correct interpretationof quantum dispersion forces (van der Waals, hydrogen bonding, and so onas quantum coherence effects hints at the necessity of includinglong-ranged forces (or mechanisms for them incondensed matter theories of biological processes.Some quantum effects in biology are reviewedand quantum mechanics is acknowledged as conceptually important to biology since withoutit most (if not all of the biological structuresand signalling processes would not even exist. Moreover, it is suggested that long-rangequantum coherent dynamics, including electron polarization,may be invoked to explain signal amplificationprocess in biological systems in general.

Profile of science process skills of Preservice Biology Teacher in General Biology Course

Science.gov (United States)

Susanti, R.; Anwar, Y.; Ermayanti

2018-04-01

This study aims to obtain portrayal images of science process skills among preservice biology teacher. This research took place in Sriwijaya University and involved 41 participants. To collect the data, this study used multiple choice test comprising 40 items to measure the mastery of science process skills. The data were then analyzed in descriptive manner. The results showed that communication aspect outperfomed the other skills with that 81%; while the lowest one was identifying variables and predicting (59%). In addition, basic science process skills was 72%; whereas for integrated skills was a bit lower, 67%. In general, the capability of doing science process skills varies among preservice biology teachers.

From point process observations to collective neural dynamics: Nonlinear Hawkes process GLMs, low-dimensional dynamics and coarse graining.

Science.gov (United States)

Truccolo, Wilson

2016-11-01

This review presents a perspective on capturing collective dynamics in recorded neuronal ensembles based on multivariate point process models, inference of low-dimensional dynamics and coarse graining of spatiotemporal measurements. A general probabilistic framework for continuous time point processes reviewed, with an emphasis on multivariate nonlinear Hawkes processes with exogenous inputs. A point process generalized linear model (PP-GLM) framework for the estimation of discrete time multivariate nonlinear Hawkes processes is described. The approach is illustrated with the modeling of collective dynamics in neocortical neuronal ensembles recorded in human and non-human primates, and prediction of single-neuron spiking. A complementary approach to capture collective dynamics based on low-dimensional dynamics ("order parameters") inferred via latent state-space models with point process observations is presented. The approach is illustrated by inferring and decoding low-dimensional dynamics in primate motor cortex during naturalistic reach and grasp movements. Finally, we briefly review hypothesis tests based on conditional inference and spatiotemporal coarse graining for assessing collective dynamics in recorded neuronal ensembles. Published by Elsevier Ltd.

Biology-inspired AMO physics

International Nuclear Information System (INIS)

Mathur, Deepak

2015-01-01

This Topical Review presents an overview of increasingly robust interconnects that are being established between atomic, molecular and optical (AMO) physics and the life sciences. AMO physics, outgrowing its historical role as a facilitator—a provider of optical methodologies, for instance—now seeks to partner biology in its quest to link systems-level descriptions of biological entities to insights based on molecular processes. Of course, perspectives differ when AMO physicists and biologists consider various processes. For instance, while AMO physicists link molecular properties and dynamics to potential energy surfaces, these have to give way to energy landscapes in considerations of protein dynamics. But there are similarities also: tunnelling and non-adiabatic transitions occur both in protein dynamics and in molecular dynamics. We bring to the fore some such differences and similarities; we consider imaging techniques based on AMO concepts, like 4D fluorescence microscopy which allows access to the dynamics of cellular processes, multiphoton microscopy which offers a built-in confocality, and microscopy with femtosecond laser beams to saturate the suppression of fluorescence in spatially controlled fashion so as to circumvent the diffraction limit. Beyond imaging, AMO physics contributes with optical traps that probe the mechanical and dynamical properties of single ‘live’ cells, highlighting differences between healthy and diseased cells. Trap methodologies have also begun to probe the dynamics governing of neural stem cells adhering to each other to form neurospheres and, with squeezed light to probe sub-diffusive motion of yeast cells. Strong field science contributes not only by providing a source of energetic electrons and γ-rays via laser-plasma accelerations schemes, but also via filamentation and supercontinuum generation, enabling mainstream collision physics into play in diverse processes like DNA damage induced by low-energy collisions to

Formal analysis of design process dynamics

NARCIS (Netherlands)

Bosse, T.; Jonker, C.M.; Treur, J.

2010-01-01

This paper presents a formal analysis of design process dynamics. Such a formal analysis is a prerequisite to come to a formal theory of design and for the development of automated support for the dynamics of design processes. The analysis was geared toward the identification of dynamic design

Formal Analysis of Design Process Dynamics

NARCIS (Netherlands)

Bosse, T.; Jonker, C.M.; Treur, J.

2010-01-01

This paper presents a formal analysis of design process dynamics. Such a formal analysis is a prerequisite to come to a formal theory of design and for the development of automated support for the dynamics of design processes. The analysis was geared toward the identification of dynamic design

Mass spectrometry in structural biology and biophysics architecture, dynamics, and interaction of biomolecules

CERN Document Server

Kaltashov, Igor A; Desiderio, Dominic M; Nibbering, Nico M

2012-01-01

The definitive guide to mass spectrometry techniques in biology and biophysics The use of mass spectrometry (MS) to study the architecture and dynamics of proteins is increasingly common within the biophysical community, and Mass Spectrometry in Structural Biology and Biophysics: Architecture, Dynamics, and Interaction of Biomolecules, Second Edition provides readers with detailed, systematic coverage of the current state of the art. Offering an unrivalled overview of modern MS-based armamentarium that can be used to solve the most challenging problems in biophysics, structural biol

The relative contributions of biological and abiotic processes to carbon dynamics in subarctic sea ice

DEFF Research Database (Denmark)

Søgaard, Dorte Haubjerg; Thomas, David; Rysgaard, Søren

2013-01-01

Knowledge on the relative effects of biological activity and precipitation/dissolution of calcium carbonate (CaCO3) in influencing the air-ice CO2 exchange in sea-ice-covered season is currently lacking. Furthermore, the spatial and temporal occurrence of CaCO3 and other biogeochemical parameters...... in sea ice are still not well described. Here we investigated autotrophic and heterotrophic activity as well as the precipitation/dissolution of CaCO3 in subarctic sea ice in South West Greenland. Integrated over the entire ice season (71 days), the sea ice was net autotrophic with a net carbon fixation...... and CaCO3 precipitation. The net biological production could only explain 4 % of this sea-ice-driven CO2 uptake. Abiotic processes contributed to an air-sea CO2 uptake of 1.5 mmol m(-2) sea ice day(-1), and dissolution of CaCO3 increased the air-sea CO2 uptake by 36 % compared to a theoretical estimate...

A review of biological processes within oceanic water columns relevant to the assessment of the safety of disposal of waste, notably radioactive isotopes on or within the sea bed

International Nuclear Information System (INIS)

Angel, M.V.

1985-01-01

Pelagic biological processes and their connotations in the assessment of possible dispersal mechanisms of contaminants released on the deep oceanic seabed are reviewed. Biological gradients tend to be from the surface down so the search is for processes which run counter to these general gradients. Observed profiles of standing crop of both plankton and micronekton show that below 2000 m biological activity would have to be exceptionally dynamic to have an influence that will even approach within an order of magnitude of the dispersive effect of physical mixing. Examination of all forms of known migration mechanisms fails to reveal such dynamic activity. Nor have any critical pathways been identified within the present or foreseeable pattern of exploitation of the oceans. However, a major gap in knowledge is whether the pattern of these biological processes changes substantially in the region of continental slopes. (author)

OFFl Models: Novel Schema for Dynamical Modeling of Biological Systems.

Directory of Open Access Journals (Sweden)

C Brandon Ogbunugafor

Full Text Available Flow diagrams are a common tool used to help build and interpret models of dynamical systems, often in biological contexts such as consumer-resource models and similar compartmental models. Typically, their usage is intuitive and informal. Here, we present a formalized version of flow diagrams as a kind of weighted directed graph which follow a strict grammar, which translate into a system of ordinary differential equations (ODEs by a single unambiguous rule, and which have an equivalent representation as a relational database. (We abbreviate this schema of "ODEs and formalized flow diagrams" as OFFL. Drawing a diagram within this strict grammar encourages a mental discipline on the part of the modeler in which all dynamical processes of a system are thought of as interactions between dynamical species that draw parcels from one or more source species and deposit them into target species according to a set of transformation rules. From these rules, the net rate of change for each species can be derived. The modeling schema can therefore be understood as both an epistemic and practical heuristic for modeling, serving both as an organizational framework for the model building process and as a mechanism for deriving ODEs. All steps of the schema beyond the initial scientific (intuitive, creative abstraction of natural observations into model variables are algorithmic and easily carried out by a computer, thus enabling the future development of a dedicated software implementation. Such tools would empower the modeler to consider significantly more complex models than practical limitations might have otherwise proscribed, since the modeling framework itself manages that complexity on the modeler's behalf. In this report, we describe the chief motivations for OFFL, carefully outline its implementation, and utilize a range of classic examples from ecology and epidemiology to showcase its features.

OFFl Models: Novel Schema for Dynamical Modeling of Biological Systems.

Science.gov (United States)

Ogbunugafor, C Brandon; Robinson, Sean P

2016-01-01

Flow diagrams are a common tool used to help build and interpret models of dynamical systems, often in biological contexts such as consumer-resource models and similar compartmental models. Typically, their usage is intuitive and informal. Here, we present a formalized version of flow diagrams as a kind of weighted directed graph which follow a strict grammar, which translate into a system of ordinary differential equations (ODEs) by a single unambiguous rule, and which have an equivalent representation as a relational database. (We abbreviate this schema of "ODEs and formalized flow diagrams" as OFFL.) Drawing a diagram within this strict grammar encourages a mental discipline on the part of the modeler in which all dynamical processes of a system are thought of as interactions between dynamical species that draw parcels from one or more source species and deposit them into target species according to a set of transformation rules. From these rules, the net rate of change for each species can be derived. The modeling schema can therefore be understood as both an epistemic and practical heuristic for modeling, serving both as an organizational framework for the model building process and as a mechanism for deriving ODEs. All steps of the schema beyond the initial scientific (intuitive, creative) abstraction of natural observations into model variables are algorithmic and easily carried out by a computer, thus enabling the future development of a dedicated software implementation. Such tools would empower the modeler to consider significantly more complex models than practical limitations might have otherwise proscribed, since the modeling framework itself manages that complexity on the modeler's behalf. In this report, we describe the chief motivations for OFFL, carefully outline its implementation, and utilize a range of classic examples from ecology and epidemiology to showcase its features.

Stochastic model of template-directed elongation processes in biology.

Science.gov (United States)

Schilstra, Maria J; Nehaniv, Chrystopher L

2010-10-01

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

Distorted wave calculations for electron loss process induced by bare ion impact on biological targets

International Nuclear Information System (INIS)

Monti, J.M.; Tachino, C.A.; Hanssen, J.; Fojón, O.A.; Galassi, M.E.; Champion, C.; Rivarola, R.D.

2014-01-01

Distorted wave models are employed to investigate the electron loss process induced by bare ions on biological targets. The two main reactions which contribute to this process, namely, the single electron ionization as well as the single electron capture are here studied. In order to further assess the validity of the theoretical descriptions used, the influence of particular mechanisms are studied, like dynamic screening for the case of electron ionization and energy deposition on the target by the impacting projectile for the electron capture one. Results are compared with existing experimental data. - Highlights: ► Distorted wave models are used to investigate ion-molecule collisions. ► Differential and total cross-sections for capture and ionization are evaluated. ► The influence of dynamic screening is determined. ► Capture reaction dominates the mean energy deposited by the projectile on the target

Parallel processing for fluid dynamics applications

International Nuclear Information System (INIS)

Johnson, G.M.

1989-01-01

The impact of parallel processing on computational science and, in particular, on computational fluid dynamics is growing rapidly. In this paper, particular emphasis is given to developments which have occurred within the past two years. Parallel processing is defined and the reasons for its importance in high-performance computing are reviewed. Parallel computer architectures are classified according to the number and power of their processing units, their memory, and the nature of their connection scheme. Architectures which show promise for fluid dynamics applications are emphasized. Fluid dynamics problems are examined for parallelism inherent at the physical level. CFD algorithms and their mappings onto parallel architectures are discussed. Several example are presented to document the performance of fluid dynamics applications on present-generation parallel processing devices

Dynamics of Intracellular Polymers in Enhanced Biological Phosphorus Removal Processes under Different Organic Carbon Concentrations

Directory of Open Access Journals (Sweden)

Lizhen Xing

2013-01-01

Full Text Available Enhanced biological phosphorus removal (EBPR may deteriorate or fail during low organic carbon loading periods. Polyphosphate accumulating organisms (PAOs in EBPR were acclimated under both high and low organic carbon conditions, and then dynamics of polymers in typical cycles, anaerobic conditions with excess organic carbons, and endogenous respiration conditions were examined. After long-term acclimation, it was found that organic loading rates did not affect the yield of PAOs and the applied low organic carbon concentrations were advantageous for the enrichment of PAOs. A low influent organic carbon concentration induced a high production of extracellular carbohydrate. During both anaerobic and aerobic endogenous respirations, when glycogen decreased to around 80 ± 10 mg C per gram of volatile suspended solids, PAOs began to utilize polyphosphate significantly. Regressed by the first-order reaction model, glycogen possessed the highest degradation rate and then was followed by polyphosphate, while biomass decay had the lowest degradation rate.

General method to find the attractors of discrete dynamic models of biological systems

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Gan, Xiao; Albert, Réka

2018-04-01

Analyzing the long-term behaviors (attractors) of dynamic models of biological networks can provide valuable insight. We propose a general method that can find the attractors of multilevel discrete dynamical systems by extending a method that finds the attractors of a Boolean network model. The previous method is based on finding stable motifs, subgraphs whose nodes' states can stabilize on their own. We extend the framework from binary states to any finite discrete levels by creating a virtual node for each level of a multilevel node, and describing each virtual node with a quasi-Boolean function. We then create an expanded representation of the multilevel network, find multilevel stable motifs and oscillating motifs, and identify attractors by successive network reduction. In this way, we find both fixed point attractors and complex attractors. We implemented an algorithm, which we test and validate on representative synthetic networks and on published multilevel models of biological networks. Despite its primary motivation to analyze biological networks, our motif-based method is general and can be applied to any finite discrete dynamical system.

General method to find the attractors of discrete dynamic models of biological systems.

Science.gov (United States)

Gan, Xiao; Albert, Réka

2018-04-01

Analyzing the long-term behaviors (attractors) of dynamic models of biological networks can provide valuable insight. We propose a general method that can find the attractors of multilevel discrete dynamical systems by extending a method that finds the attractors of a Boolean network model. The previous method is based on finding stable motifs, subgraphs whose nodes' states can stabilize on their own. We extend the framework from binary states to any finite discrete levels by creating a virtual node for each level of a multilevel node, and describing each virtual node with a quasi-Boolean function. We then create an expanded representation of the multilevel network, find multilevel stable motifs and oscillating motifs, and identify attractors by successive network reduction. In this way, we find both fixed point attractors and complex attractors. We implemented an algorithm, which we test and validate on representative synthetic networks and on published multilevel models of biological networks. Despite its primary motivation to analyze biological networks, our motif-based method is general and can be applied to any finite discrete dynamical system.

Synthetic Biology: Tools to Design, Build, and Optimize Cellular Processes

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Young, Eric; Alper, Hal

2010-01-01

The general central dogma frames the emergent properties of life, which make biology both necessary and difficult to engineer. In a process engineering paradigm, each biological process stream and process unit is heavily influenced by regulatory interactions and interactions with the surrounding environment. Synthetic biology is developing the tools and methods that will increase control over these interactions, eventually resulting in an integrative synthetic biology that will allow ground-up cellular optimization. In this review, we attempt to contextualize the areas of synthetic biology into three tiers: (1) the process units and associated streams of the central dogma, (2) the intrinsic regulatory mechanisms, and (3) the extrinsic physical and chemical environment. Efforts at each of these three tiers attempt to control cellular systems and take advantage of emerging tools and approaches. Ultimately, it will be possible to integrate these approaches and realize the vision of integrative synthetic biology when cells are completely rewired for biotechnological goals. This review will highlight progress towards this goal as well as areas requiring further research. PMID:20150964

Synthetic Biology: Tools to Design, Build, and Optimize Cellular Processes

Directory of Open Access Journals (Sweden)

Eric Young

2010-01-01

Full Text Available The general central dogma frames the emergent properties of life, which make biology both necessary and difficult to engineer. In a process engineering paradigm, each biological process stream and process unit is heavily influenced by regulatory interactions and interactions with the surrounding environment. Synthetic biology is developing the tools and methods that will increase control over these interactions, eventually resulting in an integrative synthetic biology that will allow ground-up cellular optimization. In this review, we attempt to contextualize the areas of synthetic biology into three tiers: (1 the process units and associated streams of the central dogma, (2 the intrinsic regulatory mechanisms, and (3 the extrinsic physical and chemical environment. Efforts at each of these three tiers attempt to control cellular systems and take advantage of emerging tools and approaches. Ultimately, it will be possible to integrate these approaches and realize the vision of integrative synthetic biology when cells are completely rewired for biotechnological goals. This review will highlight progress towards this goal as well as areas requiring further research.

Synthetic biology: tools to design, build, and optimize cellular processes.

Science.gov (United States)

Young, Eric; Alper, Hal

2010-01-01

The general central dogma frames the emergent properties of life, which make biology both necessary and difficult to engineer. In a process engineering paradigm, each biological process stream and process unit is heavily influenced by regulatory interactions and interactions with the surrounding environment. Synthetic biology is developing the tools and methods that will increase control over these interactions, eventually resulting in an integrative synthetic biology that will allow ground-up cellular optimization. In this review, we attempt to contextualize the areas of synthetic biology into three tiers: (1) the process units and associated streams of the central dogma, (2) the intrinsic regulatory mechanisms, and (3) the extrinsic physical and chemical environment. Efforts at each of these three tiers attempt to control cellular systems and take advantage of emerging tools and approaches. Ultimately, it will be possible to integrate these approaches and realize the vision of integrative synthetic biology when cells are completely rewired for biotechnological goals. This review will highlight progress towards this goal as well as areas requiring further research.

Biological processes influencing contaminant release from sediments

International Nuclear Information System (INIS)

Reible, D.D.

1996-01-01

The influence of biological processes, including bioturbation, on the mobility of contaminants in freshwater sediments is described. Effective mass coefficients are estimated for tubificid oligochaetes as a function of worm behavior and biomass density. The mass transfer coefficients were observed to be inversely proportional to water oxygen content and proportional to the square root of biomass density. The sediment reworking and contaminant release are contrasted with those of freshwater amphipods. The implications of these and other biological processes for contaminant release and i n-situ remediation of soils and sediments are summarized. 4 figs., 1 tab

Treatment of slaughter wastewater by coagulation sedimentation-anaerobic biological filter and biological contact oxidation process

Science.gov (United States)

Sun, M.; Yu, P. F.; Fu, J. X.; Ji, X. Q.; Jiang, T.

2017-08-01

The optimal process parameters and conditions for the treatment of slaughterhouse wastewater by coagulation sedimentation-AF - biological contact oxidation process were studied to solve the problem of high concentration organic wastewater treatment in the production of small and medium sized slaughter plants. The suitable water temperature and the optimum reaction time are determined by the experiment of precipitation to study the effect of filtration rate and reflux ratio on COD and SS in anaerobic biological filter and the effect of biofilm thickness and gas water ratio on NH3-N and COD in biological contact oxidation tank, and results show that the optimum temperature is 16-24°C, reaction time is 20 min in coagulating sedimentation, the optimum filtration rate is 0.6 m/h, and the optimum reflux ratio is 300% in anaerobic biological filter reactor. The most suitable biological film thickness range of 1.8-2.2 mm and the most suitable gas water ratio is 12:1-14:1 in biological contact oxidation pool. In the coupling process of continuous operation for 80 days, the average effluent’s mass concentrations of COD, TP and TN were 15.57 mg/L, 40 mg/L and 0.63 mg/L, the average removal rates were 98.93%, 86.10%, 88.95%, respectively. The coupling process has stable operation effect and good effluent quality, and is suitable for the industrial application.

Bioattractors: dynamical systems theory and the evolution of regulatory processes

Science.gov (United States)

Jaeger, Johannes; Monk, Nick

2014-01-01

In this paper, we illustrate how dynamical systems theory can provide a unifying conceptual framework for evolution of biological regulatory systems. Our argument is that the genotype–phenotype map can be characterized by the phase portrait of the underlying regulatory process. The features of this portrait – such as attractors with associated basins and their bifurcations – define the regulatory and evolutionary potential of a system. We show how the geometric analysis of phase space connects Waddington's epigenetic landscape to recent computational approaches for the study of robustness and evolvability in network evolution. We discuss how the geometry of phase space determines the probability of possible phenotypic transitions. Finally, we demonstrate how the active, self-organizing role of the environment in phenotypic evolution can be understood in terms of dynamical systems concepts. This approach yields mechanistic explanations that go beyond insights based on the simulation of evolving regulatory networks alone. Its predictions can now be tested by studying specific, experimentally tractable regulatory systems using the tools of modern systems biology. A systematic exploration of such systems will enable us to understand better the nature and origin of the phenotypic variability, which provides the substrate for evolution by natural selection. PMID:24882812

Female juvenile murderers: Biological and psychological dynamics leading to homicide.

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Heide, Kathleen M; Solomon, Eldra P

2009-01-01

The increasing involvement of girls under 18 in violent crime has been a matter of growing concern in the United States in recent years. This article reviews the arrests of female juveniles for violent crime and then focuses specifically on their involvement in homicide. Arrests of girls for murder, unlike arrests for assault, have not risen over the last 30 years, suggesting that the dynamics that propel female juveniles to engage in lethal violence differ from those contributing to assaultive behavior by this same group. A review of the literature indicates that theories as to why female adolescents kill do not take into account recent scientific findings on brain development and the biological effects of early trauma in explaining serious violent behavior by girls. Three cases, evaluated by the authors, involving female adolescents charged with murder or attempted murder, are presented. The authors focus on the biological and psychological dynamics that help explain their violent behavior. They discuss the effects of insecure attachment and child maltreatment, and trace a critical pathway between these early experiences and future risk of violent behavior. The dynamics of child maltreatment in fostering rage and violence are discussed thereafter in terms of offender accountability. The article concludes with a discussion of treatment and recommendations for future research.

Aging in a Relativistic Biological Space-Time

Directory of Open Access Journals (Sweden)

Davide Maestrini

2018-05-01

Full Text Available Here we present a theoretical and mathematical perspective on the process of aging. We extend the concepts of physical space and time to an abstract, mathematically-defined space, which we associate with a concept of “biological space-time” in which biological dynamics may be represented. We hypothesize that biological dynamics, represented as trajectories in biological space-time, may be used to model and study different rates of biological aging. As a consequence of this hypothesis, we show how dilation or contraction of time analogous to relativistic corrections of physical time resulting from accelerated or decelerated biological dynamics may be used to study precipitous or protracted aging. We show specific examples of how these principles may be used to model different rates of aging, with an emphasis on cancer in aging. We discuss how this theory may be tested or falsified, as well as novel concepts and implications of this theory that may improve our interpretation of biological aging.

The collective biology of the gene: Towards genetic dynamics engineering

International Nuclear Information System (INIS)

Chela-Flores, J.

1985-11-01

Chromatin dynamics is studied in terms of coupled vibrations (phonon pairing); this is shown to lead to a collective variable Δ, interpreted as a gene inhibition factor, which behaves as a biological switch turned off, not only by enzymatic action or metabolic energy, but also by means of an external probe:irradiation. We discuss the inactivation of the X chromosome and puffing. The relevance of being able to modulate Δ is emphasized, since it is equivalent to controlling chromatin dynamics without interfering with chromatin structure, unlike in the usual recombinant DNA techniques. (author)

Combination of Advanced Oxidation Processes and biological treatments for wastewater decontamination-A review

International Nuclear Information System (INIS)

Oller, I.; Malato, S.; Sanchez-Perez, J.A.

2011-01-01

Nowadays there is a continuously increasing worldwide concern for development of alternative water reuse technologies, mainly focused on agriculture and industry. In this context, Advanced Oxidation Processes (AOPs) are considered a highly competitive water treatment technology for the removal of those organic pollutants not treatable by conventional techniques due to their high chemical stability and/or low biodegradability. Although chemical oxidation for complete mineralization is usually expensive, its combination with a biological treatment is widely reported to reduce operating costs. This paper reviews recent research combining AOPs (as a pre-treatment or post-treatment stage) and bioremediation technologies for the decontamination of a wide range of synthetic and real industrial wastewater. Special emphasis is also placed on recent studies and large-scale combination schemes developed in Mediterranean countries for non-biodegradable wastewater treatment and reuse. The main conclusions arrived at from the overall assessment of the literature are that more work needs to be done on degradation kinetics and reactor modeling of the combined process, and also dynamics of the initial attack on primary contaminants and intermediate species generation. Furthermore, better economic models must be developed to estimate how the cost of this combined process varies with specific industrial wastewater characteristics, the overall decontamination efficiency and the relative cost of the AOP versus biological treatment.

Selection of Activities in Dynamic Business Process Simulation

Directory of Open Access Journals (Sweden)

Toma Rusinaitė

2016-06-01

Full Text Available Maintaining dynamicity of business processes is one of the core issues of today's business as it enables businesses to adapt to constantly changing environment. Upon changing the processes, it is vital to assess possible impact, which is achieved by using simulation of dynamic processes. In order to implement dynamicity in business processes, it is necessary to have an ability to change components of the process (a set of activities, a content of activity, a set of activity sequences, a set of rules, performers and resources or dynamically select them during execution. This problem attracted attention of researches over the past few years; however, there is no proposed solution, which ensures the business process (BP dynamicity. This paper proposes and specifies dynamic business process (DBP simulation model, which satisfies all of the formulated DBP requirements.

Processing scarce biological samples for light and transmission electron microscopy

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P Taupin

2008-06-01

Full Text Available Light microscopy (LM and transmission electron microscopy (TEM aim at understanding the relationship structure-function. With advances in biology, isolation and purification of scarce populations of cells or subcellular structures may not lead to enough biological material, for processing for LM and TEM. A protocol for preparation of scarce biological samples is presented. It is based on pre-embedding the biological samples, suspensions or pellets, in bovine serum albumin (BSA and bis-acrylamide (BA, cross-linked and polymerized. This preparation provides a simple and reproducible technique to process biological materials, present in limited quantities that can not be amplified, for light and transmission electron microscopy.

Dimension reduction for stochastic dynamical systems forced onto a manifold by large drift: a constructive approach with examples from theoretical biology

International Nuclear Information System (INIS)

Parsons, Todd L; Rogers, Tim

2017-01-01

Systems composed of large numbers of interacting agents often admit an effective coarse-grained description in terms of a multidimensional stochastic dynamical system, driven by small-amplitude intrinsic noise. In applications to biological, ecological, chemical and social dynamics it is common for these models to posses quantities that are approximately conserved on short timescales, in which case system trajectories are observed to remain close to some lower-dimensional subspace. Here, we derive explicit and general formulae for a reduced-dimension description of such processes that is exact in the limit of small noise and well-separated slow and fast dynamics. The Michaelis–Menten law of enzyme-catalysed reactions, and the link between the Lotka–Volterra and Wright–Fisher processes are explored as a simple worked examples. Extensions of the method are presented for infinite dimensional systems and processes coupled to non-Gaussian noise sources. (paper)

Dimension reduction for stochastic dynamical systems forced onto a manifold by large drift: a constructive approach with examples from theoretical biology

Science.gov (United States)

Parsons, Todd L.; Rogers, Tim

2017-10-01

Systems composed of large numbers of interacting agents often admit an effective coarse-grained description in terms of a multidimensional stochastic dynamical system, driven by small-amplitude intrinsic noise. In applications to biological, ecological, chemical and social dynamics it is common for these models to posses quantities that are approximately conserved on short timescales, in which case system trajectories are observed to remain close to some lower-dimensional subspace. Here, we derive explicit and general formulae for a reduced-dimension description of such processes that is exact in the limit of small noise and well-separated slow and fast dynamics. The Michaelis-Menten law of enzyme-catalysed reactions, and the link between the Lotka-Volterra and Wright-Fisher processes are explored as a simple worked examples. Extensions of the method are presented for infinite dimensional systems and processes coupled to non-Gaussian noise sources.

Modelling estimation and analysis of dynamic processes from image sequences using temporal random closed sets and point processes with application to the cell exocytosis and endocytosis

OpenAIRE

Díaz Fernández, Ester

2010-01-01

In this thesis, new models and methodologies are introduced for the analysis of dynamic processes characterized by image sequences with spatial temporal overlapping. The spatial temporal overlapping exists in many natural phenomena and should be addressed properly in several Science disciplines such as Microscopy, Material Sciences, Biology, Geostatistics or Communication Networks. This work is related to the Point Process and Random Closed Set theories, within Stochastic Ge...

On the selection and validation of biological treatment processes. The GDF experience; Le choix et la validation des procedes de traitement biologique. L`experience de GDF

Energy Technology Data Exchange (ETDEWEB)

Druelle, V [Gaz de France (GDF), 75 - Paris (France)

1997-12-31

The biological treatment process was selected by Gaz de France (GDF), the French national gas utility, for the de-pollution of an old gas works where the main pollutants are coal tars containing polycyclic aromatic hydrocarbons. Microorganism-based biological treatment techniques may involve bio-reactors, static ground knolls (where oxygen is brought through drains) and dynamic knolls (where oxygenation is carried out by turning up the soil). Issues on sampling, sorting, process testing, site preparation, process control, etc. are reviewed

On the selection and validation of biological treatment processes. The GDF experience; Le choix et la validation des procedes de traitement biologique. L`experience de GDF

Energy Technology Data Exchange (ETDEWEB)

Druelle, V. [Gaz de France (GDF), 75 - Paris (France)

1996-12-31

The biological treatment process was selected by Gaz de France (GDF), the French national gas utility, for the de-pollution of an old gas works where the main pollutants are coal tars containing polycyclic aromatic hydrocarbons. Microorganism-based biological treatment techniques may involve bio-reactors, static ground knolls (where oxygen is brought through drains) and dynamic knolls (where oxygenation is carried out by turning up the soil). Issues on sampling, sorting, process testing, site preparation, process control, etc. are reviewed

River, delta and coastal morphological response accounting for biological dynamics

Science.gov (United States)

Goldsmith, W.; Bernardi, D.; Schippa, L.

2015-03-01

Management and construction can increase resilience in the face of climate change, and benefits can be enhanced through integration of biogenic materials including shells and vegetation. Rivers and coastal landforms are dynamic systems that respond to intentional and unintended manipulation of critical factors, often with unforeseen and/or undesirable resulting effects. River management strategies have impacts that include deltas and coastal areas which are increasingly vulnerable to climate change with reference to sea level rise and storm intensity. Whereas conventional assessment and analysis of rivers and coasts has relied on modelling of hydrology, hydraulics and sediment transport, incorporating additional biological factors can offer more comprehensive, beneficial and realistic alternatives. Suitable modelling tools can provide improved decision support. The question has been whether current models can effectively address biological responses with suitable reliability and efficiency. Since morphodynamic evolution exhibits its effects on a large timescale, the choice of mathematical model is not trivial and depends upon the availability of data, as well as the spatial extent, timelines and computation effort desired. The ultimate goal of the work is to set up a conveniently simplified river morphodynamic model, coupled with a biological dynamics plant population model able to predict the long-term evolution of large alluvial river systems managed through bioengineering. This paper presents the first step of the work related to the application of the model accounting for stationary vegetation condition. Sensitivity analysis has been performed on the main hydraulic, sedimentology, and biological parameters. The model has been applied to significant river training in Europe, Asia and North America, and comparative analysis has been used to validate analytical solutions. Data gaps and further areas for investigation are identified.

An introduction to stochastic processes with applications to biology

CERN Document Server

Allen, Linda J S

2010-01-01

An Introduction to Stochastic Processes with Applications to Biology, Second Edition presents the basic theory of stochastic processes necessary in understanding and applying stochastic methods to biological problems in areas such as population growth and extinction, drug kinetics, two-species competition and predation, the spread of epidemics, and the genetics of inbreeding. Because of their rich structure, the text focuses on discrete and continuous time Markov chains and continuous time and state Markov processes.New to the Second EditionA new chapter on stochastic differential equations th

Mathematical modeling of heat treatment processes conserving biological activity of plant bioresources

Science.gov (United States)

Rodionova, N. S.; Popov, E. S.; Pozhidaeva, E. A.; Pynzar, S. S.; Ryaskina, L. O.

2018-05-01

The aim of this study is to develop a mathematical model of the heat exchange process of LT-processing to estimate the dynamics of temperature field changes and optimize the regime parameters, due to the non-stationarity process, the physicochemical and thermophysical properties of food systems. The application of LT-processing, based on the use of low-temperature modes in thermal culinary processing of raw materials with preliminary vacuum packaging in a polymer heat- resistant film is a promising trend in the development of technics and technology in the catering field. LT-processing application of food raw materials guarantees the preservation of biologically active substances in food environments, which are characterized by a certain thermolability, as well as extend the shelf life and high consumer characteristics of food systems that are capillary-porous bodies. When performing the mathematical modeling of the LT-processing process, the packet of symbolic mathematics “Maple” was used, as well as the mathematical packet flexPDE that uses the finite element method for modeling objects with distributed parameters. The processing of experimental results was evaluated with the help of the developed software in the programming language Python 3.4. To calculate and optimize the parameters of the LT processing process of polycomponent food systems, the differential equation of non-stationary thermal conductivity was used, the solution of which makes it possible to identify the temperature change at any point of the solid at different moments. The present study specifies data on the thermophysical characteristics of the polycomponent food system based on plant raw materials, with the help of which the physico-mathematical model of the LT- processing process has been developed. The obtained mathematical model allows defining of the dynamics of the temperature field in different sections of the LT-processed polycomponent food systems on the basis of calculating the

Spatial Organization and Dynamics of Transcription Elongation and Pre-mRNA Processing in Live Cells

Directory of Open Access Journals (Sweden)

Miguel Sánchez-Álvarez

2011-01-01

Full Text Available During the last 30 years, systematic biochemical and functional studies have significantly expanded our knowledge of the transcriptional molecular components and the pre-mRNA processing machinery of the cell. However, our current understanding of how these functions take place spatiotemporally within the highly compartmentalized eukaryotic nucleus remains limited. Moreover, it is increasingly clear that “the whole is more than the sum of its parts” and that an understanding of the dynamic coregulation of genes is essential for fully characterizing complex biological phenomena and underlying diseases. Recent technological advances in light microscopy in addition to novel cell and molecular biology approaches have led to the development of new tools, which are being used to address these questions and may contribute to achieving an integrated and global understanding of how the genome works at a cellular level. Here, we review major hallmarks and novel insights in RNA polymerase II activity and pre-mRNA processing in the context of nuclear organization, as well as new concepts and challenges arising from our ability to gather extensive dynamic information at the single-cell resolution.

Fuzzy control of pressurizer dynamic process

International Nuclear Information System (INIS)

Ming Zhedong; Zhao Fuyu

2006-01-01

Considering the characteristics of pressurizer dynamic process, the fuzzy control system that takes the advantages of both fuzzy controller and PID controller is designed for the dynamic process in pressurizer. The simulation results illustrate this type of composite control system is with better qualities than those of single fuzzy controller and single PID controller. (authors)

Modeling biological pathway dynamics with timed automata.

Science.gov (United States)

Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N

2014-05-01

Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.

An introduction to continuous-time stochastic processes theory, models, and applications to finance, biology, and medicine

CERN Document Server

Capasso, Vincenzo

2015-01-01

This textbook, now in its third edition, offers a rigorous and self-contained introduction to the theory of continuous-time stochastic processes, stochastic integrals, and stochastic differential equations. Expertly balancing theory and applications, the work features concrete examples of modeling real-world problems from biology, medicine, industrial applications, finance, and insurance using stochastic methods. No previous knowledge of stochastic processes is required. Key topics include: * Markov processes * Stochastic differential equations * Arbitrage-free markets and financial derivatives * Insurance risk * Population dynamics, and epidemics * Agent-based models New to the Third Edition: * Infinitely divisible distributions * Random measures * Levy processes * Fractional Brownian motion * Ergodic theory * Karhunen-Loeve expansion * Additional applications * Additional  exercises * Smoluchowski  approximation of  Langevin systems An Introduction to Continuous-Time Stochastic Processes, Third Editio...

Dynamics of problem setting and framing in citizen discussions on synthetic biology.

Science.gov (United States)

Betten, Afke Wieke; Broerse, Jacqueline E W; Kupper, Frank

2018-04-01

Synthetic biology is an emerging scientific field where engineers and biologists design and build biological systems for various applications. Developing synthetic biology responsibly in the public interest necessitates a meaningful societal dialogue. In this article, we argue that facilitating such a dialogue requires an understanding of how people make sense of synthetic biology. We performed qualitative research to unravel the underlying dynamics of problem setting and framing in citizen discussions on synthetic biology. We found that most people are not inherently for or against synthetic biology as a technology or development in itself, but that their perspectives are framed by core values about our relationships with science and technology and that sensemaking is much dependent on the context and general feelings of (dis)content. Given that there are many assumptions focused on a more binary idea of the public's view, we emphasize the need for frame awareness and understanding in a meaningful dialogue.

Systems Biology Graphical Notation: Process Description language Level 1 Version 1.3.

Science.gov (United States)

Moodie, Stuart; Le Novère, Nicolas; Demir, Emek; Mi, Huaiyu; Villéger, Alice

2015-09-04

The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Process Description language represents biological entities and processes between these entities within a network. SBGN PD focuses on the mechanistic description and temporal dependencies of biological interactions and transformations. The nodes (elements) are split into entity nodes describing, e.g., metabolites, proteins, genes and complexes, and process nodes describing, e.g., reactions and associations. The edges (connections) provide descriptions of relationships (or influences) between the nodes, such as consumption, production, stimulation and inhibition. Among all three languages of SBGN, PD is the closest to metabolic and regulatory pathways in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.

Stochastic transport processes in discrete biological systems

CERN Document Server

Frehland, Eckart

1982-01-01

These notes are in part based on a course for advanced students in the applications of stochastic processes held in 1978 at the University of Konstanz. These notes contain the results of re­ cent studies on the stochastic description of ion transport through biological membranes. In particular, they serve as an introduction to an unified theory of fluctuations in complex biological transport systems. We emphasize that the subject of this volume is not to introduce the mathematics of stochastic processes but to present a field of theoretical biophysics in which stochastic methods are important. In the last years the study of membrane noise has become an important method in biophysics. Valuable information on the ion transport mechanisms in membranes can be obtained from noise analysis. A number of different processes such as the opening and closing of ion channels have been shown to be sources of the measured current or voltage fluctuations. Bio­ logical 'transport systems can be complex. For example, the tr...

Dynamical 'in situ' observation of biological samples using variable pressure scanning electron microscope

International Nuclear Information System (INIS)

Nedela, V

2008-01-01

Possibilities of 'in-situ' observation of non-conductive biological samples free of charging artefacts in dynamically changed surrounding conditions are the topic of this work. The observed biological sample, the tongue of a rat, was placed on a cooled Peltier stage. We studied the visibility of topographical structure depending on transition between liquid and gas state of water in the specimen chamber of VP SEM.

Development of a computational system for management of risks in radiosterilization processes of biological tissues

International Nuclear Information System (INIS)

Montoya, Cynara Viterbo

2009-01-01

Risk management can be understood to be a systematic management which aims to identify record and control the risks of a process. Applying risk management becomes a complex activity, due to the variety of professionals involved. In order to execute risk management the following are requirements of paramount importance: the experience, discernment and judgment of a multidisciplinary team, guided by means of quality tools, so as to provide standardization in the process of investigating the cause and effects of risks and dynamism in obtaining the objective desired, i.e. the reduction and control of the risk. This work aims to develop a computational system of risk management (software) which makes it feasible to diagnose the risks of the processes of radiosterilization of biological tissues. The methodology adopted was action-research, according to which the researcher performs an active role in the establishment of the problems found, in the follow-up and in the evaluation of the actions taken owing to the problems. The scenario of this action-research was the Laboratory of Biological Tissues (LTB) in the Radiation Technology Center IPEN/CNEN-SP - Sao Paulo/Brazil. The software developed was executed in PHP and Flash/MySQL language, the server (hosting), the software is available on the Internet (www.vcrisk.com.br), which the user can access from anywhere by means of the login/access password previously sent by email to the team responsible for the tissue to be analyzed. The software presents friendly navigability whereby the user is directed step-by-step in the process of investigating the risk up to the means of reducing it. The software 'makes' the user comply with the term and present the effectiveness of the actions taken to reduce the risk. Applying this system provided the organization (LTB/CTR/IPEN) with dynamic communication, effective between the members of the multidisciplinary team: a) in decision-making; b) in lessons learned; c) in knowing the new risk

Hidden Markov processes theory and applications to biology

CERN Document Server

Vidyasagar, M

2014-01-01

This book explores important aspects of Markov and hidden Markov processes and the applications of these ideas to various problems in computational biology. The book starts from first principles, so that no previous knowledge of probability is necessary. However, the work is rigorous and mathematical, making it useful to engineers and mathematicians, even those not interested in biological applications. A range of exercises is provided, including drills to familiarize the reader with concepts and more advanced problems that require deep thinking about the theory. Biological applications are t

River, delta and coastal morphological response accounting for biological dynamics

Directory of Open Access Journals (Sweden)

W. Goldsmith

2015-03-01

Full Text Available Management and construction can increase resilience in the face of climate change, and benefits can be enhanced through integration of biogenic materials including shells and vegetation. Rivers and coastal landforms are dynamic systems that respond to intentional and unintended manipulation of critical factors, often with unforeseen and/or undesirable resulting effects. River management strategies have impacts that include deltas and coastal areas which are increasingly vulnerable to climate change with reference to sea level rise and storm intensity. Whereas conventional assessment and analysis of rivers and coasts has relied on modelling of hydrology, hydraulics and sediment transport, incorporating additional biological factors can offer more comprehensive, beneficial and realistic alternatives. Suitable modelling tools can provide improved decision support. The question has been whether current models can effectively address biological responses with suitable reliability and efficiency. Since morphodynamic evolution exhibits its effects on a large timescale, the choice of mathematical model is not trivial and depends upon the availability of data, as well as the spatial extent, timelines and computation effort desired. The ultimate goal of the work is to set up a conveniently simplified river morphodynamic model, coupled with a biological dynamics plant population model able to predict the long-term evolution of large alluvial river systems managed through bioengineering. This paper presents the first step of the work related to the application of the model accounting for stationary vegetation condition. Sensitivity analysis has been performed on the main hydraulic, sedimentology, and biological parameters. The model has been applied to significant river training in Europe, Asia and North America, and comparative analysis has been used to validate analytical solutions. Data gaps and further areas for investigation are identified.

Application of Non-Kolmogorovian Probability and Quantum Adaptive Dynamics to Unconscious Inference in Visual Perception Process

Science.gov (United States)

Accardi, Luigi; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro

2016-07-01

Recently a novel quantum information formalism — quantum adaptive dynamics — was developed and applied to modelling of information processing by bio-systems including cognitive phenomena: from molecular biology (glucose-lactose metabolism for E.coli bacteria, epigenetic evolution) to cognition, psychology. From the foundational point of view quantum adaptive dynamics describes mutual adapting of the information states of two interacting systems (physical or biological) as well as adapting of co-observations performed by the systems. In this paper we apply this formalism to model unconscious inference: the process of transition from sensation to perception. The paper combines theory and experiment. Statistical data collected in an experimental study on recognition of a particular ambiguous figure, the Schröder stairs, support the viability of the quantum(-like) model of unconscious inference including modelling of biases generated by rotation-contexts. From the probabilistic point of view, we study (for concrete experimental data) the problem of contextuality of probability, its dependence on experimental contexts. Mathematically contextuality leads to non-Komogorovness: probability distributions generated by various rotation contexts cannot be treated in the Kolmogorovian framework. At the same time they can be embedded in a “big Kolmogorov space” as conditional probabilities. However, such a Kolmogorov space has too complex structure and the operational quantum formalism in the form of quantum adaptive dynamics simplifies the modelling essentially.

Merging constitutional and motional covalent dynamics in reversible imine formation and exchange processes.

Science.gov (United States)

Kovaříček, Petr; Lehn, Jean-Marie

2012-06-06

The formation and exchange processes of imines of salicylaldehyde, pyridine-2-carboxaldehyde, and benzaldehyde have been studied, showing that the former has features of particular interest for dynamic covalent chemistry, displaying high efficiency and fast rates. The monoimines formed with aliphatic α,ω-diamines display an internal exchange process of self-transimination type, inducing a local motion of either "stepping-in-place" or "single-step" type by bond interchange, whose rate decreases rapidly with the distance of the terminal amino groups. Control of the speed of the process over a wide range may be achieved by substituents, solvent composition, and temperature. These monoimines also undergo intermolecular exchange, thus merging motional and constitutional covalent behavior within the same molecule. With polyamines, the monoimines formed execute internal motions that have been characterized by extensive one-dimensional, two-dimensional, and EXSY proton NMR studies. In particular, with linear polyamines, nondirectional displacement occurs by shifting of the aldehyde residue along the polyamine chain serving as molecular track. Imines thus behave as simple prototypes of systems displaying relative motions of molecular moieties, a subject of high current interest in the investigation of synthetic and biological molecular motors. The motional processes described are of dynamic covalent nature and take place without change in molecular constitution. They thus represent a category of dynamic covalent motions, resulting from reversible covalent bond formation and dissociation. They extend dynamic covalent chemistry into the area of molecular motions. A major further step will be to achieve control of directionality. The results reported here for imines open wide perspectives, together with other chemical groups, for the implementation of such features in multifunctional molecules toward the design of molecular devices presenting a complex combination of

Students’ learning activities while studying biological process diagrams

NARCIS (Netherlands)

Kragten, M.; Admiraal, W.; Rijlaarsdam, G.

2015-01-01

Process diagrams describe how a system functions (e.g. photosynthesis) and are an important type of representation in Biology education. In the present study, we examined students’ learning activities while studying process diagrams, related to their resulting comprehension of these diagrams. Each

Modeling biochemical transformation processes and information processing with Narrator.

Science.gov (United States)

Mandel, Johannes J; Fuss, Hendrik; Palfreyman, Niall M; Dubitzky, Werner

2007-03-27

Software tools that model and simulate the dynamics of biological processes and systems are becoming increasingly important. Some of these tools offer sophisticated graphical user interfaces (GUIs), which greatly enhance their acceptance by users. Such GUIs are based on symbolic or graphical notations used to describe, interact and communicate the developed models. Typically, these graphical notations are geared towards conventional biochemical pathway diagrams. They permit the user to represent the transport and transformation of chemical species and to define inhibitory and stimulatory dependencies. A critical weakness of existing tools is their lack of supporting an integrative representation of transport, transformation as well as biological information processing. Narrator is a software tool facilitating the development and simulation of biological systems as Co-dependence models. The Co-dependence Methodology complements the representation of species transport and transformation together with an explicit mechanism to express biological information processing. Thus, Co-dependence models explicitly capture, for instance, signal processing structures and the influence of exogenous factors or events affecting certain parts of a biological system or process. This combined set of features provides the system biologist with a powerful tool to describe and explore the dynamics of life phenomena. Narrator's GUI is based on an expressive graphical notation which forms an integral part of the Co-dependence Methodology. Behind the user-friendly GUI, Narrator hides a flexible feature which makes it relatively easy to map models defined via the graphical notation to mathematical formalisms and languages such as ordinary differential equations, the Systems Biology Markup Language or Gillespie's direct method. This powerful feature facilitates reuse, interoperability and conceptual model development. Narrator is a flexible and intuitive systems biology tool. It is

Students' Ability to Solve Process-Diagram Problems in Secondary Biology Education

Science.gov (United States)

Kragten, Marco; Admiraal, Wilfried; Rijlaarsdam, Gert

2015-01-01

Process diagrams are important tools in biology for explaining processes such as protein synthesis, compound cycles and the like. The aim of the present study was to measure the ability to solve process-diagram problems in biology and its relationship with prior knowledge, spatial ability and working memory. For this purpose, we developed a test…

Dynamical and hamiltonian dilations of stochastic processes

International Nuclear Information System (INIS)

Baumgartner, B.; Gruemm, H.-R.

1982-01-01

This is a study of the problem, which stochastic processes could arise from dynamical systems by loss of information. The notions of ''dilation'' and ''approximate dilation'' of a stochastic process are introduced to give exact definitions of this particular relationship. It is shown that every generalized stochastic process is approximately dilatable by a sequence of dynamical systems, but for stochastic processes in full generality one needs nets. (Author)

Advancing the Assessment of Dynamic Psychological Processes.

Science.gov (United States)

Wright, Aidan G C; Hopwood, Christopher J

2016-08-01

Most commonly used clinical assessment tools cannot fully capture the dynamic psychological processes often hypothesized as core mechanisms of psychopathology and psychotherapy. There is therefore a gap between our theories of problems and interventions for those problems and the tools we use to understand clients. The purpose of this special issue is to connect theory about clinical dynamics to practice by focusing on methods for collecting dynamic data, statistical models for analyzing dynamic data, and conceptual schemes for implementing dynamic data in applied settings. In this introductory article, we argue for the importance of assessing dynamic processes, highlight recent advances in assessment science that enable their measurement, review challenges in using these advances in applied practice, and adumbrate the articles in this issue.

Biology as population dynamics: heuristics for transmission risk.

Science.gov (United States)

Keebler, Daniel; Walwyn, David; Welte, Alex

2013-02-01

Population-type models, accounting for phenomena such as population lifetimes, mixing patterns, recruitment patterns, genetic evolution and environmental conditions, can be usefully applied to the biology of HIV infection and viral replication. A simple dynamic model can explore the effect of a vaccine-like stimulus on the mortality and infectiousness, which formally looks like fertility, of invading virions; the mortality of freshly infected cells; and the availability of target cells, all of which impact on the probability of infection. Variations on this model could capture the importance of the timing and duration of different key events in viral transmission, and hence be applied to questions of mucosal immunology. The dynamical insights and assumptions of such models are compatible with the continuum of between- and within-individual risks in sexual violence and may be helpful in making sense of the sparse data available on the association between HIV transmission and sexual violence. © 2012 John Wiley & Sons A/S.

Dynamic similarity in erosional processes

Science.gov (United States)

Scheidegger, A.E.

1963-01-01

A study is made of the dynamic similarity conditions obtaining in a variety of erosional processes. The pertinent equations for each type of process are written in dimensionless form; the similarity conditions can then easily be deduced. The processes treated are: raindrop action, slope evolution and river erosion. ?? 1963 Istituto Geofisico Italiano.

Separating intrinsic from extrinsic fluctuations in dynamic biological systems.

Science.gov (United States)

Hilfinger, Andreas; Paulsson, Johan

2011-07-19

From molecules in cells to organisms in ecosystems, biological populations fluctuate due to the intrinsic randomness of individual events and the extrinsic influence of changing environments. The combined effect is often too complex for effective analysis, and many studies therefore make simplifying assumptions, for example ignoring either intrinsic or extrinsic effects to reduce the number of model assumptions. Here we mathematically demonstrate how two identical and independent reporters embedded in a shared fluctuating environment can be used to identify intrinsic and extrinsic noise terms, but also how these contributions are qualitatively and quantitatively different from what has been previously reported. Furthermore, we show for which classes of biological systems the noise contributions identified by dual-reporter methods correspond to the noise contributions predicted by correct stochastic models of either intrinsic or extrinsic mechanisms. We find that for broad classes of systems, the extrinsic noise from the dual-reporter method can be rigorously analyzed using models that ignore intrinsic stochasticity. In contrast, the intrinsic noise can be rigorously analyzed using models that ignore extrinsic stochasticity only under very special conditions that rarely hold in biology. Testing whether the conditions are met is rarely possible and the dual-reporter method may thus produce flawed conclusions about the properties of the system, particularly about the intrinsic noise. Our results contribute toward establishing a rigorous framework to analyze dynamically fluctuating biological systems.

A logic-based dynamic modeling approach to explicate the evolution of the central dogma of molecular biology.

Science.gov (United States)

Jafari, Mohieddin; Ansari-Pour, Naser; Azimzadeh, Sadegh; Mirzaie, Mehdi

It is nearly half a century past the age of the introduction of the Central Dogma (CD) of molecular biology. This biological axiom has been developed and currently appears to be all the more complex. In this study, we modified CD by adding further species to the CD information flow and mathematically expressed CD within a dynamic framework by using Boolean network based on its present-day and 1965 editions. We show that the enhancement of the Dogma not only now entails a higher level of complexity, but it also shows a higher level of robustness, thus far more consistent with the nature of biological systems. Using this mathematical modeling approach, we put forward a logic-based expression of our conceptual view of molecular biology. Finally, we show that such biological concepts can be converted into dynamic mathematical models using a logic-based approach and thus may be useful as a framework for improving static conceptual models in biology.

A logic-based dynamic modeling approach to explicate the evolution of the central dogma of molecular biology.

Directory of Open Access Journals (Sweden)

Mohieddin Jafari

Full Text Available It is nearly half a century past the age of the introduction of the Central Dogma (CD of molecular biology. This biological axiom has been developed and currently appears to be all the more complex. In this study, we modified CD by adding further species to the CD information flow and mathematically expressed CD within a dynamic framework by using Boolean network based on its present-day and 1965 editions. We show that the enhancement of the Dogma not only now entails a higher level of complexity, but it also shows a higher level of robustness, thus far more consistent with the nature of biological systems. Using this mathematical modeling approach, we put forward a logic-based expression of our conceptual view of molecular biology. Finally, we show that such biological concepts can be converted into dynamic mathematical models using a logic-based approach and thus may be useful as a framework for improving static conceptual models in biology.

Protein electron transfer: is biology (thermo)dynamic?

International Nuclear Information System (INIS)

Matyushov, Dmitry V

2015-01-01

Simple physical mechanisms are behind the flow of energy in all forms of life. Energy comes to living systems through electrons occupying high-energy states, either from food (respiratory chains) or from light (photosynthesis). This energy is transformed into the cross-membrane proton-motive force that eventually drives all biochemistry of the cell. Life’s ability to transfer electrons over large distances with nearly zero loss of free energy is puzzling and has not been accomplished in synthetic systems. The focus of this review is on how this energetic efficiency is realized. General physical mechanisms and interactions that allow proteins to fold into compact water-soluble structures are also responsible for a rugged landscape of energy states and a broad distribution of relaxation times. Specific to a protein as a fluctuating thermal bath is the protein-water interface, which is heterogeneous both dynamically and structurally. The spectrum of interfacial fluctuations is a consequence of protein’s elastic flexibility combined with a high density of surface charges polarizing water dipoles into surface nanodomains. Electrostatics is critical to the protein function and the relevant questions are: (i) What is the spectrum of interfacial electrostatic fluctuations? (ii) Does the interfacial biological water produce electrostatic signatures specific to proteins? (iii) How is protein-mediated chemistry affected by electrostatics? These questions connect the fluctuation spectrum to the dynamical control of chemical reactivity, i.e. the dependence of the activation free energy of the reaction on the dynamics of the bath. Ergodicity is often broken in protein-driven reactions and thermodynamic free energies become irrelevant. Continuous ergodicity breaking in a dense spectrum of relaxation times requires using dynamically restricted ensembles to calculate statistical averages. When applied to the calculation of the rates, this formalism leads to the nonergodic

Stochastic Methods in Biology

CERN Document Server

Kallianpur, Gopinath; Hida, Takeyuki

1987-01-01

The use of probabilistic methods in the biological sciences has been so well established by now that mathematical biology is regarded by many as a distinct dis­ cipline with its own repertoire of techniques. The purpose of the Workshop on sto­ chastic methods in biology held at Nagoya University during the week of July 8-12, 1985, was to enable biologists and probabilists from Japan and the U. S. to discuss the latest developments in their respective fields and to exchange ideas on the ap­ plicability of the more recent developments in stochastic process theory to problems in biology. Eighteen papers were presented at the Workshop and have been grouped under the following headings: I. Population genetics (five papers) II. Measure valued diffusion processes related to population genetics (three papers) III. Neurophysiology (two papers) IV. Fluctuation in living cells (two papers) V. Mathematical methods related to other problems in biology, epidemiology, population dynamics, etc. (six papers) An important f...

Redox processes in radiation biology and cancer

International Nuclear Information System (INIS)

Greenstock, C.L.

1981-01-01

Free-radical intermediates, particularly the activated oxygen species OH, O - 2 , and 1 O 2 , are implicated in many types of radiation damage to biological systems. In addition, these same species may be formed, either directly or indirectly through biochemical redox reactions, in both essential and aberrant metabolic processes. Cell survival and adaptation to an environment containing ionizing radiation and other physical and chemical carcinogens ultimately depend upon the cell's ability to maintain optimal function in response to free-radical damage at the chemical level. Many of these feedback control mechanisms are redox controlled. Radiation chemical techniques using selective radical scavengers, such as product analysis and pulse radiolysis, enable us to generate, observe, and characterize individually the nature and reactivity of potentially damaging free radicals. From an analysis of the chemical kinetics of free-radical involvement in biological damage, redox mechanisms are proposed to describe the early processes of radiation damage, redox mechanisms are proposed to describe the early processes of radiation damage, its protection and sensitization, and the role of free radicals in radiation and chemical carcinogenesis

Biologic phosphorus elimination - influencing parameters, boundary conditions, process optimation

International Nuclear Information System (INIS)

Dai Xiaohu.

1992-01-01

This paper first presents a systematic study of the basic process of biologic phosphorus elimination as employed by the original 'Phoredox (Main Stream) Process'. The conditions governing the process and the factors influencing its performance were determined by trial operation. A stationary model was developed for the purpose of modelling biologic phosphorus elimination in such a main stream process and optimising the dimensioning. The validity of the model was confirmed by operational data given in the literature and by operational data from the authors' own semitechnical-scale experimental plant. The model permits simulation of the values to be expected for effluent phosphorus and phosphate concentrations for given influent data and boundary conditions. It is thus possible to dimension a plant for accomodation of the original Phoredox (Main Stream) Process or any similar phosphorus eliminating plant that is to work according to the principle of the main stream process. (orig./EF) [de

The value of mechanistic biophysical information for systems-level understanding of complex biological processes such as cytokinesis.

Science.gov (United States)

Pollard, Thomas D

2014-12-02

This review illustrates the value of quantitative information including concentrations, kinetic constants and equilibrium constants in modeling and simulating complex biological processes. Although much has been learned about some biological systems without these parameter values, they greatly strengthen mechanistic accounts of dynamical systems. The analysis of muscle contraction is a classic example of the value of combining an inventory of the molecules, atomic structures of the molecules, kinetic constants for the reactions, reconstitutions with purified proteins and theoretical modeling to account for the contraction of whole muscles. A similar strategy is now being used to understand the mechanism of cytokinesis using fission yeast as a favorable model system. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Hematopoietic differentiation: a coordinated dynamical process towards attractor stable states

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Rossi Simona

2010-06-01

Full Text Available Abstract Background The differentiation process, proceeding from stem cells towards the different committed cell types, can be considered as a trajectory towards an attractor of a dynamical process. This view, taking into consideration the transcriptome and miRNome dynamics considered as a whole, instead of looking at few 'master genes' driving the system, offers a novel perspective on this phenomenon. We investigated the 'differentiation trajectories' of the hematopoietic system considering a genome-wide scenario. Results We developed serum-free liquid suspension unilineage cultures of cord blood (CB CD34+ hematopoietic progenitor cells through erythroid (E, megakaryocytic (MK, granulocytic (G and monocytic (Mo pathways. These cultures recapitulate physiological hematopoiesis, allowing the analysis of almost pure unilineage precursors starting from initial differentiation of HPCs until terminal maturation. By analyzing the expression profile of protein coding genes and microRNAs in unilineage CB E, MK, G and Mo cultures, at sequential stages of differentiation and maturation, we observed a coordinated, fully interconnected and scalable character of cell population behaviour in both transcriptome and miRNome spaces reminiscent of an attractor-like dynamics. MiRNome and transcriptome space differed for a still not terminally committed behaviour of microRNAs. Conclusions Consistent with their roles, the transcriptome system can be considered as the state space of a cell population, while the continuously evolving miRNA space corresponds to the tuning system necessary to reach the attractor. The behaviour of miRNA machinery could be of great relevance not only for the promise of reversing the differentiated state but even for tumor biology.

The mathematics behind biological invasions

CERN Document Server

Lewis, Mark A; Potts, Jonathan R

2016-01-01

This book investigates the mathematical analysis of biological invasions. Unlike purely qualitative treatments of ecology, it draws on mathematical theory and methods, equipping the reader with sharp tools and rigorous methodology. Subjects include invasion dynamics, species interactions, population spread, long-distance dispersal, stochastic effects, risk analysis, and optimal responses to invaders. While based on the theory of dynamical systems, including partial differential equations and integrodifference equations, the book also draws on information theory, machine learning, Monte Carlo methods, optimal control, statistics, and stochastic processes. Applications to real biological invasions are included throughout. Ultimately, the book imparts a powerful principle: that by bringing ecology and mathematics together, researchers can uncover new understanding of, and effective response strategies to, biological invasions. It is suitable for graduate students and established researchers in mathematical ecolo...

Information Processing Capacity of Dynamical Systems

Science.gov (United States)

Dambre, Joni; Verstraeten, David; Schrauwen, Benjamin; Massar, Serge

2012-07-01

Many dynamical systems, both natural and artificial, are stimulated by time dependent external signals, somehow processing the information contained therein. We demonstrate how to quantify the different modes in which information can be processed by such systems and combine them to define the computational capacity of a dynamical system. This is bounded by the number of linearly independent state variables of the dynamical system, equaling it if the system obeys the fading memory condition. It can be interpreted as the total number of linearly independent functions of its stimuli the system can compute. Our theory combines concepts from machine learning (reservoir computing), system modeling, stochastic processes, and functional analysis. We illustrate our theory by numerical simulations for the logistic map, a recurrent neural network, and a two-dimensional reaction diffusion system, uncovering universal trade-offs between the non-linearity of the computation and the system's short-term memory.

Information Processing Capacity of Dynamical Systems

Science.gov (United States)

Dambre, Joni; Verstraeten, David; Schrauwen, Benjamin; Massar, Serge

2012-01-01

Many dynamical systems, both natural and artificial, are stimulated by time dependent external signals, somehow processing the information contained therein. We demonstrate how to quantify the different modes in which information can be processed by such systems and combine them to define the computational capacity of a dynamical system. This is bounded by the number of linearly independent state variables of the dynamical system, equaling it if the system obeys the fading memory condition. It can be interpreted as the total number of linearly independent functions of its stimuli the system can compute. Our theory combines concepts from machine learning (reservoir computing), system modeling, stochastic processes, and functional analysis. We illustrate our theory by numerical simulations for the logistic map, a recurrent neural network, and a two-dimensional reaction diffusion system, uncovering universal trade-offs between the non-linearity of the computation and the system's short-term memory. PMID:22816038

Process for sewage biological treatment from uranium

International Nuclear Information System (INIS)

Popa, K.; Cecal, A.; Craciun, I.

2004-01-01

The invention relates to the sewage treatment, in particular to the sewage biological treatmen from radioactive waste, namely from uranium. The process dor sewage biological treatment from uranium includes cultivation in the sewage of the aquatic plants Lemna minor and Spirulina platensis. The plants cultivation is carried out in two stages. In the first stage for cultivation is used Lemna minor in the second stage - Spirulina platensis . After finishing the plant cultivation it is carried out separation of their biomass. The result of the invention consists in increasing the uranyl ions by the biomass of plants cultivated in the sewage

Process for sewage biological treatment from uranium

International Nuclear Information System (INIS)

Popa, Karin; Cecal, Alexandru; Craciun, Iftimie Ionel; Rudic, Valeriu; Gulea, Aurelian; Cepoi, Liliana

2004-01-01

The invention relates to the sewage treatment, in particular to the sewage biological treatment from radioactive waste, namely from uranium. The process for sewage biological treatment from uranium includes cultivation in the sewage of the aquatic plants Lemna minor and Spirulina platensis. The plant cultivation is carried out in two stages. In the first stage for cultivation is used Lemna minor and in the second stage - Spirulina platensis. After finishing the plant cultivation it is carried out separation of their biomass. The result of the invention consists in increasing the uranyl ions accumulation by the biomass of plants cultivated in the sewage.

Overshoot in biological systems modelled by Markov chains: a non-equilibrium dynamic phenomenon.

Science.gov (United States)

Jia, Chen; Qian, Minping; Jiang, Daquan

2014-08-01

A number of biological systems can be modelled by Markov chains. Recently, there has been an increasing concern about when biological systems modelled by Markov chains will perform a dynamic phenomenon called overshoot. In this study, the authors found that the steady-state behaviour of the system will have a great effect on the occurrence of overshoot. They showed that overshoot in general cannot occur in systems that will finally approach an equilibrium steady state. They further classified overshoot into two types, named as simple overshoot and oscillating overshoot. They showed that except for extreme cases, oscillating overshoot will occur if the system is far from equilibrium. All these results clearly show that overshoot is a non-equilibrium dynamic phenomenon with energy consumption. In addition, the main result in this study is validated with real experimental data.

A dynamic balanced scorecard for identification internal process factor

Directory of Open Access Journals (Sweden)

Javad sofiyabadi

2012-08-01

Full Text Available We present a dynamic balanced score card (BSC to investigate the strategic internal process management factors. The proposed dynamic BSC emphasizes on internal processes aspect, and using VIKOR and Shannon Entropy, determinants the internal processes, process management and improvement and all important factors are ranked. The current study first introduces dynamic BSC and examines effective factors on the process. The proposed model focuses on internal processes perspective of BSC and determines importance degree of each factor is used using VIKOR decision-making techniques.

Computer Modelling of Dynamic Processes

Directory of Open Access Journals (Sweden)

B. Rybakin

2000-10-01

Full Text Available Results of numerical modeling of dynamic problems are summed in the article up. These problems are characteristic for various areas of human activity, in particular for problem solving in ecology. The following problems are considered in the present work: computer modeling of dynamic effects on elastic-plastic bodies, calculation and determination of performances of gas streams in gas cleaning equipment, modeling of biogas formation processes.

Modeling biochemical transformation processes and information processing with Narrator

Directory of Open Access Journals (Sweden)

Palfreyman Niall M

2007-03-01

Full Text Available Abstract Background Software tools that model and simulate the dynamics of biological processes and systems are becoming increasingly important. Some of these tools offer sophisticated graphical user interfaces (GUIs, which greatly enhance their acceptance by users. Such GUIs are based on symbolic or graphical notations used to describe, interact and communicate the developed models. Typically, these graphical notations are geared towards conventional biochemical pathway diagrams. They permit the user to represent the transport and transformation of chemical species and to define inhibitory and stimulatory dependencies. A critical weakness of existing tools is their lack of supporting an integrative representation of transport, transformation as well as biological information processing. Results Narrator is a software tool facilitating the development and simulation of biological systems as Co-dependence models. The Co-dependence Methodology complements the representation of species transport and transformation together with an explicit mechanism to express biological information processing. Thus, Co-dependence models explicitly capture, for instance, signal processing structures and the influence of exogenous factors or events affecting certain parts of a biological system or process. This combined set of features provides the system biologist with a powerful tool to describe and explore the dynamics of life phenomena. Narrator's GUI is based on an expressive graphical notation which forms an integral part of the Co-dependence Methodology. Behind the user-friendly GUI, Narrator hides a flexible feature which makes it relatively easy to map models defined via the graphical notation to mathematical formalisms and languages such as ordinary differential equations, the Systems Biology Markup Language or Gillespie's direct method. This powerful feature facilitates reuse, interoperability and conceptual model development. Conclusion Narrator is a

Quantum and classical dynamics in biologically inspired systems

International Nuclear Information System (INIS)

Guerreschi, G.

2012-01-01

Quantum biology is an emerging field in which traditional believes and paradigms are under examination. Typically, quantum effects are witnessed inside quantum optics or atomic physics laboratories in systems which are kept under control and isolated from any noise source by means of very advanced technology. Biological systems exhibit opposite characteristics: They are usually constituted of macromolecules continuously exposed to a warm and wet environment, well beyond our control; but at the same time, they operate far away from equilibrium. Recently, the experimental observation of excitonic coherence in photosynthetic complexes has con firmed that, in non-equilibrium scenarios, quantum phenomena can survive even in presence of a noisy environment. The challenge faced by the ongoing research is twofold: On one side, considering biological molecules as effective nanomachines, one has to address questions of principle regarding their design and functioning; on the other side, one has to investigate real systems which are experimentally accessible and identify such features in these concrete scenarios. The present thesis contributes to both of these aspects. In Part I, we demonstrate how entanglement can be persistently generated even under unfavorable environmental conditions. The physical mechanism is modeled after the idea of conformational changes, and it relies on the interplay of classical oscillations of large structures with the quantum dynamics of a few interacting degrees of freedom. In a similar context, we show that the transfer of an excitation through a linear chain of sites can be enhanced when the inter-site distances oscillate periodically. This enhancement is present even in comparison with the static con figuration which is optimal in the classical case and, therefore, it constitutes a clear signature of the underlying quantum dynamics. In Part II of this thesis, we study the radical pair mechanism from the perspective of quantum control and

Remote Sensing Dynamic Monitoring of Biological Invasive Species Based on Adaptive PCNN and Improved C-V Model

Directory of Open Access Journals (Sweden)

PENG Gang

2014-12-01

Full Text Available Biological species invasion problem bring serious damage to the ecosystem, and have become one of the six major enviromental problems that affect the future economic development, also have become one of the hot topic in domestic and foreign scholars. Remote sensing technology has been successfully used in the investigation of coastal zone resources, dynamic monitoring of the resources and environment, and other fields. It will cite a new remote sensing image change detection algorithm based on adaptive pulse coupled neural network (PCNN and improved C-V model, for remote sensing dynamic monitoring of biological species invasion. The experimental results show that the algorithm is effective in the test results of biological species invasions.

Test of Science Process Skills of Biology Students towards Developing of Learning Exercises

Directory of Open Access Journals (Sweden)

Judith S. Rabacal

2016-11-01

Full Text Available This is a descriptive study aimed to determine the academic achievement on science process skills of the BS Biology Students of Northern Negros State College of Science and Technology, Philippines with the end view of developing learning exercises which will enhance their academic achievement on basic and integrated science process skills. The data in this study were obtained using a validated questionnaire. Mean was the statistical tool used to determine the academic achievement on the above mentioned science process skills; t-test for independent means was used to determine significant difference on the academic achievement of science process skills of BS Biology students while Pearson Product Moment of Correlation Coefficient was used to determine the significant relationship between basic and integrated science process skills of the BS Biology students. A 0.05 level of significance was used to determine whether the hypothesis set in the study will be rejected or accepted. Findings revealed that the academic achievement on basic and integrated science process skills of the BS Biology students was average. Findings revealed that there are no significant differences on the academic performance of the BS Biology students when grouped according to year level and gender. Findings also revealed that there is a significant difference on the academic achievement between basic and integrated science process skills of the BS Biology students. Findings revealed that there is a significant relationship between academic achievement on the basic and integrated science process skills of the BS Biology students.

Dynamic process management for engineering environments

NARCIS (Netherlands)

Mentink, R.J.; van Houten, Frederikus J.A.M.; Kals, H.J.J.

2003-01-01

The research presented in this paper proposes a concept for dynamic process management as part of an integrated approach to engineering process support. The theory of information management is the starting point for the development of a process management system based on evolution of information

Active Interaction Mapping as a tool to elucidate hierarchical functions of biological processes.

Science.gov (United States)

Farré, Jean-Claude; Kramer, Michael; Ideker, Trey; Subramani, Suresh

2017-07-03

Increasingly, various 'omics data are contributing significantly to our understanding of novel biological processes, but it has not been possible to iteratively elucidate hierarchical functions in complex phenomena. We describe a general systems biology approach called Active Interaction Mapping (AI-MAP), which elucidates the hierarchy of functions for any biological process. Existing and new 'omics data sets can be iteratively added to create and improve hierarchical models which enhance our understanding of particular biological processes. The best datatypes to further improve an AI-MAP model are predicted computationally. We applied this approach to our understanding of general and selective autophagy, which are conserved in most eukaryotes, setting the stage for the broader application to other cellular processes of interest. In the particular application to autophagy-related processes, we uncovered and validated new autophagy and autophagy-related processes, expanded known autophagy processes with new components, integrated known non-autophagic processes with autophagy and predict other unexplored connections.

Spatiotemporal neural network dynamics for the processing of dynamic facial expressions

Science.gov (United States)

Sato, Wataru; Kochiyama, Takanori; Uono, Shota

2015-01-01

The dynamic facial expressions of emotion automatically elicit multifaceted psychological activities; however, the temporal profiles and dynamic interaction patterns of brain activities remain unknown. We investigated these issues using magnetoencephalography. Participants passively observed dynamic facial expressions of fear and happiness, or dynamic mosaics. Source-reconstruction analyses utilizing functional magnetic-resonance imaging data revealed higher activation in broad regions of the bilateral occipital and temporal cortices in response to dynamic facial expressions than in response to dynamic mosaics at 150–200 ms and some later time points. The right inferior frontal gyrus exhibited higher activity for dynamic faces versus mosaics at 300–350 ms. Dynamic causal-modeling analyses revealed that dynamic faces activated the dual visual routes and visual–motor route. Superior influences of feedforward and feedback connections were identified before and after 200 ms, respectively. These results indicate that hierarchical, bidirectional neural network dynamics within a few hundred milliseconds implement the processing of dynamic facial expressions. PMID:26206708

Spatiotemporal neural network dynamics for the processing of dynamic facial expressions.

Science.gov (United States)

Sato, Wataru; Kochiyama, Takanori; Uono, Shota

2015-07-24

The dynamic facial expressions of emotion automatically elicit multifaceted psychological activities; however, the temporal profiles and dynamic interaction patterns of brain activities remain unknown. We investigated these issues using magnetoencephalography. Participants passively observed dynamic facial expressions of fear and happiness, or dynamic mosaics. Source-reconstruction analyses utilizing functional magnetic-resonance imaging data revealed higher activation in broad regions of the bilateral occipital and temporal cortices in response to dynamic facial expressions than in response to dynamic mosaics at 150-200 ms and some later time points. The right inferior frontal gyrus exhibited higher activity for dynamic faces versus mosaics at 300-350 ms. Dynamic causal-modeling analyses revealed that dynamic faces activated the dual visual routes and visual-motor route. Superior influences of feedforward and feedback connections were identified before and after 200 ms, respectively. These results indicate that hierarchical, bidirectional neural network dynamics within a few hundred milliseconds implement the processing of dynamic facial expressions.

Mammalian synthetic biology for studying the cell.

Science.gov (United States)

Mathur, Melina; Xiang, Joy S; Smolke, Christina D

2017-01-02

Synthetic biology is advancing the design of genetic devices that enable the study of cellular and molecular biology in mammalian cells. These genetic devices use diverse regulatory mechanisms to both examine cellular processes and achieve precise and dynamic control of cellular phenotype. Synthetic biology tools provide novel functionality to complement the examination of natural cell systems, including engineered molecules with specific activities and model systems that mimic complex regulatory processes. Continued development of quantitative standards and computational tools will expand capacities to probe cellular mechanisms with genetic devices to achieve a more comprehensive understanding of the cell. In this study, we review synthetic biology tools that are being applied to effectively investigate diverse cellular processes, regulatory networks, and multicellular interactions. We also discuss current challenges and future developments in the field that may transform the types of investigation possible in cell biology. © 2017 Mathur et al.

Computer processing of dynamic scintigraphic studies

International Nuclear Information System (INIS)

Ullmann, V.

1985-01-01

The methods are discussed of the computer processing of dynamic scintigraphic studies which were developed, studied or implemented by the authors within research task no. 30-02-03 in nuclear medicine within the five year plan 1981 to 85. This was mainly the method of computer processing radionuclide angiography, phase radioventriculography, regional lung ventilation, dynamic sequential scintigraphy of kidneys and radionuclide uroflowmetry. The problems are discussed of the automatic definition of fields of interest, the methodology of absolute volumes of the heart chamber in radionuclide cardiology, the design and uses are described of the multipurpose dynamic phantom of heart activity for radionuclide angiocardiography and ventriculography developed within the said research task. All methods are documented with many figures showing typical clinical (normal and pathological) and phantom measurements. (V.U.)

Creative design inspired by biological knowledge: Technologies and methods

Science.gov (United States)

Tan, Runhua; Liu, Wei; Cao, Guozhong; Shi, Yuan

2018-05-01

Biological knowledge is becoming an important source of inspiration for developing creative solutions to engineering design problems and even has a huge potential in formulating ideas that can help firms compete successfully in a dynamic market. To identify the technologies and methods that can facilitate the development of biologically inspired creative designs, this research briefly reviews the existing biological-knowledge-based theories and methods and examines the application of biological-knowledge-inspired designs in various fields. Afterward, this research thoroughly examines the four dimensions of key technologies that underlie the biologically inspired design (BID) process. This research then discusses the future development trends of the BID process before presenting the conclusions.

iBiology: communicating the process of science.

Science.gov (United States)

Goodwin, Sarah S

2014-08-01

The Internet hosts an abundance of science video resources aimed at communicating scientific knowledge, including webinars, massive open online courses, and TED talks. Although these videos are efficient at disseminating information for diverse types of users, they often do not demonstrate the process of doing science, the excitement of scientific discovery, or how new scientific knowledge is developed. iBiology (www.ibiology.org), a project that creates open-access science videos about biology research and science-related topics, seeks to fill this need by producing videos by science leaders that make their ideas, stories, and experiences available to anyone with an Internet connection. © 2014 Goodwin. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Role of Biotic and Abiotic Processes on Soil CO2 Dynamics in the McMurdo Dry Valleys, Antarctica

Science.gov (United States)

Risk, D. A.; Macintyre, C. M.; Lee, C.; Cary, C.; Shanhun, F.; Almond, P. C.

2016-12-01

In the harsh conditions of the Antarctic Dry Valleys, microbial activity has been recorded via measurements of soil carbon dioxide (CO2) concentration and surface efflux. However, high temporal resolution studies in the Dry Valleys have also shown that abiotic solubility-driven processes can strongly influence (and perhaps even dominate) the CO2 dynamics in these low flux environments and suggests that biological activity may be lower than previously thought. In this study, we aim to improve our understanding of CO2 dynamics (biotic and abiotic) in Antarctic Dry Valley soils using long-term automated measurements of soil CO2 surface flux and soil profile concentration at several sites, often at sub-diel frequency. We hypothesize that soil CO2 variations are driven primarily by environmental factors affecting CO2 solubility in soil solution, mainly temperature, and that these processes may even overprint biologic production in representative Dry Valley soils. Monitoring of all sites revealed only one likely biotic CO2 production event, lasting three weeks during the Austral summer and reaching fluxes of 0.4 µmol/m2/s. Under more typical low flux conditions (sampling campaigns. Subsurface CO2 monitoring and a lab-controlled Antarctic soil simulation experiment confirmed that abiotic processes are capable of dominating soil CO2 variability. Diel temperature cycles crossing the freezing boundary revealed a dual abiotic cycle of solubility cycling and gas exclusion from ice formation observed only by high temporal frequency measurements (30 min). This work demonstrates a need for a numerical model to partition the dynamic abiotic processes underlying any biotic CO2 production in order to understand potential climate-change induced increases in microbial productivity in terrestrial Antarctica.

Computational methods to study the structure and dynamics of biomolecules and biomolecular processes from bioinformatics to molecular quantum mechanics

CERN Document Server

2014-01-01

Since the second half of the 20th century machine computations have played a critical role in science and engineering. Computer-based techniques have become especially important in molecular biology, since they often represent the only viable way to gain insights into the behavior of a biological system as a whole. The complexity of biological systems, which usually needs to be analyzed on different time- and size-scales and with different levels of accuracy, requires the application of different approaches, ranging from comparative analysis of sequences and structural databases, to the analysis of networks of interdependence between cell components and processes, through coarse-grained modeling to atomically detailed simulations, and finally to molecular quantum mechanics. This book provides a comprehensive overview of modern computer-based techniques for computing the structure, properties and dynamics of biomolecules and biomolecular processes. The twenty-two chapters, written by scientists from all over t...

Heat transfer and fluid flow in biological processes advances and applications

CERN Document Server

Becker, Sid

2015-01-01

Heat Transfer and Fluid Flow in Biological Processes covers emerging areas in fluid flow and heat transfer relevant to biosystems and medical technology. This book uses an interdisciplinary approach to provide a comprehensive prospective on biofluid mechanics and heat transfer advances and includes reviews of the most recent methods in modeling of flows in biological media, such as CFD. Written by internationally recognized researchers in the field, each chapter provides a strong introductory section that is useful to both readers currently in the field and readers interested in learning more about these areas. Heat Transfer and Fluid Flow in Biological Processes is an indispensable reference for professors, graduate students, professionals, and clinical researchers in the fields of biology, biomedical engineering, chemistry and medicine working on applications of fluid flow, heat transfer, and transport phenomena in biomedical technology. Provides a wide range of biological and clinical applications of fluid...

Quantum mechanical simulation methods for studying biological systems

International Nuclear Information System (INIS)

Bicout, D.; Field, M.

1996-01-01

Most known biological mechanisms can be explained using fundamental laws of physics and chemistry and a full understanding of biological processes requires a multidisciplinary approach in which all the tools of biology, chemistry and physics are employed. An area of research becoming increasingly important is the theoretical study of biological macromolecules where numerical experimentation plays a double role of establishing a link between theoretical models and predictions and allowing a quantitative comparison between experiments and models. This workshop brought researchers working on different aspects of the development and application of quantum mechanical simulation together, assessed the state-of-the-art in the field and highlighted directions for future research. Fourteen lectures (theoretical courses and specialized seminars) deal with following themes: 1) quantum mechanical calculations of large systems, 2) ab initio molecular dynamics where the calculation of the wavefunction and hence the energy and forces on the atoms for a system at a single nuclear configuration are combined with classical molecular dynamics algorithms in order to perform simulations which use a quantum mechanical potential energy surface, 3) quantum dynamical simulations, electron and proton transfer processes in proteins and in solutions and finally, 4) free seminars that helped to enlarge the scope of the workshop. (N.T.)

Toward understanding dynamic annealing processes in irradiated ceramics

Energy Technology Data Exchange (ETDEWEB)

Myers, Michael Thomas [Texas A & M Univ., College Station, TX (United States)

2013-05-01

High energy particle irradiation inevitably generates defects in solids. The ballistic formation and thermalization of the defect creation process occur rapidly, and are believed to be reasonably well understood. However, knowledge of the evolution of defects after damage cascade thermalization, referred to as dynamic annealing, is quite limited. Unraveling the mechanisms associated with dynamic annealing is crucial since such processes play an important role in the formation of stable postirradiation disorder in ion-beam-processing of semiconductors, and determines the “radiation tolerance” of many nuclear materials. The purpose of this dissertation is to further our understanding of the processes involved in dynamic annealing. In order to achieve this, two main tasks are undertaken.

The Intrinsic Dynamics of Psychological Process

NARCIS (Netherlands)

Vallacher, Robin R.; van Geert, Paul; Nowak, Andrzej

2015-01-01

Psychological processes unfold on various timescales in accord with internally generated patterns. The intrinsic dynamism of psychological process is difficult to investigate using traditional methods emphasizing cause–effect relations, however, and therefore is rarely incorporated into social

Phenol wastewater remediation: advanced oxidation processes coupled to a biological treatment.

Science.gov (United States)

Rubalcaba, A; Suárez-Ojeda, M E; Stüber, F; Fortuny, A; Bengoa, C; Metcalfe, I; Font, J; Carrera, J; Fabregat, A

2007-01-01

Nowadays, there are increasingly stringent regulations requiring more and more treatment of industrial effluents to generate product waters which could be easily reused or disposed of to the environment without any harmful effects. Therefore, different advanced oxidation processes were investigated as suitable precursors for the biological treatment of industrial effluents containing phenol. Wet air oxidation and Fenton process were tested batch wise, while catalytic wet air oxidation and H2O2-promoted catalytic wet air oxidation processes were studied in a trickle bed reactor, the last two using over activated carbon as catalyst. Effluent characterisation was made by means of substrate conversion (using high liquid performance chromatography), chemical oxygen demand and total organic carbon. Biodegradation parameters (i.e. maximum oxygen uptake rate and oxygen consumption) were obtained from respirometric tests using activated sludge from an urban biological wastewater treatment plant (WWTP). The main goal was to find the proper conditions in terms of biodegradability enhancement, so that these phenolic effluents could be successfully treated in an urban biological WWTP. Results show promising research ways for the development of efficient coupled processes for the treatment of wastewater containing toxic or biologically non-degradable compounds.

Generated dynamics of Markov and quantum processes

CERN Document Server

Janßen, Martin

2016-01-01

This book presents Markov and quantum processes as two sides of a coin called generated stochastic processes. It deals with quantum processes as reversible stochastic processes generated by one-step unitary operators, while Markov processes are irreversible stochastic processes generated by one-step stochastic operators. The characteristic feature of quantum processes are oscillations, interference, lots of stationary states in bounded systems and possible asymptotic stationary scattering states in open systems, while the characteristic feature of Markov processes are relaxations to a single stationary state. Quantum processes apply to systems where all variables, that control reversibility, are taken as relevant variables, while Markov processes emerge when some of those variables cannot be followed and are thus irrelevant for the dynamic description. Their absence renders the dynamic irreversible. A further aim is to demonstrate that almost any subdiscipline of theoretical physics can conceptually be put in...

Information governance in dynamic networked business process management

NARCIS (Netherlands)

Rasouli, M.; Eshuis, H.; Grefen, P.W.P.J.; Trienekens, J.J.M.; Kusters, R.J.

2016-01-01

Competition in today’s globalized markets forces organizations to collaborate within dynamic business networks to provide mass-customized integrated solutions for customers. The collaboration within dynamic business networks necessitates forming dynamic networked business processes (DNBPs).

Degradation alternatives for a commercial fungicide in water: biological, photo-Fenton, and coupled biological photo-Fenton processes.

Science.gov (United States)

López-Loveira, Elsa; Ariganello, Federico; Medina, María Sara; Centrón, Daniela; Candal, Roberto; Curutchet, Gustavo

2017-11-01

Imazalil (IMZ) is a widely used fungicide for the post-harvest treatment of citrus, classified as "likely to be carcinogenic in humans" for EPA, that can be only partially removed by conventional biological treatment. Consequently, specific or combined processes should be applied to prevent its release to the environment. Biological treatment with adapted microorganism consortium, photo-Fenton, and coupled biological photo-Fenton processes were tested as alternatives for the purification of water containing high concentration of the fungicide and the coadjutants present in the commercial formulation. IMZ-resistant consortium with the capacity to degrade IMZ in the presence of a C-rich co-substrate was isolated from sludge coming from a fruit packaging company wastewater treatment plant. This consortium was adapted to resist and degrade the organics present in photo-Fenton-oxidized IMZ water solution. Bacteria colonies from the consortia were isolated and identified. The effect of H 2 O 2 initial concentration and dosage on IMZ degradation rate, average oxidation state (AOS), organic acid concentration, oxidation, and mineralization percentage after photo-Fenton process was determined. The application of biological treatment to the oxidized solutions notably decreased the total organic carbon (TOC) in solution. The effect of the oxidation degree, limited by H 2 O 2 concentration and dosage, on the percentage of mineralization obtained after the biological treatment was determined and explained in terms of changes in AOS. The concentration of H 2 O 2 necessary to eliminate IMZ by photo-Fenton and to reduce TOC and chemical oxygen demand (COD) by biological treatment, in order to allow the release of the effluents to rivers with different flows, was estimated.

Robust and efficient parameter estimation in dynamic models of biological systems.

Science.gov (United States)

Gábor, Attila; Banga, Julio R

2015-10-29

Dynamic modelling provides a systematic framework to understand function in biological systems. Parameter estimation in nonlinear dynamic models remains a very challenging inverse problem due to its nonconvexity and ill-conditioning. Associated issues like overfitting and local solutions are usually not properly addressed in the systems biology literature despite their importance. Here we present a method for robust and efficient parameter estimation which uses two main strategies to surmount the aforementioned difficulties: (i) efficient global optimization to deal with nonconvexity, and (ii) proper regularization methods to handle ill-conditioning. In the case of regularization, we present a detailed critical comparison of methods and guidelines for properly tuning them. Further, we show how regularized estimations ensure the best trade-offs between bias and variance, reducing overfitting, and allowing the incorporation of prior knowledge in a systematic way. We illustrate the performance of the presented method with seven case studies of different nature and increasing complexity, considering several scenarios of data availability, measurement noise and prior knowledge. We show how our method ensures improved estimations with faster and more stable convergence. We also show how the calibrated models are more generalizable. Finally, we give a set of simple guidelines to apply this strategy to a wide variety of calibration problems. Here we provide a parameter estimation strategy which combines efficient global optimization with a regularization scheme. This method is able to calibrate dynamic models in an efficient and robust way, effectively fighting overfitting and allowing the incorporation of prior information.

Dynamic analysis of a guided projectile during engraving process

Directory of Open Access Journals (Sweden)

Tao Xue

2014-06-01

Full Text Available The reliability of the electronic components inside a guided projectile is highly affected by the launch dynamics of guided projectile. The engraving process plays a crucial role on determining the ballistic performance and projectile stability. This paper analyzes the dynamic response of a guided projectile during the engraving process. By considering the projectile center of gravity moving during the engraving process, a dynamics model is established with the coupling of interior ballistic equations. The results detail the stress situation of a guided projectile band during its engraving process. Meanwhile, the axial dynamic response of projectile in the several milliseconds following the engraving process is also researched. To further explore how the different performance of the engraving band can affect the dynamics of guided projectile, this paper focuses on these two aspects: (a the effects caused by the different band geometry; and (b the effects caused by different band materials. The time domain and frequency domain responses show that the dynamics of the projectile are quite sensitive to the engraving band width. A material with a small modulus of elasticity is more stable than one with a high modulus of elasticity.

Influence of different natural physical fields on biological processes

Science.gov (United States)

Mashinsky, A. L.

2001-01-01

In space flight conditions gravity, magnetic, and electrical fields as well as ionizing radiation change both in size, and in direction. This causes disruptions in the conduct of some physical processes, chemical reactions, and metabolism in living organisms. In these conditions organisms of different phylogenetic level change their metabolic reactions undergo changes such as disturbances in ionic exchange both in lower and in higher plants, changes in cell morphology for example, gyrosity in Proteus ( Proteus vulgaris), spatial disorientation in coleoptiles of Wheat ( Triticum aestivum) and Pea ( Pisum sativum) seedlings, mutational changes in Crepis ( Crepis capillaris) and Arabidopsis ( Arabidopsis thaliana) seedling. It has been found that even in the absence of gravity, gravireceptors determining spatial orientation in higher plants under terrestrial conditions are formed in the course of ontogenesis. Under weightlessness this system does not function and spatial orientation is determined by the light flux gradient or by the action of some other factors. Peculiarities of the formation of the gravireceptor apparatus in higher plants, amphibians, fish, and birds under space flight conditions have been observed. It has been found that the system in which responses were accompanied by phase transition have proven to be gravity-sensitive under microgravity conditions. Such reactions include also the process of photosynthesis which is the main energy production process in plants. In view of the established effects of microgravity and different natural physical fields on biological processes, it has been shown that these processes change due to the absence of initially rigid determination. The established biological effect of physical fields influence on biological processes in organisms is the starting point for elucidating the role of gravity and evolutionary development of various organisms on Earth.

Photobiomodulation Process

Directory of Open Access Journals (Sweden)

Yang-Yi Xu

2012-01-01

Full Text Available Photobiomodulation (PBM is a modulation of laser irradiation or monochromatic light (LI on biosystems. There is little research on PBM dynamics although its phenomena and mechanism have been widely studied. The PBM was discussed from dynamic viewpoint in this paper. It was found that the primary process of cellular PBM might be the key process of cellular PBM so that the transition rate of cellular molecules can be extended to discuss the dose relationship of PBM. There may be a dose zone in which low intensity LI (LIL at different doses has biological effects similar to each other, so that biological information model of PBM might hold. LIL may self-adaptively modulate a chronic stress until it becomes successful.

Solving Dynamic Traveling Salesman Problem Using Dynamic Gaussian Process Regression

Directory of Open Access Journals (Sweden)

Stephen M. Akandwanaho

2014-01-01

Full Text Available This paper solves the dynamic traveling salesman problem (DTSP using dynamic Gaussian Process Regression (DGPR method. The problem of varying correlation tour is alleviated by the nonstationary covariance function interleaved with DGPR to generate a predictive distribution for DTSP tour. This approach is conjoined with Nearest Neighbor (NN method and the iterated local search to track dynamic optima. Experimental results were obtained on DTSP instances. The comparisons were performed with Genetic Algorithm and Simulated Annealing. The proposed approach demonstrates superiority in finding good traveling salesman problem (TSP tour and less computational time in nonstationary conditions.

Development of the Log-in Process and the Operation Process for the VHTR-SI Process Dynamic Simulation Code

International Nuclear Information System (INIS)

Chang, Jiwoon; Shin, Youngjoon; Kim, Jihwan; Lee, Kiyoung; Lee, Wonjae; Chang, Jonghwa; Youn, Cheung

2009-01-01

The VHTR-SI process is a hydrogen production technique by using Sulfur and Iodine. The SI process for a hydrogen production uses a high temperature (about 950 .deg. C) of the He gas which is a cooling material for an energy sources. The Korea Atomic Energy Research Institute Dynamic Simulation Code (KAERI DySCo) is an integration application software that simulates the dynamic behavior of the VHTR-SI process. A dynamic modeling is used to express and model the behavior of the software system over time. The dynamic modeling deals with the control flow of system, the interaction of objects and the order of actions in view of a time and transition by using a sequence diagram and a state transition diagram. In this paper, we present an user log-in process and an operation process for the KAERI DySCo by using a sequence diagram and a state transition diagram

Negotiating the dynamics of uncomfortable knowledge: The case of dual use and synthetic biology

Science.gov (United States)

Marris, Claire; Jefferson, Catherine; Lentzos, Filippa

2014-01-01

Institutions need to ignore some knowledge in order to function. This is “uncomfortable knowledge” because it undermines the ability of those institutions to pursue their goals (Rayner, 2012). We identify three bodies of knowledge that are relevant to understandings of the dual use threat posed by synthetic biology but are excluded from related policy discussions. We demonstrate how these “unknown knowns” constitute uncomfortable knowledge because they disrupt the simplified worldview that underpins contemporary discourse on the potential misuse of synthetic biology by malign actors. We describe how these inconvenient truths have been systematically ignored and argue that this is because they are perceived as a threat by organisations involved in the promotion of synthetic biology as well as by those involved in managing biosecurity risks. This has led to a situation where concerns about the biosecurity threat posed by synthetic biology are not only exaggerated, but are, more importantly, misplaced. This, in turn, means that related policies are misdirected and unlikely to have much impact. We focus on the dynamics of discussions about synthetic biology and dual use to demonstrate how the same “knowns” that are denied or dismissed as “unknown knowns” in certain circumstances are sometimes mobilised as “known knowns” by the same category of actors in a different context, when this serves to sustain the goals of the individuals and institutions involved. Based on our own experience, we argue that negotiating the dynamics of uncomfortable knowledge is a difficult, but necessary, component of meaningful transdisciplinary collaborations. PMID:25484910

MECHANICS OF DYNAMIC POWDER COMPACTION PROCESS

OpenAIRE

Nurettin YAVUZ

1996-01-01

In recent years, interest in dynamic compaction methods of metal powders has increased due to the need to improve compaction properties and to increase production rates of compacts. In this paper, review of dynamic and explosive compaction of metal powders are given. An attempt is made to get a better understanding of the compaction process with the mechanicis of powder compaction.

Detecting subnetwork-level dynamic correlations.

Science.gov (United States)

Yan, Yan; Qiu, Shangzhao; Jin, Zhuxuan; Gong, Sihong; Bai, Yun; Lu, Jianwei; Yu, Tianwei

2017-01-15

The biological regulatory system is highly dynamic. The correlations between many functionally related genes change over different biological conditions. Finding dynamic relations on the existing biological network may reveal important regulatory mechanisms. Currently no method is available to detect subnetwork-level dynamic correlations systematically on the genome-scale network. Two major issues hampered the development. The first is gene expression profiling data usually do not contain time course measurements to facilitate the analysis of dynamic relations, which can be partially addressed by using certain genes as indicators of biological conditions. Secondly, it is unclear how to effectively delineate subnetworks, and define dynamic relations between them. Here we propose a new method named LANDD (Liquid Association for Network Dynamics Detection) to find subnetworks that show substantial dynamic correlations, as defined by subnetwork A is concentrated with Liquid Association scouting genes for subnetwork B. The method produces easily interpretable results because of its focus on subnetworks that tend to comprise functionally related genes. Also, the collective behaviour of genes in a subnetwork is a much more reliable indicator of underlying biological conditions compared to using single genes as indicators. We conducted extensive simulations to validate the method's ability to detect subnetwork-level dynamic correlations. Using a real gene expression dataset and the human protein-protein interaction network, we demonstrate the method links subnetworks of distinct biological processes, with both confirmed relations and plausible new functional implications. We also found signal transduction pathways tend to show extensive dynamic relations with other functional groups. The R package is available at https://cran.r-project.org/web/packages/LANDD CONTACTS: yunba@pcom.edu, jwlu33@hotmail.com or tianwei.yu@emory.eduSupplementary information: Supplementary data

Mathematical models in biology bringing mathematics to life

CERN Document Server

Ferraro, Maria; Guarracino, Mario

2015-01-01

This book presents an exciting collection of contributions based on the workshop “Bringing Maths to Life” held October 27-29, 2014 in Naples, Italy.  The state-of-the art research in biology and the statistical and analytical challenges facing huge masses of data collection are treated in this Work. Specific topics explored in depth surround the sessions and special invited sessions of the workshop and include genetic variability via differential expression, molecular dynamics and modeling, complex biological systems viewed from quantitative models, and microscopy images processing, to name several. In depth discussions of the mathematical analysis required to extract insights from complex bodies of biological datasets, to aid development in the field novel algorithms, methods and software tools for genetic variability, molecular dynamics, and complex biological systems are presented in this book. Researchers and graduate students in biology, life science, and mathematics/statistics will find the content...

Dynamics at the nanoscale

International Nuclear Information System (INIS)

Stoneham, A.M.; Gavartin, J.L.

2007-01-01

However fascinating structures may be at the nanoscale, time-dependent behaviour at the nanoscale has far greater importance. Some of the dynamics is random, with fluctuations controlling rate processes and making thermal ratchets possible. Some of the dynamics causes the transfer of energy, of signals, or of charge. Such transfers are especially efficiently controlled in biological systems. Other dynamical processes occur when we wish to control the nanoscale, e.g., to avoid local failures of gate dielectrics, or to manipulate structures by electronic excitation, to use spin manipulation in quantum information processing. Our prime purpose is to make clear the enormous range and variety of time-dependent nanoscale phenomena

Diffusion processes and related topics in biology

CERN Document Server

Ricciardi, Luigi M

1977-01-01

These notes are based on a one-quarter course given at the Department of Biophysics and Theoretical Biology of the University of Chicago in 1916. The course was directed to graduate students in the Division of Biological Sciences with interests in population biology and neurobiology. Only a slight acquaintance with probability and differential equations is required of the reader. Exercises are interwoven with the text to encourage the reader to play a more active role and thus facilitate his digestion of the material. One aim of these notes is to provide a heuristic approach, using as little mathematics as possible, to certain aspects of the theory of stochastic processes that are being increasingly employed in some of the population biol­ ogy and neurobiology literature. While the subject may be classical, the nov­ elty here lies in the approach and point of view, particularly in the applica­ tions such as the approach to the neuronal firing problem and its related dif­ fusion approximations. It is a ple...

Analysis of Uncertainty in Dynamic Processes Development of Banks Functioning

Directory of Open Access Journals (Sweden)

Aleksei V. Korovyakovskii

2013-01-01

Full Text Available The paper offers the approach to measure of uncertainty estimation in dynamic processes of banks functioning, using statistic data of different banking operations indicators. To calculate measure of uncertainty in dynamic processes of banks functioning the phase images of relevant sets of statistic data are considered. Besides, it is shown that the form of phase image of the studied sets of statistic data can act as a basis of measure of uncertainty estimation in dynamic processes of banks functioning. The set of analytical characteristics are offered to formalize the form of phase image definition of the studied sets of statistic data. It is shown that the offered analytical characteristics consider inequality of changes in values of the studied sets of statistic data, which is one of the ways of uncertainty display in dynamic processes development. The invariant estimates of measure of uncertainty in dynamic processes of banks functioning, considering significant changes in absolute values of the same indicators for different banks were obtained. The examples of calculation of measure of uncertainty in dynamic processes of concrete banks functioning were cited.

Classical and spatial stochastic processes with applications to biology

CERN Document Server

Schinazi, Rinaldo B

2014-01-01

The revised and expanded edition of this textbook presents the concepts and applications of random processes with the same illuminating simplicity as its first edition, but with the notable addition of substantial modern material on biological modeling. While still treating many important problems in fields such as engineering and mathematical physics, the book also focuses on the highly relevant topics of cancerous mutations, influenza evolution, drug resistance, and immune response. The models used elegantly apply various classical stochastic models presented earlier in the text, and exercises are included throughout to reinforce essential concepts. The second edition of Classical and Spatial Stochastic Processes is suitable as a textbook for courses in stochastic processes at the advanced-undergraduate and graduate levels, or as a self-study resource for researchers and practitioners in mathematics, engineering, physics, and mathematical biology. Reviews of the first edition: An appetizing textbook for a f...

Introduction to stochastic models in biology

DEFF Research Database (Denmark)

Ditlevsen, Susanne; Samson, Adeline

2013-01-01

This chapter is concerned with continuous time processes, which are often modeled as a system of ordinary differential equations (ODEs). These models assume that the observed dynamics are driven exclusively by internal, deterministic mechanisms. However, real biological systems will always be exp...

Quasielastic neutron scattering in biology: Theory and applications.

Science.gov (United States)

Vural, Derya; Hu, Xiaohu; Lindner, Benjamin; Jain, Nitin; Miao, Yinglong; Cheng, Xiaolin; Liu, Zhuo; Hong, Liang; Smith, Jeremy C

2017-01-01

Neutrons scatter quasielastically from stochastic, diffusive processes, such as overdamped vibrations, localized diffusion and transitions between energy minima. In biological systems, such as proteins and membranes, these relaxation processes are of considerable physical interest. We review here recent methodological advances and applications of quasielastic neutron scattering (QENS) in biology, concentrating on the role of molecular dynamics simulation in generating data with which neutron profiles can be unambiguously interpreted. We examine the use of massively-parallel computers in calculating scattering functions, and the application of Markov state modeling. The decomposition of MD-derived neutron dynamic susceptibilities is described, and the use of this in combination with NMR spectroscopy. We discuss dynamics at very long times, including approximations to the infinite time mean-square displacement and nonequilibrium aspects of single-protein dynamics. Finally, we examine how neutron scattering and MD can be combined to provide information on lipid nanodomains. This article is part of a Special Issue entitled "Science for Life" Guest Editor: Dr. Austen Angell, Dr. Salvatore Magazù and Dr. Federica Migliardo. Copyright © 2016 Elsevier B.V. All rights reserved.

Multi-scale Dynamical Processes in Space and Astrophysical Plasmas

CERN Document Server

Vörös, Zoltán; IAFA 2011 - International Astrophysics Forum 2011 : Frontiers in Space Environment Research

2012-01-01

Magnetized plasmas in the universe exhibit complex dynamical behavior over a huge range of scales. The fundamental mechanisms of energy transport, redistribution and conversion occur at multiple scales. The driving mechanisms often include energy accumulation, free-energy-excited relaxation processes, dissipation and self-organization. The plasma processes associated with energy conversion, transport and self-organization, such as magnetic reconnection, instabilities, linear and nonlinear waves, wave-particle interactions, dynamo processes, turbulence, heating, diffusion and convection represent fundamental physical effects. They demonstrate similar dynamical behavior in near-Earth space, on the Sun, in the heliosphere and in astrophysical environments. 'Multi-scale Dynamical Processes in Space and Astrophysical Plasmas' presents the proceedings of the International Astrophysics Forum Alpbach 2011. The contributions discuss the latest advances in the exploration of dynamical behavior in space plasmas environm...

CFD simulation of fluid dynamic and biokinetic processes within activated sludge reactors under intermittent aeration regime.

Science.gov (United States)

Sánchez, F; Rey, H; Viedma, A; Nicolás-Pérez, F; Kaiser, A S; Martínez, M

2018-08-01

Due to the aeration system, biological reactors are the most energy-consuming facilities of convectional WWTPs. Many biological reactors work under intermittent aeration regime; the optimization of the aeration process (air diffuser layout, air flow rate per diffuser, aeration length …) is necessary to ensure an efficient performance; satisfying the effluent requirements with the minimum energy consumption. This work develops a CFD modelling of an activated sludge reactor (ASR) which works under intermittent aeration regime. The model considers the fluid dynamic and biological processes within the ASR. The biological simulation, which is transient, takes into account the intermittent aeration regime. The CFD modelling is employed for the selection of the aeration system of an ASR. Two different aeration configurations are simulated. The model evaluates the aeration power consumption necessary to satisfy the effluent requirements. An improvement of 2.8% in terms of energy consumption is achieved by modifying the air diffuser layout. An analysis of the influence of the air flow rate per diffuser on the ASR performance is carried out. The results show a reduction of 14.5% in the energy consumption of the aeration system when the air flow rate per diffuser is reduced. The model provides an insight into the aeration inefficiencies produced within ASRs. Copyright © 2018 Elsevier Ltd. All rights reserved.

State of the art of biological hydrogen production processes

International Nuclear Information System (INIS)

Loubette, N.; Junker, M.

2006-01-01

Our report gives an overview of hydrogen production processes with bacteria or algae. 4 main processes are described: water biophotolysis, photo- fermentation biological CO conversion and dark fermentation. Chemical phenomena which lead to hydrogen generation are exp/aired. Performances, limits and outlook are given for each process. Main projects, programs and key players involved in this field of research have been listed. This paper resumes few results of this report. (authors)

State of the art of biological hydrogen production processes

International Nuclear Information System (INIS)

Nicolas Loubette; Michel Junker

2006-01-01

Our report gives an overview of hydrogen production processes with bacteria or algae. 4 main processes are described: water bio-photolysis, photo-fermentation biological CO conversion and dark fermentation. Chemical phenomena which lead to hydrogen generation are explained. Performances, limits and outlook are given for each process. Main projects, programs and key players involved in this field of research have been listed. This paper resumes few results of this report. (authors)

Dynamic light scattering with applications to chemistry, biology, and physics

CERN Document Server

Berne, Bruce J

2000-01-01

Lasers play an increasingly important role in a variety of detection techniques, making inelastic light scattering a tool of growing value in the investigation of dynamic and structural problems in chemistry, biology, and physics. Until the initial publication of this work, however, no monograph treated the principles behind current developments in the field.This volume presents a comprehensive introduction to the principles underlying laser light scattering, focusing on the time dependence of fluctuations in fluid systems; it also serves as an introduction to the theory of time correlation f

How does "not left" become "right"? Electrophysiological evidence for a dynamic conflict-bound negation processing account.

Science.gov (United States)

Dudschig, Carolin; Kaup, Barbara

2018-05-01

Human thought and language is traditionally considered as abstract, amodal, and symbolic. However, recent theories propose that high-level human cognition is directly linked to basic, modal biological systems such as sensorimotor areas. Despite this influential representational debate very little is known regarding whether the mechanisms involved in sensorimotor control are also shared with higher-level cognitive processes, such as language comprehension. We investigated negation as a universal of human language, addressing two key questions: (a) Does negation result in a conflict-like representation? (b) Does negation trigger executive control adjustments in a similar manner as standard information processing conflicts do (e.g., Simon, Flanker)? Electrophysiological data indicated that phrases such as "not left/not right" result in initial activation of the to-be-negated information and subsequently the outcome of the negation process. More importantly, our findings also suggest that negation triggers conflict-related adjustments in information processing in line with traditional conflict tasks. Trial-by-trial conflict adaptation patterns in both behavioral and electrophysiological data indicated that negation processing dynamically changes depending on the current cognitive state. In summary, negation processing results in cognitive conflict, and dynamic influences of the cognitive state determine conflict resolution, that is, negation implementation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Processing laboratory of radio sterilized biological tissues

International Nuclear Information System (INIS)

Aguirre H, Paulina; Zarate S, Herman; Silva R, Samy; Hitschfeld, Mario

2005-01-01

The nuclear development applications have also reached those areas related to health. The risk of getting contagious illnesses through applying biological tissues has been one of the paramount worries to be solved since infectious illnesses might be provoked by virus, fungis or bacterias coming from donors or whether they have been introduced by means of intermediate stages before the use of these tissues. Therefore it has been concluded that the tissue allografts must be sterilized. The sterilization of medical products has been one of the main applications of the ionizing radiations and that it is why the International Organization of Atomic Energy began in the 70s promoting works related to the biological tissue sterilization and pharmaceutical products. The development of different tissue preservation methods has made possible the creation of tissue banks in different countries, to deal with long-term preservation. In our country, a project was launched in 1998, 'Establishment of a Tissue Bank in Latino america', this project was supported by the OIEA through the project INT/ 6/ 049, and was the starting of the actual Processing Laboratory of Radioesterilized Biological Tissues (LPTR), leaded by the Chilean Nuclear Energy Commission (CCHEN). This first organization is part of a number of entities compounding the Tissue Bank in Chile, organizations such as the Transplantation Promotion Corporation hospitals and the LPTR. The working system is carried out by means of the interaction between the hospitals and the laboratory. The medical professionals perform the procuring of tissues in the hospitals, then send them to the LPTR where they are processed and sterilized with ionizing radiation. The cycle ends up with the tissues return released to the hospitals, where they are used, and then the result information is sent to the LPTR as a form of feedback. Up to now, human skin has been processed (64 donors), amniotic membranes (35 donors) and pig skin (175 portions

A spatial-dynamic value transfer model of economic losses from a biological invasion

Science.gov (United States)

Thomas P. Holmes; Andrew M. Liebhold; Kent F. Kovacs; Betsy. Von Holle

2010-01-01

Rigorous assessments of the economic impacts of introduced species at broad spatial scales are required to provide credible information to policy makers. We propose that economic models of aggregate damages induced by biological invasions need to link microeconomic analyses of site-specific economic damages with spatial-dynamic models of value change associated with...

Effects of Bubble-Mediated Processes on Nitrous Oxide Dynamics in Denitrifying Bioreactors

Science.gov (United States)

McGuire, P. M.; Falk, L. M.; Reid, M. C.

2017-12-01

To mitigate groundwater and surface water impacts of reactive nitrogen (N), agricultural and stormwater management practices can employ denitrifying bioreactors (DNBs) as low-cost solutions for enhancing N removal. Due to the variable nature of hydrologic events, DNBs experience dynamic flows which can impact physical and biological processes within the reactors and affect performance. A particular concern is incomplete denitrification, which can release the potent greenhouse gas nitrous oxide (N2O) to the atmosphere. This study aims to provide insight into the effects of varying hydrologic conditions upon the operation of DNBs by disentangling abiotic and biotic controls on denitrification and N2O dynamics within a laboratory-scale bioreactor. We hypothesize that under transient hydrologic flows, rising water levels lead to air entrapment and bubble formation within the DNB porous media. Mass transfer of oxygen (O2) between trapped gas and liquid phases creates aerobic microenvironments that can inhibit N2O reductase (NosZ) enzymes and lead to N2O accumulation. These bubbles also retard N2O transport and make N2O unavailable for biological reduction, further enhancing atmospheric fluxes when water levels fall. The laboratory-scale DNB permits measurements of longitudinal and vertical profiles of dissolved constituents as well as trace gas concentrations in the reactor headspace. We describe a set of experiments quantifying denitrification pathway biokinetics under steady-state and transient hydrologic conditions and evaluate the role of bubble-mediated processes in enhancing N2O accumulation and fluxes. We use sulfur hexafluoride and helium as dissolved gas tracers to examine the impact of bubble entrapment upon retarded gas transport and enhanced trace gas fluxes. A planar optode sensor within the bioreactor provides near-continuous 2-D profiles of dissolved O2 within the bioreactor and allows for identification of aerobic microenvironments. We use qPCR to

Interestingness-Driven Diffusion Process Summarization in Dynamic Networks

DEFF Research Database (Denmark)

Qu, Qiang; Liu, Siyuan; Jensen, Christian S.

2014-01-01

The widespread use of social networks enables the rapid diffusion of information, e.g., news, among users in very large communities. It is a substantial challenge to be able to observe and understand such diffusion processes, which may be modeled as networks that are both large and dynamic. A key...... tool in this regard is data summarization. However, few existing studies aim to summarize graphs/networks for dynamics. Dynamic networks raise new challenges not found in static settings, including time sensitivity and the needs for online interestingness evaluation and summary traceability, which...... render existing techniques inapplicable. We study the topic of dynamic network summarization: how to summarize dynamic networks with millions of nodes by only capturing the few most interesting nodes or edges over time, and we address the problem by finding interestingness-driven diffusion processes...

Simulation and optimization of a coking wastewater biological treatment process by activated sludge models (ASM).

Science.gov (United States)

Wu, Xiaohui; Yang, Yang; Wu, Gaoming; Mao, Juan; Zhou, Tao

2016-01-01

Applications of activated sludge models (ASM) in simulating industrial biological wastewater treatment plants (WWTPs) are still difficult due to refractory and complex components in influents as well as diversity in activated sludges. In this study, an ASM3 modeling study was conducted to simulate and optimize a practical coking wastewater treatment plant (CWTP). First, respirometric characterizations of the coking wastewater and CWTP biomasses were conducted to determine the specific kinetic and stoichiometric model parameters for the consecutive aeration-anoxic-aeration (O-A/O) biological process. All ASM3 parameters have been further estimated and calibrated, through cross validation by the model dynamic simulation procedure. Consequently, an ASM3 model was successfully established to accurately simulate the CWTP performances in removing COD and NH4-N. An optimized CWTP operation condition could be proposed reducing the operation cost from 6.2 to 5.5 €/m(3) wastewater. This study is expected to provide a useful reference for mathematic simulations of practical industrial WWTPs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Rhizosphere Biological Processes of Legume//Cereal Intercropping Systems: A Review

Directory of Open Access Journals (Sweden)

JIANG Yuan-yuan

2016-09-01

Full Text Available Intercropping, a sustainable planting pattern, was widely used in the wordwide. It not only has the advantages of yield and nutrient acquisition, but also can ensure food security and reduce the risk of crop failures. The majority of intercropping systems involve legume//cereal combinations because of interspecific facilitation or complementarity. The rhizosphere is the interface between plants and soil where there are interactions among a myriad of microorganisms and affect the uptake of nutrients, water and harmful substances. The rhizosphere biologi-cal processes not only determine the amount of nutrients and the availability of nutrients, but also affect crop productivity and nutrient use efficiency. Hence, this paper summarized the progress made on root morphology, rhizosphere microorganisms, root exudates and ecological ef-fect in the perspective of the rhizosphere biological process,which would provide theoretical basis for improving nutrient availability, remov-ing heavy metals, and plant genetic improvements.

Parallel computing and molecular dynamics of biological membranes

International Nuclear Information System (INIS)

La Penna, G.; Letardi, S.; Minicozzi, V.; Morante, S.; Rossi, G.C.; Salina, G.

1998-01-01

In this talk I discuss the general question of the portability of molecular dynamics codes for diffusive systems on parallel computers of the APE family. The intrinsic single precision of the today available platforms does not seem to affect the numerical accuracy of the simulations, while the absence of integer addressing from CPU to individual nodes puts strong constraints on possible programming strategies. Liquids can be satisfactorily simulated using the ''systolic'' method. For more complex systems, like the biological ones at which we are ultimately interested in, the ''domain decomposition'' approach is best suited to beat the quadratic growth of the inter-molecular computational time with the number of atoms of the system. The promising perspectives of using this strategy for extensive simulations of lipid bilayers are briefly reviewed. (orig.)

Diurnal rhythmicity in biological processes involved in bioavailability of functional food factors.

Science.gov (United States)

Tsurusaki, Takashi; Sakakibara, Hiroyuki; Aoshima, Yoshiki; Yamazaki, Shunsuke; Sakono, Masanobu; Shimoi, Kayoko

2013-05-01

In the past few decades, many types of functional factors have been identified in dietary foods; for example, flavonoids are major groups widely distributed in the plant kingdom. However, the absorption rates of the functional food factors are usually low, and many of these are difficult to be absorbed in the intact forms because of metabolization by biological processes during absorption. To gain adequate beneficial effects, it is therefore mandatory to know whether functional food factors are absorbed in sufficient quantity, and then reach target organs while maintaining beneficial effects. These are the reasons why the bioavailability of functional food factors has been well investigated using rodent models. Recently, many of the biological processes have been reported to follow diurnal rhythms recurring every 24 h. Therefore, absorption and metabolism of functional food factors influenced by the biological processes may vary with time of day. Consequently, the evaluation of the bioavailability of functional food factors using rodent models should take into consideration the timing of consumption. In this review, we provide a perspective overview of the diurnal rhythm of biological processes involved in the bioavailability of functional food factors, particularly flavonoids.

Application of Solution NMR Spectroscopy to Study Protein Dynamics

Directory of Open Access Journals (Sweden)

Christoph Göbl

2012-03-01

Full Text Available Recent advances in spectroscopic methods allow the identification of minute fluctuations in a protein structure. These dynamic properties have been identified as keys to some biological processes. The consequences of this structural flexibility can be far‑reaching and they add a new dimension to the structure-function relationship of biomolecules. Nuclear Magnetic Resonance (NMR spectroscopy allows the study of structure as well as dynamics of biomolecules in a very broad range of timescales at atomic level. A number of new NMR methods have been developed recently to allow the measurements of time scales and spatial fluctuations, which in turn provide the thermodynamics associated with the biological processes. Since NMR parameters reflect ensemble measurements, structural ensemble approaches in analyzing NMR data have also been developed. These new methods in some instances can even highlight previously hidden conformational features of the biomolecules. In this review we describe several solution NMR methods to study protein dynamics and discuss their impact on important biological processes.

Advances in downstream processing of biologics - Spectroscopy: An emerging process analytical technology.

Science.gov (United States)

Rüdt, Matthias; Briskot, Till; Hubbuch, Jürgen

2017-03-24

Process analytical technologies (PAT) for the manufacturing of biologics have drawn increased interest in the last decade. Besides being encouraged by the Food and Drug Administration's (FDA's) PAT initiative, PAT promises to improve process understanding, reduce overall production costs and help to implement continuous manufacturing. This article focuses on spectroscopic tools for PAT in downstream processing (DSP). Recent advances and future perspectives will be reviewed. In order to exploit the full potential of gathered data, chemometric tools are widely used for the evaluation of complex spectroscopic information. Thus, an introduction into the field will be given. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Shallow water processes govern system-wide phytoplankton bloom dynamics: A modeling study

Science.gov (United States)

Lucas, L.V.; Koseff, Jeffrey R.; Monismith, Stephen G.; Thompson, J.K.

2009-01-01

A pseudo-two-dimensional numerical model of estuarine phytoplankton growth and consumption, vertical turbulent mixing, and idealized cross-estuary transport was developed and applied to South San Francisco Bay. This estuary has two bathymetrically distinct habitat types (deep channel, shallow shoal) and associated differences in local net rates of phytoplankton growth and consumption, as well as differences in the water column's tendency to stratify. Because many physical and biological time scales relevant to algal population dynamics decrease with decreasing depth, process rates can be especially fast in the shallow water. We used the model to explore the potential significance of hydrodynamic connectivity between a channel and shoal and whether lateral transport can allow physical or biological processes (e.g. stratification, benthic grazing, light attenuation) in one sub-region to control phytoplankton biomass and bloom development in the adjacent sub-region. Model results for South San Francisco Bay suggest that lateral transport from a productive shoal can result in phytoplankton biomass accumulation in an adjacent deep, unproductive channel. The model further suggests that turbidity and benthic grazing in the shoal can control the occurrence of a bloom system-wide; whereas, turbidity, benthic grazing, and vertical density stratification in the channel are likely to only control local bloom occurrence or modify system-wide bloom magnitude. Measurements from a related field program are generally consistent with model-derived conclusions. ?? 2008 Elsevier B.V.

Organizational agility key factors for dynamic business process management

OpenAIRE

Triaa , Wafa; Gzara , Lilia; Verjus , Hervé

2016-01-01

International audience; For several years, Business Process Management (BPM) is recognized as a holistic management approach that promotes business effectiveness and efficiency. Increasingly, corporates find themselves, operating in business environments filled with unpredictable, complex and continuous change. Driven by these dynamic competitive conditions, they look for a dynamic management of their business processes to maintain their processes performance. To be competitive, companies hav...

LASER BIOLOGY: Optomechanical tests of hydrated biological tissues subjected to laser shaping

Science.gov (United States)

Omel'chenko, A. I.; Sobol', E. N.

2008-03-01

The mechanical properties of a matrix are studied upon changing the size and shape of biological tissues during dehydration caused by weak laser-induced heating. The cartilage deformation, dehydration dynamics, and hydraulic conductivity are measured upon laser heating. The hydrated state and the shape of samples of separated fascias and cartilaginous tissues were controlled by using computer-aided processing of tissue images in polarised light.

Modeling systems-level dynamics: Understanding without mechanistic explanation in integrative systems biology.

Science.gov (United States)

MacLeod, Miles; Nersessian, Nancy J

2015-02-01

In this paper we draw upon rich ethnographic data of two systems biology labs to explore the roles of explanation and understanding in large-scale systems modeling. We illustrate practices that depart from the goal of dynamic mechanistic explanation for the sake of more limited modeling goals. These processes use abstract mathematical formulations of bio-molecular interactions and data fitting techniques which we call top-down abstraction to trade away accurate mechanistic accounts of large-scale systems for specific information about aspects of those systems. We characterize these practices as pragmatic responses to the constraints many modelers of large-scale systems face, which in turn generate more limited pragmatic non-mechanistic forms of understanding of systems. These forms aim at knowledge of how to predict system responses in order to manipulate and control some aspects of them. We propose that this analysis of understanding provides a way to interpret what many systems biologists are aiming for in practice when they talk about the objective of a "systems-level understanding." Copyright © 2014 Elsevier Ltd. All rights reserved.

A novel theory: biological processes mostly involve two types of mediators, namely general and specific mediators Endogenous small radicals such as superoxide and nitric oxide may play a role of general mediator in biological processes.

Science.gov (United States)

Mo, Jian

2005-01-01

A great number of papers have shown that free radicals as well as bioactive molecules can play a role of mediator in a wide spectrum of biological processes, but the biological actions and chemical reactivity of the free radicals are quite different from that of the bioactive molecules, and that a wide variety of bioactive molecules can be easily modified by free radicals due to having functional groups sensitive to redox, and the significance of the interaction between the free radicals and the bioactive molecules in biological processes has been confirmed by the results of some in vitro and in vivo studies. Based on these evidence, this article presented a novel theory about the mediators of biological processes. The essentials of the theory are: (a) mediators of biological processes can be classified into general and specific mediators; the general mediators include two types of free radicals, namely superoxide and nitric oxide; the specific mediators include a wide variety of bioactive molecules, such as specific enzymes, transcription factors, cytokines and eicosanoids; (b) a general mediator can modify almost any class of the biomolecules, and thus play a role of mediator in nearly every biological process via diverse mechanisms; a specific mediator always acts selectively on certain classes of the biomolecules, and may play a role of mediator in different biological processes via a same mechanism; (c) biological processes are mostly controlled by networks of their mediators, so the free radicals can regulate the last consequence of a biological process by modifying some types of the bioactive molecules, or in cooperation with these bioactive molecules; the biological actions of superoxide and nitric oxide may be synergistic or antagonistic. According to this theory, keeping the integrity of these networks and the balance between the free radicals and the bioactive molecules as well as the balance between the free radicals and the free radical scavengers

Revealing complex function, process and pathway interactions with high-throughput expression and biological annotation data.

Science.gov (United States)

Singh, Nitesh Kumar; Ernst, Mathias; Liebscher, Volkmar; Fuellen, Georg; Taher, Leila

2016-10-20

The biological relationships both between and within the functions, processes and pathways that operate within complex biological systems are only poorly characterized, making the interpretation of large scale gene expression datasets extremely challenging. Here, we present an approach that integrates gene expression and biological annotation data to identify and describe the interactions between biological functions, processes and pathways that govern a phenotype of interest. The product is a global, interconnected network, not of genes but of functions, processes and pathways, that represents the biological relationships within the system. We validated our approach on two high-throughput expression datasets describing organismal and organ development. Our findings are well supported by the available literature, confirming that developmental processes and apoptosis play key roles in cell differentiation. Furthermore, our results suggest that processes related to pluripotency and lineage commitment, which are known to be critical for development, interact mainly indirectly, through genes implicated in more general biological processes. Moreover, we provide evidence that supports the relevance of cell spatial organization in the developing liver for proper liver function. Our strategy can be viewed as an abstraction that is useful to interpret high-throughput data and devise further experiments.

Quantum Information Biology: From Information Interpretation of Quantum Mechanics to Applications in Molecular Biology and Cognitive Psychology

Science.gov (United States)

Asano, Masanari; Basieva, Irina; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro

2015-10-01

We discuss foundational issues of quantum information biology (QIB)—one of the most successful applications of the quantum formalism outside of physics. QIB provides a multi-scale model of information processing in bio-systems: from proteins and cells to cognitive and social systems. This theory has to be sharply distinguished from "traditional quantum biophysics". The latter is about quantum bio-physical processes, e.g., in cells or brains. QIB models the dynamics of information states of bio-systems. We argue that the information interpretation of quantum mechanics (its various forms were elaborated by Zeilinger and Brukner, Fuchs and Mermin, and D' Ariano) is the most natural interpretation of QIB. Biologically QIB is based on two principles: (a) adaptivity; (b) openness (bio-systems are fundamentally open). These principles are mathematically represented in the framework of a novel formalism— quantum adaptive dynamics which, in particular, contains the standard theory of open quantum systems.

Biclustering with Flexible Plaid Models to Unravel Interactions between Biological Processes.

Science.gov (United States)

Henriques, Rui; Madeira, Sara C

2015-01-01

Genes can participate in multiple biological processes at a time and thus their expression can be seen as a composition of the contributions from the active processes. Biclustering under a plaid assumption allows the modeling of interactions between transcriptional modules or biclusters (subsets of genes with coherence across subsets of conditions) by assuming an additive composition of contributions in their overlapping areas. Despite the biological interest of plaid models, few biclustering algorithms consider plaid effects and, when they do, they place restrictions on the allowed types and structures of biclusters, and suffer from robustness problems by seizing exact additive matchings. We propose BiP (Biclustering using Plaid models), a biclustering algorithm with relaxations to allow expression levels to change in overlapping areas according to biologically meaningful assumptions (weighted and noise-tolerant composition of contributions). BiP can be used over existing biclustering solutions (seizing their benefits) as it is able to recover excluded areas due to unaccounted plaid effects and detect noisy areas non-explained by a plaid assumption, thus producing an explanatory model of overlapping transcriptional activity. Experiments on synthetic data support BiP's efficiency and effectiveness. The learned models from expression data unravel meaningful and non-trivial functional interactions between biological processes associated with putative regulatory modules.

The dynamics of stochastic processes

DEFF Research Database (Denmark)

Basse-O'Connor, Andreas

In the present thesis the dynamics of stochastic processes is studied with a special attention to the semimartingale property. This is mainly motivated by the fact that semimartingales provide the class of the processes for which it is possible to define a reasonable stochastic calculus due...... to the Bichteler-Dellacherie Theorem. The semimartingale property of Gaussian processes is characterized in terms of their covariance function, spectral measure and spectral representation. In addition, representation and expansion of filtration results are provided as well. Special attention is given to moving...... average processes, and when the driving process is a Lévy or a chaos process the semimartingale property is characterized in the filtration spanned by the driving process and in the natural filtration when the latter is a Brownian motion. To obtain some of the above results an integrability of seminorm...

Concise Review: Stem Cell Population Biology: Insights from Hematopoiesis.

Science.gov (United States)

MacLean, Adam L; Lo Celso, Cristina; Stumpf, Michael P H

2017-01-01

Stem cells are fundamental to human life and offer great therapeutic potential, yet their biology remains incompletely-or in cases even poorly-understood. The field of stem cell biology has grown substantially in recent years due to a combination of experimental and theoretical contributions: the experimental branch of this work provides data in an ever-increasing number of dimensions, while the theoretical branch seeks to determine suitable models of the fundamental stem cell processes that these data describe. The application of population dynamics to biology is amongst the oldest applications of mathematics to biology, and the population dynamics perspective continues to offer much today. Here we describe the impact that such a perspective has made in the field of stem cell biology. Using hematopoietic stem cells as our model system, we discuss the approaches that have been used to study their key properties, such as capacity for self-renewal, differentiation, and cell fate lineage choice. We will also discuss the relevance of population dynamics in models of stem cells and cancer, where competition naturally emerges as an influential factor on the temporal evolution of cell populations. Stem Cells 2017;35:80-88. © 2016 AlphaMed Press.

Is nanotechnology the key to unravel and engineer biological processes?

Science.gov (United States)

Navarro, Melba; Planell, Josep A

2012-01-01

Regenerative medicine is an emerging field aiming to the development of new reparative strategies to treat degenerative diseases, injury, and trauma through developmental pathways in order to rebuild the architecture of the original injured organ and take over its functionality. Most of the processes and interactions involved in the regenerative process take place at subcellular scale. Nanotechnology provides the tools and technology not only to detect, to measure, or to image the interactions between the different biomolecules and biological entities, but also to control and guide the regenerative process. The relevance of nanotechnology for the development of regenerative medicine as well as an overview of the different tools that contribute to unravel and engineer biological systems are presented in this chapter. In addition, general data about the social impact and global investment in nanotechnology are provided.

Conserving forest biological diversity: How the Montreal Process helps achieve sustainability

Science.gov (United States)

Mark Nelson; Guy Robertson; Kurt. Riitters

2015-01-01

Forests support a variety of ecosystems, species and genes — collectively referred to as biological diversity — along with important processes that tie these all together. With the growing recognition that biological diversity contributes to human welfare in a number of important ways such as providing food, medicine and fiber (provisioning services...

The socially-dynamic entrepreneurial process

DEFF Research Database (Denmark)

Bjerregaard, Toke; Lauring, Jakob

2012-01-01

Large shares of the entrepreneurship research are informed by two central lines of thought. One focuses on the role of formal and informal social networks for mobilising resources and obtaining information about new markets and opportunities. The other conceives of individual personality traits o....... The article thus proposes an approach integrating the social and subjective levels of analysis as part of the same socially-dynamic entrepreneurial process....... or cognitive schemes as the independent variable behind entrepreneurial activity. Elaborating on the socially-dynamic perspectives of anthropological theories, this article presents a coherent theoretical framework for entrepreneurship research embracing the social dimensions as well as individual factors...

Complex biological and bio-inspired systems

Energy Technology Data Exchange (ETDEWEB)

Ecke, Robert E [Los Alamos National Laboratory

2009-01-01

The understanding and characterization ofthe fundamental processes of the function of biological systems underpins many of the important challenges facing American society, from the pathology of infectious disease and the efficacy ofvaccines, to the development of materials that mimic biological functionality and deliver exceptional and novel structural and dynamic properties. These problems are fundamentally complex, involving many interacting components and poorly understood bio-chemical kinetics. We use the basic science of statistical physics, kinetic theory, cellular bio-chemistry, soft-matter physics, and information science to develop cell level models and explore the use ofbiomimetic materials. This project seeks to determine how cell level processes, such as response to mechanical stresses, chemical constituents and related gradients, and other cell signaling mechanisms, integrate and combine to create a functioning organism. The research focuses on the basic physical processes that take place at different levels ofthe biological organism: the basic role of molecular and chemical interactions are investigated, the dynamics of the DNA-molecule and its phylogenetic role are examined and the regulatory networks of complex biochemical processes are modeled. These efforts may lead to early warning algorithms ofpathogen outbreaks, new bio-sensors to detect hazards from pathomic viruses to chemical contaminants. Other potential applications include the development of efficient bio-fuel alternative-energy processes and the exploration ofnovel materials for energy usages. Finally, we use the notion of 'coarse-graining,' which is a method for averaging over less important degrees of freedom to develop computational models to predict cell function and systems-level response to disease, chemical stress, or biological pathomic agents. This project supports Energy Security, Threat Reduction, and the missions of the DOE Office of Science through its efforts to

Safety, Liveness and Run-time Refinement for Modular Process-Aware Information Systems with Dynamic Sub Processes

DEFF Research Database (Denmark)

Debois, Søren; Hildebrandt, Thomas; Slaats, Tijs

2015-01-01

and verification of flexible, run-time adaptable process-aware information systems, moved into practice via the Dynamic Condition Response (DCR) Graphs notation co-developed with our industrial partner. Our key contributions are: (1) A formal theory of dynamic sub-process instantiation for declarative, event......We study modularity, run-time adaptation and refinement under safety and liveness constraints in event-based process models with dynamic sub-process instantiation. The study is part of a larger programme to provide semantically well-founded technologies for modelling, implementation......-based processes under safety and liveness constraints, given as the DCR* process language, equipped with a compositional operational semantics and conservatively extending the DCR Graphs notation; (2) an expressiveness analysis revealing that the DCR* process language is Turing-complete, while the fragment cor...

Biological features produced by additive manufacturing processes using vat photopolymerization method

DEFF Research Database (Denmark)

Davoudinejad, Ali; Mendez Ribo, Macarena; Pedersen, David Bue

2017-01-01

of micro biological features by Additive Manufacturing (AM) processes. The study characterizes the additive manufacturing processes for polymeric micro part productions using the vat photopolymerization method. A specifically designed vat photopolymerization AM machine suitable for precision printing...

Mineralization of 2-chlorophenol by sequential electrochemical reductive dechlorination and biological processes

Energy Technology Data Exchange (ETDEWEB)

Arellano-González, Miguel Ángel; González, Ignacio [Universidad Autónoma Metropolitana-Iztapalapa, Departamento de Química, Av. San Rafael Atlixco No. 186, Col. Vicentina, 09340 Mexico D.F. (Mexico); Texier, Anne-Claire, E-mail: actx@xanum.uam.mx [Universidad Autónoma Metropolitana-Iztapalapa, Departamento de Biotecnología, Av. San Rafael Atlixco No. 186, Col. Vicentina, 09340 Mexico, D.F. (Mexico)

2016-08-15

Highlights: • Dechlorination of 2-chlorophenol to phenol was 100% efficient on Pd-Ni/Ti electrode. • An ECCOCEL reactor was efficient and selective to obtain phenol from 2-chlorophenol. • Phenol was totally mineralized in a coupled denitrifying biorreactor. • Global time of 2-chlorophenol mineralization in the combined system was 7.5 h. - Abstract: In this work, a novel approach was applied to obtain the mineralization of 2-chlorophenol (2-CP) in an electrochemical-biological combined system where an electrocatalytic dehydrogenation process (reductive dechlorination) was coupled to a biological denitrification process. Reductive dechlorination of 2-CP was conducted in an ECCOCEL-type reactor on a Pd-Ni/Ti electrode at a potential of −0.40 V vs Ag/AgCl{sub (s)}/KCl{sub (sat)}, achieving 100 percent transformation of 2-CP into phenol. The electrochemically pretreated effluent was fed to a rotating cylinder denitrifying bioreactor where the totality of phenol was mineralized by denitrification, obtaining CO{sub 2} and N{sub 2} as the end products. The total time required for 2-CP mineralization in the combined electrochemical-biological process was 7.5 h. This value is close to those previously reported for electrochemical and advanced oxidation processes but in this case, an efficient process was obtained without accumulation of by-products or generation of excessive energy costs due to the selective electrochemical pretreatment. This study showed that the use of electrochemical reductive pretreatment combined with biological processes could be a promising technology for the removal of recalcitrant molecules, such as chlorophenols, from wastewaters by more efficient, rapid, and environmentally friendly processes.

WE-DE-202-03: Modeling of Biological Processes - What Happens After Early Molecular Damage?

International Nuclear Information System (INIS)

McMahon, S.

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-202-03: Modeling of Biological Processes - What Happens After Early Molecular Damage?

Energy Technology Data Exchange (ETDEWEB)

McMahon, S. [Massachusetts General Hospital and Harvard Medical School (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

A comparative approach for the investigation of biological information processing: An examination of the structure and function of computer hard drives and DNA

OpenAIRE

D'Onofrio, David J; An, Gary

2010-01-01

Abstract Background The robust storage, updating and utilization of information are necessary for the maintenance and perpetuation of dynamic systems. These systems can exist as constructs of metal-oxide semiconductors and silicon, as in a digital computer, or in the "wetware" of organic compounds, proteins and nucleic acids that make up biological organisms. We propose that there are essential functional properties of centralized information-processing systems; for digital computers these pr...

Radiation processing of biological tissues for nuclear disaster management

International Nuclear Information System (INIS)

Singh, Rita

2012-01-01

A number of surgical procedures require tissue substitutes to repair or replace damaged or diseased tissues. Biological tissues from human donor like bone, skin, amniotic membrane and other soft tissues can be used for repair or reconstruction of the injured part of the body. Tissues from human donor can be processed and banked for orthopaedic, spinal, trauma and other surgical procedures. Allograft tissues provide an excellent alternative to autografts. The use of allograft tissue avoids the donor site morbidity and reduces the operating time, expense and trauma associated with the acquisition of autografts. Further, allografts have the added advantage of being available in large quantities. This has led to a global increase in allogeneic transplantation and development of tissue banking. However, the risk of infectious disease transmission via tissue allografts is a major concern. Therefore, tissue allografts should be sterilized to make them safe for clinical use. Radiation processing has well appreciated technological advantages and is the most suitable method for sterilization of biological tissues. Radiation processed biological tissues can be provided by the tissue banks for the management of injuries due to a nuclear disaster. A nuclear detonation will result in a large number of casualties due to the heat, blast and radiation effects of the weapon. Skin dressings or skin substitutes like allograft skin, xenograft skin and amniotic membrane can be used for the treatment of thermal burns and radiation induced skin injuries. Bone grafts can be employed for repairing fracture defects, filling in destroyed regions of bone, management of open fractures and joint injuries. Radiation processed tissues have the potential to repair or reconstruct damaged tissues and can be of great assistance in the treatment of injuries due to the nuclear weapon. (author)

High Density or Urban Sprawl: What Works Best in Biology?

Science.gov (United States)

Oreopoulos, John; Gray-Owen, Scott D; Yip, Christopher M

2017-02-28

With new approaches in imaging-from new tools or reagents to processing algorithms-come unique opportunities and challenges to our understanding of biological processes, structures, and dynamics. Although innovations in super-resolution imaging are affording novel perspectives into how molecules structurally associate and localize in response to, or in order to initiate, specific signaling events in the cell, questions arise as to how to interpret these observations in the context of biological function. Just as each neighborhood in a city has its own unique vibe, culture, and indeed density, recent work has shown that membrane receptor behavior and action is governed by their localization and association state. There is tremendous potential in developing strategies for tracking how the populations of these molecular neighborhoods change dynamically.

Musashi dynamic image processing system

International Nuclear Information System (INIS)

Murata, Yutaka; Mochiki, Koh-ichi; Taguchi, Akira

1992-01-01

In order to produce transmitted neutron dynamic images using neutron radiography, a real time system called Musashi dynamic image processing system (MDIPS) was developed to collect, process, display and record image data. The block diagram of the MDIPS is shown. The system consists of a highly sensitive, high resolution TV camera driven by a custom-made scanner, a TV camera deflection controller for optimal scanning, which adjusts to the luminous intensity and the moving speed of an object, a real-time corrector to perform the real time correction of dark current, shading distortion and field intensity fluctuation, a real time filter for increasing the image signal to noise ratio, a video recording unit and a pseudocolor monitor to realize recording in commercially available products and monitoring by means of the CRTs in standard TV scanning, respectively. The TV camera and the TV camera deflection controller utilized for producing still images can be applied to this case. The block diagram of the real-time corrector is shown. Its performance is explained. Linear filters and ranked order filters were developed. (K.I.)

Genomic signal processing

CERN Document Server

Shmulevich, Ilya

2007-01-01

Genomic signal processing (GSP) can be defined as the analysis, processing, and use of genomic signals to gain biological knowledge, and the translation of that knowledge into systems-based applications that can be used to diagnose and treat genetic diseases. Situated at the crossroads of engineering, biology, mathematics, statistics, and computer science, GSP requires the development of both nonlinear dynamical models that adequately represent genomic regulation, and diagnostic and therapeutic tools based on these models. This book facilitates these developments by providing rigorous mathema

Linking Polymer Dynamics to Melt Processing

Indian Academy of Sciences (India)

Ashish Lele

Linking Polymer Dynamics to Melt Processing. Ashish Lele. NaUonal Chemical Laboratory, Pune ak.lele@ncl.res.in www.cfpegroup.net. Mid-‐Year MeeUng July 2-‐3, 2010. Indian Academy of Sciences, Bangalore ...

Dynamical "in situ" observation of biological samples using variable pressure scanning electron microscope

Czech Academy of Sciences Publication Activity Database

Neděla, Vilém

2008-01-01

Roč. 126, - (2008), 012046:1-4 ISSN 1742-6588. [Electron Microscopy and Analysis Group Conference 2007 (EMAG 2007). Glasgow, 03.09.2007-07.09.2007] R&D Projects: GA ČR(CZ) GA102/05/0886; GA AV ČR KJB200650602 Institutional research plan: CEZ:AV0Z20650511 Keywords : biological sample * VP-SEM * dynamical experiments Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering

Combined heterogeneous Electro-Fenton and biological process for the treatment of stabilized landfill leachate.

Science.gov (United States)

Baiju, Archa; Gandhimathi, R; Ramesh, S T; Nidheesh, P V

2018-03-15

Treatment of stabilized landfill leachate is a great challenge due to its poor biodegradability. Present study made an attempt to treat this wastewater by combining electro-Fenton (E-Fenton) and biological process. E-Fenton treatment was applied prior to biological process to enhance the biodegradability of leachate, which will be beneficial for the subsequent biological process. This study also investigates the efficiency of iron molybdophosphate (FeMoPO) nanoparticles as a heterogeneous catalyst in E-Fenton process. The effects of initial pH, catalyst dosage, applied voltage and electrode spacing on Chemical Oxygen Demand (COD) removal efficiency were analyzed to determine the optimum conditions. Heterogeneous E-Fenton process gave 82% COD removal at pH 2, catalyst dosage of 50 mg/L, voltage 5 V, electrode spacing 3 cm and electrode area 25 cm 2 . Combined E-Fenton and biological treatment resulted an overall COD removal of 97%, bringing down the final COD to 192 mg/L. Copyright © 2018 Elsevier Ltd. All rights reserved.

Using Simple Manipulatives to Improve Student Comprehension of a Complex Biological Process: Protein Synthesis

Science.gov (United States)

Guzman, Karen; Bartlett, John

2012-01-01

Biological systems and living processes involve a complex interplay of biochemicals and macromolecular structures that can be challenging for undergraduate students to comprehend and, thus, misconceptions abound. Protein synthesis, or translation, is an example of a biological process for which students often hold many misconceptions. This article…

Dynamic Disturbance Processes Create Dynamic Lek Site Selection in a Prairie Grouse.

Directory of Open Access Journals (Sweden)

Torre J Hovick

Full Text Available It is well understood that landscape processes can affect habitat selection patterns, movements, and species persistence. These selection patterns may be altered or even eliminated as a result of changes in disturbance regimes and a concomitant management focus on uniform, moderate disturbance across landscapes. To assess how restored landscape heterogeneity influences habitat selection patterns, we examined 21 years (1991, 1993-2012 of Greater Prairie-Chicken (Tympanuchus cupido lek location data in tallgrass prairie with restored fire and grazing processes. Our study took place at The Nature Conservancy's Tallgrass Prairie Preserve located at the southern extent of Flint Hills in northeastern Oklahoma. We specifically addressed stability of lek locations in the context of the fire-grazing interaction, and the environmental factors influencing lek locations. We found that lek locations were dynamic in a landscape with interacting fire and grazing. While previous conservation efforts have treated leks as stable with high site fidelity in static landscapes, a majority of lek locations in our study (i.e., 65% moved by nearly one kilometer on an annual basis in this dynamic setting. Lek sites were in elevated areas with low tree cover and low road density. Additionally, lek site selection was influenced by an interaction of fire and patch edge, indicating that in recently burned patches, leks were located near patch edges. These results suggest that dynamic and interactive processes such as fire and grazing that restore heterogeneity to grasslands do influence habitat selection patterns in prairie grouse, a phenomenon that is likely to apply throughout the Greater Prairie-Chicken's distribution when dynamic processes are restored. As conservation moves toward restoring dynamic historic disturbance patterns, it will be important that siting and planning of anthropogenic structures (e.g., wind energy, oil and gas and management plans not view lek

The bottom-up approach to defining life : deciphering the functional organization of biological cells via multi-objective representation of biological complexity from molecules to cells

Directory of Open Access Journals (Sweden)

Sathish ePeriyasamy

2013-12-01

Full Text Available In silico representation of cellular systems needs to represent the adaptive dynamics of biological cells, recognizing a cell’s multi-objective topology formed by spatially and temporally cohesive intracellular structures. The design of these models needs to address the hierarchical and concurrent nature of cellular functions and incorporate the ability to self-organise in response to transitions between healthy and pathological phases, and adapt accordingly. The functions of biological systems are constantly evolving, due to the ever changing demands of their environment. Biological systems meet these demands by pursuing objectives, aided by their constituents, giving rise to biological functions. A biological cell is organised into an objective/task hierarchy. These objective hierarchy corresponds to the nested nature of temporally cohesive structures and representing them will facilitate in studying pleiotropy and polygeny by modeling causalities propagating across multiple interconnected intracellular processes. Although biological adaptations occur in physiological, developmental and reproductive timescales, the paper is focused on adaptations that occur within physiological timescales, where the biomolecular activities contributing to functional organisation, play a key role in cellular physiology. The paper proposes a multi-scale and multi-objective modelling approach from the bottom-up by representing temporally cohesive structures for multi-tasking of intracellular processes. Further the paper characterises the properties and constraints that are consequential to the organisational and adaptive dynamics in biological cells.

Network Reconstruction of Dynamic Biological Systems

OpenAIRE

Asadi, Behrang

2013-01-01

Inference of network topology from experimental data is a central endeavor in biology, since knowledge of the underlying signaling mechanisms a requirement for understanding biological phenomena. As one of the most important tools in bioinformatics area, development of methods to reconstruct biological networks has attracted remarkable attention in the current decade. Integration of different data types can lead to remarkable improvements in our ability to identify the connectivity of differe...

DYNSIR; A dynamic simulator for the chemical process

International Nuclear Information System (INIS)

Park, Hyun Soo; Yoo, Jae Hyung; Byeon, Kee Hoh; Park, Jeong Hwa; Park, Seong Won

1990-03-01

A program code for dynamic simulation of arbitrary chemical process, called DYNSIR, is developed. The code can simulate rather arbitrary arrangements of individual chemical processing units whose models are described by ordinary differential equations. The code structure to handle input/output, memory and data management, numerical interactive or predetermined changes in parameter values during the simulation. Individual model is easy to maintain since the modular approach is used. The integration routine is highly effective because of the development of algorithm for modular integration method using the cubic spline. DYNSIR's data structures are not the index but the pointer structure. This pointer structure allows the dynamic memory allocation for the memory management. The dynamic memory allocation methods is to minimize the amount of memories and to overcome the limitation of the number of variables to be used. Finally, it includes various functions, such as the input preprocessor, the effective error processing, and plotting and reporting routines. (author)

The relativity of biological function.

Science.gov (United States)

Laubichler, Manfred D; Stadler, Peter F; Prohaska, Sonja J; Nowick, Katja

2015-12-01

Function is a central concept in biological theories and explanations. Yet discussions about function are often based on a narrow understanding of biological systems and processes, such as idealized molecular systems or simple evolutionary, i.e., selective, dynamics. Conflicting conceptions of function continue to be used in the scientific literature to support certain claims, for instance about the fraction of "functional DNA" in the human genome. Here we argue that all biologically meaningful interpretations of function are necessarily context dependent. This implies that they derive their meaning as well as their range of applicability only within a specific theoretical and measurement context. We use this framework to shed light on the current debate about functional DNA and argue that without considering explicitly the theoretical and measurement contexts all attempts to integrate biological theories are prone to fail.

Dynamics robustness of cascading systems.

Directory of Open Access Journals (Sweden)

Jonathan T Young

2017-03-01

Full Text Available A most important property of biochemical systems is robustness. Static robustness, e.g., homeostasis, is the insensitivity of a state against perturbations, whereas dynamics robustness, e.g., homeorhesis, is the insensitivity of a dynamic process. In contrast to the extensively studied static robustness, dynamics robustness, i.e., how a system creates an invariant temporal profile against perturbations, is little explored despite transient dynamics being crucial for cellular fates and are reported to be robust experimentally. For example, the duration of a stimulus elicits different phenotypic responses, and signaling networks process and encode temporal information. Hence, robustness in time courses will be necessary for functional biochemical networks. Based on dynamical systems theory, we uncovered a general mechanism to achieve dynamics robustness. Using a three-stage linear signaling cascade as an example, we found that the temporal profiles and response duration post-stimulus is robust to perturbations against certain parameters. Then analyzing the linearized model, we elucidated the criteria of when signaling cascades will display dynamics robustness. We found that changes in the upstream modules are masked in the cascade, and that the response duration is mainly controlled by the rate-limiting module and organization of the cascade's kinetics. Specifically, we found two necessary conditions for dynamics robustness in signaling cascades: 1 Constraint on the rate-limiting process: The phosphatase activity in the perturbed module is not the slowest. 2 Constraints on the initial conditions: The kinase activity needs to be fast enough such that each module is saturated even with fast phosphatase activity and upstream changes are attenuated. We discussed the relevance of such robustness to several biological examples and the validity of the above conditions therein. Given the applicability of dynamics robustness to a variety of systems, it

Informing biological design by integration of systems and synthetic biology.

Science.gov (United States)

Smolke, Christina D; Silver, Pamela A

2011-03-18

Synthetic biology aims to make the engineering of biology faster and more predictable. In contrast, systems biology focuses on the interaction of myriad components and how these give rise to the dynamic and complex behavior of biological systems. Here, we examine the synergies between these two fields. Copyright © 2011 Elsevier Inc. All rights reserved.

Moving beyond a descriptive aquatic toxicology: the value of biological process and trait information.

Science.gov (United States)

Segner, Helmut

2011-10-01

In order to improve the ability to link chemical exposure to toxicological and ecological effects, aquatic toxicology will have to move from observing what chemical concentrations induce adverse effects to more explanatory approaches, that are concepts which build on knowledge of biological processes and pathways leading from exposure to adverse effects, as well as on knowledge on stressor vulnerability as given by the genetic, physiological and ecological (e.g., life history) traits of biota. Developing aquatic toxicology in this direction faces a number of challenges, including (i) taking into account species differences in toxicant responses on the basis of the evolutionarily developed diversity of phenotypic vulnerability to environmental stressors, (ii) utilizing diversified biological response profiles to serve as biological read across for prioritizing chemicals, categorizing them according to modes of action, and for guiding targeted toxicity evaluation; (iii) prediction of ecological consequences of toxic exposure from knowledge of how biological processes and phenotypic traits lead to effect propagation across the levels of biological hierarchy; and (iv) the search for concepts to assess the cumulative impact of multiple stressors. An underlying theme in these challenges is that, in addition to the question of what the chemical does to the biological receptor, we should give increasing emphasis to the question how the biological receptor handles the chemicals, i.e., through which pathways the initial chemical-biological interaction extends to the adverse effects, how this extension is modulated by adaptive or compensatory processes as well as by phenotypic traits of the biological receptor. 2011 Elsevier B.V. All rights reserved.

BioModels Database: a repository of mathematical models of biological processes.

Science.gov (United States)

Chelliah, Vijayalakshmi; Laibe, Camille; Le Novère, Nicolas

2013-01-01

BioModels Database is a public online resource that allows storing and sharing of published, peer-reviewed quantitative, dynamic models of biological processes. The model components and behaviour are thoroughly checked to correspond the original publication and manually curated to ensure reliability. Furthermore, the model elements are annotated with terms from controlled vocabularies as well as linked to relevant external data resources. This greatly helps in model interpretation and reuse. Models are stored in SBML format, accepted in SBML and CellML formats, and are available for download in various other common formats such as BioPAX, Octave, SciLab, VCML, XPP and PDF, in addition to SBML. The reaction network diagram of the models is also available in several formats. BioModels Database features a search engine, which provides simple and more advanced searches. Features such as online simulation and creation of smaller models (submodels) from the selected model elements of a larger one are provided. BioModels Database can be accessed both via a web interface and programmatically via web services. New models are available in BioModels Database at regular releases, about every 4 months.

Image processing and recognition for biological images.

Science.gov (United States)

Uchida, Seiichi

2013-05-01

This paper reviews image processing and pattern recognition techniques, which will be useful to analyze bioimages. Although this paper does not provide their technical details, it will be possible to grasp their main tasks and typical tools to handle the tasks. Image processing is a large research area to improve the visibility of an input image and acquire some valuable information from it. As the main tasks of image processing, this paper introduces gray-level transformation, binarization, image filtering, image segmentation, visual object tracking, optical flow and image registration. Image pattern recognition is the technique to classify an input image into one of the predefined classes and also has a large research area. This paper overviews its two main modules, that is, feature extraction module and classification module. Throughout the paper, it will be emphasized that bioimage is a very difficult target for even state-of-the-art image processing and pattern recognition techniques due to noises, deformations, etc. This paper is expected to be one tutorial guide to bridge biology and image processing researchers for their further collaboration to tackle such a difficult target. © 2013 The Author Development, Growth & Differentiation © 2013 Japanese Society of Developmental Biologists.

Composting of the solid fraction of digestate derived from pig slurry: Biological processes and compost properties

Energy Technology Data Exchange (ETDEWEB)

Tambone, Fulvia, E-mail: fulvia.tambone@unimi.it; Terruzzi, Laura; Scaglia, Barbara; Adani, Fabrizio

2015-01-15

Highlights: • Anaerobic digestion leads to the production of a biologically stable digestate. • Solid–liquid separation produces a solid fraction having high fertilizer value. • Composting process shows low biological activity due to high biological stability of digestate. • Solid digestate fraction can be composted in a short time or used directly as organic fertilizer. - Abstract: The aim of this paper was to assess the characteristics of the solid fractions (SF) obtained by mechanical separation of digestate, their compostability and compost quality. To do so, the SF of digestates obtained from anaerobic digestion of pig slurry, energy crops and agro-industrial residues were sampled in five plants located in Northern Italy. Results obtained indicated that anaerobic digestion by itself promoted the high biological stability of biomasses with a Potential Dynamic Respiration Index (PDRI) close to 1000 mgO{sub 2} kg V S{sup −1} h{sup −1}. Subsequent composting of digestates, with an added bulking agent, did not give remarkably different results, and led only to a slight modification of the characteristics of the initial non-composted mixtures; the composts obtained fully respected the legal limits for high quality compost. Chemical studies of organic matter composition of the biomasses by using CP MAS {sup 13}C NMR, indicated that the compost was composed of a high relative content of O-alkyl-C (71.47% of total C) (cellulose and hemicelluloses) and a low alkyl-C (12.42%) (i.e. volatile fatty acids, steroid-like molecules, aliphatic biopolymers and proteins)

Composting of the solid fraction of digestate derived from pig slurry: Biological processes and compost properties

International Nuclear Information System (INIS)

Tambone, Fulvia; Terruzzi, Laura; Scaglia, Barbara; Adani, Fabrizio

2015-01-01

Highlights: • Anaerobic digestion leads to the production of a biologically stable digestate. • Solid–liquid separation produces a solid fraction having high fertilizer value. • Composting process shows low biological activity due to high biological stability of digestate. • Solid digestate fraction can be composted in a short time or used directly as organic fertilizer. - Abstract: The aim of this paper was to assess the characteristics of the solid fractions (SF) obtained by mechanical separation of digestate, their compostability and compost quality. To do so, the SF of digestates obtained from anaerobic digestion of pig slurry, energy crops and agro-industrial residues were sampled in five plants located in Northern Italy. Results obtained indicated that anaerobic digestion by itself promoted the high biological stability of biomasses with a Potential Dynamic Respiration Index (PDRI) close to 1000 mgO 2 kg V S −1 h −1 . Subsequent composting of digestates, with an added bulking agent, did not give remarkably different results, and led only to a slight modification of the characteristics of the initial non-composted mixtures; the composts obtained fully respected the legal limits for high quality compost. Chemical studies of organic matter composition of the biomasses by using CP MAS 13 C NMR, indicated that the compost was composed of a high relative content of O-alkyl-C (71.47% of total C) (cellulose and hemicelluloses) and a low alkyl-C (12.42%) (i.e. volatile fatty acids, steroid-like molecules, aliphatic biopolymers and proteins)

In Silico Dynamics: computer simulation in a Virtual Embryo (SOT)

Science.gov (United States)

Abstract: Utilizing cell biological information to predict higher order biological processes is a significant challenge in predictive toxicology. This is especially true for highly dynamical systems such as the embryo where morphogenesis, growth and differentiation require preci...

Process dynamics, advantage and difficulties of investigations

International Nuclear Information System (INIS)

Oude-Hengel, H.H.; Geigle, F.W.; Drucks, G.

1974-01-01

Process models, amongst other things, are designed to inform about stressability of power plants. This paper introduces some of the most important models and assesses them. Mathematical results concerning a turbine trip incident are made clear. Finally some of the problems are dealt with which occur while investigating process dynamics. (orig./RW) [de

Psychosis and the dynamics of the psychotherapy process

DEFF Research Database (Denmark)

Rosenbaum, Bent; Harder, Susanne

2007-01-01

The role of psychotherapy in the treatment of psychoses remains controversial but there is improving acceptance that an understanding of the dynamics of the psychological processes involved in treatment and in the disorder itself may be important. Psychosis is understood as a detachment of the 's......The role of psychotherapy in the treatment of psychoses remains controversial but there is improving acceptance that an understanding of the dynamics of the psychological processes involved in treatment and in the disorder itself may be important. Psychosis is understood as a detachment...

Detection of microparticles in dynamic processes

International Nuclear Information System (INIS)

Ten, K A; Pruuel, E R; Kashkarov, A O; Rubtsov, I A; Shechtman, L I; Zhulanov, V V; Tolochko, B P; Rykovanov, G N; Muzyrya, A K; Smirnov, E B; Stolbikov, M Yu; Prosvirnin, K M

2016-01-01

When a metal plate is subjected to a strong shock impact, its free surface emits a flow of particles of different sizes (shock-wave “dusting”). Traditionally, the process of dusting is investigated by the methods of pulsed x-ray or piezoelectric sensor or via an optical technique. The particle size ranges from a few microns to hundreds of microns. The flow is assumed to include also finer particles, which cannot be detected with the existing methods yet. On the accelerator complex VEPP-3-VEPP-4 at the BINP there are two experiment stations for research on fast processes, including explosion ones. The stations enable measurement of both passed radiation (absorption) and small-angle x-ray scattering on synchrotron radiation (SR). Radiation is detected with a precision high-speed detector DIMEX. The detector has an internal memory of 32 frames, which enables recording of the dynamics of the process (shooting of movies) with intervals of 250 ns to 2 μ s. Flows of nano- and microparticles from free surfaces of various materials (copper and tin) have been examined. Microparticle flows were emitted from grooves of 50-200 μ s in size and joints (gaps) between metal parts. With the soft x-ray spectrum of SR one can explore the dynamics of a single microjet of micron size. The dynamics of density distribution along micro jets were determined. Under a shock wave (∼ 60 GPa) acting on tin disks, flows of microparticles from a smooth surface were recorded. (paper)

Biological soil crusts across disturbance–recovery scenarios: effect of grazing regime on community dynamics.

Science.gov (United States)

Concostrina-Zubiri, L; Huber-Sannwald, E; Martínez, I; Flores Flores, J L; Reyes-Agüero, J A; Escude, A; Belnap, J

Grazing represents one of the most common disturbances in drylands worldwide, affecting both ecosystem structure and functioning. Despite the efforts to understand the nature and magnitude of grazing effects on ecosystem components and processes, contrasting results continue to arise. This is particularly remarkable for the biological soil crust (BSC) communities (i.e., cyanobacteria, lichens, and bryophytes), which play an important role in soil dynamics. Here we evaluated simultaneously the effect of grazing impact on BSC communities (resistance) and recovery after livestock exclusion (resilience) in a semiarid grassland of Central Mexico. In particular, we examined BSC species distribution, species richness, taxonomical group cover (i.e., cyanobacteria, lichen, bryophyte), and composition along a disturbance gradient with different grazing regimes (low, medium, high impact) and along a recovery gradient with differently aged livestock exclosures (short-, medium-, long-term exclusion). Differences in grazing impact and time of recovery from grazing both resulted in slight changes in species richness; however, there were pronounced shifts in species composition and group cover. We found we could distinguish four highly diverse and dynamic BSC species groups: (1) species with high resistance and resilience to grazing, (2) species with high resistance but low resilience, (3) species with low resistance but high resilience, and (4) species with low resistance and resilience. While disturbance resulted in a novel diversity configuration, which may profoundly affect ecosystem functioning, we observed that 10 years of disturbance removal did not lead to the ecosystem structure found after 27 years of recovery. These findings are an important contribution to our understanding of BCS dynamics from a species and community perspective placed in a land use change context.

Biological soil crusts across disturbance-recovery scenarios: effect of grazing regime on community dynamics

Science.gov (United States)

Concostrina-Zubiri, L.; Huber-Sannwald, E.; Martínez, I.; Flores Flores, J. L.; Reyes-Agüero, J. A.; Escudero, A.; Belnap, Jayne

2014-01-01

Grazing represents one of the most common disturbances in drylands worldwide, affecting both ecosystem structure and functioning. Despite the efforts to understand the nature and magnitude of grazing effects on ecosystem components and processes, contrasting results continue to arise. This is particularly remarkable for the biological soil crust (BSC) communities (i.e., cyanobacteria, lichens, and bryophytes), which play an important role in soil dynamics. Here we evaluated simultaneously the effect of grazing impact on BSC communities (resistance) and recovery after livestock exclusion (resilience) in a semiarid grassland of Central Mexico. In particular, we examined BSC species distribution, species richness, taxonomical group cover (i.e., cyanobacteria, lichen, bryophyte), and composition along a disturbance gradient with different grazing regimes (low, medium, high impact) and along a recovery gradient with differently aged livestock exclosures (short-, medium-, long-term exclusion). Differences in grazing impact and time of recovery from grazing both resulted in slight changes in species richness; however, there were pronounced shifts in species composition and group cover. We found we could distinguish four highly diverse and dynamic BSC species groups: (1) species with high resistance and resilience to grazing, (2) species with high resistance but low resilience, (3) species with low resistance but high resilience, and (4) species with low resistance and resilience. While disturbance resulted in a novel diversity configuration, which may profoundly affect ecosystem functioning, we observed that 10 years of disturbance removal did not lead to the ecosystem structure found after 27 years of recovery. These findings are an important contribution to our understanding of BCS dynamics from a species and community perspective placed in a land use change context.

A non-homogeneous dynamic Bayesian network with sequentially coupled interaction parameters for applications in systems and synthetic biology.

Science.gov (United States)

Grzegorczyk, Marco; Husmeier, Dirk

2012-07-12

An important and challenging problem in systems biology is the inference of gene regulatory networks from short non-stationary time series of transcriptional profiles. A popular approach that has been widely applied to this end is based on dynamic Bayesian networks (DBNs), although traditional homogeneous DBNs fail to model the non-stationarity and time-varying nature of the gene regulatory processes. Various authors have therefore recently proposed combining DBNs with multiple changepoint processes to obtain time varying dynamic Bayesian networks (TV-DBNs). However, TV-DBNs are not without problems. Gene expression time series are typically short, which leaves the model over-flexible, leading to over-fitting or inflated inference uncertainty. In the present paper, we introduce a Bayesian regularization scheme that addresses this difficulty. Our approach is based on the rationale that changes in gene regulatory processes appear gradually during an organism's life cycle or in response to a changing environment, and we have integrated this notion in the prior distribution of the TV-DBN parameters. We have extensively tested our regularized TV-DBN model on synthetic data, in which we have simulated short non-homogeneous time series produced from a system subject to gradual change. We have then applied our method to real-world gene expression time series, measured during the life cycle of Drosophila melanogaster, under artificially generated constant light condition in Arabidopsis thaliana, and from a synthetically designed strain of Saccharomyces cerevisiae exposed to a changing environment.

Alternating event processes during lifetimes: population dynamics and statistical inference.

Science.gov (United States)

Shinohara, Russell T; Sun, Yifei; Wang, Mei-Cheng

2018-01-01

In the literature studying recurrent event data, a large amount of work has been focused on univariate recurrent event processes where the occurrence of each event is treated as a single point in time. There are many applications, however, in which univariate recurrent events are insufficient to characterize the feature of the process because patients experience nontrivial durations associated with each event. This results in an alternating event process where the disease status of a patient alternates between exacerbations and remissions. In this paper, we consider the dynamics of a chronic disease and its associated exacerbation-remission process over two time scales: calendar time and time-since-onset. In particular, over calendar time, we explore population dynamics and the relationship between incidence, prevalence and duration for such alternating event processes. We provide nonparametric estimation techniques for characteristic quantities of the process. In some settings, exacerbation processes are observed from an onset time until death; to account for the relationship between the survival and alternating event processes, nonparametric approaches are developed for estimating exacerbation process over lifetime. By understanding the population dynamics and within-process structure, the paper provide a new and general way to study alternating event processes.

Flight Dynamic Simulation of Fighter In the Asymmetric External Store Release Process

Science.gov (United States)

Safi’i, Imam; Arifianto, Ony; Nurohman, Chandra

2018-04-01

In the fighter design, it is important to evaluate and analyze the flight dynamic of the aircraft earlier in the development process. One of the case is the dynamics of external store release process. A simulation tool can be used to analyze the fighter/external store system’s dynamics in the preliminary design stage. This paper reports the flight dynamics of Jet Fighter Experiment (JF-1 E) in asymmetric Advance Medium Range Air to Air Missile (AMRAAM) release process through simulations. The JF-1 E and AIM 120 AMRAAAM models are built by using Advanced Aircraft Analysis (AAA) and Missile Datcom software. By using these softwares, the aerodynamic stability and control derivatives can be obtained and used to model the dynamic characteristic of the fighter and the external store. The dynamic system is modeled by using MATLAB/Simulink software. By using this software, both the fighter/external store integration and the external store release process is simulated, and the dynamic of the system can be analyzed.

Dynamic processes of the microbiota - from metagenomics to biofilms

Science.gov (United States)

Wingreen, Ned

The extent, origin, and impact of microbial diversity is a central question in biology. We expect that physical processes contribute to this diversity, but we are only beginning to explore the nature of these interactions. I will briefly discuss two approaches to this question, one based on metagenomics the other on observation of bacterial biofilms. First, I will address the challenge of identifying the constituents of microbial systems by presenting a new approach to analyzing community sequencing data that identifies microbial subpopulations while avoiding problematic clustering-based methods. Using data from a time-series study of human tongue microbiota, we were able to resolve within the standard definition of a ``species'' up to 20 ecologically distinct subpopulations with tag sequences differing by as little as one nucleotide (99.2% similarity). This fine resolution allowed us decouple sequence similarity from dynamical similarity, and to resolve dynamics on multiple time scales, including the slow appearance and disappearance of strains over months. Second, I will present recent results on the growth and competition of bacteria within biofilms. We imaged the growth ofliving biofilms of Vibrio choleraefrom single founder cells to ten thousand cells at single cell spatial resolution and with temporal resolution of one cell cycle. We discovered a transition from a branched 2D colony to a dense 3D cluster, in which cells at the biofilm center exhibit collective vertical alignment and local nematic packing. Our results suggest that biofilm cells exploit mechanics to simultaneously achieve strong surface adhesion, access to 3D space, resistance to invasion, and dominance over surface territory.

Psychosis and the dynamics of the psychotherapy process

DEFF Research Database (Denmark)

Rosenbaum, Bent; Harder, Susanne

2007-01-01

The role of psychotherapy in the treatment of psychoses remains controversial but there is improving acceptance that an understanding of the dynamics of the psychological processes involved in treatment and in the disorder itself may be important. Psychosis is understood as a detachment of the 's......The role of psychotherapy in the treatment of psychoses remains controversial but there is improving acceptance that an understanding of the dynamics of the psychological processes involved in treatment and in the disorder itself may be important. Psychosis is understood as a detachment......-subjective process, a therapeutic relationship is disrupted and a therapeutic alliance is not assured. Therapists have to pay particular attention to the empathic aspects of the interaction as they attempt to integrate affects to restore meaning to the inner life of the patient. The psychodynamics of this process...

Optomechanical tests of hydrated biological tissues subjected to laser shaping

International Nuclear Information System (INIS)

Omel'chenko, A I; Sobol', E N

2008-01-01

The mechanical properties of a matrix are studied upon changing the size and shape of biological tissues during dehydration caused by weak laser-induced heating. The cartilage deformation, dehydration dynamics, and hydraulic conductivity are measured upon laser heating. The hydrated state and the shape of samples of separated fascias and cartilaginous tissues were controlled by using computer-aided processing of tissue images in polarised light. (laser biology)

Economic Analysis of Biological Invasions in Forests

Science.gov (United States)

Tomas P. Holmes; Julian Aukema; Jeffrey Englin; Robert G. Haight; Kent Kovacs; Brian Leung

2014-01-01

Biological invasions of native forests by nonnative pests result from complex stochastic processes that are difficult to predict. Although economic optimization models describe efficient controls across the stages of an invasion, the ability to calibrate such models is constrained by lack of information on pest population dynamics and consequent economic damages. Here...

Respirometry applied for biological nitrogen removal process; Aplicacion de la respirometria al tratamiento biologico para la eliminacion del nitrogeno

Energy Technology Data Exchange (ETDEWEB)

Serrano, E.

2004-07-01

In waste water treatment plants, the Biological Nitrogen Removal (BNR) has acquired a fundamental importance. The BNR processes are Nitrification ( aerobic) and Denitrification (anoxic). Since both processes are carried on living microorganisms, a lack of their bioactivity information might cause serious confusion about their control criteria and following up purposes. For this reason, the Re spirometry applied to those processes has reached an important role by getting an essential information in a timely manner through respiration rate measurements in static and dynamic modes and applications such as AUR (Ammonium Uptake Rate), Nitrification Capacity. RBCOD (Readily Biodegradable COD) as well as AUR related to SRT (Sludge age), RBCOD related to NUR (Specific Nitrate Uptake Rate) and others. By other side in this article we have introduced a not very well known applications related to denitrification, about the methanol acclimatization and generated bioactivity. (Author) 6 refs.

Information processing and dynamics in minimally cognitive agents.

Science.gov (United States)

Beer, Randall D; Williams, Paul L

2015-01-01

There has been considerable debate in the literature about the relative merits of information processing versus dynamical approaches to understanding cognitive processes. In this article, we explore the relationship between these two styles of explanation using a model agent evolved to solve a relational categorization task. Specifically, we separately analyze the operation of this agent using the mathematical tools of information theory and dynamical systems theory. Information-theoretic analysis reveals how task-relevant information flows through the system to be combined into a categorization decision. Dynamical analysis reveals the key geometrical and temporal interrelationships underlying the categorization decision. Finally, we propose a framework for directly relating these two different styles of explanation and discuss the possible implications of our analysis for some of the ongoing debates in cognitive science. Copyright © 2014 Cognitive Science Society, Inc.

Visualization in simulation tools: requirements and a tool specification to support the teaching of dynamic biological processes.

Science.gov (United States)

Jørgensen, Katarina M; Haddow, Pauline C

2011-08-01

Simulation tools are playing an increasingly important role behind advances in the field of systems biology. However, the current generation of biological science students has either little or no experience with such tools. As such, this educational glitch is limiting both the potential use of such tools as well as the potential for tighter cooperation between the designers and users. Although some simulation tool producers encourage their use in teaching, little attempt has hitherto been made to analyze and discuss their suitability as an educational tool for noncomputing science students. In general, today's simulation tools assume that the user has a stronger mathematical and computing background than that which is found in most biological science curricula, thus making the introduction of such tools a considerable pedagogical challenge. This paper provides an evaluation of the pedagogical attributes of existing simulation tools for cell signal transduction based on Cognitive Load theory. Further, design recommendations for an improved educational simulation tool are provided. The study is based on simulation tools for cell signal transduction. However, the discussions are relevant to a broader biological simulation tool set.

Systems Biology of the Fluxome

Directory of Open Access Journals (Sweden)

Miguel A. Aon

2015-07-01

Full Text Available The advent of high throughput -omics has made the accumulation of comprehensive data sets possible, consisting of changes in genes, transcripts, proteins and metabolites. Systems biology-inspired computational methods for translating metabolomics data into fluxomics provide a direct functional, dynamic readout of metabolic networks. When combined with appropriate experimental design, these methods deliver insightful knowledge about cellular function under diverse conditions. The use of computational models accounting for detailed kinetics and regulatory mechanisms allow us to unravel the control and regulatory properties of the fluxome under steady and time-dependent behaviors. This approach extends the analysis of complex systems from description to prediction, including control of complex dynamic behavior ranging from biological rhythms to catastrophic lethal arrhythmias. The powerful quantitative metabolomics-fluxomics approach will help our ability to engineer unicellular and multicellular organisms evolve from trial-and-error to a more predictable process, and from cells to organ and organisms.

Systems biology approach to bioremediation

Energy Technology Data Exchange (ETDEWEB)

Chakraborty, Romy; Wu, Cindy H.; Hazen, Terry C.

2012-06-01

Bioremediation has historically been approached as a ‘black box’ in terms of our fundamental understanding. Thus it succeeds and fails, seldom without a complete understanding of why. Systems biology is an integrated research approach to study complex biological systems, by investigating interactions and networks at the molecular, cellular, community, and ecosystem level. The knowledge of these interactions within individual components is fundamental to understanding the dynamics of the ecosystem under investigation. Finally, understanding and modeling functional microbial community structure and stress responses in environments at all levels have tremendous implications for our fundamental understanding of hydrobiogeochemical processes and the potential for making bioremediation breakthroughs and illuminating the ‘black box’.

DEMONSTRATION OF AN INTEGRATED, PASSIVE BIOLOGICAL TREATMENT PROCESS FOR AMD

Science.gov (United States)

An innovative, cost-effective, biological treatment process has been designed by MSE Technology Applications, Inc. to treat acid mine drainage (AMD). A pilot-scale demonstration is being conducted under the Mine Waste Technology Program using water flowing from an abandoned mine ...

Effect of Process-Oriented Guided-Inquiry Learning on Non-majors Biology Students' Understanding of Biological Classification

Science.gov (United States)

Wozniak, Breann M.

The purpose of this study was to examine the effect of process-oriented guided-inquiry learning (POGIL) on non-majors college biology students' understanding of biological classification. This study addressed an area of science instruction, POGIL in the non-majors college biology laboratory, which has yet to be qualitatively and quantitatively researched. A concurrent triangulation mixed methods approach was used. Students' understanding of biological classification was measured in two areas: scores on pre and posttests (consisting of 11 multiple choice questions), and conceptions of classification as elicited in pre and post interviews and instructor reflections. Participants were Minnesota State University, Mankato students enrolled in BIOL 100 Summer Session. One section was taught with the traditional curriculum (n = 6) and the other section in the POGIL curriculum (n = 10) developed by the researcher. Three students from each section were selected to take part in pre and post interviews. There were no significant differences within each teaching method (p familiar animal categories and aquatic habitats, unfamiliar organisms, combining and subdividing initial groupings, and the hierarchical nature of classification. The POGIL students were the only group to surpass these challenges after the teaching intervention. This study shows that POGIL is an effective technique at eliciting students' misconceptions, and addressing these misconceptions, leading to an increase in student understanding of biological classification.

Synthesis of C-di-saccharidic compounds by radical cyclisation. Study of biological, structural and dynamic properties

International Nuclear Information System (INIS)

Rubinstenn, Gilles

1996-01-01

The synthesis of carbohydrate mimics and particularly of C-disaccharides, molecules in which the inter-glycosidic oxygen atom has been replaced by a methylene group, has become, this past two decades, an important challenge in organic chemistry. In the first chapter we present the synthesis of C-disaccharides from the neutral series by a silaketal tethering. The key step of this C-glycosylation is a radical macro-cyclisation. This strategy is applied to the synthesis of two analogues of natural, biologically active, products, the lactose and the Lewis x tri-saccharide. The biological activity of this mimetics is then evaluated. A new tethering strategy, based on the use of phosphorus III compounds, is applied, in the second chapter, to the building of C-disaccharides of the 2'-amino 2'- deoxy series. The third chapter deals with the structural and dynamics study of the C-glycosides prepared in chapter 1 by Nuclear Magnetic Resonance. A new methodology, studying the dipolar relaxation along an effective field, generated through an off-resonance RF field, allowed the precise measurement of longitudinal and transverse cross-relaxation rates. Structural and dynamics parameter thus derived are used as restraints for molecular modeling. The results of this study are then compared to those of the biological tests. (author) [fr

Becoming a Learning Organization Through Dynamic Business Process Management

Directory of Open Access Journals (Sweden)

Marek Szelągowski

2014-01-01

Full Text Available As customers demand easier access to individualized products and services, companies now face an ongoing problem of how to deliver flexible and innovative solutions while maintaining efficiency and competitiveness. In this environment, the only sustainable form of competitive advantage rests in the ability to learn faster than the competition (de Geus, 1988. The article returns to the somewhat forgotten concept of the learning organization and explores how its principles can be applied with the use of dynamic business process management (dynamic BPM. Enabling in this concept individual or team-based limited experimentation and providing conditions for learning though experience in the course of performing business processes allows for the constant creation of practical knowledge. This article provides examples of how dynamic BPM facilitates the constant creation and verification of practical knowledge, with the aim of improving and adapting processes to maintain the competitive advantage of the organization.

Observation of dehydration dynamics in biological tissues with terahertz digital holography [Invited].

Science.gov (United States)

Guo, Lihan; Wang, Xinke; Han, Peng; Sun, Wenfeng; Feng, Shengfei; Ye, Jiasheng; Zhang, Yan

2017-05-01

A terahertz (THz) digital holographic imaging system is utilized to investigate natural dehydration processes in three types of biological tissues, including cattle, mutton, and pork. An image reconstruction algorithm is applied to remove the diffraction influence of THz waves and further improve clarity of THz images. From THz images of different biological specimens, distinctive water content as well as dehydration features of adipose and muscle tissues are precisely distinguished. By analyzing THz absorption spectra of these samples, temporal evolution characteristics of the absorbances for adipose and muscle tissues are described and compared in detail. Discrepancies between water retention ability of different animal tissues are also discussed. The imaging technique provides a valuable measurement platform for biological sensing.

The dynamics of correlated novelties.

Science.gov (United States)

Tria, F; Loreto, V; Servedio, V D P; Strogatz, S H

2014-07-31

Novelties are a familiar part of daily life. They are also fundamental to the evolution of biological systems, human society, and technology. By opening new possibilities, one novelty can pave the way for others in a process that Kauffman has called "expanding the adjacent possible". The dynamics of correlated novelties, however, have yet to be quantified empirically or modeled mathematically. Here we propose a simple mathematical model that mimics the process of exploring a physical, biological, or conceptual space that enlarges whenever a novelty occurs. The model, a generalization of Polya's urn, predicts statistical laws for the rate at which novelties happen (Heaps' law) and for the probability distribution on the space explored (Zipf's law), as well as signatures of the process by which one novelty sets the stage for another. We test these predictions on four data sets of human activity: the edit events of Wikipedia pages, the emergence of tags in annotation systems, the sequence of words in texts, and listening to new songs in online music catalogues. By quantifying the dynamics of correlated novelties, our results provide a starting point for a deeper understanding of the adjacent possible and its role in biological, cultural, and technological evolution.

Dynamical systems, attractors, and neural circuits.

Science.gov (United States)

Miller, Paul

2016-01-01

Biology is the study of dynamical systems. Yet most of us working in biology have limited pedagogical training in the theory of dynamical systems, an unfortunate historical fact that can be remedied for future generations of life scientists. In my particular field of systems neuroscience, neural circuits are rife with nonlinearities at all levels of description, rendering simple methodologies and our own intuition unreliable. Therefore, our ideas are likely to be wrong unless informed by good models. These models should be based on the mathematical theories of dynamical systems since functioning neurons are dynamic-they change their membrane potential and firing rates with time. Thus, selecting the appropriate type of dynamical system upon which to base a model is an important first step in the modeling process. This step all too easily goes awry, in part because there are many frameworks to choose from, in part because the sparsely sampled data can be consistent with a variety of dynamical processes, and in part because each modeler has a preferred modeling approach that is difficult to move away from. This brief review summarizes some of the main dynamical paradigms that can arise in neural circuits, with comments on what they can achieve computationally and what signatures might reveal their presence within empirical data. I provide examples of different dynamical systems using simple circuits of two or three cells, emphasizing that any one connectivity pattern is compatible with multiple, diverse functions.

Modeling physiological processes that relate toxicant exposure and bacterial population dynamics.

Directory of Open Access Journals (Sweden)

Tin Klanjscek

Full Text Available Quantifying effects of toxicant exposure on metabolic processes is crucial to predicting microbial growth patterns in different environments. Mechanistic models, such as those based on Dynamic Energy Budget (DEB theory, can link physiological processes to microbial growth.Here we expand the DEB framework to include explicit consideration of the role of reactive oxygen species (ROS. Extensions considered are: (i additional terms in the equation for the "hazard rate" that quantifies mortality risk; (ii a variable representing environmental degradation; (iii a mechanistic description of toxic effects linked to increase in ROS production and aging acceleration, and to non-competitive inhibition of transport channels; (iv a new representation of the "lag time" based on energy required for acclimation. We estimate model parameters using calibrated Pseudomonas aeruginosa optical density growth data for seven levels of cadmium exposure. The model reproduces growth patterns for all treatments with a single common parameter set, and bacterial growth for treatments of up to 150 mg(Cd/L can be predicted reasonably well using parameters estimated from cadmium treatments of 20 mg(Cd/L and lower. Our approach is an important step towards connecting levels of biological organization in ecotoxicology. The presented model reveals possible connections between processes that are not obvious from purely empirical considerations, enables validation and hypothesis testing by creating testable predictions, and identifies research required to further develop the theory.

Influence of attapulgite addition on the biological performance and microbial communities of submerged dynamic membrane bioreactor

Directory of Open Access Journals (Sweden)

Wensong Duan

2017-12-01

Full Text Available A submerged dynamic membrane bioreactor (sDMBR was developed to test the influence of attapulgite (AT addition on the treatment performances and the microbial community structure and function. The batch experimental results displayed the highest UV254 and dissolved organic carbon (DOC removal efficiencies with 5% AT/mixed liquid suspended solids addition dosage. The continuous sDMBR results showed that the removal efficiencies of chemical oxygen demand, NH4+-N, total nitrogen and total phosphorus significantly increased in the AT added sDMBR. Excitation emission matrix analysis demonstrated that the protein-like peaks and fulvic acid-like peaks were significantly decreased in both in the mixed liquid and the effluent of the AT added reactor. The obligate anaerobes were observed in the sDMBR with AT addition, such as Bacteroidetes and Gamma proteobacterium in the dynamic membrane, which played an important role in the process of sludge granulation. Bacterial community richness significantly increased after AT addition with predominated phyla of Proteobacteria and Bacteroidetes. Similarly, species abundance significantly increased in the AT added sDMBR. Further investigations with cluster proved that AT was a favorite biological carrier for the microbial ecology, which enriched microbial abundance and community diversity of the sDMBR.

msiDBN: A Method of Identifying Critical Proteins in Dynamic PPI Networks

Directory of Open Access Journals (Sweden)

Yuan Zhang

2014-01-01

Full Text Available Dynamics of protein-protein interactions (PPIs reveals the recondite principles of biological processes inside a cell. Shown in a wealth of study, just a small group of proteins, rather than the majority, play more essential roles at crucial points of biological processes. This present work focuses on identifying these critical proteins exhibiting dramatic structural changes in dynamic PPI networks. First, a comprehensive way of modeling the dynamic PPIs is presented which simultaneously analyzes the activity of proteins and assembles the dynamic coregulation correlation between proteins at each time point. Second, a novel method is proposed, named msiDBN, which models a common representation of multiple PPI networks using a deep belief network framework and analyzes the reconstruction errors and the variabilities across the time courses in the biological process. Experiments were implemented on data of yeast cell cycles. We evaluated our network construction method by comparing the functional representations of the derived networks with two other traditional construction methods. The ranking results of critical proteins in msiDBN were compared with the results from the baseline methods. The results of comparison showed that msiDBN had better reconstruction rate and identified more proteins of critical value to yeast cell cycle process.

Workshop on Dynamic Process Management (DPM 2006) : Preface

NARCIS (Netherlands)

Reichert, Manfred; Verma, Kunal; Wombacher, Andreas; Eder, Johann; Dustdar, Schahram

The agility of an enterprise increasingly depends on its ability to dynamically set up new business processes or to modify existing ones, and to quickly adapt its information systems to these process changes. Companies are therefore developing a growing interest in concepts, technologies and systems

Imaging morphogenesis: technological advances and biological insights.

Science.gov (United States)

Keller, Philipp J

2013-06-07

Morphogenesis, the development of the shape of an organism, is a dynamic process on a multitude of scales, from fast subcellular rearrangements and cell movements to slow structural changes at the whole-organism level. Live-imaging approaches based on light microscopy reveal the intricate dynamics of this process and are thus indispensable for investigating the underlying mechanisms. This Review discusses emerging imaging techniques that can record morphogenesis at temporal scales from seconds to days and at spatial scales from hundreds of nanometers to several millimeters. To unlock their full potential, these methods need to be matched with new computational approaches and physical models that help convert highly complex image data sets into biological insights.

VISUALIZATION OF BIOLOGICAL TISSUE IMPEDANCE PARAMETERS

Directory of Open Access Journals (Sweden)

V. I. Bankov

2016-01-01

Full Text Available Objective. Investigation the opportunity for measurement of biological tissue impedance to visualize its parameters.Materials and methods. Studies were undertook on the experimental facility, consists of registrating measuring cell, constructed from flat inductors system, formed in oscillatory circuit, herewith investigated biological tissue is the part of this oscillatory circuit. An excitation of oscillatory circuit fulfilled by means of exciter inductor which forms impulse complex modulated electromagnetic field (ICM EMF. The measurement process and visualizations provided by set of certificated instruments: a digital oscillograph AKTAKOM ADS-2221MV, a digital generator АКТАКОМ AWG-4150 (both with software and a gauge RLC E7-22. Comparative dynamic studies of fixed volume and weight pig’s blood, adipose tissue, muscular tissue impedance were conducted by contact versus contactless methods. Contactless method in contrast to contact method gives opportunity to obtain the real morphological visualization of biological tissue irrespective of their nature.Results. Comparison of contact and contactless methods of impedance measurement shows that the inductance to capacitance ratio X(L / X(C was equal: 17 – for muscular tissue, 4 – for blood, 1 – for adipose tissue. It demonstrates the technical correspondence of both impedance registration methods. If propose the base relevance of X (L and X (C parameters for biological tissue impedance so contactless measurement method for sure shows insulating properties of adipose tissue and high conductivity for blood and muscular tissue in fixed volume-weight parameters. Registration of biological tissue impedance complex parameters by contactless method with the help of induced ICM EMF in fixed volume of biological tissue uncovers the most important informative volumes to characterize morphofunctional condition of biological tissue namely X (L / X (C.Conclusion. Contactless method of biological

Fed-Batch Production of Bacterial Ghosts Using Dielectric Spectroscopy for Dynamic Process Control

Directory of Open Access Journals (Sweden)

Andrea Meitz

2016-03-01

Full Text Available The Bacterial Ghost (BG platform technology evolved from a microbiological expression system incorporating the ϕX174 lysis gene E. E-lysis generates empty but structurally intact cell envelopes (BGs from Gram-negative bacteria which have been suggested as candidate vaccines, immunotherapeutic agents or drug delivery vehicles. E-lysis is a highly dynamic and complex biological process that puts exceptional demands towards process understanding and control. The development of a both economic and robust fed-batch production process for BGs required a toolset capable of dealing with rapidly changing concentrations of viable biomass during the E-lysis phase. This challenge was addressed using a transfer function combining dielectric spectroscopy and soft-sensor based biomass estimation for monitoring the rapid decline of viable biomass during the E-lysis phase. The transfer function was implemented to a feed-controller, which followed the permittivity signal closely and was capable of maintaining a constant specific substrate uptake rate during lysis phase. With the described toolset, we were able to increase the yield of BG production processes by a factor of 8–10 when compared to currently used batch procedures reaching lysis efficiencies >98%. This provides elevated potentials for commercial application of the Bacterial Ghost platform technology.

Transmission as a basic process in microbial biology. Lwoff Award Prize Lecture.

Science.gov (United States)

Baquero, Fernando

2017-11-01

Transmission is a basic process in biology and evolution, as it communicates different biological entities within and across hierarchical levels (from genes to holobionts) both in time and space. Vertical descent, replication, is transmission of information across generations (in the time dimension), and horizontal descent is transmission of information across compartments (in the space dimension). Transmission is essentially a communication process that can be studied by analogy of the classic information theory, based on 'emitters', 'messages' and 'receivers'. The analogy can be easily extended to the triad 'emigration', 'migration' and 'immigration'. A number of causes (forces) determine the emission, and another set of causes (energies) assures the reception. The message in fact is essentially constituted by 'meaningful' biological entities. A DNA sequence, a cell and a population have a semiotic dimension, are 'signs' that are eventually recognized (decoded) and integrated by receiver biological entities. In cis-acting or unenclosed transmission, the emitters and receivers correspond to separated entities of the same hierarchical level; in trans-acting or embedded transmission, the information flows between different, but frequently nested, hierarchical levels. The result (as in introgressive events) is constantly producing innovation and feeding natural selection, influencing also the evolution of transmission processes. This review is based on the concepts presented at the André Lwoff Award Lecture in the FEMS Microbiology Congress in Maastricht in 2015. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Exploiting Fast-Variables to Understand Population Dynamics and Evolution

Science.gov (United States)

Constable, George W. A.; McKane, Alan J.

2017-11-01

We describe a continuous-time modelling framework for biological population dynamics that accounts for demographic noise. In the spirit of the methodology used by statistical physicists, transitions between the states of the system are caused by individual events while the dynamics are described in terms of the time-evolution of a probability density function. In general, the application of the diffusion approximation still leaves a description that is quite complex. However, in many biological applications one or more of the processes happen slowly relative to the system's other processes, and the dynamics can be approximated as occurring within a slow low-dimensional subspace. We review these time-scale separation arguments and analyse the more simple stochastic dynamics that result in a number of cases. We stress that it is important to retain the demographic noise derived in this way, and emphasise this point by showing that it can alter the direction of selection compared to the prediction made from an analysis of the corresponding deterministic model.

Learning (from) the errors of a systems biology model.

Science.gov (United States)

Engelhardt, Benjamin; Frőhlich, Holger; Kschischo, Maik

2016-02-11

Mathematical modelling is a labour intensive process involving several iterations of testing on real data and manual model modifications. In biology, the domain knowledge guiding model development is in many cases itself incomplete and uncertain. A major problem in this context is that biological systems are open. Missed or unknown external influences as well as erroneous interactions in the model could thus lead to severely misleading results. Here we introduce the dynamic elastic-net, a data driven mathematical method which automatically detects such model errors in ordinary differential equation (ODE) models. We demonstrate for real and simulated data, how the dynamic elastic-net approach can be used to automatically (i) reconstruct the error signal, (ii) identify the target variables of model error, and (iii) reconstruct the true system state even for incomplete or preliminary models. Our work provides a systematic computational method facilitating modelling of open biological systems under uncertain knowledge.

A Three-Level Process Framework for Contract-Based Dynamic Service Outsourcing

NARCIS (Netherlands)

Grefen, P.W.P.J.; Angelov, S.A.

Service outsourcing is the business paradigm, in which an organization has part of its business process performed by a service provider. In dynamic markets, service providers are selected on the fly during process enactment. The cooperation between the parties is specified in a dynamically made

PM Synchronous Motor Dynamic Modeling with Genetic Algorithm ...

African Journals Online (AJOL)

Adel

This paper proposes dynamic modeling simulation for ac Surface Permanent Magnet Synchronous ... Simulations are implemented using MATLAB with its genetic algorithm toolbox. .... selection, the process that drives biological evolution.

Nuclear magnetic resonance applications in biological systems

International Nuclear Information System (INIS)

Jiang Ling; Liu Maili

2011-01-01

Nuclear magnetic resonance (NMR) spectroscopy is a state-of-the-art technology which has been widely applied in biological systems over the past decades. It is a powerful tool for macromolecular structure determination in solution, and has the unique advantage of being capable of elucidating the structure and dynamic behavior of proteins during vital biomedical processes. In this review, we introduce the recent progress in NMR techniques for studying the structure, interaction and dynamics of proteins. The methods for NMR based drug discovery and metabonomics are also briefly introduced. (authors)

Treatment of winery wastewater by physicochemical, biological and advanced processes: a review.

Science.gov (United States)

Ioannou, L A; Li Puma, G; Fatta-Kassinos, D

2015-04-09

Winery wastewater is a major waste stream resulting from numerous cleaning operations that occur during the production stages of wine. The resulting effluent contains various organic and inorganic contaminants and its environmental impact is notable, mainly due to its high organic/inorganic load, the large volumes produced and its seasonal variability. Several processes for the treatment of winery wastewater are currently available, but the development of alternative treatment methods is necessary in order to (i) maximize the efficiency and flexibility of the treatment process to meet the discharge requirements for winery effluents, and (ii) decrease both the environmental footprint, as well as the investment/operational costs of the process. This review, presents the state-of-the-art of the processes currently applied and/or tested for the treatment of winery wastewater, which were divided into five categories: i.e., physicochemical, biological, membrane filtration and separation, advanced oxidation processes, and combined biological and advanced oxidation processes. The advantages and disadvantages, as well as the main parameters/factors affecting the efficiency of winery wastewater treatment are discussed. Both bench- and pilot/industrial-scale processes have been considered for this review. Copyright © 2014 Elsevier B.V. All rights reserved.

Information Processing and Dynamics in Minimally Cognitive Agents

Science.gov (United States)

Beer, Randall D.; Williams, Paul L.

2015-01-01

There has been considerable debate in the literature about the relative merits of information processing versus dynamical approaches to understanding cognitive processes. In this article, we explore the relationship between these two styles of explanation using a model agent evolved to solve a relational categorization task. Specifically, we…

Dynamic Processes in Biology, Chemistry, and Materials Science: Opportunities for UltraFast Transmission Electron Microscopy - Workshop Summary Report

Energy Technology Data Exchange (ETDEWEB)

Kabius, Bernd C.; Browning, Nigel D.; Thevuthasan, Suntharampillai; Diehl, Barbara L.; Stach, Eric A.

2012-07-25

This report summarizes a 2011 workshop that addressed the potential role of rapid, time-resolved electron microscopy measurements in accelerating the solution of important scientific and technical problems. A series of U.S. Department of Energy (DOE) and National Academy of Science workshops have highlighted the critical role advanced research tools play in addressing scientific challenges relevant to biology, sustainable energy, and technologies that will fuel economic development without degrading our environment. Among the specific capability needs for advancing science and technology are tools that extract more detailed information in realistic environments (in situ or operando) at extreme conditions (pressure and temperature) and as a function of time (dynamic and time-dependent). One of the DOE workshops, Future Science Needs and Opportunities for Electron Scattering: Next Generation Instrumentation and Beyond, specifically addressed the importance of electron-based characterization methods for a wide range of energy-relevant Grand Scientific Challenges. Boosted by the electron optical advancement in the last decade, a diversity of in situ capabilities already is available in many laboratories. The obvious remaining major capability gap in electron microscopy is in the ability to make these direct in situ observations over a broad spectrum of fast (µs) to ultrafast (picosecond [ps] and faster) temporal regimes. In an effort to address current capability gaps, EMSL, the Environmental Molecular Sciences Laboratory, organized an Ultrafast Electron Microscopy Workshop, held June 14-15, 2011, with the primary goal to identify the scientific needs that could be met by creating a facility capable of a strongly improved time resolution with integrated in situ capabilities. The workshop brought together more than 40 leading scientists involved in applying and/or advancing electron microscopy to address important scientific problems of relevance to DOE’s research

Identifying and tracking dynamic processes in social networks

Science.gov (United States)

Chung, Wayne; Savell, Robert; Schütt, Jan-Peter; Cybenko, George

2006-05-01

The detection and tracking of embedded malicious subnets in an active social network can be computationally daunting due to the quantity of transactional data generated in the natural interaction of large numbers of actors comprising a network. In addition, detection of illicit behavior may be further complicated by evasive strategies designed to camouflage the activities of the covert subnet. In this work, we move beyond traditional static methods of social network analysis to develop a set of dynamic process models which encode various modes of behavior in active social networks. These models will serve as the basis for a new application of the Process Query System (PQS) to the identification and tracking of covert dynamic processes in social networks. We present a preliminary result from application of our technique in a real-world data stream-- the Enron email corpus.

Applications of Structural Biology and Bioinformatics in the Investigation of Oxidative Stress-Related Processes

NARCIS (Netherlands)

Bersch, Beate; Groves, Matthew; Johann, Klare; Torda, Andrew; Ortiz, Dario; Laher, I.

2014-01-01

Reactive oxygen species (ROS)-mediated dysfunction of certain biological processes is implicated in different diseases in humans, including cardiovascular, cancer, or neurodegenerative disorders. Not only human cells and tissues are affected by ROS but also all other biological systems, including

Modeling Cancer Metastasis using Global, Quantitative and Integrative Network Biology

DEFF Research Database (Denmark)

Schoof, Erwin; Erler, Janine

understanding of molecular processes which are fundamental to tumorigenesis. In Article 1, we propose a novel framework for how cancer mutations can be studied by taking into account their effect at the protein network level. In Article 2, we demonstrate how global, quantitative data on phosphorylation dynamics...... can be generated using MS, and how this can be modeled using a computational framework for deciphering kinase-substrate dynamics. This framework is described in depth in Article 3, and covers the design of KinomeXplorer, which allows the prediction of kinases responsible for modulating observed...... phosphorylation dynamics in a given biological sample. In Chapter III, we move into Integrative Network Biology, where, by combining two fundamental technologies (MS & NGS), we can obtain more in-depth insights into the links between cellular phenotype and genotype. Article 4 describes the proof...

Systems Biology-Driven Hypotheses Tested In Vivo: The Need to Advancing Molecular Imaging Tools.

Science.gov (United States)

Verma, Garima; Palombo, Alessandro; Grigioni, Mauro; La Monaca, Morena; D'Avenio, Giuseppe

2018-01-01

Processing and interpretation of biological images may provide invaluable insights on complex, living systems because images capture the overall dynamics as a "whole." Therefore, "extraction" of key, quantitative morphological parameters could be, at least in principle, helpful in building a reliable systems biology approach in understanding living objects. Molecular imaging tools for system biology models have attained widespread usage in modern experimental laboratories. Here, we provide an overview on advances in the computational technology and different instrumentations focused on molecular image processing and analysis. Quantitative data analysis through various open source software and algorithmic protocols will provide a novel approach for modeling the experimental research program. Besides this, we also highlight the predictable future trends regarding methods for automatically analyzing biological data. Such tools will be very useful to understand the detailed biological and mathematical expressions under in-silico system biology processes with modeling properties.

A comparative approach for the investigation of biological information processing: An examination of the structure and function of computer hard drives and DNA

Science.gov (United States)

2010-01-01

Background The robust storage, updating and utilization of information are necessary for the maintenance and perpetuation of dynamic systems. These systems can exist as constructs of metal-oxide semiconductors and silicon, as in a digital computer, or in the "wetware" of organic compounds, proteins and nucleic acids that make up biological organisms. We propose that there are essential functional properties of centralized information-processing systems; for digital computers these properties reside in the computer's hard drive, and for eukaryotic cells they are manifest in the DNA and associated structures. Methods Presented herein is a descriptive framework that compares DNA and its associated proteins and sub-nuclear structure with the structure and function of the computer hard drive. We identify four essential properties of information for a centralized storage and processing system: (1) orthogonal uniqueness, (2) low level formatting, (3) high level formatting and (4) translation of stored to usable form. The corresponding aspects of the DNA complex and a computer hard drive are categorized using this classification. This is intended to demonstrate a functional equivalence between the components of the two systems, and thus the systems themselves. Results Both the DNA complex and the computer hard drive contain components that fulfill the essential properties of a centralized information storage and processing system. The functional equivalence of these components provides insight into both the design process of engineered systems and the evolved solutions addressing similar system requirements. However, there are points where the comparison breaks down, particularly when there are externally imposed information-organizing structures on the computer hard drive. A specific example of this is the imposition of the File Allocation Table (FAT) during high level formatting of the computer hard drive and the subsequent loading of an operating system (OS). Biological

A comparative approach for the investigation of biological information processing: an examination of the structure and function of computer hard drives and DNA.

Science.gov (United States)

D'Onofrio, David J; An, Gary

2010-01-21

The robust storage, updating and utilization of information are necessary for the maintenance and perpetuation of dynamic systems. These systems can exist as constructs of metal-oxide semiconductors and silicon, as in a digital computer, or in the "wetware" of organic compounds, proteins and nucleic acids that make up biological organisms. We propose that there are essential functional properties of centralized information-processing systems; for digital computers these properties reside in the computer's hard drive, and for eukaryotic cells they are manifest in the DNA and associated structures. Presented herein is a descriptive framework that compares DNA and its associated proteins and sub-nuclear structure with the structure and function of the computer hard drive. We identify four essential properties of information for a centralized storage and processing system: (1) orthogonal uniqueness, (2) low level formatting, (3) high level formatting and (4) translation of stored to usable form. The corresponding aspects of the DNA complex and a computer hard drive are categorized using this classification. This is intended to demonstrate a functional equivalence between the components of the two systems, and thus the systems themselves. Both the DNA complex and the computer hard drive contain components that fulfill the essential properties of a centralized information storage and processing system. The functional equivalence of these components provides insight into both the design process of engineered systems and the evolved solutions addressing similar system requirements. However, there are points where the comparison breaks down, particularly when there are externally imposed information-organizing structures on the computer hard drive. A specific example of this is the imposition of the File Allocation Table (FAT) during high level formatting of the computer hard drive and the subsequent loading of an operating system (OS). Biological systems do not have an

A comparative approach for the investigation of biological information processing: An examination of the structure and function of computer hard drives and DNA

Directory of Open Access Journals (Sweden)

D'Onofrio David J

2010-01-01

Full Text Available Abstract Background The robust storage, updating and utilization of information are necessary for the maintenance and perpetuation of dynamic systems. These systems can exist as constructs of metal-oxide semiconductors and silicon, as in a digital computer, or in the "wetware" of organic compounds, proteins and nucleic acids that make up biological organisms. We propose that there are essential functional properties of centralized information-processing systems; for digital computers these properties reside in the computer's hard drive, and for eukaryotic cells they are manifest in the DNA and associated structures. Methods Presented herein is a descriptive framework that compares DNA and its associated proteins and sub-nuclear structure with the structure and function of the computer hard drive. We identify four essential properties of information for a centralized storage and processing system: (1 orthogonal uniqueness, (2 low level formatting, (3 high level formatting and (4 translation of stored to usable form. The corresponding aspects of the DNA complex and a computer hard drive are categorized using this classification. This is intended to demonstrate a functional equivalence between the components of the two systems, and thus the systems themselves. Results Both the DNA complex and the computer hard drive contain components that fulfill the essential properties of a centralized information storage and processing system. The functional equivalence of these components provides insight into both the design process of engineered systems and the evolved solutions addressing similar system requirements. However, there are points where the comparison breaks down, particularly when there are externally imposed information-organizing structures on the computer hard drive. A specific example of this is the imposition of the File Allocation Table (FAT during high level formatting of the computer hard drive and the subsequent loading of an operating

Uncovering the underlying physical mechanisms of biological systems via quantification of landscape and flux

International Nuclear Information System (INIS)

Xu Li; Chu Xiakun; Yan Zhiqiang; Zheng Xiliang; Zhang Kun; Zhang Feng; Yan Han; Wu Wei; Wang Jin

2016-01-01

In this review, we explore the physical mechanisms of biological processes such as protein folding and recognition, ligand binding, and systems biology, including cell cycle, stem cell, cancer, evolution, ecology, and neural networks. Our approach is based on the landscape and flux theory for nonequilibrium dynamical systems. This theory provides a unifying principle and foundation for investigating the underlying mechanisms and physical quantification of biological systems. (topical review)

Predicting seizures in untreated temporal lobe epilepsy using point-process nonlinear models of heartbeat dynamics.

Science.gov (United States)

Valenza, G; Romigi, A; Citi, L; Placidi, F; Izzi, F; Albanese, M; Scilingo, E P; Marciani, M G; Duggento, A; Guerrisi, M; Toschi, N; Barbieri, R

2016-08-01

Symptoms of temporal lobe epilepsy (TLE) are frequently associated with autonomic dysregulation, whose underlying biological processes are thought to strongly contribute to sudden unexpected death in epilepsy (SUDEP). While abnormal cardiovascular patterns commonly occur during ictal events, putative patterns of autonomic cardiac effects during pre-ictal (PRE) periods (i.e. periods preceding seizures) are still unknown. In this study, we investigated TLE-related heart rate variability (HRV) through instantaneous, nonlinear estimates of cardiovascular oscillations during inter-ictal (INT) and PRE periods. ECG recordings from 12 patients with TLE were processed to extract standard HRV indices, as well as indices of instantaneous HRV complexity (dominant Lyapunov exponent and entropy) and higher-order statistics (bispectra) obtained through definition of inhomogeneous point-process nonlinear models, employing Volterra-Laguerre expansions of linear, quadratic, and cubic kernels. Experimental results demonstrate that the best INT vs. PRE classification performance (balanced accuracy: 73.91%) was achieved only when retaining the time-varying, nonlinear, and non-stationary structure of heartbeat dynamical features. The proposed approach opens novel important avenues in predicting ictal events using information gathered from cardiovascular signals exclusively.

A new theoretical approach to analyze complex processes in cytoskeleton proteins.

Science.gov (United States)

Li, Xin; Kolomeisky, Anatoly B

2014-03-20

Cytoskeleton proteins are filament structures that support a large number of important biological processes. These dynamic biopolymers exist in nonequilibrium conditions stimulated by hydrolysis chemical reactions in their monomers. Current theoretical methods provide a comprehensive picture of biochemical and biophysical processes in cytoskeleton proteins. However, the description is only qualitative under biologically relevant conditions because utilized theoretical mean-field models neglect correlations. We develop a new theoretical method to describe dynamic processes in cytoskeleton proteins that takes into account spatial correlations in the chemical composition of these biopolymers. Our approach is based on analysis of probabilities of different clusters of subunits. It allows us to obtain exact analytical expressions for a variety of dynamic properties of cytoskeleton filaments. By comparing theoretical predictions with Monte Carlo computer simulations, it is shown that our method provides a fully quantitative description of complex dynamic phenomena in cytoskeleton proteins under all conditions.

Dynamic Modeling of Process Technologies for Closed-Loop Water Recovery Systems

Science.gov (United States)

Allada, Rama Kumar; Lange, Kevin E.; Anderson, Molly S.

2012-01-01

Detailed chemical process simulations are a useful tool in designing and optimizing complex systems and architectures for human life support. Dynamic and steady-state models of these systems help contrast the interactions of various operating parameters and hardware designs, which become extremely useful in trade-study analyses. NASA s Exploration Life Support technology development project recently made use of such models to compliment a series of tests on different waste water distillation systems. This paper presents dynamic simulations of chemical process for primary processor technologies including: the Cascade Distillation System (CDS), the Vapor Compression Distillation (VCD) system, the Wiped-Film Rotating Disk (WFRD), and post-distillation water polishing processes such as the Volatiles Removal Assembly (VRA). These dynamic models were developed using the Aspen Custom Modeler (Registered TradeMark) and Aspen Plus(Registered TradeMark) process simulation tools. The results expand upon previous work for water recovery technology models and emphasize dynamic process modeling and results. The paper discusses system design, modeling details, and model results for each technology and presents some comparisons between the model results and available test data. Following these initial comparisons, some general conclusions and forward work are discussed.

Boolean modeling in systems biology: an overview of methodology and applications

International Nuclear Information System (INIS)

Wang, Rui-Sheng; Albert, Réka; Saadatpour, Assieh

2012-01-01

Mathematical modeling of biological processes provides deep insights into complex cellular systems. While quantitative and continuous models such as differential equations have been widely used, their use is obstructed in systems wherein the knowledge of mechanistic details and kinetic parameters is scarce. On the other hand, a wealth of molecular level qualitative data on individual components and interactions can be obtained from the experimental literature and high-throughput technologies, making qualitative approaches such as Boolean network modeling extremely useful. In this paper, we build on our research to provide a methodology overview of Boolean modeling in systems biology, including Boolean dynamic modeling of cellular networks, attractor analysis of Boolean dynamic models, as well as inferring biological regulatory mechanisms from high-throughput data using Boolean models. We finally demonstrate how Boolean models can be applied to perform the structural analysis of cellular networks. This overview aims to acquaint life science researchers with the basic steps of Boolean modeling and its applications in several areas of systems biology. (paper)

A Dynamic Simulation Program for a Hydriodic Acid Concentration and Decomposition Process in the VHTR-SI Process

International Nuclear Information System (INIS)

Chang, Ji Woon; Shin, Young Joon; Lee, Tae Hoon; Lee, Ki Young; Kim, Yong Wan; Chang, Jong Hwa; Youn, Cheung

2011-01-01

The Sulfur-Iodine (SI) cycle which can produce hydrogen by using nuclear heat consists of a Bunsen reaction (Section 1), a sulfur acid concentration and decomposition (Section 2), and a hydriodic acid concentration and decomposition (Section 3). The heat required in the SI process can be supplied through an intermediate heat exchanger (IHX) by a Very High Temperature Gas Cooled Reactor (VHTR). The Korea Atomic Energy Research Institute-Dynamic Simulation Code (KAERI-DySCo) based on the Visual C++ is an integration application software that simulates the dynamic behavior of the SI process. KAERI-DySCo was prepared to solve dynamic problem of the seven chemical reactors which consist of Sections 2 and 3. Section 3 is the key part of the SI process, because the strong non-ideality and the partial immiscibility of the binary HI.H 2 O and the ternary HI.I 2 .H 2 O (HIX solution) mixture make it difficult to model and simulate the dynamic behavior of the system. Therefore, it is necessary to compose separately a dynamic simulation program for Section 3 in KAERI-DySCo optimization. In this paper, a simulation program to analyze the dynamic behavior of Section 3 is introduced using the prepared KAERI-DySCo, and results of dynamic simulation are represented by running the program

Improved Prediction of Phosphorus Dynamics in Biotechnological Processes by Considering Precipitation and Polyphosphate Formation: A Case Study on Antibiotic Production with Streptomyces coelicolor

DEFF Research Database (Denmark)

Bürger, Patrick; Flores-Alsina, Xavier; Arellano-Garcia, Harvey

2018-01-01

The multiplicity of physicochemical and biological processes, where phosphorus is involved, makes their accurate prediction using current mathematical models in biotechnology quite a challenge. In this work, an antibiotic production model of Streptomyces coelicolor is chosen as a representative...... approach describing intracellular polyphosphate accumulation and consumption has been developed and implemented. A heuristic re-estimation of selected parameters is carried out to improve overall model performance. The improved process model predicts phosphate dynamics (root mean squared error ≤52h: −90...

Developmental Dynamics of Emotion and Cognition Processes in Preschoolers

Science.gov (United States)

Blankson, A. Nayena; O'Brien, Marion; Leerkes, Esther M.; Marcovitch, Stuart; Calkins, Susan D.; Weaver, Jennifer Miner

2013-01-01

Dynamic relations during the preschool years across processes of control and understanding in the domains of emotion and cognition were examined. Participants were 263 children (42% non-White) and their mothers who were seen first when the children were 3 years old and again when they were 4. Results indicated dynamic dependence among the…

Novel recurrent neural network for modelling biological networks: oscillatory p53 interaction dynamics.

Science.gov (United States)

Ling, Hong; Samarasinghe, Sandhya; Kulasiri, Don

2013-12-01

Understanding the control of cellular networks consisting of gene and protein interactions and their emergent properties is a central activity of Systems Biology research. For this, continuous, discrete, hybrid, and stochastic methods have been proposed. Currently, the most common approach to modelling accurate temporal dynamics of networks is ordinary differential equations (ODE). However, critical limitations of ODE models are difficulty in kinetic parameter estimation and numerical solution of a large number of equations, making them more suited to smaller systems. In this article, we introduce a novel recurrent artificial neural network (RNN) that addresses above limitations and produces a continuous model that easily estimates parameters from data, can handle a large number of molecular interactions and quantifies temporal dynamics and emergent systems properties. This RNN is based on a system of ODEs representing molecular interactions in a signalling network. Each neuron represents concentration change of one molecule represented by an ODE. Weights of the RNN correspond to kinetic parameters in the system and can be adjusted incrementally during network training. The method is applied to the p53-Mdm2 oscillation system - a crucial component of the DNA damage response pathways activated by a damage signal. Simulation results indicate that the proposed RNN can successfully represent the behaviour of the p53-Mdm2 oscillation system and solve the parameter estimation problem with high accuracy. Furthermore, we presented a modified form of the RNN that estimates parameters and captures systems dynamics from sparse data collected over relatively large time steps. We also investigate the robustness of the p53-Mdm2 system using the trained RNN under various levels of parameter perturbation to gain a greater understanding of the control of the p53-Mdm2 system. Its outcomes on robustness are consistent with the current biological knowledge of this system. As more

Adaptive Dynamic Process Scheduling on Distributed Memory Parallel Computers

Directory of Open Access Journals (Sweden)

Wei Shu

1994-01-01

Full Text Available One of the challenges in programming distributed memory parallel machines is deciding how to allocate work to processors. This problem is particularly important for computations with unpredictable dynamic behaviors or irregular structures. We present a scheme for dynamic scheduling of medium-grained processes that is useful in this context. The adaptive contracting within neighborhood (ACWN is a dynamic, distributed, load-dependent, and scalable scheme. It deals with dynamic and unpredictable creation of processes and adapts to different systems. The scheme is described and contrasted with two other schemes that have been proposed in this context, namely the randomized allocation and the gradient model. The performance of the three schemes on an Intel iPSC/2 hypercube is presented and analyzed. The experimental results show that even though the ACWN algorithm incurs somewhat larger overhead than the randomized allocation, it achieves better performance in most cases due to its adaptiveness. Its feature of quickly spreading the work helps it outperform the gradient model in performance and scalability.

Understanding the Entrepreneurial Process: a Dynamic Approach

Directory of Open Access Journals (Sweden)

Vânia Maria Jorge Nassif

2010-04-01

Full Text Available There is considerable predominance in the adoption of perspectives based on characteristics in research into entrepreneurship. However, most studies describe the entrepreneur from a static or snapshot approach; very few adopt a dynamic perspective. The aim of this study is to contribute to the enhancement of knowledge concerning entrepreneurial process dynamics through an understanding of the values, characteristics and actions of the entrepreneur over time. By focusing on personal attributes, we have developed a framework that shows the importance of affective and cognitive aspects of entrepreneurs and the way that they evolve during the development of their business.

Dynamics of carbon 14 in soils: a review

International Nuclear Information System (INIS)

Tamponnet, C.

2004-01-01

In terrestrial ecosystems, soil is the main interface between atmosphere, hydrosphere, lithosphere and biosphere. Its interactions with carbon cycle are primordial. Information about carbon 14 dynamics in soils is quite dispersed and an up-to-date status is therefore presented in this paper. Carbon 14 dynamics in soils are governed by physical processes (soil structure, soil aggregation, soil erosion) chemical processes (sequestration by soil components either mineral or organic), and soil biological processes (soil microbes, soil fauna, soil biochemistry). The relative importance of such processes varied remarkably among the various biomes (tropical forest, temperate forest, boreal forest, tropical savannah, temperate pastures, deserts, tundra, marshlands, agro ecosystems) encountered in the terrestrial eco-sphere. Moreover, application for a simplified modelling of carbon 14 dynamics in soils is proposed. (author)

Evolutionary game theory for physical and biological scientists. I. Training and validating population dynamics equations.

Science.gov (United States)

Liao, David; Tlsty, Thea D

2014-08-06

Failure to understand evolutionary dynamics has been hypothesized as limiting our ability to control biological systems. An increasing awareness of similarities between macroscopic ecosystems and cellular tissues has inspired optimism that game theory will provide insights into the progression and control of cancer. To realize this potential, the ability to compare game theoretic models and experimental measurements of population dynamics should be broadly disseminated. In this tutorial, we present an analysis method that can be used to train parameters in game theoretic dynamics equations, used to validate the resulting equations, and used to make predictions to challenge these equations and to design treatment strategies. The data analysis techniques in this tutorial are adapted from the analysis of reaction kinetics using the method of initial rates taught in undergraduate general chemistry courses. Reliance on computer programming is avoided to encourage the adoption of these methods as routine bench activities.

Darlington tritium removal facility and station upgrading plant dynamic process simulation

International Nuclear Information System (INIS)

Busigin, A.; Williams, G. I. D.; Wong, T. C. W.; Kulczynski, D.; Reid, A.

2008-01-01

Ontario Power Generation Nuclear (OPGN) has a 4 x 880 MWe CANDU nuclear station at its Darlington Nuclear Div. located in Bowmanville. The station has been operating a Tritium Removal Facility (TRF) and a D 2 O station Upgrading Plant (SUP) since 1989. Both facilities were designed with a Distributed Control System (DCS) and programmable logic controllers (PLC) for process control. This control system was replaced with a DCS only, in 1998. A dynamic plant simulator was developed for the Darlington TRF (DTRF) and the SUP, as part of the computer control system replacement. The simulator was used to test the new software, required to eliminate the PLCs. The simulator is now used for operator training and testing of process control software changes prior to field installation. Dynamic simulation will be essential for the ITER isotope separation system, where the process is more dynamic than the relatively steady-state DTRF process. This paper describes the development and application of the DTRF and SUP dynamic simulator, its benefits, architecture, and the operational experience with the simulator. (authors)

Genomic Signal Processing: Predicting Basic Molecular Biological Principles

Science.gov (United States)

Alter, Orly

2005-03-01

Advances in high-throughput technologies enable acquisition of different types of molecular biological data, monitoring the flow of biological information as DNA is transcribed to RNA, and RNA is translated to proteins, on a genomic scale. Future discovery in biology and medicine will come from the mathematical modeling of these data, which hold the key to fundamental understanding of life on the molecular level, as well as answers to questions regarding diagnosis, treatment and drug development. Recently we described data-driven models for genome-scale molecular biological data, which use singular value decomposition (SVD) and the comparative generalized SVD (GSVD). Now we describe an integrative data-driven model, which uses pseudoinverse projection (1). We also demonstrate the predictive power of these matrix algebra models (2). The integrative pseudoinverse projection model formulates any number of genome-scale molecular biological data sets in terms of one chosen set of data samples, or of profiles extracted mathematically from data samples, designated the ``basis'' set. The mathematical variables of this integrative model, the pseudoinverse correlation patterns that are uncovered in the data, represent independent processes and corresponding cellular states (such as observed genome-wide effects of known regulators or transcription factors, the biological components of the cellular machinery that generate the genomic signals, and measured samples in which these regulators or transcription factors are over- or underactive). Reconstruction of the data in the basis simulates experimental observation of only the cellular states manifest in the data that correspond to those of the basis. Classification of the data samples according to their reconstruction in the basis, rather than their overall measured profiles, maps the cellular states of the data onto those of the basis, and gives a global picture of the correlations and possibly also causal coordination of

Collective Phenomena Emerging from the Interactions between Dynamical Processes in Multiplex Networks.

Science.gov (United States)

Nicosia, Vincenzo; Skardal, Per Sebastian; Arenas, Alex; Latora, Vito

2017-03-31

We introduce a framework to intertwine dynamical processes of different nature, each with its own distinct network topology, using a multilayer network approach. As an example of collective phenomena emerging from the interactions of multiple dynamical processes, we study a model where neural dynamics and nutrient transport are bidirectionally coupled in such a way that the allocation of the transport process at one layer depends on the degree of synchronization at the other layer, and vice versa. We show numerically, and we prove analytically, that the multilayer coupling induces a spontaneous explosive synchronization and a heterogeneous distribution of allocations, otherwise not present in the two systems considered separately. Our framework can find application to other cases where two or more dynamical processes such as synchronization, opinion formation, information diffusion, or disease spreading, are interacting with each other.

Collective Phenomena Emerging from the Interactions between Dynamical Processes in Multiplex Networks

Science.gov (United States)

Nicosia, Vincenzo; Skardal, Per Sebastian; Arenas, Alex; Latora, Vito

2017-03-01

We introduce a framework to intertwine dynamical processes of different nature, each with its own distinct network topology, using a multilayer network approach. As an example of collective phenomena emerging from the interactions of multiple dynamical processes, we study a model where neural dynamics and nutrient transport are bidirectionally coupled in such a way that the allocation of the transport process at one layer depends on the degree of synchronization at the other layer, and vice versa. We show numerically, and we prove analytically, that the multilayer coupling induces a spontaneous explosive synchronization and a heterogeneous distribution of allocations, otherwise not present in the two systems considered separately. Our framework can find application to other cases where two or more dynamical processes such as synchronization, opinion formation, information diffusion, or disease spreading, are interacting with each other.

A System Structure for a VHTR-SI Process Dynamic Simulation Code

International Nuclear Information System (INIS)

Chang, Jiwoon; Shin, Youngjoon; Kim, Jihwan; Lee, Kiyoung; Lee, Wonjae; Chang, Jonghwa; Youn, Cheung

2008-01-01

The VHTR-SI process dynamic simulation code embedded in a mathematical solution engine is an application software system that simulates the dynamic behavior of the VHTR-SI process. Also, the software system supports a user friendly graphical user interface (GUI) for user input/out. Structured analysis techniques were developed in the late 1970s by Yourdon, DeMarco, Gane and Sarson for applying a systematic approach to a systems analysis. It included the use of data flow diagrams and data modeling and fostered the use of an implementation-independent graphical notation for a documentation. In this paper, we present a system structure for a VHRT-SI process dynamic simulation code by using the methodologies of structured analysis

PRODIAG -- Dynamic qualitative analysis for process fault diagnosis

International Nuclear Information System (INIS)

Reifman, J.; Wei, T.Y.C.

1995-01-01

The authors present a method for handling the dynamic effects of process component malfunctions through time-independent rule-based diagnostic systems. The method's theory is discussed and a simplified version is implemented in the process diagnostic expert system PRODIAG. Simulation results from a full-scope operator training simulator of a nuclear power plant are used to illustrate the method

Biological processes for mitigation of greenhouse gases

Energy Technology Data Exchange (ETDEWEB)

Benemann, John R. [California Univ., Dept. of Plant and Microbial Biology, Berkeley, CA (United States)

1999-07-01

Biological processes driven by photosynthesis cycle through the atmosphere well over an order of magnitude more CO{sub 2} than is currently emitted from the combustion of fossils fuels. Already human activities control and appropriate almost half the primary photosynthetic productivity of the planet. Better management of natural and man-made ecosystems affords many opportunities for mitigation of greenhouse gases, through sink enhancements, source reduction and substitution of fossil fuels with biofuels. Biofuels can be recovered from most organic wastes, from agricultural and forestry residues, and from biomass produced solely for energy use. However, the currently low costs of fossil fuels limits the market for biofuels. Accounting for the greenhouse mitigation value of biofuels would significantly increase their contribution to world fuel suppliers, estimated to be currently equivalent to about 15% of fossil fuel usage. Another limiting factor in expanding the use of biofuels is the relatively low solar energy conversion efficiencies of photosynthesis. Currently well below 1% of solar energy is converted into biomass energy even by intensive agricultural or forestry systems, with peak conversion efficiencies about 2 to 3% for sugar cane or microalgae cultures. One approach to increase photosynthetic efficiencies, being developed at the University of California Berkeley, is to reduce the amount of light-gathering chlorophyll in microalgae and higher plants. This would reduce mutual shading and also increase photosynthetic efficiencies under full sunlight intensities. Estimates of the potential of photosynthetic greenhouse mitigation processes vary widely. However, even conservative estimates for biofuels substituting for fossil fuels project the potential to reduce a large fraction of current increases in atmospheric CO{sub 2} levels. Biofuels production will require integration with existing agronomic, forestry and animal husbandry systems, and improved

Dynamic modelling of an adsorption storage tank using a hybrid approach combining computational fluid dynamics and process simulation

Science.gov (United States)

Mota, J.P.B.; Esteves, I.A.A.C.; Rostam-Abadi, M.

2004-01-01

A computational fluid dynamics (CFD) software package has been coupled with the dynamic process simulator of an adsorption storage tank for methane fuelled vehicles. The two solvers run as independent processes and handle non-overlapping portions of the computational domain. The codes exchange data on the boundary interface of the two domains to ensure continuity of the solution and of its gradient. A software interface was developed to dynamically suspend and activate each process as necessary, and be responsible for data exchange and process synchronization. This hybrid computational tool has been successfully employed to accurately simulate the discharge of a new tank design and evaluate its performance. The case study presented here shows that CFD and process simulation are highly complementary computational tools, and that there are clear benefits to be gained from a close integration of the two. ?? 2004 Elsevier Ltd. All rights reserved.

Linking Adverse Outcome Pathways to Dynamic Energy Budgets: A Conceptual Model

Energy Technology Data Exchange (ETDEWEB)

Murphy, Cheryl [Michigan State University, East Lansing; Nisbet, Roger [University of California Santa Barbara; Antczak, Philipp [University of Liverpool, UK; Reyero, Natalia [Army Corps of Engineers, Vicksburg; Gergs, Andre [Gaiac; Lika, Dina [University of Crete; Mathews, Teresa J. [ORNL; Muller, Eric [University of California, Santa Barbara; Nacci, Dianne [U.S. Environmental Protection Agency (EPA); Peace, Angela L. [ORNL; Remien, Chris [University of Idaho; Schulz, Irv [Pacific Northwest National Laboratory (PNNL); Watanabe, Karen [Arizona State University

2018-02-01

Ecological risk assessment quantifies the likelihood of undesirable impacts of stressors, primarily at high levels of biological organization. Data used to inform ecological risk assessments come primarily from tests on individual organisms or from suborganismal studies, indicating a disconnect between primary data and protection goals. We know how to relate individual responses to population dynamics using individual-based models, and there are emerging ideas on how to make connections to ecosystem services. However, there is no established methodology to connect effects seen at higher levels of biological organization with suborganismal dynamics, despite progress made in identifying Adverse Outcome Pathways (AOPs) that link molecular initiating events to ecologically relevant key events. This chapter is a product of a working group at the National Center for Mathematical and Biological Synthesis (NIMBioS) that assessed the feasibility of using dynamic energy budget (DEB) models of individual organisms as a “pivot” connecting suborganismal processes to higher level ecological processes. AOP models quantify explicit molecular, cellular or organ-level processes, but do not offer a route to linking sub-organismal damage to adverse effects on individual growth, reproduction, and survival, which can be propagated to the population level through individual-based models. DEB models describe these processes, but use abstract variables with undetermined connections to suborganismal biology. We propose linking DEB and quantitative AOP models by interpreting AOP key events as measures of damage-inducing processes in a DEB model. Here, we present a conceptual model for linking AOPs to DEB models and review existing modeling tools available for both AOP and DEB.

Effects of aerobic and anaerobic biological processes on leaching of heavy metals from soil amended with sewage sludge compost.

Science.gov (United States)

Fang, Wen; Wei, Yonghong; Liu, Jianguo; Kosson, David S; van der Sloot, Hans A; Zhang, Peng

2016-12-01

The risk from leaching of heavy metals is a major factor hindering land application of sewage sludge compost (SSC). Understanding the change in heavy metal leaching resulting from soil biological processes provides important information for assessing long-term behavior of heavy metals in the compost amended soil. In this paper, 180days aerobic incubation and 240days anaerobic incubation were conducted to investigate the effects of the aerobic and anaerobic biological processes on heavy metal leaching from soil amended with SSC, combined with chemical speciation modeling. Results showed that leaching concentrations of heavy metals at natural pH were similar before and after biological process. However, the major processes controlling heavy metals were influenced by the decrease of DOC with organic matter mineralization during biological processes. Mineralization of organic matter lowered the contribution of DOC-complexation to Ni and Zn leaching. Besides, the reducing condition produced by biological processes, particularly by the anaerobic biological process, resulted in the loss of sorption sites for As on Fe hydroxide, which increased the potential risk of As release at alkaline pH. Copyright © 2016 Elsevier Ltd. All rights reserved.

Process for the biological purification of waste water

DEFF Research Database (Denmark)

1992-01-01

Process for the biological purification of waste water by the activated sludge method, the waste water being mixed with recirculated sludge and being subjected to an anaerobic treatment, before the waste water thus treated is alternately subjected to anoxic and aerobic treatments and the waste...... water thus treated is led into a clarification zone for settling sludge, which sludge is recirculated in order to be mixed with the crude waste water. As a result, a simultaneous reduction of the content both of nitrogen and phosphorus of the waste water is achieved....

Statistical inference for noisy nonlinear ecological dynamic systems.

Science.gov (United States)

Wood, Simon N

2010-08-26

Chaotic ecological dynamic systems defy conventional statistical analysis. Systems with near-chaotic dynamics are little better. Such systems are almost invariably driven by endogenous dynamic processes plus demographic and environmental process noise, and are only observable with error. Their sensitivity to history means that minute changes in the driving noise realization, or the system parameters, will cause drastic changes in the system trajectory. This sensitivity is inherited and amplified by the joint probability density of the observable data and the process noise, rendering it useless as the basis for obtaining measures of statistical fit. Because the joint density is the basis for the fit measures used by all conventional statistical methods, this is a major theoretical shortcoming. The inability to make well-founded statistical inferences about biological dynamic models in the chaotic and near-chaotic regimes, other than on an ad hoc basis, leaves dynamic theory without the methods of quantitative validation that are essential tools in the rest of biological science. Here I show that this impasse can be resolved in a simple and general manner, using a method that requires only the ability to simulate the observed data on a system from the dynamic model about which inferences are required. The raw data series are reduced to phase-insensitive summary statistics, quantifying local dynamic structure and the distribution of observations. Simulation is used to obtain the mean and the covariance matrix of the statistics, given model parameters, allowing the construction of a 'synthetic likelihood' that assesses model fit. This likelihood can be explored using a straightforward Markov chain Monte Carlo sampler, but one further post-processing step returns pure likelihood-based inference. I apply the method to establish the dynamic nature of the fluctuations in Nicholson's classic blowfly experiments.

Aggregation of flexible polyelectrolytes: Phase diagram and dynamics.

Science.gov (United States)

Tom, Anvy Moly; Rajesh, R; Vemparala, Satyavani

2017-10-14

Similarly charged polymers in solution, known as polyelectrolytes, are known to form aggregated structures in the presence of oppositely charged counterions. Understanding the dependence of the equilibrium phases and the dynamics of the process of aggregation on parameters such as backbone flexibility and charge density of such polymers is crucial for insights into various biological processes which involve biological polyelectrolytes such as protein, DNA, etc. Here, we use large-scale coarse-grained molecular dynamics simulations to obtain the phase diagram of the aggregated structures of flexible charged polymers and characterize the morphology of the aggregates as well as the aggregation dynamics, in the presence of trivalent counterions. Three different phases are observed depending on the charge density: no aggregation, a finite bundle phase where multiple small aggregates coexist with a large aggregate and a fully phase separated phase. We show that the flexibility of the polymer backbone causes strong entanglement between charged polymers leading to additional time scales in the aggregation process. Such slowing down of the aggregation dynamics results in the exponent, characterizing the power law decay of the number of aggregates with time, to be dependent on the charge density of the polymers. These results are contrary to those obtained for rigid polyelectrolytes, emphasizing the role of backbone flexibility.

Removal of Refractory Organics from Biologically Treated Landfill Leachate by Microwave Discharge Electrodeless Lamp Assisted Fenton Process

Directory of Open Access Journals (Sweden)

Jiuyi Li

2015-01-01

Full Text Available Biologically treated leachate usually contains considerable amount of refractory organics and trace concentrations of xenobiotic pollutants. Removal of refractory organics from biologically treated landfill leachate by a novel microwave discharge electrodeless lamp (MDEL assisted Fenton process was investigated in the present study in comparison to conventional Fenton and ultraviolet Fenton processes. Conventional Fenton and ultraviolet Fenton processes could substantially remove up to 70% of the refractory organics in a membrane bioreactor treated leachate. MDEL assisted Fenton process achieved excellent removal performance of the refractory components, and the effluent chemical oxygen demand concentration was lower than 100 mg L−1. Most organic matters were transformed into smaller compounds with molecular weights less than 1000 Da. Ten different polycyclic aromatic hydrocarbons were detected in the biologically treated leachate, most of which were effectively removed by MDEL-Fenton treatment. MDEL-Fenton process provides powerful capability in degradation of refractory and xenobiotic organic pollutants in landfill leachate and could be adopted as a single-stage polishing process for biologically treated landfill leachate to meet the stringent discharge limit.

Identification of wastewater processes

DEFF Research Database (Denmark)

Carstensen, Niels Jacob

The introduction of on-line sensors for monitoring of nutrient salts concentrations on wastewater treatment plants with nutrient removal, opens a wide new area of modelling wastewater processes. The subject of this thesis is the formulation of operational dynamic models based on time series...... of ammonia, nitrate, and phosphate concentrations, which are measured in the aeration tanks of the biological nutrient removal system. The alternatign operation modes of the BIO-DENITRO and BIO-DENIPHO processes are of particular interest. Time series models of the hydraulic and biological processes are very......-known theory of the processes with the significant effects found in data. These models are called grey box models, and they contain rate expressions for the processes of influent load of nutrients, transport of nutrients between the aeration tanks, hydrolysis and growth of biomass, nitrification...

A functional-dynamic reflection on participatory processes in modeling projects.

Science.gov (United States)

Seidl, Roman

2015-12-01

The participation of nonscientists in modeling projects/studies is increasingly employed to fulfill different functions. However, it is not well investigated if and how explicitly these functions and the dynamics of a participatory process are reflected by modeling projects in particular. In this review study, I explore participatory modeling projects from a functional-dynamic process perspective. The main differences among projects relate to the functions of participation-most often, more than one per project can be identified, along with the degree of explicit reflection (i.e., awareness and anticipation) on the dynamic process perspective. Moreover, two main approaches are revealed: participatory modeling covering diverse approaches and companion modeling. It becomes apparent that the degree of reflection on the participatory process itself is not always explicit and perfectly visible in the descriptions of the modeling projects. Thus, the use of common protocols or templates is discussed to facilitate project planning, as well as the publication of project results. A generic template may help, not in providing details of a project or model development, but in explicitly reflecting on the participatory process. It can serve to systematize the particular project's approach to stakeholder collaboration, and thus quality management.

Advanced oxidation process-biological system for wastewater containing a recalcitrant pollutant.

Science.gov (United States)

Oller, I; Malato, S; Sánchez-Pérez, J A; Maldonado, M I; Gernjak, W; Pérez-Estrada, L A

2007-01-01

Two advanced oxidation processes (AOPs), ozonation and photo-Fenton, combined with a pilot aerobic biological reactor at field scale were employed for the treatment of industrial non-biodegradable saline wastewater (TOC around 200 mgL(-1)) containing a biorecalcitrant compound, alpha-methylphenylglycine (MPG), at a concentration of 500 mgL(-1). Ozonation experiments were performed in a 50-L reactor with constant inlet ozone of 21.9 g m(-3). Solar photo-Fenton tests were carried out in a 75-L pilot plant made up of four compound parabolic collector (CPC) units. The catalyst concentration employed in this system was 20 mgL(-1) of Fe2+ and the H2O2 concentration was kept in the range of 200-500mgL(-1). Complete degradation of MPG was attained after 1,020 min of ozone treatment, while only 195 min were required for photo-Fenton. Samples from different stages of both AOPs were taken for Zahn-Wellens biocompatibility tests. Biodegradability enhancement of the industrial saline wastewater was confirmed (>70% biodegradability). Biodegradable compounds generated during the preliminary oxidative processes were biologically mineralised in a 170-L aerobic immobilised biomass reactor (IBR). The global efficiency of both AOP/biological combined systems was 90% removal of an initial TOC of over 500 mgL(-1).

Removal of pharmaceuticals from wastewater by biological processes, hydrodynamic cavitation and UV treatment.

Science.gov (United States)

Zupanc, Mojca; Kosjek, Tina; Petkovšek, Martin; Dular, Matevž; Kompare, Boris; Širok, Brane; Blažeka, Željko; Heath, Ester

2013-07-01

To augment the removal of pharmaceuticals different conventional and alternative wastewater treatment processes and their combinations were investigated. We tested the efficiency of (1) two distinct laboratory scale biological processes: suspended activated sludge and attached-growth biomass, (2) a combined hydrodynamic cavitation-hydrogen peroxide process and (3) UV treatment. Five pharmaceuticals were chosen including ibuprofen, naproxen, ketoprofen, carbamazepine and diclofenac, and an active metabolite of the lipid regulating agent clofibric acid. Biological treatment efficiency was evaluated using lab-scale suspended activated sludge and moving bed biofilm flow-through reactors, which were operated under identical conditions in respect to hydraulic retention time, working volume, concentration of added pharmaceuticals and synthetic wastewater composition. The suspended activated sludge process showed poor and inconsistent removal of clofibric acid, carbamazepine and diclofenac, while ibuprofen, naproxen and ketoprofen yielded over 74% removal. Moving bed biofilm reactors were filled with two different types of carriers i.e. Kaldnes K1 and Mutag BioChip™ and resulted in higher removal efficiencies for ibuprofen and diclofenac. Augmentation and consistency in the removal of diclofenac were observed in reactors using Mutag BioChip™ carriers (85%±10%) compared to reactors using Kaldnes carriers and suspended activated sludge (74%±22% and 48%±19%, respectively). To enhance the removal of pharmaceuticals hydrodynamic cavitation with hydrogen peroxide process was evaluated and optimal conditions for removal were established regarding the duration of cavitation, amount of added hydrogen peroxide and initial pressure, all of which influence the efficiency of the process. Optimal parameters resulted in removal efficiencies between 3-70%. Coupling the attached-growth biomass biological treatment, hydrodynamic cavitation/hydrogen peroxide process and UV treatment

Exogenic geomorphic processes dynamics at the Black Sea coast, Russia

Science.gov (United States)

Kuznetsova, Yulia; Tsvetkova, Daria

2017-04-01

Nowadays there is an obvious grow of anthropogenic load going on in many areas worldwide. Under such conditions, intensive activation of a number of exogenic geomorphic processes may be observed. Moreover, if natural environment is aggressive itself their dynamics and rates may reach enormous values. Our work is conducted at the Black Sea coast, known for its mountainous topography, wet subtropical climate and intensive anthropogenic development (especially during the last decade due to the recent Olympic games). We chose two key basins near Sochi, Russia to study a number of presented exogenic processes, including rill, gully and channel erosion, weathering, suffusion and piping, soil creep. A set of field study methods is used to monitor the processes dynamics since 2005 (and late 1970s for soil creep). In addition, soil erosion rates and landslide susceptibility were modelled to get information of the watersheds dynamics. This is ongoing work, but the results of the passed period of observations will be resented. Special attention is paid to the processes connectivity and their input into sediment redistribution over the river basins.

Dynamic process model of a plutonium oxalate precipitator. Final report

Energy Technology Data Exchange (ETDEWEB)

Miller, C.L.; Hammelman, J.E.; Borgonovi, G.M.

1977-11-01

In support of LLL material safeguards program, a dynamic process model was developed which simulates the performance of a plutonium (IV) oxalate precipitator. The plutonium oxalate precipitator is a component in the plutonium oxalate process for making plutonium oxide powder from plutonium nitrate. The model is based on state-of-the-art crystallization descriptive equations, the parameters of which are quantified through the use of batch experimental data. The dynamic model predicts performance very similar to general Hanford oxalate process experience. The utilization of such a process model in an actual plant operation could promote both process control and material safeguards control by serving as a baseline predictor which could give early warning of process upsets or material diversion. The model has been incorporated into a FORTRAN computer program and is also compatible with the DYNSYS 2 computer code which is being used at LLL for process modeling efforts.

Dynamic process model of a plutonium oxalate precipitator. Final report

International Nuclear Information System (INIS)

Miller, C.L.; Hammelman, J.E.; Borgonovi, G.M.

1977-11-01

In support of LLL material safeguards program, a dynamic process model was developed which simulates the performance of a plutonium (IV) oxalate precipitator. The plutonium oxalate precipitator is a component in the plutonium oxalate process for making plutonium oxide powder from plutonium nitrate. The model is based on state-of-the-art crystallization descriptive equations, the parameters of which are quantified through the use of batch experimental data. The dynamic model predicts performance very similar to general Hanford oxalate process experience. The utilization of such a process model in an actual plant operation could promote both process control and material safeguards control by serving as a baseline predictor which could give early warning of process upsets or material diversion. The model has been incorporated into a FORTRAN computer program and is also compatible with the DYNSYS 2 computer code which is being used at LLL for process modeling efforts

Applying the Nernst equation to simulate redox potential variations for biological nitrification and denitrification processes.

Science.gov (United States)

Chang, Cheng-Nan; Cheng, Hong-Bang; Chao, Allen C

2004-03-15

In this paper, various forms of Nernst equations have been developed based on the real stoichiometric relationship of biological nitrification and denitrification reactions. Instead of using the Nernst equation based on a one-to-one stoichiometric relation for the oxidizing and the reducing species, the basic Nernst equation is modified into slightly different forms. Each is suitable for simulating the redox potential (ORP) variation of a specific biological nitrification or denitrification process. Using the data published in the literature, the validity of these developed Nernst equations has been verified by close fits of the measured ORP data with the calculated ORP curve. The simulation results also indicate that if the biological process is simulated using an incorrect form of Nernst equation, the calculated ORP curve will not fit the measured data. Using these Nernst equations, the ORP value that corresponds to a predetermined degree of completion for the biochemical reaction can be calculated. Thus, these Nernst equations will enable a more efficient on-line control of the biological process.

Process of Argumentation in High School Biology Class: A Qualitative Analysis

Science.gov (United States)

Ramli, M.; Rakhmawati, E.; Hendarto, P.; Winarni

2017-02-01

Argumentation skill can be nurtured by designing a lesson in which students are provided with the opportunity to argue. This research aims to analyse argumentation process in biology class. The participants were students of three biology classes from different high schools in Surakarta Indonesia. One of the classroom was taught by a student teacher, and the rest were instructed by the assigned teachers. Through a classroom observation, oral activities were noted, audio-recorded and video-taped. Coding was done based on the existence of claiming-reasoning-evidence (CRE) process by McNeill and Krajcik. Data was analysed qualitatively focusing on the role of teachers to initiate questioning to support argumentation process. The lesson design of three were also analysed. The result shows that pedagogical skill of teachers to support argumentation process, such as skill to ask, answer, and respond to students’ question and statements need to be trained intensively. Most of the argumentation found were only claiming, without reasoning and evidence. Teachers have to change the routine of mostly posing open-ended questions to students, and giving directly a correct answer to students’ questions. Knowledge and skills to encourage student to follow inquiry-based learning have to be acquired by teachers.

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...

Quantifying chaotic dynamics from integrate-and-fire processes

Energy Technology Data Exchange (ETDEWEB)

Pavlov, A. N. [Department of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov (Russian Federation); Saratov State Technical University, Politehnicheskaya Str. 77, 410054 Saratov (Russian Federation); Pavlova, O. N. [Department of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov (Russian Federation); Mohammad, Y. K. [Department of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov (Russian Federation); Tikrit University Salahudin, Tikrit Qadisiyah, University Str. P.O. Box 42, Tikrit (Iraq); Kurths, J. [Potsdam Institute for Climate Impact Research, Telegraphenberg A 31, 14473 Potsdam (Germany); Institute of Physics, Humboldt University Berlin, 12489 Berlin (Germany)

2015-01-15

Characterizing chaotic dynamics from integrate-and-fire (IF) interspike intervals (ISIs) is relatively easy performed at high firing rates. When the firing rate is low, a correct estimation of Lyapunov exponents (LEs) describing dynamical features of complex oscillations reflected in the IF ISI sequences becomes more complicated. In this work we discuss peculiarities and limitations of quantifying chaotic dynamics from IF point processes. We consider main factors leading to underestimated LEs and demonstrate a way of improving numerical determining of LEs from IF ISI sequences. We show that estimations of the two largest LEs can be performed using around 400 mean periods of chaotic oscillations in the regime of phase-coherent chaos. Application to real data is discussed.

Cellular automaton modeling of biological pattern formation characterization, examples, and analysis

CERN Document Server

Deutsch, Andreas

2017-01-01

This text explores the use of cellular automata in modeling pattern formation in biological systems. It describes several mathematical modeling approaches utilizing cellular automata that can be used to study the dynamics of interacting cell systems both in simulation and in practice. New in this edition are chapters covering cell migration, tissue development, and cancer dynamics, as well as updated references and new research topic suggestions that reflect the rapid development of the field. The book begins with an introduction to pattern-forming principles in biology and the various mathematical modeling techniques that can be used to analyze them. Cellular automaton models are then discussed in detail for different types of cellular processes and interactions, including random movement, cell migration, adhesive cell interaction, alignment and cellular swarming, growth processes, pigment cell pattern formation, tissue development, tumor growth and invasion, and Turing-type patterns and excitable media. In ...

Emergence of dynamical order synchronization phenomena in complex systems

CERN Document Server

Manrubia, Susanna C; Zanette, Damián H

2004-01-01

Synchronization processes bring about dynamical order and lead tospontaneous development of structural organization in complex systemsof various origins, from chemical oscillators and biological cells tohuman societies and the brain. This book provides a review and adetailed theoretical analysis of synchronization phenomena in complexsystems with different architectures, composed of elements withperiodic or chaotic individual dynamics. Special attention is paid tostatistical concepts, such as nonequilibrium phase transitions, orderparameters and dynamical glasses.

Dynamics Explorer science data processing system

International Nuclear Information System (INIS)

Smith, P.H.; Freeman, C.H.; Hoffman, R.A.

1981-01-01

The Dynamics Explorer project has acquired the ground data processing system from the Atmosphere Explorer project to provide a central computer facility for the data processing, data management and data analysis activities of the investigators. Access to this system is via remote terminals at the investigators' facilities, which provide ready access to the data sets derived from groups of instruments on both spacecraft. The original system has been upgraded with both new hardware and enhanced software systems. These new systems include color and grey scale graphics terminals, an augmentation computer, micrographies facility, a versatile data base with a directory and data management system, and graphics display software packages. (orig.)

Diffusion-advection within dynamic biological gaps driven by structural motion

Science.gov (United States)

Asaro, Robert J.; Zhu, Qiang; Lin, Kuanpo

2018-04-01

To study the significance of advection in the transport of solutes, or particles, within thin biological gaps (channels), we examine theoretically the process driven by stochastic fluid flow caused by random thermal structural motion, and we compare it with transport via diffusion. The model geometry chosen resembles the synaptic cleft; this choice is motivated by the cleft's readily modeled structure, which allows for well-defined mechanical and physical features that control the advection process. Our analysis defines a Péclet-like number, AD, that quantifies the ratio of time scales of advection versus diffusion. Another parameter, AM, is also defined by the analysis that quantifies the full potential extent of advection in the absence of diffusion. These parameters provide a clear and compact description of the interplay among the well-defined structural, geometric, and physical properties vis-a ̀-vis the advection versus diffusion process. For example, it is found that AD˜1 /R2 , where R is the cleft diameter and hence diffusion distance. This curious, and perhaps unexpected, result follows from the dependence of structural motion that drives fluid flow on R . AM, on the other hand, is directly related (essentially proportional to) the energetic input into structural motion, and thereby to fluid flow, as well as to the mechanical stiffness of the cleftlike structure. Our model analysis thus provides unambiguous insight into the prospect of competition of advection versus diffusion within biological gaplike structures. The importance of the random, versus a regular, nature of structural motion and of the resulting transient nature of advection under random motion is made clear in our analysis. Further, by quantifying the effects of geometric and physical properties on the competition between advection and diffusion, our results clearly demonstrate the important role that metabolic energy (ATP) plays in this competitive process.

A Non-Homogeneous Dynamic Bayesian Network with Sequentially Coupled Interaction Parameters for Applications in Systems and Synthetic Biology

NARCIS (Netherlands)

Grzegorczyk, Marco; Husmeier, Dirk

2012-01-01

An important and challenging problem in systems biology is the inference of gene regulatory networks from short non-stationary time series of transcriptional profiles. A popular approach that has been widely applied to this end is based on dynamic Bayesian networks (DBNs), although traditional

Modeling Dynamic Systems with Efficient Ensembles of Process-Based Models.

Directory of Open Access Journals (Sweden)

Nikola Simidjievski

Full Text Available Ensembles are a well established machine learning paradigm, leading to accurate and robust models, predominantly applied to predictive modeling tasks. Ensemble models comprise a finite set of diverse predictive models whose combined output is expected to yield an improved predictive performance as compared to an individual model. In this paper, we propose a new method for learning ensembles of process-based models of dynamic systems. The process-based modeling paradigm employs domain-specific knowledge to automatically learn models of dynamic systems from time-series observational data. Previous work has shown that ensembles based on sampling observational data (i.e., bagging and boosting, significantly improve predictive performance of process-based models. However, this improvement comes at the cost of a substantial increase of the computational time needed for learning. To address this problem, the paper proposes a method that aims at efficiently learning ensembles of process-based models, while maintaining their accurate long-term predictive performance. This is achieved by constructing ensembles with sampling domain-specific knowledge instead of sampling data. We apply the proposed method to and evaluate its performance on a set of problems of automated predictive modeling in three lake ecosystems using a library of process-based knowledge for modeling population dynamics. The experimental results identify the optimal design decisions regarding the learning algorithm. The results also show that the proposed ensembles yield significantly more accurate predictions of population dynamics as compared to individual process-based models. Finally, while their predictive performance is comparable to the one of ensembles obtained with the state-of-the-art methods of bagging and boosting, they are substantially more efficient.

Do two machine-learning based prognostic signatures for breast cancer capture the same biological processes?

Science.gov (United States)

Drier, Yotam; Domany, Eytan

2011-03-14

The fact that there is very little if any overlap between the genes of different prognostic signatures for early-discovery breast cancer is well documented. The reasons for this apparent discrepancy have been explained by the limits of simple machine-learning identification and ranking techniques, and the biological relevance and meaning of the prognostic gene lists was questioned. Subsequently, proponents of the prognostic gene lists claimed that different lists do capture similar underlying biological processes and pathways. The present study places under scrutiny the validity of this claim, for two important gene lists that are at the focus of current large-scale validation efforts. We performed careful enrichment analysis, controlling the effects of multiple testing in a manner which takes into account the nested dependent structure of gene ontologies. In contradiction to several previous publications, we find that the only biological process or pathway for which statistically significant concordance can be claimed is cell proliferation, a process whose relevance and prognostic value was well known long before gene expression profiling. We found that the claims reported by others, of wider concordance between the biological processes captured by the two prognostic signatures studied, were found either to be lacking statistical rigor or were in fact based on addressing some other question.

Do two machine-learning based prognostic signatures for breast cancer capture the same biological processes?

Directory of Open Access Journals (Sweden)

Yotam Drier

2011-03-01

Full Text Available The fact that there is very little if any overlap between the genes of different prognostic signatures for early-discovery breast cancer is well documented. The reasons for this apparent discrepancy have been explained by the limits of simple machine-learning identification and ranking techniques, and the biological relevance and meaning of the prognostic gene lists was questioned. Subsequently, proponents of the prognostic gene lists claimed that different lists do capture similar underlying biological processes and pathways. The present study places under scrutiny the validity of this claim, for two important gene lists that are at the focus of current large-scale validation efforts. We performed careful enrichment analysis, controlling the effects of multiple testing in a manner which takes into account the nested dependent structure of gene ontologies. In contradiction to several previous publications, we find that the only biological process or pathway for which statistically significant concordance can be claimed is cell proliferation, a process whose relevance and prognostic value was well known long before gene expression profiling. We found that the claims reported by others, of wider concordance between the biological processes captured by the two prognostic signatures studied, were found either to be lacking statistical rigor or were in fact based on addressing some other question.

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.

Review on Physicochemical, Chemical, and Biological Processes for Pharmaceutical Wastewater

Science.gov (United States)

Li, Zhenchen; Yang, Ping

2018-02-01

Due to the needs of human life and health, pharmaceutical industry has made great progress in recent years, but it has also brought about severe environmental problems. The presence of pharmaceuticals in natural waters which might pose potential harm to the ecosystems and humans raised increasing concern worldwide. Pharmaceuticals cannot be effectively removed by conventional wastewater treatment plants (WWTPs) owing to the complex composition, high concentration of organic contaminants, high salinity and biological toxicity of pharmaceutical wastewater. Therefore, the development of efficient methods is needed to improve the removal effect of pharmaceuticals. This review provides an overview on three types of treatment technologies including physicochemical, chemical and biological processes and their advantages and disadvantages respectively. In addition, the future perspectives of pharmaceutical wastewater treatment are given.

Dynamic networks: Presentation held at the Workshop "Beyond Workflow Management: Supporting Dynamic Organizational Processes", CSCW 2000. 2. Dezember 2000, Philadelphia

OpenAIRE

Fuchs-Kittowski, F.

2000-01-01

Complex, dynamic organizational processes, especially problem-solving processes, require that the design and control of the cooperative work process is left to the cooperating persons. In reality of social organizations, a permanent change between extraneous- and self-organization is taking place. By integrating communication tools with application sharing synchronous CSCW systems can support dynamic workflows without restraining the self-organizing social processes of the people involved. .

Understanding system dynamics of an adaptive enzyme network from globally profiled kinetic parameters.

Science.gov (United States)

Chiang, Austin W T; Liu, Wei-Chung; Charusanti, Pep; Hwang, Ming-Jing

2014-01-15

A major challenge in mathematical modeling of biological systems is to determine how model parameters contribute to systems dynamics. As biological processes are often complex in nature, it is desirable to address this issue using a systematic approach. Here, we propose a simple methodology that first performs an enrichment test to find patterns in the values of globally profiled kinetic parameters with which a model can produce the required system dynamics; this is then followed by a statistical test to elucidate the association between individual parameters and different parts of the system's dynamics. We demonstrate our methodology on a prototype biological system of perfect adaptation dynamics, namely the chemotaxis model for Escherichia coli. Our results agreed well with those derived from experimental data and theoretical studies in the literature. Using this model system, we showed that there are motifs in kinetic parameters and that these motifs are governed by constraints of the specified system dynamics. A systematic approach based on enrichment statistical tests has been developed to elucidate the relationships between model parameters and the roles they play in affecting system dynamics of a prototype biological network. The proposed approach is generally applicable and therefore can find wide use in systems biology modeling research.

Biology and hemodynamics of aneurismal vasculopathies

International Nuclear Information System (INIS)

Pereira, Vitor Mendes; Brina, Olivier; Gonzalez, Ana Marcos; Narata, Ana Paula; Ouared, Rafik; Karl-Olof, Lovblad

2013-01-01

Aneurysm vasculopathies represents a group of vascular disorders that share a common morphological diagnosis: a vascular dilation, the aneurysm. They can have a same etiology and a different clinical presentation or morphology, or have different etiology and very similar anatomical geometry. The biology of the aneurysm formation is a complex process that will be a result of an endogenous predisposition and epigenetic factors later on including the intracranial hemodynamics. We describe the biology of saccular aneurysms, its growth and rupture, as well as, current concepts of hemodynamics derived from application of computational flow dynamics on patient specific vascular models. Furthermore, we describe different aneurysm phenotypes and its extremely variability on morphological and etiological presentation

Dynamic modeling of ultrafiltration membranes for whey separation processes

NARCIS (Netherlands)

Saltik, M.B.; Ozkan, L.; Jacobs, M.; van der Padt, A.

2017-01-01

In this paper, we present a control relevant rigorous dynamic model for an ultrafiltration membrane unit in a whey separation process. The model consists of a set of differential algebraic equations and is developed for online model based applications such as model based control and process

4D-Var data assimilation system for a coupled physical-biological ...

Indian Academy of Sciences (India)

A 3-compartment model of phytoplankton growth dynamics has been coupled with a primitive-equation circulation model to better understand and quantify physical and biological processes in the Adriatic Sea. This paper presents the development and application of a data assimilation procedure based on optimal.

Spies and Bloggers: New Synthetic Biology Tools to Understand Microbial Processes in Soils and Sediments

Science.gov (United States)

Masiello, C. A.; Silberg, J. J.; Cheng, H. Y.; Del Valle, I.; Fulk, E. M.; Gao, X.; Bennett, G. N.

2017-12-01

Microbes can be programmed through synthetic biology to report on their behavior, informing researchers when their environment has triggered changes in their gene expression (e.g. in response to shifts in O2 or H2O), or when they have participated in a specific step of an elemental cycle (e.g. denitrification). This use of synthetic biology has the potential to significantly improve our understanding of microbes' roles in elemental and water cycling, because it allows reporting on the environment from the perspective of a microbe, matching the measurement scale exactly to the scale that a microbe experiences. However, synthetic microbes have not yet seen wide use in soil and sediment laboratory experiments because synthetic organisms typically report by fluorescing, making their signals difficult to detect outside the petri dish. We are developing a new suite of microbial programs that report instead by releasing easily-detected gases, allowing the real-time, noninvasive monitoring of behaviors in sediments and soils. Microbial biosensors can, in theory, be programmed to detect dynamic processes that contribute to a wide range of geobiological processes, including C cycling (biofilm production, methanogenesis, and synthesis of extracellular enzymes that degrade organic matter), N cycling (expression of enzymes that underlie different steps of the N cycle) and potentially S cycling. We will provide an overview of the potential uses of gas-reporting biosensors in soil and sediment lab experiments, and will report the development of the systematics of these sensors. Successful development of gas biosensors for laboratory use will require addressing issues including: engineering the intensity and selectivity of microbial gas production to maximize the signal to noise ratio; normalizing the gas reporter signal to cell population size, managing gas diffusion effects on signal shape; and developing multiple gases that can be used in parallel.

Fusion of biological membranes

Indian Academy of Sciences (India)

Home; Journals; Pramana – Journal of Physics; Volume 64; Issue 6. Fusion of biological membranes. K Katsov M Müller M Schick. Invited Talks:- Topic 11. Biologically motivated problems (protein-folding models, dynamics at the scale of the cell; biological networks, evolution models, etc.) Volume 64 Issue 6 June 2005 pp ...

Sex matters: The effects of biological sex on adipose tissue biology and energy metabolism

Directory of Open Access Journals (Sweden)

Teresa G. Valencak

2017-08-01

Full Text Available Adipose tissue is a complex and multi-faceted organ. It responds dynamically to internal and external stimuli, depending on the developmental stage and activity of the organism. The most common functional subunits of adipose tissue, white and brown adipocytes, regulate and respond to endocrine processes, which then determine metabolic rate as well as adipose tissue functions. While the molecular aspects of white and brown adipose biology have become clearer in the recent past, much less is known about sex-specific differences in regulation and deposition of adipose tissue, and the specific role of the so-called pink adipocytes during lactation in females. This review summarises the current understanding of adipose tissue dynamics with a focus on sex-specific differences in adipose tissue energy metabolism and endocrine functions, focussing on mammalian model organisms as well as human-derived data. In females, pink adipocytes trans-differentiate during pregnancy from subcutaneous white adipocytes and are responsible for milk-secretion in mammary glands. Overlooking biological sex variation may ultimately hamper clinical treatments of many aspects of metabolic disorders. Keywords: Body fatness, Adipose tissue, Sex-specific differences, Adipokines, Adipocytes, Obesity, Energy metabolism

Fluid models and simulations of biological cell phenomena

Science.gov (United States)

Greenspan, H. P.

1982-01-01

The dynamics of coated droplets are examined within the context of biofluids. Of specific interest is the manner in which the shape of a droplet, the motion within it as well as that of aggregates of droplets can be controlled by the modulation of surface properties and the extent to which such fluid phenomena are an intrinsic part of cellular processes. From the standpoint of biology, an objective is to elucidate some of the general dynamical features that affect the disposition of an entire cell, cell colonies and tissues. Conventionally averaged field variables of continuum mechanics are used to describe the overall global effects which result from the myriad of small scale molecular interactions. An attempt is made to establish cause and effect relationships from correct dynamical laws of motion rather than by what may have been unnecessary invocation of metabolic or life processes. Several topics are discussed where there are strong analogies droplets and cells including: encapsulated droplets/cell membranes; droplet shape/cell shape; adhesion and spread of a droplet/cell motility and adhesion; and oams and multiphase flows/cell aggregates and tissues. Evidence is presented to show that certain concepts of continuum theory such as suface tension, surface free energy, contact angle, bending moments, etc. are relevant and applicable to the study of cell biology.

Impaired global, and compensatory local, biological motion processing in people with high levels of autistic traits.

Science.gov (United States)

van Boxtel, Jeroen J A; Lu, Hongjing

2013-01-01

People with Autism Spectrum Disorder (ASD) are hypothesized to have poor high-level processing but superior low-level processing, causing impaired social recognition, and a focus on non-social stimulus contingencies. Biological motion perception provides an ideal domain to investigate exactly how ASD modulates the interaction between low and high-level processing, because it involves multiple processing stages, and carries many important social cues. We investigated individual differences among typically developing observers in biological motion processing, and whether such individual differences associate with the number of autistic traits. In Experiment 1, we found that individuals with fewer autistic traits were automatically and involuntarily attracted to global biological motion information, whereas individuals with more autistic traits did not show this pre-attentional distraction. We employed an action adaptation paradigm in the second study to show that individuals with more autistic traits were able to compensate for deficits in global processing with an increased involvement in local processing. Our findings can be interpreted within a predictive coding framework, which characterizes the functional relationship between local and global processing stages, and explains how these stages contribute to the perceptual difficulties associated with ASD.

Impaired global, and compensatory local, biological motion processing in people with high levels of autistic traits

Directory of Open Access Journals (Sweden)

Jeroen J A Van Boxtel

2013-04-01

Full Text Available People with Autism Spectrum Disorder (ASD are hypothesized to have poor high-level processing but superior low-level processing, causing impaired social recognition, and a focus on non-social stimulus contingencies. Biological motion perception provides an ideal domain to investigate exactly how ASD modulates the interaction between low and high-level processing, because it involves multiple processing stages, and carries many important social cues. We investigated individual differences among typically developing observers in biological motion processing, and whether such individual differences associate with the number of autistic traits. In Experiment 1, we found that individuals with fewer autistic traits were automatically and involuntarily attracted to global biological motion information, whereas individuals with more autistic traits did not show this pre-attentional distraction. We employed an action adaptation paradigm in the second study to show that individuals with more autistic traits were able to compensate for deficits in global processing with an increased involvement in local processing. Our findings can be interpreted within a predictive coding framework, which characterizes the functional relationship between local and global processing stages, and explains how these stages contribute to the perceptual difficulties associated with ASD.

Unity and disunity in evolutionary sciences: process-based analogies open common research avenues for biology and linguistics.

Science.gov (United States)

List, Johann-Mattis; Pathmanathan, Jananan Sylvestre; Lopez, Philippe; Bapteste, Eric

2016-08-20

For a long time biologists and linguists have been noticing surprising similarities between the evolution of life forms and languages. Most of the proposed analogies have been rejected. Some, however, have persisted, and some even turned out to be fruitful, inspiring the transfer of methods and models between biology and linguistics up to today. Most proposed analogies were based on a comparison of the research objects rather than the processes that shaped their evolution. Focusing on process-based analogies, however, has the advantage of minimizing the risk of overstating similarities, while at the same time reflecting the common strategy to use processes to explain the evolution of complexity in both fields. We compared important evolutionary processes in biology and linguistics and identified processes specific to only one of the two disciplines as well as processes which seem to be analogous, potentially reflecting core evolutionary processes. These new process-based analogies support novel methodological transfer, expanding the application range of biological methods to the field of historical linguistics. We illustrate this by showing (i) how methods dealing with incomplete lineage sorting offer an introgression-free framework to analyze highly mosaic word distributions across languages; (ii) how sequence similarity networks can be used to identify composite and borrowed words across different languages; (iii) how research on partial homology can inspire new methods and models in both fields; and (iv) how constructive neutral evolution provides an original framework for analyzing convergent evolution in languages resulting from common descent (Sapir's drift). Apart from new analogies between evolutionary processes, we also identified processes which are specific to either biology or linguistics. This shows that general evolution cannot be studied from within one discipline alone. In order to get a full picture of evolution, biologists and linguists need to

Application of the recurrent multilayer perceptron in modeling complex process dynamics.

Science.gov (United States)

Parlos, A G; Chong, K T; Atiya, A F

1994-01-01

A nonlinear dynamic model is developed for a process system, namely a heat exchanger, using the recurrent multilayer perceptron network as the underlying model structure. The perceptron is a dynamic neural network, which appears effective in the input-output modeling of complex process systems. Dynamic gradient descent learning is used to train the recurrent multilayer perceptron, resulting in an order of magnitude improvement in convergence speed over a static learning algorithm used to train the same network. In developing the empirical process model the effects of actuator, process, and sensor noise on the training and testing sets are investigated. Learning and prediction both appear very effective, despite the presence of training and testing set noise, respectively. The recurrent multilayer perceptron appears to learn the deterministic part of a stochastic training set, and it predicts approximately a moving average response of various testing sets. Extensive model validation studies with signals that are encountered in the operation of the process system modeled, that is steps and ramps, indicate that the empirical model can substantially generalize operational transients, including accurate prediction of instabilities not in the training set. However, the accuracy of the model beyond these operational transients has not been investigated. Furthermore, online learning is necessary during some transients and for tracking slowly varying process dynamics. Neural networks based empirical models in some cases appear to provide a serious alternative to first principles models.

Cellular potts models multiscale extensions and biological applications

CERN Document Server

Scianna, Marco

2013-01-01

A flexible, cell-level, and lattice-based technique, the cellular Potts model accurately describes the phenomenological mechanisms involved in many biological processes. Cellular Potts Models: Multiscale Extensions and Biological Applications gives an interdisciplinary, accessible treatment of these models, from the original methodologies to the latest developments. The book first explains the biophysical bases, main merits, and limitations of the cellular Potts model. It then proposes several innovative extensions, focusing on ways to integrate and interface the basic cellular Potts model at the mesoscopic scale with approaches that accurately model microscopic dynamics. These extensions are designed to create a nested and hybrid environment, where the evolution of a biological system is realistically driven by the constant interplay and flux of information between the different levels of description. Through several biological examples, the authors demonstrate a qualitative and quantitative agreement with t...

Oscillation and stability of delay models in biology

CERN Document Server

Agarwal, Ravi P; Saker, Samir H

2014-01-01

Environmental variation plays an important role in many biological and ecological dynamical systems. This monograph focuses on the study of oscillation and the stability of delay models occurring in biology. The book presents recent research results on the qualitative behavior of mathematical models under different physical and environmental conditions, covering dynamics including the distribution and consumption of food. Researchers in the fields of mathematical modeling, mathematical biology, and population dynamics will be particularly interested in this material.

Implementing Firm Dynamic Capabilities Through the Concept Design Process

DEFF Research Database (Denmark)

Nedergaard, Nicky; Jones, Richard

2011-01-01

It is well understood that firms operating in highly dynamic and fluid markets need to possess strong dynamic capabilities of sensing (market trajectories), seizing (to capitalise on these trajectories), and transformation (in order to implement sustainable strategies). Less understood is how firms...... actually implement these capabilities. A conceptual model showing how managing concept design processes can help firms systematically develop dynamic capabilities and help bridge the gap between the market-oriented and resource-focused strategic perspectives is presented. By placing this model in a design......-driven innovation perspective three theoretical propositions is derived explicating both the paper’s implementation approach to dynamic capabilities as well as new ways of understanding these capabilities. Concluding remarks are made discussing both the paper’s contribution to the strategic marketing literature...

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....

Wavelet data processing of micro-Raman spectra of biological samples

Science.gov (United States)

Camerlingo, C.; Zenone, F.; Gaeta, G. M.; Riccio, R.; Lepore, M.

2006-02-01

A wavelet multi-component decomposition algorithm is proposed for processing data from micro-Raman spectroscopy (μ-RS) of biological tissue. The μ-RS has been recently recognized as a promising tool for the biopsy test and in vivo diagnosis of degenerative human tissue pathologies, due to the high chemical and structural information contents of this spectroscopic technique. However, measurements of biological tissues are usually hampered by typically low-level signals and by the presence of noise and background components caused by light diffusion or fluorescence processes. In order to overcome these problems, a numerical method based on discrete wavelet transform is used for the analysis of data from μ-RS measurements performed in vitro on animal (pig and chicken) tissue samples and, in a preliminary form, on human skin and oral tissue biopsy from normal subjects. Visible light μ-RS was performed using a He-Ne laser and a monochromator with a liquid nitrogen cooled charge coupled device equipped with a grating of 1800 grooves mm-1. The validity of the proposed data procedure has been tested on the well-characterized Raman spectra of reference acetylsalicylic acid samples.

Single amino acid substitution in important hemoglobinopathies does not disturb molecular function and biological process

Directory of Open Access Journals (Sweden)

Viroj Wiwanitkit

2008-06-01

Full Text Available Viroj WiwanitkitDepartment of Laboratory Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, ThailandAbstract: Hemoglobin is an important protein found in the red cells of many animals. In humans, the hemoglobin is mainly distributed in the red blood cell. Single amino acid substitution is the main pathogenesis of most hemoglobin disorders. Here, the author used a new gene ontology technology to predict the molecular function and biological process of four important hemoglobin disorders with single substitution. The four studied important abnormal hemoglobins (Hb with single substitution included Hb S, Hb E, Hb C, and Hb J-Baltimore. Using the GoFigure server, the molecular function and biological process in normal and abnormal hemoglobins was predicted. Compared with normal hemoglobin, all studied abnormal hemoglobins had the same function and biological process. This indicated that the overall function of oxygen transportation is not disturbed in the studied hemoglobin disorders. Clinical findings of oxygen depletion in abnormal hemoglobin should therefore be due to the other processes rather than genomics, proteomics, and expression levels.Keywords: hemoglobin, amino acid, substitution, function

Dynamical Systems Theory: Application to Pedagogy

Science.gov (United States)

Abraham, Jane L.

Theories of learning affect how cognition is viewed, and this subsequently leads to the style of pedagogical practice that is used in education. Traditionally, educators have relied on a variety of theories on which to base pedagogy. Behavioral learning theories influenced the teaching/learning process for over 50 years. In the 1960s, the information processing approach brought the mind back into the learning process. The current emphasis on constructivism integrates the views of Piaget, Vygotsky, and cognitive psychology. Additionally, recent scientific advances have allowed researchers to shift attention to biological processes in cognition. The problem is that these theories do not provide an integrated approach to understanding principles responsible for differences among students in cognitive development and learning ability. Dynamical systems theory offers a unifying theoretical framework to explain the wider context in which learning takes place and the processes involved in individual learning. This paper describes how principles of Dynamic Systems Theory can be applied to cognitive processes of students, the classroom community, motivation to learn, and the teaching/learning dynamic giving educational psychologists a framework for research and pedagogy.

Molecular dynamics study of dynamic and structural properties of supercooled liquid and glassy iron in the rapid-cooling processes

Energy Technology Data Exchange (ETDEWEB)

Cao, Qi-Long; Huang, Duo-Hui; Yang, Jun-Sheng; Wan, Min-Jie; Wang, Fan-Hou, E-mail: eatonch@gmail.com

2014-10-01

Molecular dynamics simulations were applied to study the dynamic and structural properties of supercooled liquid and glassy iron in the rapid-cooling processes. The mean-square displacement and the non-Gaussian parameter were used to describe the dynamic properties. The evolution of structural properties was investigated using the pair distribution functions and bond-angle distribution functions. Results for dynamic and structural relaxations indicate that the dynamic features are consistently correlated with the structure evolution, and there are three temperature regions as the temperature decreases: (1) at higher temperatures (1500 K, 1300 K, and 1100 K), the system remains in the liquid characteristics during the overall relaxation process. (2) At medial temperatures (1050 K, 900 K, and 700 K), a fast β-relaxation is followed by a much slower α-relaxation. There is a little change in the structural properties in the β-relaxation region, while major configuration rearrangements occurred in the α-relaxation range and the crystallization process was completed at the end of α-relaxation region. (3) At lower temperature (500 K), the system shows glassy characteristics during the overall relaxation process. In addition, the melting temperature, glass transition temperature and diffusion coefficients of supercooled liquid iron are also computed.

Effect of Food Regulation on the Spanish Food Processing Industry: A Dynamic Productivity Analysis.

Science.gov (United States)

Kapelko, Magdalena; Oude Lansink, Alfons; Stefanou, Spiro E

2015-01-01

This article develops the decomposition of the dynamic Luenberger productivity growth indicator into dynamic technical change, dynamic technical inefficiency change and dynamic scale inefficiency change in the dynamic directional distance function context using Data Envelopment Analysis. These results are used to investigate for the Spanish food processing industry the extent to which dynamic productivity growth and its components are affected by the introduction of the General Food Law in 2002 (Regulation (EC) No 178/2002). The empirical application uses panel data of Spanish meat, dairy, and oils and fats industries over the period 1996-2011. The results suggest that in the oils and fats industry the impact of food regulation on dynamic productivity growth is negative initially and then positive over the long run. In contrast, the opposite pattern is observed for the meat and dairy processing industries. The results further imply that firms in the meat processing and oils and fats industries face similar impacts of food safety regulation on dynamic technical change, dynamic inefficiency change and dynamic scale inefficiency change.

Effect of Food Regulation on the Spanish Food Processing Industry: A Dynamic Productivity Analysis

Science.gov (United States)

Kapelko, Magdalena; Lansink, Alfons Oude; Stefanou, Spiro E.

2015-01-01

This article develops the decomposition of the dynamic Luenberger productivity growth indicator into dynamic technical change, dynamic technical inefficiency change and dynamic scale inefficiency change in the dynamic directional distance function context using Data Envelopment Analysis. These results are used to investigate for the Spanish food processing industry the extent to which dynamic productivity growth and its components are affected by the introduction of the General Food Law in 2002 (Regulation (EC) No 178/2002). The empirical application uses panel data of Spanish meat, dairy, and oils and fats industries over the period 1996-2011. The results suggest that in the oils and fats industry the impact of food regulation on dynamic productivity growth is negative initially and then positive over the long run. In contrast, the opposite pattern is observed for the meat and dairy processing industries. The results further imply that firms in the meat processing and oils and fats industries face similar impacts of food safety regulation on dynamic technical change, dynamic inefficiency change and dynamic scale inefficiency change. PMID:26057878

4D-Var data assimilation system for a coupled physical biological ...

Indian Academy of Sciences (India)

A 3-compartment model of phytoplankton growth dynamics has been coupled with a primitive-equation circulation model to better understand and quantify physical and biological processes in the Adriatic Sea. This paper presents the development and application of a data assimilation procedure based on optimal control ...

Adoption: biological and social processes linked to adaptation.

Science.gov (United States)

Grotevant, Harold D; McDermott, Jennifer M

2014-01-01

Children join adoptive families through domestic adoption from the public child welfare system, infant adoption through private agencies, and international adoption. Each pathway presents distinctive developmental opportunities and challenges. Adopted children are at higher risk than the general population for problems with adaptation, especially externalizing, internalizing, and attention problems. This review moves beyond the field's emphasis on adoptee-nonadoptee differences to highlight biological and social processes that affect adaptation of adoptees across time. The experience of stress, whether prenatal, postnatal/preadoption, or during the adoption transition, can have significant impacts on the developing neuroendocrine system. These effects can contribute to problems with physical growth, brain development, and sleep, activating cascading effects on social, emotional, and cognitive development. Family processes involving contact between adoptive and birth family members, co-parenting in gay and lesbian adoptive families, and racial socialization in transracially adoptive families affect social development of adopted children into adulthood.

Development trend of radiation biology research-systems radiation biology

International Nuclear Information System (INIS)

Min Rui

2010-01-01

Radiation biology research has past 80 years. We have known much more about fundamentals, processes and results of biology effects induced by radiation and various factors that influence biology effects wide and deep, however many old and new scientific problems occurring in the field of radiation biology research remain to be illustrated. To explore and figure these scientific problems need systemic concept, methods and multi dimension view on the base of considerations of complexity of biology system, diversity of biology response, temporal and spatial process of biological effects during occurrence, and complex feed back network of biological regulations. (authors)

Synthetic biological networks

International Nuclear Information System (INIS)

Archer, Eric; Süel, Gürol M

2013-01-01

Despite their obvious relationship and overlap, the field of physics is blessed with many insightful laws, while such laws are sadly absent in biology. Here we aim to discuss how the rise of a more recent field known as synthetic biology may allow us to more directly test hypotheses regarding the possible design principles of natural biological networks and systems. In particular, this review focuses on synthetic gene regulatory networks engineered to perform specific functions or exhibit particular dynamic behaviors. Advances in synthetic biology may set the stage to uncover the relationship of potential biological principles to those developed in physics. (review article)

Network Dynamics of Innovation Processes

Science.gov (United States)

Iacopini, Iacopo; Milojević, Staša; Latora, Vito

2018-01-01

We introduce a model for the emergence of innovations, in which cognitive processes are described as random walks on the network of links among ideas or concepts, and an innovation corresponds to the first visit of a node. The transition matrix of the random walk depends on the network weights, while in turn the weight of an edge is reinforced by the passage of a walker. The presence of the network naturally accounts for the mechanism of the "adjacent possible," and the model reproduces both the rate at which novelties emerge and the correlations among them observed empirically. We show this by using synthetic networks and by studying real data sets on the growth of knowledge in different scientific disciplines. Edge-reinforced random walks on complex topologies offer a new modeling framework for the dynamics of correlated novelties and are another example of coevolution of processes and networks.

New sources and instrumentation for neutrons in biology

DEFF Research Database (Denmark)

Teixeira, S. C. M.; Zaccai, G.; Ankner, J.

2008-01-01

Neutron radiation offers significant advantages for the study of biological molecular structure and dynamics. A broad and significant effort towards instrumental and methodological development to facilitate biology experiments at neutron sources worldwide is reviewed.......Neutron radiation offers significant advantages for the study of biological molecular structure and dynamics. A broad and significant effort towards instrumental and methodological development to facilitate biology experiments at neutron sources worldwide is reviewed....

Nonequilibrium thermodynamics transport and rate processes in physical, chemical and biological systems

CERN Document Server

Demirel, Yasar

2014-01-01

Natural phenomena consist of simultaneously occurring transport processes and chemical reactions. These processes may interact with each other and may lead to self-organized structures, fluctuations, instabilities, and evolutionary systems. Nonequilibrium Thermodynamics, 3rd edition emphasizes the unifying role of thermodynamics in analyzing the natural phenomena. This third edition updates and expands on the first and second editions by focusing on the general balance equations for coupled processes of physical, chemical, and biological systems. The new edition contains a new chapte

Integrating interactive computational modeling in biology curricula.

Directory of Open Access Journals (Sweden)

Tomáš Helikar

2015-03-01

Full Text Available While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.

Integrating interactive computational modeling in biology curricula.

Science.gov (United States)

Helikar, Tomáš; Cutucache, Christine E; Dahlquist, Lauren M; Herek, Tyler A; Larson, Joshua J; Rogers, Jim A

2015-03-01

While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology) class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.

The role of reconsolidation and the dynamic process of long-term memory formation and storage

Directory of Open Access Journals (Sweden)

Cristina M Alberini

2011-03-01

Full Text Available It is becoming increasingly clear that the processes of memory formation and storage are exquisitely dynamic. Elucidating the nature and temporal evolution of the biological changes that accompany encoding, storage and retrieval is key to understand memory formation. For explicit or medial temporal lobe-dependent memories that form after a discrete event and are stored for a long time, the physical changes underlying the encoding and processing of the information (memory trace or engram remain in a fragile state for some time. However, over time, the new memory becomes increasingly resistant to disruption until it is consolidated. Retrieval or reactivation of an apparently consolidated memory can render the memory labile again, and reconsolidation is the process that occurs to mediate its restabilization. Reconsolidation also evolves with the age of the memory: Young memories are sensitive to postreactivation disruption, but older memories are more resistant. Why does a memory become labile again if it is retrieved or reactivated? Here I suggest that the main function of reconsolidation is to contribute to the lingering consolidation process and mediate memory strengthening. I also discuss the literature and results regarding the influence of the passage of time on the reconsolidation of memory. These points have important implications for the use of reconsolidation in therapeutic settings.

Interactions of heavy ions with biomolecules: a dynamical microscopic approach

International Nuclear Information System (INIS)

Zhang Fengshou; Beijing Radiation Center, Beijing; National Laboratory of Heavy Ion Accelerator of Lanzhou, Lanzhou

2006-01-01

The status of studying biology system therapy with X-rays, γ-rays, neutron, proton, and heavy ions is reviewed. The depth dose profile, called Bragg profile, makes heavy ion an ideal tool for radiotherapy. The physical process of therapy with heavy ions is analyzed and a 3-step interaction processes of heavy ions with biomolecules is proposed, that is, nuclear fragmentation in nuclear interaction, electron excitation in Coulomb interaction, and the biomolecules relaxation in surroundings, finally leads to a new structure of biomolecule. Since this physical process is the base of the following chemical process and biological process, a dynamical microscopic approach is strongly demanded to be built. (authors)

Computational systems biology and dose-response modeling in relation to new directions in toxicity testing.

Science.gov (United States)

Zhang, Qiang; Bhattacharya, Sudin; Andersen, Melvin E; Conolly, Rory B

2010-02-01

The new paradigm envisioned for toxicity testing in the 21st century advocates shifting from the current animal-based testing process to a combination of in vitro cell-based studies, high-throughput techniques, and in silico modeling. A strategic component of the vision is the adoption of the systems biology approach to acquire, analyze, and interpret toxicity pathway data. As key toxicity pathways are identified and their wiring details elucidated using traditional and high-throughput techniques, there is a pressing need to understand their qualitative and quantitative behaviors in response to perturbation by both physiological signals and exogenous stressors. The complexity of these molecular networks makes the task of understanding cellular responses merely by human intuition challenging, if not impossible. This process can be aided by mathematical modeling and computer simulation of the networks and their dynamic behaviors. A number of theoretical frameworks were developed in the last century for understanding dynamical systems in science and engineering disciplines. These frameworks, which include metabolic control analysis, biochemical systems theory, nonlinear dynamics, and control theory, can greatly facilitate the process of organizing, analyzing, and understanding toxicity pathways. Such analysis will require a comprehensive examination of the dynamic properties of "network motifs"--the basic building blocks of molecular circuits. Network motifs like feedback and feedforward loops appear repeatedly in various molecular circuits across cell types and enable vital cellular functions like homeostasis, all-or-none response, memory, and biological rhythm. These functional motifs and associated qualitative and quantitative properties are the predominant source of nonlinearities observed in cellular dose response data. Complex response behaviors can arise from toxicity pathways built upon combinations of network motifs. While the field of computational cell

Web Services Support for Dynamic Business Process Outsourcing

NARCIS (Netherlands)

Grefen, P.W.P.J.; Ludwig, Heiko; Dan, Asit; Angelov, S.A.

2003-01-01

Outsourcing of business processes is crucial for organizations to be effective, efficient and flexible. To meet fast-changing market conditions, dynamic outsourcing is required, in which business relationships are established and enacted on-the-fly in an adaptive, fine-grained way unrestricted by

Multi-level and hybrid modelling approaches for systems biology.

Science.gov (United States)

Bardini, R; Politano, G; Benso, A; Di Carlo, S

2017-01-01

During the last decades, high-throughput techniques allowed for the extraction of a huge amount of data from biological systems, unveiling more of their underling complexity. Biological systems encompass a wide range of space and time scales, functioning according to flexible hierarchies of mechanisms making an intertwined and dynamic interplay of regulations. This becomes particularly evident in processes such as ontogenesis, where regulative assets change according to process context and timing, making structural phenotype and architectural complexities emerge from a single cell, through local interactions. The information collected from biological systems are naturally organized according to the functional levels composing the system itself. In systems biology, biological information often comes from overlapping but different scientific domains, each one having its own way of representing phenomena under study. That is, the different parts of the system to be modelled may be described with different formalisms. For a model to have improved accuracy and capability for making a good knowledge base, it is good to comprise different system levels, suitably handling the relative formalisms. Models which are both multi-level and hybrid satisfy both these requirements, making a very useful tool in computational systems biology. This paper reviews some of the main contributions in this field.

Fixation and utilization of CO2 by biological and/or chemical processes

International Nuclear Information System (INIS)

Hiromichi, N.

1994-01-01

This paper presents the carbon dioxide fixation and utilisation by biological and/or chemical processes. It presents research objectives and program contents for the effective fixation of carbon dioxide by micro-organism and its hydrogenation. (TEC). 5 figs., 2 tabs

Degrading organic micropollutants: The next challenge in the evolution of biological wastewater treatment processes

Directory of Open Access Journals (Sweden)

Naresh eSinghal

2016-05-01

Full Text Available Global water scarcity is driving the need for identifying new water source. Wastewater could be a potential water resource if appropriate treatment technologies could be developed. One of the barriers to obtaining high quality water from wastewater arises from the presence of organic micropollutants, which are biologically active at trace levels. Removal of these compounds from wastewater by current physico-chemical technologies is prohibitively expensive. While biological treatment processes are comparatively cheap, current systems are not capable of degrading the wide range of organic micropollutants present in wastewater. As current wastewater treatment processes were developed for treating conventional pollutants present at mg/L levels, degrading the ng/L levels of micropollutants will require a different approach to system design and operation. In this paper we discuss strategies that could be employed to develop biological wastewater treatment systems capable of degrading organic micropollutants.

6,7-dimethoxy-coumarin as a probe of hydration dynamics in biologically relevant systems

Science.gov (United States)

Ghose, Avisek; Amaro, Mariana; Kovaricek, Petr; Hof, Martin; Sykora, Jan

2018-04-01

Coumarin derivatives are well known fluorescence reporters for investigating biological systems due to their strong micro-environment sensitivity. Despite having wide range of environment sensitive fluorescence probes, the potential of 6,7-dimethoxy-coumarin has not been studied extensively so far. With a perspective of its use in protein studies, namely using the unnatural amino acid technology or as a substrate for hydrolase enzymes, we study acetyloxymethyl-6,7-dimethoxycoumarin (Ac-DMC). We investigate the photophysics and hydration dynamics of this dye in aerosol-OT (AOT) reverse micelles at various water contents using the time dependent fluorescence shift (TDFS) method. The TDFS response in AOT reverse micelles from water/surfactant ratio of 0 to 20 confirms its sensitivity towards the hydration and mobility of its microenvironment. Moreover, we show that the fluorophore can be efficiently quenched by halide ions. Hence, we conclude that the 6,7-dimethoxy-methylcoumarin fluorophore is useful for studying hydration parameters in biologically relevant systems.

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.

The representational dynamics of task and object processing in humans

Science.gov (United States)

Bankson, Brett B; Harel, Assaf

2018-01-01

Despite the importance of an observer’s goals in determining how a visual object is categorized, surprisingly little is known about how humans process the task context in which objects occur and how it may interact with the processing of objects. Using magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI) and multivariate techniques, we studied the spatial and temporal dynamics of task and object processing. Our results reveal a sequence of separate but overlapping task-related processes spread across frontoparietal and occipitotemporal cortex. Task exhibited late effects on object processing by selectively enhancing task-relevant object features, with limited impact on the overall pattern of object representations. Combining MEG and fMRI data, we reveal a parallel rise in task-related signals throughout the cerebral cortex, with an increasing dominance of task over object representations from early to higher visual areas. Collectively, our results reveal the complex dynamics underlying task and object representations throughout human cortex. PMID:29384473

Numerical studies of neon gas-puff Z-pinch dynamic processes

International Nuclear Information System (INIS)

Ning Cheng; Yang Zhenhua; Ding Ning

2003-01-01

Dynamic processes of neon gas-puff Z-pinch are studied numerically in this paper. A high temperature plasma with a high density can be generated in the process. Based on some physical analysis and assumption, a set of equations of one-dimensional Lagrangian radiation magneto-hydrodynamic (MHD) and its code are developed to solve the problem. Spatio-temporal distributions of plasma parameters in the processes are obtained, and their dynamic variations show that the major results are self-consistent. The duration for the plasma pinched to centre, as well as the width and the total energy of the x-ray pulse caused by the Z-pinch are in reasonable agreement with experimental results of GAMBLE-II. A zipping effect is also clearly shown in the simulation

Howard Brenner's Legacy for Biological Transport Processes

Science.gov (United States)

Nitsche, Johannes

2014-11-01

This talk discusses the manner in which Howard Brenner's theoretical contributions have had, and long will have, strong and direct impact on the understanding of transport processes occurring in biological systems. His early work on low Reynolds number resistance/mobility coefficients of arbitrarily shaped particles, and particles near walls and in pores, is an essential component of models of hindered diffusion through many types of membranes and tissues, and convective transport in microfluidic diagnostic systems. His seminal contributions to macrotransport (coarse-graining, homogenization) theory presaged the growing discipline of multiscale modeling. For biological systems they represent the key to infusing diffusion models of a wide variety of tissues with a sound basis in their microscopic structure and properties, often over a hierarchy of scales. Both scientific currents are illustrated within the concrete context of diffusion models of drug/chemical diffusion through the skin. This area of theory, which is key to transdermal drug development and risk assessment of chemical exposure, has benefitted very directly from Brenner's contributions. In this as in other areas, Brenner's physicochemical insight, mathematical virtuosity, drive for fully justified analysis free of ad hoc assumptions, quest for generality, and impeccable exposition, have consistently elevated the level of theoretical understanding and presentation. We close with anecdotes showing how his personal qualities and warmth helped to impart high standards of rigor to generations of grateful research students. Authors are Johannes M. Nitsche, Ludwig C. Nitsche and Gerald B. Kasting.

Direction of Amygdala-Neocortex Interaction During Dynamic Facial Expression Processing.

Science.gov (United States)

Sato, Wataru; Kochiyama, Takanori; Uono, Shota; Yoshikawa, Sakiko; Toichi, Motomi

2017-03-01

Dynamic facial expressions of emotion strongly elicit multifaceted emotional, perceptual, cognitive, and motor responses. Neuroimaging studies revealed that some subcortical (e.g., amygdala) and neocortical (e.g., superior temporal sulcus and inferior frontal gyrus) brain regions and their functional interaction were involved in processing dynamic facial expressions. However, the direction of the functional interaction between the amygdala and the neocortex remains unknown. To investigate this issue, we re-analyzed functional magnetic resonance imaging (fMRI) data from 2 studies and magnetoencephalography (MEG) data from 1 study. First, a psychophysiological interaction analysis of the fMRI data confirmed the functional interaction between the amygdala and neocortical regions. Then, dynamic causal modeling analysis was used to compare models with forward, backward, or bidirectional effective connectivity between the amygdala and neocortical networks in the fMRI and MEG data. The results consistently supported the model of effective connectivity from the amygdala to the neocortex. Further increasing time-window analysis of the MEG demonstrated that this model was valid after 200 ms from the stimulus onset. These data suggest that emotional processing in the amygdala rapidly modulates some neocortical processing, such as perception, recognition, and motor mimicry, when observing dynamic facial expressions of emotion. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Dynamic Modeling of Process Technologies for Closed-Loop Water Recovery Systems

Science.gov (United States)

Allada, Rama Kumar; Lange, Kevin; Anderson, Molly

2011-01-01

Detailed chemical process simulations are a useful tool in designing and optimizing complex systems and architectures for human life support. Dynamic and steady-state models of these systems help contrast the interactions of various operating parameters and hardware designs, which become extremely useful in trade-study analyses. NASA s Exploration Life Support technology development project recently made use of such models to compliment a series of tests on different waste water distillation systems. This paper presents dynamic simulations of chemical process for primary processor technologies including: the Cascade Distillation System (CDS), the Vapor Compression Distillation (VCD) system, the Wiped-Film Rotating Disk (WFRD), and post-distillation water polishing processes such as the Volatiles Removal Assembly (VRA) that were developed using the Aspen Custom Modeler and Aspen Plus process simulation tools. The results expand upon previous work for water recovery technology models and emphasize dynamic process modeling and results. The paper discusses system design, modeling details, and model results for each technology and presents some comparisons between the model results and available test data. Following these initial comparisons, some general conclusions and forward work are discussed.

Dynamic information processing states revealed through neurocognitive models of object semantics

Science.gov (United States)

Clarke, Alex

2015-01-01

Recognising objects relies on highly dynamic, interactive brain networks to process multiple aspects of object information. To fully understand how different forms of information about objects are represented and processed in the brain requires a neurocognitive account of visual object recognition that combines a detailed cognitive model of semantic knowledge with a neurobiological model of visual object processing. Here we ask how specific cognitive factors are instantiated in our mental processes and how they dynamically evolve over time. We suggest that coarse semantic information, based on generic shared semantic knowledge, is rapidly extracted from visual inputs and is sufficient to drive rapid category decisions. Subsequent recurrent neural activity between the anterior temporal lobe and posterior fusiform supports the formation of object-specific semantic representations – a conjunctive process primarily driven by the perirhinal cortex. These object-specific representations require the integration of shared and distinguishing object properties and support the unique recognition of objects. We conclude that a valuable way of understanding the cognitive activity of the brain is though testing the relationship between specific cognitive measures and dynamic neural activity. This kind of approach allows us to move towards uncovering the information processing states of the brain and how they evolve over time. PMID:25745632

Diagnosis of dynamic process over rainband of landfall typhoon

International Nuclear Information System (INIS)

Ling-Kun, Ran; Wen-Xia, Yang; Yan-Li, Chu

2010-01-01

This paper introduces a new physical parameter — thermodynamic shear advection parameter combining the perturbation vertical component of convective vorticity vector with the coupling of horizontal divergence perturbation and vertical gradient of general potential temperature perturbation. For a heavy-rainfall event resulting from the landfall typhoon 'Wipha', the parameter is calculated by using National Centres for Enviromental Prediction/National Centre for Atmospheric Research global final analysis data. The results showed that the parameter corresponds to the observed 6 h accumulative rainband since it is capable of catching hold of the dynamic and thermodynamic disturbance in the lower troposphere over the observed rainband. Before the typhoon landed, the advection of the parameter by basic-state flow and the coupling of general potential temperature perturbation with curl of Coriolis force perturbation are the primary dynamic processes which are responsible for the local change of the parameter. After the typhoon landed, the disturbance is mainly driven by the combination of five primary dynamic processes. The advection of the parameter by basic-state flow was weakened after the typhoon landed. (geophysics, astronomy and astrophysics)

Diagnosis of dynamic process over rainband of landfall typhoon

Science.gov (United States)

Ran, Ling-Kun; Yang, Wen-Xia; Chu, Yan-Li

2010-07-01

This paper introduces a new physical parameter — thermodynamic shear advection parameter combining the perturbation vertical component of convective vorticity vector with the coupling of horizontal divergence perturbation and vertical gradient of general potential temperature perturbation. For a heavy-rainfall event resulting from the landfall typhoon 'Wipha', the parameter is calculated by using National Centres for Enviromental Prediction/National Centre for Atmospheric Research global final analysis data. The results showed that the parameter corresponds to the observed 6 h accumulative rainband since it is capable of catching hold of the dynamic and thermodynamic disturbance in the lower troposphere over the observed rainband. Before the typhoon landed, the advection of the parameter by basic-state flow and the coupling of general potential temperature perturbation with curl of Coriolis force perturbation are the primary dynamic processes which are responsible for the local change of the parameter. After the typhoon landed, the disturbance is mainly driven by the combination of five primary dynamic processes. The advection of the parameter by basic-state flow was weakened after the typhoon landed.

Software for the nuclear reactor dynamics study using time series processing

International Nuclear Information System (INIS)

Valero, Esbel T.; Montesino, Maria E.

1997-01-01

The parametric monitoring in Nuclear Power Plant (NPP) permits the operational surveillance of nuclear reactor. The methods employed in order to process this information such as FFT, autoregressive models and other, have some limitations when those regimens in which appear strongly non-linear behaviors are analyzed. In last years the chaos theory has offered new ways in order to explain complex dynamic behaviors. This paper describes a software (ECASET) that allow, by time series processing from NPP's acquisition system, to characterize the nuclear reactor dynamic as a complex dynamical system. Here we show using ECASET's results the possibility of classifying the different regimens appearing in nuclear reactors. The results of several temporal series processing from real systems are introduced. This type of analysis complements the results obtained with traditional methods and can constitute a new tool for monitoring nuclear reactors. (author). 13 refs., 3 figs

Scaling for Dynamical Systems in Biology.

Science.gov (United States)

Ledder, Glenn

2017-11-01

Asymptotic methods can greatly simplify the analysis of all but the simplest mathematical models and should therefore be commonplace in such biological areas as ecology and epidemiology. One essential difficulty that limits their use is that they can only be applied to a suitably scaled dimensionless version of the original dimensional model. Many books discuss nondimensionalization, but with little attention given to the problem of choosing the right scales and dimensionless parameters. In this paper, we illustrate the value of using asymptotics on a properly scaled dimensionless model, develop a set of guidelines that can be used to make good scaling choices, and offer advice for teaching these topics in differential equations or mathematical biology courses.

Microbial ecology of denitrification in biological wastewater treatment.

Science.gov (United States)

Lu, Huijie; Chandran, Kartik; Stensel, David

2014-11-01

Globally, denitrification is commonly employed in biological nitrogen removal processes to enhance water quality. However, substantial knowledge gaps remain concerning the overall community structure, population dynamics and metabolism of different organic carbon sources. This systematic review provides a summary of current findings pertaining to the microbial ecology of denitrification in biological wastewater treatment processes. DNA fingerprinting-based analysis has revealed a high level of microbial diversity in denitrification reactors and highlighted the impacts of carbon sources in determining overall denitrifying community composition. Stable isotope probing, fluorescence in situ hybridization, microarrays and meta-omics further link community structure with function by identifying the functional populations and their gene regulatory patterns at the transcriptional and translational levels. This review stresses the need to integrate microbial ecology information into conventional denitrification design and operation at full-scale. Some emerging questions, from physiological mechanisms to practical solutions, for example, eliminating nitrous oxide emissions and supplementing more sustainable carbon sources than methanol, are also discussed. A combination of high-throughput approaches is next in line for thorough assessment of wastewater denitrifying community structure and function. Though denitrification is used as an example here, this synergy between microbial ecology and process engineering is applicable to other biological wastewater treatment processes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Dynamic simulation and modeling of the motion modes produced during the 3D controlled manipulation of biological micro/nanoparticles based on the AFM.

Science.gov (United States)

Saraee, Mahdieh B; Korayem, Moharam H

2015-08-07

Determining the motion modes and the exact position of a particle displaced during the manipulation process is of special importance. This issue becomes even more important when the studied particles are biological micro/nanoparticles and the goals of manipulation are the transfer of these particles within body cells, repair of cancerous cells and the delivery of medication to damaged cells. However, due to the delicate nature of biological nanoparticles and their higher vulnerability, by obtaining the necessary force of manipulation for the considered motion mode, we can prevent the sample from interlocking with or sticking to the substrate because of applying a weak force or avoid damaging the sample due to the exertion of excessive force. In this paper, the dynamic behaviors and the motion modes of biological micro/nanoparticles such as DNA, yeast, platelet and bacteria due to the 3D manipulation effect have been investigated. Since the above nanoparticles generally have a cylindrical shape, the cylindrical contact models have been employed in an attempt to more precisely model the forces exerted on the nanoparticle during the manipulation process. Also, this investigation has performed a comprehensive modeling and simulation of all the possible motion modes in 3D manipulation by taking into account the eccentricity of the applied load on the biological nanoparticle. The obtained results indicate that unlike the macroscopic scale, the sliding of nanoparticle on substrate in nano-scale takes place sooner than the other motion modes and that the spinning about the vertical and transverse axes and the rolling of nanoparticle occur later than the other motion modes. The simulation results also indicate that the applied force necessary for the onset of nanoparticle movement and the resulting motion mode depend on the size and aspect ratio of the nanoparticle. Copyright © 2015 Elsevier Ltd. All rights reserved.

Natural physical and biological processes compromise the long-term performance of compacted soil caps

International Nuclear Information System (INIS)

Smith, E.D.

1995-01-01

Compacted soil barriers are components of essentially all caps placed on closed waste disposal sites. The intended functions of soil barriers in waste facility caps include restricting infiltration of water and release of gases and vapors, either independently or in combination with synthetic membrane barriers, and protecting other manmade or natural barrier components. Review of the performance of installed soil barriers and of natural processes affecting their performance indicates that compacted soil caps may function effectively for relatively short periods (years to decades), but natural physical and biological processes can be expected to cause them to fail in the long term (decades to centuries). This paper addresses natural physical and biological processes that compromise the performance of compacted soil caps and suggests measures that may reduce the adverse consequences of these natural failure mechanisms

Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

International Nuclear Information System (INIS)

Lewis, Daniel D.; Villarreal, Fernando D.; Wu, Fan; Tan, Cheemeng

2014-01-01

As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

Energy Technology Data Exchange (ETDEWEB)

Lewis, Daniel D. [Integrative Genetics and Genomics, University of California Davis, Davis, CA (United States); Department of Biomedical Engineering, University of California Davis, Davis, CA (United States); Villarreal, Fernando D.; Wu, Fan; Tan, Cheemeng, E-mail: cmtan@ucdavis.edu [Department of Biomedical Engineering, University of California Davis, Davis, CA (United States)

2014-12-09

As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

Multidimensional biochemical information processing of dynamical patterns.

Science.gov (United States)

Hasegawa, Yoshihiko

2018-02-01

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

Mixing and Processing of Complex Biological Fluids

National Research Council Canada - National Science Library

Liepmann, Dorian

2003-01-01

... of microfluidic control on the makeup and molecular structure of biological fluids. For this project, we focused on two critical fluids that are biologically significant and that are of critical importance to DoD...

A finite element simulation of biological conversion processes in landfills

International Nuclear Information System (INIS)

Robeck, M.; Ricken, T.; Widmann, R.

2011-01-01

Landfills are the most common way of waste disposal worldwide. Biological processes convert the organic material into an environmentally harmful landfill gas, which has an impact on the greenhouse effect. After the depositing of waste has been stopped, current conversion processes continue and emissions last for several decades and even up to 100 years and longer. A good prediction of these processes is of high importance for landfill operators as well as for authorities, but suitable models for a realistic description of landfill processes are rather poor. In order to take the strong coupled conversion processes into account, a constitutive three-dimensional model based on the multiphase Theory of Porous Media (TPM) has been developed at the University of Duisburg-Essen. The theoretical formulations are implemented in the finite element code FEAP. With the presented calculation concept we are able to simulate the coupled processes that occur in an actual landfill. The model's theoretical background and the results of the simulations as well as the meantime successfully performed simulation of a real landfill body will be shown in the following.

Controlled Carbon Source Addition to an Alternating Nitrification-Denitrification Wastewater Treatment Process Including Biological P Removal

DEFF Research Database (Denmark)

Isaacs, Steven Howard; Henze, Mogens

1995-01-01

The paper investigates the effect of adding an external carbon source on the rate of denitrification in an alternating activated sludge process including biological P removal. Two carbon sources were examined, acetate and hydrolysate derived from biologically hydrolyzed sludge. Preliminary batch ...

A concise review of dynamical processes in polymorphic ...

Indian Academy of Sciences (India)

TECS

This article describes our ongoing efforts to understand dynamical processes such as rota- tional diffusion and photoisomerization in polymorphic environments of a block copolymer. ... tional surfactants, these triblock copolymers do not possess a polar head group and nonpolar tail, but at- tain amphiphilic character as a ...

Emulating short-term synaptic dynamics with memristive devices

Science.gov (United States)

Berdan, Radu; Vasilaki, Eleni; Khiat, Ali; Indiveri, Giacomo; Serb, Alexandru; Prodromakis, Themistoklis

2016-01-01

Neuromorphic architectures offer great promise for achieving computation capacities beyond conventional Von Neumann machines. The essential elements for achieving this vision are highly scalable synaptic mimics that do not undermine biological fidelity. Here we demonstrate that single solid-state TiO2 memristors can exhibit non-associative plasticity phenomena observed in biological synapses, supported by their metastable memory state transition properties. We show that, contrary to conventional uses of solid-state memory, the existence of rate-limiting volatility is a key feature for capturing short-term synaptic dynamics. We also show how the temporal dynamics of our prototypes can be exploited to implement spatio-temporal computation, demonstrating the memristors full potential for building biophysically realistic neural processing systems.

Enabling dynamic network analysis through visualization in TVNViewer

Directory of Open Access Journals (Sweden)

Curtis Ross E

2012-08-01

Full Text Available Abstract Background Many biological processes are context-dependent or temporally specific. As a result, relationships between molecular constituents evolve across time and environments. While cutting-edge machine learning techniques can recover these networks, exploring and interpreting the rewiring behavior is challenging. Information visualization shines in this type of exploratory analysis, motivating the development ofTVNViewer (http://sailing.cs.cmu.edu/tvnviewer, a visualization tool for dynamic network analysis. Results In this paper, we demonstrate visualization techniques for dynamic network analysis by using TVNViewer to analyze yeast cell cycle and breast cancer progression datasets. Conclusions TVNViewer is a powerful new visualization tool for the analysis of biological networks that change across time or space.

Enabling dynamic network analysis through visualization in TVNViewer

Science.gov (United States)

2012-01-01

Background Many biological processes are context-dependent or temporally specific. As a result, relationships between molecular constituents evolve across time and environments. While cutting-edge machine learning techniques can recover these networks, exploring and interpreting the rewiring behavior is challenging. Information visualization shines in this type of exploratory analysis, motivating the development ofTVNViewer (http://sailing.cs.cmu.edu/tvnviewer), a visualization tool for dynamic network analysis. Results In this paper, we demonstrate visualization techniques for dynamic network analysis by using TVNViewer to analyze yeast cell cycle and breast cancer progression datasets. Conclusions TVNViewer is a powerful new visualization tool for the analysis of biological networks that change across time or space. PMID:22897913

Mind the gap: non-biological processes contributing to soil CO2 efflux.

Science.gov (United States)

Rey, Ana

2015-05-01

Widespread recognition of the importance of soil CO2 efflux as a major source of CO2 to the atmosphere has led to active research. A large soil respiration database and recent reviews have compiled data, methods, and current challenges. This study highlights some deficiencies for a proper understanding of soil CO2 efflux focusing on processes of soil CO2 production and transport that have not received enough attention in the current soil respiration literature. It has mostly been assumed that soil CO2 efflux is the result of biological processes (i.e. soil respiration), but recent studies demonstrate that pedochemical and geological processes, such as geothermal and volcanic CO2 degassing, are potentially important in some areas. Besides the microbial decomposition of litter, solar radiation is responsible for photodegradation or photochemical degradation of litter. Diffusion is considered to be the main mechanism of CO2 transport in the soil, but changes in atmospheric pressure and thermal convection may also be important mechanisms driving soil CO2 efflux greater than diffusion under certain conditions. Lateral fluxes of carbon as dissolved organic and inorganic carbon occur and may cause an underestimation of soil CO2 efflux. Traditionally soil CO2 efflux has been measured with accumulation chambers assuming that the main transport mechanism is diffusion. New techniques are available such as improved automated chambers, CO2 concentration profiles and isotopic techniques that may help to elucidate the sources of carbon from soils. We need to develop specific and standardized methods for different CO2 sources to quantify this flux on a global scale. Biogeochemical models should include biological and non-biological CO2 production processes before we can predict the response of soil CO2 efflux to climate change. Improving our understanding of the processes involved in soil CO2 efflux should be a research priority given the importance of this flux in the global

Dynamic Complexity Study of Nuclear Reactor and Process Heat Application Integration

International Nuclear Information System (INIS)

Taylor, J'Tia Patrice; Shropshire, David E.

2009-01-01

This paper describes the key obstacles and challenges facing the integration of nuclear reactors with process heat applications as they relate to dynamic issues. The paper also presents capabilities of current modeling and analysis tools available to investigate these issues. A pragmatic approach to an analysis is developed with the ultimate objective of improving the viability of nuclear energy as a heat source for process industries. The extension of nuclear energy to process heat industries would improve energy security and aid in reduction of carbon emissions by reducing demands for foreign derived fossil fuels. The paper begins with an overview of nuclear reactors and process application for potential use in an integrated system. Reactors are evaluated against specific characteristics that determine their compatibility with process applications such as heat outlet temperature. The reactor system categories include light water, heavy water, small to medium, near term high-temperature, and far term high temperature reactors. Low temperature process systems include desalination, district heating, and tar sands and shale oil recovery. High temperature processes that support hydrogen production include steam reforming, steam cracking, hydrogen production by electrolysis, and far-term applications such as the sulfur iodine chemical process and high-temperature electrolysis. A simple static matching between complementary systems is performed; however, to gain a true appreciation for system integration complexity, time dependent dynamic analysis is required. The paper identifies critical issues arising from dynamic complexity associated with integration of systems. Operational issues include scheduling conflicts and resource allocation for heat and electricity. Additionally, economic and safety considerations that could impact the successful integration of these systems are considered. Economic issues include the cost differential arising due to an integrated system

Atypical biological motion kinematics are represented by complementary lower-level and top-down processes during imitation learning.

Science.gov (United States)

Hayes, Spencer J; Dutoy, Chris A; Elliott, Digby; Gowen, Emma; Bennett, Simon J

2016-01-01

Learning a novel movement requires a new set of kinematics to be represented by the sensorimotor system. This is often accomplished through imitation learning where lower-level sensorimotor processes are suggested to represent the biological motion kinematics associated with an observed movement. Top-down factors have the potential to influence this process based on the social context, attention and salience, and the goal of the movement. In order to further examine the potential interaction between lower-level and top-down processes in imitation learning, the aim of this study was to systematically control the mediating effects during an imitation of biological motion protocol. In this protocol, we used non-human agent models that displayed different novel atypical biological motion kinematics, as well as a control model that displayed constant velocity. Importantly the three models had the same movement amplitude and movement time. Also, the motion kinematics were displayed in the presence, or absence, of end-state-targets. Kinematic analyses showed atypical biological motion kinematics were imitated, and that this performance was different from the constant velocity control condition. Although the imitation of atypical biological motion kinematics was not modulated by the end-state-targets, movement time was more accurate in the absence, compared to the presence, of an end-state-target. The fact that end-state targets modulated movement time accuracy, but not biological motion kinematics, indicates imitation learning involves top-down attentional, and lower-level sensorimotor systems, which operate as complementary processes mediated by the environmental context. Copyright © 2015 Elsevier B.V. All rights reserved.

Coupled Modeling of Rhizosphere and Reactive Transport Processes

Science.gov (United States)

Roque-Malo, S.; Kumar, P.

2017-12-01

The rhizosphere, as a bio-diverse plant root-soil interface, hosts many hydrologic and biochemical processes, including nutrient cycling, hydraulic redistribution, and soil carbon dynamics among others. The biogeochemical function of root networks, including the facilitation of nutrient cycling through absorption and rhizodeposition, interaction with micro-organisms and fungi, contribution to biomass, etc., plays an important role in myriad Critical Zone processes. Despite this knowledge, the role of the rhizosphere on watershed-scale ecohydrologic functions in the Critical Zone has not been fully characterized, and specifically, the extensive capabilities of reactive transport models (RTMs) have not been applied to these hydrobiogeochemical dynamics. This study uniquely links rhizospheric processes with reactive transport modeling to couple soil biogeochemistry, biological processes, hydrologic flow, hydraulic redistribution, and vegetation dynamics. Key factors in the novel modeling approach are: (i) bi-directional effects of root-soil interaction, such as simultaneous root exudation and nutrient absorption; (ii) multi-state biomass fractions in soil (i.e. living, dormant, and dead biological and root materials); (iii) expression of three-dimensional fluxes to represent both vertical and lateral interconnected flows and processes; and (iv) the potential to include the influence of non-stationary external forcing and climatic factors. We anticipate that the resulting model will demonstrate the extensive effects of plant root dynamics on ecohydrologic functions at the watershed scale and will ultimately contribute to a better characterization of efflux from both agricultural and natural systems.

Dynamic modeling and control of industrial crude terephthalic acid hydropurification process

Energy Technology Data Exchange (ETDEWEB)

Li, Zhi; Zhong, Weimin; Liu, Yang; Luo, Na; Qian, Feng [East China University of Science and Technology, Shanghai (China)

2015-04-15

Purified terephthalic acid (PTA) is critical to the development of the polyester industry. PTA production consists of p-xylene oxidation reaction and crude terephthalic acid (CTA) hydropurification. The hydropurification process is necessary to eliminate 4-carboxybenzaldehyde (4-CBA), which is a harmful byproduct of the oxidation reaction process. Based on the dynamic model of the hydropurification process, two control systems are studied using Aspen Dynamics. The first system is the ratio control system, in which the mass flows of CTA and deionized water are controlled. The second system is the multivariable predictive control-proportional-integral-derivative cascade control strategy, in which the concentrations of 4-CBA and carbon monoxide are chosen as control variables and the reaction temperature and hydrogen flow are selected as manipulated variables. A detailed dynamic behavior is investigated through simulation. Results show that the developed control strategies exhibit good control performances, thereby providing theoretical guidance for advanced control of industry-scale PTA production.

Network analysis reveals stage-specific changes in zebrafish embryo development using time course whole transcriptome profiling and prior biological knowledge.

Science.gov (United States)

Zhang, Yuji

2015-01-01

Molecular networks act as the backbone of molecular activities within cells, offering a unique opportunity to better understand the mechanism of diseases. While network data usually constitute only static network maps, integrating them with time course gene expression information can provide clues to the dynamic features of these networks and unravel the mechanistic driver genes characterizing cellular responses. Time course gene expression data allow us to broadly "watch" the dynamics of the system. However, one challenge in the analysis of such data is to establish and characterize the interplay among genes that are altered at different time points in the context of a biological process or functional category. Integrative analysis of these data sources will lead us a more complete understanding of how biological entities (e.g., genes and proteins) coordinately perform their biological functions in biological systems. In this paper, we introduced a novel network-based approach to extract functional knowledge from time-dependent biological processes at a system level using time course mRNA sequencing data in zebrafish embryo development. The proposed method was applied to investigate 1α, 25(OH)2D3-altered mechanisms in zebrafish embryo development. We applied the proposed method to a public zebrafish time course mRNA-Seq dataset, containing two different treatments along four time points. We constructed networks between gene ontology biological process categories, which were enriched in differential expressed genes between consecutive time points and different conditions. The temporal propagation of 1α, 25-Dihydroxyvitamin D3-altered transcriptional changes started from a few genes that were altered initially at earlier stage, to large groups of biological coherent genes at later stages. The most notable biological processes included neuronal and retinal development and generalized stress response. In addition, we also investigated the relationship among

Biological soil crusts exhibit a dynamic response to seasonal rain and release from grazing with implications for soil stability