Plimpton, Steven James; Heffernan, Julieanne; Sasaki, Darryl Yoshio; Frischknecht, Amalie Lucile; Stevens, Mark Jackson; Frink, Laura J. Douglas
2005-11-01
Understanding the properties and behavior of biomembranes is fundamental to many biological processes and technologies. Microdomains in biomembranes or ''lipid rafts'' are now known to be an integral part of cell signaling, vesicle formation, fusion processes, protein trafficking, and viral and toxin infection processes. Understanding how microdomains form, how they depend on membrane constituents, and how they act not only has biological implications, but also will impact Sandia's effort in development of membranes that structurally adapt to their environment in a controlled manner. To provide such understanding, we created physically-based models of biomembranes. Molecular dynamics (MD) simulations and classical density functional theory (DFT) calculations using these models were applied to phenomena such as microdomain formation, membrane fusion, pattern formation, and protein insertion. Because lipid dynamics and self-organization in membranes occur on length and time scales beyond atomistic MD, we used coarse-grained models of double tail lipid molecules that spontaneously self-assemble into bilayers. DFT provided equilibrium information on membrane structure. Experimental work was performed to further help elucidate the fundamental membrane organization principles.
Structure and physical properties of biomembranes and model membranes
NASA Astrophysics Data System (ADS)
Hianik, T.
2006-12-01
Biomembranes belong to the most important structures of the cell and the cell organels. They play not only structural role of the barrier separating the external and internal part of the membrane but contain also various functional molecules, like receptors, ionic channels, carriers and enzymes. The cell membrane also preserves non-equillibrium state in a cell which is crucial for maintaining its excitability and other signaling functions. The growing interest to the biomembranes is also due to their unique physical properties. From physical point of view the biomembranes, that are composed of lipid bilayer into which are incorporated integral proteins and on their surface are anchored peripheral proteins and polysaccharides, represent liquid scrystal of smectic type. The biomembranes are characterized by anisotropy of structural and physical properties. The complex structure of biomembranes makes the study of their physical properties rather difficult. Therefore several model systems that mimic the structure of biomembranes were developed. Among them the lipid monolayers at an air-water interphase, bilayer lipid membranes (BLM), supported bilayer lipid membranes (sBLM) and liposomes are most known. This work is focused on the introduction into the "physical word" of the biomembranes and their models. After introduction to the membrane structure and the history of its establishment, the physical properties of the biomembranes and their models areare stepwise presented. The most focus is on the properties of lipid monolayers, BLM, sBLM and liposomes that were most detailed studied. This contribution has tutorial character that may be usefull for undergraduate and graduate students in the area of biophysics, biochemistry, molecular biology and bioengineering, however it contains also original work of the author and his co-worker and PhD students, that may be usefull also for specialists working in the field of biomembranes and model membranes.
Ojwang', Loice M; Cook, Robert L
2013-08-01
The interaction of humic acids (HAs) with 1-palmitoyl-2-oleoyl-Sn-glycero-3-phosphocholine (POPC) large unilamellar vesicle (LUV) model biomembrane system was studied by fluorescence spectroscopy. HAs from aquatic and terrestrial (including coal) sources were studied. The effects of HA concentration and temperature over environmentally relevant ranges of 0 to 20 mg C/L and 10 to 30 °C, respectively, were investigated. The dosage studies revealed that the aquatic Suwannee River humic acid (SRHA) causes an increased biomembrane perturbation (percent leakage of the fluorescent dye, Sulforhodamine B) over the entire studied concentration range. The two terrestrial HAs, namely Leonardite humic acid (LAHA) and Florida peat humic acid (FPHA), at concentrations above 5 mg C/L, show a decrease or a plateau effect attributable to the competition within the HA mixture and/or the formation of "partial aggregates". The temperature studies revealed that biomembrane perturbation increases with decreasing temperature for all three HAs. Kinetic studies showed that the membrane perturbation process is complex with both fast and slow absorption (sorption into the bilayer) components and that the slow component could be fitted by first order kinetics. A mechanism based on "lattice errors" within the POPC LUVs is put forward to explain the fast and slow components. A rationale behind the concentration and temperature findings is provided, and the environmental implications are discussed. PMID:23805776
Interactions of PAMAM dendrimers with negatively charged model biomembranes.
Yanez Arteta, Marianna; Ainalem, Marie-Louise; Porcar, Lionel; Martel, Anne; Coker, Helena; Lundberg, Dan; Chang, Debby P; Soltwedel, Olaf; Barker, Robert; Nylander, Tommy
2014-11-13
We have investigated the interactions between cationic poly(amidoamine) (PAMAM) dendrimers of generation 4 (G4), a potential gene transfection vector, with net-anionic model biomembranes composed of different ratios of zwitterionic phosphocholine (PC) and anionic phospho-L-serine (PS) phospholipids. Two types of model membranes were used: solid-supported bilayers, prepared with lipids carrying palmitoyl-oleoyl (PO) and diphytanoyl (DPh) acyl chains, and free-standing bilayers, formed at the interface between two aqueous droplets in oil (droplet interface bilayers, DIBs) using the DPh-based lipids. G4 dendrimers were found to translocate through POPC:POPS bilayers deposited on silica surfaces. The charge density of the bilayer affects translocation, which is reduced when the ionic strength increases. This shows that the dendrimer-bilayer interactions are largely controlled by their electrostatic attraction. The structure of the solid-supported bilayers remains intact upon translocation of the dendrimer. However, the amount of lipids in the bilayer decreases and dendrimer/lipid aggregates are formed in bulk solution, which can be deposited on the interfacial layers upon dilution of the system with dendrimer-free solvent. Electrophysiology measurements on DIBs confirm that G4 dendrimers cross the lipid membranes containing PS, which then become more permeable to ions. The obtained results have implications for PAMAM dendrimers as delivery vehicles to cells. PMID:25310456
Pignatello, R.; Musumeci, T.; Basile, L.; Carbone, C.; Puglisi, G.
2011-01-01
Contact with many different biological membranes goes along the destiny of a drug after its systemic administration. From the circulating macrophage cells to the vessel endothelium, to more complex absorption barriers, the interaction of a biomolecule with these membranes largely affects its rate and time of biodistribution in the body and at the target sites. Therefore, investigating the phenomena occurring on the cell membranes, as well as their different interaction with drugs in the physiological or pathological conditions, is important to exploit the molecular basis of many diseases and to identify new potential therapeutic strategies. Of course, the complexity of the structure and functions of biological and cell membranes, has pushed researchers toward the proposition and validation of simpler two- and three-dimensional membrane models, whose utility and drawbacks will be discussed. This review also describes the analytical methods used to look at the interactions among bioactive compounds with biological membrane models, with a particular accent on the calorimetric techniques. These studies can be considered as a powerful tool for medicinal chemistry and pharmaceutical technology, in the steps of designing new drugs and optimizing the activity and safety profile of compounds already used in the therapy. PMID:21430952
Transfer kinetics from colloidal drug carriers and liposomes to biomembrane models: DSC studies
Sarpietro, Maria Grazia; Castelli, Francesco
2011-01-01
The release of bioactive molecules by different delivery systems has been studied. We have proposed a protocol that takes into account a system that is able to carry out the uptake of a bioactive molecule released during the time, resembling an in vivo-like system, and for this reason we have used biomembrane models represented by multi-lamellar and unilamellar vesicles. The bioactive molecule loaded delivery system has been put in contact with the biomembrane model and the release has been evaluated, to consider the effect of the bioactive molecule on the biomembrane model thermotropic behavior, and to compare the results with those obtained when a pure drug interacts with the biomembrane model. The differential scanning calorimetry technique has been employed. Depending on the delivery system used, our research permits to evaluate the effect of different parameters on the bioactive molecule release, such as pH, drug loading degree, delivery system swelling, crosslinking agent, degree of cross-linking, and delivery system side chains. PMID:21430957
Interaction of α-Hexylcinnamaldehyde with a Biomembrane Model: A Possible MDR Reversal Mechanism.
Sarpietro, Maria Grazia; Di Sotto, Antonella; Accolla, Maria Lorena; Castelli, Francesco
2015-05-22
The ability of the naturally derived compound α-hexylcinnamaldehyde (1) to interact with biomembranes and to modulate their permeability has been investigated as a strategy to reverse multidrug resistance (MDR) in cancer cells. Dimyristoylphosphatidylcholine (DMPC) multilamellar vesicles (MLVs) were used as biomembrane models, and differential scanning calorimetry was applied to measure the effect of 1 on the thermotropic behavior of DMPC MLVs. The effect of an aqueous medium or a lipid carrier on the uptake of 1 by the biomembrane was also characterized. Furthermore, taking into account that MDR is strictly regulated by redox signaling, the pro-oxidant and/or antioxidant effects of 1 were evaluated by the crocin-bleaching assay, in both hydrophilic and lipophilic environments. Compound 1 was uniformly distributed in the phospholipid bilayers and deeply interacted with DMPC MLVs, intercalating among the phospholipid acyl chains and thus decreasing their cooperativity. The lipophilic medium allowed the absorption of 1 into the phospholipid membrane. In the crocin-bleaching assay, the substance produced no pro-oxidant effects in both hydrophilic and lipophilic environments; conversely, a significant inhibition of AAPH-induced oxidation was exerted in hydrophilic medium. These results suggest a possible role of 1 as a chemopreventive and chemosensitizing agent for fighting cancer. PMID:25893313
Development of a Nonionic Azobenzene Amphiphile for Remote Photocontrol of a Model Biomembrane.
Benedini, Luciano A; Sequeira, M Alejandra; Fanani, Maria Laura; Maggio, Bruno; Dodero, Verónica I
2016-05-01
We report the synthesis and characterization of a simple nonionic azoamphiphile, C12OazoE3OH, which behaves as an optically controlled molecule alone and in a biomembrane environment. First, Langmuir monolayer and Brewster angle microscopy (BAM) experiments showed that pure C12OazoE3OH enriched in the (E) isomer was able to form solidlike mesophase even at low surface pressure associated with supramolecular organization of the azobenzene derivative at the interface. On the other hand, pure C12OazoE3OH enriched in the (Z) isomer formed a less solidlike monolayer due to the bent geometry around the azobenzene moiety. Second, C12OazoE3OH is well-mixed in a biological membrane model, Lipoid s75 (up to 20%mol), and photoisomerization among the lipids proceeded smoothly depending on light conditions. It is proposed that the cross-sectional area of the hydroxyl triethylenglycol head of C12OazoE3OH inhibits azobenzenes H-aggregation in the model membrane; thus, the tails conformation change due to photoisomerization is transferred efficiently to the lipid membrane. We showed that the lipid membrane effectively senses the azobenzene geometrical change photomodulating some properties, like compressibility modulus, transition temperature, and morphology. In addition, photomodulation proceeds with a color change from yellow to orange, providing the possibility to externally monitor the system. Finally, Gibbs monolayers showed that C12OazoE3OH is able to penetrate the highly packing biomembrane model; thus, C12OazoE3OH might be used as photoswitchable molecular probe in real systems. PMID:27070294
Chen, Yu; Yang, Yumin; Liao, Qingping; Yang, Wei; Ma, Wanfeng; Zhao, Jian; Zheng, Xionggao; Yang, Yang; Chen, Rui
2016-10-01
Cervical erosion is one of the common diseases of women. The loop electrosurgical excisional procedure (LEEP) has been used widely in the treatment of the cervical diseases. However, there are no effective wound dressings for the postoperative care to protect the wound area from further infection, leading to increased secretion and longer healing time. Iodine is a widely used inorganic antibacterial agent with many advantages. However, the carrier for stable iodine complex antibacterial agents is lack. In the present study, a novel iodine carrier, Carboxymethyl chitosan-g-(poly(sodium acrylate)-co-polyvinylpyrrolidone) (CMCTS-g-(PAANa-co-PVP), was prepared by graft copolymerization of sodium acrylate (AANa) and N-vinylpyrrolidone (NVP) to a carboxymethyl chitosan (CMCTS) skeleton. The obtained structure could combine prominent property of poly(sodium acrylate) (PAANa) anionic polyelectrolyte segment and good complex property of polyvinylpyrrolidone (PVP) segment to iodine. The bioactivity of CMCTS could also be kept. The properties of the complex, CMCTS-g-(PAANa-co-PVP)-I2, were studied. The in vitro experiment shows that it has broad-spectrum bactericidal effects to virus, fungus, gram-positive bacteria and gram-negative bacteria. A CMCTS-g-(PAANa-co-PVP)-I2 complex contained cervical antibacterial biomembrane (CABM) was prepared. The iodine release from the CABM is pH-dependent. The clinic trial results indicate that CABM has better treatment effectiveness than the conventional treatment in the postoperative care of the LEEP operation. PMID:27287120
Travelling lipid domains in a dynamic model for protein-induced pattern formation in biomembranes
NASA Astrophysics Data System (ADS)
John, Karin; Bär, Markus
2005-06-01
Cell membranes are composed of a mixture of lipids. Many biological processes require the formation of spatial domains in the lipid distribution of the plasma membrane. We have developed a mathematical model that describes the dynamic spatial distribution of acidic lipids in response to the presence of GMC proteins and regulating enzymes. The model encompasses diffusion of lipids and GMC proteins, electrostatic attraction between acidic lipids and GMC proteins as well as the kinetics of membrane attachment/detachment of GMC proteins. If the lipid-protein interaction is strong enough, phase separation occurs in the membrane as a result of free energy minimization and protein/lipid domains are formed. The picture is changed if a constant activity of enzymes is included into the model. We chose the myristoyl-electrostatic switch as a regulatory module. It consists of a protein kinase C that phosphorylates and removes the GMC proteins from the membrane and a phosphatase that dephosphorylates the proteins and enables them to rebind to the membrane. For sufficiently high enzymatic activity, the phase separation is replaced by travelling domains of acidic lipids and proteins. The latter active process is typical for nonequilibrium systems. It allows for a faster restructuring and polarization of the membrane since it acts on a larger length scale than the passive phase separation. The travelling domains can be pinned by spatial gradients in the activity; thus the membrane is able to detect spatial clues and can adapt its polarity dynamically to changes in the environment.
Neves, Ana Rute; Nunes, Cláudia; Reis, Salette
2015-09-01
Resveratrol has been widely studied because of its pleiotropic effects in cancer therapy, neuroprotection, and cardioprotection. It is believed that the interaction of resveratrol with biological membranes may play a key role in its therapeutic activity. The capacity of resveratrol to partition into lipid bilayers, its possible location within the membrane, and the influence of this compound on the membrane fluidity were investigated using membrane mimetic systems composed of egg l-α-phosphatidylcholine (EPC), cholesterol (CHOL), and sphingomyelin (SM). The results showed that resveratrol has greater affinity for the EPC bilayers than for EPC:CHOL [4:1] and EPC:CHOL:SM [1:1:1] membrane models. The increased difficulty in penetrating tight packed membranes is also demonstrated by fluorescence quenching of probes and by fluorescence anisotropy measurements. Resveratrol may be involved in the regulation of cell membrane fluidity, thereby contributing for cell homeostasis. PMID:26237152
Ahlers, M; Grainger, D W; Herron, J N; Lim, K; Ringsdorf, H; Salesse, C
1992-01-01
Three model biomembrane systems, monolayers, micelles, and vesicles, have been used to study the influence of chemical and physical variables of hapten presentation at membrane interfaces on antibody binding. Hapten recognition and binding were monitored for the anti-fluorescein monoclonal antibody 4-4-20 generated against the hapten, fluorescein, in these membrane models as a function of fluorescein-conjugated lipid architecture. Specific recognition and binding in this system are conveniently monitored by quenching of fluorescein emission upon penetration of fluorescein into the antibody's active site. Lipid structure was shown to play a large role in affecting antibody quenching. Interestingly, the observed degrees of quenching were nearly independent of the lipid membrane model studied, but directly correlated with the chemical structure of the lipids. In all cases, the antibody recognized and quenched most efficiently a lipid based on dioctadecylamine where fluorescein is attached to the headgroup via a long, flexible hydrophilic spacer. Dipalmitoyl phosphatidylethanolamine containing a fluorescein headgroup demonstrated only partial binding/quenching. Egg phosphatidylethanolamine with a fluorescein headgroup showed no susceptibility to antibody recognition, binding, or quenching. Formation of two-dimensional protein domains upon antibody binding to the fluorescein-lipids in monolayers is also presented. Chemical and physical requirements for these antibody-hapten complexes at membrane surfaces have been discussed in terms of molecular dynamics simulations based on recent crystallographic models for this antibody-hapten complex (Herron et al., 1989. Proteins Struct. Funct. Genet. 5:271-280). Images FIGURE 7 FIGURE 8 PMID:1420916
Oliver, Miquel; Bauzá, Antonio; Frontera, Antonio; Miró, Manuel
2016-07-01
Experimental sensing schemes and thermodynamic in-silico studies are combined holistically in this manuscript so as to give new insights into the bioavailability of environmental contaminants via permeation across lipid nanoparticles (liposomes) as a mimicry of biological membranes. Using Prodan and Laurdan as fluorescent membrane probes, phosphatidylcholine-based unilamellar liposomes are harnessed to investigate membranotropic effects of alkyl esters of p-hydroxybenzoic acid and triclosan in vitro on the basis of steady-state fluorescence anisotropy, light scattering, and generalized polarization measurements. The feasibility of the analytical responses to ascertain differences in temperature-dependent contaminant bioavailability is investigated in detail. High level density functional theory (DFT) calculations (RI-BP86-D3/def2-SVP) have been resorted to investigate noncovalent 1:1 complexes of the fluorescent probes and emerging contaminants with dipalmitoylphosphatidylcholine, as a minimalist model of a lipid nanoparticle, to evaluate both the interaction energies and the geometries of the complexes. This information can be related to the degree of penetration of the guest across the lipid bilayer. Our experimental results supported by in-silico DFT calculations and ecotoxicological data let us to conclude that simple analytical measurements of liposomal changes in lipid packaging, permeability, and fluidity are appropriate to foresee the potential bioavailability and toxicity of emerging contaminants. PMID:27243463
Andreani, Tatiana; Miziara, Leonardo; Lorenzón, Esteban N; de Souza, Ana Luiza R; Kiill, Charlene P; Fangueiro, Joana F; Garcia, Maria L; Gremião, Palmira D; Silva, Amélia M; Souto, Eliana B
2015-06-01
The present paper focuses on the development and characterization of silica nanoparticles (SiNP) coated with hydrophilic polymers as mucoadhesive carriers for oral administration of insulin. SiNP were prepared by sol-gel technology under mild conditions and coated with different hydrophilic polymers, namely, chitosan, sodium alginate or poly(ethylene glycol) (PEG) with low and high molecular weight (PEG 6000 and PEG 20000) to increase the residence time at intestinal mucosa. The mean size and size distribution, association efficiency, insulin structure and insulin thermal denaturation have been determined. The mean nanoparticle diameter ranged from 289 nm to 625 nm with a PI between 0.251 and 0.580. The insulin association efficiency in SiNP was recorded above 70%. After coating, the association efficiency of insulin increased up to 90%, showing the high affinity of the protein to the hydrophilic polymer chains. Circular dichroism (CD) indicated that no conformation changes of insulin structure occurred after loading the peptide into SiNP. Nano-differential scanning calorimetry (nDSC) showed that SiNP shifted the insulin endothermic peak to higher temperatures. The influence of coating on the interaction of nanoparticles with dipalmitoylphosphatidylcholine (DPPC) biomembrane models was also evaluated by nDSC. The increase of ΔH values suggested a strong association of non-coated SiNP and those PEGylated nanoparticles coated with DPPC polar heads by forming hydrogen bonds and/or by electrostatic interaction. The mucoadhesive properties of nanoparticles were examined by studying the interaction with mucin in aqueous solution. SiNP coated with alginate or chitosan showed high contact with mucin. On the other hand, non-coated SiNP and PEGylated SiNP showed lower interaction with mucin, indicating that these nanoparticles can interdiffuse across mucus network. The results of the present work provide valuable data in assessing the in vitro performance of insulin
Single-Molecule Analysis of Biomembranes
NASA Astrophysics Data System (ADS)
Schmidt, Thomas; Schütz, Gerhard J.
Biomembranes are more than just a cell's envelope - as the interface to the surrounding of a cell they carry key signalling functions. Consequentially, membranes are highly complex organelles: they host about thousand different types of lipids and about half of the proteome, whose interaction has to be orchestrated appropriately for the various signalling purposes. In particular, knowledge on the nanoscopic organization of the plasma membrane appears critical for understanding the regulation of interactions between membrane proteins. The high localization precision of ˜20 nm combined with a high time resolution of ˜1 ms made single molecule tracking an excellent technology to obtain insights into membrane nanostructures, even in a live cell context. In this chapter, we will highlight concepts to achieve superresolution by single molecule imaging, summarize tools for data analysis, and review applications on artificial and live cell membranes.
Casadó, Ana; Giuffrida, M Chiara; Sagristá, M Lluïsa; Castelli, Francesco; Pujol, Montserrat; Alsina, M Asunción; Mora, Margarita
2016-02-01
CPT-11 and SN-38 are camptothecins with strong antitumor activity. Nevertheless, their severe side effects and the chemical instability of their lactone ring have questioned the usual forms for its administration and have focused the current research on the development of new suitable pharmaceutical formulations. This work presents a biophysical study of the interfacial interactions of CPT-11 and SN-38 with membrane mimetic models by using monolayer techniques and Differential Scanning Calorimetry. The aim is to get new insights for the understanding of the bilayer mechanics after drug incorporation and to optimize the design of drug delivery systems based on the formation of stable bilayer structures. Moreover, from our knowledge, the molecular interactions between camptothecins and phospholipids have not been investigated in detail, despite their importance in the context of drug action. The results show that neither CPT-11 nor SN-38 disturbs the structure of the complex liposome bilayers, despite their different solubility, that CPT-11, positively charged in its piperidine group, interacts electrostatically with DOPS, making stable the incorporation of a high percentage of CPT-11 into liposomes and that SN-38 establishes weak repulsive interactions with lipid molecules that modify the compressibility of the bilayer without affecting significantly neither the lipid collapse pressure nor the miscibility pattern of drug-lipid mixed monolayers. The suitability of a binary and a ternary lipid mixture for encapsulating SN-38 and CPT-11, respectively, has been demonstrated. PMID:26656185
Phase Studies of Model Biomembranes: Complex Behavior of DSPC/DOPC/Cholesterol
Zhao, Jiang; Wu, Jing; Heberle, Frederick A.; Mills, Thalia T.; Klawitter, Paul; Huang, Grace; Costanza, Greg; Feigenson, Gerald W.
2009-01-01
We have undertaken a series of experiments to examine the behavior of individual components of cell membranes. Here we report an initial stage of these experiments, in which the properties of a chemically simple lipid mixture are carefully mapped onto a phase diagram. Four different experimental methods were used to establish the phase behavior of the 3-component mixture DSPC/DOPC/chol: (1) confocal fluorescence microscopy observation of giant unilamellar vesicles, GUVs; (2) FRET from perylene to C20:0-DiI; (3) fluorescence of dilute dyes C18:2-DiO and C20:0-DiI; and (4) wide angle x-ray diffraction. This particular 3-component mixture was chosen, in part, for a high level of immiscibility of the components in order to facilitate solving the phase behavior at all compositions. At 23 °C, a large fraction of the possible compositions for this mixture give rise to a solid phase. A region of 3-phase coexistence of {Lα + Lβ + Lo} was detected and defined based on a combination of fluorescence microscopy of GUVs, FRET, and dilute C20:0-DiI fluorescence. At very low cholesterol concentrations, the solid phase is the tilted-chain phase Lβ′. Most of the phase boundaries have been determined to within a few percent of the composition. Measurements of the perturbations of the boundaries of this accurate phase diagram could serve as a means to understand the behaviors of a range of added lipids and proteins. PMID:17825247
Statistical Thermodynamics of Biomembranes
Devireddy, Ram V.
2010-01-01
An overview of the major issues involved in the statistical thermodynamic treatment of phospholipid membranes at the atomistic level is summarized: thermodynamic ensembles, initial configuration (or the physical system being modeled), force field representation as well as the representation of long-range interactions. This is followed by a description of the various ways that the simulated ensembles can be analyzed: area of the lipid, mass density profiles, radial distribution functions (RDFs), water orientation profile, Deuteurium order parameter, free energy profiles and void (pore) formation; with particular focus on the results obtained from our recent molecular dynamic (MD) simulations of phospholipids interacting with dimethylsulfoxide (Me2SO), a commonly used cryoprotective agent (CPA). PMID:19460363
Kinetics of hole nucleation in biomembrane rupture
NASA Astrophysics Data System (ADS)
Evans, Evan; Smith, Benjamin A.
2011-09-01
The core component of a biological membrane is a fluid-lipid bilayer held together by interfacial-hydrophobic and van der Waals interactions, which are balanced for the most part by acyl chain entropy confinement. If biomembranes are subjected to persistent tensions, an unstable (nanoscale) hole will emerge at some time to cause rupture. Because of the large energy required to create a hole, thermal activation appears to be requisite for initiating a hole and the activation energy is expected to depend significantly on mechanical tension. Although models exist for the kinetic process of hole nucleation in tense membranes, studies of membrane survival have failed to cover the ranges of tension and lifetime needed to critically examine nucleation theory. Hence, rupturing giant (~20 μm) membrane vesicles ultra-slowly to ultra-quickly with slow to fast ramps of tension, we demonstrate a method to directly quantify kinetic rates at which unstable holes form in fluid membranes, at the same time providing a range of kinetic rates from <0.01 to >100 s-1. Measuring lifetimes of many hundreds of vesicles, each tensed by precision control of micropipette suction, we have determined the rates of failure for vesicles made from several synthetic phospholipids plus 1:1 mixtures of phospho- and sphingo-lipids with cholesterol, all of which represent prominent constituents of eukaryotic cell membranes. Plotted on a logarithmic scale, the failure rates for vesicles are found to rise dramatically with an increase in tension. Converting the experimental profiles of kinetic rates into changes of activation energy versus tension, we show that the results closely match expressions for thermal activation derived from a combination of meso-scale theory and molecular-scale simulations of hole formation. Moreover, we demonstrate a generic approach to transform analytical fits of activation energies obtained from rupture experiments into energy landscapes characterizing the process of hole
Lipid Biomembrane in Ionic Liquids
NASA Astrophysics Data System (ADS)
Yoo, Brian; Jing, Benxin; Shah, Jindal; Maginn, Ed; Zhu, Y. Elaine; Department of Chemical and Biomolecular Engineering Team
2014-03-01
Ionic liquids (ILs) have been recently explored as new ``green'' chemicals in several chemical and biomedical processes. In our pursuit of understanding their toxicities towards aquatic and terrestrial organisms, we have examined the IL interaction with lipid bilayers as model cell membranes. Experimentally by fluorescence microscopy, we have directly observed the disruption of lipid bilayer by added ILs. Depending on the concentration, alkyl chain length, and anion hydrophobicity of ILs, the interaction of ILs with lipid bilayers leads to the formation of micelles, fibrils, and multi-lamellar vesicles for IL-lipid complexes. By MD computer simulations, we have confirmed the insertion of ILs into lipid bilayers to modify the spatial organization of lipids in the membrane. The combined experimental and simulation results correlate well with the bioassay results of IL-induced suppression in bacteria growth, thereby suggesting a possible mechanism behind the IL toxicity. National Science Foundation, Center for Research Computing at Notre Dame.
Biomembranes research using thermal and cold neutrons.
Heberle, F A; Myles, D A A; Katsaras, J
2015-11-01
In 1932 James Chadwick discovered the neutron using a polonium source and a beryllium target (Chadwick, 1932). In a letter to Niels Bohr dated February 24, 1932, Chadwick wrote: "whatever the radiation from Be may be, it has most remarkable properties." Where it concerns hydrogen-rich biological materials, the "most remarkable" property is the neutron's differential sensitivity for hydrogen and its isotope deuterium. Such differential sensitivity is unique to neutron scattering, which unlike X-ray scattering, arises from nuclear forces. Consequently, the coherent neutron scattering length can experience a dramatic change in magnitude and phase as a result of resonance scattering, imparting sensitivity to both light and heavy atoms, and in favorable cases to their isotopic variants. This article describes recent biomembranes research using a variety of neutron scattering techniques. PMID:26241882
Biomembranes research using thermal and cold neutrons
Heberle, Frederick A.; Myles, Dean A. A.; Katsaras, John
2015-08-01
In 1932 James Chadwick discovered the neutron using a polonium source and a beryllium target (Chadwick, 1932). In a letter to Niels Bohr dated February 24, 1932, Chadwick wrote: “whatever the radiation from Be may be, it has most remarkable properties.” Where it concerns hydrogen-rich biological materials, the “most remarkable” property is the neutron’s differential sensitivity for hydrogen and its isotope deuterium. Such differential sensitivity is unique to neutron scattering, which unlike X-ray scattering, arises from nuclear forces. Consequently, the coherent neutron scattering length can experience a dramatic change in magnitude and phase as a result of resonance scattering, impartingmore » sensitivity to both light and heavy atoms, and in favorable cases to their isotopic variants. Furthermore, this article describes recent biomembranes research using a variety of neutron scattering techniques.« less
Biomembranes research using thermal and cold neutrons
Heberle, Frederick A.; Myles, Dean A. A.; Katsaras, John
2015-08-01
In 1932 James Chadwick discovered the neutron using a polonium source and a beryllium target (Chadwick, 1932). In a letter to Niels Bohr dated February 24, 1932, Chadwick wrote: “whatever the radiation from Be may be, it has most remarkable properties.” Where it concerns hydrogen-rich biological materials, the “most remarkable” property is the neutron’s differential sensitivity for hydrogen and its isotope deuterium. Such differential sensitivity is unique to neutron scattering, which unlike X-ray scattering, arises from nuclear forces. Consequently, the coherent neutron scattering length can experience a dramatic change in magnitude and phase as a result of resonance scattering, imparting sensitivity to both light and heavy atoms, and in favorable cases to their isotopic variants. Furthermore, this article describes recent biomembranes research using a variety of neutron scattering techniques.
The decreasing of corn root biomembrane penetration for acetochlor with vermicompost amendment
NASA Astrophysics Data System (ADS)
Sytnyk, Svitlana; Wiche, Oliver
2016-04-01
One of the topical environmental security issues is management and control of anthropogenic (artificially synthesized) chemical agents usage and utilization. Protection systems development against toxic effects of herbicides should be based on studies of biological indication mechanisms for identification of stressors effect in organisms. Lipid degradation is non-specific reaction to exogenous chemical agents effects. Therefore it is important to study responses of lipid components depending on the stressor type. We studied physiological and biochemical characteristics of lipid metabolism under action of herbicides of chloracetamide group. Corn at different stages of ontogenesis was used as testing object during model laboratory and microfield experiments. Cattle manure treated with earth worms Essenia Foetida was used as compost fertilizer to add to chain: chernozem (black soil) -corn system. It was found several acetochlor actions as following: -decreasing of sterols, phospholipids, phosphatidylcholines and phosphatidylethanolamines content; -increasing pool of available fatty acids and phosphatidic acids associated with intensification of hydrolysis processes; -lypase activity stimulation under effect of stressor in low concentrations; -lypase activity inhibition under effect of high stressor level; -decreasing of polyenoic free fatty acids indicating biomembrane degradation; -accumulation of phospholipids degradation products (phosphatidic acids); -decreasing of high-molecular compounds (phosphatidylcholin and phosphatidylinositol) concentrations; -change in the index of unsaturated and saturated free fatty acids ratio in biomembranes structure; It was established that incorporation of vermicompost in dose 0.4 kg/m2 in black soil lead to corn roots biomembrane restoration. It was fixed the decreasing roots biomembrane penetration for acetochlor in trial with vermicompost. Second compost substances antidote effect is the soil microorganism's activation
Goto, Thiago E; Lopes, Carla C; Nader, Helena B; Silva, Anielle C A; Dantas, Noelio O; Siqueira, José R; Caseli, Luciano
2016-07-01
Cadmium selenide (CdSe) magic-sized quantum dots (MSQDs) are semiconductor nanocrystals with stable luminescence that are feasible for biomedical applications, especially for in vivo and in vitro imaging of tumor cells. In this work, we investigated the specific interaction of CdSe MSQDs with tumorigenic and non-tumorigenic cells using Langmuir monolayers and Langmuir-Blodgett (LB) films of lipids as membrane models for diagnosis of cancerous cells. Surface pressure-area isotherms and polarization modulation reflection-absorption spectroscopy (PM-IRRAS) showed an intrinsic interaction between the quantum dots, inserted in the aqueous subphase, and Langmuir monolayers constituted either of selected lipids or of tumorigenic and non-tumorigenic cell extracts. The films were transferred to solid supports to obtain microscopic images, providing information on their morphology. Similarity between films with different compositions representing cell membranes, with or without the quantum dots, was evaluated by atomic force microscopy (AFM) and confocal microscopy. This study demonstrates that the affinity of quantum dots for models representing cancer cells permits the use of these systems as devices for cancer diagnosis. PMID:27107554
Brown, T. W.
2011-04-15
The same complex matrix model calculates both tachyon scattering for the c=1 noncritical string at the self-dual radius and certain correlation functions of operators which preserve half the supersymmetry in N=4 super-Yang-Mills theory. It is dual to another complex matrix model where the couplings of the first model are encoded in the Kontsevich-like variables of the second. The duality between the theories is mirrored by the duality of their Feynman diagrams. Analogously to the Hermitian Kontsevich-Penner model, the correlation functions of the second model can be written as sums over discrete points in subspaces of the moduli space of punctured Riemann surfaces.
Technology Transfer Automated Retrieval System (TEKTRAN)
Adsorption-desorption reactions are important processes that affect the transport of contaminants in the environment. Surface complexation models are chemical models that can account for the effects of variable chemical conditions, such as pH, on adsorption reactions. These models define specific ...
Performance of skeleton-reinforced biomembranes in locomotion
NASA Astrophysics Data System (ADS)
Zhu, Qiang; Shoele, Kourosh
2008-11-01
Skeleton-reinforced biomembranes are ubiquitous in nature and play critical roles in many biological functions. Representative examples include insect wings, cell membranes, and mollusk nacres. In this study we focus on the ray fins of fish and investigate the effects of anisotropic flexibility on their performance. Employing a fluid-structure interaction algorithm by coupling a boundary-element model with a nonlinear structural model, we examined the dynamics of a membrane that is geometrically and structurally similar to a caudal fin. Several locomotion modes that closely resemble caudal fin kinematics reported in the literature are applied. Our results show that the flexibility of the fin significantly increases its capacity of thrust generation, manifested as increased efficiency, reduced transverse force, and reduced sensitivity to kinematic parameters. This design also makes the fin more controllable and deployable. Despite simplifications made in this model in terms of fin geometry, internal structure, and kinematics, detailed features of the simulated flow field are consistent with observations and speculations based upon Particle Image Velocimetry (PIV) measurements of flow around live fish.
NASA Technical Reports Server (NTRS)
Figueroa-Feliciano, Enectali
2004-01-01
We have developed a software suite that models complex calorimeters in the time and frequency domain. These models can reproduce all measurements that we currently do in a lab setting, like IV curves, impedance measurements, noise measurements, and pulse generation. Since all these measurements are modeled from one set of parameters, we can fully describe a detector and characterize its behavior. This leads to a model than can be used effectively for engineering and design of detectors for particular applications.
Liu, Ying; Zhang, Zhen; Zhang, Quanxuan; Baker, Gregory L.; Worden, R. Mark
2013-01-01
Engineered nanomaterials (ENM) have desirable properties that make them well suited for many commercial applications. However, a limited understanding of how ENM’s properties influence their molecular interactions with biomembranes hampers efforts to design ENM that are both safe and effective. This paper describes the use of a tethered bilayer lipid membrane (tBLM) to characterize biomembrane disruption by functionalized silica-core nanoparticles. Electrochemical impedance spectroscopy was used to measure the time trajectory of tBLM resistance following nanoparticle exposure. Statistical analysis of parameters from an exponential resistance decay model was then used to quantify and analyze differences between the impedance profiles of nanoparticles that were unfunctionalized, amine-functionalized, or carboxyl-functionalized. All of the nanoparticles triggered a decrease in membrane resistance, indicating nanoparticle-induced disruption of the tBLM. Hierarchical clustering allowed the potency of nanoparticles for reducing tBLM resistance to be ranked in the order amine > carboxyl ~ bare silica. Dynamic light scattering analysis revealed that tBLM exposure triggered minor coalescence for bare and amine-functionalized silica nanoparticles but not for carboxyl-functionalized silica nanoparticles. These results indicate that the tBLM method can reproducibly characterize ENM-induced biomembrane disruption and can distinguish the BLM-disruption patterns of nanoparticles that are identical except for their surface functional groups. The method provides insight into mechanisms of molecular interaction involving biomembranes and is suitable for miniaturization and automation for high-throughput applications to help assess the health risk of nanomaterial exposure or identify ENM having a desired mode of interaction with biomembranes. PMID:24060565
Eggeling, Christian; Honigmann, Alf
2016-10-01
Biological membranes are complex composites of lipids, proteins and sugars, which catalyze a myriad of vital cellular reactions in a spatiotemporal tightly controlled manner. Our understanding of the organization principles of biomembranes is limited mainly by the challenge to measure distributions and interactions of lipids and proteins within the complex environment of living cells. With the recent advent of super-resolution optical microscopy (or nanoscopy) one now has approached the molecular scale regime with non-invasive live cell fluorescence observation techniques. Since in silico molecular dynamics (MD) simulation techniques are also improving to study larger and more complex systems we can now start to integrate live-cell and in silico experiments to develop a deeper understanding of biomembranes. In this review we summarize recent progress to measure lipid-protein interactions in living cells and give examples how MD simulations can complement and upgrade the experimental data. This article is part of a Special Issue entitled: Biosimulations edited by Ilpo Vattulainen and Tomasz Róg. PMID:27039279
Debating complexity in modeling
Hunt, Randall J.; Zheng, Chunmiao
1999-01-01
As scientists trying to understand the natural world, how should our effort be apportioned? We know that the natural world is characterized by complex and interrelated processes. Yet do we need to explicitly incorporate these intricacies to perform the tasks we are charged with? In this era of expanding computer power and development of sophisticated preprocessors and postprocessors, are bigger machines making better models? Put another way, do we understand the natural world better now with all these advancements in our simulation ability? Today the public's patience for long-term projects producing indeterminate results is wearing thin. This increases pressure on the investigator to use the appropriate technology efficiently. On the other hand, bringing scientific results into the legal arena opens up a new dimension to the issue: to the layperson, a tool that includes more of the complexity known to exist in the real world is expected to provide the more scientifically valid answer.
Biomembranes in atomistic and coarse-grained simulations
NASA Astrophysics Data System (ADS)
Pluhackova, Kristyna; Böckmann, Rainer A.
2015-08-01
The architecture of biological membranes is tightly coupled to the localization, organization, and function of membrane proteins. The organelle-specific distribution of lipids allows for the formation of functional microdomains (also called rafts) that facilitate the segregation and aggregation of membrane proteins and thus shape their function. Molecular dynamics simulations enable to directly access the formation, structure, and dynamics of membrane microdomains at the molecular scale and the specific interactions among lipids and proteins on timescales from picoseconds to microseconds. This review focuses on the latest developments of biomembrane force fields for both atomistic and coarse-grained molecular dynamics (MD) simulations, and the different levels of coarsening of biomolecular structures. It also briefly introduces scale-bridging methods applicable to biomembrane studies, and highlights selected recent applications.
Elasticity of biomembranes studied by dynamic light scattering
NASA Astrophysics Data System (ADS)
Fujime, Satoru; Miyamoto, Shigeaki
1991-05-01
Combination of osmotic swelling and dynamic light scattering makes it possible to measure the elastic modulus of biomembranes. By this technique we have observed a drastic increase in membrane flexibility on activation of Na/glucose cotransporters in membrane vesicles prepared from brush-borders of rat small intestine and on activation by micromolar [Ca2] of exocytosis in secretory granules isolated from rat pancreatic acinar cells and bovine adrenal chromaffin cells. 1 .
Evaluation of the mechanism of skin enhancing surfactants on the biomembrane of shed snake skin.
Wonglertnirant, Nanthida; Ngawhirunpat, Tanasait; Kumpugdee-Vollrath, Mont
2012-01-01
The aim of the present work was to investigate the effects of different surfactants at various concentrations as a skin penetration enhancer through the biomembrane of the shed skin of Naja kaouthia. Additionally, the enhancer mechanism(s) of each class of surfactants were evaluated using physical characterization techniques, such as scanning electron microscopy (SEM), attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, and small and wide angle X-ray scattering (SWAXS). Our results showed that skin permeability increased with increasing concentrations of surfactants and the degree of increase was higher for the model hydrophilic permeant, deuterium dioxide (D(2)O), than the lipophilic permeant, ketoprofen (KP). Ionic surfactants, sodium lauryl sulfate (SLS) and cetyl trimethyl ammonium bromide (CTAB), demonstrated higher enhancement ability than the polyoxyethylene (20) sorbitan mono-oleate (Tween 80) non-ionic surfactant, which was consistent with the results from physical characterization studies. Increasing amounts of permeated drug resulted in an increase in membrane interactions. From our observations, it can be assumed that SLS and CTAB can be localized inside the biomembrane and thereby enhance drug permeation mainly through interactions with intercellular lipids in the stratum corneum (SC) and the creation of a perturbed microenvironment among lipid alkyl chains and polar head groups. PMID:22466556
Response of biomembrane domains to external stimuli
NASA Astrophysics Data System (ADS)
Urbancic, Iztok
To enrich our knowledge about membrane domains, new measurement techniques with extended spatial and temporal windows are being vigorously developed by combining various approaches. Following such efforts of the scientific community, we set up fluorescence microspectroscopy (FMS), bridging two well established methods: fluorescence microscopy, which enables imaging of the samples with spatial resolution down to 200 nm, and fluorescence spectroscopy that provides molecular information of the environment at nanometer and nanosecond scale. The combined method therefore allows us to localize this type of information with the precision suitable for studying various cellular structures. Faced with weak available fluorescence signals, we have put considerable efforts into optimization of measurement processes and analysis of the data. By introducing a novel acquisition scheme and by fitting the data with a mathematical model, we preserved the spectral resolution, characteristic for spectroscopic measurements of bulk samples, also at microscopic level. We have at the same time overcome the effects of photobleaching, which had previously considerably distorted the measured spectral lineshape of photosensitive dyes and consequently hindered the reliability of FMS. Our new approach has therefore greatly extended the range of applicable environmentally sensitive probes, which can now be designed to better accommodate the needs of each particular experiment. Moreover, photobleaching of fluorescence signal can now even be exploited to obtain new valuable information about molecular environment of the probes, as bleaching rates of certain probes also depend on physical and chemical properties of the local surroundings. In this manner we increased the number of available spatially localized spectral parameters, which becomes invaluable when investigating complex biological systems that can only be adequately characterized by several independent variables. Applying the developed
NASA Astrophysics Data System (ADS)
Yi, Zheng
Bio-membranes of the natural living cells are made of bilayers of phospholipids molecules embedded with other constituents, such as cholesterol and membrane proteins, which help to accomplish a broad range of functions. Vesicles made of lipid bilayers can serve as good model systems for bio-membranes. Therefore these systems have been extensively characterized and much is known about their shape, size, porosity and functionality. In this dissertation we report the studies of the effects of the phosoholipid conformation, such as hydrocarbon number and presence of double bond in hydrophobic tails on dynamics of phospholipids bilayers studied by neutron spin echo (NSE) technique. We have investigated how lidocaine, the most medically used local anesthetics (LA), influence the structural and dynamical properties of model bio-membranes by small angle neutron scattering (SANS), NSE and differential scanning calorimetry (DSC). To investigate the influence of phospholipid conformation on bio-membranes, the bending elasticities kappac of seven saturated and monounsaturated phospholipid bilayers were investigated by NSE spectroscopy. kappa c of phosphatidylcholines (PCS) in liquid crystalline (L alpha) phase ranges from 0.38x10-19 J for 1,2-Dimyristoyl- sn-Glycero-3-Phosphocholine (14:0 PC) to 0.64x10-19 J for 1,2-Dieicosenoyl-sn-Glycero-3-Phosphocholine (20:1 PC). It was confirmed that when the area modulus KA varies little with chain unsaturation or length, the elastic ratios (kappac/ KA)1/2 of bilayers varies linearly with lipid hydrophobic thickness d. For the study of the influence of LA on bio-membranes, SANS measurements have been performed on 14:0 PC bilayers with different concentrations of lidocaine to determine the bilayer thickness dL as a function of the lidocaine concentration. NSE has been used to study the influence of lidocaine on the bending elasticity of 14:0 PC bilayers in Lalpha and ripple gel (Pbeta') phases. Our results confirmed that the molecules of
57 Fe Mössbauer probe of spin crossover thin films on a bio-membrane
NASA Astrophysics Data System (ADS)
Naik, Anil D.; Garcia, Yann
2012-03-01
An illustrious complex [Fe(ptz)6](BF4)2 (ptz = 1-propyl-tetrazole) ( 1) which was produced in the form of submicron crystals and thin film on Allium cepa membrane was probed by 57Fe Mossbauer spectroscopy in order to follow its intrinsic spin crossover. In addition to a weak signal that corresponds to neat SCO compound significant amount of other iron compounds are found that could have morphed from 1 due to specific host-guest interaction on the lipid-bilayer of bio-membrane. Further complimentary information about biogenic role of membrane, was obtained from variable temperature Mossbauer spectroscopy on a ~5% enriched [57Fe(H2O)6](BF4)2 salt on this membrane.
NASA Astrophysics Data System (ADS)
Akdim, Mohamed Reda
2003-09-01
Nowadays plasmas are used for various applications such as the fabrication of silicon solar cells, integrated circuits, coatings and dental cleaning. In the case of a processing plasma, e.g. for the fabrication of amorphous silicon solar cells, a mixture of silane and hydrogen gas is injected in a reactor. These gases are decomposed by making a plasma. A plasma with a low degree of ionization (typically 10_5) is usually made in a reactor containing two electrodes driven by a radio-frequency (RF) power source in the megahertz range. Under the right circumstances the radicals, neutrals and ions can react further to produce nanometer sized dust particles. The particles can stick to the surface and thereby contribute to a higher deposition rate. Another possibility is that the nanometer sized particles coagulate and form larger micron sized particles. These particles obtain a high negative charge, due to their large radius and are usually trapped in a radiofrequency plasma. The electric field present in the discharge sheaths causes the entrapment. Such plasmas are called dusty or complex plasmas. In this thesis numerical models are presented which describe dusty plasmas in reactive and nonreactive plasmas. We started first with the development of a simple one-dimensional silane fluid model where a dusty radio-frequency silane/hydrogen discharge is simulated. In the model, discharge quantities like the fluxes, densities and electric field are calculated self-consistently. A radius and an initial density profile for the spherical dust particles are given and the charge and the density of the dust are calculated with an iterative method. During the transport of the dust, its charge is kept constant in time. The dust influences the electric field distribution through its charge and the density of the plasma through recombination of positive ions and electrons at its surface. In the model this process gives an extra production of silane radicals, since the growth of dust is
Intelligent biomembranes for nicotine releases by radiation curing
NASA Astrophysics Data System (ADS)
Nakayama, Hiroshi; Kaetsu, Isao; Uchida, Kumao; Oishibashi, Manabu; Matsubara, Yoshio
2003-06-01
The authors have studied stimuli-responsive polyelectrolyte and polyampholyte hydrogels. Thermo-responsive copolymer hydrogels have also been studied. Recently, the authors have applied those hydrogels to radiation curable intelligent coatings for the gating of drug release channel. One way of this application is the coating on a drug including membrane to initiate and stop the drug release by on-off switching of stimulations. Some results of application to practical intelligent biomembranes such as glucose-responsive nicotine release membrane and temperature-responsive nicotine release membrane were investigated and their functions as well as of some effective factors on the release profiles were proved.
Modeling complexity in biology
NASA Astrophysics Data System (ADS)
Louzoun, Yoram; Solomon, Sorin; Atlan, Henri; Cohen, Irun. R.
2001-08-01
Biological systems, unlike physical or chemical systems, are characterized by the very inhomogeneous distribution of their components. The immune system, in particular, is notable for self-organizing its structure. Classically, the dynamics of natural systems have been described using differential equations. But, differential equation models fail to account for the emergence of large-scale inhomogeneities and for the influence of inhomogeneity on the overall dynamics of biological systems. Here, we show that a microscopic simulation methodology enables us to model the emergence of large-scale objects and to extend the scope of mathematical modeling in biology. We take a simple example from immunology and illustrate that the methods of classical differential equations and microscopic simulation generate contradictory results. Microscopic simulations generate a more faithful approximation of the reality of the immune system.
Tools for characterizing biomembranes : final LDRD report.
Alam, Todd Michael; Stevens, Mark; Holland, Gregory P.; McIntyre, Sarah K.
2007-10-01
A suite of experimental nuclear magnetic resonance (NMR) spectroscopy tools were developed to investigate lipid structure and dynamics in model membrane systems. By utilizing both multinuclear and multidimensional NMR experiments a range of different intra- and inter-molecular contacts were probed within the membranes. Examples on pure single component lipid membranes and on the canonical raft forming mixture of DOPC/SM/Chol are presented. A unique gel phase pretransition in SM was also identified and characterized using these NMR techniques. In addition molecular dynamics into the hydrogen bonding network unique to sphingomyelin containing membranes were evaluated as a function of temperature, and are discussed.
The thermodynamics of simple biomembrane mimetic systems
Raudino, Antonio; Sarpietro, Maria Grazia; Pannuzzo, Martina
2011-01-01
Insight into the forces governing a system is essential for understanding its behavior and function. Thermodynamic investigations provide a wealth of information that is not, or is hardly, available from other methods. This article reviews thermodynamic approaches and assays to measure collective properties such as heat adsorption / emission and volume variations. These methods can be successfully applied to the study of lipid vesicles (liposomes) and biological membranes. With respect to instrumentation, differential scanning calorimetry, pressure perturbation calorimetry, isothermal titration calorimetry, dilatometry, and acoustic techniques aimed at measuring the isothermal and adiabatic processes, two- and three-dimensional compressibilities are considered. Applications of these techniques to lipid systems include the measurement of different thermodynamic parameters and a detailed characterization of thermotropic, barotropic, and lyotropic phase behavior. The membrane binding and / or partitioning of solutes (proteins, peptides, drugs, surfactants, ions, etc.) can also be quantified and modeled. Many thermodynamic assays are available for studying the effect of proteins and other additives on membranes, characterizing non-ideal mixing, domain formation, bilayer stability, curvature strain, permeability, solubilization, and fusion. Studies of membrane proteins in lipid environments elucidate lipid–protein interactions in membranes. Finally, a plethora of relaxation phenomena toward equilibrium thermodynamic structures can be also investigated. The systems are described in terms of enthalpic and entropic forces, equilibrium constants, heat capacities, partial volume changes, volume and area compressibility, and so on, also shedding light on the stability of the structures and the molecular origin and mechanism of the structural changes. PMID:21430953
Field theoretical approach for bio-membrane coupled with flow field
NASA Astrophysics Data System (ADS)
Oya, Y.; Kawakatsu, T.
2013-02-01
Shape deformation of bio-membranes in flow field is well known phenomenon in biological systems, for example red blood cell in blood vessel. To simulate such deformation with use of field theoretical approach, we derived the dynamical equation of phase field for shape of membrane and coupled the equation with Navier-Stokes equation for flow field. In 2-dimensional simulations, we found that a bio-membrane in a Poiseuille flow takes a parachute shape similar to the red blood cells.
[Effects of selective extraction on microorganisms on biomembrane in natural water body].
Li, Yu; Chen, Jiejiang; Haiyan, Ma; Hua, Xiuyi; Dong, Deming; Guo, Shuhai
2006-02-01
By the methods of direct viable count and plate count, this paper studied the effects of different selective extractants on the bacteria, algae and protozoan on the biomembrane in natural water body. The results indicated that the stronger the extraction ability of selective extractant, the fewer the living microorganisms on the biomembrane after extraction. Compared with the control, the percentages of living microorganisms on the biomembrane were 27.6, 14.1 and 0.01, respectively, after extracted by hydroxylamine hydrochloride (0.01 mol x L(-1) NH2OH.HCl + 0.01 mol x L(-1) HNO3), sodium dithionite (0.4 mol x L(-1) Na2S2O4, pH 6.0), and acidified ammonium oxalate. Very few bacteria was left after extracted by nitric acid (15% HNO3), and no microorgariisms could be detected after extracted by H2O2/HNO3, suggesting that the use of selective extractants affected the activity of biomembrane. With the decreasing amount of microorganisms on the biomembrane after treated with selective extractants, the adsorption of heavy metals by the biomembrane was gradually depressed. PMID:16706056
Banthiya, Swathi; Pekárová, Mária; Kuhn, Hartmut; Heydeck, Dagmar
2015-10-15
Pseudomonas aeruginosa (PA) expresses a secreted lipoxygenase (LOX), which oxygenates free arachidonic acid predominantly to 15S-H(p)ETE. The enzyme is capable of binding phospholipids at its active site and physically interacts with model membranes. However, its membrane oxygenase activity has not been quantified. To address this question, we overexpressed PA-LOX as intracellular his-tag fusion protein in Escherichia coli, purified it to electrophoretic homogeneity and compared its biomembrane oxygenase activity with that of rabbit ALOX15. We found that both enzymes were capable of oxygenating mitochondrial membranes to specific oxygenation products and 13S-H(p)ODE and 15S-H(p)ETE esterified to phosphatidylcholine and phosphatidylethanolamine were identified as major oxygenation products. When normalized to similar linoleic acid oxygenase activity, the rabbit enzyme exhibited a much more effective mitochondrial membrane oxygenase activity. In contrast, during long-term incubations (24 h) with red blood cells PA-LOX induced significant (50%) hemolysis whereas rabbit ALOX15 was more or less ineffective. These data indicate the principle capability of PA-LOX of oxygenating membrane bound phospholipids which is likely to alter the barrier function of the biomembranes. Although the membrane oxygenase activity was lower than the fatty acid oxygenase activity of PA-LOX red blood cell membrane oxygenation might be of biological relevance for P. aeruginosa septicemia. PMID:26361973
Complex Networks in Psychological Models
NASA Astrophysics Data System (ADS)
Wedemann, R. S.; Carvalho, L. S. A. V. D.; Donangelo, R.
We develop schematic, self-organizing, neural-network models to describe mechanisms associated with mental processes, by a neurocomputational substrate. These models are examples of real world complex networks with interesting general topological structures. Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, we propose neural network models to explain development of cortical map structure and dynamics of memory access, and unify different mental processes into a single neurocomputational substrate. Based on our neural network models, neurotic behavior may be understood as an associative memory process in the brain, and the linguistic, symbolic associative process involved in psychoanalytic working-through can be mapped onto a corresponding process of reconfiguration of the neural network. The models are illustrated through computer simulations, where we varied dopaminergic modulation and observed the self-organizing emergent patterns at the resulting semantic map, interpreting them as different manifestations of mental functioning, from psychotic through to normal and neurotic behavior, and creativity.
Dynamics of biomembranes with active multiple-state inclusions.
Chen, Hsuan-Yi; Mikhailov, Alexander S
2010-03-01
Nonequilibrium dynamics of biomembranes with active multiple-state inclusions is considered. The inclusions represent protein molecules which perform cyclic internal conformational motions driven by the energy brought with adenosine triphosphate (ATP) ligands. As protein conformations cyclically change, this induces hydrodynamical flows and also directly affects the local curvature of a membrane. On the other hand, variations in the local curvature of the membrane modify the transition rates between conformational states in a protein, leading to a feedback in the considered system. Moreover, active inclusions can move diffusively through the membrane so that their surface concentration varies. The kinetic description of this system is constructed and the stability of the uniform stationary state is analytically investigated. We show that, as the rate of supply of chemical energy is increased above a certain threshold, this uniform state becomes unstable and stationary or traveling waves spontaneously develop in the system. Such waves are accompanied by periodic spatial variations of the membrane curvature and the inclusion density. For typical parameter values, their characteristic wavelengths are of the order of hundreds of nanometers. For traveling waves, the characteristic frequency is of the order of a thousand Hz or less. The predicted instabilities are possible only if at least three internal inclusion states are present. PMID:20365764
Morphological and Physical Analysis of Natural Phospholipids-Based Biomembranes
Jacquot, Adrien; Francius, Grégory; Razafitianamaharavo, Angelina; Dehghani, Fariba; Tamayol, Ali; Linder, Michel; Arab-Tehrany, Elmira
2014-01-01
Background Liposomes are currently an important part of biological, pharmaceutical, medical and nutritional research, as they are considered to be among the most effective carriers for the introduction of various types of bioactive agents into target cells. Scope of Review In this work, we study the lipid organization and mechanical properties of biomembranes made of marine and plant phospholipids. Membranes based on phospholipids extracted from rapeseed and salmon are studied in the form of liposome and as supported lipid bilayer. Dioleylphosphatidylcholine (DOPC) and dipalmitoylphosphatidylcholine (DPPC) are used as references to determine the lipid organization of marine and plant phospholipid based membranes. Atomic force microscopy (AFM) imaging and force spectroscopy measurements are performed to investigate the membranes' topography at the micrometer scale and to determine their mechanical properties. Major Conclusions The mechanical properties of the membranes are correlated to the fatty acid composition, the morphology, the electrophoretic mobility and the membrane fluidity. Thus, soft and homogeneous mechanical properties are evidenced for salmon phospholipids membrane containing various polyunsaturated fatty acids. Besides, phase segregation in rapeseed membrane and more important mechanical properties were emphasized for this type of membranes by contrast to the marine phospholipids based membranes. General Significance This paper provides new information on the nanomechanical and morphological properties of membrane in form of liposome by AFM. The originality of this work is to characterize the physico-chemical properties of the nanoliposome from the natural sources containing various fatty acids and polar head. PMID:25238543
Interaction of holothurian triterpene glycoside with biomembranes of mouse immune cells.
Pislyagin, E A; Gladkikh, R V; Kapustina, I I; Kim, N Yu; Shevchenko, V P; Nagaev, I Yu; Avilov, S A; Aminin, D L
2012-09-01
The in vitro interactions between triterpene glycoside, cucumarioside A(2)-2, isolated from the Far-Eastern holothurian Cucumaria japonica, and mouse splenocyte and peritoneal macrophage biomembranes were studied. Multiple experimental approaches were employed, including determination of biomembrane microviscosity, membrane potential and Ca(2+) signaling, and radioligand binding assays. Cucumarioside A(2)-2 exhibited strong cytotoxic effect in the micromolar range of concentrations and showed pronounced immunomodulatory activity in the nanomolar concentration range. It was established that the cucumarioside A(2)-2 effectively interacted with immune cells and increased the cellular biomembrane microviscosity. This interaction led to a dose-dependent reversible shift in cellular membrane potential and temporary biomembrane depolarization; and an increase in [Ca(2+)](i) in the cytoplasm. It is suggested that there are at least two binding sites for [(3)H]-cucumarioside A(2)-2 on cellular membranes corresponding to different biomembrane components: a low affinity site match to membrane cholesterol that is responsible for the cytotoxic properties, and a high affinity site corresponding to a hypothetical receptor that is responsible for immunostimulation. PMID:22683181
Modeling Wildfire Incident Complexity Dynamics
Thompson, Matthew P.
2013-01-01
Wildfire management in the United States and elsewhere is challenged by substantial uncertainty regarding the location and timing of fire events, the socioeconomic and ecological consequences of these events, and the costs of suppression. Escalating U.S. Forest Service suppression expenditures is of particular concern at a time of fiscal austerity as swelling fire management budgets lead to decreases for non-fire programs, and as the likelihood of disruptive within-season borrowing potentially increases. Thus there is a strong interest in better understanding factors influencing suppression decisions and in turn their influence on suppression costs. As a step in that direction, this paper presents a probabilistic analysis of geographic and temporal variation in incident management team response to wildfires. The specific focus is incident complexity dynamics through time for fires managed by the U.S. Forest Service. The modeling framework is based on the recognition that large wildfire management entails recurrent decisions across time in response to changing conditions, which can be represented as a stochastic dynamic system. Daily incident complexity dynamics are modeled according to a first-order Markov chain, with containment represented as an absorbing state. A statistically significant difference in complexity dynamics between Forest Service Regions is demonstrated. Incident complexity probability transition matrices and expected times until containment are presented at national and regional levels. Results of this analysis can help improve understanding of geographic variation in incident management and associated cost structures, and can be incorporated into future analyses examining the economic efficiency of wildfire management. PMID:23691014
Hepatocellular biomembrane peroxidation in copper-induced injury
Homer, B.L.
1986-01-01
The pathogenesis of Cu-induced hepatocellular biomembrane peroxidation was studied in male Fischer rats by analyzing hepatic morphologic alterations, measuring the activity of hepatic free radical scavenger enzymes, and determining the distribution of hepatic cytosolic Cu bound to high and low molecular weight proteins. Seventy-five weanling rats were divided into 3 group of 25 each and injected once daily with either 6.25 mg/kg or 12.5 mg/kg cupric chloride, or 0.2 ml/100 gm saline. Five rats from each group were killed after 3, 14, 28, 42, and 70 consecutive days of injections. The level of malondialdehyde was elevated after 3 days of Cu injections and continued to increase until it peaked in the high-dose group after 28 days and in the low-dose group after 42 days. The density of catalase-containing peroxisomes was reduced in Cu-treated rats, correlating with a reduced activity of hepatic catalase. Catalase activity in Cu-treated rats was reduced after 3 days, and always remained < or = to the activity in control rats. The activity of glutathione peroxidase in high-dose rats always was < or = to the level in control rats, while the activity in control rats always was < or = to the level in low-dose rats. Meanwhile, the activity of superoxide dismutase increase in Cu-treated rats after 28 days. The concentration of cytosolic low molecular weight protein-bound Cu was elevated after 3 days in both Cu-treated groups and continued to increase, leveling off or peaking after 42 days. Regression analysis and in vitro studies, involving the peroxidation of erythrocyte ghost membranes, demonstrated that Cu bound to low molecular weight proteins was less likely to induce lipoperoxidation than copper bound to high molecular weight proteins.
Explosion modelling for complex geometries
NASA Astrophysics Data System (ADS)
Nehzat, Naser
A literature review suggested that the combined effects of fuel reactivity, obstacle density, ignition strength, and confinement result in flame acceleration and subsequent pressure build-up during a vapour cloud explosion (VCE). Models for the prediction of propagating flames in hazardous areas, such as coal mines, oil platforms, storage and process chemical areas etc. fall into two classes. One class involves use of Computation Fluid Dynamics (CFD). This approach has been utilised by several researchers. The other approach relies upon a lumped parameter approach as developed by Baker (1983). The former approach is restricted by the appropriateness of sub-models and numerical stability requirements inherent in the computational solution. The latter approach raises significant questions regarding the validity of the simplification involved in representing the complexities of a propagating explosion. This study was conducted to investigate and improve the Computational Fluid Dynamic (CFD) code EXPLODE which has been developed by Green et al., (1993) for use on practical gas explosion hazard assessments. The code employs a numerical method for solving partial differential equations by using finite volume techniques. Verification exercises, involving comparison with analytical solutions for the classical shock-tube and with experimental (small-scale, medium and large-scale) results, demonstrate the accuracy of the code and the new combustion models but also identify differences between predictions and the experimental results. The project has resulted in a developed version of the code (EXPLODE2) with new combustion models for simulating gas explosions. Additional features of this program include the physical models necessary to simulate the combustion process using alternative combustion models, improvement to the numerical accuracy and robustness of the code, and special input for simulation of different gas explosions. The present code has the capability of
A physical interpretation of hydrologic model complexity
NASA Astrophysics Data System (ADS)
Moayeri, MohamadMehdi; Pande, Saket
2015-04-01
It is intuitive that instability of hydrological system representation, in the sense of how perturbations in input forcings translate into perturbation in a hydrologic response, may depend on its hydrological characteristics. Responses of unstable systems are thus complex to model. We interpret complexity in this context and define complexity as a measure of instability in hydrological system representation. We provide algorithms to quantify model complexity in this context. We use Sacramento soil moisture accounting model (SAC-SMA) parameterized for MOPEX basins and quantify complexities of corresponding models. Relationships between hydrologic characteristics of MOPEX basins such as location, precipitation seasonality index, slope, hydrologic ratios, saturated hydraulic conductivity and NDVI and respective model complexities are then investigated. We hypothesize that complexities of basin specific SAC-SMA models correspond to aforementioned hydrologic characteristics, thereby suggesting that model complexity, in the context presented here, may have a physical interpretation.
Teacher Modeling Using Complex Informational Texts
ERIC Educational Resources Information Center
Fisher, Douglas; Frey, Nancy
2015-01-01
Modeling in complex texts requires that teachers analyze the text for factors of qualitative complexity and then design lessons that introduce students to that complexity. In addition, teachers can model the disciplinary nature of content area texts as well as word solving and comprehension strategies. Included is a planning guide for think aloud.
Formation of Biomembrane Microarrays with a Squeegee-based Assembly Method
Wittenberg, Nathan J.; Johnson, Timothy W.; Jordan, Luke R.; Xu, Xiaohua; Warrington, Arthur E.; Rodriguez, Moses; Oh, Sang-Hyun
2014-01-01
Lipid bilayer membranes form the plasma membranes of cells and define the boundaries of subcellular organelles. In nature, these membranes are heterogeneous mixtures of many types of lipids, contain membrane-bound proteins and are decorated with carbohydrates. In some experiments, it is desirable to decouple the biophysical or biochemical properties of the lipid bilayer from those of the natural membrane. Such cases call for the use of model systems such as giant vesicles, liposomes or supported lipid bilayers (SLBs). Arrays of SLBs are particularly attractive for sensing applications and mimicking cell-cell interactions. Here we describe a new method for forming SLB arrays. Submicron-diameter SiO2 beads are first coated with lipid bilayers to form spherical SLBs (SSLBs). The beads are then deposited into an array of micro-fabricated submicron-diameter microwells. The preparation technique uses a "squeegee" to clean the substrate surface, while leaving behind SSLBs that have settled into microwells. This method requires no chemical modification of the microwell substrate, nor any particular targeting ligands on the SSLB. Microwells are occupied by single beads because the well diameter is tuned to be just larger than the bead diameter. Typically, more 75% of the wells are occupied, while the rest remain empty. In buffer SSLB arrays display long-term stability of greater than one week. Multiple types of SSLBs can be placed in a single array by serial deposition, and the arrays can be used for sensing, which we demonstrate by characterizing the interaction of cholera toxin with ganglioside GM1. We also show that phospholipid vesicles without the bead supports and biomembranes from cellular sources can be arrayed with the same method and cell-specific membrane lipids can be identified. PMID:24837169
Formation of biomembrane microarrays with a squeegee-based assembly method.
Wittenberg, Nathan J; Johnson, Timothy W; Jordan, Luke R; Xu, Xiaohua; Warrington, Arthur E; Rodriguez, Moses; Oh, Sang-Hyun
2014-01-01
Lipid bilayer membranes form the plasma membranes of cells and define the boundaries of subcellular organelles. In nature, these membranes are heterogeneous mixtures of many types of lipids, contain membrane-bound proteins and are decorated with carbohydrates. In some experiments, it is desirable to decouple the biophysical or biochemical properties of the lipid bilayer from those of the natural membrane. Such cases call for the use of model systems such as giant vesicles, liposomes or supported lipid bilayers (SLBs). Arrays of SLBs are particularly attractive for sensing applications and mimicking cell-cell interactions. Here we describe a new method for forming SLB arrays. Submicron-diameter SiO2 beads are first coated with lipid bilayers to form spherical SLBs (SSLBs). The beads are then deposited into an array of micro-fabricated submicron-diameter microwells. The preparation technique uses a "squeegee" to clean the substrate surface, while leaving behind SSLBs that have settled into microwells. This method requires no chemical modification of the microwell substrate, nor any particular targeting ligands on the SSLB. Microwells are occupied by single beads because the well diameter is tuned to be just larger than the bead diameter. Typically, more 75% of the wells are occupied, while the rest remain empty. In buffer SSLB arrays display long-term stability of greater than one week. Multiple types of SSLBs can be placed in a single array by serial deposition, and the arrays can be used for sensing, which we demonstrate by characterizing the interaction of cholera toxin with ganglioside GM1. We also show that phospholipid vesicles without the bead supports and biomembranes from cellular sources can be arrayed with the same method and cell-specific membrane lipids can be identified. PMID:24837169
"Computational Modeling of Actinide Complexes"
Balasubramanian, K
2007-03-07
We will present our recent studies on computational actinide chemistry of complexes which are not only interesting from the standpoint of actinide coordination chemistry but also of relevance to environmental management of high-level nuclear wastes. We will be discussing our recent collaborative efforts with Professor Heino Nitsche of LBNL whose research group has been actively carrying out experimental studies on these species. Computations of actinide complexes are also quintessential to our understanding of the complexes found in geochemical, biochemical environments and actinide chemistry relevant to advanced nuclear systems. In particular we have been studying uranyl, plutonyl, and Cm(III) complexes are in aqueous solution. These studies are made with a variety of relativistic methods such as coupled cluster methods, DFT, and complete active space multi-configuration self-consistent-field (CASSCF) followed by large-scale CI computations and relativistic CI (RCI) computations up to 60 million configurations. Our computational studies on actinide complexes were motivated by ongoing EXAFS studies of speciated complexes in geo and biochemical environments carried out by Prof Heino Nitsche's group at Berkeley, Dr. David Clark at Los Alamos and Dr. Gibson's work on small actinide molecules at ORNL. The hydrolysis reactions of urnayl, neputyl and plutonyl complexes have received considerable attention due to their geochemical and biochemical importance but the results of free energies in solution and the mechanism of deprotonation have been topic of considerable uncertainty. We have computed deprotonating and migration of one water molecule from the first solvation shell to the second shell in UO{sub 2}(H{sub 2}O){sub 5}{sup 2+}, UO{sub 2}(H{sub 2}O){sub 5}{sup 2+}NpO{sub 2}(H{sub 2}O){sub 6}{sup +}, and PuO{sub 2}(H{sub 2}O){sub 5}{sup 2+} complexes. Our computed Gibbs free energy(7.27 kcal/m) in solution for the first time agrees with the experiment (7.1 kcal
Capturing Complexity through Maturity Modelling
ERIC Educational Resources Information Center
Underwood, Jean; Dillon, Gayle
2004-01-01
The impact of information and communication technologies (ICT) on the process and products of education is difficult to assess for a number of reasons. In brief, education is a complex system of interrelationships, of checks and balances. This context is not a neutral backdrop on which teaching and learning are played out. Rather, it may help, or…
Does increased hydrochemical model complexity decrease robustness?
NASA Astrophysics Data System (ADS)
Medici, C.; Wade, A. J.; Francés, F.
2012-05-01
SummaryThe aim of this study was, within a sensitivity analysis framework, to determine if additional model complexity gives a better capability to model the hydrology and nitrogen dynamics of a small Mediterranean forested catchment or if the additional parameters cause over-fitting. Three nitrogen-models of varying hydrological complexity were considered. For each model, general sensitivity analysis (GSA) and Generalized Likelihood Uncertainty Estimation (GLUE) were applied, each based on 100,000 Monte Carlo simulations. The results highlighted the most complex structure as the most appropriate, providing the best representation of the non-linear patterns observed in the flow and streamwater nitrate concentrations between 1999 and 2002. Its 5% and 95% GLUE bounds, obtained considering a multi-objective approach, provide the narrowest band for streamwater nitrogen, which suggests increased model robustness, though all models exhibit periods of inconsistent good and poor fits between simulated outcomes and observed data. The results confirm the importance of the riparian zone in controlling the short-term (daily) streamwater nitrogen dynamics in this catchment but not the overall flux of nitrogen from the catchment. It was also shown that as the complexity of a hydrological model increases over-parameterisation occurs, but the converse is true for a water quality model where additional process representation leads to additional acceptable model simulations. Water quality data help constrain the hydrological representation in process-based models. Increased complexity was justifiable for modelling river-system hydrochemistry. Increased complexity was justifiable for modelling river-system hydrochemistry.
Complexity and Uncertainty in Soil Nitrogen Modeling
NASA Astrophysics Data System (ADS)
Ajami, N. K.; Gu, C.
2009-12-01
Model uncertainty is rarely considered in the field of biogeochemical modeling. The standard biogeochemical modeling approach is to proceed based on one selected model with the “right” complexity level based on data availability. However other plausible models can result in dissimilar answer to the scientific question in hand using the same set of data. Relying on a single model can lead to underestimation of uncertainty associated with the results and therefore lead to unreliable conclusions. Multi-model ensemble strategy is a means to exploit the diversity of skillful predictions from different models with multiple levels of complexity. The aim of this study is two fold, first to explore the impact of a model’s complexity level on the accuracy of the end results and second to introduce a probabilistic multi-model strategy in the context of a process-based biogeochemical model. We developed three different versions of a biogeochemical model, TOUGHREACT-N, with various complexity levels. Each one of these models was calibrated against the observed data from a tomato field in Western Sacramento County, California, and considered two different weighting sets on the objective function. This way we created a set of six ensemble members. The Bayesian Model Averaging (BMA) approach was then used to combine these ensemble members by the likelihood that an individual model is correct given the observations. The results clearly indicate the need to consider a multi-model ensemble strategy over a single model selection in biogeochemical modeling.
Fock spaces for modeling macromolecular complexes
NASA Astrophysics Data System (ADS)
Kinney, Justin
Large macromolecular complexes play a fundamental role in how cells function. Here I describe a Fock space formalism for mathematically modeling these complexes. Specifically, this formalism allows ensembles of complexes to be defined in terms of elementary molecular ``building blocks'' and ``assembly rules.'' Such definitions avoid the massive redundancy inherent in standard representations, in which all possible complexes are manually enumerated. Methods for systematically computing ensembles of complexes from a list of components and interaction rules are described. I also show how this formalism readily accommodates coarse-graining. Finally, I introduce diagrammatic techniques that greatly facilitate the application of this formalism to both equilibrium and non-equilibrium biochemical systems.
Molecular simulation and modeling of complex I.
Hummer, Gerhard; Wikström, Mårten
2016-07-01
Molecular modeling and molecular dynamics simulations play an important role in the functional characterization of complex I. With its large size and complicated function, linking quinone reduction to proton pumping across a membrane, complex I poses unique modeling challenges. Nonetheless, simulations have already helped in the identification of possible proton transfer pathways. Simulations have also shed light on the coupling between electron and proton transfer, thus pointing the way in the search for the mechanistic principles underlying the proton pump. In addition to reviewing what has already been achieved in complex I modeling, we aim here to identify pressing issues and to provide guidance for future research to harness the power of modeling in the functional characterization of complex I. This article is part of a Special Issue entitled Respiratory complex I, edited by Volker Zickermann and Ulrich Brandt. PMID:26780586
Selecting model complexity in learning problems
Buescher, K.L.; Kumar, P.R.
1993-10-01
To learn (or generalize) from noisy data, one must resist the temptation to pick a model for the underlying process that overfits the data. Many existing techniques solve this problem at the expense of requiring the evaluation of an absolute, a priori measure of each model`s complexity. We present a method that does not. Instead, it uses a natural, relative measure of each model`s complexity. This method first creates a pool of ``simple`` candidate models using part of the data and then selects from among these by using the rest of the data.
Scaffolding in Complex Modelling Situations
ERIC Educational Resources Information Center
Stender, Peter; Kaiser, Gabriele
2015-01-01
The implementation of teacher-independent realistic modelling processes is an ambitious educational activity with many unsolved problems so far. Amongst others, there hardly exists any empirical knowledge about efficient ways of possible teacher support with students' activities, which should be mainly independent from the teacher. The research…
Role models for complex networks
NASA Astrophysics Data System (ADS)
Reichardt, J.; White, D. R.
2007-11-01
We present a framework for automatically decomposing (“block-modeling”) the functional classes of agents within a complex network. These classes are represented by the nodes of an image graph (“block model”) depicting the main patterns of connectivity and thus functional roles in the network. Using a first principles approach, we derive a measure for the fit of a network to any given image graph allowing objective hypothesis testing. From the properties of an optimal fit, we derive how to find the best fitting image graph directly from the network and present a criterion to avoid overfitting. The method can handle both two-mode and one-mode data, directed and undirected as well as weighted networks and allows for different types of links to be dealt with simultaneously. It is non-parametric and computationally efficient. The concepts of structural equivalence and modularity are found as special cases of our approach. We apply our method to the world trade network and analyze the roles individual countries play in the global economy.
Agent-based modeling of complex infrastructures
North, M. J.
2001-06-01
Complex Adaptive Systems (CAS) can be applied to investigate complex infrastructures and infrastructure interdependencies. The CAS model agents within the Spot Market Agent Research Tool (SMART) and Flexible Agent Simulation Toolkit (FAST) allow investigation of the electric power infrastructure, the natural gas infrastructure and their interdependencies.
Numerical models of complex diapirs
NASA Astrophysics Data System (ADS)
Podladchikov, Yu.; Talbot, C.; Poliakov, A. N. B.
1993-12-01
Numerically modelled diapirs that rise into overburdens with viscous rheology produce a large variety of shapes. This work uses the finite-element method to study the development of diapirs that rise towards a surface on which a diapir-induced topography creeps flat or disperses ("erodes") at different rates. Slow erosion leads to diapirs with "mushroom" shapes, moderate erosion rate to "wine glass" diapirs and fast erosion to "beer glass"- and "column"-shaped diapirs. The introduction of a low-viscosity layer at the top of the overburden causes diapirs to develop into structures resembling a "Napoleon hat". These spread lateral sheets.
Complex system modelling for veterinary epidemiology.
Lanzas, Cristina; Chen, Shi
2015-02-01
The use of mathematical models has a long tradition in infectious disease epidemiology. The nonlinear dynamics and complexity of pathogen transmission pose challenges in understanding its key determinants, in identifying critical points, and designing effective mitigation strategies. Mathematical modelling provides tools to explicitly represent the variability, interconnectedness, and complexity of systems, and has contributed to numerous insights and theoretical advances in disease transmission, as well as to changes in public policy, health practice, and management. In recent years, our modelling toolbox has considerably expanded due to the advancements in computing power and the need to model novel data generated by technologies such as proximity loggers and global positioning systems. In this review, we discuss the principles, advantages, and challenges associated with the most recent modelling approaches used in systems science, the interdisciplinary study of complex systems, including agent-based, network and compartmental modelling. Agent-based modelling is a powerful simulation technique that considers the individual behaviours of system components by defining a set of rules that govern how individuals ("agents") within given populations interact with one another and the environment. Agent-based models have become a recent popular choice in epidemiology to model hierarchical systems and address complex spatio-temporal dynamics because of their ability to integrate multiple scales and datasets. PMID:25449734
Modelling Canopy Flows over Complex Terrain
NASA Astrophysics Data System (ADS)
Grant, Eleanor R.; Ross, Andrew N.; Gardiner, Barry A.
2016-06-01
Recent studies of flow over forested hills have been motivated by a number of important applications including understanding CO_2 and other gaseous fluxes over forests in complex terrain, predicting wind damage to trees, and modelling wind energy potential at forested sites. Current modelling studies have focussed almost exclusively on highly idealized, and usually fully forested, hills. Here, we present model results for a site on the Isle of Arran, Scotland with complex terrain and heterogeneous forest canopy. The model uses an explicit representation of the canopy and a 1.5-order turbulence closure for flow within and above the canopy. The validity of the closure scheme is assessed using turbulence data from a field experiment before comparing predictions of the full model with field observations. For near-neutral stability, the results compare well with the observations, showing that such a relatively simple canopy model can accurately reproduce the flow patterns observed over complex terrain and realistic, variable forest cover, while at the same time remaining computationally feasible for real case studies. The model allows closer examination of the flow separation observed over complex forested terrain. Comparisons with model simulations using a roughness length parametrization show significant differences, particularly with respect to flow separation, highlighting the need to explicitly model the forest canopy if detailed predictions of near-surface flow around forests are required.
Explicit stress integration of complex soil models
NASA Astrophysics Data System (ADS)
Zhao, Jidong; Sheng, Daichao; Rouainia, M.; Sloan, Scott W.
2005-10-01
In this paper, two complex critical-state models are implemented in a displacement finite element code. The two models are used for structured clays and sands, and are characterized by multiple yield surfaces, plastic yielding within the yield surface, and complex kinematic and isotropic hardening laws. The consistent tangent operators - which lead to a quadratic convergence when used in a fully implicit algorithm - are difficult to derive or may even not exist. The stress integration scheme used in this paper is based on the explicit Euler method with automatic substepping and error control. This scheme employs the classical elastoplastic stiffness matrix and requires only the first derivatives of the yield function and plastic potential. This explicit scheme is used to integrate the two complex critical-state models - the sub/super-loading surfaces model (SSLSM) and the kinematic hardening structure model (KHSM). Various boundary-value problems are then analysed. The results for the two models are compared with each other, as well with those from standard Cam-clay models. Accuracy and efficiency of the scheme used for the complex models are also investigated. Copyright
SUMMARY OF COMPLEX TERRAIN MODEL EVALUATION
The Environmental Protection Agency conducted a scientific review of a set of eight complex terrain dispersion models. TRC Environmental Consultants, Inc. calculated and tabulated a uniform set of performance statistics for the models using the Cinder Cone Butte and Westvaco Luke...
Building phenomenological models of complex biological processes
NASA Astrophysics Data System (ADS)
Daniels, Bryan; Nemenman, Ilya
2009-11-01
A central goal of any modeling effort is to make predictions regarding experimental conditions that have not yet been observed. Overly simple models will not be able to fit the original data well, but overly complex models are likely to overfit the data and thus produce bad predictions. Modern quantitative biology modeling efforts often err on the complexity side of this balance, using myriads of microscopic biochemical reaction processes with a priori unknown kinetic parameters to model relatively simple biological phenomena. In this work, we show how Bayesian model selection (which is mathematically similar to low temperature expansion in statistical physics) can be used to build coarse-grained, phenomenological models of complex dynamical biological processes, which have better predictive powers than microscopically correct, but poorely constrained mechanistic molecular models. We illustrate this on the example of a multiply-modifiable protein molecule, which is a simplified description of multiple biological systems, such as an immune receptors and an RNA polymerase complex. Our approach is similar in spirit to the phenomenological Landau expansion for the free energy in the theory of critical phenomena.
From Complex to Simple: Interdisciplinary Stochastic Models
ERIC Educational Resources Information Center
Mazilu, D. A.; Zamora, G.; Mazilu, I.
2012-01-01
We present two simple, one-dimensional, stochastic models that lead to a qualitative understanding of very complex systems from biology, nanoscience and social sciences. The first model explains the complicated dynamics of microtubules, stochastic cellular highways. Using the theory of random walks in one dimension, we find analytical expressions…
Modeling the chemistry of complex petroleum mixtures.
Quann, R J
1998-01-01
Determining the complete molecular composition of petroleum and its refined products is not feasible with current analytical techniques because of the astronomical number of molecular components. Modeling the composition and behavior of such complex mixtures in refinery processes has accordingly evolved along a simplifying concept called lumping. Lumping reduces the complexity of the problem to a manageable form by grouping the entire set of molecular components into a handful of lumps. This traditional approach does not have a molecular basis and therefore excludes important aspects of process chemistry and molecular property fundamentals from the model's formulation. A new approach called structure-oriented lumping has been developed to model the composition and chemistry of complex mixtures at a molecular level. The central concept is to represent an individual molecular or a set of closely related isomers as a mathematical construct of certain specific and repeating structural groups. A complex mixture such as petroleum can then be represented as thousands of distinct molecular components, each having a mathematical identity. This enables the automated construction of large complex reaction networks with tens of thousands of specific reactions for simulating the chemistry of complex mixtures. Further, the method provides a convenient framework for incorporating molecular physical property correlations, existing group contribution methods, molecular thermodynamic properties, and the structure--activity relationships of chemical kinetics in the development of models. PMID:9860903
Updating the debate on model complexity
Simmons, Craig T.; Hunt, Randall J.
2012-01-01
As scientists who are trying to understand a complex natural world that cannot be fully characterized in the field, how can we best inform the society in which we live? This founding context was addressed in a special session, “Complexity in Modeling: How Much is Too Much?” convened at the 2011 Geological Society of America Annual Meeting. The session had a variety of thought-provoking presentations—ranging from philosophy to cost-benefit analyses—and provided some areas of broad agreement that were not evident in discussions of the topic in 1998 (Hunt and Zheng, 1999). The session began with a short introduction during which model complexity was framed borrowing from an economic concept, the Law of Diminishing Returns, and an example of enjoyment derived by eating ice cream. Initially, there is increasing satisfaction gained from eating more ice cream, to a point where the gain in satisfaction starts to decrease, ending at a point when the eater sees no value in eating more ice cream. A traditional view of model complexity is similar—understanding gained from modeling can actually decrease if models become unnecessarily complex. However, oversimplified models—those that omit important aspects of the problem needed to make a good prediction—can also limit and confound our understanding. Thus, the goal of all modeling is to find the “sweet spot” of model sophistication—regardless of whether complexity was added sequentially to an overly simple model or collapsed from an initial highly parameterized framework that uses mathematics and statistics to attain an optimum (e.g., Hunt et al., 2007). Thus, holistic parsimony is attained, incorporating “as simple as possible,” as well as the equally important corollary “but no simpler.”
Balancing model complexity and measurements in hydrology
NASA Astrophysics Data System (ADS)
Van De Giesen, N.; Schoups, G.; Weijs, S. V.
2012-12-01
The Data Processing Inequality implies that hydrological modeling can only reduce, and never increase, the amount of information available in the original data used to formulate and calibrate hydrological models: I(X;Z(Y)) ≤ I(X;Y). Still, hydrologists around the world seem quite content building models for "their" watersheds to move our discipline forward. Hydrological models tend to have a hybrid character with respect to underlying physics. Most models make use of some well established physical principles, such as mass and energy balances. One could argue that such principles are based on many observations, and therefore add data. These physical principles, however, are applied to hydrological models that often contain concepts that have no direct counterpart in the observable physical universe, such as "buckets" or "reservoirs" that fill up and empty out over time. These not-so-physical concepts are more like the Artificial Neural Networks and Support Vector Machines of the Artificial Intelligence (AI) community. Within AI, one quickly came to the realization that by increasing model complexity, one could basically fit any dataset but that complexity should be controlled in order to be able to predict unseen events. The more data are available to train or calibrate the model, the more complex it can be. Many complexity control approaches exist in AI, with Solomonoff inductive inference being one of the first formal approaches, the Akaike Information Criterion the most popular, and Statistical Learning Theory arguably being the most comprehensive practical approach. In hydrology, complexity control has hardly been used so far. There are a number of reasons for that lack of interest, the more valid ones of which will be presented during the presentation. For starters, there are no readily available complexity measures for our models. Second, some unrealistic simplifications of the underlying complex physics tend to have a smoothing effect on possible model
Multifaceted Modelling of Complex Business Enterprises.
Chakraborty, Subrata; Mengersen, Kerrie; Fidge, Colin; Ma, Lin; Lassen, David
2015-01-01
We formalise and present a new generic multifaceted complex system approach for modelling complex business enterprises. Our method has a strong focus on integrating the various data types available in an enterprise which represent the diverse perspectives of various stakeholders. We explain the challenges faced and define a novel approach to converting diverse data types into usable Bayesian probability forms. The data types that can be integrated include historic data, survey data, and management planning data, expert knowledge and incomplete data. The structural complexities of the complex system modelling process, based on various decision contexts, are also explained along with a solution. This new application of complex system models as a management tool for decision making is demonstrated using a railway transport case study. The case study demonstrates how the new approach can be utilised to develop a customised decision support model for a specific enterprise. Various decision scenarios are also provided to illustrate the versatility of the decision model at different phases of enterprise operations such as planning and control. PMID:26247591
Multifaceted Modelling of Complex Business Enterprises
2015-01-01
We formalise and present a new generic multifaceted complex system approach for modelling complex business enterprises. Our method has a strong focus on integrating the various data types available in an enterprise which represent the diverse perspectives of various stakeholders. We explain the challenges faced and define a novel approach to converting diverse data types into usable Bayesian probability forms. The data types that can be integrated include historic data, survey data, and management planning data, expert knowledge and incomplete data. The structural complexities of the complex system modelling process, based on various decision contexts, are also explained along with a solution. This new application of complex system models as a management tool for decision making is demonstrated using a railway transport case study. The case study demonstrates how the new approach can be utilised to develop a customised decision support model for a specific enterprise. Various decision scenarios are also provided to illustrate the versatility of the decision model at different phases of enterprise operations such as planning and control. PMID:26247591
Slip complexity in earthquake fault models.
Rice, J R; Ben-Zion, Y
1996-01-01
We summarize studies of earthquake fault models that give rise to slip complexities like those in natural earthquakes. For models of smooth faults between elastically deformable continua, it is critical that the friction laws involve a characteristic distance for slip weakening or evolution of surface state. That results in a finite nucleation size, or coherent slip patch size, h*. Models of smooth faults, using numerical cell size properly small compared to h*, show periodic response or complex and apparently chaotic histories of large events but have not been found to show small event complexity like the self-similar (power law) Gutenberg-Richter frequency-size statistics. This conclusion is supported in the present paper by fully inertial elastodynamic modeling of earthquake sequences. In contrast, some models of locally heterogeneous faults with quasi-independent fault segments, represented approximately by simulations with cell size larger than h* so that the model becomes "inherently discrete," do show small event complexity of the Gutenberg-Richter type. Models based on classical friction laws without a weakening length scale or for which the numerical procedure imposes an abrupt strength drop at the onset of slip have h* = 0 and hence always fall into the inherently discrete class. We suggest that the small-event complexity that some such models show will not survive regularization of the constitutive description, by inclusion of an appropriate length scale leading to a finite h*, and a corresponding reduction of numerical grid size. Images Fig. 2 Fig. 3 Fig. 4 Fig. 5 PMID:11607669
Minimum-complexity helicopter simulation math model
NASA Technical Reports Server (NTRS)
Heffley, Robert K.; Mnich, Marc A.
1988-01-01
An example of a minimal complexity simulation helicopter math model is presented. Motivating factors are the computational delays, cost, and inflexibility of the very sophisticated math models now in common use. A helicopter model form is given which addresses each of these factors and provides better engineering understanding of the specific handling qualities features which are apparent to the simulator pilot. The technical approach begins with specification of features which are to be modeled, followed by a build up of individual vehicle components and definition of equations. Model matching and estimation procedures are given which enable the modeling of specific helicopters from basic data sources such as flight manuals. Checkout procedures are given which provide for total model validation. A number of possible model extensions and refinement are discussed. Math model computer programs are defined and listed.
Constructing minimal models for complex system dynamics
NASA Astrophysics Data System (ADS)
Barzel, Baruch; Liu, Yang-Yu; Barabási, Albert-László
2015-05-01
One of the strengths of statistical physics is the ability to reduce macroscopic observations into microscopic models, offering a mechanistic description of a system's dynamics. This paradigm, rooted in Boltzmann's gas theory, has found applications from magnetic phenomena to subcellular processes and epidemic spreading. Yet, each of these advances were the result of decades of meticulous model building and validation, which are impossible to replicate in most complex biological, social or technological systems that lack accurate microscopic models. Here we develop a method to infer the microscopic dynamics of a complex system from observations of its response to external perturbations, allowing us to construct the most general class of nonlinear pairwise dynamics that are guaranteed to recover the observed behaviour. The result, which we test against both numerical and empirical data, is an effective dynamic model that can predict the system's behaviour and provide crucial insights into its inner workings.
Modeling acuity for optotypes varying in complexity.
Watson, Andrew B; Ahumada, Albert J
2012-01-01
Watson and Ahumada (2008) described a template model of visual acuity based on an ideal-observer limited by optical filtering, neural filtering, and noise. They computed predictions for selected optotypes and optical aberrations. Here we compare this model's predictions to acuity data for six human observers, each viewing seven different optotype sets, consisting of one set of Sloan letters and six sets of Chinese characters, differing in complexity (Zhang, Zhang, Xue, Liu, & Yu, 2007). Since optical aberrations for the six observers were unknown, we constructed 200 model observers using aberrations collected from 200 normal human eyes (Thibos, Hong, Bradley, & Cheng, 2002). For each condition (observer, optotype set, model observer) we estimated the model noise required to match the data. Expressed as efficiency, performance for Chinese characters was 1.4 to 2.7 times lower than for Sloan letters. Efficiency was weakly and inversely related to perimetric complexity of optotype set. We also compared confusion matrices for human and model observers. Correlations for off-diagonal elements ranged from 0.5 to 0.8 for different sets, and the average correlation for the template model was superior to a geometrical moment model with a comparable number of parameters (Liu, Klein, Xue, Zhang, & Yu, 2009). The template model performed well overall. Estimated psychometric function slopes matched the data, and noise estimates agreed roughly with those obtained independently from contrast sensitivity to Gabor targets. For optotypes of low complexity, the model accurately predicted relative performance. This suggests the model may be used to compare acuities measured with different sets of simple optotypes. PMID:23024356
The Kuramoto model in complex networks
NASA Astrophysics Data System (ADS)
Rodrigues, Francisco A.; Peron, Thomas K. DM.; Ji, Peng; Kurths, Jürgen
2016-01-01
Synchronization of an ensemble of oscillators is an emergent phenomenon present in several complex systems, ranging from social and physical to biological and technological systems. The most successful approach to describe how coherent behavior emerges in these complex systems is given by the paradigmatic Kuramoto model. This model has been traditionally studied in complete graphs. However, besides being intrinsically dynamical, complex systems present very heterogeneous structure, which can be represented as complex networks. This report is dedicated to review main contributions in the field of synchronization in networks of Kuramoto oscillators. In particular, we provide an overview of the impact of network patterns on the local and global dynamics of coupled phase oscillators. We cover many relevant topics, which encompass a description of the most used analytical approaches and the analysis of several numerical results. Furthermore, we discuss recent developments on variations of the Kuramoto model in networks, including the presence of noise and inertia. The rich potential for applications is discussed for special fields in engineering, neuroscience, physics and Earth science. Finally, we conclude by discussing problems that remain open after the last decade of intensive research on the Kuramoto model and point out some promising directions for future research.
Modelling biological complexity: a physical scientist's perspective
Coveney, Peter V; Fowler, Philip W
2005-01-01
We discuss the modern approaches of complexity and self-organization to understanding dynamical systems and how these concepts can inform current interest in systems biology. From the perspective of a physical scientist, it is especially interesting to examine how the differing weights given to philosophies of science in the physical and biological sciences impact the application of the study of complexity. We briefly describe how the dynamics of the heart and circadian rhythms, canonical examples of systems biology, are modelled by sets of nonlinear coupled differential equations, which have to be solved numerically. A major difficulty with this approach is that all the parameters within these equations are not usually known. Coupled models that include biomolecular detail could help solve this problem. Coupling models across large ranges of length- and time-scales is central to describing complex systems and therefore to biology. Such coupling may be performed in at least two different ways, which we refer to as hierarchical and hybrid multiscale modelling. While limited progress has been made in the former case, the latter is only beginning to be addressed systematically. These modelling methods are expected to bring numerous benefits to biology, for example, the properties of a system could be studied over a wider range of length- and time-scales, a key aim of systems biology. Multiscale models couple behaviour at the molecular biological level to that at the cellular level, thereby providing a route for calculating many unknown parameters as well as investigating the effects at, for example, the cellular level, of small changes at the biomolecular level, such as a genetic mutation or the presence of a drug. The modelling and simulation of biomolecular systems is itself very computationally intensive; we describe a recently developed hybrid continuum-molecular model, HybridMD, and its associated molecular insertion algorithm, which point the way towards the
Modelling biological complexity: a physical scientist's perspective.
Coveney, Peter V; Fowler, Philip W
2005-09-22
We discuss the modern approaches of complexity and self-organization to understanding dynamical systems and how these concepts can inform current interest in systems biology. From the perspective of a physical scientist, it is especially interesting to examine how the differing weights given to philosophies of science in the physical and biological sciences impact the application of the study of complexity. We briefly describe how the dynamics of the heart and circadian rhythms, canonical examples of systems biology, are modelled by sets of nonlinear coupled differential equations, which have to be solved numerically. A major difficulty with this approach is that all the parameters within these equations are not usually known. Coupled models that include biomolecular detail could help solve this problem. Coupling models across large ranges of length- and time-scales is central to describing complex systems and therefore to biology. Such coupling may be performed in at least two different ways, which we refer to as hierarchical and hybrid multiscale modelling. While limited progress has been made in the former case, the latter is only beginning to be addressed systematically. These modelling methods are expected to bring numerous benefits to biology, for example, the properties of a system could be studied over a wider range of length- and time-scales, a key aim of systems biology. Multiscale models couple behaviour at the molecular biological level to that at the cellular level, thereby providing a route for calculating many unknown parameters as well as investigating the effects at, for example, the cellular level, of small changes at the biomolecular level, such as a genetic mutation or the presence of a drug. The modelling and simulation of biomolecular systems is itself very computationally intensive; we describe a recently developed hybrid continuum-molecular model, HybridMD, and its associated molecular insertion algorithm, which point the way towards the
How useful are complex flood damage models?
NASA Astrophysics Data System (ADS)
Schröter, Kai; Kreibich, Heidi; Vogel, Kristin; Riggelsen, Carsten; Scherbaum, Frank; Merz, Bruno
2014-04-01
We investigate the usefulness of complex flood damage models for predicting relative damage to residential buildings in a spatial and temporal transfer context. We apply eight different flood damage models to predict relative building damage for five historic flood events in two different regions of Germany. Model complexity is measured in terms of the number of explanatory variables which varies from 1 variable up to 10 variables which are singled out from 28 candidate variables. Model validation is based on empirical damage data, whereas observation uncertainty is taken into consideration. The comparison of model predictive performance shows that additional explanatory variables besides the water depth improve the predictive capability in a spatial and temporal transfer context, i.e., when the models are transferred to different regions and different flood events. Concerning the trade-off between predictive capability and reliability the model structure seem more important than the number of explanatory variables. Among the models considered, the reliability of Bayesian network-based predictions in space-time transfer is larger than for the remaining models, and the uncertainties associated with damage predictions are reflected more completely.
Intrinsic curvature hypothesis for biomembrane lipid composition: a role for nonbilayer lipids.
Gruner, S M
1985-01-01
A rationale is presented for the mix of "bilayer" and "nonbilayer" lipids, which occurs in biomembranes. A theory for the L alpha-HII phase transition and experimental tests of the theory are reviewed. It is suggested that the phase behavior is largely the result of a competition between the tendency for certain lipid monolayers to curl and the hydrocarbon packing strains that result. The tendency to curl is quantitatively given by the intrinsic radius of curvature, Ro, which minimizes the bending energy of a lipid monolayer. When bilayer (large Ro) and nonbilayer (small Ro) lipids are properly mixed, the resulting layer has a value of Ro that is at the critical edge of bilayer stability. In this case, bilayers may be destabilized by the protein-mediated introduction of hydrophobic molecules, such as dolichol. An x-ray diffraction investigation of the effect of dolichol on such a lipid mixture is described. This leads to the hypothesis that biomembranes homeostatically adjust their intrinsic curvatures to fall into an optimum range. Experimental strategies for testing the hypothesis are outlined. PMID:3858841
Modeling Electromagnetic Scattering From Complex Inhomogeneous Objects
NASA Technical Reports Server (NTRS)
Deshpande, Manohar; Reddy, C. J.
2011-01-01
This software innovation is designed to develop a mathematical formulation to estimate the electromagnetic scattering characteristics of complex, inhomogeneous objects using the finite-element-method (FEM) and method-of-moments (MoM) concepts, as well as to develop a FORTRAN code called FEMOM3DS (Finite Element Method and Method of Moments for 3-Dimensional Scattering), which will implement the steps that are described in the mathematical formulation. Very complex objects can be easily modeled, and the operator of the code is not required to know the details of electromagnetic theory to study electromagnetic scattering.
Synthetic seismograms for a complex crustal model
NASA Astrophysics Data System (ADS)
Sandmeier, K.-J.; Wenzel, F.
1986-01-01
The algorithm of the original Reflectivity Method has been vectorized and implemented on a CDC CYBER 205 computer. Calculation times are shortened by a factor of 20 to 30 compared with a general purpose computer with a capacity of several million floating point operations per second (MFLOP). The rapid calculation of synthetic seismograms for complex models, high frequency sources and all offset ranges is a provision for modeling not only particular phases but the whole observed wavefield. As an example we model refraction data of the Black Forest, Southwest Germany and are able to derive rather tight constraints on the physical properties of the lower crust.
Dual-resolution molecular dynamics simulation of antimicrobials in biomembranes
Orsi, Mario; Noro, Massimo G.; Essex, Jonathan W.
2011-01-01
Triclocarban and triclosan, two potent antibacterial molecules present in many consumer products, have been subject to growing debate on a number of issues, particularly in relation to their possible role in causing microbial resistance. In this computational study, we present molecular-level insights into the interaction between these antimicrobial agents and hydrated phospholipid bilayers (taken as a simple model for the cell membrane). Simulations are conducted by a novel ‘dual-resolution’ molecular dynamics approach which combines accuracy with efficiency: the antimicrobials, modelled atomistically, are mixed with simplified (coarse-grain) models of lipids and water. A first set of calculations is run to study the antimicrobials' transfer free energies and orientations as a function of depth inside the membrane. Both molecules are predicted to preferentially accumulate in the lipid headgroup–glycerol region; this finding, which reproduces corresponding experimental data, is also discussed in terms of a general relation between solute partitioning and the intramembrane distribution of pressure. A second set of runs involves membranes incorporated with different molar concentrations of antimicrobial molecules (up to one antimicrobial per two lipids). We study the effects induced on fundamental membrane properties, such as the electron density, lateral pressure and electrical potential profiles. In particular, the analysis of the spontaneous curvature indicates that increasing antimicrobial concentrations promote a ‘destabilizing’ tendency towards non-bilayer phases, as observed experimentally. The antimicrobials' influence on the self-assembly process is also investigated. The significance of our results in the context of current theories of antimicrobial action is discussed. PMID:21131331
Human driven transitions in complex model ecosystems
NASA Astrophysics Data System (ADS)
Harfoot, Mike; Newbold, Tim; Tittinsor, Derek; Purves, Drew
2015-04-01
Human activities have been observed to be impacting ecosystems across the globe, leading to reduced ecosystem functioning, altered trophic and biomass structure and ultimately ecosystem collapse. Previous attempts to understand global human impacts on ecosystems have usually relied on statistical models, which do not explicitly model the processes underlying the functioning of ecosystems, represent only a small proportion of organisms and do not adequately capture complex non-linear and dynamic responses of ecosystems to perturbations. We use a mechanistic ecosystem model (1), which simulates the underlying processes structuring ecosystems and can thus capture complex and dynamic interactions, to investigate boundaries of complex ecosystems to human perturbation. We explore several drivers including human appropriation of net primary production and harvesting of animal biomass. We also present an analysis of the key interactions between biotic, societal and abiotic earth system components, considering why and how we might think about these couplings. References: M. B. J. Harfoot et al., Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model., PLoS Biol. 12, e1001841 (2014).
A Practical Philosophy of Complex Climate Modelling
NASA Technical Reports Server (NTRS)
Schmidt, Gavin A.; Sherwood, Steven
2014-01-01
We give an overview of the practice of developing and using complex climate models, as seen from experiences in a major climate modelling center and through participation in the Coupled Model Intercomparison Project (CMIP).We discuss the construction and calibration of models; their evaluation, especially through use of out-of-sample tests; and their exploitation in multi-model ensembles to identify biases and make predictions. We stress that adequacy or utility of climate models is best assessed via their skill against more naive predictions. The framework we use for making inferences about reality using simulations is naturally Bayesian (in an informal sense), and has many points of contact with more familiar examples of scientific epistemology. While the use of complex simulations in science is a development that changes much in how science is done in practice, we argue that the concepts being applied fit very much into traditional practices of the scientific method, albeit those more often associated with laboratory work.
Intrinsic Uncertainties in Modeling Complex Systems.
Cooper, Curtis S; Bramson, Aaron L.; Ames, Arlo L.
2014-09-01
Models are built to understand and predict the behaviors of both natural and artificial systems. Because it is always necessary to abstract away aspects of any non-trivial system being modeled, we know models can potentially leave out important, even critical elements. This reality of the modeling enterprise forces us to consider the prospective impacts of those effects completely left out of a model - either intentionally or unconsidered. Insensitivity to new structure is an indication of diminishing returns. In this work, we represent a hypothetical unknown effect on a validated model as a finite perturba- tion whose amplitude is constrained within a control region. We find robustly that without further constraints, no meaningful bounds can be placed on the amplitude of a perturbation outside of the control region. Thus, forecasting into unsampled regions is a very risky proposition. We also present inherent difficulties with proper time discretization of models and representing in- herently discrete quantities. We point out potentially worrisome uncertainties, arising from math- ematical formulation alone, which modelers can inadvertently introduce into models of complex systems. Acknowledgements This work has been funded under early-career LDRD project #170979, entitled "Quantify- ing Confidence in Complex Systems Models Having Structural Uncertainties", which ran from 04/2013 to 09/2014. We wish to express our gratitude to the many researchers at Sandia who con- tributed ideas to this work, as well as feedback on the manuscript. In particular, we would like to mention George Barr, Alexander Outkin, Walt Beyeler, Eric Vugrin, and Laura Swiler for provid- ing invaluable advice and guidance through the course of the project. We would also like to thank Steven Kleban, Amanda Gonzales, Trevor Manzanares, and Sarah Burwell for their assistance in managing project tasks and resources.
Simulating Complex Modulated Phases Through Spin Models
NASA Astrophysics Data System (ADS)
Selinger, Jonathan V.; Lopatina, Lena M.; Geng, Jun; Selinger, Robin L. B.
2009-03-01
We extend the computational approach for studying striped phases on curved surfaces, presented in the previous talk, to two new problems involving complex modulated phases. First, we simulate a smectic liquid crystal on an arbitrary mesh by mapping the director field onto a vector spin and the density wave onto an Ising spin. We can thereby determine how the smectic phase responds to any geometrical constraints, including hybrid boundary conditions, patterned substrates, and disordered substrates. This method may provide a useful tool for designing ferroelectric liquid crystal cells. Second, we explore a model of vector spins on a flat two-dimensional (2D) lattice with long-range antiferromagnetic interactions. This model generates modulated phases with surprisingly complex structures, including 1D stripes and 2D periodic cells, which are independent of the underlying lattice. We speculate on the physical significance of these structures.
Industrial Source Complex (ISC) dispersion model. Software
Schewe, G.; Sieurin, E.
1980-01-01
The model updates various EPA dispersion model algorithms and combines them in two computer programs that can be used to assess the air quality impact of emissions from the wide variety of source types associated with an industrial source complex. The ISC Model short-term program ISCST, an updated version of the EPA Single Source (CRSTER) Model uses sequential hourly meteorological data to calculate values of average concentration or total dry deposition for time periods of 1, 2, 3, 4, 6, 8, 12 and 24 hours. Additionally, ISCST may be used to calculate 'N' is 366 days. The ISC Model long-term computer program ISCLT, a sector-averaged model that updates and combines basic features of the EPA Air Quality Display Model (AQDM) and the EPA Climatological Dispersion Model (CDM), uses STAR Summaries to calculate seasonal and/or annual average concentration or total deposition values. Both the ISCST and ISCLT programs make the same basic dispersion-model assumptions. Additionally, both the ISCST and ISCLT programs use either a polar or a Cartesian receptor grid...Software Description: The programs are written in the FORTRAN IV programming language for implementation on a UNIVAC 1110 computer and also on medium-to-large IBM or CDC systems. 65,000k words of core storage are required to operate the model.
Noncommutative complex Grosse-Wulkenhaar model
Hounkonnou, Mahouton Norbert; Samary, Dine Ousmane
2008-11-18
This paper stands for an application of the noncommutative (NC) Noether theorem, given in our previous work [AIP Proc 956(2007) 55-60], for the NC complex Grosse-Wulkenhaar model. It provides with an extension of a recent work [Physics Letters B 653(2007) 343-345]. The local conservation of energy-momentum tensors (EMTs) is recovered using improvement procedures based on Moyal algebraic techniques. Broken dilatation symmetry is discussed. NC gauge currents are also explicitly computed.
Molecular Rationale for Improved Dynamic Nuclear Polarization of Biomembranes.
Smith, Adam N; Twahir, Umar T; Dubroca, Thierry; Fanucci, Gail E; Long, Joanna R
2016-08-18
Dynamic nuclear polarization (DNP) enhanced solid-state NMR can provide orders of magnitude in signal enhancement. One of the most important aspects of obtaining efficient DNP enhancements is the optimization of the paramagnetic polarization agents used. To date, the most utilized polarization agents are nitroxide biradicals. However, the efficiency of these polarization agents is diminished when used with samples other than small molecule model compounds. We recently demonstrated the effectiveness of nitroxide labeled lipids as polarization agents for lipids and a membrane embedded peptide. Here, we systematically characterize, via electron paramagnetic (EPR), the dynamics of and the dipolar couplings between nitroxide labeled lipids under conditions relevant to DNP applications. Complemented by DNP enhanced solid-state NMR measurements at 600 MHz/395 GHz, a molecular rationale for the efficiency of nitroxide labeled lipids as DNP polarization agents is developed. Specifically, optimal DNP enhancements are obtained when the nitroxide moiety is attached to the lipid choline headgroup and local nitroxide concentrations yield an average e(-)-e(-) dipolar coupling of 47 MHz. On the basis of these measurements, we propose a framework for development of DNP polarization agents optimal for membrane protein structure determination. PMID:27434371
The noisy voter model on complex networks
NASA Astrophysics Data System (ADS)
Carro, Adrián; Toral, Raúl; San Miguel, Maxi
2016-04-01
We propose a new analytical method to study stochastic, binary-state models on complex networks. Moving beyond the usual mean-field theories, this alternative approach is based on the introduction of an annealed approximation for uncorrelated networks, allowing to deal with the network structure as parametric heterogeneity. As an illustration, we study the noisy voter model, a modification of the original voter model including random changes of state. The proposed method is able to unfold the dependence of the model not only on the mean degree (the mean-field prediction) but also on more complex averages over the degree distribution. In particular, we find that the degree heterogeneity—variance of the underlying degree distribution—has a strong influence on the location of the critical point of a noise-induced, finite-size transition occurring in the model, on the local ordering of the system, and on the functional form of its temporal correlations. Finally, we show how this latter point opens the possibility of inferring the degree heterogeneity of the underlying network by observing only the aggregate behavior of the system as a whole, an issue of interest for systems where only macroscopic, population level variables can be measured.
The noisy voter model on complex networks
Carro, Adrián; Toral, Raúl; San Miguel, Maxi
2016-01-01
We propose a new analytical method to study stochastic, binary-state models on complex networks. Moving beyond the usual mean-field theories, this alternative approach is based on the introduction of an annealed approximation for uncorrelated networks, allowing to deal with the network structure as parametric heterogeneity. As an illustration, we study the noisy voter model, a modification of the original voter model including random changes of state. The proposed method is able to unfold the dependence of the model not only on the mean degree (the mean-field prediction) but also on more complex averages over the degree distribution. In particular, we find that the degree heterogeneity—variance of the underlying degree distribution—has a strong influence on the location of the critical point of a noise-induced, finite-size transition occurring in the model, on the local ordering of the system, and on the functional form of its temporal correlations. Finally, we show how this latter point opens the possibility of inferring the degree heterogeneity of the underlying network by observing only the aggregate behavior of the system as a whole, an issue of interest for systems where only macroscopic, population level variables can be measured. PMID:27094773
The noisy voter model on complex networks.
Carro, Adrián; Toral, Raúl; San Miguel, Maxi
2016-01-01
We propose a new analytical method to study stochastic, binary-state models on complex networks. Moving beyond the usual mean-field theories, this alternative approach is based on the introduction of an annealed approximation for uncorrelated networks, allowing to deal with the network structure as parametric heterogeneity. As an illustration, we study the noisy voter model, a modification of the original voter model including random changes of state. The proposed method is able to unfold the dependence of the model not only on the mean degree (the mean-field prediction) but also on more complex averages over the degree distribution. In particular, we find that the degree heterogeneity-variance of the underlying degree distribution-has a strong influence on the location of the critical point of a noise-induced, finite-size transition occurring in the model, on the local ordering of the system, and on the functional form of its temporal correlations. Finally, we show how this latter point opens the possibility of inferring the degree heterogeneity of the underlying network by observing only the aggregate behavior of the system as a whole, an issue of interest for systems where only macroscopic, population level variables can be measured. PMID:27094773
Complexity of groundwater models in catchment hydrological models
NASA Astrophysics Data System (ADS)
Attinger, Sabine; Herold, Christian; Kumar, Rohini; Mai, Juliane; Ross, Katharina; Samaniego, Luis; Zink, Matthias
2015-04-01
In catchment hydrological models, groundwater is usually modeled very simple: it is conceptualized as a linear reservoir that gets the water from the upper unsaturated zone reservoir and releases water to the river system as baseflow. The baseflow is only a minor component of the total river flow and groundwater reservoir parameters are therefore difficult to be inversely estimated by means of river flow data only. In addition, the modelled values of the absolute height of the water filling the groundwater reservoir - in other words the groundwater levels - are of limited meaning due to coarse or no spatial resolution of groundwater and due to the fact that only river flow data are used for the calibration. The talk focuses on the question: Which complexity in terms of model complexity and model resolution is necessary to characterize groundwater processes and groundwater responses adequately in distributed catchment hydrological models? Starting from a spatially distributed catchment hydrological model with a groundwater compartment that is conceptualized as a linear reservoir we stepwise increase the groundwater model complexity and its spatial resolution to investigate which resolution, which complexity and which data are needed to reproduce baseflow and groundwater level data adequately.
Complex Constructivism: A Theoretical Model of Complexity and Cognition
ERIC Educational Resources Information Center
Doolittle, Peter E.
2014-01-01
Education has long been driven by its metaphors for teaching and learning. These metaphors have influenced both educational research and educational practice. Complexity and constructivism are two theories that provide functional and robust metaphors. Complexity provides a metaphor for the structure of myriad phenomena, while constructivism…
Describing Ecosystem Complexity through Integrated Catchment Modeling
NASA Astrophysics Data System (ADS)
Shope, C. L.; Tenhunen, J. D.; Peiffer, S.
2011-12-01
Land use and climate change have been implicated in reduced ecosystem services (ie: high quality water yield, biodiversity, and agricultural yield. The prediction of ecosystem services expected under future land use decisions and changing climate conditions has become increasingly important. Complex policy and management decisions require the integration of physical, economic, and social data over several scales to assess effects on water resources and ecology. Field-based meteorology, hydrology, soil physics, plant production, solute and sediment transport, economic, and social behavior data were measured in a South Korean catchment. A variety of models are being used to simulate plot and field scale experiments within the catchment. Results from each of the local-scale models provide identification of sensitive, local-scale parameters which are then used as inputs into a large-scale watershed model. We used the spatially distributed SWAT model to synthesize the experimental field data throughout the catchment. The approach of our study was that the range in local-scale model parameter results can be used to define the sensitivity and uncertainty in the large-scale watershed model. Further, this example shows how research can be structured for scientific results describing complex ecosystems and landscapes where cross-disciplinary linkages benefit the end result. The field-based and modeling framework described is being used to develop scenarios to examine spatial and temporal changes in land use practices and climatic effects on water quantity, water quality, and sediment transport. Development of accurate modeling scenarios requires understanding the social relationship between individual and policy driven land management practices and the value of sustainable resources to all shareholders.
Magnetic modeling of the Bushveld Igneous Complex
NASA Astrophysics Data System (ADS)
Webb, S. J.; Cole, J.; Letts, S. A.; Finn, C.; Torsvik, T. H.; Lee, M. D.
2009-12-01
Magnetic modeling of the 2.06 Ga Bushveld Complex presents special challenges due a variety of magnetic effects. These include strong remanence in the Main Zone and extremely high magnetic susceptibilities in the Upper Zone, which exhibit self-demagnetization. Recent palaeomagnetic results have resolved a long standing discrepancy between age data, which constrain the emplacement to within 1 million years, and older palaeomagnetic data which suggested ~50 million years for emplacement. The new palaeomagnetic results agree with the age data and present a single consistent pole, as opposed to a long polar wander path, for the Bushveld for all of the Zones and all of the limbs. These results also pass a fold test indicating the Bushveld Complex was emplaced horizontally lending support to arguments for connectivity. The magnetic signature of the Bushveld Complex provides an ideal mapping tool as the UZ has high susceptibility values and is well layered showing up as distinct anomalies on new high resolution magnetic data. However, this signature is similar to the highly magnetic BIFs found in the Transvaal and in the Witwatersrand Supergroups. Through careful mapping using new high resolution aeromagnetic data, we have been able to map the Bushveld UZ in complicated geological regions and identify a characteristic signature with well defined layers. The Main Zone, which has a more subdued magnetic signature, does have a strong remanent component and exhibits several magnetic reversals. The magnetic layers of the UZ contain layers of magnetitite with as much as 80-90% pure magnetite with large crystals (1-2 cm). While these layers are not strongly remanent, they have extremely high magnetic susceptibilities, and the self demagnetization effect must be taken into account when modeling these layers. Because the Bushveld Complex is so large, the geometry of the Earth’s magnetic field relative to the layers of the UZ Bushveld Complex changes orientation, creating
Structured analysis and modeling of complex systems
NASA Technical Reports Server (NTRS)
Strome, David R.; Dalrymple, Mathieu A.
1992-01-01
The Aircrew Evaluation Sustained Operations Performance (AESOP) facility at Brooks AFB, Texas, combines the realism of an operational environment with the control of a research laboratory. In recent studies we collected extensive data from the Airborne Warning and Control Systems (AWACS) Weapons Directors subjected to high and low workload Defensive Counter Air Scenarios. A critical and complex task in this environment involves committing a friendly fighter against a hostile fighter. Structured Analysis and Design techniques and computer modeling systems were applied to this task as tools for analyzing subject performance and workload. This technology is being transferred to the Man-Systems Division of NASA Johnson Space Center for application to complex mission related tasks, such as manipulating the Shuttle grappler arm.
Lab on a Biomembrane: Rapid prototyping and manipulation of 2D fluidic lipid bilayers circuits
Ainla, Alar; Gözen, Irep; Hakonen, Bodil; Jesorka, Aldo
2013-01-01
Lipid bilayer membranes are among the most ubiquitous structures in the living world, with intricate structural features and a multitude of biological functions. It is attractive to recreate these structures in the laboratory, as this allows mimicking and studying the properties of biomembranes and their constituents, and to specifically exploit the intrinsic two-dimensional fluidity. Even though diverse strategies for membrane fabrication have been reported, the development of related applications and technologies has been hindered by the unavailability of both versatile and simple methods. Here we report a rapid prototyping technology for two-dimensional fluidic devices, based on in-situ generated circuits of phospholipid films. In this “lab on a molecularly thin membrane”, various chemical and physical operations, such as writing, erasing, functionalization, and molecular transport, can be applied to user-defined regions of a membrane circuit. This concept is an enabling technology for research on molecular membranes and their technological use. PMID:24067786
The Intermediate Complexity Atmospheric Research Model
NASA Astrophysics Data System (ADS)
Gutmann, Ethan; Clark, Martyn; Rasmussen, Roy; Arnold, Jeffrey; Brekke, Levi
2015-04-01
The high-resolution, non-hydrostatic atmospheric models often used for dynamical downscaling are extremely computationally expensive, and, for a certain class of problems, their complexity hinders our ability to ask key scientific questions, particularly those related to hydrology and climate change. For changes in precipitation in particular, an atmospheric model grid spacing capable of resolving the structure of mountain ranges is of critical importance, yet such simulations can not currently be performed with an advanced regional climate model for long time periods, over large areas, and forced by many climate models. Here we present the newly developed Intermediate Complexity Atmospheric Research model (ICAR) capable of simulating critical atmospheric processes two to three orders of magnitude faster than a state of the art regional climate model. ICAR uses a simplified dynamical formulation based off of linear theory, combined with the circulation field from a low-resolution climate model. The resulting three-dimensional wind field is used to advect heat and moisture within the domain, while sub-grid physics (e.g. microphysics) are processed by standard and simplified physics schemes from the Weather Research and Forecasting (WRF) model. ICAR is tested in comparison to WRF by downscaling a climate change scenario over the Colorado Rockies. Both atmospheric models predict increases in precipitation across the domain with a greater increase on the western half. In contrast, statistically downscaled precipitation using multiple common statistical methods predict decreases in precipitation over the western half of the domain. Finally, we apply ICAR to multiple CMIP5 climate models and scenarios with multiple parameterization options to investigate the importance of uncertainty in sub-grid physics as compared to the uncertainty in the large scale climate scenario. ICAR is a useful tool for climate change and weather forecast downscaling, particularly for orographic
Interactions of a Tetrazine Derivative with Biomembrane Constituents: A Langmuir Monolayer Study.
Nakahara, Hiromichi; Hagimori, Masayori; Mukai, Takahiro; Shibata, Osamu
2016-07-01
Tetrazine (Tz) is expected to be used for bioimaging and as an analytical reagent. It is known to react very fast with trans-cyclooctene under water in organic chemistry. Here, to understand the interaction between Tz and biomembrane constituents, we first investigated the interfacial behavior of a newly synthesized Tz derivative comprising a C18-saturated hydrocarbon chain (rTz-C18) using a Langmuir monolayer spread at the air-water interface. Surface pressure (π)-molecular area (A) and surface potential (ΔV)-A isotherms were measured for monolayers of rTz-C18 and biomembrane constituents such as dipalmitoylphosphatidylcholine (DPPC), dipalmitoylphosphatidylglycerol (DPPG), dipalmitoyl phosphatidylethanolamine (DPPE), palmitoyl sphingomyelin (PSM), and cholesterol (Ch). The lateral interaction between rTz-C18 and the lipids was thermodynamically elucidated from the excess Gibbs free energy of mixing and two-dimensional phase diagram. The binary monolayers except for the Ch system indicated high miscibility or affinity. In particular, rTz-C18 was found to interact more strongly with DPPE, which is a major constituent of the inner surface of cell membranes. The phase behavior and morphology upon monolayer compression were investigated by using Brewster angle microscopy (BAM), fluorescence microscopy (FM), and atomic force microscopy (AFM). The BAM and FM images of the DPPC/rTz-C18, DPPG/rTz-C18, and PSM/rTz-C18 systems exhibited a coexistence state of two different liquid-condensed domains derived mainly from monolayers of phospholipids and phospholipids-rTz-C18. From these morphological observations, it is worthy to note that rTz-C18 is possible to interact with a limited amount of the lipids except for DPPE. PMID:27280946
Soares, Diana Gabriela; Rosseto, Hebert Luís; Basso, Fernanda Gonçalves; Scheffel, Débora Salles; Hebling, Josimeri; Costa, Carlos Alberto de Souza
2016-01-01
The development of biomaterials capable of driving dental pulp stem cell differentiation into odontoblast-like cells able to secrete reparative dentin is the goal of current conservative dentistry. In the present investigation, a biomembrane (BM) composed of a chitosan/collagen matrix embedded with calcium-aluminate microparticles was tested. The BM was produced by mixing collagen gel with a chitosan solution (2:1), and then adding bioactive calcium-aluminate cement as the mineral phase. An inert material (polystyrene) was used as the negative control. Human dental pulp cells were seeded onto the surface of certain materials, and the cytocompatibility was evaluated by cell proliferation and cell morphology, assessed after 1, 7, 14 and 28 days in culture. The odontoblastic differentiation was evaluated by measuring alkaline phosphatase (ALP) activity, total protein production, gene expression of DMP-1/DSPP and mineralized nodule deposition. The pulp cells were able to attach onto the BM surface and spread, displaying a faster proliferative rate at initial periods than that of the control cells. The BM also acted on the cells to induce more intense ALP activity, protein production at 14 days, and higher gene expression of DSPP and DMP-1 at 28 days, leading to the deposition of about five times more mineralized matrix than the cells in the control group. Therefore, the experimental biomembrane induced the differentiation of pulp cells into odontoblast-like cells featuring a highly secretory phenotype. This innovative bioactive material can drive other protocols for dental pulp exposure treatment by inducing the regeneration of dentin tissue mediated by resident cells. PMID:27119587
Lee, Tzong-Hsien; Hirst, Daniel J; Aguilar, Marie-Isabel
2015-09-01
Biomolecular-membrane interactions play a critical role in the regulation of many important biological processes such as protein trafficking, cellular signalling and ion channel formation. Peptide/protein-membrane interactions can also destabilise and damage the membrane which can lead to cell death. Characterisation of the molecular details of these binding-mediated membrane destabilisation processes is therefore central to understanding cellular events such as antimicrobial action, membrane-mediated amyloid aggregation, and apoptotic protein induced mitochondrial membrane permeabilisation. Optical biosensors have provided a unique approach to characterising membrane interactions allowing quantitation of binding events and new insight into the kinetic mechanism of these interactions. One of the most commonly used optical biosensor technologies is surface plasmon resonance (SPR) and there have been an increasing number of studies reporting the use of this technique for investigating biophysical analysis of membrane-mediated events. More recently, a number of new optical biosensors based on waveguide techniques have been developed, allowing membrane structure changes to be measured simultaneously with mass binding measurements. These techniques include dual polarisation interferometry (DPI), plasmon waveguide resonance spectroscopy (PWR) and optical waveguide light mode spectroscopy (OWLS). These techniques have expanded the application of optical biosensors to allow the analysis of membrane structure changes during peptide and protein binding. This review provides a theoretical and practical overview of the application of biosensor technology with a specific focus on DPI, PWR and OWLS to study biomembrane-mediated events and the mechanism of biomembrane disruption. This article is part of a Special Issue entitled: Lipid-protein interactions. PMID:26009270
Modeling the human prothrombinase complex components
NASA Astrophysics Data System (ADS)
Orban, Tivadar
Thrombin generation is the culminating stage of the blood coagulation process. Thrombin is obtained from prothrombin (the substrate) in a reaction catalyzed by the prothrombinase complex (the enzyme). The prothrombinase complex is composed of factor Xa (the enzyme), factor Va (the cofactor) associated in the presence of calcium ions on a negatively charged cell membrane. Factor Xa, alone, can activate prothrombin to thrombin; however, the rate of conversion is not physiologically relevant for survival. Incorporation of factor Va into prothrombinase accelerates the rate of prothrombinase activity by 300,000-fold, and provides the physiological pathway of thrombin generation. The long-term goal of the current proposal is to provide the necessary support for the advancing of studies to design potential drug candidates that may be used to avoid development of deep venous thrombosis in high-risk patients. The short-term goals of the present proposal are to (1) to propose a model of a mixed asymmetric phospholipid bilayer, (2) expand the incomplete model of human coagulation factor Va and study its interaction with the phospholipid bilayer, (3) to create a homology model of prothrombin (4) to study the dynamics of interaction between prothrombin and the phospholipid bilayer.
Membrane associated complexes in calcium dynamics modelling
NASA Astrophysics Data System (ADS)
Szopa, Piotr; Dyzma, Michał; Kaźmierczak, Bogdan
2013-06-01
Mitochondria not only govern energy production, but are also involved in crucial cellular signalling processes. They are one of the most important organelles determining the Ca2+ regulatory pathway in the cell. Several mathematical models explaining these mechanisms were constructed, but only few of them describe interplay between calcium concentrations in endoplasmic reticulum (ER), cytoplasm and mitochondria. Experiments measuring calcium concentrations in mitochondria and ER suggested the existence of cytosolic microdomains with locally elevated calcium concentration in the nearest vicinity of the outer mitochondrial membrane. These intermediate physical connections between ER and mitochondria are called MAM (mitochondria-associated ER membrane) complexes. We propose a model with a direct calcium flow from ER to mitochondria, which may be justified by the existence of MAMs, and perform detailed numerical analysis of the effect of this flow on the type and shape of calcium oscillations. The model is partially based on the Marhl et al model. We have numerically found that the stable oscillations exist for a considerable set of parameter values. However, for some parameter sets the oscillations disappear and the trajectories of the model tend to a steady state with very high calcium level in mitochondria. This can be interpreted as an early step in an apoptotic pathway.
Wind modelling over complex terrain using CFD
NASA Astrophysics Data System (ADS)
Avila, Matias; Owen, Herbert; Folch, Arnau; Prieto, Luis; Cosculluela, Luis
2015-04-01
The present work deals with the numerical CFD modelling of onshore wind farms in the context of High Performance Computing (HPC). The CFD model involves the numerical solution of the Reynolds-Averaged Navier-Stokes (RANS) equations together with a κ-É turbulence model and the energy equation, specially designed for Atmospheric Boundary Layer (ABL) flows. The aim is to predict the wind velocity distribution over complex terrain, using a model that includes meteorological data assimilation, thermal coupling, forested canopy and Coriolis effects. The modelling strategy involves automatic mesh generation, terrain data assimilation and generation of boundary conditions for the inflow wind flow distribution up to the geostrophic height. The CFD model has been implemented in Alya, a HPC multi physics parallel solver able to run with thousands of processors with an optimal scalability, developed in Barcelona Supercomputing Center. The implemented thermal stability and canopy physical model was developed by Sogachev in 2012. The k-É equations are of non-linear convection diffusion reaction type. The implemented numerical scheme consists on a stabilized finite element formulation based on the variational multiscale method, that is known to be stable for this kind of turbulence equations. We present a numerical formulation that stresses on the robustness of the solution method, tackling common problems that produce instability. The iterative strategy and linearization scheme is discussed. It intends to avoid the possibility of having negative values of diffusion during the iterative process, which may lead to divergence of the scheme. These problems are addressed by acting on the coefficients of the reaction and diffusion terms and on the turbulent variables themselves. The k-É equations are highly nonlinear. Complex terrain induces transient flow instabilities that may preclude the convergence of computer flow simulations based on steady state formulation of the
Modeling the relational complexities of symptoms.
Dolin, R H
1994-12-01
Realization of the value of reliable codified medical data is growing at a rapid rate. Symptom data in particular have been shown to be useful in decision analysis and in the determination of patient outcomes. Electronic medical record systems are emerging, and attempts are underway to define the structure and content of these systems to support the storage of all medical data. The underlying models upon which these systems are being built continue to be strengthened by a deeper understanding of the complex information they are to store. This report analyzes symptoms as they might be recorded in free text notes and presents a high-level conceptual data model representation of this domain. PMID:7869941
Inexpensive Complex Hand Model Twenty Years Later.
Frenger, Paul
2015-01-01
Twenty years ago the author unveiled his inexpensive complex hand model, which reproduced every motion of the human hand. A control system programmed in the Forth language operated its actuators and sensors. Follow-on papers for this popular project were next presented in Texas, Canada and Germany. From this hand grew the authors meter-tall robot (nicknamed ANNIE: Android With Neural Networks, Intellect and Emotions). It received machine vision, facial expressiveness, speech synthesis and speech recognition; a simian version also received a dexterous ape foot. New artificial intelligence features included op-amp neurons for OCR and simulated emotions, hormone emulation, endocannabinoid receptors, fear-trust-love mechanisms, a Grandmother Cell recognizer and artificial consciousness. Simulated illnesses included narcotic addiction, autism, PTSD, fibromyalgia and Alzheimers disease. The author gave 13 robotics-AI presentations at NASA in Houston since 2006. A meter-tall simian robot was proposed with gripping hand-feet for use with space vehicles and to explore distant planets and moons. Also proposed were: intelligent motorized exoskeletons for astronaut force multiplication; a cognitive prosthesis to detect and alleviate decreased crew mental performance; and a gynoid robot medic to tend astronauts in deep space missions. What began as a complex hand model evolved into an innovative robot-AI within two decades. PMID:25996742
Complex Educational Design: A Course Design Model Based on Complexity
ERIC Educational Resources Information Center
Freire, Maximina Maria
2013-01-01
Purpose: This article aims at presenting a conceptual framework which, theoretically grounded on complexity, provides the basis to conceive of online language courses that intend to respond to the needs of students and society. Design/methodology/approach: This paper is introduced by reflections on distance education and on the paradigmatic view…
Using Perspective to Model Complex Processes
Kelsey, R.L.; Bisset, K.R.
1999-04-04
The notion of perspective, when supported in an object-based knowledge representation, can facilitate better abstractions of reality for modeling and simulation. The object modeling of complex physical and chemical processes is made more difficult in part due to the poor abstractions of state and phase changes available in these models. The notion of perspective can be used to create different views to represent the different states of matter in a process. These techniques can lead to a more understandable model. Additionally, the ability to record the progress of a process from start to finish is problematic. It is desirable to have a historic record of the entire process, not just the end result of the process. A historic record should facilitate backtracking and re-start of a process at different points in time. The same representation structures and techniques can be used to create a sequence of process markers to represent a historic record. By using perspective, the sequence of markers can have multiple and varying views tailored for a particular user's context of interest.
Ants (Formicidae): models for social complexity.
Smith, Chris R; Dolezal, Adam; Eliyahu, Dorit; Holbrook, C Tate; Gadau, Jürgen
2009-07-01
The family Formicidae (ants) is composed of more than 12,000 described species that vary greatly in size, morphology, behavior, life history, ecology, and social organization. Ants occur in most terrestrial habitats and are the dominant animals in many of them. They have been used as models to address fundamental questions in ecology, evolution, behavior, and development. The literature on ants is extensive, and the natural history of many species is known in detail. Phylogenetic relationships for the family, as well as within many subfamilies, are known, enabling comparative studies. Their ease of sampling and ecological variation makes them attractive for studying populations and questions relating to communities. Their sociality and variation in social organization have contributed greatly to an understanding of complex systems, division of labor, and chemical communication. Ants occur in colonies composed of tens to millions of individuals that vary greatly in morphology, physiology, and behavior; this variation has been used to address proximate and ultimate mechanisms generating phenotypic plasticity. Relatedness asymmetries within colonies have been fundamental to the formulation and empirical testing of kin and group selection theories. Genomic resources have been developed for some species, and a whole-genome sequence for several species is likely to follow in the near future; comparative genomics in ants should provide new insights into the evolution of complexity and sociogenomics. Future studies using ants should help establish a more comprehensive understanding of social life, from molecules to colonies. PMID:20147200
Physical modelling of the nuclear pore complex
Fassati, Ariberto; Ford, Ian J.; Hoogenboom, Bart W.
2013-01-01
Physically interesting behaviour can arise when soft matter is confined to nanoscale dimensions. A highly relevant biological example of such a phenomenon is the Nuclear Pore Complex (NPC) found perforating the nuclear envelope of eukaryotic cells. In the central conduit of the NPC, of ∼30–60 nm diameter, a disordered network of proteins regulates all macromolecular transport between the nucleus and the cytoplasm. In spite of a wealth of experimental data, the selectivity barrier of the NPC has yet to be explained fully. Experimental and theoretical approaches are complicated by the disordered and heterogeneous nature of the NPC conduit. Modelling approaches have focused on the behaviour of the partially unfolded protein domains in the confined geometry of the NPC conduit, and have demonstrated that within the range of parameters thought relevant for the NPC, widely varying behaviour can be observed. In this review, we summarise recent efforts to physically model the NPC barrier and function. We illustrate how attempts to understand NPC barrier function have employed many different modelling techniques, each of which have contributed to our understanding of the NPC.
Reducing Spatial Data Complexity for Classification Models
Ruta, Dymitr; Gabrys, Bogdan
2007-11-29
Intelligent data analytics gradually becomes a day-to-day reality of today's businesses. However, despite rapidly increasing storage and computational power current state-of-the-art predictive models still can not handle massive and noisy corporate data warehouses. What is more adaptive and real-time operational environment requires multiple models to be frequently retrained which further hinders their use. Various data reduction techniques ranging from data sampling up to density retention models attempt to address this challenge by capturing a summarised data structure, yet they either do not account for labelled data or degrade the classification performance of the model trained on the condensed dataset. Our response is a proposition of a new general framework for reducing the complexity of labelled data by means of controlled spatial redistribution of class densities in the input space. On the example of Parzen Labelled Data Compressor (PLDC) we demonstrate a simulatory data condensation process directly inspired by the electrostatic field interaction where the data are moved and merged following the attracting and repelling interactions with the other labelled data. The process is controlled by the class density function built on the original data that acts as a class-sensitive potential field ensuring preservation of the original class density distributions, yet allowing data to rearrange and merge joining together their soft class partitions. As a result we achieved a model that reduces the labelled datasets much further than any competitive approaches yet with the maximum retention of the original class densities and hence the classification performance. PLDC leaves the reduced dataset with the soft accumulative class weights allowing for efficient online updates and as shown in a series of experiments if coupled with Parzen Density Classifier (PDC) significantly outperforms competitive data condensation methods in terms of classification performance at the
Reducing Spatial Data Complexity for Classification Models
NASA Astrophysics Data System (ADS)
Ruta, Dymitr; Gabrys, Bogdan
2007-11-01
Intelligent data analytics gradually becomes a day-to-day reality of today's businesses. However, despite rapidly increasing storage and computational power current state-of-the-art predictive models still can not handle massive and noisy corporate data warehouses. What is more adaptive and real-time operational environment requires multiple models to be frequently retrained which further hinders their use. Various data reduction techniques ranging from data sampling up to density retention models attempt to address this challenge by capturing a summarised data structure, yet they either do not account for labelled data or degrade the classification performance of the model trained on the condensed dataset. Our response is a proposition of a new general framework for reducing the complexity of labelled data by means of controlled spatial redistribution of class densities in the input space. On the example of Parzen Labelled Data Compressor (PLDC) we demonstrate a simulatory data condensation process directly inspired by the electrostatic field interaction where the data are moved and merged following the attracting and repelling interactions with the other labelled data. The process is controlled by the class density function built on the original data that acts as a class-sensitive potential field ensuring preservation of the original class density distributions, yet allowing data to rearrange and merge joining together their soft class partitions. As a result we achieved a model that reduces the labelled datasets much further than any competitive approaches yet with the maximum retention of the original class densities and hence the classification performance. PLDC leaves the reduced dataset with the soft accumulative class weights allowing for efficient online updates and as shown in a series of experiments if coupled with Parzen Density Classifier (PDC) significantly outperforms competitive data condensation methods in terms of classification performance at the
40 CFR 80.45 - Complex emissions model.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 40 Protection of Environment 17 2012-07-01 2012-07-01 false Complex emissions model. 80.45 Section...) REGULATION OF FUELS AND FUEL ADDITIVES Reformulated Gasoline § 80.45 Complex emissions model. (a) Definition... fuel which is being evaluated for its emissions performance using the complex model OXY =...
Comparison of Two Pasture Growth Models of Differing Complexity
Technology Transfer Automated Retrieval System (TEKTRAN)
Two pasture growth models that share many common features but differ in model complexity have been developed for incorporation into the Integrated Farm System Model (IFSM). Major differences between models include the explicit representation of roots in the more complex model, and their effects on c...
Koynova, Rumiana; MacDonald, Robert C.
2010-01-18
A viewpoint now emerging is that a critical factor in lipid-mediated transfection (lipofection) is the structural evolution of lipoplexes upon interacting and mixing with cellular lipids. Here we report our finding that lipid mixtures mimicking biomembrane lipid compositions are superior to pure anionic liposomes in their ability to release DNA from lipoplexes (cationic lipid/DNA complexes), even though they have a much lower negative charge density (and thus lower capacity to neutralize the positive charge of the lipoplex lipids). Flow fluorometry revealed that the portion of DNA released after a 30-min incubation of the cationic O-ethylphosphatidylcholine lipoplexes with the anionic phosphatidylserine or phosphatidylglycerol was 19% and 37%, respectively, whereas a mixture mimicking biomembranes (MM: phosphatidylcholine/phosphatidylethanolamine/phosphatidylserine /cholesterol 45:20:20:15 w/w) and polar lipid extract from bovine liver released 62% and 74%, respectively, of the DNA content. A possible reason for this superior power in releasing DNA by the natural lipid mixtures was suggested by structural experiments: while pure anionic lipids typically form lamellae, the natural lipid mixtures exhibited a surprising predilection to form nonlamellar phases. Thus, the MM mixture arranged into lamellar arrays at physiological temperature, but began to convert to the hexagonal phase at a slightly higher temperature, {approx} 40-45 C. A propensity to form nonlamellar phases (hexagonal, cubic, micellar) at close to physiological temperatures was also found with the lipid extracts from natural tissues (from bovine liver, brain, and heart). This result reveals that electrostatic interactions are only one of the factors involved in lipid-mediated DNA delivery. The tendency of lipid bilayers to form nonlamellar phases has been described in terms of bilayer 'frustration' which imposes a nonzero intrinsic curvature of the two opposing monolayers. Because the stored curvature
Analytical models for complex swirling flows
NASA Astrophysics Data System (ADS)
Borissov, A.; Hussain, V.
1996-11-01
We develops a new class of analytical solutions of the Navier-Stokes equations for swirling flows, and suggests ways to predict and control such flows occurring in various technological applications. We view momentum accumulation on the axis as a key feature of swirling flows and consider vortex-sink flows on curved axisymmetric surfaces with an axial flow. We show that these solutions model swirling flows in a cylindrical can, whirlpools, tornadoes, and cosmic swirling jets. The singularity of these solutions on the flow axis is removed by matching them with near-axis Schlichting and Long's swirling jets. The matched solutions model flows with very complex patterns, consisting of up to seven separation regions with recirculatory 'bubbles' and vortex rings. We apply the matched solutions for computing flows in the Ranque-Hilsch tube, in the meniscus of electrosprays, in vortex breakdown, and in an industrial vortex burner. The simple analytical solutions allow a clear understanding of how different control parameters affect the flow and guide selection of optimal parameter values for desired flow features. These solutions permit extension to other problems (such as heat transfer and chemical reaction) and have the potential of being significantly useful for further detailed investigation by direct or large-eddy numerical simulations as well as laboratory experimentation.
Discrete Element Modeling of Complex Granular Flows
NASA Astrophysics Data System (ADS)
Movshovitz, N.; Asphaug, E. I.
2010-12-01
Granular materials occur almost everywhere in nature, and are actively studied in many fields of research, from food industry to planetary science. One approach to the study of granular media, the continuum approach, attempts to find a constitutive law that determines the material's flow, or strain, under applied stress. The main difficulty with this approach is that granular systems exhibit different behavior under different conditions, behaving at times as an elastic solid (e.g. pile of sand), at times as a viscous fluid (e.g. when poured), or even as a gas (e.g. when shaken). Even if all these physics are accounted for, numerical implementation is made difficult by the wide and often discontinuous ranges in continuum density and sound speed. A different approach is Discrete Element Modeling (DEM). Here the goal is to directly model every grain in the system as a rigid body subject to various body and surface forces. The advantage of this method is that it treats all of the above regimes in the same way, and can easily deal with a system moving back and forth between regimes. But as a granular system typically contains a multitude of individual grains, the direct integration of the system can be very computationally expensive. For this reason most DEM codes are limited to spherical grains of uniform size. However, spherical grains often cannot replicate the behavior of real world granular systems. A simple pile of spherical grains, for example, relies on static friction alone to keep its shape, while in reality a pile of irregular grains can maintain a much steeper angle by interlocking force chains. In the present study we employ a commercial DEM, nVidia's PhysX Engine, originally designed for the game and animation industry, to simulate complex granular flows with irregular, non-spherical grains. This engine runs as a multi threaded process and can be GPU accelerated. We demonstrate the code's ability to physically model granular materials in the three regimes
Modeling competitive substitution in a polyelectrolyte complex
Peng, B.; Muthukumar, M.
2015-12-28
We have simulated the invasion of a polyelectrolyte complex made of a polycation chain and a polyanion chain, by another longer polyanion chain, using the coarse-grained united atom model for the chains and the Langevin dynamics methodology. Our simulations reveal many intricate details of the substitution reaction in terms of conformational changes of the chains and competition between the invading chain and the chain being displaced for the common complementary chain. We show that the invading chain is required to be sufficiently longer than the chain being displaced for effecting the substitution. Yet, having the invading chain to be longer than a certain threshold value does not reduce the substitution time much further. While most of the simulations were carried out in salt-free conditions, we show that presence of salt facilitates the substitution reaction and reduces the substitution time. Analysis of our data shows that the dominant driving force for the substitution process involving polyelectrolytes lies in the release of counterions during the substitution.
Drvenica, Ivana T; Bukara, Katarina M; Ilić, Vesna Lj; Mišić, Danijela M; Vasić, Borislav Z; Gajić, Radoš B; Đorđević, Verica B; Veljović, Đorđe N; Belić, Aleksandar; Bugarski, Branko M
2016-07-01
The present study investigated preparation of bovine and porcine erythrocyte membranes from slaughterhouse blood as bio-derived materials for delivery of dexamethasone-sodium phosphate (DexP). The obtained biomembranes, i.e., ghosts were characterized in vitro in terms of morphological properties, loading parameters, and release behavior. For the last two, an UHPLC/-HESI-MS/MS based analytical procedure for absolute drug identification and quantification was developed. The results revealed that loading of DexP into both type of ghosts was directly proportional to the increase of drug concentration in the incubation medium, while incubation at 37°C had statistically significant effect on loaded amount of DexP (P < 0.05). The encapsulation efficiency was about fivefold higher in porcine compared to bovine ghosts. Insight into ghosts' surface morphology by field emission-scanning electron microscopy and atomic force microscopy confirmed that besides inevitable effects of osmosis, DexP inclusion itself had no observable additional effect on the morphology of the ghosts carriers. DexP release profiles were dependent on erythrocyte ghost type and amount of residual hemoglobin. However, sustained DexP release was achieved and shown over 3 days from porcine ghosts and 5 days from bovine erythrocyte ghosts. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1046-1055, 2016. PMID:27254304
Biomembrane-mimicking lipid bilayer system as a mechanically tunable cell substrate
Lin, C. Y.; Auernheimer, V.; Naumann, C.; Goldmann, W. H.; Fabry, B.
2014-01-01
Cell behavior such as cell adhesion, spreading, and contraction critically depends on the elastic properties of the extracellular matrix. It is not known, however, how cells respond to viscoelastic or plastic material properties that more closely resemble the mechanical environment that cells encounter in the body. In this report, we employ viscoelastic and plastic biomembrane-mimicking cell substrates. The compliance of the substrates can be tuned by increasing the number of polymer-tethered bilayers. This leaves the density and conformation of adhesive ligands on the top bilayer unaltered. We then observe the response of fibroblasts to these property changes. For comparison, we also study the cells on soft polyacrylamide and hard glass surfaces. Cell morphology, motility, cell stiffness, contractile forces and adhesive contact size all decrease on more compliant matrices but are less sensitive to changes in matrix dissipative properties. These data suggest that cells are able to feel and respond predominantly to the effective matrix compliance, which arises as a combination of substrate and adhesive ligand mechanical properties. PMID:24439398
Monzel, Cornelia; Schmidt, Daniel; Seifert, Udo; Smith, Ana-Sunčana; Merkel, Rudolf; Sengupta, Kheya
2016-05-25
We probe the bending fluctuations of bio-membranes using highly deflated giant unilamellar vesicles (GUVs) bound to a substrate by a weak potential arising from generic interactions. The substrate is either homogeneous, with GUVs bound only by the weak potential, or is chemically functionalized with a micro-pattern of very strong specific binders. In both cases, the weakly adhered membrane is seen to be confined at a well-defined distance above the surface while it continues to fluctuate strongly. We quantify the fluctuations of the weakly confined membrane at the substrate proximal surface as well as of the free membrane at the distal surface of the same GUV. This strategy enables us to probe in detail the damping of fluctuations in the presence of the substrate, and to independently measure the membrane tension and the strength of the generic interaction potential. Measurements were done using two complementary techniques - dynamic optical displacement spectroscopy (DODS, resolution: 20 nm, 10 μs), and dual wavelength reflection interference contrast microscopy (DW-RICM, resolution: 4 nm, 50 ms). After accounting for the spatio-temporal resolution of the techniques, an excellent agreement between the two measurements was obtained. For both weakly confined systems we explore in detail the link between fluctuations on the one hand and membrane tension and the interaction potential on the other hand. PMID:27142463
Wang, Tianshu; Liu, Jiyang; Ren, Jiangtao; Wang, Jin; Wang, Erkang
2015-10-01
A hybrid composite constructed of phospholipids bilayer membrane, gold nanoparticles and graphene was prepared and used as matrices for microperoxidase-11 (MP11) immobilization. The direct electrochemistry and corresponding bioelectrocatalysis of the enzyme electrode was further investigated. Phospholipid bilayer membrane protected gold nanoparticles (AuNPs) were assembled on polyelectrolyte functionalized graphene sheets through electrostatic attraction to form a hybrid bionanocomposite. Owing to the biocompatible microenvironment provided by the mimetic biomembrane, microperoxidase-11 entrapped in this matrix well retained its native structure and exhibited high bioactivity. Moreover, the AuNPs-graphene assemblies could efficiently promote the direct electron transfer between the immobilized MP11 and the substrate electrode. The as-prepared enzyme electrode presented good direct electrochemistry and electrocatalytic responses to the reduction of hydrogen peroxide (H2O2). The resulting H2O2 biosensor showed a wide linear range (2.0×10(-5)-2.8×10(-4) M), a low detection limit (2.6×10(-6) M), good reproducibility and stability. Furthermore, this sensor was used for real-time detection of H2O2 dynamically released from the tumor cells MCF-7 in response to a pro-inflammatory stimulant. PMID:26078181
Wound healing modulation by a latex protein-containing polyvinyl alcohol biomembrane.
Ramos, Márcio V; de Alencar, Nylane Maria N; de Oliveira, Raquel S B; Freitas, Lyara B N; Aragão, Karoline S; de Andrade, Thiago Antônio M; Frade, Marco Andrey C; Brito, Gerly Anne C; de Figueiredo, Ingrid Samantha T
2016-07-01
In a previous study, we performed the chemical characterization of a polyvinyl alcohol (PVA) membrane supplemented with latex proteins (LP) displaying wound healing activity, and its efficacy as a delivery system was demonstrated. Here, we report on aspects of the mechanism underlying the performance of the PVA-latex protein biomembrane on wound healing. LP-PVA, but not PVA, induced more intense leukocyte (neutrophil) migration and mast cell degranulation during the inflammatory phase of the cicatricial process. Likewise, LP-PVA induced an increase in key markers and mediators of the inflammatory response (myeloperoxidase activity, nitric oxide, TNF, and IL-1β). These results demonstrated that LP-PVA significantly accelerates the early phase of the inflammatory process by upregulating cytokine release. This remarkable effect improves the subsequent phases of the healing process. The polyvinyl alcohol membrane was fully absorbed as an inert support while LP was shown to be active. It is therefore concluded that the LP-PVA is a suitable bioresource for biomedical engineering. PMID:27037828
Vanegas, Juan M; Torres-Sánchez, Alejandro; Arroyo, Marino
2014-02-11
Local stress fields are routinely computed from molecular dynamics trajectories to understand the structure and mechanical properties of lipid bilayers. These calculations can be systematically understood with the Irving-Kirkwood-Noll theory. In identifying the stress tensor, a crucial step is the decomposition of the forces on the particles into pairwise contributions. However, such a decomposition is not unique in general, leading to an ambiguity in the definition of the stress tensor, particularly for multibody potentials. Furthermore, a theoretical treatment of constraints in local stress calculations has been lacking. Here, we present a new implementation of local stress calculations that systematically treats constraints and considers a privileged decomposition, the central force decomposition, that leads to a symmetric stress tensor by construction. We focus on biomembranes, although the methodology presented here is widely applicable. Our results show that some unphysical behavior obtained with previous implementations (e.g. nonconstant normal stress profiles along an isotropic bilayer in equilibrium) is a consequence of an improper treatment of constraints. Furthermore, other valid force decompositions produce significantly different stress profiles, particularly in the presence of dihedral potentials. Our methodology reveals the striking effect of unsaturations on the bilayer mechanics, missed by previous stress calculation implementations. PMID:26580046
Clinical complexity in medicine: A measurement model of task and patient complexity
Islam, R.; Weir, C.; Fiol, G. Del
2016-01-01
Summary Background Complexity in medicine needs to be reduced to simple components in a way that is comprehensible to researchers and clinicians. Few studies in the current literature propose a measurement model that addresses both task and patient complexity in medicine. Objective The objective of this paper is to develop an integrated approach to understand and measure clinical complexity by incorporating both task and patient complexity components focusing on infectious disease domain. The measurement model was adapted and modified to healthcare domain. Methods Three clinical Infectious Disease teams were observed, audio-recorded and transcribed. Each team included an Infectious Diseases expert, one Infectious Diseases fellow, one physician assistant and one pharmacy resident fellow. The transcripts were parsed and the authors independently coded complexity attributes. This baseline measurement model of clinical complexity was modified in an initial set of coding process and further validated in a consensus-based iterative process that included several meetings and email discussions by three clinical experts from diverse backgrounds from the Department of Biomedical Informatics at the University of Utah. Inter-rater reliability was calculated using Cohen’s kappa. Results The proposed clinical complexity model consists of two separate components. The first is a clinical task complexity model with 13 clinical complexity-contributing factors and 7 dimensions. The second is the patient complexity model with 11 complexity-contributing factors and 5 dimensions. Conclusion The measurement model for complexity encompassing both task and patient complexity will be a valuable resource for future researchers and industry to measure and understand complexity in healthcare. PMID:26404626
Power Curve Modeling in Complex Terrain Using Statistical Models
NASA Astrophysics Data System (ADS)
Bulaevskaya, V.; Wharton, S.; Clifton, A.; Qualley, G.; Miller, W.
2014-12-01
Traditional power output curves typically model power only as a function of the wind speed at the turbine hub height. While the latter is an essential predictor of power output, wind speed information in other parts of the vertical profile, as well as additional atmospheric variables, are also important determinants of power. The goal of this work was to determine the gain in predictive ability afforded by adding wind speed information at other heights, as well as other atmospheric variables, to the power prediction model. Using data from a wind farm with a moderately complex terrain in the Altamont Pass region in California, we trained three statistical models, a neural network, a random forest and a Gaussian process model, to predict power output from various sets of aforementioned predictors. The comparison of these predictions to the observed power data revealed that considerable improvements in prediction accuracy can be achieved both through the addition of predictors other than the hub-height wind speed and the use of statistical models. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344 and was funded by Wind Uncertainty Quantification Laboratory Directed Research and Development Project at LLNL under project tracking code 12-ERD-069.
Spatiotemporal Organization of Spin-Coated Supported Model Membranes
NASA Astrophysics Data System (ADS)
Simonsen, Adam Cohen
All cells of living organisms are separated from their surroundings and organized internally by means of flexible lipid membranes. In fact, there is consensus that the minimal requirements for self-replicating life processes include the following three features: (1) information carriers (DNA, RNA), (2) a metabolic system, and (3) encapsulation in a container structure [1]. Therefore, encapsulation can be regarded as an essential part of life itself. In nature, membranes are highly diverse interfacial structures that compartmentalize cells [2]. While prokaryotic cells only have an outer plasma membrane and a less-well-developed internal membrane structure, eukaryotic cells have a number of internal membranes associated with the organelles and the nucleus. Many of these membrane structures, including the plasma membrane, are complex layered systems, but with the basic structure of a lipid bilayer. Biomembranes contain hundreds of different lipid species in addition to embedded or peripherally associated membrane proteins and connections to scaffolds such as the cytoskeleton. In vitro, lipid bilayers are spontaneously self-organized structures formed by a large group of amphiphilic lipid molecules in aqueous suspensions. Bilayer formation is driven by the entropic properties of the hydrogen bond network in water in combination with the amphiphilic nature of the lipids. The molecular shapes of the lipid constituents play a crucial role in bilayer formation, and only lipids with approximately cylindrical shapes are able to form extended bilayers. The bilayer structure of biomembranes was discovered by Gorter and Grendel in 1925 [3] using monolayer studies of lipid extracts from red blood cells. Later, a number of conceptual models were developed to rationalize the organization of lipids and proteins in biological membranes. One of the most celebrated is the fluid-mosaic model by Singer and Nicolson (1972) [4]. According to this model, the lipid bilayer component of
APPLICATION OF SURFACE COMPLEXATION MODELS TO SOIL SYSTEMS
Technology Transfer Automated Retrieval System (TEKTRAN)
Chemical surface complexation models were developed to describe potentiometric titration and ion adsorption data on oxide minerals. These models provide molecular descriptions of adsorption using an equilibrium approach that defines surface species, chemical reactions, mass and charge balances and ...
Modeling Complex Workflow in Molecular Diagnostics
Gomah, Mohamed E.; Turley, James P.; Lu, Huimin; Jones, Dan
2010-01-01
One of the hurdles to achieving personalized medicine has been implementing the laboratory processes for performing and reporting complex molecular tests. The rapidly changing test rosters and complex analysis platforms in molecular diagnostics have meant that many clinical laboratories still use labor-intensive manual processing and testing without the level of automation seen in high-volume chemistry and hematology testing. We provide here a discussion of design requirements and the results of implementation of a suite of lab management tools that incorporate the many elements required for use of molecular diagnostics in personalized medicine, particularly in cancer. These applications provide the functionality required for sample accessioning and tracking, material generation, and testing that are particular to the evolving needs of individualized molecular diagnostics. On implementation, the applications described here resulted in improvements in the turn-around time for reporting of more complex molecular test sets, and significant changes in the workflow. Therefore, careful mapping of workflow can permit design of software applications that simplify even the complex demands of specialized molecular testing. By incorporating design features for order review, software tools can permit a more personalized approach to sample handling and test selection without compromising efficiency. PMID:20007844
Specifying and Refining a Complex Measurement Model.
ERIC Educational Resources Information Center
Levy, Roy; Mislevy, Robert J.
This paper aims to describe a Bayesian approach to modeling and estimating cognitive models both in terms of statistical machinery and actual instrument development. Such a method taps the knowledge of experts to provide initial estimates for the probabilistic relationships among the variables in a multivariate latent variable model and refines…
Dispersion Modeling in Complex Urban Systems
Models are used to represent real systems in an understandable way. They take many forms. A conceptual model explains the way a system works. In environmental studies, for example, a conceptual model may delineate all the factors and parameters for determining how a particle move...
Turbulence modeling for complex hypersonic flows
NASA Technical Reports Server (NTRS)
Huang, P. G.; Coakley, T. J.
1993-01-01
The paper presents results of calculations for a range of 2D turbulent hypersonic flows using two-equation models. The baseline models and the model corrections required for good hypersonic-flow predictions will be illustrated. Three experimental data sets were chosen for comparison. They are: (1) the hypersonic flare flows of Kussoy and Horstman, (2) a 2D hypersonic compression corner flow of Coleman and Stollery, and (3) the ogive-cylinder impinging shock-expansion flows of Kussoy and Horstman. Comparisons with the experimental data have shown that baseline models under-predict the extent of flow separation but over-predict the heat transfer rate near flow reattachment. Modifications to the models are described which remove the above-mentioned deficiencies. Although we have restricted the discussion only to the selected baseline models in this paper, the modifications proposed are universal and can in principle be transferred to any existing two-equation model formulation.
Studying complex chemistries using PLASIMO's global model
NASA Astrophysics Data System (ADS)
Koelman, PMJ; Tadayon Mousavi, S.; Perillo, R.; Graef, WAAD; Mihailova, DB; van Dijk, J.
2016-02-01
The Plasimo simulation software is used to construct a Global Model of a CO2 plasma. A DBD plasma between two coaxial cylinders is considered, which is driven by a triangular input power pulse. The plasma chemistry is studied during this power pulse and in the afterglow. The model consists of 71 species that interact in 3500 reactions. Preliminary results from the model are presented. The model has been validated by comparing its results with those presented in Kozák et al. (Plasma Sources Science and Technology 23(4) p. 045004, 2014). A good qualitative agreement has been reached; potential sources of remaining discrepancies are extensively discussed.
Multiscale Computational Models of Complex Biological Systems
Walpole, Joseph; Papin, Jason A.; Peirce, Shayn M.
2014-01-01
Integration of data across spatial, temporal, and functional scales is a primary focus of biomedical engineering efforts. The advent of powerful computing platforms, coupled with quantitative data from high-throughput experimental platforms, has allowed multiscale modeling to expand as a means to more comprehensively investigate biological phenomena in experimentally relevant ways. This review aims to highlight recently published multiscale models of biological systems while using their successes to propose the best practices for future model development. We demonstrate that coupling continuous and discrete systems best captures biological information across spatial scales by selecting modeling techniques that are suited to the task. Further, we suggest how to best leverage these multiscale models to gain insight into biological systems using quantitative, biomedical engineering methods to analyze data in non-intuitive ways. These topics are discussed with a focus on the future of the field, the current challenges encountered, and opportunities yet to be realized. PMID:23642247
Information, complexity and efficiency: The automobile model
Allenby, B. |
1996-08-08
The new, rapidly evolving field of industrial ecology - the objective, multidisciplinary study of industrial and economic systems and their linkages with fundamental natural systems - provides strong ground for believing that a more environmentally and economically efficient economy will be more information intensive and complex. Information and intellectual capital will be substituted for the more traditional inputs of materials and energy in producing a desirable, yet sustainable, quality of life. While at this point this remains a strong hypothesis, the evolution of the automobile industry can be used to illustrate how such substitution may, in fact, already be occurring in an environmentally and economically critical sector.
Sensitivity Analysis in Complex Plasma Chemistry Models
NASA Astrophysics Data System (ADS)
Turner, Miles
2015-09-01
The purpose of a plasma chemistry model is prediction of chemical species densities, including understanding the mechanisms by which such species are formed. These aims are compromised by an uncertain knowledge of the rate constants included in the model, which directly causes uncertainty in the model predictions. We recently showed that this predictive uncertainty can be large--a factor of ten or more in some cases. There is probably no context in which a plasma chemistry model might be used where the existence of uncertainty on this scale could not be a matter of concern. A question that at once follows is: Which rate constants cause such uncertainty? In the present paper we show how this question can be answered by applying a systematic screening procedure--the so-called Morris method--to identify sensitive rate constants. We investigate the topical example of the helium-oxygen chemistry. Beginning with a model with almost four hundred reactions, we show that only about fifty rate constants materially affect the model results, and as few as ten cause most of the uncertainty. This means that the model can be improved, and the uncertainty substantially reduced, by focussing attention on this tractably small set of rate constants. Work supported by Science Foundation Ireland under grant08/SRC/I1411, and by COST Action MP1101 ``Biomedical Applications of Atmospheric Pressure Plasmas.''
Modeling Power Systems as Complex Adaptive Systems
Chassin, David P.; Malard, Joel M.; Posse, Christian; Gangopadhyaya, Asim; Lu, Ning; Katipamula, Srinivas; Mallow, J V.
2004-12-30
Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We review and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.
Uniform surface complexation approaches to radionuclide sorption modeling
Turner, D.R.; Pabalan, R.T.; Muller, P.; Bertetti, F.P.
1995-12-01
Simplified surface complexation models, based on a uniform set of model parameters have been developed to address complex radionuclide sorption behavior. Existing data have been examined, and interpreted using numerical nonlinear least-squares optimization techniques to determine the necessary binding constants. Simplified modeling approaches have generally proven successful at simulating and predicting radionuclide sorption on (hydr)oxides and aluminosilicates over a wide range of physical and chemical conditions.
Integrated Modeling of Complex Optomechanical Systems
NASA Astrophysics Data System (ADS)
Andersen, Torben; Enmark, Anita
2011-09-01
Mathematical modeling and performance simulation are playing an increasing role in large, high-technology projects. There are two reasons; first, projects are now larger than they were before, and the high cost calls for detailed performance prediction before construction. Second, in particular for space-related designs, it is often difficult to test systems under realistic conditions beforehand, and mathematical modeling is then needed to verify in advance that a system will work as planned. Computers have become much more powerful, permitting calculations that were not possible before. At the same time mathematical tools have been further developed and found acceptance in the community. Particular progress has been made in the fields of structural mechanics, optics and control engineering, where new methods have gained importance over the last few decades. Also, methods for combining optical, structural and control system models into global models have found widespread use. Such combined models are usually called integrated models and were the subject of this symposium. The objective was to bring together people working in the fields of groundbased optical telescopes, ground-based radio telescopes, and space telescopes. We succeeded in doing so and had 39 interesting presentations and many fruitful discussions during coffee and lunch breaks and social arrangements. We are grateful that so many top ranked specialists found their way to Kiruna and we believe that these proceedings will prove valuable during much future work.
The sigma model on complex projective superspaces
NASA Astrophysics Data System (ADS)
Candu, Constantin; Mitev, Vladimir; Quella, Thomas; Saleur, Hubert; Schomerus, Volker
2010-02-01
The sigma model on projective superspaces mathbb{C}{mathbb{P}^{S - 1left| S right.}} gives rise to a continuous family of interacting 2D conformal field theories which are parametrized by the curvature radius R and the theta angle θ. Our main goal is to determine the spectrum of the model, non-perturbatively as a function of both parameters. We succeed to do so for all open boundary conditions preserving the full global symmetry of the model. In string theory parlor, these correspond to volume filling branes that are equipped with a monopole line bundle and connection. The paper consists of two parts. In the first part, we approach the problem within the continuum formulation. Combining combinatorial arguments with perturbative studies and some simple free field calculations, we determine a closed formula for the partition function of the theory. This is then tested numerically in the second part. There we extend the proposal of [
A simple model clarifies the complicated relationships of complex networks
NASA Astrophysics Data System (ADS)
Zheng, Bojin; Wu, Hongrun; Kuang, Li; Qin, Jun; Du, Wenhua; Wang, Jianmin; Li, Deyi
2014-08-01
Real-world networks such as the Internet and WWW have many common traits. Until now, hundreds of models were proposed to characterize these traits for understanding the networks. Because different models used very different mechanisms, it is widely believed that these traits origin from different causes. However, we find that a simple model based on optimisation can produce many traits, including scale-free, small-world, ultra small-world, Delta-distribution, compact, fractal, regular and random networks. Moreover, by revising the proposed model, the community-structure networks are generated. By this model and the revised versions, the complicated relationships of complex networks are illustrated. The model brings a new universal perspective to the understanding of complex networks and provide a universal method to model complex networks from the viewpoint of optimisation.
A simple model clarifies the complicated relationships of complex networks
Zheng, Bojin; Wu, Hongrun; Kuang, Li; Qin, Jun; Du, Wenhua; Wang, Jianmin; Li, Deyi
2014-01-01
Real-world networks such as the Internet and WWW have many common traits. Until now, hundreds of models were proposed to characterize these traits for understanding the networks. Because different models used very different mechanisms, it is widely believed that these traits origin from different causes. However, we find that a simple model based on optimisation can produce many traits, including scale-free, small-world, ultra small-world, Delta-distribution, compact, fractal, regular and random networks. Moreover, by revising the proposed model, the community-structure networks are generated. By this model and the revised versions, the complicated relationships of complex networks are illustrated. The model brings a new universal perspective to the understanding of complex networks and provide a universal method to model complex networks from the viewpoint of optimisation. PMID:25160506
Improving phylogenetic regression under complex evolutionary models.
Mazel, Florent; Davies, T Jonathan; Georges, Damien; Lavergne, Sébastien; Thuiller, Wilfried; Peres-NetoO, Pedro R
2016-02-01
Phylogenetic Generalized Least Square (PGLS) is the tool of choice among phylogenetic comparative methods to measure the correlation between species features such as morphological and life-history traits or niche characteristics. In its usual form, it assumes that the residual variation follows a homogenous model of evolution across the branches of the phylogenetic tree. Since a homogenous model of evolution is unlikely to be realistic in nature, we explored the robustness of the phylogenetic regression when this assumption is violated. We did so by simulating a set of traits under various heterogeneous models of evolution, and evaluating the statistical performance (type I error [the percentage of tests based on samples that incorrectly rejected a true null hypothesis] and power [the percentage of tests that correctly rejected a false null hypothesis]) of classical phylogenetic regression. We found that PGLS has good power but unacceptable type I error rates. This finding is important since this method has been increasingly used in comparative analyses over the last decade. To address this issue, we propose a simple solution based on transforming the underlying variance-covariance matrix to adjust for model heterogeneity within PGLS. We suggest that heterogeneous rates of evolution might be particularly prevalent in large phylogenetic trees, while most current approaches assume a homogenous rate of evolution. Our analysis demonstrates that overlooking rate heterogeneity can result in inflated type I errors, thus misleading comparative analyses. We show that it is possible to correct for this bias even when the underlying model of evolution is not known a priori. PMID:27145604
A musculoskeletal model of the elbow joint complex
NASA Technical Reports Server (NTRS)
Gonzalez, Roger V.; Barr, Ronald E.; Abraham, Lawrence D.
1993-01-01
This paper describes a musculoskeletal model that represents human elbow flexion-extension and forearm pronation-supination. Musculotendon parameters and the skeletal geometry were determined for the musculoskeletal model in the analysis of ballistic elbow joint complex movements. The key objective was to develop a computational model, guided by optimal control, to investigate the relationship among patterns of muscle excitation, individual muscle forces, and movement kinematics. The model was verified using experimental kinematic, torque, and electromyographic data from volunteer subjects performing both isometric and ballistic elbow joint complex movements. In general, the model predicted kinematic and muscle excitation patterns similar to what was experimentally measured.
Optimal Complexity of Nonlinear Rainfall-Runoff Models
NASA Astrophysics Data System (ADS)
Schoups, G.; Vrugt, J.; van de Giesen, N.; Fenicia, F.
2008-12-01
Identification of an appropriate level of model complexity to accurately translate rainfall into runoff remains an unresolved issue. The model has to be complex enough to generate accurate predictions, but not too complex such that its parameters cannot be reliably estimated from the data. Earlier work with linear models (Jakeman and Hornberger, 1993) concluded that a model with 4 to 5 parameters is sufficient. However, more recent results with a nonlinear model (Vrugt et al., 2006) suggest that 10 or more parameters may be identified from daily rainfall-runoff time-series. The goal here is to systematically investigate optimal complexity of nonlinear rainfall-runoff models, yielding accurate models with identifiable parameters. Our methodology consists of four steps: (i) a priori specification of a family of model structures from which to pick an optimal one, (ii) parameter optimization of each model structure to estimate empirical or calibration error, (iii) estimation of parameter uncertainty of each calibrated model structure, and (iv) estimation of prediction error of each calibrated model structure. For the first step we formulate a flexible model structure that allows us to systematically vary the complexity with which physical processes are simulated. The second and third steps are achieved using a recently developed Markov chain Monte Carlo algorithm (DREAM), which minimizes calibration error yielding optimal parameter values and their underlying posterior probability density function. Finally, we compare several methods for estimating prediction error of each model structure, including statistical methods based on information criteria and split-sample calibration-validation. Estimates of parameter uncertainty and prediction error are then used to identify optimal complexity for rainfall-runoff modeling, using data from dry and wet MOPEX catchments as case studies.
Blueprints for Complex Learning: The 4C/ID-Model.
ERIC Educational Resources Information Center
van Merrienboer, Jeroen J. G.; Clark, Richard E.; de Croock, Marcel B. M.
2002-01-01
Describes the four-component instructional design system (4C/ID-model) developed for the design of training programs for complex skills. Discusses the structure of training blueprints for complex learning and associated instructional methods, focusing on learning tasks, supportive information, just-in-time information, and part-task practice.…
Classrooms as Complex Adaptive Systems: A Relational Model
ERIC Educational Resources Information Center
Burns, Anne; Knox, John S.
2011-01-01
In this article, we describe and model the language classroom as a complex adaptive system (see Logan & Schumann, 2005). We argue that linear, categorical descriptions of classroom processes and interactions do not sufficiently explain the complex nature of classrooms, and cannot account for how classroom change occurs (or does not occur), over…
Prequential Analysis of Complex Data with Adaptive Model Reselection†
Clarke, Jennifer; Clarke, Bertrand
2010-01-01
In Prequential analysis, an inference method is viewed as a forecasting system, and the quality of the inference method is based on the quality of its predictions. This is an alternative approach to more traditional statistical methods that focus on the inference of parameters of the data generating distribution. In this paper, we introduce adaptive combined average predictors (ACAPs) for the Prequential analysis of complex data. That is, we use convex combinations of two different model averages to form a predictor at each time step in a sequence. A novel feature of our strategy is that the models in each average are re-chosen adaptively at each time step. To assess the complexity of a given data set, we introduce measures of data complexity for continuous response data. We validate our measures in several simulated contexts prior to using them in real data examples. The performance of ACAPs is compared with the performances of predictors based on stacking or likelihood weighted averaging in several model classes and in both simulated and real data sets. Our results suggest that ACAPs achieve a better trade off between model list bias and model list variability in cases where the data is very complex. This implies that the choices of model class and averaging method should be guided by a concept of complexity matching, i.e. the analysis of a complex data set may require a more complex model class and averaging strategy than the analysis of a simpler data set. We propose that complexity matching is akin to a bias–variance tradeoff in statistical modeling. PMID:20617104
Size and complexity in model financial systems.
Arinaminpathy, Nimalan; Kapadia, Sujit; May, Robert M
2012-11-01
The global financial crisis has precipitated an increasing appreciation of the need for a systemic perspective toward financial stability. For example: What role do large banks play in systemic risk? How should capital adequacy standards recognize this role? How is stability shaped by concentration and diversification in the financial system? We explore these questions using a deliberately simplified, dynamic model of a banking system that combines three different channels for direct transmission of contagion from one bank to another: liquidity hoarding, asset price contagion, and the propagation of defaults via counterparty credit risk. Importantly, we also introduce a mechanism for capturing how swings in "confidence" in the system may contribute to instability. Our results highlight that the importance of relatively large, well-connected banks in system stability scales more than proportionately with their size: the impact of their collapse arises not only from their connectivity, but also from their effect on confidence in the system. Imposing tougher capital requirements on larger banks than smaller ones can thus enhance the resilience of the system. Moreover, these effects are more pronounced in more concentrated systems, and continue to apply, even when allowing for potential diversification benefits that may be realized by larger banks. We discuss some tentative implications for policy, as well as conceptual analogies in ecosystem stability and in the control of infectious diseases. PMID:23091020
Size and complexity in model financial systems
Arinaminpathy, Nimalan; Kapadia, Sujit; May, Robert M.
2012-01-01
The global financial crisis has precipitated an increasing appreciation of the need for a systemic perspective toward financial stability. For example: What role do large banks play in systemic risk? How should capital adequacy standards recognize this role? How is stability shaped by concentration and diversification in the financial system? We explore these questions using a deliberately simplified, dynamic model of a banking system that combines three different channels for direct transmission of contagion from one bank to another: liquidity hoarding, asset price contagion, and the propagation of defaults via counterparty credit risk. Importantly, we also introduce a mechanism for capturing how swings in “confidence” in the system may contribute to instability. Our results highlight that the importance of relatively large, well-connected banks in system stability scales more than proportionately with their size: the impact of their collapse arises not only from their connectivity, but also from their effect on confidence in the system. Imposing tougher capital requirements on larger banks than smaller ones can thus enhance the resilience of the system. Moreover, these effects are more pronounced in more concentrated systems, and continue to apply, even when allowing for potential diversification benefits that may be realized by larger banks. We discuss some tentative implications for policy, as well as conceptual analogies in ecosystem stability and in the control of infectious diseases. PMID:23091020
Rogalska, Ewa; Więcław-Czapla, Katarzyna
2013-01-01
Three antimicrobial peptides derived from bovine milk proteins were examined with regard to penetration into insoluble monolayers formed with 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) or 1,2-dipalmitoyl-sn-glycero-3-phospho-rac-(1-glycerol) sodium salt (DPPG). Effects on surface pressure (Π) and electric surface potential (ΔV) were measured, Π with a platinum Wilhelmy plate and ΔV with a vibrating plate. The penetration measurements were performed under stationary diffusion conditions and upon the compression of the monolayers. The two type measurements showed greatly different effects of the peptide-lipid interactions. Results of the stationary penetration show that the peptide interactions with DPPC monolayer are weak, repulsive, and nonspecific while the interactions with DPPG monolayer are significant, attractive, and specific. These results are in accord with the fact that antimicrobial peptides disrupt bacteria membranes (negative) while no significant effect on the host membranes (neutral) is observed. No such discrimination was revealed from the compression isotherms. The latter indicate that squeezing the penetrant out of the monolayer upon compression does not allow for establishing the penetration equilibrium, so the monolayer remains supersaturated with the penetrant and shows an under-equilibrium orientation within the entire compression range, practically. PMID:24455264
Orientation of Tie-Lines in the Phase Diagram of DOPC:DPPC:Cholesterol Model Biomembranes
Uppamoochikkal, Pradeep; Tristram-Nagle, Stephanie; Nagle, John F.
2010-01-01
We report the direction of tie-lines of coexisting phases in a ternary diagram of DOPC:DPPC:Cholesterol lipid bilayers, which has been a system of interest in the discussion of biological rafts. For coexisting Ld and Lo phases we find that the orientation angle α of the tie-lines increases as the cholesterol concentration increases and it also increases as temperature increases from T=15 °C to T=30 °C. Results at lower cholesterol concentrations support the existence of a different 2-phase coexistence region of Ld and So phases and the existence of a 3-phase region separating the two 2-phase regions. Our method uses the X-ray lamellar D-spacings observed in oriented bilayers as a function of varying hydration. Although this method does not obtain the ends of the tie-lines, it gives precise values (±1°) of their angles α in the ternary phase diagram. PMID:20968281
Effect of Fengycin, a Lipopeptide Produced by Bacillus subtilis, on Model Biomembranes
Deleu, Magali; Paquot, Michel; Nylander, Tommy
2008-01-01
Fengycin is a biologically active lipopeptide produced by several Bacillus subtilis strains. The lipopeptide is known to develop antifungal activity against filamentous fungi and to have hemolytic activity 40-fold lower than that of surfactin, another lipopeptide produced by B. subtilis. The aim of this work is to use complementary biophysical techniques to reveal the mechanism of membrane perturbation by fengycin. These include: 1), the Langmuir trough technique in combination with Brewster angle microscopy to study the lipopeptide penetration into monolayers; 2), ellipsometry to investigate the adsorption of fengycin onto supported lipid bilayers; 3), differential scanning calorimetry to determine the thermotropic properties of lipid bilayers in the presence of fengycin; and 4), cryogenic transmission electron microscopy, which provides information on the structural organization of the lipid/lipopeptide system. From these experiments, the mechanism of fengycin action appears to be based on a two-state transition controlled by the lipopeptide concentration. One state is the monomeric, not deeply anchored and nonperturbing lipopeptide, and the other state is a buried, aggregated form, which is responsible for membrane leakage and bioactivity. The mechanism, thus, appears to be driven mainly by the physicochemical properties of the lipopeptide, i.e., its amphiphilic character and affinity for lipid bilayers. PMID:18178659
Amirkavei, Mooud; Kinnunen, Paavo K J
2016-02-01
In order to obtain molecular level insight into the biophysics of the apoptosis promoting phospholipid 1-palmitoyl-2-azelaoyl-sn-glycero-3-phosphocholine (PazePC) we studied its partitioning into different lipid phases by isothermal titration calorimetry (ITC). To aid the interpretation of these data for PazePC, we additionally characterized by both ITC and fluorescence spectroscopy the fluorescent phospholipid analog 1-palmitoyl-2-{6-[(7-nitro-2-1,3-benzoxadiazol-4-yl)amino]hexanoyl}-sn-glycero-3-phosphocholine (NBD-C6-PC), which similarly to PazePC can adopt extended conformation in lipid bilayers. With the NBD-hexanoyl chain reversing its direction and extending into the aqueous space out of the bilayer, 7-nitro-2,1,3-benzoxadiazol-4-yl (NBD) becomes accessible to the water soluble dithionite, which reduces to non-fluorescent product. Our results suggest that these phospholipid derivatives first partition and penetrate into the outer bilayer leaflet of liquid disordered phase liposomes composed of unsaturated 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC). Upon increase up to 2 mol% PazePC and NBD-C6-PC of the overall content, flip-flop from the outer into the inner bilayer leaflet commences. Interestingly, the presence of 40 mol% cholesterol in POPC liposomes did not abrogate the partitioning of PazePC into the liquid ordered phase. In contrast, only insignificant partitioning of PazePC and NBD-C6-PC into sphingomyelin/cholesterol liposomes was evident, highlighting a specific membrane permeability barrier function of this particular lipid composition against oxidatively truncated PazePC, thus emphasizing the importance of detailed characterization of the biophysical properties of membranes found in different cellular organelles, in terms of providing barriers for lipid-mediated cellular signals in processes such as apoptosis. Our data suggest NBD-C6-PC to represent useful fluorescent probe to study the cellular dynamics of oxidized phospholipid species, such as PazePC. PMID:26656184
Barzyk, Wanda; Rogalska, Ewa; Więcław-Czapla, Katarzyna
2013-01-01
Three antimicrobial peptides derived from bovine milk proteins were examined with regard to penetration into insoluble monolayers formed with 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) or 1,2-dipalmitoyl-sn-glycero-3-phospho-rac-(1-glycerol) sodium salt (DPPG). Effects on surface pressure (Π) and electric surface potential (ΔV) were measured, Π with a platinum Wilhelmy plate and ΔV with a vibrating plate. The penetration measurements were performed under stationary diffusion conditions and upon the compression of the monolayers. The two type measurements showed greatly different effects of the peptide-lipid interactions. Results of the stationary penetration show that the peptide interactions with DPPC monolayer are weak, repulsive, and nonspecific while the interactions with DPPG monolayer are significant, attractive, and specific. These results are in accord with the fact that antimicrobial peptides disrupt bacteria membranes (negative) while no significant effect on the host membranes (neutral) is observed. No such discrimination was revealed from the compression isotherms. The latter indicate that squeezing the penetrant out of the monolayer upon compression does not allow for establishing the penetration equilibrium, so the monolayer remains supersaturated with the penetrant and shows an under-equilibrium orientation within the entire compression range, practically. PMID:24455264
Reassessing Geophysical Models of the Bushveld Complex in 3D
NASA Astrophysics Data System (ADS)
Cole, J.; Webb, S. J.; Finn, C.
2012-12-01
Conceptual geophysical models of the Bushveld Igneous Complex show three possible geometries for its mafic component: 1) Separate intrusions with vertical feeders for the eastern and western lobes (Cousins, 1959) 2) Separate dipping sheets for the two lobes (Du Plessis and Kleywegt, 1987) 3) A single saucer-shaped unit connected at depth in the central part between the two lobes (Cawthorn et al, 1998) Model three incorporates isostatic adjustment of the crust in response to the weight of the dense mafic material. The model was corroborated by results of a broadband seismic array over southern Africa, known as the Southern African Seismic Experiment (SASE) (Nguuri, et al, 2001; Webb et al, 2004). This new information about the crustal thickness only became available in the last decade and could not be considered in the earlier models. Nevertheless, there is still on-going debate as to which model is correct. All of the models published up to now have been done in 2 or 2.5 dimensions. This is not well suited to modelling the complex geometry of the Bushveld intrusion. 3D modelling takes into account effects of variations in geometry and geophysical properties of lithologies in a full three dimensional sense and therefore affects the shape and amplitude of calculated fields. The main question is how the new knowledge of the increased crustal thickness, as well as the complexity of the Bushveld Complex, will impact on the gravity fields calculated for the existing conceptual models, when modelling in 3D. The three published geophysical models were remodelled using full 3Dl potential field modelling software, and including crustal thickness obtained from the SASE. The aim was not to construct very detailed models, but to test the existing conceptual models in an equally conceptual way. Firstly a specific 2D model was recreated in 3D, without crustal thickening, to establish the difference between 2D and 3D results. Then the thicker crust was added. Including the less
A mechanistic model of the cysteine synthase complex.
Feldman-Salit, Anna; Wirtz, Markus; Hell, Ruediger; Wade, Rebecca C
2009-02-13
Plants and bacteria assimilate and incorporate inorganic sulfur into organic compounds such as the amino acid cysteine. Cysteine biosynthesis involves a bienzyme complex, the cysteine synthase (CS) complex. The CS complex is composed of the enzymes serine acetyl transferase (SAT) and O-acetyl-serine-(thiol)-lyase (OAS-TL). Although it is experimentally known that formation of the CS complex influences cysteine production, the exact biological function of the CS complex, the mechanism of reciprocal regulation of the constituent enzymes and the structure of the complex are still poorly understood. Here, we used docking techniques to construct a model of the CS complex from mitochondrial Arabidopsis thaliana. The three-dimensional structures of the enzymes were modeled by comparative techniques. The C-termini of SAT, missing in the template structures but crucial for CS formation, were modeled de novo. Diffusional encounter complexes of SAT and OAS-TL were generated by rigid-body Brownian dynamics simulation. By incorporating experimental constraints during Brownian dynamics simulation, we identified complexes consistent with experiments. Selected encounter complexes were refined by molecular dynamics simulation to generate structures of bound complexes. We found that although a stoichiometric ratio of six OAS-TL dimers to one SAT hexamer in the CS complex is geometrically possible, binding energy calculations suggest that, consistent with experiments, a ratio of only two OAS-TL dimers to one SAT hexamer is more likely. Computational mutagenesis of residues in OAS-TL that are experimentally significant for CS formation hindered the association of the enzymes due to a less-favorable electrostatic binding free energy. Since the enzymes from A. thaliana were expressed in Escherichia coli, the cross-species binding of SAT and OAS-TL from E. coli and A. thaliana was explored. The results showed that reduced cysteine production might be due to a cross-binding of A. thaliana
The Use of Behavior Models for Predicting Complex Operations
NASA Technical Reports Server (NTRS)
Gore, Brian F.
2010-01-01
Modeling and simulation (M&S) plays an important role when complex human-system notions are being proposed, developed and tested within the system design process. National Aeronautics and Space Administration (NASA) as an agency uses many different types of M&S approaches for predicting human-system interactions, especially when it is early in the development phase of a conceptual design. NASA Ames Research Center possesses a number of M&S capabilities ranging from airflow, flight path models, aircraft models, scheduling models, human performance models (HPMs), and bioinformatics models among a host of other kinds of M&S capabilities that are used for predicting whether the proposed designs will benefit the specific mission criteria. The Man-Machine Integration Design and Analysis System (MIDAS) is a NASA ARC HPM software tool that integrates many models of human behavior with environment models, equipment models, and procedural / task models. The challenge to model comprehensibility is heightened as the number of models that are integrated and the requisite fidelity of the procedural sets are increased. Model transparency is needed for some of the more complex HPMs to maintain comprehensibility of the integrated model performance. This will be exemplified in a recent MIDAS v5 application model and plans for future model refinements will be presented.
NASA Astrophysics Data System (ADS)
He, Bing; Yuan, Lan; Dai, Wenbing; Gao, Wei; Zhang, Hua; Wang, Xueqing; Fang, Weigang; Zhang, Qiang
2016-03-01
Nowadays, concern about the use of nanotechnology for biomedical application is unprecedentedly increasing. In fact, nanosystems applied for various potential clinical uses always have to cross the primary biological barrier consisting of epithelial cells. However, little is really known currently in terms of the influence of the dynamic bio-adhesion of nanosystems on bio-membranes as well as on endocytosis and transcytosis. This was investigated here using polymer nanoparticles (PNs) and MDCK epithelial cells as the models. Firstly, the adhesion of PNs on cell membranes was found to be time-dependent with a shift of both location and dispersion pattern, from the lateral adhesion of mainly mono-dispersed PNs initially to the apical coverage of the PN aggregate later. Then, it was interesting to observe in this study that the dynamic bio-adhesion of PNs only affected their endocytosis but not their transcytosis. It was important to find that the endocytosis of PNs was not a constant process. A GM1 dependent CDE (caveolae dependent endocytosis) pathway was dominant in the preliminary stage, followed by the co-existence of a CME (clathrin-mediated endocytosis) pathway for the PN aggregate at a later stage, in accordance with the adhesion features of PNs, suggesting the modification of PN adhesion patterns on the endocytosis pathways. Next, the PN adhesion was noticed to affect the structure of cell junctions, via altering the extra- and intra-cellular calcium levels, leading to the enhanced paracellular transport of small molecules, but not favorably enough for the obviously increased passing of PNs themselves. Finally, FRAP and other techniques all demonstrated the obvious impact of PN adhesion on the membrane confirmation, independent of the adhesion location and time, which might lower the threshold for the internalization of PNs, even their aggregates. Generally, these findings confirm that the transport pathway mechanism of PNs through epithelial cells is rather
He, Bing; Yuan, Lan; Dai, Wenbing; Gao, Wei; Zhang, Hua; Wang, Xueqing; Fang, Weigang; Zhang, Qiang
2016-03-10
Nowadays, concern about the use of nanotechnology for biomedical application is unprecedentedly increasing. In fact, nanosystems applied for various potential clinical uses always have to cross the primary biological barrier consisting of epithelial cells. However, little is really known currently in terms of the influence of the dynamic bio-adhesion of nanosystems on bio-membranes as well as on endocytosis and transcytosis. This was investigated here using polymer nanoparticles (PNs) and MDCK epithelial cells as the models. Firstly, the adhesion of PNs on cell membranes was found to be time-dependent with a shift of both location and dispersion pattern, from the lateral adhesion of mainly mono-dispersed PNs initially to the apical coverage of the PN aggregate later. Then, it was interesting to observe in this study that the dynamic bio-adhesion of PNs only affected their endocytosis but not their transcytosis. It was important to find that the endocytosis of PNs was not a constant process. A GM1 dependent CDE (caveolae dependent endocytosis) pathway was dominant in the preliminary stage, followed by the co-existence of a CME (clathrin-mediated endocytosis) pathway for the PN aggregate at a later stage, in accordance with the adhesion features of PNs, suggesting the modification of PN adhesion patterns on the endocytosis pathways. Next, the PN adhesion was noticed to affect the structure of cell junctions, via altering the extra- and intra-cellular calcium levels, leading to the enhanced paracellular transport of small molecules, but not favorably enough for the obviously increased passing of PNs themselves. Finally, FRAP and other techniques all demonstrated the obvious impact of PN adhesion on the membrane confirmation, independent of the adhesion location and time, which might lower the threshold for the internalization of PNs, even their aggregates. Generally, these findings confirm that the transport pathway mechanism of PNs through epithelial cells is rather
Modeling of protein binary complexes using structural mass spectrometry data
Kamal, J.K. Amisha; Chance, Mark R.
2008-01-01
In this article, we describe a general approach to modeling the structure of binary protein complexes using structural mass spectrometry data combined with molecular docking. In the first step, hydroxyl radical mediated oxidative protein footprinting is used to identify residues that experience conformational reorganization due to binding or participate in the binding interface. In the second step, a three-dimensional atomic structure of the complex is derived by computational modeling. Homology modeling approaches are used to define the structures of the individual proteins if footprinting detects significant conformational reorganization as a function of complex formation. A three-dimensional model of the complex is constructed from these binary partners using the ClusPro program, which is composed of docking, energy filtering, and clustering steps. Footprinting data are used to incorporate constraints—positive and/or negative—in the docking step and are also used to decide the type of energy filter—electrostatics or desolvation—in the successive energy-filtering step. By using this approach, we examine the structure of a number of binary complexes of monomeric actin and compare the results to crystallographic data. Based on docking alone, a number of competing models with widely varying structures are observed, one of which is likely to agree with crystallographic data. When the docking steps are guided by footprinting data, accurate models emerge as top scoring. We demonstrate this method with the actin/gelsolin segment-1 complex. We also provide a structural model for the actin/cofilin complex using this approach which does not have a crystal or NMR structure. PMID:18042684
Geometric modeling of subcellular structures, organelles, and multiprotein complexes
Feng, Xin; Xia, Kelin; Tong, Yiying; Wei, Guo-Wei
2013-01-01
SUMMARY Recently, the structure, function, stability, and dynamics of subcellular structures, organelles, and multi-protein complexes have emerged as a leading interest in structural biology. Geometric modeling not only provides visualizations of shapes for large biomolecular complexes but also fills the gap between structural information and theoretical modeling, and enables the understanding of function, stability, and dynamics. This paper introduces a suite of computational tools for volumetric data processing, information extraction, surface mesh rendering, geometric measurement, and curvature estimation of biomolecular complexes. Particular emphasis is given to the modeling of cryo-electron microscopy data. Lagrangian-triangle meshes are employed for the surface presentation. On the basis of this representation, algorithms are developed for surface area and surface-enclosed volume calculation, and curvature estimation. Methods for volumetric meshing have also been presented. Because the technological development in computer science and mathematics has led to multiple choices at each stage of the geometric modeling, we discuss the rationales in the design and selection of various algorithms. Analytical models are designed to test the computational accuracy and convergence of proposed algorithms. Finally, we select a set of six cryo-electron microscopy data representing typical subcellular complexes to demonstrate the efficacy of the proposed algorithms in handling biomolecular surfaces and explore their capability of geometric characterization of binding targets. This paper offers a comprehensive protocol for the geometric modeling of subcellular structures, organelles, and multiprotein complexes. PMID:23212797
Between complexity of modelling and modelling of complexity: An essay on econophysics
NASA Astrophysics Data System (ADS)
Schinckus, C.
2013-09-01
Econophysics is an emerging field dealing with complex systems and emergent properties. A deeper analysis of themes studied by econophysicists shows that research conducted in this field can be decomposed into two different computational approaches: “statistical econophysics” and “agent-based econophysics”. This methodological scission complicates the definition of the complexity used in econophysics. Therefore, this article aims to clarify what kind of emergences and complexities we can find in econophysics in order to better understand, on one hand, the current scientific modes of reasoning this new field provides; and on the other hand, the future methodological evolution of the field.
Network model of bilateral power markets based on complex networks
NASA Astrophysics Data System (ADS)
Wu, Yang; Liu, Junyong; Li, Furong; Yan, Zhanxin; Zhang, Li
2014-06-01
The bilateral power transaction (BPT) mode becomes a typical market organization with the restructuring of electric power industry, the proper model which could capture its characteristics is in urgent need. However, the model is lacking because of this market organization's complexity. As a promising approach to modeling complex systems, complex networks could provide a sound theoretical framework for developing proper simulation model. In this paper, a complex network model of the BPT market is proposed. In this model, price advantage mechanism is a precondition. Unlike other general commodity transactions, both of the financial layer and the physical layer are considered in the model. Through simulation analysis, the feasibility and validity of the model are verified. At same time, some typical statistical features of BPT network are identified. Namely, the degree distribution follows the power law, the clustering coefficient is low and the average path length is a bit long. Moreover, the topological stability of the BPT network is tested. The results show that the network displays a topological robustness to random market member's failures while it is fragile against deliberate attacks, and the network could resist cascading failure to some extent. These features are helpful for making decisions and risk management in BPT markets.
Evapotranspiration model of different complexity for multiple land cover types
Technology Transfer Automated Retrieval System (TEKTRAN)
A comparison between half-hourly and daily measured and computed evapotranspiration (ET) using three models of different complexity, namely the Priestley-Taylor (P-T), reference Penman-Monteith (P-M), and Common Land Model (CLM) was conducted using three AmeriFlux sites under different land cover an...
Using fMRI to Test Models of Complex Cognition
ERIC Educational Resources Information Center
Anderson, John R.; Carter, Cameron S.; Fincham, Jon M.; Qin, Yulin; Ravizza, Susan M.; Rosenberg-Lee, Miriam
2008-01-01
This article investigates the potential of fMRI to test assumptions about different components in models of complex cognitive tasks. If the components of a model can be associated with specific brain regions, one can make predictions for the temporal course of the BOLD response in these regions. An event-locked procedure is described for dealing…
Tips on Creating Complex Geometry Using Solid Modeling Software
ERIC Educational Resources Information Center
Gow, George
2008-01-01
Three-dimensional computer-aided drafting (CAD) software, sometimes referred to as "solid modeling" software, is easy to learn, fun to use, and becoming the standard in industry. However, many users have difficulty creating complex geometry with the solid modeling software. And the problem is not entirely a student problem. Even some teachers and…
Zebrafish as an emerging model for studying complex brain disorders
Kalueff, Allan V.; Stewart, Adam Michael; Gerlai, Robert
2014-01-01
The zebrafish (Danio rerio) is rapidly becoming a popular model organism in pharmacogenetics and neuropharmacology. Both larval and adult zebrafish are currently used to increase our understanding of brain function, dysfunction, and their genetic and pharmacological modulation. Here we review the developing utility of zebrafish in the analysis of complex brain disorders (including, for example, depression, autism, psychoses, drug abuse and cognitive disorders), also covering zebrafish applications towards the goal of modeling major human neuropsychiatric and drug-induced syndromes. We argue that zebrafish models of complex brain disorders and drug-induced conditions have become a rapidly emerging critical field in translational neuropharmacology research. PMID:24412421
Simulating complex intracellular processes using object-oriented computational modelling.
Johnson, Colin G; Goldman, Jacki P; Gullick, William J
2004-11-01
The aim of this paper is to give an overview of computer modelling and simulation in cellular biology, in particular as applied to complex biochemical processes within the cell. This is illustrated by the use of the techniques of object-oriented modelling, where the computer is used to construct abstractions of objects in the domain being modelled, and these objects then interact within the computer to simulate the system and allow emergent properties to be observed. The paper also discusses the role of computer simulation in understanding complexity in biological systems, and the kinds of information which can be obtained about biology via simulation. PMID:15302205
González-Henríquez, C M; Pizarro-Guerra, G C; Córdova-Alarcón, E N; Sarabia-Vallejos, M A; Terraza-Inostroza, C A
2016-03-01
Hydrogel films possess the ability of retain water and deliver it to a phospholipid bilayer mainly composed by DPPC (1,2-dipalmitoyl-sn-glycero-3-phosphocholine); moisture of the medium favors the stability of an artificial biomembrane when it is subjected to repetitive heating cycles. This hypothesis is valid when the hydrogel film, used as scaffold, present a flat surface morphology and a high ability for water releasing. On the other hand, when the sample presents a wrinkle topography (periodic undulations), free lateral molecular movement of the bilayer becomes lower, disfavoring the occurrence of clear phases/phase transitions according to applied temperature. Hydrogel films were prepared using HEMA (hydroxyethylmetacrylate), different crosslinking agents and initiators. This reaction mixture was spread over hydrophilic silicon wafers using spin coating technique. Resultant films were then exposed to UV light favoring polymeric chain crosslinking and interactions between hydrogel and substrate; this process is also known to generate tensile stress mismatch between different hydrogel strata, producing out-of-plane net force that generate ordered undulations or collapsed crystals at surface level. DPPC bilayers were then placed over hydrogel using Langmuir-Blodgett technique. Surface morphology was detected in order to clarify the behavior of these films. Obtained data corroborate DPPC membrane stability making possible to detect phases/phase transitions by ellipsometric methods and Atomic Force Microscopy due to their high hydration level. This system is intended to be used as biosensor through the insertion of transmembrane proteins or peptides that detect minimal variations of some analyte in the environment; artificial biomembrane stability and behavior is fundamental for this purpose. PMID:26855412
Complexation and molecular modeling studies of europium(III)-gallic acid-amino acid complexes.
Taha, Mohamed; Khan, Imran; Coutinho, João A P
2016-04-01
With many metal-based drugs extensively used today in the treatment of cancer, attention has focused on the development of new coordination compounds with antitumor activity with europium(III) complexes recently introduced as novel anticancer drugs. The aim of this work is to design new Eu(III) complexes with gallic acid, an antioxida'nt phenolic compound. Gallic acid was chosen because it shows anticancer activity without harming health cells. As antioxidant, it helps to protect human cells against oxidative damage that implicated in DNA damage, cancer, and accelerated cell aging. In this work, the formation of binary and ternary complexes of Eu(III) with gallic acid, primary ligand, and amino acids alanine, leucine, isoleucine, and tryptophan was studied by glass electrode potentiometry in aqueous solution containing 0.1M NaNO3 at (298.2±0.1) K. Their overall stability constants were evaluated and the concentration distributions of the complex species in solution were calculated. The protonation constants of gallic acid and amino acids were also determined at our experimental conditions and compared with those predicted by using conductor-like screening model for realistic solvation (COSMO-RS) model. The geometries of Eu(III)-gallic acid complexes were characterized by the density functional theory (DFT). The spectroscopic UV-visible and photoluminescence measurements are carried out to confirm the formation of Eu(III)-gallic acid complexes in aqueous solutions. PMID:26827296
Multiscale Model for the Assembly Kinetics of Protein Complexes.
Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao
2016-02-01
The assembly of proteins into high-order complexes is a general mechanism for these biomolecules to implement their versatile functions in cells. Natural evolution has developed various assembling pathways for specific protein complexes to maintain their stability and proper activities. Previous studies have provided numerous examples of the misassembly of protein complexes leading to severe biological consequences. Although the research focusing on protein complexes has started to move beyond the static representation of quaternary structures to the dynamic aspect of their assembly, the current understanding of the assembly mechanism of protein complexes is still largely limited. To tackle this problem, we developed a new multiscale modeling framework. This framework combines a lower-resolution rigid-body-based simulation with a higher-resolution Cα-based simulation method so that protein complexes can be assembled with both structural details and computational efficiency. We applied this model to a homotrimer and a heterotetramer as simple test systems. Consistent with experimental observations, our simulations indicated very different kinetics between protein oligomerization and dimerization. The formation of protein oligomers is a multistep process that is much slower than dimerization but thermodynamically more stable. Moreover, we showed that even the same protein quaternary structure can have very diverse assembly pathways under different binding constants between subunits, which is important for regulating the functions of protein complexes. Finally, we revealed that the binding between subunits in a complex can be synergistically strengthened during assembly without considering allosteric regulation or conformational changes. Therefore, our model provides a useful tool to understand the general principles of protein complex assembly. PMID:26738810
Pedigree models for complex human traits involving the mitochondrial genome.
Schork, N J; Guo, S W
1993-01-01
Recent biochemical and molecular-genetic discoveries concerning variations in human mtDNA have suggested a role for mtDNA mutations in a number of human traits and disorders. Although the importance of these discoveries cannot be emphasized enough, the complex natures of mitochondrial biogenesis, mutant mtDNA phenotype expression, and the maternal inheritance pattern exhibited by mtDNA transmission make it difficult to develop models that can be used routinely in pedigree analyses to quantify and test hypotheses about the role of mtDNA in the expression of a trait. In the present paper, we describe complexities inherent in mitochondrial biogenesis and genetic transmission and show how these complexities can be incorporated into appropriate mathematical models. We offer a variety of likelihood-based models which account for the complexities discussed. The derivation of our models is meant to stimulate the construction of statistical tests for putative mtDNA contribution to a trait. Results of simulation studies which make use of the proposed models are described. The results of the simulation studies suggest that, although pedigree models of mtDNA effects can be reliable, success in mapping chromosomal determinants of a trait does not preclude the possibility that mtDNA determinants exists for the trait as well. Shortcomings inherent in the proposed models are described in an effort to expose areas in need of additional research. PMID:8250048
Pedigree models for complex human traits involving the mitochrondrial genome
Schork, N.J.; Guo, S.W. )
1993-12-01
Recent biochemical and molecular-genetic discoveries concerning variations in human mtDNA have suggested a role for mtDNA mutations in a number of human traits and disorders. Although the importance of these discoveries cannot be emphasized enough, the complex natures of mitochondrial biogenesis, mutant mtDNA phenotype expression, and the maternal inheritance pattern exhibited by mtDNA transmission make it difficult to develop models that can be used routinely in pedigree analyses to quantify and test hypotheses about the role of mtDNA in the expression of a trait. In the present paper, the authors describe complexities inherent in mitochondrial biogenesis and genetic transmission and show how these complexities can be incorporated into appropriate mathematical models. The authors offer a variety of likelihood-based models which account for the complexities discussed. The derivation of the models is meant to stimulate the construction of statistical tests for putative mtDNA contribution to a trait. Results of simulation studies which make use of the proposed models are described. The results of the simulation studies suggest that, although pedigree models of mtDNA effects can be reliable, success in mapping chromosomal determinants of a trait does not preclude the possibility that mtDNA determinants exist for the trait as well. Shortcomings inherent in the proposed models are described in an effort to expose areas in need of additional research. 58 refs., 5 figs., 2 tabs.
Systems Engineering Metrics: Organizational Complexity and Product Quality Modeling
NASA Technical Reports Server (NTRS)
Mog, Robert A.
1997-01-01
Innovative organizational complexity and product quality models applicable to performance metrics for NASA-MSFC's Systems Analysis and Integration Laboratory (SAIL) missions and objectives are presented. An intensive research effort focuses on the synergistic combination of stochastic process modeling, nodal and spatial decomposition techniques, organizational and computational complexity, systems science and metrics, chaos, and proprietary statistical tools for accelerated risk assessment. This is followed by the development of a preliminary model, which is uniquely applicable and robust for quantitative purposes. Exercise of the preliminary model using a generic system hierarchy and the AXAF-I architectural hierarchy is provided. The Kendall test for positive dependence provides an initial verification and validation of the model. Finally, the research and development of the innovation is revisited, prior to peer review. This research and development effort results in near-term, measurable SAIL organizational and product quality methodologies, enhanced organizational risk assessment and evolutionary modeling results, and 91 improved statistical quantification of SAIL productivity interests.
Emulator-assisted data assimilation in complex models
NASA Astrophysics Data System (ADS)
Margvelashvili, Nugzar Yu; Herzfeld, Mike; Rizwi, Farhan; Mongin, Mathieu; Baird, Mark E.; Jones, Emlyn; Schaffelke, Britta; King, Edward; Schroeder, Thomas
2016-08-01
Emulators are surrogates of complex models that run orders of magnitude faster than the original model. The utility of emulators for the data assimilation into ocean models is still not well understood. High complexity of ocean models translates into high uncertainty of the corresponding emulators which may undermine the quality of the assimilation schemes based on such emulators. Numerical experiments with a chaotic Lorenz-95 model are conducted to illustrate this point and suggest a strategy to alleviate this problem through the localization of the emulation and data assimilation procedures. Insights gained through these experiments are used to design and implement data assimilation scenario for a 3D fine-resolution sediment transport model of the Great Barrier Reef (GBR), Australia.
Calibration of Complex Subsurface Reaction Models Using a Surrogate-Model Approach
Application of model assessment techniques to complex subsurface reaction models involves numerous difficulties, including non-trivial model selection, parameter non-uniqueness, and excessive computational burden. To overcome these difficulties, this study introduces SAMM (Simult...
Improving a regional model using reduced complexity and parameter estimation
Kelson, Victor A.; Hunt, Randall J.; Haitjema, Henk M.
2002-01-01
The availability of powerful desktop computers and graphical user interfaces for ground water flow models makes possible the construction of ever more complex models. A proposed copper-zinc sulfide mine in northern Wisconsin offers a unique case in which the same hydrologic system has been modeled using a variety of techniques covering a wide range of sophistication and complexity. Early in the permitting process, simple numerical models were used to evaluate the necessary amount of water to be pumped from the mine, reductions in streamflow, and the drawdowns in the regional aquifer. More complex models have subsequently been used in an attempt to refine the predictions. Even after so much modeling effort, questions regarding the accuracy and reliability of the predictions remain. We have performed a new analysis of the proposed mine using the two-dimensional analytic element code GFLOW coupled with the nonlinear parameter estimation code UCODE. The new model is parsimonious, containing fewer than 10 parameters, and covers a region several times larger in areal extent than any of the previous models. The model demonstrates the suitability of analytic element codes for use with parameter estimation codes. The simplified model results are similar to the more complex models; predicted mine inflows and UCODE-derived 95% confidence intervals are consistent with the previous predictions. More important, the large areal extent of the model allowed us to examine hydrological features not included in the previous models, resulting in new insights about the effects that far-field boundary conditions can have on near-field model calibration and parameterization. In this case, the addition of surface water runoff into a lake in the headwaters of a stream while holding recharge constant moved a regional ground watershed divide and resulted in some of the added water being captured by the adjoining basin. Finally, a simple analytical solution was used to clarify the GFLOW model
Complex groundwater flow systems as traveling agent models
Padilla, Pablo; Escolero, Oscar; González, Tomas; Morales-Casique, Eric; Osorio-Olvera, Luis
2014-01-01
Analyzing field data from pumping tests, we show that as with many other natural phenomena, groundwater flow exhibits complex dynamics described by 1/f power spectrum. This result is theoretically studied within an agent perspective. Using a traveling agent model, we prove that this statistical behavior emerges when the medium is complex. Some heuristic reasoning is provided to justify both spatial and dynamic complexity, as the result of the superposition of an infinite number of stochastic processes. Even more, we show that this implies that non-Kolmogorovian probability is needed for its study, and provide a set of new partial differential equations for groundwater flow. PMID:25337455
Synchronization Experiments With A Global Coupled Model of Intermediate Complexity
NASA Astrophysics Data System (ADS)
Selten, Frank; Hiemstra, Paul; Shen, Mao-Lin
2013-04-01
In the super modeling approach an ensemble of imperfect models are connected through nudging terms that nudge the solution of each model to the solution of all other models in the ensemble. The goal is to obtain a synchronized state through a proper choice of connection strengths that closely tracks the trajectory of the true system. For the super modeling approach to be successful, the connections should be dense and strong enough for synchronization to occur. In this study we analyze the behavior of an ensemble of connected global atmosphere-ocean models of intermediate complexity. All atmosphere models are connected to the same ocean model through the surface fluxes of heat, water and momentum, the ocean is integrated using weighted averaged surface fluxes. In particular we analyze the degree of synchronization between the atmosphere models and the characteristics of the ensemble mean solution. The results are interpreted using a low order atmosphere-ocean toy model.
On explicit algebraic stress models for complex turbulent flows
NASA Technical Reports Server (NTRS)
Gatski, T. B.; Speziale, C. G.
1992-01-01
Explicit algebraic stress models that are valid for three-dimensional turbulent flows in noninertial frames are systematically derived from a hierarchy of second-order closure models. This represents a generalization of the model derived by Pope who based his analysis on the Launder, Reece, and Rodi model restricted to two-dimensional turbulent flows in an inertial frame. The relationship between the new models and traditional algebraic stress models -- as well as anistropic eddy visosity models -- is theoretically established. The need for regularization is demonstrated in an effort to explain why traditional algebraic stress models have failed in complex flows. It is also shown that these explicit algebraic stress models can shed new light on what second-order closure models predict for the equilibrium states of homogeneous turbulent flows and can serve as a useful alternative in practical computations.
Prediction of Complex Aerodynamic Flows with Explicit Algebraic Stress Models
NASA Technical Reports Server (NTRS)
Abid, Ridha; Morrison, Joseph H.; Gatski, Thomas B.; Speziale, Charles G.
1996-01-01
An explicit algebraic stress equation, developed by Gatski and Speziale, is used in the framework of K-epsilon formulation to predict complex aerodynamic turbulent flows. The nonequilibrium effects are modeled through coefficients that depend nonlinearly on both rotational and irrotational strains. The proposed model was implemented in the ISAAC Navier-Stokes code. Comparisons with the experimental data are presented which clearly demonstrate that explicit algebraic stress models can predict the correct response to nonequilibrium flow.
A Complex Systems Model Approach to Quantified Mineral Resource Appraisal
Gettings, M.E.; Bultman, M.W.; Fisher, F.S.
2004-01-01
For federal and state land management agencies, mineral resource appraisal has evolved from value-based to outcome-based procedures wherein the consequences of resource development are compared with those of other management options. Complex systems modeling is proposed as a general framework in which to build models that can evaluate outcomes. Three frequently used methods of mineral resource appraisal (subjective probabilistic estimates, weights of evidence modeling, and fuzzy logic modeling) are discussed to obtain insight into methods of incorporating complexity into mineral resource appraisal models. Fuzzy logic and weights of evidence are most easily utilized in complex systems models. A fundamental product of new appraisals is the production of reusable, accessible databases and methodologies so that appraisals can easily be repeated with new or refined data. The data are representations of complex systems and must be so regarded if all of their information content is to be utilized. The proposed generalized model framework is applicable to mineral assessment and other geoscience problems. We begin with a (fuzzy) cognitive map using (+1,0,-1) values for the links and evaluate the map for various scenarios to obtain a ranking of the importance of various links. Fieldwork and modeling studies identify important links and help identify unanticipated links. Next, the links are given membership functions in accordance with the data. Finally, processes are associated with the links; ideally, the controlling physical and chemical events and equations are found for each link. After calibration and testing, this complex systems model is used for predictions under various scenarios.
Goldsby, Michael E.; Mayo, Jackson R.; Bhattacharyya, Arnab; Armstrong, Robert C.; Vanderveen, Keith
2008-09-01
The goal of this research was to examine foundational methods, both computational and theoretical, that can improve the veracity of entity-based complex system models and increase confidence in their predictions for emergent behavior. The strategy was to seek insight and guidance from simplified yet realistic models, such as cellular automata and Boolean networks, whose properties can be generalized to production entity-based simulations. We have explored the usefulness of renormalization-group methods for finding reduced models of such idealized complex systems. We have prototyped representative models that are both tractable and relevant to Sandia mission applications, and quantified the effect of computational renormalization on the predictive accuracy of these models, finding good predictivity from renormalized versions of cellular automata and Boolean networks. Furthermore, we have theoretically analyzed the robustness properties of certain Boolean networks, relevant for characterizing organic behavior, and obtained precise mathematical constraints on systems that are robust to failures. In combination, our results provide important guidance for more rigorous construction of entity-based models, which currently are often devised in an ad-hoc manner. Our results can also help in designing complex systems with the goal of predictable behavior, e.g., for cybersecurity.
SEE Rate Estimation: Model Complexity and Data Requirements
NASA Technical Reports Server (NTRS)
Ladbury, Ray
2008-01-01
Statistical Methods outlined in [Ladbury, TNS20071 can be generalized for Monte Carlo Rate Calculation Methods Two Monte Carlo Approaches: a) Rate based on vendor-supplied (or reverse-engineered) model SEE testing and statistical analysis performed to validate model; b) Rate calculated based on model fit to SEE data Statistical analysis very similar to case for CREME96. Information Theory allows simultaneous consideration of multiple models with different complexities: a) Model with lowest AIC usually has greatest predictive power; b) Model averaging using AIC weights may give better performance if several models have similar good performance; and c) Rates can be bounded for a given confidence level over multiple models, as well as over the parameter space of a model.
Turing instability in reaction-diffusion models on complex networks
NASA Astrophysics Data System (ADS)
Ide, Yusuke; Izuhara, Hirofumi; Machida, Takuya
2016-09-01
In this paper, the Turing instability in reaction-diffusion models defined on complex networks is studied. Here, we focus on three types of models which generate complex networks, i.e. the Erdős-Rényi, the Watts-Strogatz, and the threshold network models. From analysis of the Laplacian matrices of graphs generated by these models, we numerically reveal that stable and unstable regions of a homogeneous steady state on the parameter space of two diffusion coefficients completely differ, depending on the network architecture. In addition, we theoretically discuss the stable and unstable regions in the cases of regular enhanced ring lattices which include regular circles, and networks generated by the threshold network model when the number of vertices is large enough.
Multikernel linear mixed models for complex phenotype prediction.
Weissbrod, Omer; Geiger, Dan; Rosset, Saharon
2016-07-01
Linear mixed models (LMMs) and their extensions have recently become the method of choice in phenotype prediction for complex traits. However, LMM use to date has typically been limited by assuming simple genetic architectures. Here, we present multikernel linear mixed model (MKLMM), a predictive modeling framework that extends the standard LMM using multiple-kernel machine learning approaches. MKLMM can model genetic interactions and is particularly suitable for modeling complex local interactions between nearby variants. We additionally present MKLMM-Adapt, which automatically infers interaction types across multiple genomic regions. In an analysis of eight case-control data sets from the Wellcome Trust Case Control Consortium and more than a hundred mouse phenotypes, MKLMM-Adapt consistently outperforms competing methods in phenotype prediction. MKLMM is as computationally efficient as standard LMMs and does not require storage of genotypes, thus achieving state-of-the-art predictive power without compromising computational feasibility or genomic privacy. PMID:27302636
Complex solutions for the scalar field model of the Universe
NASA Astrophysics Data System (ADS)
Lyons, Glenn W.
1992-08-01
The Hartle-Hawking proposal is implemented for Hawking's scalar field model of the Universe. For this model the complex saddle-point geometries required by the semiclassical approximation to the path integral cannot simply be deformed into real Euclidean and real Lorentzian sections. Approximate saddle points are constructed which are fully complex and have contours of real Lorentzian evolution. The semiclassical wave function is found to give rise to classical spacetimes at late times and extra terms in the Hamilton-Jacobi equation do not contribute significantly to the potential.
Deterministic ripple-spreading model for complex networks.
Hu, Xiao-Bing; Wang, Ming; Leeson, Mark S; Hines, Evor L; Di Paolo, Ezequiel
2011-04-01
This paper proposes a deterministic complex network model, which is inspired by the natural ripple-spreading phenomenon. The motivations and main advantages of the model are the following: (i) The establishment of many real-world networks is a dynamic process, where it is often observed that the influence of a few local events spreads out through nodes, and then largely determines the final network topology. Obviously, this dynamic process involves many spatial and temporal factors. By simulating the natural ripple-spreading process, this paper reports a very natural way to set up a spatial and temporal model for such complex networks. (ii) Existing relevant network models are all stochastic models, i.e., with a given input, they cannot output a unique topology. Differently, the proposed ripple-spreading model can uniquely determine the final network topology, and at the same time, the stochastic feature of complex networks is captured by randomly initializing ripple-spreading related parameters. (iii) The proposed model can use an easily manageable number of ripple-spreading related parameters to precisely describe a network topology, which is more memory efficient when compared with traditional adjacency matrix or similar memory-expensive data structures. (iv) The ripple-spreading model has a very good potential for both extensions and applications. PMID:21599256
A Compact Model for the Complex Plant Circadian Clock
De Caluwé, Joëlle; Xiao, Qiying; Hermans, Christian; Verbruggen, Nathalie; Leloup, Jean-Christophe; Gonze, Didier
2016-01-01
The circadian clock is an endogenous timekeeper that allows organisms to anticipate and adapt to the daily variations of their environment. The plant clock is an intricate network of interlocked feedback loops, in which transcription factors regulate each other to generate oscillations with expression peaks at specific times of the day. Over the last decade, mathematical modeling approaches have been used to understand the inner workings of the clock in the model plant Arabidopsis thaliana. Those efforts have produced a number of models of ever increasing complexity. Here, we present an alternative model that combines a low number of equations and parameters, similar to the very earliest models, with the complex network structure found in more recent ones. This simple model describes the temporal evolution of the abundance of eight clock gene mRNA/protein and captures key features of the clock on a qualitative level, namely the entrained and free-running behaviors of the wild type clock, as well as the defects found in knockout mutants (such as altered free-running periods, lack of entrainment, or changes in the expression of other clock genes). Additionally, our model produces complex responses to various light cues, such as extreme photoperiods and non-24 h environmental cycles, and can describe the control of hypocotyl growth by the clock. Our model constitutes a useful tool to probe dynamical properties of the core clock as well as clock-dependent processes. PMID:26904049
Simple and complex models for studying muscle function in walking.
Pandy, Marcus G
2003-09-29
While simple models can be helpful in identifying basic features of muscle function, more complex models are needed to discern the functional roles of specific muscles in movement. In this paper, two very different models of walking, one simple and one complex, are used to study how muscle forces, gravitational forces and centrifugal forces (i.e. forces arising from motion of the joints) combine to produce the pattern of force exerted on the ground. Both the simple model and the complex one predict that muscles contribute significantly to the ground force pattern generated in walking; indeed, both models show that muscle action is responsible for the appearance of the two peaks in the vertical force. The simple model, an inverted double pendulum, suggests further that the first and second peaks are due to net extensor muscle moments exerted about the knee and ankle, respectively. Analyses based on a much more complex, muscle-actuated simulation of walking are in general agreement with these results; however, the more detailed model also reveals that both the hip extensor and hip abductor muscles contribute significantly to vertical motion of the centre of mass, and therefore to the appearance of the first peak in the vertical ground force, in early single-leg stance. This discrepancy in the model predictions is most probably explained by the difference in model complexity. First, movements of the upper body in the sagittal plane are not represented properly in the double-pendulum model, which may explain the anomalous result obtained for the contribution of a hip-extensor torque to the vertical ground force. Second, the double-pendulum model incorporates only three of the six major elements of walking, whereas the complex model is fully 3D and incorporates all six gait determinants. In particular, pelvic list occurs primarily in the frontal plane, so there is the potential for this mechanism to contribute significantly to the vertical ground force, especially
Surface complexation modeling of inositol hexaphosphate sorption onto gibbsite.
Ruyter-Hooley, Maika; Larsson, Anna-Carin; Johnson, Bruce B; Antzutkin, Oleg N; Angove, Michael J
2015-02-15
The sorption of Inositol hexaphosphate (IP6) onto gibbsite was investigated using a combination of adsorption experiments, (31)P solid-state MAS NMR spectroscopy, and surface complexation modeling. Adsorption experiments conducted at four temperatures showed that IP6 sorption decreased with increasing pH. At pH 6, IP6 sorption increased with increasing temperature, while at pH 10 sorption decreased as the temperature was raised. (31)P MAS NMR measurements at pH 3, 6, 9 and 11 produced spectra with broad resonance lines that could be de-convoluted with up to five resonances (+5, 0, -6, -13 and -21ppm). The chemical shifts suggest the sorption process involves a combination of both outer- and inner-sphere complexation and surface precipitation. Relative intensities of the observed resonances indicate that outer-sphere complexation is important in the sorption process at higher pH, while inner-sphere complexation and surface precipitation are dominant at lower pH. Using the adsorption and (31)P MAS NMR data, IP6 sorption to gibbsite was modeled with an extended constant capacitance model (ECCM). The adsorption reactions that best described the sorption of IP6 to gibbsite included two inner-sphere surface complexes and one outer-sphere complex: ≡AlOH + IP₆¹²⁻ + 5H⁺ ↔ ≡Al(IP₆H₄)⁷⁻ + H₂O, ≡3AlOH + IP₆¹²⁻ + 6H⁺ ↔ ≡Al₃(IP₆H₃)⁶⁻ + 3H₂O, ≡2AlOH + IP₆¹²⁻ + 4H⁺ ↔ (≡AlOH₂)₂²⁺(IP₆H₂)¹⁰⁻. The inner-sphere complex involving three surface sites may be considered to be equivalent to a surface precipitate. Thermodynamic parameters were obtained from equilibrium constants derived from surface complexation modeling. Enthalpies for the formation of inner-sphere surface complexes were endothermic, while the enthalpy for the outer-sphere complex was exothermic. The entropies for the proposed sorption reactions were large and positive suggesting that changes in solvation of species play a major role in driving
(Relatively) Simple Models of Flow in Complex Terrain
NASA Astrophysics Data System (ADS)
Taylor, Peter; Weng, Wensong; Salmon, Jim
2013-04-01
The term, "complex terrain" includes both topography and variations in surface roughness and thermal properties. The scales that are affected can differ and there are some advantages to modeling them separately. In studies of flow in complex terrain we have developed 2 D and 3 D models of atmospheric PBL boundary layer flow over roughness changes, appropriate for longer fetches than most existing models. These "internal boundary layers" are especially important for understanding and predicting wind speed variations with distance from shorelines, an important factor for wind farms around, and potentially in, the Great Lakes. The models can also form a base for studying the wakes behind woodlots and wind turbines. Some sample calculations of wind speed evolution over water and the reduced wind speeds behind an isolated woodlot, represented simply in terms of an increase in surface roughness, will be presented. Note that these models can also include thermal effects and non-neutral stratification. We can use the model to deal with 3-D roughness variations and will describe applications to both on-shore and off-shore situations around the Great Lakes. In particular we will show typical results for hub height winds and indicate the length of over-water fetch needed to get the full benefit of siting turbines over water. The linear Mixed Spectral Finite-Difference (MSFD) and non-linear (NLMSFD) models for surface boundary-layer flow over complex terrain have been extended to planetary boundary-layer flow over topography This allows for their use for larger scale regions and increased heights. The models have been applied to successfully simulate the Askervein hill experimental case and we will show examples of applications to more complex terrain, typical of some Canadian wind farms. Output from the model can be used as an alternative to MS-Micro, WAsP or other CFD calculations of topographic impacts for input to wind farm design software.
Predictive modelling of complex agronomic and biological systems.
Keurentjes, Joost J B; Molenaar, Jaap; Zwaan, Bas J
2013-09-01
Biological systems are tremendously complex in their functioning and regulation. Studying the multifaceted behaviour and describing the performance of such complexity has challenged the scientific community for years. The reduction of real-world intricacy into simple descriptive models has therefore convinced many researchers of the usefulness of introducing mathematics into biological sciences. Predictive modelling takes such an approach another step further in that it takes advantage of existing knowledge to project the performance of a system in alternating scenarios. The ever growing amounts of available data generated by assessing biological systems at increasingly higher detail provide unique opportunities for future modelling and experiment design. Here we aim to provide an overview of the progress made in modelling over time and the currently prevalent approaches for iterative modelling cycles in modern biology. We will further argue for the importance of versatility in modelling approaches, including parameter estimation, model reduction and network reconstruction. Finally, we will discuss the difficulties in overcoming the mathematical interpretation of in vivo complexity and address some of the future challenges lying ahead. PMID:23777295
Computer models of complex multiloop branched pipeline systems
NASA Astrophysics Data System (ADS)
Kudinov, I. V.; Kolesnikov, S. V.; Eremin, A. V.; Branfileva, A. N.
2013-11-01
This paper describes the principal theoretical concepts of the method used for constructing computer models of complex multiloop branched pipeline networks, and this method is based on the theory of graphs and two Kirchhoff's laws applied to electrical circuits. The models make it possible to calculate velocities, flow rates, and pressures of a fluid medium in any section of pipeline networks, when the latter are considered as single hydraulic systems. On the basis of multivariant calculations the reasons for existing problems can be identified, the least costly methods of their elimination can be proposed, and recommendations for planning the modernization of pipeline systems and construction of their new sections can be made. The results obtained can be applied to complex pipeline systems intended for various purposes (water pipelines, petroleum pipelines, etc.). The operability of the model has been verified on an example of designing a unified computer model of the heat network for centralized heat supply of the city of Samara.
Modeling the propagation of mobile malware on complex networks
NASA Astrophysics Data System (ADS)
Liu, Wanping; Liu, Chao; Yang, Zheng; Liu, Xiaoyang; Zhang, Yihao; Wei, Zuxue
2016-08-01
In this paper, the spreading behavior of malware across mobile devices is addressed. By introducing complex networks to model mobile networks, which follows the power-law degree distribution, a novel epidemic model for mobile malware propagation is proposed. The spreading threshold that guarantees the dynamics of the model is calculated. Theoretically, the asymptotic stability of the malware-free equilibrium is confirmed when the threshold is below the unity, and the global stability is further proved under some sufficient conditions. The influences of different model parameters as well as the network topology on malware propagation are also analyzed. Our theoretical studies and numerical simulations show that networks with higher heterogeneity conduce to the diffusion of malware, and complex networks with lower power-law exponents benefit malware spreading.
Petri net model for analysis of concurrently processed complex algorithms
NASA Technical Reports Server (NTRS)
Stoughton, John W.; Mielke, Roland R.
1986-01-01
This paper presents a Petri-net model suitable for analyzing the concurrent processing of computationally complex algorithms. The decomposed operations are to be processed in a multiple processor, data driven architecture. Of particular interest is the application of the model to both the description of the data/control flow of a particular algorithm, and to the general specification of the data driven architecture. A candidate architecture is also presented.
The Complex Model of Television Viewing and Educational Achievement.
ERIC Educational Resources Information Center
Razel, Micha
2001-01-01
Meta-analyzed data from six national studies of elementary through high school students to determine the relationship between amount of television viewing and educational achievement. According to a complex viewing-achievement model, for small amounts of viewing, achievement increased with viewing, but as viewing increased beyond a certain point,…
Conceptual Complexity, Teaching Style and Models of Teaching.
ERIC Educational Resources Information Center
Joyce, Bruce; Weil, Marsha
The focus of this paper is on the relative roles of personality and training in enabling teachers to carry out the kinds of complex learning models which are envisioned by curriculum reformers in the social sciences. The paper surveys some of the major research done in this area and concludes that: 1) Most teachers do not manifest the complex…
Modeling complex diffusion mechanisms in L1 2 -structured compounds
NASA Astrophysics Data System (ADS)
Zacate, M. O.; Lape, M.; Stufflebeam, M.; Evenson, W. E.
2010-04-01
We report on a procedure developed to create stochastic models of hyperfine interactions for complex diffusion mechanisms and demonstrate its application to simulate perturbed angular correlation spectra for the divacancy and 6-jump cycle diffusion mechanisms in L12-structured compounds.
Performance of Random Effects Model Estimators under Complex Sampling Designs
ERIC Educational Resources Information Center
Jia, Yue; Stokes, Lynne; Harris, Ian; Wang, Yan
2011-01-01
In this article, we consider estimation of parameters of random effects models from samples collected via complex multistage designs. Incorporation of sampling weights is one way to reduce estimation bias due to unequal probabilities of selection. Several weighting methods have been proposed in the literature for estimating the parameters of…
Catastrophe, Chaos, and Complexity Models and Psychosocial Adjustment to Disability.
ERIC Educational Resources Information Center
Parker, Randall M.; Schaller, James; Hansmann, Sandra
2003-01-01
Rehabilitation professionals may unknowingly rely on stereotypes and specious beliefs when dealing with people with disabilities, despite the formulation of theories that suggest new models of the adjustment process. Suggests that Catastrophe, Chaos, and Complexity Theories hold considerable promise in this regard. This article reviews these…
The Complexity of Developmental Predictions from Dual Process Models
ERIC Educational Resources Information Center
Stanovich, Keith E.; West, Richard F.; Toplak, Maggie E.
2011-01-01
Drawing developmental predictions from dual-process theories is more complex than is commonly realized. Overly simplified predictions drawn from such models may lead to premature rejection of the dual process approach as one of many tools for understanding cognitive development. Misleading predictions can be avoided by paying attention to several…
Fischer and Schrock Carbene Complexes: A Molecular Modeling Exercise
ERIC Educational Resources Information Center
Montgomery, Craig D.
2015-01-01
An exercise in molecular modeling that demonstrates the distinctive features of Fischer and Schrock carbene complexes is presented. Semi-empirical calculations (PM3) demonstrate the singlet ground electronic state, restricted rotation about the C-Y bond, the positive charge on the carbon atom, and hence, the electrophilic nature of the Fischer…
Surface complexation modeling of americium sorption onto volcanic tuff.
Ding, M; Kelkar, S; Meijer, A
2014-10-01
Results of a surface complexation model (SCM) for americium sorption on volcanic rocks (devitrified and zeolitic tuff) are presented. The model was developed using PHREEQC and based on laboratory data for americium sorption on quartz. Available data for sorption of americium on quartz as a function of pH in dilute groundwater can be modeled with two surface reactions involving an americium sulfate and an americium carbonate complex. It was assumed in applying the model to volcanic rocks from Yucca Mountain, that the surface properties of volcanic rocks can be represented by a quartz surface. Using groundwaters compositionally representative of Yucca Mountain, americium sorption distribution coefficient (Kd, L/Kg) values were calculated as function of pH. These Kd values are close to the experimentally determined Kd values for americium sorption on volcanic rocks, decreasing with increasing pH in the pH range from 7 to 9. The surface complexation constants, derived in this study, allow prediction of sorption of americium in a natural complex system, taking into account the inherent uncertainty associated with geochemical conditions that occur along transport pathways. PMID:24963803
A random interacting network model for complex networks
NASA Astrophysics Data System (ADS)
Goswami, Bedartha; Shekatkar, Snehal M.; Rheinwalt, Aljoscha; Ambika, G.; Kurths, Jürgen
2015-12-01
We propose a RAndom Interacting Network (RAIN) model to study the interactions between a pair of complex networks. The model involves two major steps: (i) the selection of a pair of nodes, one from each network, based on intra-network node-based characteristics, and (ii) the placement of a link between selected nodes based on the similarity of their relative importance in their respective networks. Node selection is based on a selection fitness function and node linkage is based on a linkage probability defined on the linkage scores of nodes. The model allows us to relate within-network characteristics to between-network structure. We apply the model to the interaction between the USA and Schengen airline transportation networks (ATNs). Our results indicate that two mechanisms: degree-based preferential node selection and degree-assortative link placement are necessary to replicate the observed inter-network degree distributions as well as the observed inter-network assortativity. The RAIN model offers the possibility to test multiple hypotheses regarding the mechanisms underlying network interactions. It can also incorporate complex interaction topologies. Furthermore, the framework of the RAIN model is general and can be potentially adapted to various real-world complex systems.
A random interacting network model for complex networks
Goswami, Bedartha; Shekatkar, Snehal M.; Rheinwalt, Aljoscha; Ambika, G.; Kurths, Jürgen
2015-01-01
We propose a RAndom Interacting Network (RAIN) model to study the interactions between a pair of complex networks. The model involves two major steps: (i) the selection of a pair of nodes, one from each network, based on intra-network node-based characteristics, and (ii) the placement of a link between selected nodes based on the similarity of their relative importance in their respective networks. Node selection is based on a selection fitness function and node linkage is based on a linkage probability defined on the linkage scores of nodes. The model allows us to relate within-network characteristics to between-network structure. We apply the model to the interaction between the USA and Schengen airline transportation networks (ATNs). Our results indicate that two mechanisms: degree-based preferential node selection and degree-assortative link placement are necessary to replicate the observed inter-network degree distributions as well as the observed inter-network assortativity. The RAIN model offers the possibility to test multiple hypotheses regarding the mechanisms underlying network interactions. It can also incorporate complex interaction topologies. Furthermore, the framework of the RAIN model is general and can be potentially adapted to various real-world complex systems. PMID:26657032
A random interacting network model for complex networks.
Goswami, Bedartha; Shekatkar, Snehal M; Rheinwalt, Aljoscha; Ambika, G; Kurths, Jürgen
2015-01-01
We propose a RAndom Interacting Network (RAIN) model to study the interactions between a pair of complex networks. The model involves two major steps: (i) the selection of a pair of nodes, one from each network, based on intra-network node-based characteristics, and (ii) the placement of a link between selected nodes based on the similarity of their relative importance in their respective networks. Node selection is based on a selection fitness function and node linkage is based on a linkage probability defined on the linkage scores of nodes. The model allows us to relate within-network characteristics to between-network structure. We apply the model to the interaction between the USA and Schengen airline transportation networks (ATNs). Our results indicate that two mechanisms: degree-based preferential node selection and degree-assortative link placement are necessary to replicate the observed inter-network degree distributions as well as the observed inter-network assortativity. The RAIN model offers the possibility to test multiple hypotheses regarding the mechanisms underlying network interactions. It can also incorporate complex interaction topologies. Furthermore, the framework of the RAIN model is general and can be potentially adapted to various real-world complex systems. PMID:26657032
On Using Meta-Modeling and Multi-Modeling to Address Complex Problems
ERIC Educational Resources Information Center
Abu Jbara, Ahmed
2013-01-01
Models, created using different modeling techniques, usually serve different purposes and provide unique insights. While each modeling technique might be capable of answering specific questions, complex problems require multiple models interoperating to complement/supplement each other; we call this Multi-Modeling. To address the syntactic and…
Probabilistic Analysis Techniques Applied to Complex Spacecraft Power System Modeling
NASA Technical Reports Server (NTRS)
Hojnicki, Jeffrey S.; Rusick, Jeffrey J.
2005-01-01
Electric power system performance predictions are critical to spacecraft, such as the International Space Station (ISS), to ensure that sufficient power is available to support all the spacecraft s power needs. In the case of the ISS power system, analyses to date have been deterministic, meaning that each analysis produces a single-valued result for power capability because of the complexity and large size of the model. As a result, the deterministic ISS analyses did not account for the sensitivity of the power capability to uncertainties in model input variables. Over the last 10 years, the NASA Glenn Research Center has developed advanced, computationally fast, probabilistic analysis techniques and successfully applied them to large (thousands of nodes) complex structural analysis models. These same techniques were recently applied to large, complex ISS power system models. This new application enables probabilistic power analyses that account for input uncertainties and produce results that include variations caused by these uncertainties. Specifically, N&R Engineering, under contract to NASA, integrated these advanced probabilistic techniques with Glenn s internationally recognized ISS power system model, System Power Analysis for Capability Evaluation (SPACE).
Boolean modeling of collective effects in complex networks.
Norrell, Johannes; Socolar, Joshua E S
2009-06-01
Complex systems are often modeled as Boolean networks in attempts to capture their logical structure and reveal its dynamical consequences. Approximating the dynamics of continuous variables by discrete values and Boolean logic gates may, however, introduce dynamical possibilities that are not accessible to the original system. We show that large random networks of variables coupled through continuous transfer functions often fail to exhibit the complex dynamics of corresponding Boolean models in the disordered (chaotic) regime, even when each individual function appears to be a good candidate for Boolean idealization. A suitably modified Boolean theory explains the behavior of systems in which information does not propagate faithfully down certain chains of nodes. Model networks incorporating calculated or directly measured transfer functions reported in the literature on transcriptional regulation of genes are described by the modified theory. PMID:19658525
Entropy, complexity, and Markov diagrams for random walk cancer models
NASA Astrophysics Data System (ADS)
Newton, Paul K.; Mason, Jeremy; Hurt, Brian; Bethel, Kelly; Bazhenova, Lyudmila; Nieva, Jorge; Kuhn, Peter
2014-12-01
The notion of entropy is used to compare the complexity associated with 12 common cancers based on metastatic tumor distribution autopsy data. We characterize power-law distributions, entropy, and Kullback-Liebler divergence associated with each primary cancer as compared with data for all cancer types aggregated. We then correlate entropy values with other measures of complexity associated with Markov chain dynamical systems models of progression. The Markov transition matrix associated with each cancer is associated with a directed graph model where nodes are anatomical locations where a metastatic tumor could develop, and edge weightings are transition probabilities of progression from site to site. The steady-state distribution corresponds to the autopsy data distribution. Entropy correlates well with the overall complexity of the reduced directed graph structure for each cancer and with a measure of systemic interconnectedness of the graph, called graph conductance. The models suggest that grouping cancers according to their entropy values, with skin, breast, kidney, and lung cancers being prototypical high entropy cancers, stomach, uterine, pancreatic and ovarian being mid-level entropy cancers, and colorectal, cervical, bladder, and prostate cancers being prototypical low entropy cancers, provides a potentially useful framework for viewing metastatic cancer in terms of predictability, complexity, and metastatic potential.
Entropy, complexity, and Markov diagrams for random walk cancer models
Newton, Paul K.; Mason, Jeremy; Hurt, Brian; Bethel, Kelly; Bazhenova, Lyudmila; Nieva, Jorge; Kuhn, Peter
2014-01-01
The notion of entropy is used to compare the complexity associated with 12 common cancers based on metastatic tumor distribution autopsy data. We characterize power-law distributions, entropy, and Kullback-Liebler divergence associated with each primary cancer as compared with data for all cancer types aggregated. We then correlate entropy values with other measures of complexity associated with Markov chain dynamical systems models of progression. The Markov transition matrix associated with each cancer is associated with a directed graph model where nodes are anatomical locations where a metastatic tumor could develop, and edge weightings are transition probabilities of progression from site to site. The steady-state distribution corresponds to the autopsy data distribution. Entropy correlates well with the overall complexity of the reduced directed graph structure for each cancer and with a measure of systemic interconnectedness of the graph, called graph conductance. The models suggest that grouping cancers according to their entropy values, with skin, breast, kidney, and lung cancers being prototypical high entropy cancers, stomach, uterine, pancreatic and ovarian being mid-level entropy cancers, and colorectal, cervical, bladder, and prostate cancers being prototypical low entropy cancers, provides a potentially useful framework for viewing metastatic cancer in terms of predictability, complexity, and metastatic potential. PMID:25523357
Modeling the respiratory chain complexes with biothermokinetic equations - the case of complex I.
Heiske, Margit; Nazaret, Christine; Mazat, Jean-Pierre
2014-10-01
The mitochondrial respiratory chain plays a crucial role in energy metabolism and its dysfunction is implicated in a wide range of human diseases. In order to understand the global expression of local mutations in the rate of oxygen consumption or in the production of adenosine triphosphate (ATP) it is useful to have a mathematical model in which the changes in a given respiratory complex are properly modeled. Our aim in this paper is to provide thermodynamics respecting and structurally simple equations to represent the kinetics of each isolated complexes which can, assembled in a dynamical system, also simulate the behavior of the respiratory chain, as a whole, under a large set of different physiological and pathological conditions. On the example of the reduced nicotinamide adenine dinucleotide (NADH)-ubiquinol-oxidoreductase (complex I) we analyze the suitability of different types of rate equations. Based on our kinetic experiments we show that very simple rate laws, as those often used in many respiratory chain models, fail to describe the kinetic behavior when applied to a wide concentration range. This led us to adapt rate equations containing the essential parameters of enzyme kinetic, maximal velocities and Henri-Michaelis-Menten like-constants (KM and KI) to satisfactorily simulate these data. PMID:25064016
Complex 2D matrix model and geometrical map on the complex-Nc plane
NASA Astrophysics Data System (ADS)
Nawa, Kanabu; Ozaki, Sho; Nagahiro, Hideko; Jido, Daisuke; Hosaka, Atsushi
2013-08-01
We study the parameter dependence of the internal structure of resonance states by formulating a complex two-dimensional (2D) matrix model, where the two dimensions represent two levels of resonances. We calculate a critical value of the parameter at which a "nature transition" with character exchange occurs between two resonance states, from the viewpoint of geometry on complex-parameter space. Such a critical value is useful for identifying the internal structure of resonance states with variation of the parameter in the system. We apply the model to analyze the internal structure of hadrons with variation of the color number N_c from infty to a realistic value 3. By regarding 1/N_c as the variable parameter in our model, we calculate a critical color number of the nature transition between hadronic states in terms of a quark-antiquark pair and a mesonic molecule as exotics from the geometry on the complex-N_c plane. For large-N_c effective theory, we employ the chiral Lagrangian induced by holographic QCD with a D4/D8/overline {D8} multi-D brane system in type IIA superstring theory.
Complex Behavior in Simple Models of Biological Coevolution
NASA Astrophysics Data System (ADS)
Rikvold, Per Arne
We explore the complex dynamical behavior of simple predator-prey models of biological coevolution that account for interspecific and intraspecific competition for resources, as well as adaptive foraging behavior. In long kinetic Monte Carlo simulations of these models we find quite robust 1/f-like noise in species diversity and population sizes, as well as power-law distributions for the lifetimes of individual species and the durations of quiet periods of relative evolutionary stasis. In one model, based on the Holling Type II functional response, adaptive foraging produces a metastable low-diversity phase and a stable high-diversity phase.
Modeling and Algorithmic Approaches to Constitutively-Complex, Microstructured Fluids
Miller, Gregory H.; Forest, Gregory
2011-12-22
We present a new multiscale model for complex uids based on three scales: microscopic, kinetic, and continuum. We choose the microscopic level as Kramers' bead-rod model for polymers, which we describe as a system of stochastic di erential equations with an implicit constraint formulation. The associated Fokker-Planck equation is then derived, and adiabatic elimination removes the fast momentum coordinates. Approached in this way, the kinetic level reduces to a dispersive drift equation. The continuum level is modeled with a nite volume Godunov-projection algorithm. We demonstrate computation of viscoelastic stress divergence using this multiscale approach.
Modeling of Carbohydrate Binding Modules Complexed to Cellulose
Nimlos, M. R.; Beckham, G. T.; Bu, L.; Himmel, M. E.; Crowley, M. F.; Bomble, Y. J.
2012-01-01
Modeling results are presented for the interaction of two carbohydrate binding modules (CBMs) with cellulose. The family 1 CBM from Trichoderma reesei's Cel7A cellulase was modeled using molecular dynamics to confirm that this protein selectively binds to the hydrophobic (100) surface of cellulose fibrils and to determine the energetics and mechanisms for locating this surface. Modeling was also conducted of binding of the family 4 CBM from the CbhA complex from Clostridium thermocellum. There is a cleft in this protein, which may accommodate a cellulose chain that is detached from crystalline cellulose. This possibility is explored using molecular dynamics.
Hill, Renee J.; Chopra, Pradeep; Richardi, Toni
2012-01-01
Abstract Explaining the etiology of Complex Regional Pain Syndrome (CRPS) from the psychogenic model is exceedingly unsophisticated, because neurocognitive deficits, neuroanatomical abnormalities, and distortions in cognitive mapping are features of CRPS pathology. More importantly, many people who have developed CRPS have no history of mental illness. The psychogenic model offers comfort to physicians and mental health practitioners (MHPs) who have difficulty understanding pain maintained by newly uncovered neuro inflammatory processes. With increased education about CRPS through a biopsychosocial perspective, both physicians and MHPs can better diagnose, treat, and manage CRPS symptomatology. PMID:24223338
Bridging Mechanistic and Phenomenological Models of Complex Biological Systems
Transtrum, Mark K.; Qiu, Peng
2016-01-01
The inherent complexity of biological systems gives rise to complicated mechanistic models with a large number of parameters. On the other hand, the collective behavior of these systems can often be characterized by a relatively small number of phenomenological parameters. We use the Manifold Boundary Approximation Method (MBAM) as a tool for deriving simple phenomenological models from complicated mechanistic models. The resulting models are not black boxes, but remain expressed in terms of the microscopic parameters. In this way, we explicitly connect the macroscopic and microscopic descriptions, characterize the equivalence class of distinct systems exhibiting the same range of collective behavior, and identify the combinations of components that function as tunable control knobs for the behavior. We demonstrate the procedure for adaptation behavior exhibited by the EGFR pathway. From a 48 parameter mechanistic model, the system can be effectively described by a single adaptation parameter τ characterizing the ratio of time scales for the initial response and recovery time of the system which can in turn be expressed as a combination of microscopic reaction rates, Michaelis-Menten constants, and biochemical concentrations. The situation is not unlike modeling in physics in which microscopically complex processes can often be renormalized into simple phenomenological models with only a few effective parameters. The proposed method additionally provides a mechanistic explanation for non-universal features of the behavior. PMID:27187545
Bridging Mechanistic and Phenomenological Models of Complex Biological Systems.
Transtrum, Mark K; Qiu, Peng
2016-05-01
The inherent complexity of biological systems gives rise to complicated mechanistic models with a large number of parameters. On the other hand, the collective behavior of these systems can often be characterized by a relatively small number of phenomenological parameters. We use the Manifold Boundary Approximation Method (MBAM) as a tool for deriving simple phenomenological models from complicated mechanistic models. The resulting models are not black boxes, but remain expressed in terms of the microscopic parameters. In this way, we explicitly connect the macroscopic and microscopic descriptions, characterize the equivalence class of distinct systems exhibiting the same range of collective behavior, and identify the combinations of components that function as tunable control knobs for the behavior. We demonstrate the procedure for adaptation behavior exhibited by the EGFR pathway. From a 48 parameter mechanistic model, the system can be effectively described by a single adaptation parameter τ characterizing the ratio of time scales for the initial response and recovery time of the system which can in turn be expressed as a combination of microscopic reaction rates, Michaelis-Menten constants, and biochemical concentrations. The situation is not unlike modeling in physics in which microscopically complex processes can often be renormalized into simple phenomenological models with only a few effective parameters. The proposed method additionally provides a mechanistic explanation for non-universal features of the behavior. PMID:27187545
Complexity and robustness in hypernetwork models of metabolism.
Pearcy, Nicole; Chuzhanova, Nadia; Crofts, Jonathan J
2016-10-01
Metabolic reaction data is commonly modelled using a complex network approach, whereby nodes represent the chemical species present within the organism of interest, and connections are formed between those nodes participating in the same chemical reaction. Unfortunately, such an approach provides an inadequate description of the metabolic process in general, as a typical chemical reaction will involve more than two nodes, thus risking oversimplification of the system of interest in a potentially significant way. In this paper, we employ a complex hypernetwork formalism to investigate the robustness of bacterial metabolic hypernetworks by extending the concept of a percolation process to hypernetworks. Importantly, this provides a novel method for determining the robustness of these systems and thus for quantifying their resilience to random attacks/errors. Moreover, we performed a site percolation analysis on a large cohort of bacterial metabolic networks and found that hypernetworks that evolved in more variable environments displayed increased levels of robustness and topological complexity. PMID:27354314
Modeling of ion complexation and extraction using substructural molecular fragments
Solov'ev; Varnek; Wipff
2000-05-01
A substructural molecular fragment (SMF) method has been developed to model the relationships between the structure of organic molecules and their thermodynamic parameters of complexation or extraction. The method is based on the splitting of a molecule into fragments, and on calculations of their contributions to a given property. It uses two types of fragments: atom/bond sequences and "augmented atoms" (atoms with their nearest neighbors). The SMF approach is tested on physical properties of C2-C9 alkanes (boiling point, molar volume, molar refraction, heat of vaporization, surface tension, melting point, critical temperature, and critical pressures) and on octanol/water partition coefficients. Then, it is applied to the assessment of (i) complexation stability constants of alkali cations with crown ethers and phosphoryl-containing podands, and of beta-cyclodextrins with mono- and 1,4-disubstituted benzenes, and (ii) solvent extraction constants for the complexes of uranyl cation by phosphoryl-containing ligands. PMID:10850791
Mathematical modelling of complex contagion on clustered networks
NASA Astrophysics Data System (ADS)
O'sullivan, David J.; O'Keeffe, Gary; Fennell, Peter; Gleeson, James
2015-09-01
The spreading of behavior, such as the adoption of a new innovation, is influenced bythe structure of social networks that interconnect the population. In the experiments of Centola (Science, 2010), adoption of new behavior was shown to spread further and faster across clustered-lattice networks than across corresponding random networks. This implies that the “complex contagion” effects of social reinforcement are important in such diffusion, in contrast to “simple” contagion models of disease-spread which predict that epidemics would grow more efficiently on random networks than on clustered networks. To accurately model complex contagion on clustered networks remains a challenge because the usual assumptions (e.g. of mean-field theory) regarding tree-like networks are invalidated by the presence of triangles in the network; the triangles are, however, crucial to the social reinforcement mechanism, which posits an increased probability of a person adopting behavior that has been adopted by two or more neighbors. In this paper we modify the analytical approach that was introduced by Hebert-Dufresne et al. (Phys. Rev. E, 2010), to study disease-spread on clustered networks. We show how the approximation method can be adapted to a complex contagion model, and confirm the accuracy of the method with numerical simulations. The analytical results of the model enable us to quantify the level of social reinforcement that is required to observe—as in Centola’s experiments—faster diffusion on clustered topologies than on random networks.
Parameter uncertainty and interaction in complex environmental models
NASA Astrophysics Data System (ADS)
Spear, Robert C.; Grieb, Thomas M.; Shang, Nong
1994-11-01
Recently developed models for the estimation of risks arising from the release of toxic chemicals from hazardous waste sites are inherently complex both structurally and parametrically. To better understand the impact of uncertainty and interaction in the high-dimensional parameter spaces of these models, the set of procedures termed regional sensitivity analysis has been extended and applied to the groundwater pathway of the MMSOILS model. The extension consists of a tree-structured density estimation technique which allows the characterization of complex interaction in that portion of the parameter space which gives rise to successful simulation. Results show that the parameter space can be partitioned into small, densely populated regions and relatively large, sparsely populated regions. From the high-density regions one can identify the important or controlling parameters as well as the interaction between parameters in different local areas of the space. This new tool can provide guidance in the analysis and interpretation of site-specific application of these complex models.
An Adaptive Complex Network Model for Brain Functional Networks
Gomez Portillo, Ignacio J.; Gleiser, Pablo M.
2009-01-01
Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence) of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution. PMID:19738902
a Model Study of Complex Behavior in the Belousov - Reaction.
NASA Astrophysics Data System (ADS)
Lindberg, David Mark
1988-12-01
We have studied the complex oscillatory behavior in a model of the Belousov-Zhabotinskii (BZ) reaction in a continuously-fed stirred tank reactor (CSTR). The model consisted of a set of nonlinear ordinary differential equations derived from a reduced mechanism of the chemical system. These equations were integrated numerically on a computer, which yielded the concentrations of the constituent chemicals as functions of time. In addition, solutions were tracked as functions of a single parameter, the stability of the solutions was determined, and bifurcations of the solutions were located and studied. The intent of this study was to use this BZ model to explore further a region of complex oscillatory behavior found in experimental investigations, the most thorough of which revealed an alternating periodic-chaotic (P-C) sequence of states. A P-C sequence was discovered in the model which showed the same qualitative features as the experimental sequence. In order to better understand the P-C sequence, a detailed study was conducted in the vicinity of the P-C sequence, with two experimentally accessible parameters as control variables. This study mapped out the bifurcation sets, and included examination of the dynamics of the stable periodic, unstable periodic, and chaotic oscillatory motion. Observations made from the model results revealed a rough symmetry which suggests a new way of looking at the P-C sequence. Other nonlinear phenomena uncovered in the model were boundary and interior crises, several codimension-two bifurcations, and similarities in the shapes of areas of stability for periodic orbits in two-parameter space. Each earlier model study of this complex region involved only a limited one-parameter scan and had limited success in producing agreement with experiments. In contrast, for those regions of complex behavior that have been studied experimentally, the observations agree qualitatively with our model results. Several new predictions of the model
NASA Astrophysics Data System (ADS)
Jing, Benxin; Lan, Nan; Zhu, Y. Elaine
2013-03-01
An explosion in the research activities using ionic liquids (ILs) as new ``green'' chemicals in several chemical and biomedical processes has resulted in the urgent need to understand their impact in term of their transport and toxicity towards aquatic organisms. Though a few experimental toxicology studies have reported that some ionic liquids are toxic with increased hydrophobicity of ILs while others are not, our understanding of the molecular level mechanism of IL toxicity remains poorly understood. In this talk, we will discuss our recent study of the interaction of ionic liquids with model cell membranes. We have found that the ILs could induce morphological change of lipid bilayers when a critical concentration is exceeded, leading to the swelling and tube-like formation of lipid bilayers. The critical concentration shows a strong dependence on the length of hydrocarbon tails and hydrophobic counterions. By SAXS, Langmuir-Blodgett (LB) and fluorescence microscopic measurement, we have confirmed that tube-like lipid complexes result from the insertion of ILs with long hydrocarbon chains to minimize the hydrophobic interaction with aqueous media. This finding could give insight to the modification and adoption of ILs for the engineering of micro-organisms.
Yue, Tongtao; Sun, Mingbin; Zhang, Shuai; Ren, Hao; Ge, Baosheng; Huang, Fang
2016-06-29
After the synthesis of transmembrane peptides/proteins (TMPs), their insertion into a lipid bilayer is a fundamental biophysical process. Moreover, correct orientations of TMPs in membranes determine the normal functions they play in relevant cellular activities. In this study, we have established a method to determine the orientation of TMPs in membranes. This method is based on the use of TAMRA, a fluorescent molecule with high extinction coefficient and fluorescence quantum yield, to act as a fluorescent probe and tryptophan as a quencher. Fluorescence quenching indicates that the model peptide displays membrane orientation with the N terminus outside and the C terminus inside dominantly. To elucidate the underlying mechanism, we performed molecular dynamics simulations. Our simulations suggest that both membrane insertion and the orientation of TMPs are determined by complex competition and cooperation between hydrophobic and electrostatic interactions. After initial membrane anchorage via electrostatic interactions of the charged residues with the lipid headgroups, further insertion is hindered by unfavorable interactions between the polar residues and lipid tails, which result in an energy barrier. Nevertheless, such a finite energy barrier is reduced by hydrophobic interactions between the non-polar residues and lipid tails. Moreover, a transient terminal flipping was captured to facilitate the membrane insertion. Once the inserted terminus reaches the opposite lipid headgroups, the hydrophobic interactions cooperate with the electrostatic interactions to complete the membrane insertion process. PMID:27302083
Cx-02 Program, workshop on modeling complex systems
Mossotti, Victor G.; Barragan, Jo Ann; Westergard, Todd D.
2003-01-01
This publication contains the abstracts and program for the workshop on complex systems that was held on November 19-21, 2002, in Reno, Nevada. Complex systems are ubiquitous within the realm of the earth sciences. Geological systems consist of a multiplicity of linked components with nested feedback loops; the dynamics of these systems are non-linear, iterative, multi-scale, and operate far from equilibrium. That notwithstanding, It appears that, with the exception of papers on seismic studies, geology and geophysics work has been disproportionally underrepresented at regional and national meetings on complex systems relative to papers in the life sciences. This is somewhat puzzling because geologists and geophysicists are, in many ways, preadapted to thinking of complex system mechanisms. Geologists and geophysicists think about processes involving large volumes of rock below the sunlit surface of Earth, the accumulated consequence of processes extending hundreds of millions of years in the past. Not only do geologists think in the abstract by virtue of the vast time spans, most of the evidence is out-of-sight. A primary goal of this workshop is to begin to bridge the gap between the Earth sciences and life sciences through demonstration of the universality of complex systems science, both philosophically and in model structures.
Mechanistic modeling confronts the complexity of molecular cell biology.
Phair, Robert D
2014-11-01
Mechanistic modeling has the potential to transform how cell biologists contend with the inescapable complexity of modern biology. I am a physiologist-electrical engineer-systems biologist who has been working at the level of cell biology for the past 24 years. This perspective aims 1) to convey why we build models, 2) to enumerate the major approaches to modeling and their philosophical differences, 3) to address some recurrent concerns raised by experimentalists, and then 4) to imagine a future in which teams of experimentalists and modelers build-and subject to exhaustive experimental tests-models covering the entire spectrum from molecular cell biology to human pathophysiology. There is, in my view, no technical obstacle to this future, but it will require some plasticity in the biological research mind-set. PMID:25368428
Paradigms of Complexity in Modelling of Fluid and Kinetic Processes
NASA Astrophysics Data System (ADS)
Diamond, P. H.
2006-10-01
The need to discuss and compare a wide variety of models of fluid and kinetic processes is motivated by the astonishing wide variety of complex physical phenomena which occur in plasmas in nature. Such phenomena include, but are not limited to: turbulence, turbulent transport and mixing, reconnection and structure formation. In this talk, I will review how various fluid and kinetic models come to grips with the essential physics of these phenomena. For example, I will discuss how the idea of a turbulent cascade and the concept of an ``eddy'' are realized quite differently in fluid and Vlasov models. Attention will be placed primarily on physical processes, the physics content of various models, and the consequences of choices in model construction, rather than on the intrinsic mathematical structure of the theories. Examples will be chosen from fusion, laboratory, space and astrophysical plasmas.
Lateral organization of complex lipid mixtures from multiscale modeling
NASA Astrophysics Data System (ADS)
Tumaneng, Paul W.; Pandit, Sagar A.; Zhao, Guijun; Scott, H. L.
2010-02-01
The organizational properties of complex lipid mixtures can give rise to functionally important structures in cell membranes. In model membranes, ternary lipid-cholesterol (CHOL) mixtures are often used as representative systems to investigate the formation and stabilization of localized structural domains ("rafts"). In this work, we describe a self-consistent mean-field model that builds on molecular dynamics simulations to incorporate multiple lipid components and to investigate the lateral organization of such mixtures. The model predictions reveal regions of bimodal order on ternary plots that are in good agreement with experiment. Specifically, we have applied the model to ternary mixtures composed of dioleoylphosphatidylcholine:18:0 sphingomyelin:CHOL. This work provides insight into the specific intermolecular interactions that drive the formation of localized domains in these mixtures. The model makes use of molecular dynamics simulations to extract interaction parameters and to provide chain configuration order parameter libraries.
RHIC injector complex online model status and plans
Schoefer,V.; Ahrens, L.; Brown, K.; Morris, J.; Nemesure, S.
2009-05-04
An online modeling system is being developed for the RHIC injector complex, which consists of the Booster, the AGS and the transfer lines connecting the Booster to the AGS and the AGS to RHIC. Historically the injectors have been operated using static values from design specifications or offline model runs, but tighter beam optics constraints required by polarized proton operations (e.g, accelerating with near-integer tunes) have necessitated a more dynamic system. An online model server for the AGS has been implemented using MAD-X [1] as the model engine, with plans to extend the system to the Booster and the injector transfer lines and to add the option of calculating optics using the Polymorphic Tracking Code (PTC [2]) as the model engine.
Structuring temporal sequences: comparison of models and factors of complexity.
Essens, P
1995-05-01
Two stages for structuring tone sequences have been distinguished by Povel and Essens (1985). In the first, a mental clock segments a sequence into equal time units (clock model); in the second, intervals are specified in terms of subdivisions of these units. The present findings support the clock model in that it predicts human performance better than three other algorithmic models. Two further experiments in which clock and subdivision characteristics were varied did not support the hypothesized effect of the nature of the subdivisions on complexity. A model focusing on the variations in the beat-anchored envelopes of the tone clusters was proposed. Errors in reproduction suggest a dual-code representation comprising temporal and figural characteristics. The temporal part of the representation is based on the clock model but specifies, in addition, the metric of the level below the clock. The beat-tone-cluster envelope concept was proposed to specify the figural part. PMID:7596749
Heo, Lim; Lee, Hasup; Seok, Chaok
2016-01-01
Protein-protein docking methods have been widely used to gain an atomic-level understanding of protein interactions. However, docking methods that employ low-resolution energy functions are popular because of computational efficiency. Low-resolution docking tends to generate protein complex structures that are not fully optimized. GalaxyRefineComplex takes such low-resolution docking structures and refines them to improve model accuracy in terms of both interface contact and inter-protein orientation. This refinement method allows flexibility at the protein interface and in the overall docking structure to capture conformational changes that occur upon binding. Symmetric refinement is also provided for symmetric homo-complexes. This method was validated by refining models produced by available docking programs, including ZDOCK and M-ZDOCK, and was successfully applied to CAPRI targets in a blind fashion. An example of using the refinement method with an existing docking method for ligand binding mode prediction of a drug target is also presented. A web server that implements the method is freely available at http://galaxy.seoklab.org/refinecomplex. PMID:27535582
Heo, Lim; Lee, Hasup; Seok, Chaok
2016-01-01
Protein-protein docking methods have been widely used to gain an atomic-level understanding of protein interactions. However, docking methods that employ low-resolution energy functions are popular because of computational efficiency. Low-resolution docking tends to generate protein complex structures that are not fully optimized. GalaxyRefineComplex takes such low-resolution docking structures and refines them to improve model accuracy in terms of both interface contact and inter-protein orientation. This refinement method allows flexibility at the protein interface and in the overall docking structure to capture conformational changes that occur upon binding. Symmetric refinement is also provided for symmetric homo-complexes. This method was validated by refining models produced by available docking programs, including ZDOCK and M-ZDOCK, and was successfully applied to CAPRI targets in a blind fashion. An example of using the refinement method with an existing docking method for ligand binding mode prediction of a drug target is also presented. A web server that implements the method is freely available at http://galaxy.seoklab.org/refinecomplex. PMID:27535582
Reduced Complexity Modeling (RCM): toward more use of less
NASA Astrophysics Data System (ADS)
Paola, Chris; Voller, Vaughan
2014-05-01
Although not exact, there is a general correspondence between reductionism and detailed, high-fidelity models, while 'synthesism' is often associated with reduced-complexity modeling. There is no question that high-fidelity reduction- based computational models are extremely useful in simulating the behaviour of complex natural systems. In skilled hands they are also a source of insight and understanding. We focus here on the case for the other side (reduced-complexity models), not because we think they are 'better' but because their value is more subtle, and their natural constituency less clear. What kinds of problems and systems lend themselves to the reduced-complexity approach? RCM is predicated on the idea that the mechanism of the system or phenomenon in question is, for whatever reason, insensitive to the full details of the underlying physics. There are multiple ways in which this can happen. B.T. Werner argued for the importance of process hierarchies in which processes at larger scales depend on only a small subset of everything going on at smaller scales. Clear scale breaks would seem like a way to test systems for this property but to our knowledge has not been used in this way. We argue that scale-independent physics, as for example exhibited by natural fractals, is another. We also note that the same basic criterion - independence of the process in question from details of the underlying physics - underpins 'unreasonably effective' laboratory experiments. There is thus a link between suitability for experimentation at reduced scale and suitability for RCM. Examples from RCM approaches to erosional landscapes, braided rivers, and deltas illustrate these ideas, and suggest that they are insufficient. There is something of a 'wild west' nature to RCM that puts some researchers off by suggesting a departure from traditional methods that have served science well for centuries. We offer two thoughts: first, that in the end the measure of a model is its
An Ontology for Modeling Complex Inter-relational Organizations
NASA Astrophysics Data System (ADS)
Wautelet, Yves; Neysen, Nicolas; Kolp, Manuel
This paper presents an ontology for organizational modeling through multiple complementary aspects. The primary goal of the ontology is to dispose of an adequate set of related concepts for studying complex organizations involved in a lot of relationships at the same time. In this paper, we define complex organizations as networked organizations involved in a market eco-system that are playing several roles simultaneously. In such a context, traditional approaches focus on the macro analytic level of transactions; this is supplemented here with a micro analytic study of the actors' rationale. At first, the paper overviews enterprise ontologies literature to position our proposal and exposes its contributions and limitations. The ontology is then brought to an advanced level of formalization: a meta-model in the form of a UML class diagram allows to overview the ontology concepts and their relationships which are formally defined. Finally, the paper presents the case study on which the ontology has been validated.
Engineering complex topological memories from simple Abelian models
NASA Astrophysics Data System (ADS)
Wootton, James R.; Lahtinen, Ville; Doucot, Benoit; Pachos, Jiannis K.
2011-09-01
In three spatial dimensions, particles are limited to either bosonic or fermionic statistics. Two-dimensional systems, on the other hand, can support anyonic quasiparticles exhibiting richer statistical behaviors. An exciting proposal for quantum computation is to employ anyonic statistics to manipulate information. Since such statistical evolutions depend only on topological characteristics, the resulting computation is intrinsically resilient to errors. The so-called non-Abelian anyons are most promising for quantum computation, but their physical realization may prove to be complex. Abelian anyons, however, are easier to understand theoretically and realize experimentally. Here we show that complex topological memories inspired by non-Abelian anyons can be engineered in Abelian models. We explicitly demonstrate the control procedures for the encoding and manipulation of quantum information in specific lattice models that can be implemented in the laboratory. This bridges the gap between requirements for anyonic quantum computation and the potential of state-of-the-art technology.